An FPGA Implementation to Detect Selective Cationic Antibacterial Peptides

PubMed Central

Polanco González, Carlos; Nuño Maganda, Marco Aurelio; Arias-Estrada, Miguel; del Rio, Gabriel

2011-01-01

Exhaustive prediction of physicochemical properties of peptide sequences is used in different areas of biological research. One example is the identification of selective cationic antibacterial peptides (SCAPs), which may be used in the treatment of different diseases. Due to the discrete nature of peptide sequences, the physicochemical properties calculation is considered a high-performance computing problem. A competitive solution for this class of problems is to embed algorithms into dedicated hardware. In the present work we present the adaptation, design and implementation of an algorithm for SCAPs prediction into a Field Programmable Gate Array (FPGA) platform. Four physicochemical properties codes useful in the identification of peptide sequences with potential selective antibacterial activity were implemented into an FPGA board. The speed-up gained in a single-copy implementation was up to 108 times compared with a single Intel processor cycle for cycle. The inherent scalability of our design allows for replication of this code into multiple FPGA cards and consequently improvements in speed are possible. Our results show the first embedded SCAPs prediction solution described and constitutes the grounds to efficiently perform the exhaustive analysis of the sequence-physicochemical properties relationship of peptides. PMID:21738652

Rapid experimental measurements of physicochemical properties to inform models and testing.

PubMed

Nicolas, Chantel I; Mansouri, Kamel; Phillips, Katherine A; Grulke, Christopher M; Richard, Ann M; Williams, Antony J; Rabinowitz, James; Isaacs, Kristin K; Yau, Alice; Wambaugh, John F

2018-05-02

The structures and physicochemical properties of chemicals are important for determining their potential toxicological effects, toxicokinetics, and route(s) of exposure. These data are needed to prioritize the risk for thousands of environmental chemicals, but experimental values are often lacking. In an attempt to efficiently fill data gaps in physicochemical property information, we generated new data for 200 structurally diverse compounds, which were rigorously selected from the USEPA ToxCast chemical library, and whose structures are available within the Distributed Structure-Searchable Toxicity Database (DSSTox). This pilot study evaluated rapid experimental methods to determine five physicochemical properties, including the log of the octanol:water partition coefficient (known as log(K ow ) or logP), vapor pressure, water solubility, Henry's law constant, and the acid dissociation constant (pKa). For most compounds, experiments were successful for at least one property; log(K ow ) yielded the largest return (176 values). It was determined that 77 ToxPrint structural features were enriched in chemicals with at least one measurement failure, indicating which features may have played a role in rapid method failures. To gauge consistency with traditional measurement methods, the new measurements were compared with previous measurements (where available). Since quantitative structure-activity/property relationship (QSAR/QSPR) models are used to fill gaps in physicochemical property information, 5 suites of QSPRs were evaluated for their predictive ability and chemical coverage or applicability domain of new experimental measurements. The ability to have accurate measurements of these properties will facilitate better exposure predictions in two ways: 1) direct input of these experimental measurements into exposure models; and 2) construction of QSPRs with a wider applicability domain, as their predicted physicochemical values can be used to parameterize exposure models in the absence of experimental data. Published by Elsevier B.V.

Prediction of gas chromatographic retention indices by the use of radial basis function neural networks.

PubMed

Yao, Xiaojun; Zhang, Xiaoyun; Zhang, Ruisheng; Liu, Mancang; Hu, Zhide; Fan, Botao

2002-05-16

A new method for the prediction of retention indices for a diverse set of compounds from their physicochemical parameters has been proposed. The two used input parameters for representing molecular properties are boiling point and molar volume. Models relating relationships between physicochemical parameters and retention indices of compounds are constructed by means of radial basis function neural networks. To get the best prediction results, some strategies are also employed to optimize the topology and learning parameters of the RBFNNs. For the test set, a predictive correlation coefficient R=0.9910 and root mean squared error of 14.1 are obtained. Results show that radial basis function networks can give satisfactory prediction ability and its optimization is less-time consuming and easy to implement.

Structural Prediction and In Silico Physicochemical Characterization for Mouse Caltrin I and Bovine Caltrin Proteins

PubMed Central

Grasso, Ernesto J.; Sottile, Adolfo E.; Coronel, Carlos E.

2016-01-01

It is known that caltrin (calcium transport inhibitor) protein binds to sperm cells during ejaculation and inhibits extracellular Ca2+ uptake. Although the sequence and some biological features of mouse caltrin I and bovine caltrin are known, their physicochemical properties and tertiary structure are mainly unknown. We predicted the 3D structures of mouse caltrin I and bovine caltrin by molecular homology modeling and threading. Surface electrostatic potentials and electric fields were calculated using the Poisson–Boltzmann equation. Several different bioinformatics tools and available web servers were used to thoroughly analyze the physicochemical characteristics of both proteins, such as their Kyte and Doolittle hydropathy scores and helical wheel projections. The results presented in this work significantly aid further understanding of the molecular mechanisms of caltrin proteins modulating physiological processes associated with fertilization. PMID:27812283

Contribution of engineered nanomaterials physicochemical properties to mast cell degranulation

NASA Astrophysics Data System (ADS)

Johnson, Monica M.; Mendoza, Ryan; Raghavendra, Achyut J.; Podila, Ramakrishna; Brown, Jared M.

2017-03-01

The rapid development of engineered nanomaterials (ENMs) has grown dramatically in the last decade, with increased use in consumer products, industrial materials, and nanomedicines. However, due to increased manufacturing, there is concern that human and environmental exposures may lead to adverse immune outcomes. Mast cells, central to the innate immune response, are one of the earliest sensors of environmental insult and have been shown to play a role in ENM-mediated immune responses. Our laboratory previously determined that mast cells are activated via a non-FcɛRI mediated response following silver nanoparticle (Ag NP) exposure, which was dependent upon key physicochemical properties. Using bone marrow-derived mast cells (BMMCs), we tested the hypothesis that ENM physicochemical properties influence mast cell degranulation. Exposure to 13 physicochemically distinct ENMs caused a range of mast degranulation responses, with smaller sized Ag NPs (5 nm and 20 nm) causing the most dramatic response. Mast cell responses were dependent on ENMs physicochemical properties such as size, apparent surface area, and zeta potential. Surprisingly, minimal ENM cellular association by mast cells was not correlated with mast cell degranulation. This study suggests that a subset of ENMs may elicit an allergic response and contribute to the exacerbation of allergic diseases.

Informatic deconvolution of biased GPCR signaling mechanisms from in vivo pharmacological experimentation.

PubMed

Maudsley, Stuart; Martin, Bronwen; Janssens, Jonathan; Etienne, Harmonie; Jushaj, Areta; van Gastel, Jaana; Willemsen, Ann; Chen, Hongyu; Gesty-Palmer, Diane; Luttrell, Louis M

2016-01-01

Ligands possessing different physico-chemical structures productively interact with G protein-coupled receptors generating distinct downstream signaling events due to their abilities to activate/select idiosyncratic receptor entities ('receptorsomes') from the full spectrum of potential receptor partners. We have employed multiple novel informatic approaches to identify and characterize the in vivo transcriptomic signature of an arrestin-signaling biased ligand, [D-Trp(12),Tyr(34)]-bPTH(7-34), acting at the parathyroid hormone type 1 receptor (PTH1R), across six different murine tissues after chronic drug exposure. We are able to demonstrate that [D-Trp(12),Tyr(34)]-bPTH(7-34) elicits a distinctive arrestin-signaling focused transcriptomic response that is more coherently regulated, in an arrestin signaling-dependent manner, across more tissues than that of the pluripotent endogenous PTH1R ligand, hPTH(1-34). This arrestin-focused response signature is strongly linked with the transcriptional regulation of cell growth and development. Our informatic deconvolution of a conserved arrestin-dependent transcriptomic signature from wild type mice demonstrates a conceptual framework within which the in vivo outcomes of biased receptor signaling may be further investigated or predicted. Published by Elsevier Inc.

Adhesive and abrasive wear mechanisms in ion implanted metals

NASA Astrophysics Data System (ADS)

Dearnaley, G.

1985-03-01

The distinction between adhesive and abrasive wear processes was introduced originally by Burwell during the nineteen-fifties, though some authors prefer to classify wear according to whether it is mild or severe. It is argued here that, on the basis of the performance of a variety of ion implanted metal surfaces, exposed to different modes of wear, the Burwell distinction is a valid one which, moreover, enables us to predict under which circumstances a given treatment will perform well. It is shown that, because wear rates under abrasive conditions are very sensitive to the ratio of the hardness of the surface to that of the abrasive particles, large increases in working life are attainable as a result of ion implantation. Under adhesive wear conditions, the wear rate appears to fall inversely as the hardness increases, and it is advantageous to implant species which will create and retain a hard surface oxide or other continuous film in order to reduce metal-metal contact. By the appropriate combination of physico-chemical changes in an implanted layer it has been possible to reduce wear rates by up to three orders of magnitude. Such rates compensate for the shallow depths achievable by ion implantation.

Beyond clay: Towards an improved set of variables for predicting soil organic matter content

USGS Publications Warehouse

Rasmussen, Craig; Heckman, Katherine; Wieder, William R.; Keiluweit, Marco; Lawrence, Corey R.; Berhe, Asmeret Asefaw; Blankinship, Joseph C.; Crow, Susan E.; Druhan, Jennifer; Hicks Pries, Caitlin E.; Marin-Spiotta, Erika; Plante, Alain F.; Schadel, Christina; Schmiel, Joshua P.; Sierra, Carlos A.; Thompson, Aaron; Wagai, Rota

2018-01-01

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.

Dry powder aerosols generated by standardized entrainment tubes from alternative sugar blends: 3. Trehalose dihydrate and D-mannitol carriers.

PubMed

Mansour, Heidi M; Xu, Zhen; Hickey, Anthony J

2010-08-01

The relationship between physicochemical properties of drug/carrier blends and aerosol drug powder delivery was evaluated. Four pulmonary drugs each representing the major pulmonary therapeutic classes and with a different pharmacological action were employed. Specifically, the four pulmonary drugs were albuterol sulfate, ipratropium bromide monohydrate, disodium cromoglycate, and fluticasone propionate. The two carrier sugars, each representing a different sugar class, were D-mannitol and trehalose dihydrate. Dry powder aerosols (2%, w/w, drug in carrier) delivered using standardized entrainment tubes (SETs) were characterized by twin-stage liquid impinger. The fine particle fraction (FPF) was correlated with SET shear stress, tau(s), and the maximum fine particle fraction (FPF(max)) was correlated with a deaggregation constant, k(d), by using a powder aerosol deaggregation equation (PADE) by nonlinear and linear regression analyses applied to pharmaceutical inhalation aerosol systems in the solid state. For the four pulmonary drugs representing the major pulmonary therapeutic classes and two chemically distinct pulmonary sugar carriers (non-lactose types) aerosolized with SETs having well-defined shear stress values, excellent correlation and predictive relationships were demonstrated for the novel and rigorous application of PADE for dry powder inhalation aerosol dispersion within a well-defined shear stress range, in the context of pulmonary drug/sugar carrier physicochemical and interfacial properties. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

PubMed

Wang, Hsin-Wei; Lin, Ya-Chi; Pai, Tun-Wen; Chang, Hao-Teng

2011-01-01

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

PubMed Central

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors. PMID:22701576

Integrating in Silico and in Vitro Approaches To Predict Drug Accessibility to the Central Nervous System.

PubMed

Zhang, Yan-Yan; Liu, Houfu; Summerfield, Scott G; Luscombe, Christopher N; Sahi, Jasminder

2016-05-02

Estimation of uptake across the blood-brain barrier (BBB) is key to designing central nervous system (CNS) therapeutics. In silico approaches ranging from physicochemical rules to quantitative structure-activity relationship (QSAR) models are utilized to predict potential for CNS penetration of new chemical entities. However, there are still gaps in our knowledge of (1) the relationship between marketed human drug derived CNS-accessible chemical space and preclinical neuropharmacokinetic (neuroPK) data, (2) interpretability of the selected physicochemical descriptors, and (3) correlation of the in vitro human P-glycoprotein (P-gp) efflux ratio (ER) and in vivo rodent unbound brain-to-blood ratio (Kp,uu), as these are assays routinely used to predict clinical CNS exposure, during drug discovery. To close these gaps, we explored the CNS druglike property boundaries of 920 market oral drugs (315 CNS and 605 non-CNS) and 846 compounds (54 CNS drugs and 792 proprietary GlaxoSmithKline compounds) with available rat Kp,uu data. The exact permeability coefficient (Pexact) and P-gp ER were determined for 176 compounds from the rat Kp,uu data set. Receiver operating characteristic curves were performed to evaluate the predictive power of human P-gp ER for rat Kp,uu. Our data demonstrates that simple physicochemical rules (most acidic pKa ≥ 9.5 and TPSA < 100) in combination with P-gp ER < 1.5 provide mechanistic insights for filtering BBB permeable compounds. For comparison, six classification modeling methods were investigated using multiple sets of in silico molecular descriptors. We present a random forest model with excellent predictive power (∼0.75 overall accuracy) using the rat neuroPK data set. We also observed good concordance between the structural interpretation results and physicochemical descriptor importance from the Kp,uu classification QSAR model. In summary, we propose a novel, hybrid in silico/in vitro approach and an in silico screening model for the effective development of chemical series with the potential to achieve optimal CNS exposure.

Chemical structures and characteristics of animal manures and composts during composting and assessment of maturity indices

PubMed Central

Huang, Jieying; Yu, Zixuan; Gao, Hongjian; Yan, Xiaoming; Chang, Jiang; Wang, Chengming; Hu, Jingwei

2017-01-01

Changes in physicochemical characteristics, chemical structures and maturity of swine, cattle and chicken manures and composts during 70-day composting without addition of bulking agents were investigated. Physicochemical characteristics were measured by routine analyses and chemical structures by solid-state 13C NMR and FT-IR. Three manures were of distinct properties. Their changes in physicochemical characteristics, chemical structures, and maturity were different not only from each other but also from those with addition of bulking agents during composting. Aromaticity in chicken manure composts decreased at first, and then increased whereas that in cattle and swine manure composts increased. Enhanced ammonia volatilization occurred without addition of bulking agents. NMR structural information indicated that cattle and chicken composts were relatively stable at day 36 and 56, respectively, but swine manure composts were not mature up to day 70. Finally, the days required for three manures to reach the threshold values of different maturity indices were different. PMID:28604783

Odor Impression Prediction from Mass Spectra.

PubMed

Nozaki, Yuji; Nakamoto, Takamichi

2016-01-01

The sense of smell arises from the perception of odors from chemicals. However, the relationship between the impression of odor and the numerous physicochemical parameters has yet to be understood owing to its complexity. As such, there is no established general method for predicting the impression of odor of a chemical only from its physicochemical properties. In this study, we designed a novel predictive model based on an artificial neural network with a deep structure for predicting odor impression utilizing the mass spectra of chemicals, and we conducted a series of computational analyses to evaluate its performance. Feature vectors extracted from the original high-dimensional space using two autoencoders equipped with both input and output layers in the model are used to build a mapping function from the feature space of mass spectra to the feature space of sensory data. The results of predictions obtained by the proposed new method have notable accuracy (R≅0.76) in comparison with a conventional method (R≅0.61).

Physicochemical Parameters Affecting the Electrospray Ionization Efficiency of Amino Acids after Acylation

PubMed Central

2017-01-01

Electrospray ionization (ESI) is widely used in liquid chromatography coupled to mass spectrometry (LC–MS) for the analysis of biomolecules. However, the ESI process is still not completely understood, and it is often a matter of trial and error to enhance ESI efficiency and, hence, the response of a given set of compounds. In this work we performed a systematic study of the ESI response of 14 amino acids that were acylated with organic acid anhydrides of increasing chain length and with poly(ethylene glycol) (PEG) changing certain physicochemical properties in a predictable manner. By comparing the ESI response of 70 derivatives, we found that there was a strong correlation between the calculated molecular volume and the ESI response, while correlation with hydrophobicity (log P values), pKa, and the inverse calculated surface tension was significantly lower although still present, especially for individual derivatized amino acids with increasing acyl chain lengths. Acylation with PEG containing five ethylene glycol units led to the largest gain in ESI response. This response was maximal independent of the calculated physicochemical properties or the type of amino acid. Since no actual physicochemical data is available for most derivatized compounds, the responses were also used as input for a quantitative structure–property relationship (QSPR) model to find the best physicochemical descriptors relating to the ESI response from molecular structures using the amino acids and their derivatives as a reference set. A topological descriptor related to molecular size (SPAN) was isolated next to a descriptor related to the atomic composition and structural groups (BIC0). The validity of the model was checked with a test set of 43 additional compounds that were unrelated to amino acids. While prediction was generally good (R2 > 0.9), compounds containing halogen atoms or nitro groups gave a lower predicted ESI response. PMID:28737384

Analysis of Physicochemical and Structural Properties Determining HIV-1 Coreceptor Usage

PubMed Central

Bozek, Katarzyna; Lengauer, Thomas; Sierra, Saleta; Kaiser, Rolf; Domingues, Francisco S.

2013-01-01

The relationship of HIV tropism with disease progression and the recent development of CCR5-blocking drugs underscore the importance of monitoring virus coreceptor usage. As an alternative to costly phenotypic assays, computational methods aim at predicting virus tropism based on the sequence and structure of the V3 loop of the virus gp120 protein. Here we present a numerical descriptor of the V3 loop encoding its physicochemical and structural properties. The descriptor allows for structure-based prediction of HIV tropism and identification of properties of the V3 loop that are crucial for coreceptor usage. Use of the proposed descriptor for prediction results in a statistically significant improvement over the prediction based solely on V3 sequence with 3 percentage points improvement in AUC and 7 percentage points in sensitivity at the specificity of the 11/25 rule (95%). We additionally assessed the predictive power of the new method on clinically derived ‘bulk’ sequence data and obtained a statistically significant improvement in AUC of 3 percentage points over sequence-based prediction. Furthermore, we demonstrated the capacity of our method to predict therapy outcome by applying it to 53 samples from patients undergoing Maraviroc therapy. The analysis of structural features of the loop informative of tropism indicates the importance of two loop regions and their physicochemical properties. The regions are located on opposite strands of the loop stem and the respective features are predominantly charge-, hydrophobicity- and structure-related. These regions are in close proximity in the bound conformation of the loop potentially forming a site determinant for the coreceptor binding. The method is available via server under http://structure.bioinf.mpi-inf.mpg.de/. PMID:23555214

Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages.

PubMed

de Moraes, Fábio R; Neshich, Izabella A P; Mazoni, Ivan; Yano, Inácio H; Pereira, José G C; Salim, José A; Jardine, José G; Neshich, Goran

2014-01-01

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

PubMed Central

de Moraes, Fábio R.; Neshich, Izabella A. P.; Mazoni, Ivan; Yano, Inácio H.; Pereira, José G. C.; Salim, José A.; Jardine, José G.; Neshich, Goran

2014-01-01

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html). PMID:24489849

Implementing Marine Organic Aerosols Into the GEOS-Chem Model

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.

2015-01-01

Marine-sourced organic aerosols (MOA) have been shown to play an important role in tropospheric chemistry by impacting surface mass, cloud condensation nuclei, and ice nuclei concentrations over remote marine and coastal regions. In this work, an online marine primary organic aerosol emission parameterization, designed to be used for both global and regional models, was implemented into the GEOS-Chem model. The implemented emission scheme improved the large under-prediction of organic aerosol concentrations in clean marine regions (normalized mean bias decreases from -79% when using the default settings to -12% when marine organic aerosols are added). Model predictions were also in good agreement (correlation coefficient of 0.62 and normalized mean bias of -36%) with hourly surface concentrations of MOA observed during the summertime at an inland site near Paris, France. Our study shows that MOA have weaker coastal-to-inland concentration gradients than sea-salt aerosols, leading to several inland European cities having > 10% of their surface submicron organic aerosol mass concentration with a marine source. The addition of MOA tracers to GEOS-Chem enabled us to identify the regions with large contributions of freshly-emitted or aged aerosol having distinct physicochemical properties, potentially indicating optimal locations for future field studies.

Physicochemical properties of aerosol released in the case of a fire involving materials used in the nuclear industry.

PubMed

Ouf, F-X; Mocho, V-M; Pontreau, S; Wang, Z; Ferry, D; Yon, J

2015-01-01

For industrial concerns, and more especially for nuclear applications, the characterization of soot is essential for predicting the behaviour of containment barriers in fire conditions. This study deals with the characterization (emission factor, composition, size, morphology, microstructure) of particles produced during thermal degradation of materials found in nuclear facilities (electrical cables, polymers, oil and solvents). Small-scale experiments have been conducted for oxygen concentrations [O2] ranging from 15% to 21% in order to imitate the oxygen depletion encountered during a confined fire. Particles denote distinct shapes, from aggregates composed of monomers with diameters ranging from 31.2 nm to 52.8 nm, to compact nanoparticles with diameters ranging from 15 nm to 400 nm, and their composition strongly depends on fuel type. Despite the organic to total carbon ratio (OC/TC), their properties are poorly influenced by the decrease in [O2]. Finally, two empirical correlations are proposed for predicting the OC/TC ratio and the monomer diameter, respectively, as a function of the fuel's carbon to hydrogen ratio and the emission factor. Copyright © 2014 Elsevier B.V. All rights reserved.

Reduced and unstratified crust in CV chondrite parent body.

PubMed

Ganino, Clément; Libourel, Guy

2017-08-15

Early Solar System planetesimal thermal models predict the heating of the chondritic protolith and the preservation of a chondritic crust on differentiated parent bodies. Petrological and geochemical analyses of chondrites have suggested that secondary alteration phases formed at low temperatures (<300 °C) by fluid-rock interaction where reduced and oxidized Vigarano type Carbonaceous (CV) chondrites witness different physicochemical conditions. From a thermodynamical survey of Ca-Fe-rich secondary phases in CV3 chondrites including silica activity (aSiO 2 ), here we show that the classical distinction between reduced and oxidized chondrites is no longer valid and that their Ca-Fe-rich secondary phases formed in similar reduced conditions near the iron-magnetite redox buffer at low aSiO 2 (log(aSiO 2 ) <-1) and moderate temperature (210-610 °C). The various lithologies in CV3 chondrites are inferred to be fragments of an asteroid percolated heterogeneously via porous flow of hydrothermal fluid. Putative 'onion shell' structures are not anymore a requirement for the CV parent body crust.Meteorites may unlock the history of the early solar system. Here, the authors find, through Ca-Fe-rich secondary phases, that the distinction between reduced and oxidized CV chondrites is invalid; therefore, CV3 chondrites are asteroid fragments that percolated heterogeneously via porous flow of hydrothermal fluid.

Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools

NASA Astrophysics Data System (ADS)

Judycka, U.; Jagiello, K.; Bober, L.; Błażejowski, J.; Puzyn, T.

2018-06-01

Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 2. Aqueous solubility, octanol solubility and octanol-water partition coefficient.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses additive and non-additive parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky (2014) on a data set of 700 hydrocarbons. Recently, Admire et al. (2014) expanded the model to predict the boiling and melting points of 1288 polyhalogenated benzenes, biphenyls, dibenzo-p-dioxins, diphenyl ethers, anisoles and alkanes. In this work, 19 new group descriptors are determined and used to predict the aqueous solubilities, octanol solubilities and the octanol-water coefficients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictions of the physicochemical properties of amino acid side chain analogs using molecular simulation.

PubMed

Ahmed, Alauddin; Sandler, Stanley I

2016-03-07

A candidate drug compound is released for clinical trails (in vivo activity) only if its physicochemical properties meet desirable bioavailability and partitioning criteria. Amino acid side chain analogs play vital role in the functionalities of protein and peptides and as such are important in drug discovery. We demonstrate here that the predictions of solvation free energies in water, in 1-octanol, and self-solvation free energies computed using force field-based expanded ensemble molecular dynamics simulation provide good accuracy compared to existing empirical and semi-empirical methods. These solvation free energies are then, as shown here, used for the prediction of a wide range of physicochemical properties important in the assessment of bioavailability and partitioning of compounds. In particular, we consider here the vapor pressure, the solubility in both water and 1-octanol, and the air-water, air-octanol, and octanol-water partition coefficients of amino acid side chain analogs computed from the solvation free energies. The calculated solvation free energies using different force fields are compared against each other and with available experimental data. The protocol here can also be used for a newly designed drug and other molecules where force field parameters and charges are obtained from density functional theory.

Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.

PubMed

McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D; Schaffner, Donald W; Danyluk, Michelle D

2013-07-01

Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R(2) < 0.1) and between physicochemical indicators and Salmonella levels (R(2) < 0.1). The average rainfall (previous day, week, and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration can predict the probability of enumerating selected Salmonella levels. The lack of good correlations between biological indicators and Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression.

Predicting Salmonella Populations from Biological, Chemical, and Physical Indicators in Florida Surface Waters

PubMed Central

McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D.; Schaffner, Donald W.

2013-01-01

Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R2 < 0.1) and between physicochemical indicators and Salmonella levels (R2 < 0.1). The average rainfall (previous day, week, and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration can predict the probability of enumerating selected Salmonella levels. The lack of good correlations between biological indicators and Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression. PMID:23624476

Two-level QSAR network (2L-QSAR) for peptide inhibitor design based on amino acid properties and sequence positions.

PubMed

Du, Q S; Ma, Y; Xie, N Z; Huang, R B

2014-01-01

In the design of peptide inhibitors the huge possible variety of the peptide sequences is of high concern. In collaboration with the fast accumulation of the peptide experimental data and database, a statistical method is suggested for peptide inhibitor design. In the two-level peptide prediction network (2L-QSAR) one level is the physicochemical properties of amino acids and the other level is the peptide sequence position. The activity contributions of amino acids are the functions of physicochemical properties and the sequence positions. In the prediction equation two weight coefficient sets {ak} and {bl} are assigned to the physicochemical properties and to the sequence positions, respectively. After the two coefficient sets are optimized based on the experimental data of known peptide inhibitors using the iterative double least square (IDLS) procedure, the coefficients are used to evaluate the bioactivities of new designed peptide inhibitors. The two-level prediction network can be applied to the peptide inhibitor design that may aim for different target proteins, or different positions of a protein. A notable advantage of the two-level statistical algorithm is that there is no need for host protein structural information. It may also provide useful insight into the amino acid properties and the roles of sequence positions.

Exploratory multivariate modeling and prediction of the physico-chemical properties of surface water and groundwater

NASA Astrophysics Data System (ADS)

Ayoko, Godwin A.; Singh, Kirpal; Balerea, Steven; Kokot, Serge

2007-03-01

SummaryPhysico-chemical properties of surface water and groundwater samples from some developing countries have been subjected to multivariate analyses by the non-parametric multi-criteria decision-making methods, PROMETHEE and GAIA. Complete ranking information necessary to select one source of water in preference to all others was obtained, and this enabled relationships between the physico-chemical properties and water quality to be assessed. Thus, the ranking of the quality of the water bodies was found to be strongly dependent on the total dissolved solid, phosphate, sulfate, ammonia-nitrogen, calcium, iron, chloride, magnesium, zinc, nitrate and fluoride contents of the waters. However, potassium, manganese and zinc composition showed the least influence in differentiating the water bodies. To model and predict the water quality influencing parameters, partial least squares analyses were carried out on a matrix made up of the results of water quality assessment studies carried out in Nigeria, Papua New Guinea, Egypt, Thailand and India/Pakistan. The results showed that the total dissolved solid, calcium, sulfate, sodium and chloride contents can be used to predict a wide range of physico-chemical characteristics of water. The potential implications of these observations on the financial and opportunity costs associated with elaborate water quality monitoring are discussed.

Amino acid sequence analysis of the annexin super-gene family of proteins.

PubMed

Barton, G J; Newman, R H; Freemont, P S; Crumpton, M J

1991-06-15

The annexins are a widespread family of calcium-dependent membrane-binding proteins. No common function has been identified for the family and, until recently, no crystallographic data existed for an annexin. In this paper we draw together 22 available annexin sequences consisting of 88 similar repeat units, and apply the techniques of multiple sequence alignment, pattern matching, secondary structure prediction and conservation analysis to the characterisation of the molecules. The analysis clearly shows that the repeats cluster into four distinct families and that greatest variation occurs within the repeat 3 units. Multiple alignment of the 88 repeats shows amino acids with conserved physicochemical properties at 22 positions, with only Gly at position 23 being absolutely conserved in all repeats. Secondary structure prediction techniques identify five conserved helices in each repeat unit and patterns of conserved hydrophobic amino acids are consistent with one face of a helix packing against the protein core in predicted helices a, c, d, e. Helix b is generally hydrophobic in all repeats, but contains a striking pattern of repeat-specific residue conservation at position 31, with Arg in repeats 4 and Glu in repeats 2, but unconserved amino acids in repeats 1 and 3. This suggests repeats 2 and 4 may interact via a buried saltbridge. The loop between predicted helices a and b of repeat 3 shows features distinct from the equivalent loop in repeats 1, 2 and 4, suggesting an important structural and/or functional role for this region. No compelling evidence emerges from this study for uteroglobin and the annexins sharing similar tertiary structures, or for uteroglobin representing a derivative of a primordial one-repeat structure that underwent duplication to give the present day annexins. The analyses performed in this paper are re-evaluated in the Appendix, in the light of the recently published X-ray structure for human annexin V. The structure confirms most of the predictions and shows the power of techniques for the determination of tertiary structural information from the amino acid sequences of an aligned protein family.

An Online Prediction Platform to Support the Environmental Sciences (American Chemical Society)

EPA Science Inventory

Historical QSAR models are currently utilized across a broad range of applications within the U.S. Environmental Protection Agency (EPA). These models predict basic physicochemical properties (e.g., logP, aqueous solubility, vapor pressure), which are then incorporated into expo...

Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity.

PubMed

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous system) suggesting specific molecular and physiological roles of promiscuous metabolites.

Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity

PubMed Central

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous system) suggesting specific molecular and physiological roles of promiscuous metabolites. PMID:26442281

Spatially uniform resistance switching of low current, high endurance titanium–niobium-oxide memristors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Suhas; Davila, Noraica; Wang, Ziwen

2016-11-24

Here we analyzed micrometer-scale titanium-niobium-oxide prototype memristors, which exhibited low write-power (< 3 μW) and energy (< 200 fJ per bit per μm 2), low read-power (~nW), and high endurance ( > millions of cycles). To understand their physico-chemical operating mechanisms, we performed in operando synchrotron X-ray transmission nanoscale spectromicroscopy using an ultra-sensitive time-multiplexed technique. We observed only spatially uniform material changes during cell operation, in sharp contrast to the frequently detected formation of a localized conduction channel in transition-metal-oxide memristors. We also associated the response of assigned spectral features distinctly to non-volatile storage (resistance change) and writing of informationmore » (application of voltage and Joule heating). Lastly, these results provide critical insights into high-performance memristors that will aid in device design, scaling and predictive circuit-modeling, all of which are essential for the widespread deployment of successful memristor applications.« less

Evaluation of chemical parameters in soft mold-ripened cheese during ripening by mid-infrared spectroscopy.

PubMed

Martín-del-Campo, S T; Picque, D; Cosío-Ramírez, R; Corrieu, G

2007-06-01

The suitability of mid-infrared spectroscopy (MIR) to follow the evolution throughout ripening of specific physicochemical parameters in Camembert-type cheeses was evaluated. The infrared spectra were obtained directly from raw cheese samples deposited on an attenuated total reflectance crystal. Significant correlations were observed between physicochemical data, pH, acid-soluble nitrogen, nonprotein nitrogen, ammonia (NH4+), lactose, and lactic acid. Dry matter showed significant correlation only with lactose and nonprotein nitrogen. Principal components analysis factorial maps of physicochemical data showed a ripening evolution in 2 steps, from d 1 to d 7 and from d 8 to d 27, similar to that observed previously from infrared spectral data. Partial least squares regressions made it possible to obtain good prediction models for dry matter, acid-soluble nitrogen, nonprotein nitrogen, lactose, lactic acid, and NH4+ values from spectral data of raw cheese. The values of 3 statistical parameters (coefficient of determination, root mean square error of cross validation, and ratio prediction deviation) are satisfactory. Less precise models were obtained for pH.

Target-Independent Prediction of Drug Synergies Using Only Drug Lipophilicity

PubMed Central

2015-01-01

Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds (“drugs”) previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms. PMID:25026390

Dyes assay for measuring physicochemical parameters.

PubMed

Moczko, Ewa; Meglinski, Igor V; Bessant, Conrad; Piletsky, Sergey A

2009-03-15

A combination of selective fluorescent dyes has been developed for simultaneous quantitative measurements of several physicochemical parameters. The operating principle of the assay is similar to electronic nose and tongue systems, which combine nonspecific or semispecific elements for the determination of diverse analytes and chemometric techniques for multivariate data analysis. The analytical capability of the proposed mixture is engendered by changes in fluorescence signal in response to changes in environment such as pH, temperature, ionic strength, and presence of oxygen. The signal is detected by a three-dimensional spectrofluorimeter, and the acquired data are processed using an artificial neural network (ANN) for multivariate calibration. The fluorescence spectrum of a solution of selected dyes allows discreet reading of emission maxima of all dyes composing the mixture. The variations in peaks intensities caused by environmental changes provide distinctive fluorescence patterns which can be handled in the same way as the signals collected from nose/tongue electrochemical or piezoelectric devices. This optical system opens possibilities for rapid, inexpensive, real-time detection of a multitude of physicochemical parameters and analytes of complex samples.

Influence of the inlet air temperature in a fluid bed coating process on drug release from shellac-coated pellets.

PubMed

Farag, Yassin; Leopold, Claudia Sabine

2011-03-01

Since the introduction of aqueous ammoniacal solutions, shellac regained importance for pharmaceutical applications. However, as shellac is a material obtained from natural resources, its quality and thus its physicochemical properties may vary depending on its origin and the type of refining. In this study theophylline pellets were coated with aqueous solutions of three different commercially available shellac types. The inlet air temperature of the coating process was varied, and its influence on drug release from the coated pellet formulations was investigated. Film formation was correlated to the physicochemical and mechanical properties of the investigated shellac types. Pellets coated at lower temperatures showed distinct cracks in the coating film resulting in a loss of the barrier function during dissolution testing. These cracks were nonreversible by additional curing. The physicochemical and mechanical properties of the investigated shellac types varied significantly and could hardly be related to the drug release performance of the investigated formulations. Obviously, with shellac a minimum inlet air temperature must be exceeded to achieve a coherent coating film. This temperature was dependent on the investigated shellac type.

In silico Study of the Pharmacologic Properties and Cytotoxicity Pathways in Cancer Cells of Various Indolylquinone Analogues of Perezone.

PubMed

Escobedo-González, René; Vargas-Requena, Claudia Lucia; Moyers-Montoya, Edgar; Aceves-Hernández, Juan Manuel; Nicolás-Vázquez, María Inés; Miranda-Ruvalcaba, René

2017-06-25

Several indolylquinone analogues of perezone, a natural sesquiterpene quinone, were characterized in this work by theoretical methods. In addition, some physicochemical, toxicological and metabolic properties were predicted using bioinformatics software. The predicted physicochemical properties are in agreement with the solubility and cLogP values, the penetration across the cell membrane, and absorption values, as well as with a possible apoptosis-activated mechanism of cytotoxic action. The toxicological predictions suggest no mutagenic, tumorigenic or reproductive effects of the four target molecules. Complementarily, the results of a performed docking study show high scoring values and hydrogen bonding values in agreement with the cytotoxicity IC 50 value ranking, i.e: indolylmenadione > indolylperezone > indolylplumbagine > indolylisoperezone. Consequently, it is possible to suggest an appropriate apoptotic pathway for each compound. Finally, potential metabolic pathways of the molecules were proposed.

Components of spatial and temporal soil variation at Canyonlands National Park: Implications for P dynamics and cheatgrass (Bromus tectorum) performance

Treesearch

Mark Miller; Jayne Belnap; Susan Beatty; Bruce Webb

2001-01-01

From January 1997 through October 1998, research was conducted at Canyonlands National Park to investigate soil traits responsible for distinct spatial patterns of cheatgrass (Bromus tectorum) occurrence. Field experiments were conducted at sites representing a broad range of soil conditions and cheatgrass abundances. Standard physicochemical soil measures in...

Isolation and separation of physicochemically distinct fimbrial types expressed on a single culture of Escherichia coli O7:K1:H6.

PubMed Central

Karch, H; Leying, H; Büscher, K H; Kroll, H P; Opferkuch, W

1985-01-01

The fimbrial (pili) profile of a single strain of Escherichia coli O7:K1:H6 (WF96) was evaluated. Fimbriae were isolated by sucrose density gradient ultracentrifugation, purified from flagellae by the use of 0.4% sodium dodecyl sulfate (SDS), and separated into distinct fimbrial types. Analysis of the purified WF96 fimbriae by SDS-polyacrylamide gel electrophoresis revealed two polypeptide bands with molecular weights of 16,000 and 21,000. Treatment of the fimbrial mixture with saturated guanidine hydrochloride resulted in the appearance of a third band with a molecular weight of 19,500. The relative susceptibilities of the WF96 fimbrial types to disrupting chemicals (octyl-glucoside, urea, SDS, and guanidine hydrochloride) were assessed by exposure of the fimbrial mixture to each agent, separation of the depolymerized fimbriae from intact fimbriae by gel filtration on Sepharose CL-4B, and identification of the disaggregated fimbrial types by SDS-polyacrylamide gel electrophoresis of column fractions. The physicochemical heterogeneity of the three fimbrial types coexpressed on WF96 was exploited to develop a method for separation of individual fimbriae. Images PMID:2857155

Process signatures in glatiramer acetate synthesis: structural and functional relationships.

PubMed

Campos-García, Víctor R; Herrera-Fernández, Daniel; Espinosa-de la Garza, Carlos E; González, German; Vallejo-Castillo, Luis; Avila, Sandra; Muñoz-García, Leslie; Medina-Rivero, Emilio; Pérez, Néstor O; Gracia-Mora, Isabel; Pérez-Tapia, Sonia Mayra; Salazar-Ceballos, Rodolfo; Pavón, Lenin; Flores-Ortiz, Luis F

2017-09-21

Glatiramer Acetate (GA) is an immunomodulatory medicine approved for the treatment of multiple sclerosis, whose mechanisms of action are yet to be fully elucidated. GA is comprised of a complex mixture of polypeptides with different amino acid sequences and structures. The lack of sensible information about physicochemical characteristics of GA has contributed to its comprehensiveness complexity. Consequently, an unambiguous determination of distinctive attributes that define GA is of highest relevance towards dissecting its identity. Herein we conducted a study of characteristic GA heterogeneities throughout its manufacturing process (process signatures), revealing a strong impact of critical process parameters (CPPs) on the reactivity of amino acid precursors; reaction initiation and polymerization velocities; and peptide solubility, susceptibility to hydrolysis, and size-exclusion properties. Further, distinctive GA heterogeneities were correlated to defined immunological and toxicological profiles, revealing that GA possesses a unique repertoire of active constituents (epitopes) responsible of its immunological responses, whose modification lead to altered profiles. This novel approach established CPPs influence on intact GA peptide mixture, whose physicochemical identity cannot longer rely on reduced properties (based on complete or partial GA degradation), providing advanced knowledge on GA structural and functional relationships to ensure a consistent manufacturing of safe and effective products.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 1. Boiling point and melting point.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses enthalpic and entropic parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky on a data set of 700 hydrocarbons. The aim of this work is to expand the UPPER model to estimate the boiling and melting points of polyhalogenated compounds. In this work, 19 new group descriptors are defined and used to predict the transition temperatures of an additional 1288 compounds. The boiling points of 808 and the melting points of 742 polyhalogenated compounds are predicted with average absolute errors of 13.56 K and 25.85 K, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

PREDICTING THE ADSORPTION CAPACITY OF ACTIVATED CARBON FOR ORGANIC CONTAMINANTS FROM ADSORBENT AND ADSORBATE PROPERTIES

EPA Science Inventory

A quantitative structure-property relationship (QSPR) was developed and combined with the Polanyi-Dubinin-Manes model to predict adsorption isotherms of emerging contaminants on activated carbons with a wide range of physico-chemical properties. Affinity coefficients (β_l

Dipeptide Formation from Amino Acid Monomer Induced by keV Ion Irradiation: An Implication for Physicochemical Repair by Radiation Itself

NASA Astrophysics Data System (ADS)

Wang, Wei; Yuan, Hang; Wang, Xiangqin; Yu, Zengliang

2008-02-01

An identification of Phe dipeptide from L-phenylalanine monomers after keV nitrogen and argon ion implantation, by using the HPLC (high performance liquid chromatography) and LC-MS(liquid chromatography mass spectrometer) methods is reported. The results showed a similar yield behavior for both ion species, namely: 1) the yield of dipeptides under alkalescent conditions was distinctly higher than that under acidic or neutral conditions; 2) for different ion species, the dose-yield curves tracked a similar trend which was called a counter-saddle curve. The dipeptide formation may implicate a recombination repair mechanism of damaged biomolecules that energetic ions have left in their wake. Accordingly a physicochemical self-repair mechanism by radiation itself for the ion-beam radiobiological effects is proposed.

Associations between soil bacterial community structure and nutrient cycling functions in long-term organic farm soils following cover crop and organic fertilizer amendment.

PubMed

Fernandez, Adria L; Sheaffer, Craig C; Wyse, Donald L; Staley, Christopher; Gould, Trevor J; Sadowsky, Michael J

2016-10-01

Agricultural management practices can produce changes in soil microbial populations whose functions are crucial to crop production and may be detectable using high-throughput sequencing of bacterial 16S rRNA. To apply sequencing-derived bacterial community structure data to on-farm decision-making will require a better understanding of the complex associations between soil microbial community structure and soil function. Here 16S rRNA sequencing was used to profile soil bacterial communities following application of cover crops and organic fertilizer treatments in certified organic field cropping systems. Amendment treatments were hairy vetch (Vicia villosa), winter rye (Secale cereale), oilseed radish (Raphanus sativus), buckwheat (Fagopyrum esculentum), beef manure, pelleted poultry manure, Sustane(®) 8-2-4, and a no-amendment control. Enzyme activities, net N mineralization, soil respiration, and soil physicochemical properties including nutrient levels, organic matter (OM) and pH were measured. Relationships between these functional and physicochemical parameters and soil bacterial community structure were assessed using multivariate methods including redundancy analysis, discriminant analysis, and Bayesian inference. Several cover crops and fertilizers affected soil functions including N-acetyl-β-d-glucosaminidase and β-glucosidase activity. Effects, however, were not consistent across locations and sampling timepoints. Correlations were observed among functional parameters and relative abundances of individual bacterial families and phyla. Bayesian analysis inferred no directional relationships between functional activities, bacterial families, and physicochemical parameters. Soil functional profiles were more strongly predicted by location than by treatment, and differences were largely explained by soil physicochemical parameters. Composition of soil bacterial communities was predictive of soil functional profiles. Differences in soil function were better explained using both soil physicochemical test values and bacterial community structure data than using soil tests alone. Pursuing a better understanding of bacterial community composition and how it is affected by farming practices is a promising avenue for increasing our ability to predict the impact of management practices on important soil functions. Copyright © 2016. Published by Elsevier B.V.

PREDICTING THE ADSORPTION CAPACITY OF ACTIVATED CARBON FOR EMERGING ORGANIC CONTAMINANTS FROM FUNDAMENTAL ADSORBENT AND ADSORBATE PROPERTIES - PRESENTATION

EPA Science Inventory

A quantitative structure-property relationship (QSPR) was developed and combined with the Polanyi-Dubinin-Manes model to predict adsorption isotherms of emerging contaminants on activated carbons with a wide range of physico-chemical properties. Affinity coefficients (β_l

Data Aggregation, Curation and Modeling Approaches to Deliver Prediction Models to Support Computational Toxicology at the EPA (ACS Fall meeting)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program develops and utilizes QSAR modeling approaches across a broad range of applications. In terms of physical chemistry we have a particular interest in the prediction of basic physicochemical parameters ...

MOLE 2.0: advanced approach for analysis of biomacromolecular channels

PubMed Central

2013-01-01

Background Channels and pores in biomacromolecules (proteins, nucleic acids and their complexes) play significant biological roles, e.g., in molecular recognition and enzyme substrate specificity. Results We present an advanced software tool entitled MOLE 2.0, which has been designed to analyze molecular channels and pores. Benchmark tests against other available software tools showed that MOLE 2.0 is by comparison quicker, more robust and more versatile. As a new feature, MOLE 2.0 estimates physicochemical properties of the identified channels, i.e., hydropathy, hydrophobicity, polarity, charge, and mutability. We also assessed the variability in physicochemical properties of eighty X-ray structures of two members of the cytochrome P450 superfamily. Conclusion Estimated physicochemical properties of the identified channels in the selected biomacromolecules corresponded well with the known functions of the respective channels. Thus, the predicted physicochemical properties may provide useful information about the potential functions of identified channels. The MOLE 2.0 software is available at http://mole.chemi.muni.cz. PMID:23953065

Xanthine oxidase inhibitors beyond allopurinol and febuxostat; an overview and selection of potential leads based on in silico calculated physico-chemical properties, predicted pharmacokinetics and toxicity.

PubMed

Šmelcerović, Andrija; Tomović, Katarina; Šmelcerović, Žaklina; Petronijević, Živomir; Kocić, Gordana; Tomašič, Tihomir; Jakopin, Žiga; Anderluh, Marko

2017-07-28

Xanthine oxidase (XO), a versatile metalloflavoprotein enzyme, catalyzes the oxidative hydroxylation of hypoxanthine and xanthine to uric acid in purine catabolism while simultaneously producing reactive oxygen species. Both lead to the gout-causing hyperuricemia and oxidative damage of the tissues where overactivity of XO is present. Over the past years, significant progress and efforts towards the discovery and development of new XO inhibitors have been made and we believe that not only experts in the field, but also general readership would benefit from a review that addresses this topic. Accordingly, the aim of this article was to overview and select the most potent recently reported XO inhibitors and to compare their structures, mechanisms of action, potency and effectiveness of their inhibitory activity, in silico calculated physico-chemical properties as well as predicted pharmacokinetics and toxicity. Derivatives of imidazole, 1,3-thiazole and pyrimidine proved to be more potent than febuxostat while also displaying/possessing favorable predicted physico-chemical, pharmacokinetic and toxicological properties. Although being structurally similar to febuxostat, these optimized inhibitors bear some structural freshness and could be adopted as hits for hit-to-lead development and further evaluation by in vivo studies towards novel drug candidates, and represent valuable model structures for design of novel XO inhibitors. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences.

PubMed

Chen, Peng; Li, Jinyan; Wong, Limsoon; Kuwahara, Hiroyuki; Huang, Jianhua Z; Gao, Xin

2013-08-01

Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. Copyright © 2013 Wiley Periodicals, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fast, J; Zhang, Q; Tilp, A

Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.

Transport of Cryptosporidium oocysts in porous media: Role of straining and physicochemical filtration

USGS Publications Warehouse

Tufenkji, N.; Miller, G.F.; Ryan, J.N.; Harvey, R.W.; Elimelech, M.

2004-01-01

The transport and filtration behavior of Cryptosporidium parvum oocysts in columns packed with quartz sand was systematically examined under repulsive electrostatic conditions. An increase in solution ionic strength resulted in greater oocyst deposition rates despite theoretical predictions of a significant electrostatic energy barrier to deposition. Relatively high deposition rates obtained with both oocysts and polystyrene latex particles of comparable size at low ionic strength (1 mM) suggest that a physical mechanism may play a key role in oocyst removal. Supporting experiments conducted with latex particles of varying sizes, under very low ionic strength conditions where physicochemical filtration is negligible, clearly indicated that physical straining is an important capture mechanism. The results of this study indicate that irregularity of sand grain shape (verified by SEM imaging) contributes considerably to the straining potential of the porous medium. Hence, both straining and physicochemical filtration are expected to control the removal of C. parvum oocysts in settings typical of riverbank filtration, soil infiltration, and slow sand filtration. Because classic colloid filtration theory does not account for removal by straining, these observations have important implications with respect to predictions of oocyst transport.

A comparative study of Northern Ireland's estuaries based on the results of beam trawl fish surveys

NASA Astrophysics Data System (ADS)

Harrison, Trevor D.; Armour, Neil D.; McNeill, Michael T.; Moorehead, Peter W.

2017-11-01

The fish communities of Northern Ireland's estuaries were described and compared using data collected with a modified beam trawl over a six year period from 2009 to 2014. Multivariate analyses identified four estuary groups based on variations in their physico-chemical attributes. These groups broadly corresponded with the distribution and variation of estuary geomorphic types identified around the Irish coast. The dominant fish species captured were also among the main species reported in other North East Atlantic estuaries. A significant link between the estuary types and their fish communities was found; each estuary group contained a somewhat distinctive fish community. The fish communities also showed a significant relationship with the physico-chemical characteristics of the estuaries. Differences in fish species composition are attributed to habitat and environmental preferences of key estuary-associated species.

Differences in Temperature and Water Chemistry Shape Distinct Diversity Patterns in Thermophilic Microbial Communities

PubMed Central

Chiriac, Cecilia M.; Szekeres, Edina; Rudi, Knut; Baricz, Andreea; Hegedus, Adriana; Dragoş, Nicolae

2017-01-01

ABSTRACT This report describes the biodiversity and ecology of microbial mats developed in thermal gradients (20 to 65°C) in the surroundings of three drillings (Chiraleu [CH], Ciocaia [CI], and Mihai Bravu [MB]) tapping a hyperthermal aquifer in Romania. Using a metabarcoding approach, 16S rRNA genes were sequenced from both DNA and RNA transcripts (cDNA) and compared. The relationships between the microbial diversity and the physicochemical factors were explored. Additionally, the cDNA data were used for in silico functionality predictions, bringing new insights into the functional potential and dynamics of these communities. The results showed that each hot spring determined the formation of distinct microbial communities. In the CH mats (40 to 53°C), the abundance of Cyanobacteria decreased with temperature, opposite to those of Chloroflexi and Proteobacteria. Ectothiorhodospira, Oscillatoria, and methanogenic archaea dominated the CI communities (20 to 65°C), while the MB microbial mats (53 to 65°C) were mainly composed of Chloroflexi, Hydrogenophilus, Thermi, and Aquificae. Alpha-diversity was negatively correlated with the increase in water temperature, while beta-diversity was shaped in each hot spring by the unique combination of physicochemical parameters, regardless of the type of nucleic acid analyzed (DNA versus cDNA). The rank correlation analysis revealed a unique model that associated environmental data with community composition, consisting in the combined effect of Na+, K+, HCO3−, and PO43− concentrations, together with temperature and electrical conductivity. These factors seem to determine the grouping of samples according to location, rather than with the similarities in thermal regimes, showing that other parameters beside temperature are significant drivers of biodiversity. IMPORTANCE Hot spring microbial mats represent a remarkable manifestation of life on Earth and have been intensively studied for decades. Moreover, as hot spring areas are isolated and have a limited exchange of organisms, nutrients, and energy with the surrounding environments, hot spring microbial communities can be used in model studies to elucidate the colonizing potential within extreme settings. Thus, they are of great importance in evolutionary biology, microbial ecology, and exobiology. In spite of all the efforts that have been made, the current understanding of the influence of temperature and water chemistry on the microbial community composition, diversity, and abundance in microbial mats is limited. In this study, the composition and diversity of microbial communities developed in thermal gradients in the vicinity of three hot springs from Romania were investigated, each having particular physicochemical characteristics. Our results expose new factors that could determine the formation of these ecosystems, expanding the current knowledge in this regard. PMID:28821552

Genome-scale prediction of proteins with long intrinsically disordered regions.

PubMed

Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

2014-01-01

Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

An investigation into studying of the activated sludge foaming potential by using physicochemical parameters.

PubMed

Hladikova, K; Ruzickova, I; Klucova, P; Wanner, J

2002-01-01

This paper examines how the physicochemical characteristics of the solids are related to foam formation and describes how the foaming potential of full-scale plants can be assessed. The relations among activated sludge and biological foam hydrophobicity, scum index, aeration tank cover and filamentous population are evaluated. Individual parameter comparison reveals the scumming intensity can be estimated only on the assumption that foams is already established. None of the above mentioned characteristics can be reliably used to predict the foaming episodes at wastewater treatment plants.

Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties.

PubMed

Salahinejad, Maryam

2015-01-01

Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

Human β-Synuclein Rendered Fibrillogenic by Designed Mutations

PubMed Central

Zibaee, Shahin; Fraser, Graham; Jakes, Ross; Owen, David; Serpell, Louise C.; Crowther, R. Anthony; Goedert, Michel

2010-01-01

Filamentous inclusions made of α-synuclein are found in nerve cells and glial cells in a number of human neurodegenerative diseases, including Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. The assembly and spreading of these inclusions are likely to play an important role in the etiology of common dementias and movement disorders. Both α-synuclein and the homologous β-synuclein are abundantly expressed in the central nervous system; however, β-synuclein is not present in the pathological inclusions. Previously, we observed a poor correlation between filament formation and the presence of residues 73–83 of α-synuclein, which are absent in β-synuclein. Instead, filament formation correlated with the mean β-sheet propensity, charge, and hydrophilicity of the protein (global physicochemical properties) and β-strand contiguity calculated by a simple algorithm of sliding averages (local physicochemical property). In the present study, we rendered β-synuclein fibrillogenic via one set of point mutations engineered to enhance global properties and a second set engineered to enhance predominantly β-strand contiguity. Our findings show that the intrinsic physicochemical properties of synucleins influence their fibrillogenic propensity via two distinct but overlapping modalities. The implications for filament formation and the pathogenesis of neurodegenerative diseases are discussed. PMID:20833719

Relating physico-chemical properties of frozen green peas (Pisum sativum L.) to sensory quality.

PubMed

Nleya, Kathleen M; Minnaar, Amanda; de Kock, Henriëtte L

2014-03-30

The acceptability of frozen green peas depends on their sensory quality. There is a need to relate physico-chemical parameters to sensory quality. In this research, six brands of frozen green peas representing product sold for retail and caterer's markets were purchased and subjected to descriptive sensory evaluation and physico-chemical analyses (including dry matter content, alcohol insoluble solids content, starch content, °Brix, residual peroxidase activity, size sorting, hardness using texture analysis and colour measurements) to assess and explain product quality. The sensory quality of frozen green peas, particularly texture properties, were well explained using physico-chemical methods of analysis notably alcohol insoluble solids, starch content, hardness and °Brix. Generally, retail class peas were of superior sensory quality to caterer's class peas although one caterer's brand was comparable to the retail brands. Retail class peas were sweeter, smaller, greener, more moist and more tender than the caterer's peas. Retail class peas also had higher °Brix, a(*) , hue and chroma values; lower starch, alcohol insoluble solids, dry matter content and hardness measured. The sensory quality of frozen green peas can be partially predicted by measuring physico-chemical parameters particularly °Brix and to a lesser extent hardness by texture analyser, alcohol insoluble solids, dry matter and starch content. © 2013 Society of Chemical Industry.

Prediction of pork quality parameters by applying fractals and data mining on MRI.

PubMed

Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés; Amigo, José Manuel; Dahl, Anders B; ErsbØll, Bjarne K; Antequera, Teresa

2017-09-01

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy. Copyright © 2017. Published by Elsevier Ltd.

Insight into the Structure of Amyloid Fibrils from the Analysis of Globular Proteins

PubMed Central

Trovato, Antonio; Chiti, Fabrizio; Maritan, Amos; Seno, Flavio

2006-01-01

The conversion from soluble states into cross-β fibrillar aggregates is a property shared by many different proteins and peptides and was hence conjectured to be a generic feature of polypeptide chains. Increasing evidence is now accumulating that such fibrillar assemblies are generally characterized by a parallel in-register alignment of β-strands contributed by distinct protein molecules. Here we assume a universal mechanism is responsible for β-structure formation and deduce sequence-specific interaction energies between pairs of protein fragments from a statistical analysis of the native folds of globular proteins. The derived fragment–fragment interaction was implemented within a novel algorithm, prediction of amyloid structure aggregation (PASTA), to investigate the role of sequence heterogeneity in driving specific aggregation into ordered self-propagating cross-β structures. The algorithm predicts that the parallel in-register arrangement of sequence portions that participate in the fibril cross-β core is favoured in most cases. However, the antiparallel arrangement is correctly discriminated when present in fibrils formed by short peptides. The predictions of the most aggregation-prone portions of initially unfolded polypeptide chains are also in excellent agreement with available experimental observations. These results corroborate the recent hypothesis that the amyloid structure is stabilised by the same physicochemical determinants as those operating in folded proteins. They also suggest that side chain–side chain interaction across neighbouring β-strands is a key determinant of amyloid fibril formation and of their self-propagating ability. PMID:17173479

Physicochemical properties of an insensitive munitions compound, N-methyl-4-nitroaniline (MNA).

PubMed

Boddu, Veera M; Abburi, Krishnaiah; Maloney, Stephen W; Damavarapu, Reddy

2008-06-30

Accurate information on physicochemical properties of an organic contaminant is essential for predicting its environmental impact and fate. These properties also provide invaluable information for the overall understanding of environmental distribution, biotransformation, and potential treatment processes. In this study the aqueous solubility (Sw), octanol-water partition coefficient (Kow), and Henry's law constant (K(H)) were determined for an insensitive munitions (IM) compound, N-methyl-4-nitroaniline (MNA), at 298.15, 308.15, and 318.15 K. Effect of ionic strength on solubility, using electrolytes such as NaCl and CaCl2, was also studied. The data on the physicochemical parameters were correlated using the standard Van't Hoff equation. All three properties exhibited a linear relationship with reciprocal temperature. The enthalpy and entropy of phase transfer were derived from the experimental data.

Chemical Transformation Simulator

EPA Science Inventory

The Chemical Transformation Simulator (CTS) is a web-based, high-throughput screening tool that automates the calculation and collection of physicochemical properties for an organic chemical of interest and its predicted products resulting from transformations in environmental sy...

Biokinetics of zinc oxide nanoparticles: toxicokinetics, biological fates, and protein interaction

PubMed Central

Choi, Soo-Jin; Choy, Jin-Ho

2014-01-01

Biokinetic studies of zinc oxide (ZnO) nanoparticles involve systematic and quantitative analyses of absorption, distribution, metabolism, and excretion in plasma and tissues of whole animals after exposure. A full understanding of the biokinetics provides basic information about nanoparticle entry into systemic circulation, target organs of accumulation and toxicity, and elimination time, which is important for predicting the long-term toxic potential of nanoparticles. Biokinetic behaviors can be dependent on physicochemical properties, dissolution property in biological fluids, and nanoparticle–protein interaction. Moreover, the determination of biological fates of ZnO nanoparticles in the systemic circulation and tissues is critical in interpreting biokinetic behaviors and predicting toxicity potential as well as mechanism. This review focuses on physicochemical factors affecting the biokinetics of ZnO nanoparticles, in concert with understanding bioavailable fates and their interaction with proteins. PMID:25565844

Stochasticity of bacterial attachment and its predictability by the extended derjaguin-landau-verwey-overbeek theory.

PubMed

Chia, Teck Wah R; Nguyen, Vu Tuan; McMeekin, Thomas; Fegan, Narelle; Dykes, Gary A

2011-06-01

Bacterial attachment onto materials has been suggested to be stochastic by some authors but nonstochastic and based on surface properties by others. We investigated this by attaching pairwise combinations of two Salmonella enterica serovar Sofia (S. Sofia) strains (with different physicochemical and attachment properties) with one strain each of S. enterica serovar Typhimurium, S. enterica serovar Infantis, or S. enterica serovar Virchow (all with similar physicochemical and attachment abilities) in ratios of 0.428, 1, and 2.333 onto glass, stainless steel, Teflon, and polysulfone. Attached bacterial cells were recovered and counted. If the ratio of attached cells of each Salmonella serovar pair recovered was the same as the initial inoculum ratio, the attachment process was deemed stochastic. Experimental outcomes from the study were compared to those predicted by the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory. Significant differences (P < 0.05) between the initial and the attached ratios for serovar pairs containing S. Sofia S1296a for all different ratios were apparent for all materials. For S. Sofia S1635-containing pairs, 7 out of 12 combinations of serovar pairs and materials had attachment ratios not significantly different (P > 0.05) from the initial ratio of 0.428. Five out of 12 and 10 out of 12 samples had attachment ratios not significantly different (P > 0.05) from the initial ratios of 1 and 2.333, respectively. These results demonstrate that bacterial attachment to different materials is likely to be nonstochastic only when the key physicochemical properties of the bacteria were significantly different (P < 0.05) from each other. XDLVO theory could successfully predict the attachment of some individual isolates to particular materials but could not be used to predict the likelihood of stochasticity in pairwise attachment experiments.

Roasting pumpkin seeds and changes in the composition and oxidative stability of cold-pressed oils.

PubMed

Raczyk, Marianna; Siger, Aleksander; Radziejewska-Kubzdela, Elżbieta; Ratusz, Katarzyna; Rudzińska, Magdalena

2017-01-01

Pumpkin seed oil is valuable oil for its distinctive taste and aroma, as well as supposed health- promoting properties. The aim of this study was to investigate how roasting pumpkin seeds influences the physicochemical properties of cold-pressed oils. The fatty acid composition, content of phytosterols, carotenoids and tocopherols, oxidative stability and colour were determined in oils after cold pressing and storage for 3 months using GC-FID, GCxGC-ToFMS, HPLC, Rancimat and spectrophotometric methods. The results of this study indicate that the seed-roasting and storage process have no effect on the fatty acid composition of pumpkin seed oils, but does affect phytosterols and tocopherols. The carotenoid content decreased after storage. The colour of the roasted oil was darker and changed significantly during storage. Pumpkin oil obtained from roasted seeds shows better physicochemical properties and oxidative stability than oil from unroasted seeds.

Physicochemical characterization of epigallocatechin gallate lipid nanoparticles (EGCG-LNs) for ocular instillation.

PubMed

Fangueiro, Joana F; Andreani, Tatiana; Fernandes, Lisete; Garcia, Maria L; Egea, Maria A; Silva, Amélia M; Souto, Eliana B

2014-11-01

The encapsulation of epigallocatechin gallate (EGCG) in lipid nanoparticles (LNs) could be a suitable approach to avoid drug oxidation and epimerization, which are common processes that lead to low bioavailability of the drug limiting its therapeutic efficacy. The human health benefits of EGCG gained much interest in the pharmaceutical field, and so far there are no studies reporting its encapsulation in LNs. The purpose of this study has been the development of an innovative system for the ocular delivery of EGCG using LNs as carrier for the future treatment of several diseases, such as dry eye, age-related macular degeneration (AMD), glaucoma, diabetic retinopathy and macular oedema. LNs dispersions have been produced by multiple emulsion technique and previously optimized by a factorial design. In order to increase ocular retention time and mucoadhesion by electrostatic attraction, two distinct cationic lipids were used, namely, cetyltrimethylammonium bromide (CTAB) and dimethyldioctadecylammonium bromide (DDAB). EGCG has been successfully loaded in the LNs dispersions and the nanoparticles analysis over 30 days of storage time predicted a good physicochemical stability. The particles were found to be in the nanometer range (<300 nm) and all the evaluated parameters, namely pH, osmolarity and viscosity, were compatible to the ocular administration. The evaluation of the cationic lipid used was compared regarding physical and chemical parameters, lipid crystallization and polymorphism, and stability of dispersion during storage. The results show that different lipids lead to different characteristics mainly associated with the acyl chain composition, i.e. double lipid shows to have influence in the crystallization and stability. Despite the recorded differences between DTAB and DDAB, both cationic LNs seem to fit the parameters for ocular drug delivery. Copyright © 2014 Elsevier B.V. All rights reserved.

Discovery of Antibiotics-derived Polymers for Gene Delivery using Combinatorial Synthesis and Cheminformatics Modeling

PubMed Central

Potta, Thrimoorthy; Zhen, Zhuo; Grandhi, Taraka Sai Pavan; Christensen, Matthew D.; Ramos, James; Breneman, Curt M.; Rege, Kaushal

2014-01-01

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology. PMID:24331709

A hypothetical model for predicting the toxicity of high aspect ratio nanoparticles (HARN)

NASA Astrophysics Data System (ADS)

Tran, C. L.; Tantra, R.; Donaldson, K.; Stone, V.; Hankin, S. M.; Ross, B.; Aitken, R. J.; Jones, A. D.

2011-12-01

The ability to predict nanoparticle (dimensional structures which are less than 100 nm in size) toxicity through the use of a suitable model is an important goal if nanoparticles are to be regulated in terms of exposures and toxicological effects. Recently, a model to predict toxicity of nanoparticles with high aspect ratio has been put forward by a consortium of scientists. The High aspect ratio nanoparticles (HARN) model is a platform that relates the physical dimensions of HARN (specifically length and diameter ratio) and biopersistence to their toxicity in biological environments. Potentially, this model is of great public health and economic importance, as it can be used as a tool to not only predict toxicological activity but can be used to classify the toxicity of various fibrous nanoparticles, without the need to carry out time-consuming and expensive toxicology studies. However, this model of toxicity is currently hypothetical in nature and is based solely on drawing similarities in its dimensional geometry with that of asbestos and synthetic vitreous fibres. The aim of this review is two-fold: (a) to present findings from past literature, on the physicochemical property and pathogenicity bioassay testing of HARN (b) to identify some of the challenges and future research steps crucial before the HARN model can be accepted as a predictive model. By presenting what has been done, we are able to identify scientific challenges and research directions that are needed for the HARN model to gain public acceptance. Our recommendations for future research includes the need to: (a) accurately link physicochemical data with corresponding pathogenicity assay data, through the use of suitable reference standards and standardised protocols, (b) develop better tools/techniques for physicochemical characterisation, (c) to develop better ways of monitoring HARN in the workplace, (d) to reliably measure dose exposure levels, in order to support future epidemiological studies.

Modeling of phytoextraction efficiency of microbially stimulated Salix dasyclados L. in the soils with different speciation of heavy metals.

PubMed

Złoch, Michał; Kowalkowski, Tomasz; Tyburski, Jarosław; Hrynkiewicz, Katarzyna

2017-12-02

Bioaugmentation of soils with selected microorganisms during phytoextraction can be the key solution for successful bioremediation and should be accurately calculated for different physicochemical soil properties and heavy metal availability to guarantee the universality of this method. Equally important is the development of an accurate prediction tool to manage phytoremediation process. The main objective of this study was to evaluate the role of three metallotolerant siderophore-producing Streptomyces sp. B1-B3 strains in the phytoremediation of heavy metals with the use of S. dasyclados L. growing in four metalliferrous soils as well as modeling the efficiency of this process based on physicochemical and microbiological properties of the soils using artificial neural network (ANN) analysis. The bacterial inoculation of plants significantly stimulated plant biomass and reduced oxidative stress. Moreover, the bacteria affected the speciation of heavy metals and finally their mobility, thereby enhancing the uptake and bioaccumulation of Zn, Cd, and Pb in the biomass. The best capacity for phytoextraction was noted for strain B1, which had the highest siderophore secretion ability. Finally, ANN model permitted to predict efficiency of phytoextraction based on both the physicochemical properties of the soils and the activity of the soil microbiota with high precision.

Soil-Bacterium Compatibility Model as a Decision-Making Tool for Soil Bioremediation.

PubMed

Horemans, Benjamin; Breugelmans, Philip; Saeys, Wouter; Springael, Dirk

2017-02-07

Bioremediation of organic pollutant contaminated soil involving bioaugmentation with dedicated bacteria specialized in degrading the pollutant is suggested as a green and economically sound alternative to physico-chemical treatment. However, intrinsic soil characteristics impact the success of bioaugmentation. The feasibility of using partial least-squares regression (PLSR) to predict the success of bioaugmentation in contaminated soil based on the intrinsic physico-chemical soil characteristics and, hence, to improve the success of bioaugmentation, was examined. As a proof of principle, PLSR was used to build soil-bacterium compatibility models to predict the bioaugmentation success of the phenanthrene-degrading Novosphingobium sp. LH128. The survival and biodegradation activity of strain LH128 were measured in 20 soils and correlated with the soil characteristics. PLSR was able to predict the strain's survival using 12 variables or less while the PAH-degrading activity of strain LH128 in soils that show survival was predicted using 9 variables. A three-step approach using the developed soil-bacterium compatibility models is proposed as a decision making tool and first estimation to select compatible soils and organisms and increase the chance of success of bioaugmentation.

OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

PubMed

Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

2017-03-01

Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

Predicting consumer preferences for mineral composition of bottled and tap water.

PubMed

Platikanov, Stefan; Hernández, Alejandra; González, Susana; Luis Cortina, Jose; Tauler, Roma; Devesa, Ricard

2017-01-01

The overall liking for taste of water was correlated with the mineral composition of selected bottled and tap waters. Sixty-nine untrained volunteers assessed and rated twenty-five different commercial bottled and tap waters from. Water samples were physicochemical characterised by analysing conductivity, pH, total dissolved solids (TDS) and major anions and cations: HCO 3 - , SO 4 2- , Cl - , NO 3 - , Ca 2+ , Mg 2+ , Na + , and K + . Residual chlorine levels were also analysed in the tap water samples. Globally, volunteers preferred waters rich in calcium bicarbonate and sulfate, rather than in sodium chloride. This study also demonstrated that it was possible to accurately predict the overall liking by a Partial Least Squares regression using either all measured physicochemical parameters or a reduced number of them. These results were in agreement with previously published results using trained panellists. Copyright © 2016 Elsevier B.V. All rights reserved.

Influence of selected physicochemical parameters on microbiological activity of mucks.

NASA Astrophysics Data System (ADS)

Całka, A.; Sokołowska, Z.; Warchulska, P.; Dąbek-Szreniawska, M.

2009-04-01

One of the basic factor decided about soil fertility are microorganisms that together with flora, determine trend and character of biochemical processes as well totality of fundamental transformations connected with biogeochemistry and physicochemical properties of soil. Determination of general bacteria number, quantity of selected groups of microorganisms and investigation of respiration intensity let estimate microbiological activity of soil. Intensity of microbiological processes is directly connected with physicochemical soil parameters. In that case, such structural parameters as bulk density, porosity, surface or carbon content play significant role. Microbiological activity also changes within the bounds of mucks with different stage of humification and secondary transformation. Knowledge of relations between structural properties, microorganism activity and degree of transformation and humification can lead to better understanding microbiological processes as well enable to estimate microbiological activity at given physicochemical conditions and at progressing process of soil transformation. The study was carried out on two peaty-moorsh (muck) soils at different state of secondary transformation and humification degree. Soil samples were collected from Polesie Lubelskie (layer depth: 5 - 25 cm). Investigated mucks originated from soils formed from low peatbogs. Soil sample marked as I belonged to muck group weakly secondary transformed. Second sample (II) represented soil group with middle stage of secondary transformation. The main purpose of the research was to examine the relations between some physicochemical and surface properties and their biological activity. Total number and respiration activity of microorganisms were determined. The effectiveness of utilizing the carbon substances from the soil by the bacteria increased simultaneously with the transformation state of the peat-muck soils. Quantity of organic carbon decreased distinctly in the soil at the higher stage of secondary transformation and it influenced quantity and activity of soil microorganisms. Bulk density and surface increased with increasing secondary transformation degree. On the other hand, porosity decreased with increasing secondary transformation index. Process of secondary transformation influenced the soil environment for the microbes by changing the physicochemical properties. This way it influenced the number of microorganisms and caused changes of biological activity in the soils.

Honey collected from different floras of Chandigarh Tricity: a comparative study involving physicochemical parameters and biochemical activities.

PubMed

Kumar, Pradeep; Sindhu, Rakesh K; Narayan, Shridhar; Singh, Inderbir

2010-12-01

Different monofloral honeys have a distinctive flavor and color because of differences in physicochemical parameters because of their principal nectar sources or floral types. Honey samples were collected from Apis mellifera colonies forged on 10 floras to analyze the quality of honey in terms of standards laid by Honey Grading and Marking Rules (HGMR), India, 2008 and Codex Alimentarious Commission (CAC), 1969 . The honey samples were analyzed for various physicochemical parameters of honey quality control, i.e., pH, total acidity, moisture, reducing sugars, non-reducing sugars, total sugars, water insoluble solids (WIS), ash content, 5-hydroxymethylfurfural content, and diastase value. The antioxidant potential was estimated using Folin-Ciocalteu reagent. Further, honey samples were assayed for antibacterial activities against clinical isolates of Staphylococcus aureus and Escherichia coli using the hole-plate diffusion method. The physicochemical variation in the composition of honey because of floral source shows Ziziphus honey with high pH and diastase values along with low acidity, whereas Helianthus honey contained high reducing sugar and low moisture content. Amomum, Brassica, Acacia, and Citrus contained lowest amount of non-reducing sugars, ash, WIS, and moisture, respectively. Lowest 5-hydroxymethylfurfural (HMF) value was detected in Amomum honey, while highest HMF value was observed with Eucalyptus. The maximum antibacterial and antioxidant potential was observed in Azadirachta and Citrus, respectively. The quality of honey produced by local beekeepers met HGMR and CAC standards, and the chemical composition and biological properties of honey were dependent on the floral source from which it was produced.

Safety, Efficacy, and Physicochemical Characterization of Tinospora crispa Ointment: A Community-Based Formulation against Pediculus humanus capitis

PubMed Central

Torre, Gerwin Louis Tapan Dela; Ponsaran, Kerstin Mariae Gonzales; de Guzman, Angelica Louise Dela Peña; Manalo, Richelle Ann Mallapre; Arollado, Erna Custodio

2017-01-01

The high prevalence of pediculosis capitis, commonly known as head lice (Pediculus humanus capitis) infestation, has led to the preparation of a community-based pediculicidal ointment, which is made of common household items and the extract of Tinospora crispa stem. The present study aimed to evaluate the safety, efficacy, and physicochemical characteristics of the T. crispa pediculicidal ointment. The physicochemical properties of the ointment were characterized, and safety was determined using acute dermal irritation test (OECD 404), while the efficacy was assessed using an in vitro pediculicidal assay. Furthermore, the chemical compounds present in T. crispa were identified using liquid-liquid extraction followed by ultra-performance liquid chromatography quadruple time-of-flight mass spectrometric (UPLC-qTOF/MS) analysis. The community-based ointment formulation was light yellow in color, homogeneous, smooth, with distinct aromatic odor and pH of 6.92±0.09. It has spreadability value of 15.04±0.98 g·cm/sec and has thixotropic behavior. It was also found to be non-irritant, with a primary irritation index value of 0.15. Moreover, it was comparable to the pediculicidal activity of the positive control Kwell®, a commercially available 1% permethrin shampoo (P>0.05), and was significantly different to the activity of the negative control ointment, a mixture of palm oil and candle wax (P<0.05). These findings suggested that the community-based T. crispa pediculicidal ointment is safe and effective, having acceptable physicochemical characteristics. Its activity can be attributed to the presence of compounds moupinamide and physalin I. PMID:28877572

Nonequilibrium description of de novo biogenesis and transport through Golgi-like cisternae

NASA Astrophysics Data System (ADS)

Sachdeva, Himani; Barma, Mustansir; Rao, Madan

2016-12-01

A central issue in cell biology is the physico-chemical basis of organelle biogenesis in intracellular trafficking pathways, its most impressive manifestation being the biogenesis of Golgi cisternae. At a basic level, such morphologically and chemically distinct compartments should arise from an interplay between the molecular transport and chemical maturation. Here, we formulate analytically tractable, minimalist models, that incorporate this interplay between transport and chemical progression in physical space, and explore the conditions for de novo biogenesis of distinct cisternae. We propose new quantitative measures that can discriminate between the various models of transport in a qualitative manner-this includes measures of the dynamics in steady state and the dynamical response to perturbations of the kind amenable to live-cell imaging.

Characterization of physicochemical and thermal properties and crystallization behavior of krabok (Irvingia Malayana ) and rambutan seed fats.

PubMed

Sonwai, Sopark; Ponprachanuvut, Punnee

2012-01-01

Fatty acid composition, physicochemical and thermal properties and crystallization behavior of fats extracted from the seeds of krabok (Irvingia Malayana) and rambutan (Nephelium lappaceum L.) trees grown in Thailand were studied and compared with cocoa butter (CB). The krabok seed fat, KSF, consisted of 46.9% lauric and 40.3% myristic acids. It exhibited the highest saponification value and slip melting point but the lowest iodine values. The three fats displayed different crystallization behavior at 25°C. KSF crystallized into a mixture of β' and pseudo-β' structures with a one-step crystallization curve and high solid fat content (SFC). The fat showed simple DSC crystallization and melting thermograms with one distinct peak. The rambutan seed fat, RSF, consisted of 42.5% arachidic and 33.1% oleic acids. Its crystallization behavior was more similar to CB than KSF, displaying a two-step crystallization curve with SFC lower than that of KSF. RSF solidified into a mixture of β' and pseudo-β' before transforming to β after 24 h. The large spherulitic microstructures were observed in both KSF and RSF. According to these results, the Thai KSF and RSF exhibited physicochemical, thermal characteristics and crystallization behavior that could be suitable for specific applications in several areas of the food, cosmetic and pharmaceutical industries.

Statistical Analysis of Crystallization Database Links Protein Physico-Chemical Features with Crystallization Mechanisms

PubMed Central

Fusco, Diana; Barnum, Timothy J.; Bruno, Andrew E.; Luft, Joseph R.; Snell, Edward H.; Mukherjee, Sayan; Charbonneau, Patrick

2014-01-01

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis. PMID:24988076

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

PubMed

Fusco, Diana; Barnum, Timothy J; Bruno, Andrew E; Luft, Joseph R; Snell, Edward H; Mukherjee, Sayan; Charbonneau, Patrick

2014-01-01

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

The physicochemical process of bacterial attachment to abiotic surfaces: Challenges for mechanistic studies, predictability and the development of control strategies.

PubMed

Wang, Yi; Lee, Sui Mae; Dykes, Gary

2015-01-01

Bacterial attachment to abiotic surfaces can be explained as a physicochemical process. Mechanisms of the process have been widely studied but are not yet well understood due to their complexity. Physicochemical processes can be influenced by various interactions and factors in attachment systems, including, but not limited to, hydrophobic interactions, electrostatic interactions and substratum surface roughness. Mechanistic models and control strategies for bacterial attachment to abiotic surfaces have been established based on the current understanding of the attachment process and the interactions involved. Due to a lack of process control and standardization in the methodologies used to study the mechanisms of bacterial attachment, however, various challenges are apparent in the development of models and control strategies. In this review, the physicochemical mechanisms, interactions and factors affecting the process of bacterial attachment to abiotic surfaces are described. Mechanistic models established based on these parameters are discussed in terms of their limitations. Currently employed methods to study these parameters and bacterial attachment are critically compared. The roles of these parameters in the development of control strategies for bacterial attachment are reviewed, and the challenges that arise in developing mechanistic models and control strategies are assessed.

In vitro oral drug permeation models: the importance of taking physiological and physico-chemical factors into consideration.

PubMed

Joubert, Ruan; Steyn, Johan Dewald; Heystek, Hendrik Jacobus; Steenekamp, Jan Harm; Du Preez, Jan Lourens; Hamman, Josias Hendrik

2017-02-01

The assessment of intestinal membrane permeability properties of new chemical entities is a crucial step in the drug discovery and development process and a variety of in vitro models, methods and techniques are available to estimate the extent of oral drug absorption in humans. However, variations in certain physiological and physico-chemical factors are often not reflected in the results and the complex dynamic interplay between these factors is sometimes oversimplified with in vitro models. Areas covered: In vitro models to evaluate drug pharmacokinetics are briefly outlined, while both physiological and physico-chemical factors that may have an influence on these techniques are critically reviewed. The shortcomings identified for some of the in vitro techniques are discussed in conjunction with novel ways to improve and thereby overcome some challenges. Expert opinion: Although conventional in vitro methods and theories are used as basic guidelines to predict drug absorption, critical evaluations have identified some shortcomings. Advancements in technology have made it possible to investigate and understand the role of physiological and physico-chemical factors in drug delivery more clearly, which can be used to improve and refine the techniques to more closely mimic the in vivo environment.

CALCULATION OF PHYSICOCHEMICAL PROPERTIES FOR ENVIRONMENTAL MODELING

EPA Science Inventory

Recent trends in environmental regulatory strategies dictate that EPA will rely heavily on predictive modeling to carry out the increasingly complex array of exposure and risk assessments necessary to develop scientifically defensible regulations. In response to this need, resea...

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: V. Predictive absorbability models.

PubMed

Langenbucher, Frieder

2007-08-01

This paper discusses Excel applications related to the prediction of drug absorbability from physicochemical constants. PHDISSOC provides a generalized model for pH profiles of electrolytic dissociation, water solubility, and partition coefficient. SKMODEL predicts drug absorbability, based on a log-log plot of water solubility and O/W partitioning; augmented by additional features such as electrolytic dissociation, melting point, and the dose administered. GIABS presents a mechanistic model of g.i. drug absorption. BIODATCO presents a database compiling relevant drug data to be used for quantitative predictions.

Influence of monitoring data selection for optimization of a steady state multimedia model on the magnitude and nature of the model prediction bias.

PubMed

Kim, Hee Seok; Lee, Dong Soo

2017-11-01

SimpleBox is an important multimedia model used to estimate the predicted environmental concentration for screening-level exposure assessment. The main objectives were (i) to quantitatively assess how the magnitude and nature of prediction bias of SimpleBox vary with the selection of observed concentration data set for optimization and (ii) to present the prediction performance of the optimized SimpleBox. The optimization was conducted using a total of 9604 observed multimedia data for 42 chemicals of four groups (i.e., polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs), polybrominated diphenyl ethers (PBDEs), phthalates, and polycyclic aromatic hydrocarbons (PAHs)). The model performance was assessed based on the magnitude and skewness of prediction bias. Monitoring data selection in terms of number of data and kind of chemicals plays a significant role in optimization of the model. The coverage of the physicochemical properties was found to be very important to reduce the prediction bias. This suggests that selection of observed data should be made such that the physicochemical property (such as vapor pressure, octanol-water partition coefficient, octanol-air partition coefficient, and Henry's law constant) range of the selected chemical groups be as wide as possible. With optimization, about 55%, 90%, and 98% of the total number of the observed concentration ratios were predicted within factors of three, 10, and 30, respectively, with negligible skewness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linking water quality guidelines to the natural characteristics of catchments in order to support distinct aquatic ecosystems: Water quality guidelines for suspended particulate matter

NASA Astrophysics Data System (ADS)

Bilotta, G. S.; Grove, M. K.; Harrison, C.; Joyce, C. B.; Peacock, C.

2012-12-01

The natural characteristics of a catchment provide a template that controls the background rates of geomorphological processes operating within that catchment, which in-turn determines the background physico-chemical and hydro-morphological characteristics of the catchment's surface waters. Large differences in the natural characteristics of catchments (e.g. geology, topography, climate), lead to unique physico-chemical and hydro-morphological conditions that support unique freshwater communities. However, this uniqueness is not always recognised in international water quality guidelines, which often attempt to apply blanket water-quality guidelines to 'protect' a wide range of ecosystems. In this paper we investigate the natural characteristics that control background concentrations of suspended particulate matter (SPM - including nano-scale particles to sand-sized sediments), which is a well-known cause of ecological degradation. At present, the management of SPM is hampered by a lack of understanding of the SPM conditions that water quality managers should aim to achieve in contrasting environments in order to support good ecological status. To address this, in this paper we examine the SPM preferences of contrasting biological communities that are in reference condition (minimal anthropogenic disturbance and high ecological status). We analyse historical SPM data collected on a monthly basis from a wide range of reference-condition temperate environments (638 stream/river sites comprising 42 different biological community-types). This analysis reveals that there are statistically significant differences (One-way ANOVA p < 0.001) between the background SPM concentrations observed in contrasting communities that are in reference condition. Mean background SPM concentrations for contrasting communities ranged from 1.7 to 26.2 mg L-1 (i.e. more than a 15-fold difference). We propose a model for predicting environment-specific water quality guidelines for SPM. In order to develop this model, the 638 reference-condition sites were first classified into one of five mean background SPM ranges (0.00-5.99, 6.00-11.99, 12.00-17.99, 18.00-23.99 and >24.00 mg L-1). Stepwise Multiple Discriminant Analysis (MDA) of these ranges showed that a site's SPM range can be predicted as a function of: mean annual air temperature, mean annual precipitation, mean altitude of upstream catchment, distance from source, slope to source, channel width and depth, the percentage of catchment area comprised of clay, chalk, and hard rock solid geology, and the percentage of the catchment area comprised of blown sand/landslide material as the surface (drift) material. Although the model is still being improved and developed, this research highlights the need to link water quality guidelines to the natural characteristics of catchments and the physico-chemical preferences of the biological communities that would naturally inhabit them.

Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

PubMed

De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

2007-10-01

The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics.

CELLULAR UPTAKE AND TOXICITY OF DENDRITIC NANOMATERIALS: AN INTEGRATED PHYSICOCHEMICAL AND TOXICOGENOMICS STUDY

EPA Science Inventory

The successful completion of this project is expected to provide industry with critical data and predictive tools needed to assess the health and environmental impact of dendritic nanomaterials such as EDA core PAMAM dendrimers.

In Vitro Pulmonary Toxicity of Metal Oxide Nanoparticles

EPA Science Inventory

Nanomaterials (NMs) encompass a diversity of materials with unique physicochemical characteristics which raise concerns about their potential risk to human health. Rapid predictive testing methods are needed to characterize NMs health effects as well as to screen and prioritize N...

Utilization of physicochemical variables developed from changes in sensory attributes and consumer acceptability to predict the shelf life of fresh-cut mango fruit.

PubMed

Salinas-Hernández, Rosa María; González-Aguilar, Gustavo A; Tiznado-Hernández, Martín Ernesto

2015-01-01

Sensory evaluation is the ideal tool for shelf-life determination. With the objective to develop an easy shelf-life indicator, color (L*, a*, b*, chroma and hue angle), total soluble solids (TSS), firmness (F), pH, acidity, and the sensory attributes of appearance, brightness, browning, odor, flavor, texture, color, acidity and sweetness were evaluated in fresh cut mangoes (FCM) stored at 5, 10, 15 and 20 °C. Overall acceptability was evaluated by consumers. Correlation analysis between sensory attributes and physicochemical variables was carried out. Physicochemical cut-off points based on sensory attributes and consumer acceptability was obtained by regression analysis and utilized to estimate FCM shelf-life by kinetic models fitted to each variable. The validation of the model was done by comparing the shelf life estimated by kinetic models and consumers. It was recorded large correlations between appearance, brightness, and color with L*; appearance and color with chroma and hue angle; sweetness and flavor with TSS, and between F and texture. The shelf life estimated based on consumer using a 9 point hedonic scale was in the range of 10-12, 2.3-2.6, 1.3-1.5 and 1.0-1.1 days for 5, 10, 15 and 20 °C. It was recorded large correlation coefficients between the shelf life estimated by consumer acceptability scores and physicochemical variables. Kinetic models based on physicochemical variables showed a tendency to overestimate the shelf life as compared with the models bases on the sensory attributes. It was concluded that physicochemical variables can be used as a tool to estimate the FCM shelf life.

Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

PubMed

Mager, P P; Rothe, H

1990-10-01

Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.

Diversity of A-conotoxins of three worm-hunting cone snails (Conus brunneus, Conus nux, and Conus princeps) from the Mexican Pacific coast.

PubMed

Morales-González, Daniel; Flores-Martínez, Ernesto; Zamora-Bustillos, Roberto; Rivera-Reyes, Reginaldo; Michel-Morfín, Jesús Emilio; Landa-Jaime, Víctor; Falcón, Andrés; Aguilar, Manuel B

2015-06-01

Conus marine snails (∼500 species) are tropical predators that use venoms mainly to capture prey and defend themselves from predators. The principal components of these venoms are peptides that are known as "conotoxins" and generally comprise 7-40 amino acid residues, including 0-5 disulfide bridges and distinct posttranslational modifications. The most common molecular targets of conotoxins are voltage- and ligand-gated ion channels, G protein-coupled receptors, and neurotransmitter transporters, to which they bind, typically, with high affinity and specificity. Due to these properties, several conotoxins have become molecular probes, medicines, and leads for drug design. Conotoxins have been classified into genetic superfamilies based on the signal sequence of their precursors, and into pharmacological families according to their molecular targets. The objective of this work was to identify and analyze partial cDNAs encoding conotoxin precursors belonging to the A superfamily from Conus brunneus, Conus nux, and Conus princeps. These are vermivorous species of the Mexican Pacific coast from which only one A-conotoxin, and few O- and I2-conotoxins have been reported. Employing RT-PCR, we identified 30 distinct precursors that contain 13 different predicted mature toxins. With the exception of two groups of four highly similar peptides, these toxins are diverse at both the sequence and the physicochemical levels, and they belong to the 4/3, 4/4, 4/5, 4/6, and 4/7 structural subfamilies. These toxins are predicted to target diverse nicotinic acetylcholine receptor (nAChR) subtypes: nx1d, muscle; pi1a-pi1d, α3β2, α7, and/or α9α10; br1a, muscle, α3β4, and/or α4β2; and nx1a-nx1c/pi1g and pi1h, α3β2, α3β4, α9β10, and/or α7. Copyright © 2015 Elsevier Inc. All rights reserved.

Nanocarbon surfaces for biomedicine

PubMed Central

Reina, Giacomo; Tamburri, Emanuela; Orlanducci, Silvia; Gay, Stefano; Matassa, Roberto; Guglielmotti, Valeria; Lavecchia, Teresa; Letizia Terranova, Maria; Rossi, Marco

2014-01-01

The distinctive physicochemical, mechanical and electrical properties of carbon nanostructures are currently gaining the interest of researchers working in bioengineering and biomedical fields. Carbon nanotubes, carbon dendrimers, graphenic platelets and nanodiamonds are deeply studied aiming at their application in several areas of biology and medicine.   Here we provide a summary of the carbon nanomaterials prepared in our labs and of the fabrication techniques used to produce several biomedical utilities, from scaffolds for tissue growth to cargos for drug delivery and to biosensors. PMID:24646883

Predicting SVOC Emissions into Air and Foods in Support of ...

EPA Pesticide Factsheets

The release of semi-volatile organic compounds (SVOCs) from consumer articles may be a critical human exposure pathway. In addition, the migration of SVOCs from food packaging materials into foods may also be a dominant source of exposure for some chemicals. Here we describe recent efforts to characterize emission-related parameters for these exposure pathways to support prediction of aggregate exposures for thousands of chemicals For chemicals in consumer articles, Little et al. (2012) developed a screening-level indoor exposure prediction model which, for a given SVOC, principally depends on steady-state gas-phase concentrations (y0). We have developed a model that predicts y0 for SVOCs in consumer articles, allowing exposure predictions for 274 ToxCast chemicals. Published emissions data for 31 SVOCs found in flooring materials, provided a training set where both chemical-specific physicochemical properties, article specific formulation properties, and experimental design aspects were available as modeling descriptors. A linear regression yielded R2- and p- values of approximately 0.62 and 3.9E-05, respectively. A similar model was developed based upon physicochemical properties alone, since article information is often not available for a given SVOC or product. This latter model yielded R2 - and p- values of approximately 0.47 and 1.2E-10, respectively. Many SVOCs are also used as additives (e.g. plasticizers, antioxidants, lubricants) in plastic food pac

Proteochemometric model for predicting the inhibition of penicillin-binding proteins

NASA Astrophysics Data System (ADS)

Nabu, Sunanta; Nantasenamat, Chanin; Owasirikul, Wiwat; Lawung, Ratana; Isarankura-Na-Ayudhya, Chartchalerm; Lapins, Maris; Wikberg, Jarl E. S.; Prachayasittikul, Virapong

2015-02-01

Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing β-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic β-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability ( R 2 = 0.91, Q 2 = 0.77, Q Ext 2 = 0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future.

LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches

PubMed Central

2014-01-01

Background Laccases (E.C. 1.10.3.2) are multi-copper oxidases that have gained importance in many industries such as biofuels, pulp production, textile dye bleaching, bioremediation, and food production. Their usefulness stems from the ability to act on a diverse range of phenolic compounds such as o-/p-quinols, aminophenols, polyphenols, polyamines, aryl diamines, and aromatic thiols. Despite acting on a wide range of compounds as a family, individual Laccases often exhibit distinctive and varied substrate ranges. This is likely due to Laccases involvement in many metabolic roles across diverse taxa. Classification systems for multi-copper oxidases have been developed using multiple sequence alignments, however, these systems seem to largely follow species taxonomy rather than substrate ranges, enzyme properties, or specific function. It has been suggested that the roles and substrates of various Laccases are related to their optimal pH. This is consistent with the observation that fungal Laccases usually prefer acidic conditions, whereas plant and bacterial Laccases prefer basic conditions. Based on these observations, we hypothesize that a descriptor-based unsupervised learning system could generate homology independent classification system for better describing the functional properties of Laccases. Results In this study, we first utilized unsupervised learning approach to develop a novel homology independent Laccase classification system. From the descriptors considered, physicochemical properties showed the best performance. Physicochemical properties divided the Laccases into twelve subtypes. Analysis of the clusters using a t-test revealed that the majority of the physicochemical descriptors had statistically significant differences between the classes. Feature selection identified the most important features as negatively charges residues, the peptide isoelectric point, and acidic or amidic residues. Secondly, to allow for classification of new Laccases, a supervised learning system was developed from the clusters. The models showed high performance with an overall accuracy of 99.03%, error of 0.49%, MCC of 0.9367, precision of 94.20%, sensitivity of 94.20%, and specificity of 99.47% in a 5-fold cross-validation test. In an independent test, our models still provide a high accuracy of 97.98%, error rate of 1.02%, MCC of 0.8678, precision of 87.88%, sensitivity of 87.88% and specificity of 98.90%. Conclusion This study provides a useful classification system for better understanding of Laccases from their physicochemical properties perspective. We also developed a publically available web tool for the characterization of Laccase protein sequences (http://lacsubpred.bioinfo.ucr.edu/). Finally, the programs used in the study are made available for researchers interested in applying the system to other enzyme classes (https://github.com/tweirick/SubClPred). PMID:25350584

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

NASA Astrophysics Data System (ADS)

Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

2015-03-01

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

Physicochemical properties of dietary phytochemicals can predict their passive absorption in the human small intestine.

PubMed

Selby-Pham, Sophie N B; Miller, Rosalind B; Howell, Kate; Dunshea, Frank; Bennett, Louise E

2017-05-16

A diet high in phytochemical-rich plant foods is associated with reducing the risk of chronic diseases such as cardiovascular and neurodegenerative diseases, obesity, diabetes and cancer. Oxidative stress and inflammation (OSI) is the common component underlying these chronic diseases. Whilst the positive health effects of phytochemicals and their metabolites have been demonstrated to regulate OSI, the timing and absorption for best effect is not well understood. We developed a model to predict the time to achieve maximal plasma concentration (T max ) of phytochemicals in fruits and vegetables. We used a training dataset containing 67 dietary phytochemicals from 31 clinical studies to develop the model and validated the model using three independent datasets comprising a total of 108 dietary phytochemicals and 98 pharmaceutical compounds. The developed model based on dietary intake forms and the physicochemical properties lipophilicity and molecular mass accurately predicts T max of dietary phytochemicals and pharmaceutical compounds over a broad range of chemical classes. This is the first direct model to predict T max of dietary phytochemicals in the human body. The model informs the clinical dosing frequency for optimising uptake and sustained presence of dietary phytochemicals in circulation, to maximise their bio-efficacy for positively affect human health and managing OSI in chronic diseases.

Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins.

PubMed Central

Mocz, G.

1995-01-01

Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields approximately 73% matching for correctly predicted and correctly rejected residues with approximately 60% overall success rate for the correctly recognized ones in three folding states: alpha-helix, beta-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain approximately 95% of prediction results. hydrogen bonding and hydrophobicity induces do not yet enable clear clustering and prediction. PMID:7549882

The Rule of Five for Non-Oral Routes of Drug Delivery: Ophthalmic, Inhalation and Transdermal

PubMed Central

Choy, Young Bin; Prausnitz, Mark R.

2011-01-01

The Rule of Five predicts suitability of drug candidates, but was developed primarily using orally administered drugs. Here, we test whether the Rule of Five predicts drugs for delivery via non-oral routes, specifically ophthalmic, inhalation and transdermal. We assessed 111 drugs approved by FDA for those routes of administration and found that >98% of current non-oral drugs have physicochemical properties within the limits of the Rule of Five. However, given the inherent bias in the dataset, this analysis was not able to assess whether drugs with properties outside those limits are poor candidates. Indeed, further analysis indicates that drugs well outside the Rule of Five limits, including hydrophilic macromolecules, can be delivered by inhalation. In contrast, drugs currently administered across skin fall within more stringent limits than predicted by the Rule of Five, but new transdermal delivery technologies may make these constraints obsolete by dramatically increasing skin permeability. The Rule of Five does appear to apply well to ophthalmic delivery. We conclude that although current non-oral drugs mostly have physicochemical properties within the Rule of Five thresholds, the Rule of Five should not be used to predict non-oral drug candidates, especially for inhalation and transdermal routes. PMID:20967491

Physicochemical Approach to Determine the Mechanism for Acid-Base Disorders in 793 Hospitalized Foals.

PubMed

Gomez, D E; Biermann, N M; Sanchez, L C

2015-01-01

The quantitative effect of strong electrolytes, unmeasured strong anions (UAs), pCO2, and plasma protein concentrations in determining plasma pH can be demonstrated using the physicochemical approach. Plasma anion gap (AG) and strong ion gap (SIG) are used to assess UAs in different species. Strong ions are a major factor influencing changes in plasma pH of hospitalized foals. AG and SIG accurately predict severe hyper-L-lactatemia ([L-lac(-)] > 7 mmol/L). Seven hundred and ninety three hospitalized foals < 7 days old. Retrospective study. The relationship between measured pH and physicochemical variables, and the relationship between plasma [L-lac(-)] and AG and SIG, were determined using regression analyses. Optimal AG and SIG cut points to predict hyper-L-lactatemia were identified using an ROC curve analysis. Combined, the measured strong ion difference and SIG accounted for 54-69% of the changes in the measured arterial pH of hospitalized foals. AG and SIG were significantly associated with plasma [L-lac(-)] (P < .0001). The receiver operator characteristics (ROC) AUC of AG and SIG for prediction of severe hyper-L-lactatemia were 0.89 (95%CI, 0.8-0.95; P < .0001) and 0.90 (95%CI, 0.81-0.96; P < .0001), respectively. Severe hyper-L-lactatemia was best predicted by AG > 27 mmol/L (sensitivity 80%, 95%CI, 56-94, specificity 85%, 95%CI, 73-93; P < .0001) and SIG <-15 mmol/L (sensitivity 90%, 95%CI, 68-98; specificity 80%; 95%CI, 68-90; P < .0001). Altered concentrations of strong ions (Na(+), K(+), Cl(-)) and UAs were the primary cause of acidemia of hospitalized foals. AG and SIG were good predictors of hyper-L-lactatemia and could be used as surrogate tests. Copyright © 2015 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Origins of life and biochemistry under high-pressure conditions.

PubMed

Daniel, Isabelle; Oger, Philippe; Winter, Roland

2006-10-01

Life on Earth can be traced back to as far as 3.8 billion years (Ga) ago. The catastrophic meteoritic bombardment ended between 4.2 and 3.9 Ga ago. Therefore, if life emerged, and we know it did, it must have emerged from nothingness in less than 400 million years. The most recent scenarios of Earth accretion predict some very unstable physico-chemical conditions at the surface of Earth, which, in such a short time period, would impede the emergence of life from a proto-biotic soup. A possible alternative would be that life originated in the depth of the proto-ocean of the Hadean Earth, under high hydrostatic pressure. The large body of water would filter harmful radiation and buffer physico-chemical variations, and therefore would provide a more stable radiation-free environment for pre-biotic chemistry. After a short introduction to Earth history, the current tutorial review presents biological and physico-chemical arguments in support of high-pressure origin for life on Earth.

Effect of banana pulp and peel flour on physicochemical properties and in vitro starch digestibility of yellow alkaline noodles.

PubMed

Ramli, Saifullah; Alkarkhi, Abbas F M; Shin Yong, Yeoh; Min-Tze, Liong; Easa, Azhar Mat

2009-01-01

The present study describes the utilization of banana--Cavendish (Musa acuminata L., cv cavendshii) and Dream (Musa acuminata colla. AAA, cv 'Berangan')--pulp and peel flours as functional ingredients in yellow alkaline noodles. Noodles were prepared by partial substitution of wheat flour with ripe banana pulp or peel flours. In most cases, the starch hydrolysis index, predicted glycaemic index (pGI) and physicochemical properties of cooked noodles were affected by banana flour addition. In general, the pGI values of cooked noodles were in the order; banana peel noodles < banana pulp noodles < control noodles. Since the peel flour was higher in total dietary fibre but lower in resistant starch contents than the pulp flour, the low pGI of banana peel noodles was mainly due to its high dietary fibre content. In conclusion, banana pulp and peel flour could be useful for controlling starch hydrolysis of yellow noodles, even though some physicochemical properties of the noodles were altered.

Physicochemical Drivers of Microbial Community Structure in Sediments of Lake Hazen, Nunavut, Canada.

PubMed

Ruuskanen, Matti O; St Pierre, Kyra A; St Louis, Vincent L; Aris-Brosou, Stéphane; Poulain, Alexandre J

2018-01-01

The Arctic is undergoing rapid environmental change, potentially affecting the physicochemical constraints of microbial communities that play a large role in both carbon and nutrient cycling in lacustrine environments. However, the microbial communities in such Arctic environments have seldom been studied, and the drivers of their composition are poorly characterized. To address these gaps, we surveyed the biologically active surface sediments in Lake Hazen, the largest lake by volume north of the Arctic Circle, and a small lake and shoreline pond in its watershed. High-throughput amplicon sequencing of the 16S rRNA gene uncovered a community dominated by Proteobacteria, Bacteroidetes, and Chloroflexi, similar to those found in other cold and oligotrophic lake sediments. We also show that the microbial community structure in this Arctic polar desert is shaped by pH and redox gradients. This study lays the groundwork for predicting how sediment microbial communities in the Arctic could respond as climate change proceeds to alter their physicochemical constraints.

Insights into the physico-chemical evolution of pyrogenic organic carbon emissions from biomass burning using coupled Lagrangian-Eulerian simulations

NASA Astrophysics Data System (ADS)

Suciu, L. G.; Griffin, R. J.; Masiello, C. A.

2017-12-01

Wildfires and prescribed burning are important sources of particulate and gaseous pyrogenic organic carbon (PyOC) emissions to the atmosphere. These emissions impact atmospheric chemistry, air quality and climate, but the spatial and temporal variabilities of these impacts are poorly understood, primarily because small and fresh fire plumes are not well predicted by three-dimensional Eulerian chemical transport models due to their coarser grid size. Generally, this results in underestimation of downwind deposition of PyOC, hydroxyl radical reactivity, secondary organic aerosol formation and ozone (O3) production. However, such models are very good for simulation of multiple atmospheric processes that could affect the lifetimes of PyOC emissions over large spatiotemporal scales. Finer resolution models, such as Lagrangian reactive plumes models (or plume-in-grid), could be used to trace fresh emissions at the sub-grid level of the Eulerian model. Moreover, Lagrangian plume models need background chemistry predicted by the Eulerian models to accurately simulate the interactions of the plume material with the background air during plume aging. Therefore, by coupling the two models, the physico-chemical evolution of the biomass burning plumes can be tracked from local to regional scales. In this study, we focus on the physico-chemical changes of PyOC emissions from sub-grid to grid levels using an existing chemical mechanism. We hypothesize that finer scale Lagrangian-Eulerian simulations of several prescribed burns in the U.S. will allow more accurate downwind predictions (validated by airborne observations from smoke plumes) of PyOC emissions (i.e., submicron particulate matter, organic aerosols, refractory black carbon) as well as O3 and other trace gases. Simulation results could be used to optimize the implementation of additional PyOC speciation in the existing chemical mechanism.

PatchSurfers: Two methods for local molecular property-based binding ligand prediction.

PubMed

Shin, Woong-Hee; Bures, Mark Gregory; Kihara, Daisuke

2016-01-15

Protein function prediction is an active area of research in computational biology. Function prediction can help biologists make hypotheses for characterization of genes and help interpret biological assays, and thus is a productive area for collaboration between experimental and computational biologists. Among various function prediction methods, predicting binding ligand molecules for a target protein is an important class because ligand binding events for a protein are usually closely intertwined with the proteins' biological function, and also because predicted binding ligands can often be directly tested by biochemical assays. Binding ligand prediction methods can be classified into two types: those which are based on protein-protein (or pocket-pocket) comparison, and those that compare a target pocket directly to ligands. Recently, our group proposed two computational binding ligand prediction methods, Patch-Surfer, which is a pocket-pocket comparison method, and PL-PatchSurfer, which compares a pocket to ligand molecules. The two programs apply surface patch-based descriptions to calculate similarity or complementarity between molecules. A surface patch is characterized by physicochemical properties such as shape, hydrophobicity, and electrostatic potentials. These properties on the surface are represented using three-dimensional Zernike descriptors (3DZD), which are based on a series expansion of a 3 dimensional function. Utilizing 3DZD for describing the physicochemical properties has two main advantages: (1) rotational invariance and (2) fast comparison. Here, we introduce Patch-Surfer and PL-PatchSurfer with an emphasis on PL-PatchSurfer, which is more recently developed. Illustrative examples of PL-PatchSurfer performance on binding ligand prediction as well as virtual drug screening are also provided. Copyright © 2015 Elsevier Inc. All rights reserved.

Seed characteristics and physicochemical properties of powders of 25 edible dry bean varieties.

PubMed

Cappa, Carola; Kelly, James D; Ng, Perry K W

2018-07-01

Information on the physicochemical variability in dry bean seeds from different varieties grown over distinct crop years is lacking. This study was designed to investigate the relationship between the environment and the seed characteristics of 25 edible dry bean varieties and to expand the knowledge on their proximate composition, starch digestibility, solvent retention capacity, and pasting and thermal properties. The impact of bean genotype (25 varieties), growing environment (two crop years), and powder particle size (≤0.5 mm, ≤1.0 mm) was investigated. Statistical differences (P > 0.05) in seed characteristics and in starch, amylose and protein contents were found among the 25 varieties. Unique pasting and thermal properties were observed, and genotype and particle size greatly affected these properties. The accumulated information can be used in breeding programs to select bean lines possessing unique properties for food ingredients while increasing the market value of the crop and enhancing human health. Copyright © 2018 Elsevier Ltd. All rights reserved.

Physicochemical mechanisms of plasma-liquid interactions within plasma channels in liquid

NASA Astrophysics Data System (ADS)

Franclemont, Joshua; Fan, Xiangru; Mededovic Thagard, Selma

2015-10-01

The goal of this study is to advance the fundamental understanding of the physical and chemical mechanisms by which excited radical species produced by electrical plasmas directly in water, OH radicals especially, induce chemical changes in aqueous organic compounds and to exploit this for the development and optimization of drinking and wastewater plasma-based treatment systems. To achieve this goal, this study measured and correlated the production rate of hydrogen peroxide (H2O2) with physicochemical properties of 11 organic compounds. The observed individual correlations between the investigated physicochemical properties and the resulting H2O2 concentrations were used to develop an equation that would allow predicting the measured H2O2 concentration from physicochemical properties of a compound. Results reveal that the production rate of H2O2 directly depends on the surface tension of the solution and compounds’ bulk liquid concentration, hydrophobicity (K ow value), and molecular volume. Other properties such as vapor pressure, Henry’s constant, enthalpy of vaporization, ionization energy, electron affinity, and molecular dipole moment do not affect the H2O2 chemistry. K ow value and surface tension of the solution determine the compound’s concentration at the plasma interface. Once at the interface, the molecular volume determines the rate at which the molecule will react with OH radicals.

Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 2. Solubility in 1-octanol.

PubMed

Raevsky, O A; Perlovich, G L; Schaper, K-J

2007-01-01

On the basis of octanol solubility data (log S(o)) for 218 structurally diverse solid chemicals it was shown that the exclusive consideration of melting points did not provide satisfactory results in the quantitative prediction of this parameter (s = 0.92). The application of HYBOT physicochemical descriptors separately (s = 0.94) and together with melting points (s = 0.70) in the framework of a common regression model also was not successful, although contributions of volume-related and H-bond terms to solubility in octanol were identified. It was proposed that the main reason for such behaviour was the different crystal lattice interaction of different classes of chemicals. Successful calculations of the solubility in octanol of chemicals of interest were performed on the basis of the experimental solubility of structurally/physicochemically/numerically similar nearest neighbours with consideration of their difference in physicochemical parameters (molecular polarisability, H-bond acceptor and donor factors (s = 0.66)) and of these descriptors together with melting point differences (s = 0.38). Good results were obtained for all compounds having nearest neighbours with sufficient similarity, expressed by Tanimoto indexes, and by distances in the scaled 3D descriptor space. Obviously the success of this approach depends on the size of the database.

Modeling Zebrafish Developmental Toxicity using a Concurrent In vitro Assay Battery (SOT)

EPA Science Inventory

We describe the development of computational models that predict activity in a repeat-dose zebrafish embryo developmental toxicity assay using a combination of physico-chemical parameters and in vitro (human) assay measurements. The data set covered 986 chemicals including pestic...

TECHNICAL CHALLENGES ASSOCIATED WITH ASSESSING THE IN VITRO PULMONARY TOXICITY OF CARBON NANOTUBES

EPA Science Inventory

Nanotechnology continues to produce a large number of diverse engineered nanomaterials (NMs) with novel physicochemical properties for a variety of applications. Test methods that accurately assess/predict the toxicity of NMs are critically needed and it is unclear whether curren...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takeshita, Kenji

A mathematical model to predict the extraction behavior of metal ion between a polymer gel and an aqueous solution was proposed. It consists of the Flory-Huggins formula for evaluating thermodynamically the physico-chemical properties of polymer gel, the modified Stokes-Einstein equation to evaluate the mass transfer rate of metal ion into polymer gel and the equation to evaluate the extraction equilibrium. The extraction of lanthanide elements, Nd(III), Sm(III) and Gd(III), from an aqueous solution containing nitrate ion was carried out by the use of SDB (styrene-divinylbenzene copolymer) gel swollen with a bidentate organophosphorus compound, CMP (dihexyl-N,N-diethylcarbamoylmethylpohosphonate). The binary extraction and themore » effect of the crosslinking degree of SDB gel on the extraction rate were examined. These experimental results were in agreement with the predictions calculated by the proposed model. It was confirmed that the extraction behavior of lanthanide ions into the SDB gel was predicted accurately, when the physico-chemical properties of SDB gel, such as the affinity between SDB and CMP ({chi}) and the crosslinking degree ({nu}{sub e}), and a coefficient defined in the modified Stokes-Einstein equation (K{sub 0}) were known. This model is available as a tool to design an extraction chromatographic process using polymer gel.« less

Chemometric analysis of correlations between electronic absorption characteristics and structural and/or physicochemical parameters for ampholytic substances of biological and pharmaceutical relevance.

PubMed

Judycka-Proma, U; Bober, L; Gajewicz, A; Puzyn, T; Błażejowski, J

2015-03-05

Forty ampholytic compounds of biological and pharmaceutical relevance were subjected to chemometric analysis based on unsupervised and supervised learning algorithms. This enabled relations to be found between empirical spectral characteristics derived from electronic absorption data and structural and physicochemical parameters predicted by quantum chemistry methods or phenomenological relationships based on additivity rules. It was found that the energies of long wavelength absorption bands are correlated through multiparametric linear relationships with parameters reflecting the bulkiness features of the absorbing molecules as well as their nucleophilicity and electrophilicity. These dependences enable the quantitative analysis of spectral features of the compounds, as well as a comparison of their similarities and certain pharmaceutical and biological features. Three QSPR models to predict the energies of long-wavelength absorption in buffers with pH=2.5 and pH=7.0, as well as in methanol, were developed and validated in this study. These models can be further used to predict the long-wavelength absorption energies of untested substances (if they are structurally similar to the training compounds). Copyright © 2014 Elsevier B.V. All rights reserved.

Physicochemical properties of honey from Marche, Central Italy: classification of unifloral and multifloral honeys by multivariate analysis.

PubMed

Truzzi, Cristina; Illuminati, Silvia; Annibaldia, Anna; Finale, Carolina; Rossetti, Monica; Scarponi, Giuseppe

2014-11-01

The purpose of this study was the physicochemical characterization and classification of Italian honey from Marche Region with a chemometric approach. A total of 135 honeys of different botanical origins [acacia (Robinia pseudoacacia L.), chestnut (Castanea sativa), coriander (Coriandrum sativum L.), lime (Tilia spp.), sunflower (Helianthus annuus L.), Metcalfa honeydew and multifloral honey] were considered. The average results of electrical conductivity (0.14-1.45 mS cm(-1)), pH (3.89-5.42), free acidity (10.9-39.0 meq(NaOH) kg(-1)), lactones (2.4-4.5 meq(NaOH) kg(-1)), total acidity (14.5-40.9 meq(NaOH) kg(-1)), proline (229-665 mg kg(-1)) and 5-(hydroxy-methyl)-2-furaldehyde (0.6-3.9 mg kg(-1)) content show wide variability among the analysed honey types, with statistically significant differences between the different honey types. Pattern recognition methods such as principal component analysis and discriminant analysis were performed in order to find a relationship between variables and types of honey and to classify honey on the basis of its physicochemical properties. The variables of electrical conductivity, acidity (free, lactones), pH and proline content exhibited higher discriminant power and provided enough information for the classification and distinction of unifloral honey types, but not for the classification of multifloral honey (100% and 85% of samples correctly classified, respectively).

A study of the stabilities, microstructures and fuel characteristics of tri-fuel (diesel-biodiesel-ethanol) using various fuel preparation methods

NASA Astrophysics Data System (ADS)

Lee, K. H.; Mukhtar, N. A. M.; Yohaness Hagos, Ftwi; Noor, M. M.

2017-10-01

In this study, the work was carried out to investigate the effects of ethanol proportions on the stabilities and physicochemical characteristics of tri-fuel (Diesel-Biodiesel-Ethanol). For the first time, tri-fuel emulsions and blended were compared side by side. The experiment was done with composition having 5%, 10%, 15%, 20% and 25 % of ethanol with fixed 10% of biodiesel from palm oil origin on a volume basis into diesel. The results indicated that the phase stabilities of the emulsified fuels were higher compared to the blended fuels. In addition, tri-fuel composition with higher proportion of ethanol were found unstable with high tendency to form layer separation. It was found that tri-fuel emulsion with 5% ethanol content (D85B10E5) was of the best in stability with little separation. Furthermore, tri-fuel with lowest ethanol proportion indicated convincing physicochemical characteristics compared to others. Physicochemical characteristics of tri-fuel blending yield almost similar results to tri-fuel emulsion but degrading as more proportion ethanol content added. Emulsion category had cloudy look but on temporarily basis. Under the microscope, tri-fuel emulsion and blending droplet were similar for its active moving about micro-bubble but distinct in term of detection of collision, average disperse micro-bubble size, the spread and organization of the microstructure.

Physicochemical characterization of discrete weapons grade plutonium metal particles originating from the 1960 BOMARC incident

NASA Astrophysics Data System (ADS)

Bowen, James M.

The goal of this research was to investigate the physicochemical properties of weapons grade plutonium particles originating from the 1960 BOMARC incident for the purpose of predicting their fate in the environment and to address radiation protection and nuclear security concerns. Methods were developed to locate and isolate the particles in order to characterize them. Physical, chemical, and radiological characterization was performed using a variety of techniques. And finally, the particles were subjected to a sequential extraction procedure, a series of increasingly aggressive reagents, to simulate an accelerated environmental exposure. A link between the morphology of the particles and their partitioning amongst environmental mechanisms was established.

Spatiotemporal Variation of Arctic Nearshore Fish Communities in Barrow, AK

NASA Astrophysics Data System (ADS)

Boswell, K. M.; Barton, M. B.; Lemoine, N. P.; Heintz, R.; Vollenweider, J.; Norcross, B.; Sousa, L.

2016-02-01

Climate change, oil and gas development, and increased transportation opportunities associated with retreating sea ice cover are likely to affect the processes underlying community development. Unfortunately, there is a paucity of information that prohibits establishing a baseline from which to examine biological and ecological changes. To address these concerns, we developed an intensive field sampling program using weekly beach seining for the six weeks following land-fast ice break-up during the summers of 2013-2015 (183 beach seine hauls totaling 37,303 fish) in three distinct water masses near Pt. Barrow, Alaska to examine how fish communities develop in the Arctic nearshore. Preliminary analyses indicate that inter-annual variability in temperature and salinity influence species composition observed in late summer, but it is unclear which factors operate on smaller temporal scales. We applied multivariate variance partitioning to quantify variation in community structure on multiple spatial and temporal scales during the summer season and identified several physicochemical parameters as important spatiotemporal drivers in structuring nearshore fish communities. Understanding how these drivers affect nearshore communities on the seasonal scale is an integral step to predict how these ecologically important ecosystems may shift in the face of Arctic climate change and continued development.

Millions of Boreal Shield Lakes can be used to Probe Archaean Ocean Biogeochemistry

NASA Astrophysics Data System (ADS)

Schiff, S. L.; Tsuji, J. M.; Wu, L.; Venkiteswaran, J. J.; Molot, L. A.; Elgood, R. J.; Paterson, M. J.; Neufeld, J. D.

2017-04-01

Life originated in Archaean oceans, almost 4 billion years ago, in the absence of oxygen and the presence of high dissolved iron concentrations. Early Earth oxidation is marked globally by extensive banded iron formations but the contributing processes and timing remain controversial. Very few aquatic habitats have been discovered that match key physico-chemical parameters of the early Archaean Ocean. All previous whole ecosystem Archaean analogue studies have been confined to rare, low sulfur, and permanently stratified lakes. Here we provide first evidence that millions of Boreal Shield lakes with natural anoxia offer the opportunity to constrain biogeochemical and microbiological aspects of early Archaean life. Specifically, we combined novel isotopic signatures and nucleic acid sequence data to examine processes in the anoxic zone of stratified boreal lakes that are naturally low in sulfur and rich in ferrous iron, hallmark characteristics predicted for the Archaean Ocean. Anoxygenic photosynthesis was prominent in total water column biogeochemistry, marked by distinctive patterns in natural abundance isotopes of carbon, nitrogen, and iron. These processes are robust, returning reproducibly after water column re-oxygenation following lake turnover. Evidence of coupled iron oxidation, iron reduction, and methane oxidation affect current paradigms of both early Earth and modern aquatic ecosystems.

Comparative genomics reveals adaptations of a halotolerant thaumarchaeon in the interfaces of brine pools in the Red Sea.

PubMed

Kamanda Ngugi, David; Blom, Jochen; Alam, Intikhab; Rashid, Mamoon; Ba-Alawi, Wail; Zhang, Guishan; Hikmawan, Tyas; Guan, Yue; Antunes, Andre; Siam, Rania; El Dorry, Hamza; Bajic, Vladimir; Stingl, Ulrich

2015-02-01

The bottom of the Red Sea harbors over 25 deep hypersaline anoxic basins that are geochemically distinct and characterized by vertical gradients of extreme physicochemical conditions. Because of strong changes in density, particulate and microbial debris get entrapped in the brine-seawater interface (BSI), resulting in increased dissolved organic carbon, reduced dissolved oxygen toward the brines and enhanced microbial activities in the BSI. These features coupled with the deep-sea prevalence of ammonia-oxidizing archaea (AOA) in the global ocean make the BSI a suitable environment for studying the osmotic adaptations and ecology of these important players in the marine nitrogen cycle. Using phylogenomic-based approaches, we show that the local archaeal community of five different BSI habitats (with up to 18.2% salinity) is composed mostly of a single, highly abundant Nitrosopumilus-like phylotype that is phylogenetically distinct from the bathypelagic thaumarchaea; ammonia-oxidizing bacteria were absent. The composite genome of this novel Nitrosopumilus-like subpopulation (RSA3) co-assembled from multiple single-cell amplified genomes (SAGs) from one such BSI habitat further revealed that it shares ∼54% of its predicted genomic inventory with sequenced Nitrosopumilus species. RSA3 also carries several, albeit variable gene sets that further illuminate the phylogenetic diversity and metabolic plasticity of this genus. Specifically, it encodes for a putative proline-glutamate 'switch' with a potential role in osmotolerance and indirect impact on carbon and energy flows. Metagenomic fragment recruitment analyses against the composite RSA3 genome, Nitrosopumilus maritimus, and SAGs of mesopelagic thaumarchaea also reiterate the divergence of the BSI genotypes from other AOA.

Differential contributions of archaeal ammonia oxidizer ecotypes to nitrification in coastal surface waters

PubMed Central

Smith, Jason M; Casciotti, Karen L; Chavez, Francisco P; Francis, Christopher A

2014-01-01

The occurrence of nitrification in the oceanic water column has implications extending from local effects on the structure and activity of phytoplankton communities to broader impacts on the speciation of nitrogenous nutrients and production of nitrous oxide. The ammonia-oxidizing archaea, responsible for carrying out the majority of nitrification in the sea, are present in the marine water column as two taxonomically distinct groups. Water column group A (WCA) organisms are detected at all depths, whereas Water column group B (WCB) are present primarily below the photic zone. An open question in marine biogeochemistry is whether the taxonomic definition of WCA and WCB organisms and their observed distributions correspond to distinct ecological and biogeochemical niches. We used the natural gradients in physicochemical and biological properties that upwelling establishes in surface waters to study their roles in nitrification, and how their activity—ascertained from quantification of ecotype-specific ammonia monooxygenase (amoA) genes and transcripts—varies in response to environmental fluctuations. Our results indicate a role for both ecotypes in nitrification in Monterey Bay surface waters. However, their respective contributions vary, due to their different sensitivities to surface water conditions. WCA organisms exhibited a remarkably consistent level of activity and their contribution to nitrification appears to be related to community size. WCB activity was less consistent and primarily constrained to colder, high nutrient and low chlorophyll waters. Overall, the results of our characterization yielded a strong, potentially predictive, relationship between archaeal amoA gene abundance and the rate of nitrification. PMID:24553472

Molecular modeling of polymers 16. Gaseous diffusion in polymers: a quantitative structure-property relationship (QSPR) analysis.

PubMed

Patel, H C; Tokarski, J S; Hopfinger, A J

1997-10-01

The purpose of this study was to identify the key physicochemical molecular properties of polymeric materials responsible for gaseous diffusion in the polymers. Quantitative structure-property relationships, QSPRs were constructed using a genetic algorithm on a training set of 16 polymers for which CO2, N2, O2 diffusion constants were measured. Nine physicochemical properties of each of the polymers were used in the trial basis set for QSPR model construction. The linear cross-correlation matrices were constructed and investigated for colinearity among the members of the training sets. Common water diffusion measures for a limited training set of six polymers was used to construct a "semi-QSPR" model. The bulk modulus of the polymer was overwhelmingly found to be the dominant physicochemical polymer property that governs CO2, N2 and O2 diffusion. Some secondary physicochemical properties controlling diffusion, including conformational entropy, were also identified as correlation descriptors. Very significant QSPR diffusion models were constructed for all three gases. Cohesive energy was identified as the main correlation physicochemical property with aqueous diffusion measures. The dominant role of polymer bulk modulus on gaseous diffusion makes it difficult to develop criteria for selective transport of gases through polymers. Moreover, high bulk moduli are predicted to be necessary for effective gas barrier materials. This property requirement may limit the processing and packaging features of the material. Aqueous diffusion in polymers may occur by a different mechanism than gaseous diffusion since bulk modulus does not correlate with aqueous diffusion, but rather cohesive energy of the polymer.

Designing of peptides with desired half-life in intestine-like environment.

PubMed

Sharma, Arun; Singla, Deepak; Rashid, Mamoon; Raghava, Gajendra Pal Singh

2014-08-20

In past, a number of peptides have been reported to possess highly diverse properties ranging from cell penetrating, tumor homing, anticancer, anti-hypertensive, antiviral to antimicrobials. Owing to their excellent specificity, low-toxicity, rich chemical diversity and availability from natural sources, FDA has successfully approved a number of peptide-based drugs and several are in various stages of drug development. Though peptides are proven good drug candidates, their usage is still hindered mainly because of their high susceptibility towards proteases degradation. We have developed an in silico method to predict the half-life of peptides in intestine-like environment and to design better peptides having optimized physicochemical properties and half-life. In this study, we have used 10mer (HL10) and 16mer (HL16) peptides dataset to develop prediction models for peptide half-life in intestine-like environment. First, SVM based models were developed on HL10 dataset which achieved maximum correlation R/R2 of 0.57/0.32, 0.68/0.46, and 0.69/0.47 using amino acid, dipeptide and tripeptide composition, respectively. Secondly, models developed on HL16 dataset showed maximum R/R2 of 0.91/0.82, 0.90/0.39, and 0.90/0.31 using amino acid, dipeptide and tripeptide composition, respectively. Furthermore, models that were developed on selected features, achieved a correlation (R) of 0.70 and 0.98 on HL10 and HL16 dataset, respectively. Preliminary analysis suggests the role of charged residue and amino acid size in peptide half-life/stability. Based on above models, we have developed a web server named HLP (Half Life Prediction), for predicting and designing peptides with desired half-life. The web server provides three facilities; i) half-life prediction, ii) physicochemical properties calculation and iii) designing mutant peptides. In summary, this study describes a web server 'HLP' that has been developed for assisting scientific community for predicting intestinal half-life of peptides and to design mutant peptides with better half-life and physicochemical properties. HLP models were trained using a dataset of peptides whose half-lives have been determined experimentally in crude intestinal proteases preparation. Thus, HLP server will help in designing peptides possessing the potential to be administered via oral route (http://www.imtech.res.in/raghava/hlp/).

WRF-TMH: predicting transmembrane helix by fusing composition index and physicochemical properties of amino acids.

PubMed

Hayat, Maqsood; Khan, Asifullah

2013-05-01

Membrane protein is the prime constituent of a cell, which performs a role of mediator between intra and extracellular processes. The prediction of transmembrane (TM) helix and its topology provides essential information regarding the function and structure of membrane proteins. However, prediction of TM helix and its topology is a challenging issue in bioinformatics and computational biology due to experimental complexities and lack of its established structures. Therefore, the location and orientation of TM helix segments are predicted from topogenic sequences. In this regard, we propose WRF-TMH model for effectively predicting TM helix segments. In this model, information is extracted from membrane protein sequences using compositional index and physicochemical properties. The redundant and irrelevant features are eliminated through singular value decomposition. The selected features provided by these feature extraction strategies are then fused to develop a hybrid model. Weighted random forest is adopted as a classification approach. We have used two benchmark datasets including low and high-resolution datasets. tenfold cross validation is employed to assess the performance of WRF-TMH model at different levels including per protein, per segment, and per residue. The success rates of WRF-TMH model are quite promising and are the best reported so far on the same datasets. It is observed that WRF-TMH model might play a substantial role, and will provide essential information for further structural and functional studies on membrane proteins. The accompanied web predictor is accessible at http://111.68.99.218/WRF-TMH/ .

Toward a systematic exploration of nano-bio interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bai, Xue; Liu, Fang; Liu, Yin

Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships between inherent physicochemical properties of these materials and their interactions with, and effects on, biological systems. Data driven artificial intelligence methods such as machine learning algorithms have proven highly effective in generating models with good predictivity and some degree of interpretability. They can provide a viable method of reducing or eliminating animal testing. However, careful experimental design with the modelling of the results in mind is a proven andmore » efficient way of exploring large materials spaces. This approach, coupled with high speed automated experimental synthesis and characterization technologies now appearing, is the fastest route to developing models that regulatory bodies may find useful. We advocate greatly increased focus on systematic modification of physicochemical properties of nanoparticles combined with comprehensive biological evaluation and computational analysis. This is essential to obtain better mechanistic understanding of nano-bio interactions, and to derive quantitatively predictive and robust models for the properties of nanomaterials that have useful domains of applicability. - Highlights: • Nanomaterials studies make non-systematic alterations to nanoparticle properties. • Vast nanomaterials property spaces require systematic studies of nano-bio interactions. • Experimental design and modelling are efficient ways of exploring materials spaces. • We advocate systematic modification and computational analysis to probe nano-bio interactions.« less

Classification of cassava starch films by physicochemical properties and water vapor permeability quantification by FTIR and PLS.

PubMed

Henrique, C M; Teófilo, R F; Sabino, L; Ferreira, M M C; Cereda, M P

2007-05-01

Cassava starches are widely used in the production of biodegradable films, but their resistance to humidity migration is very low. In this work, commercial cassava starch films were studied and classified according to their physicochemical properties. A nondestructive method for water vapor permeability determination, which combines with infrared spectroscopy and multivariate calibration, is also presented. The following commercial cassava starches were studied: pregelatinized (amidomax 3550), carboxymethylated starch (CMA) of low and high viscosities, and esterified starches. To make the films, 2 different starch concentrations were evaluated, consisting of water suspensions with 3% and 5% starch. The filmogenic solutions were dried and characterized for their thickness, grammage, water vapor permeability, water activity, tensile strength (deformation force), water solubility, and puncture strength (deformation). The minimum thicknesses were 0.5 to 0.6 mm in pregelatinized starch films. The results were treated by means of the following chemometric methods: principal component analysis (PCA) and partial least squares (PLS) regression. PCA analysis on the physicochemical properties of the films showed that the differences in concentration of the dried material (3% and 5% starch) and also in the type of starch modification were mainly related to the following properties: permeability, solubility, and thickness. IR spectra collected in the region of 4000 to 600 cm(-1) were used to build a PLS model with good predictive power for water vapor permeability determination, with mean relative errors of 10.0% for cross-validation and 7.8% for the prediction set.

Classification and characterization of Japanese consumers' beef preferences by external preference mapping.

PubMed

Sasaki, Keisuke; Ooi, Motoki; Nagura, Naoto; Motoyama, Michiyo; Narita, Takumi; Oe, Mika; Nakajima, Ikuyo; Hagi, Tatsuro; Ojima, Koichi; Kobayashi, Miho; Nomura, Masaru; Muroya, Susumu; Hayashi, Takeshi; Akama, Kyoko; Fujikawa, Akira; Hokiyama, Hironao; Kobayashi, Kuniyuki; Nishimura, Takanori

2017-08-01

Over the past few decades, beef producers in Japan have improved marbling in their beef products. It was recently reported that marbling is not well correlated with palatability as rated by Japanese consumers. This study sought to identify the consumer segments in Japan that prefer sensory characteristics of beef other than high marbling. Three Wagyu beef, one Holstein beef and two lean imported beef longissimus samples were subjected to a descriptive sensory test, physicochemical analysis and a consumer (n = 307) preference test. According to consumer classification and external preference mapping, four consumer segments were identified as 'gradual high-fat likers', 'moderate-fat and distinctive taste likers', 'Wagyu likers' and 'distinctive texture likers'. Although the major trend of Japanese consumers' beef preference was 'marbling liking', 16.9% of the consumers preferred beef samples that had moderate marbling and distinctive taste. The consumers' attitudes expressed in a questionnaire survey were in good agreement with the preference for marbling among the 'moderate-fat and distinctive taste likers'. These results indicate that moderately marbled beef is a potent category in the Japanese beef market. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

OPERA: A free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints

EPA Science Inventory

Collecting the chemical structures and data for necessary QSAR modeling is facilitated by available public databases and open data. However, QSAR model performance is dependent on the quality of data and modeling methodology used. This study developed robust QSAR models for physi...

Use of the Chemical Transformation Simulator as a Parameterization Tool for Modeling the Environmental Fate of Organic Chemicals and their Transformation Products

EPA Science Inventory

A Chemical Transformation Simulator is a web-based system for predicting transformation pathways and physicochemical properties of organic chemicals. Role in Environmental Modeling • Screening tool for identifying likely transformation products in the environment • Parameteri...

OPERA: A QSAR tool for physicochemical properties and environmental fate predictions (ACS Spring meeting)

EPA Science Inventory

The collection of chemical structures and associated experimental data for QSAR modeling is facilitated by the increasing number and size of public databases. However, the performance of QSAR models highly depends on the quality of the data used and the modeling methodology. The ...

Applicability domains for classification problems: benchmarking of distance to models for AMES mutagenicity set

EPA Science Inventory

For QSAR and QSPR modeling of biological and physicochemical properties, estimating the accuracy of predictions is a critical problem. The “distance to model” (DM) can be defined as a metric that defines the similarity between the training set molecules and the test set compound ...

PARTICLE NUMBER AND SURFACE CHARGE PREDICT THE BIOLOGICAL ACTIVATION OF HUMAN BRONCHIAL EPITHELIAL CELLS EXPOSED TO PARTICULATE MATTER.

EPA Science Inventory

Exposure to particulate matter (PM) produces a uniform degree of mortality in exposed populations, in spite of its diverse sources. This suggests a common mechanism of action to explain its initial toxicity. The present study relates certain physicochemical characteristics (i.e.,...

Human Exposure Assessment: Development of methods to assess the bioaccessibility of organic contaminants sorbed to soils and house dusts

EPA Science Inventory

Research task- Are physicochemical properties of soil and house dust predictive of the bioaccessibility of sorbed organic compoundsGoalIdentify dust and soil characteristics that influence the bioaccessibility of organic compounds and provide chemical specific data on the fractio...

Coastal inshore waters in the NW Mediterranean: Physicochemical and biological characterization and management implications

NASA Astrophysics Data System (ADS)

Flo, Eva; Garcés, Esther; Manzanera, Marta; Camp, Jordi

2011-07-01

The physicochemical and biological characteristics of coastal waters form a gradient extending from land to ocean. In the Mediterranean this gradient is particularly large, due to the sea's weak tides. Within coastal waters, those waters in contact with land are called coastal inshore waters (CIW), defined herein as between 0 and 200 m from the shoreline. Here we present the first physicochemical and biological characterization of CIW of the NW Mediterranean Sea. This case study is based on 19 years of data collected from coastal inshore (CIW; 0-200 m), nearshore (CNW; 200-1500 m), and offshore (COW; >1500 m) waters of the Catalan coast. Analyses of these data showed that the physicochemical and biological characteristics of CIW differ significantly from those of CNW and COW due to: (1) significantly higher concentrations of dissolved inorganic nutrients (nitrate = 11.07 μM, nitrite = 0.52 μM, ammonium = 6.43 μM, phosphate = 0.92 μM, silicates = 5.99 μM) and chlorophyll- a (=2.42 μg/L) in CIW than in either CNW or COW (in some cases up to one order of magnitude); (2) a greater variability of dissolved inorganic nutrients and chlorophyll- a in CIW than in CNW and COW, and (3) the presence of a mostly urban population and the effects of river inflows as a primary source of CIW variability but with minimal impact on CNW or COW. In addition, the risk of eutrophication was found to be highest in CIW, placing human and environmental interests at greater risk than in the outermost coastal waters. The results highlight the importance of considering the distinctive physicochemical and biological properties of CIW in future coastal waters studies. This is of major importance in assessments of eutrophication and coastal water quality, not only to identify the pressure-impact relationships but also to allow the timely detection of local environmental problems and thus avoid endangering the unique communities of CIW and ensuring the sustainability of human activities. In conclusion, CIW characterization is essential to integrate coastal zone management.

Theoretical investigation on the microstructure of triethylene glycol based deep eutectic solvents: COSMO-RS and TURBOMOLE prediction

NASA Astrophysics Data System (ADS)

Aissaoui, Tayeb; Benguerba, Yacine; AlNashef, Inas M.

2017-08-01

The in-silico combination mechanism of triethylene glycol based DESs has been studied. COSMO-RS and graphical user interface TmoleX software were used to predict the interaction mechanism of hydrogen bond donors (HBDs) with hydrogen bond acceptors (HBA) to form DESs. The predicted IR results were compared with the previously reported experimental FT-IR analysis for the same studied DESs. The sigma profiles for the HBD, HBAs and formed DESs were interpreted to identify qualitatively molecular properties like polarity or hydrogen bonding donor and acceptor abilities. The predicted physicochemical properties reported in this study were in good agreement with experimental ones.

Prediction of skin sensitization potency using machine learning approaches.

PubMed

Zang, Qingda; Paris, Michael; Lehmann, David M; Bell, Shannon; Kleinstreuer, Nicole; Allen, David; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Strickland, Judy

2017-07-01

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Protein structure and evolution: are they constrained globally by a principle derived from information theory?

PubMed

Hatton, Leslie; Warr, Gregory

2015-01-01

That the physicochemical properties of amino acids constrain the structure, function and evolution of proteins is not in doubt. However, principles derived from information theory may also set bounds on the structure (and thus also the evolution) of proteins. Here we analyze the global properties of the full set of proteins in release 13-11 of the SwissProt database, showing by experimental test of predictions from information theory that their collective structure exhibits properties that are consistent with their being guided by a conservation principle. This principle (Conservation of Information) defines the global properties of systems composed of discrete components each of which is in turn assembled from discrete smaller pieces. In the system of proteins, each protein is a component, and each protein is assembled from amino acids. Central to this principle is the inter-relationship of the unique amino acid count and total length of a protein and its implications for both average protein length and occurrence of proteins with specific unique amino acid counts. The unique amino acid count is simply the number of distinct amino acids (including those that are post-translationally modified) that occur in a protein, and is independent of the number of times that the particular amino acid occurs in the sequence. Conservation of Information does not operate at the local level (it is independent of the physicochemical properties of the amino acids) where the influences of natural selection are manifest in the variety of protein structure and function that is well understood. Rather, this analysis implies that Conservation of Information would define the global bounds within which the whole system of proteins is constrained; thus it appears to be acting to constrain evolution at a level different from natural selection, a conclusion that appears counter-intuitive but is supported by the studies described herein.

Design and physicochemical stability studies of paediatric oral formulations of sildenafil.

PubMed

Provenza, N; Calpena, A C; Mallandrich, M; Halbaut, L; Clares, B

2014-01-02

Personalized medicine is a challenging research area in paediatric treatments. Elaborating new paediatric formulations when no commercial forms are available is a common practice in pharmacy laboratories; among these, oral liquid formulations are the most common. But due to the lack of specialized equipment, frequently studies to assure the efficiency and safety of the final medicine cannot be carried out. Thus the purpose of this work was the development, characterization and stability evaluation of two oral formulations of sildenafil for the treatment of neonatal persistent pulmonary hypertension. After the establishment of a standard operating procedure (SOP) and elaboration, the physicochemical stability parameters appearance, pH, particle size, rheological behaviour and drug content of formulations were evaluated at three different temperatures for 90 days. Equally, prediction of long term stability, as well as, microbiological stability was performed. Formulations resulted in a suspension and a solution slightly coloured exhibiting fruity odour. Formulation I (suspension) exhibited the best physicochemical properties including Newtonian behaviour and uniformity of API content above 90% to assure an exact dosification process. Copyright © 2013 Elsevier B.V. All rights reserved.

Physicochemical characterization of ultrasmall superparamagnetic iron oxide particles (USPIO) for biomedical application as MRI contrast agents

PubMed Central

Di Marco, Mariagrazia; Sadun, Claudia; Port, Marc; Guilbert, Irene; Couvreur, Patrick; Dubernet, Catherine

2007-01-01

Ultrasmall superparamagnetic iron oxide (USPIO) particles are maghemite or magnetite nanoparticles currently used as contrast agent in magnetic resonance imaging. The coatings surrounding the USPIO inorganic core play a major role in both the in vitro stability and, over all, USPIO’s in vivo fate. Different physicochemical properties such as final size, surface charge and coating density are key factors in this respect. Up to now no precise structure – activity relationship has been described to predict entirely the USPIOs stability, as well as their pharmacokinetics and their safety. This review is focused on both the classical and the latest available techniques allowing a better insight in the magnetic core structure and the organic surface of these particles. Concurrently, this work clearly shows the difficulty to obtain a complete physicochemical characterization of USPIOs particles owing to their small dimensions, reaching the analytical resolution limits of many commercial instruments. An extended characterization is therefore necessary to improve the understanding of the properties of USPIOs when dispersed in an aqueous environment and to set the specifications and limits for their conception. PMID:18203428

Interactions between suspension characteristics and physicochemical properties of silver and copper oxide nanoparticles: a case study for optimizing nanoparticle stock suspensions using a central composite design.

PubMed

Son, Jino; Vavra, Janna; Li, Yusong; Seymour, Megan; Forbes, Valery

2015-04-01

The preparation of a stable nanoparticle stock suspension is the first step in nanotoxicological studies, but how different preparation methods influence the physicochemical properties of nanoparticles in a solution, even in Milli-Q water, is often under-appreciated. In this study, a systematic approach using a central composite design (CCD) was employed to investigate the effects of sonication time and suspension concentration on the physicochemical properties (i.e. hydrodynamic diameter, zeta potential and ion dissolution) of silver (Ag) and copper oxide (CuO) nanoparticles (NPs) and to identify optimal conditions for suspension preparation in Milli-Q water; defined as giving the smallest particle sizes, highest suspension stability and lowest ion dissolution. Indeed, all the physicochemical properties of AgNPs and CuONPs varied dramatically depending on how the stock suspensions were prepared and differed profoundly between nanoparticle types, indicating the importance of suspension preparation. Moreover, the physicochemical properties of AgNPs and CuONPs, at least in simple media (Milli-Q water), behaved in predictable ways as a function of sonication time and suspension concentration, confirming the validity of our models. Overall, the approach allows systematic assessment of the influence of various factors on key properties of nanoparticle suspensions, which will facilitate optimization of the preparation of nanoparticle stock suspensions and improve the reproducibility of nanotoxicological results. We recommend that further attention be given to details of stock suspension preparation before conducting nanotoxicological studies as these can have an important influence on the behavior and subsequent toxicity of nanoparticles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Physico-chemical and biological characterization of urban municipal landfill leachate.

PubMed

Naveen, B P; Mahapatra, Durga Madhab; Sitharam, T G; Sivapullaiah, P V; Ramachandra, T V

2017-01-01

Unscientific management and ad-hoc approaches in municipal solid waste management have led to a generation of voluminous leachate in urban conglomerates. Quantification, quality assessment, following treatment and management of leachate has become a serious problem worldwide. In this context, the present study investigates the physico-chemical and biological characterization of landfill leachate and nearby water sources and attempts to identify relationships between the key parameters together with understanding the various processes for chemical transformations. The analysis shows an intermediate leachate age (5-10 years) with higher nutrient levels of 10,000-12,000 mg/l and ∼2000-3000 mg/l of carbon (COD) and nitrogen (TKN) respectively. Elemental analysis and underlying mechanisms reveal chemical precipitation and co-precipitation as the vital processes in leachate pond systems resulting in accumulation of trace metals. Based on the above criteria the samples were clustered into major groups that showed a clear distinction between leachate and water bodies. The microbial analysis showed bacterial communities correlating with specific factors relevant to redox environments indicating a gradient in nature and abundance of biotic diversity with a change in leachate environment. Finally, the quality and the contamination potential of the samples were evaluated with the help of leachate pollution index (LPI) and water quality index (WQI) analysis. The study helps in understanding the contamination potential of landfill leachate and establishes linkages between microbial communities and physico-chemical parameters for effective management of landfill leachate. Copyright © 2016 Elsevier Ltd. All rights reserved.

In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning

EPA Science Inventory

There are little available toxicity data on the vast majority of chemicals in commerce. High-throughput screening (HTS) studies, such as those being carried out by the U.S. Environmental Protection Agency (EPA) ToxCast program in partnership with the federal Tox21 research progra...

In Vitro Vascular Toxicity of Manufactured Metal Oxide Nanoparticles: Size Profile Predicts Cellular Specificity, Delivered Dose, and Toxicity

EPA Science Inventory

Metal oxide nanoparticles (NPs) are being used in an expanding range of products and applications due to their unique physicochemical properties. In vivo biokinetic studies have demonstrated the ability of metal oxide NPs to translocate to the distal organs, including the cardiov...

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Palou, Anna; Miró, Aira; Blanco, Marcelo; Larraz, Rafael; Gómez, José Francisco; Martínez, Teresa; González, Josep Maria; Alcalà, Manel

2017-06-01

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

General Pharmacokinetic Model for Topically Administered Ocular Drug Dosage Forms.

PubMed

Deng, Feng; Ranta, Veli-Pekka; Kidron, Heidi; Urtti, Arto

2016-11-01

In ocular drug development, an early estimate of drug behavior before any in vivo experiments is important. The pharmacokinetics (PK) and bioavailability depend not only on active compound and excipients but also on physicochemical properties of the ocular drug formulation. We propose to utilize PK modelling to predict how drug and formulational properties affect drug bioavailability and pharmacokinetics. A physiologically relevant PK model based on the rabbit eye was built to simulate the effect of formulation and physicochemical properties on PK of pilocarpine solutions and fluorometholone suspensions. The model consists of four compartments: solid and dissolved drug in tear fluid, drug in corneal epithelium and aqueous humor. Parameter values and in vivo PK data in rabbits were taken from published literature. The model predicted the pilocarpine and fluorometholone concentrations in the corneal epithelium and aqueous humor with a reasonable accuracy for many different formulations. The model includes a graphical user interface that enables the user to modify parameters easily and thus simulate various formulations. The model is suitable for the development of ophthalmic formulations and the planning of bioequivalence studies.

Effects of pyrolysis temperature on the physicochemical properties of empty fruit bunch and rice husk biochars.

PubMed

Claoston, N; Samsuri, A W; Ahmad Husni, M H; Mohd Amran, M S

2014-04-01

Biochar has received great attention recently due to its potential to improve soil fertility and immobilize contaminants as well as serving as a way of carbon sequestration and therefore a possible carbon sink. In this work, a series of biochars were produced from empty fruit bunch (EFB) and rice husk (RH) by slow pyrolysis at different temperatures (350, 500, and 650°C) and their physicochemical properties were analysed. The results indicate that porosity, ash content, electrical conductivity (EC), and pH value of both EFB and RH biochars were increased with temperature; however, yield, cation exchange capacity (CEC), and H, C, and N content were decreased with increasing pyrolysis temperature. The Fourier transform IR spectra were similar for both RH and EFB biochars but the functional groups were more distinct in the EFB biochar spectra. There were reductions in the amount of functional groups as pyrolysis temperature increased especially for the EFB biochar. However, total acidity of the functional groups increased with pyrolysis temperature for both biochars.

Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Ortiz, Carina A.; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

2016-08-01

Inaccurate estimate of the largest terrestrial carbon pool, soil organic carbon (SOC) stock, is the major source of uncertainty in simulating feedback of climate warming on ecosystem-atmosphere carbon dioxide exchange by process-based ecosystem and soil carbon models. Although the models need to simplify complex environmental processes of soil carbon sequestration, in a large mosaic of environments a missing key driver could lead to a modeling bias in predictions of SOC stock change.We aimed to evaluate SOC stock estimates of process-based models (Yasso07, Q, and CENTURY soil sub-model v4) against a massive Swedish forest soil inventory data set (3230 samples) organized by a recursive partitioning method into distinct soil groups with underlying SOC stock development linked to physicochemical conditions.For two-thirds of measurements all models predicted accurate SOC stock levels regardless of the detail of input data, e.g., whether they ignored or included soil properties. However, in fertile sites with high N deposition, high cation exchange capacity, or moderately increased soil water content, Yasso07 and Q models underestimated SOC stocks. In comparison to Yasso07 and Q, accounting for the site-specific soil characteristics (e. g. clay content and topsoil mineral N) by CENTURY improved SOC stock estimates for sites with high clay content, but not for sites with high N deposition.Our analysis suggested that the soils with poorly predicted SOC stocks, as characterized by the high nutrient status and well-sorted parent material, indeed have had other predominant drivers of SOC stabilization lacking in the models, presumably the mycorrhizal organic uptake and organo-mineral stabilization processes. Our results imply that the role of soil nutrient status as regulator of organic matter mineralization has to be re-evaluated, since correct SOC stocks are decisive for predicting future SOC change and soil CO2 efflux.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

PubMed

Srinivasulu, Yerukala Sathipati; Wang, Jyun-Rong; Hsu, Kai-Ti; Tsai, Ming-Ju; Charoenkwan, Phasit; Huang, Wen-Lin; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes

PubMed Central

2015-01-01

Background Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. Results This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. Conclusions The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes. PMID:26681483

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Strategies for multivariate modeling of moisture content in freeze-dried mannitol-containing products by near-infrared spectroscopy.

PubMed

Yip, Wai Lam; Gausemel, Ingvil; Sande, Sverre Arne; Dyrstad, Knut

2012-11-01

Accurate determination of residual moisture content of a freeze-dried (FD) pharmaceutical product is critical for prediction of its quality. Near-infrared (NIR) spectroscopy is a fast and non-invasive method routinely used for quantification of moisture. However, several physicochemical properties of the FD product may interfere with absorption bands related to the water content. A commonly used stabilizer and bulking agent in FD known for variation in physicochemical properties, is mannitol. To minimize this physicochemical interference, different approaches for multivariate correlation between NIR spectra of a FD product containing mannitol and the corresponding moisture content measured by Karl Fischer (KF) titration have been investigated. A novel method, MIPCR (Main and Interactions of Individual Principal Components Regression), was found to have significantly increased predictive ability of moisture content compared to a traditional PLS approach. The philosophy behind the MIPCR is that the interference from a variety of particle and morphology attributes has interactive effects on the water related absorption bands. The transformation of original wavelength variables to orthogonal scores gives a new set of variables (scores) without covariance structure, and the possibility of inclusion of interaction terms in the further modeling. The residual moisture content of the FD product investigated is in the range from 0.7% to 2.6%. The mean errors of cross validated prediction of models developed in the investigated NIR regions were reduced from a range of 24.1-27.6% for traditional PLS method to 15.7-20.5% for the MIPCR method. Improved model quality by application of MIPCR, without the need for inclusion of a large number of calibration samples, might increase the use of NIR in early phase product development, where availability of calibration samples is often limited. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory.

PubMed

Netzeva, Tatiana I; Gallegos Saliner, Ana; Worth, Andrew P

2006-05-01

The aim of the present study was to illustrate that it is possible and relatively straightforward to compare the domain of applicability of a quantitative structure-activity relationship (QSAR) model in terms of its physicochemical descriptors with a large inventory of chemicals. A training set of 105 chemicals with data for relative estrogenic gene activation, obtained in a recombinant yeast assay, was used to develop the QSAR. A binary classification model for predicting active versus inactive chemicals was developed using classification tree analysis and two descriptors with a clear physicochemical meaning (octanol-water partition coefficient, or log Kow, and the number of hydrogen bond donors, or n(Hdon)). The model demonstrated a high overall accuracy (90.5%), with a sensitivity of 95.9% and a specificity of 78.1%. The robustness of the model was evaluated using the leave-many-out cross-validation technique, whereas the predictivity was assessed using an artificial external test set composed of 12 compounds. The domain of the QSAR training set was compared with the chemical space covered by the European Inventory of Existing Commercial Chemical Substances (EINECS), as incorporated in the CDB-EC software, in the log Kow / n(Hdon) plane. The results showed that the training set and, therefore, the applicability domain of the QSAR model covers a small part of the physicochemical domain of the inventory, even though a simple method for defining the applicability domain (ranges in the descriptor space) was used. However, a large number of compounds are located within the narrow descriptor window.

Comparative genomics reveals adaptations of a halotolerant thaumarchaeon in the interfaces of brine pools in the Red Sea

PubMed Central

Kamanda Ngugi, David; Blom, Jochen; Alam, Intikhab; Rashid, Mamoon; Ba-Alawi, Wail; Zhang, Guishan; Hikmawan, Tyas; Guan, Yue; Antunes, Andre; Siam, Rania; El Dorry, Hamza; Bajic, Vladimir; Stingl, Ulrich

2015-01-01

The bottom of the Red Sea harbors over 25 deep hypersaline anoxic basins that are geochemically distinct and characterized by vertical gradients of extreme physicochemical conditions. Because of strong changes in density, particulate and microbial debris get entrapped in the brine-seawater interface (BSI), resulting in increased dissolved organic carbon, reduced dissolved oxygen toward the brines and enhanced microbial activities in the BSI. These features coupled with the deep-sea prevalence of ammonia-oxidizing archaea (AOA) in the global ocean make the BSI a suitable environment for studying the osmotic adaptations and ecology of these important players in the marine nitrogen cycle. Using phylogenomic-based approaches, we show that the local archaeal community of five different BSI habitats (with up to 18.2% salinity) is composed mostly of a single, highly abundant Nitrosopumilus-like phylotype that is phylogenetically distinct from the bathypelagic thaumarchaea; ammonia-oxidizing bacteria were absent. The composite genome of this novel Nitrosopumilus-like subpopulation (RSA3) co-assembled from multiple single-cell amplified genomes (SAGs) from one such BSI habitat further revealed that it shares ∼54% of its predicted genomic inventory with sequenced Nitrosopumilus species. RSA3 also carries several, albeit variable gene sets that further illuminate the phylogenetic diversity and metabolic plasticity of this genus. Specifically, it encodes for a putative proline-glutamate ‘switch' with a potential role in osmotolerance and indirect impact on carbon and energy flows. Metagenomic fragment recruitment analyses against the composite RSA3 genome, Nitrosopumilus maritimus, and SAGs of mesopelagic thaumarchaea also reiterate the divergence of the BSI genotypes from other AOA. PMID:25105904

Evaluation of SARs for the prediction of eye irritation/corrosion potential: structural inclusion rules in the BfR decision support system.

PubMed

Tsakovska, I; Saliner, A Gallegos; Netzeva, T; Pavan, M; Worth, A P

2007-01-01

The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure-activity relationships ([Q]SARs), suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB to assess the performance of the BfR structural rulebase. The assessment included: (a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and (b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.

Effect of inulin on the physicochemical properties, flow behavior and probiotic survival of frozen yogurt.

PubMed

Rezaei, Rahil; Khomeiri, Morteza; Aalami, Mehran; Kashaninejad, Mahdi

2014-10-01

This study investigated the effect of inulin (0, 1 and 2 %), on some physicochemical properties of frozen yogurt, as well as its effect on flow behavior and probiotic survival. The results showed that the addition of inulin improved overrun, viscosity and melting properties significantly (p < 0.05); when added at 2 % level, it also had significant effect on pH. Total acceptability of samples revealed that frozen yogurt with 2 % inulin had the most appealing sensory characteristics. The flow behavior of all samples showed their pseudoplastic nature; power law was the best model to predict their flow behavior. In terms of probiotic survival, the sample with 2 % inulin significantly improved the viability of Lactobacillus acidophilus and Bifidobacterium lactis.

Static and transport properties of alkyltrimethylammonium cation-based room-temperature ionic liquids.

PubMed

Seki, Shiro; Tsuzuki, Seiji; Hayamizu, Kikuko; Serizawa, Nobuyuki; Ono, Shimpei; Takei, Katsuhito; Doi, Hiroyuki; Umebayashi, Yasuhiro

2014-05-01

We have measured physicochemical properties of five alkyltrimethylammonium cation-based room-temperature ionic liquids and compared them with those obtained from computational methods. We have found that static properties (density and refractive index) and transport properties (ionic conductivity, self-diffusion coefficient, and viscosity) of these ionic liquids show close relations with the length of the alkyl chain. In particular, static properties obtained by experimental methods exhibit a trend complementary to that by computational methods (refractive index ∝ [polarizability/molar volume]). Moreover, the self-diffusion coefficient obtained by molecular dynamics (MD) simulation was consistent with the data obtained by the pulsed-gradient spin-echo nuclear magnetic resonance technique, which suggests that computational methods can be supplemental tools to predict physicochemical properties of room-temperature ionic liquids.

Mass Transfer Behavior of Perfluorinated Chemicals in Saturated Clay-rich Sands: A Laboratory-based Study on Fate and Transport in Groundwater and Sediments

NASA Astrophysics Data System (ADS)

Greenberg, R. R.; Tick, G. R.; Abbott, J. B., III; Carroll, K. C.

2017-12-01

Perfluoroalkyl substances (PFAS) are a class of emerging contaminants that pose a threat to the human health and the quality of groundwater, surface water, and drinking water supplies. This study aims to elucidate the primary physicochemical factors controlling the fate and transport of the PFAS contaminants, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), in groundwater. Physicochemical processes of intercalation, adsorption, and desorption were investigated for the retention of PFAS at different initial aqueous-phase concentrations in modified-natural sediments composed of sand (40/50 accusand; foc = 0.04% unmodified) with low, medium, and high organic carbon contents (foc = 10, 20, and 50%) and various pre-conditioned clay-fractions. Diffusional mass-transfer limitations were evaluated based on initial PFAS concentration, specific clay structure, and resulting contaminant intercalation (d-spacing changes). A series of short- (48 hr), medium- (7 day) and long-term (30 day) batch and column experiments were conducted to determine physicochemical processes as a function of compound chemistry, sediment geochemistry, sorbent crystalline structure, and contaminant/sediment contact-time. Physicochemical parameters, PFAS concentrations, and sediment characterization were conducted using high performance liquid chromatography (HPLC), X-ray diffraction (XRD), and furnace combustion analytical techniques. The results of PFAS contaminant transport, under the different conditions tested, provide a scientific contribution with application to the development of improved risk assessments, predictions of fate and transport, and more effective remediation strategies for emerging perfluorinated contaminants in soil and groundwater.

How far are rheological parameters from amplitude sweep tests predictable using common physicochemical soil properties?

NASA Astrophysics Data System (ADS)

Stoppe, N.; Horn, R.

2017-01-01

A basic understanding of soil behavior on the mesoscale resp. macroscale (i.e. soil aggregates resp. bulk soil) requires knowledge of the processes at the microscale (i.e. particle scale), therefore rheological investigations of natural soils receive growing attention. In the present research homogenized and sieved (< 2 mm) samples from Marshland soils of the riparian zone of the River Elbe (North Germany) were analyzed with a modular compact rheometer MCR 300 (Anton Paar, Ostfildern, Germany) with a profiled parallel-plate measuring system. Amplitude sweep tests (AST) with controlled shear deformation were conducted to investigate the viscoelastic properties of the studied soils under oszillatory stress. The gradual depletion of microstructural stiffness during AST cannot only be characterized by the well-known rheological parameters G, G″ and tan δ but also by the dimensionless area parameter integral z, which quantifies the elasticity of microstructure. To discover the physicochemical parameters, which influences the microstructural stiffness, statistical tests were used taking the combined effects of these parameters into account. Although the influence of the individual factors varies depending on soil texture, the physicochemical features significantly affecting soil micro structure were identified. Based on the determined statistical relationships between rheological and physicochemical parameters, pedotransfer functions (PTF) have been developed, which allow a mathematical estimation of the rheological target value integral z. Thus, stabilizing factors are: soil organic matter, concentration of Ca2+, content of CaCO3 and pedogenic iron oxides; whereas the concentration of Na+ and water content represent structurally unfavorable factors.

In Vitro Drug-Induced Liver Injury Prediction: Criteria Optimization of Efflux Transporter IC50 and Physicochemical Properties.

PubMed

Yucha, Robert W; He, Kan; Shi, Qin; Cai, Lining; Nakashita, Yukie; Xia, Cindy Q; Liao, Mingxiang

2017-06-01

Drug-induced liver injury (DILI) is a severe drug adverse response, which cannot always be reliably predicted in preclinical or clinical studies. Lack of observation of DILI during preclinical and clinical drug development has led to DILI being a leading cause of drug withdrawal from the market. As DILI is potentially fatal, pharmaceutical companies have been developing in vitro tools to screen for potential liver injury. Screens for physicochemical properties, mitochondrial function, and transport protein inhibition have all been employed to varying degrees of success. In vitro inhibition of the bile salt export pump (BSEP) has become a major risk factor for in vivo DILI predictions, yet discrepancies exist in which methods to use and the extent to which BSEP inhibition predicts clinical DILI. The presented work focuses on optimizing DILI predictions by comparing BSEP inhibition via the membrane vesicle assay and the hepatocyte-based BSEPcyte assay, as well as dual and triple liabilities. BSEP transport inhibition of taurcholic acids and glycocholic acids were similar for up to 29 drugs tested, in both the vesicle and hepatocyte-based assays. Positive and negative DILI predictions were optimized at a 50-µM cutoff value for 50 drugs using both NIH Livertox and PharmaPendium databases. Additionally, dual inhibition of BSEP and other efflux transporters (multidrug resistance-associated protein [MRP]2, MRP3, or MRP4) provided no observable predictive benefit compared with BSEP inhibition alone. Eighty-five percent of drugs with high molecular weight (>600 Da), high cLogP (>3), or a daily dose >100 mg and BSEP inhibition were associated with DILI. Triple liability of BSEP inhibition, high molecular weight, and high cLogP attained a 100% positive prediction rate. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

PubMed

Majid, Abdul; Ali, Safdar

2015-01-01

We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

MODELING THE UPTAKE OF GASES BY THE DOG NASAL-PHARYNGEAL REGION: EFFECTS OF MORPHOMETRIC AND PHYSICOCHEMICAL FACTORS

EPA Science Inventory

Generally, the uptake of reactive gases by the respiratory tract is simulated assuming that all path from the trachea to the most distal airspaces ore equivalent. s this is not the case, especially for non-humans, the adequacy of this approach to predict doses that con be useful ...

Millions of Boreal Shield Lakes can be used to Probe Archaean Ocean Biogeochemistry

PubMed Central

Schiff, S. L.; Tsuji, J. M.; Wu, L.; Venkiteswaran, J. J.; Molot, L. A.; Elgood, R. J.; Paterson, M. J.; Neufeld, J. D.

2017-01-01

Life originated in Archaean oceans, almost 4 billion years ago, in the absence of oxygen and the presence of high dissolved iron concentrations. Early Earth oxidation is marked globally by extensive banded iron formations but the contributing processes and timing remain controversial. Very few aquatic habitats have been discovered that match key physico-chemical parameters of the early Archaean Ocean. All previous whole ecosystem Archaean analogue studies have been confined to rare, low sulfur, and permanently stratified lakes. Here we provide first evidence that millions of Boreal Shield lakes with natural anoxia offer the opportunity to constrain biogeochemical and microbiological aspects of early Archaean life. Specifically, we combined novel isotopic signatures and nucleic acid sequence data to examine processes in the anoxic zone of stratified boreal lakes that are naturally low in sulfur and rich in ferrous iron, hallmark characteristics predicted for the Archaean Ocean. Anoxygenic photosynthesis was prominent in total water column biogeochemistry, marked by distinctive patterns in natural abundance isotopes of carbon, nitrogen, and iron. These processes are robust, returning reproducibly after water column re-oxygenation following lake turnover. Evidence of coupled iron oxidation, iron reduction, and methane oxidation affect current paradigms of both early Earth and modern aquatic ecosystems. PMID:28447615

Implementing marine organic aerosols into the GEOS-Chem model

DOE PAGES

Gantt, B.; Johnson, M. S.; Crippa, M.; ...

2015-03-17

Marine-sourced organic aerosols (MOAs) have been shown to play an important role in tropospheric chemistry by impacting surface mass, cloud condensation nuclei, and ice nuclei concentrations over remote marine and coastal regions. In this work, an online marine primary organic aerosol emission parameterization, designed to be used for both global and regional models, was implemented into the GEOS-Chem (Global Earth Observing System Chemistry) model. The implemented emission scheme improved the large underprediction of organic aerosol concentrations in clean marine regions (normalized mean bias decreases from -79% when using the default settings to -12% when marine organic aerosols are added). Modelmore » predictions were also in good agreement (correlation coefficient of 0.62 and normalized mean bias of -36%) with hourly surface concentrations of MOAs observed during the summertime at an inland site near Paris, France. Our study shows that MOAs have weaker coastal-to-inland concentration gradients than sea-salt aerosols, leading to several inland European cities having >10% of their surface submicron organic aerosol mass concentration with a marine source. The addition of MOA tracers to GEOS-Chem enabled us to identify the regions with large contributions of freshly emitted or aged aerosol having distinct physicochemical properties, potentially indicating optimal locations for future field studies.« less

Dietary supplementation with flaxseed meal and oat hulls modulates intestinal histomorphometric characteristics, digesta- and mucosa-associated microbiota in pigs.

PubMed

Ndou, S P; Tun, H M; Kiarie, E; Walsh, M C; Khafipour, E; Nyachoti, C M

2018-04-12

The establishment of a healthy gastrointestinal milieu may not only offer an opportunity to reduce swine production costs but could also open the way for a lifetime of human health improvement. This study investigates the effects of feeding soluble fibre from flaxseed meal-containing diet (FM) and insoluble fibre from oat hulls-containing diet (OH) on histomorphological characteristics, digesta- and mucosa-associated microbiota and their associations with metabolites in pig intestines. In comparison with the control (CON) and OH diets, the consumption of FM increased (P < 0.001) the jejunal villi height (VH) and the ratio of VH to crypt depths. The PERMANOVA analyses showed distinct (P < 0.05) microbial communities in ileal digesta and mucosa, and caecal mucosa in CON and FM-diets fed pigs compared to the OH diet-fed pigs. The predicted functional metagenomes indicated that amino acids and butanoate metabolism, lysine degradation, bile acids biosynthesis, and apoptosis were selectively enhanced at more than 2.2 log-folds in intestinal microbiota of pigs fed the FM diet. Taken together, flaxseed meal and oat hulls supplementation in growing pigs' diets altered the gastrointestinal development, as well as the composition and function of microbial communities, depending on the intestinal segment and physicochemical property of the dietary fibre source.

Evaluation of extra virgin olive oil stability by artificial neural network.

PubMed

Silva, Simone Faria; Anjos, Carlos Alberto Rodrigues; Cavalcanti, Rodrigo Nunes; Celeghini, Renata Maria dos Santos

2015-07-15

The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions was evaluated. The following analyses were carried out: free fatty acids, peroxide value, specific extinction at 232 and 270 nm, chlorophyll, L(∗)C(∗)h color, total phenolic compounds, tocopherols and squalene. The physicochemical changes were evaluated by artificial neural network (ANN) modeling with respect to light exposure conditions and packaging material. The optimized ANN structure consists of 11 input neurons, 18 hidden neurons and 5 output neurons using hyperbolic tangent and softmax activation functions in hidden and output layers, respectively. The five output neurons correspond to five possible classifications according to packaging material (PET amber, PET transparent and tinplate can) and light exposure (dark and light storage). The predicted physicochemical changes agreed very well with the experimental data showing high classification accuracy for test (>90%) and training set (>85). Sensitivity analysis showed that free fatty acid content, peroxide value, L(∗)Cab(∗)hab(∗) color parameters, tocopherol and chlorophyll contents were the physicochemical attributes with the most discriminative power. Copyright © 2015 Elsevier Ltd. All rights reserved.

Some engineering aspects of homoionized mixed clay minerals.

PubMed

Oren, Ali Hakan; Kaya, Abidin

2003-05-01

Many studies have been conducted to investigate the physicochemical behavior of pure clay minerals and predict their engineering performance in the field. In this study, the physicochemical properties of an artificial mixture of different clay minerals namely, 40-50% montmorillonite, 20-30% illite and 10-15% kaolin were investigated. The mixture was homoionized with sodium, Na+; calcium, Ca2+; and aluminum, Al3+. The engineering properties studied were consistency limits, sediment volume, compressibility behavior, and hydraulic conductivity. The results revealed that the liquid, plastic and shrinkage limits of soil increased with increasing cation valence. The hydraulic conductivity of the soil also increased with an increase in the valence of the cation at any given void ratio. Aluminum and sodium treated clays had the highest and the lowest modified compression index values, respectively. Furthermore, trivalent cation saturated clayey soil consolidates three times faster than that of monovalent and two times faster than that of divalent. These properties of the soils determined were, in general, similar to those of kaolinite rather than those of montmorillonite. The comparison of the results obtained with the published data in the literature revealed that the physicochemical behavior of the tested clay soil was, in general, similar to that of kaolinite.

PLS-based quantitative structure-activity relationship for substituted benzamides of clebopride type. Application of experimental design in drug design.

PubMed

Norinder, U; Högberg, T

1992-04-01

The advantageous approach of using an experimentally designed training set as the basis for establishing a quantitative structure-activity relationship with good predictive capability is described. The training set was selected from a fractional factorial design scheme based on a principal component description of physico-chemical parameters of aromatic substituents. The derived model successfully predicts the activities of additional substituted benzamides of 6-methoxy-N-(4-piperidyl)salicylamide type. The major influence on activity of the 3-substituent is demonstrated.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

NASA Astrophysics Data System (ADS)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

Nanomaterial Toxicity Testing in the 21st Century: Use of a Predictive Toxicological Approach and High Throughput Screening

PubMed Central

NEL, ANDRE; XIA, TIAN; MENG, HUAN; WANG, XIANG; LIN, SIJIE; JI, ZHAOXIA; ZHANG, HAIYUAN

2014-01-01

Conspectus The production of engineered nanomaterials (ENMs) is a scientific breakthrough in material design and the development of new consumer products. While the successful implementation of nanotechnology is important for the growth of the global economy, we also need to consider the possible environmental health and safety (EHS) impact as a result of the novel physicochemical properties that could generate hazardous biological outcomes. In order to assess ENM hazard, reliable and reproducible screening approaches are needed to test the basic materials as well as nano-enabled products. A platform is required to investigate the potentially endless number of bio-physicochemical interactions at the nano/bio interface, in response to which we have developed a predictive toxicological approach. We define a predictive toxicological approach as the use of mechanisms-based high throughput screening in vitro to make predictions about the physicochemical properties of ENMs that may lead to the generation of pathology or disease outcomes in vivo. The in vivo results are used to validate and improve the in vitro high throughput screening (HTS) and to establish structure-activity relationships (SARs) that allow hazard ranking and modeling by an appropriate combination of in vitro and in vivo testing. This notion is in agreement with the landmark 2007 report from the US National Academy of Sciences, “Toxicity Testing in the 21st Century: A Vision and a Strategy” (http://www.nap.edu/catalog.php?record_id=11970), which advocates increased efficiency of toxicity testing by transitioning from qualitative, descriptive animal testing to quantitative, mechanistic and pathway-based toxicity testing in human cells or cell lines using high throughput approaches. Accordingly, we have implemented HTS approaches to screen compositional and combinatorial ENM libraries to develop hazard ranking and structure-activity relationships that can be used for predicting in vivo injury outcomes. This predictive approach allows the bulk of the screening analysis and high volume data generation to be carried out in vitro, following which limited, but critical, validation studies are carried out in animals or whole organisms. Risk reduction in the exposed human or environmental populations can then focus on limiting or avoiding exposures that trigger these toxicological responses as well as implementing safer design of potentially hazardous ENMs. In this communication, we review the tools required for establishing predictive toxicology paradigms to assess inhalation and environmental toxicological scenarios through the use of compositional and combinatorial ENM libraries, mechanism-based HTS assays, hazard ranking and development of nano-SARs. We will discuss the major injury paradigms that have emerged based on specific ENM properties, as well as describing the safer design of ZnO nanoparticles based on characterization of dissolution chemistry as a major predictor of toxicity. PMID:22676423

Learning to predict chemical reactions.

PubMed

Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

2011-09-26

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system is generalizable, making reasonable predictions over reactants and conditions which the rule-based expert does not handle. A web interface to the machine learning based mechanistic reaction predictor is accessible through our chemoinformatics portal ( http://cdb.ics.uci.edu) under the Toolkits section.

Learning to Predict Chemical Reactions

PubMed Central

Kayala, Matthew A.; Azencott, Chloé-Agathe; Chen, Jonathan H.

2011-01-01

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles respectively are not high-throughput, are not generalizable or scalable, or lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry dataset consisting of 1630 full multi-step reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval, problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of non-productive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system is generalizable, making reasonable predictions over reactants and conditions which the rule-based expert does not handle. A web interface to the machine learning based mechanistic reaction predictor is accessible through our chemoinformatics portal (http://cdb.ics.uci.edu) under the Toolkits section. PMID:21819139

Relationship between global structural parameters and Enzyme Commission hierarchy: implications for function prediction.

PubMed

Boareto, Marcelo; Yamagishi, Michel E B; Caticha, Nestor; Leite, Vitor B P

2012-10-01

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. Copyright © 2012 Elsevier Ltd. All rights reserved.

Traits, States, and Encoding Speed: Support for a Top-Down View of Neuroticism/State Relations

PubMed Central

Robinson, Michael D.; Clore, Gerald L.

2008-01-01

Recent theories suggest that trait neuroticism gains its pernicious power particularly among individuals less capable of making distinctions concerning present reality. Four studies, involving 272 undergraduates, sought to provide some basic, assessment-related support for such theories in the context of individual differences in choice reaction time, which reflect abilities to make distinctions at encoding. Studies 1–3 focused on somatic symptoms, whereas Study 4 focused on neurotic behaviors and negative affect. As predicted, neuroticism consistently interacted with categorization speed in predicting these dependent measures. Specifically, neuroticism/outcome relations were robust among individuals slow to make distinctions at encoding; by contrast, neuroticism did not predict the dependent measures among individuals fast to make distinctions. Such data reinforce suggestions that neuroticism is particularly pernicious among individuals less capable of making distinctions at encoding. PMID:17214593

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

PubMed

Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding.

Insights into an Original Pocket-Ligand Pair Classification: A Promising Tool for Ligand Profile Prediction

PubMed Central

Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A.; Villoutreix, Bruno O.; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding. PMID:23840299

Food, gastrointestinal pH, and models of oral drug absorption.

PubMed

Abuhelwa, Ahmad Y; Williams, Desmond B; Upton, Richard N; Foster, David J R

2017-03-01

This article reviews the major physiological and physicochemical principles of the effect of food and gastrointestinal (GI) pH on the absorption and bioavailability of oral drugs, and the various absorption models that are used to describe/predict oral drug absorption. The rate and extent of oral drug absorption is determined by a complex interaction between a drug's physicochemical properties, GI physiologic factors, and the nature of the formulation administered. GI pH is an important factor that can markedly affect oral drug absorption and bioavailability as it may have significant influence on drug dissolution & solubility, drug release, drug stability, and intestinal permeability. Different regions of the GI tract have different drug absorptive properties. Thus, the transit time in each GI region and its variability between subjects may contribute to the variability in the rate and/or extent of drug absorption. Food-drug interactions can result in delayed, decreased, increased, and sometimes un-altered drug absorption. Food effects on oral absorption can be achieved by direct and indirect mechanisms. Various models have been proposed to describe oral absorption ranging from empirical models to the more sophisticated "mechanism-based" models. Through understanding of the physicochemical and physiological rate-limiting factors affecting oral absorption, modellers can implement simplified population-based modelling approaches that are less complex than whole-body physiologically-based models but still capture the essential elements in a physiological way and hence will be more suited for population modelling of large clinical data sets. It will also help formulation scientists to better predict formulation performance and to develop formulations that maximize oral bioavailability. Copyright © 2016 Elsevier B.V. All rights reserved.

Toward toxicity testing of nanomaterials in the 21st century: a paradigm for moving forward.

PubMed

Lai, David Y

2012-01-01

A challenge-facing hazard identification and safety evaluation of engineered nanomaterials being introduced to market is the diversity and complexity of the types of materials with varying physicochemical properties, many of which can affect their toxicity by different mechanisms. In general, in vitro test systems have limited usefulness for hazard identification of nanoparticles due to various issues. Meanwhile, conducting chronic toxicity/carcinogenicity studies in rodents for every new nanomaterial introduced into the commerce is impractical if not impossible. New toxicity testing systems which rely on predictive, high-throughput technologies may be the ultimate goal of evaluating the potential hazard of nanomaterials. However, at present, this approach alone is unlikely to succeed in evaluating the toxicity of the wide array of nanomaterials and requires validation from in vivo studies. This article proposes a paradigm for toxicity testing and elucidation of the molecular mechanisms of reference materials for specific nanomaterial classes/subclasses using short-term in vivo animal studies in conjunction with high-throughput screenings and mechanism-based short-term in vitro assays. The hazard potential of a particular nanomaterial can be evaluated by conducting only in vitro high-throughput assays and mechanistic studies and comparing the data with those of the reference materials in the specific class/subclass-an approach in line with the vision for 'Toxicity Testing in the 21st Century' of chemicals. With well-designed experiments, testing nanomaterials of varying/selected physicochemical parameters may be able to identify the physicochemical parameters contributing to toxicity. The data so derived could be used for the development of computer model systems to predict the hazard potential of specific nanoparticles based on property-activity relationships. Copyright © 2011 John Wiley & Sons, Inc.

Beyond clay - using selective extractions to improve predictions of soil carbon content

NASA Astrophysics Data System (ADS)

Rasmussen, C.; Berhe, A. A.; Blankinship, J. C.; Crow, S. E.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Plante, A. F.; Schaedel, C.; Schimel, J.; Sierra, C. A.; Thompson, A.; Wagai, R.; Wieder, W. R.

2016-12-01

A central component of modern soil carbon (C) models is the use of clay content to scale the relative partitioning of decomposing plant material to respiration and mineral stabilized soil C. However, numerous pedon to plot scale studies indicate that other soil mineral parameters, such as Fe- or Al-oxyhydroxide content and specific surface area, may be more effective than clay alone for predicting soil C content and stabilization. Here we directly address the following question: Are there soil physicochemical parameters that represent mineral C association and soil C content that can replace or be used in conjunction with clay content as scalars in soil C models. We explored the relationship of soil C content to a number of soil physicochemical and physiographic parameters using the National Cooperative Soil Survey database that contains horizon level data for > 62,000 pedons spanning global ecoregions and geographic areas. The data indicated significant variation in the degree of correlation among soil C, clay and Fe-/Al-oxyhydroxides with increasing moisture variability. Specifically, dry, water-limited systems (PET/MAP > 1) presented strong positive correlations between clay and soil C, that decreased significantly to little or no correlation in wet, energy-limited systems (PET/MAP < 1). In contrast, the correlation of soil C to oxalate extractable Al+Fe increased significantly with increasing moisture availability. This pattern was particularly well expressed for subsurface B horizons. Multivariate analyses indicated similar patterns, with clear climate and ecosystem level variation in the degree of correlation among soil C and soil physicochemical properties. The results indicate a need to modify current soil C models to incorporate additional C partitioning parameters that better account for climate and ecoregion variability in C stabilization mechanisms.

Protein and Lipid Binding Parameters in Rainbow Trout (Oncorhynchus mykiss) Blood and Liver Fractions to Extrapolate from an in Vitro metabolic Degradation Assay to in Vivo Bioaccumulation Potential of Hydrophobic Organic Chemicals

EPA Science Inventory

Biotransformation reduces the extent to which environmental contaminants accumulate in fish and other aquatic biota. Unfortunately, the tendency for compounds to be metabolized is not easily predicted from physico-chemical properties (e.g., octanol:water partitioning) or an exam...

Application of Multivariable Analysis and FTIR-ATR Spectroscopy to the Prediction of Properties in Campeche Honey

PubMed Central

Pat, Lucio; Ali, Bassam; Guerrero, Armando; Córdova, Atl V.; Garduza, José P.

2016-01-01

Attenuated total reflectance-Fourier transform infrared spectrometry and chemometrics model was used for determination of physicochemical properties (pH, redox potential, free acidity, electrical conductivity, moisture, total soluble solids (TSS), ash, and HMF) in honey samples. The reference values of 189 honey samples of different botanical origin were determined using Association Official Analytical Chemists, (AOAC), 1990; Codex Alimentarius, 2001, International Honey Commission, 2002, methods. Multivariate calibration models were built using partial least squares (PLS) for the measurands studied. The developed models were validated using cross-validation and external validation; several statistical parameters were obtained to determine the robustness of the calibration models: (PCs) optimum number of components principal, (SECV) standard error of cross-validation, (R 2 cal) coefficient of determination of cross-validation, (SEP) standard error of validation, and (R 2 val) coefficient of determination for external validation and coefficient of variation (CV). The prediction accuracy for pH, redox potential, electrical conductivity, moisture, TSS, and ash was good, while for free acidity and HMF it was poor. The results demonstrate that attenuated total reflectance-Fourier transform infrared spectrometry is a valuable, rapid, and nondestructive tool for the quantification of physicochemical properties of honey. PMID:28070445

Optimization of physico-chemical properties of gelatin extracted from fish skin of rainbow trout (Onchorhynchus mykiss).

PubMed

Tabarestani, H Shahiri; Maghsoudlou, Y; Motamedzadegan, A; Mahoonak, A R Sadeghi

2010-08-01

Physico-chemical properties of gelatin extracted from rainbow trout (Onchorhynchus mykiss) skin were optimized using response surface methodology (RSM). Central rotatable composite design was applied to study the combined effects of NaOH concentration (0.01-0.21 N), acetic acid concentration (0.01-0.21 N) and pre-treatment time (1-3h) on yield, molecular weight distribution, gel strength, viscosity and melting point of gelatin. Regression models were developed to predict the variables. Predict values of multiple response at optimal condition were that yield=9.36%, alpha(1)/alpha(2) chain ratio=1.76, beta chain percent=32.81, gel strength=459 g, viscosity=3.2 mPa s and melting point=20.4 degrees C. The optimal condition was obtained using 0.19 N NaOH and 0.121 N acetic acid for 3h. The results showed that the concentration of H(+) during pre-treatment had significant effect on molecular weight distribution, melting point and gel strength. The concentration of OH(-) had significant effect on viscosity and for extraction yield, pretreatment time was the critical factor. (c) 2010 Elsevier Ltd. All rights reserved.

Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

PubMed Central

Hsing, Michael; Byler, Kendall; Cherkasov, Artem

2009-01-01

Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

Comparison of two DSC-based methods to predict drug-polymer solubility.

PubMed

Rask, Malte Bille; Knopp, Matthias Manne; Olesen, Niels Erik; Holm, René; Rades, Thomas

2018-04-05

The aim of the present study was to compare two DSC-based methods to predict drug-polymer solubility (melting point depression method and recrystallization method) and propose a guideline for selecting the most suitable method based on physicochemical properties of both the drug and the polymer. Using the two methods, the solubilities of celecoxib, indomethacin, carbamazepine, and ritonavir in polyvinylpyrrolidone, hydroxypropyl methylcellulose, and Soluplus® were determined at elevated temperatures and extrapolated to room temperature using the Flory-Huggins model. For the melting point depression method, it was observed that a well-defined drug melting point was required in order to predict drug-polymer solubility, since the method is based on the depression of the melting point as a function of polymer content. In contrast to previous findings, it was possible to measure melting point depression up to 20 °C below the glass transition temperature (T g ) of the polymer for some systems. Nevertheless, in general it was possible to obtain solubility measurements at lower temperatures using polymers with a low T g . Finally, for the recrystallization method it was found that the experimental composition dependence of the T g must be differentiable for compositions ranging from 50 to 90% drug (w/w) so that one T g corresponds to only one composition. Based on these findings, a guideline for selecting the most suitable thermal method to predict drug-polymer solubility based on the physicochemical properties of the drug and polymer is suggested in the form of a decision tree. Copyright © 2018 Elsevier B.V. All rights reserved.

Predictive Array Design. A method for sampling combinatorial chemistry library space.

PubMed

Lipkin, M J; Rose, V S; Wood, J

2002-01-01

A method, Predictive Array Design, is presented for sampling combinatorial chemistry space and selecting a subarray for synthesis based on the experimental design method of Latin Squares. The method is appropriate for libraries with three sites of variation. Libraries with four sites of variation can be designed using the Graeco-Latin Square. Simulated annealing is used to optimise the physicochemical property profile of the sub-array. The sub-array can be used to make predictions of the activity of compounds in the all combinations array if we assume each monomer has a relatively constant contribution to activity and that the activity of a compound is composed of the sum of the activities of its constitutive monomers.

High Levels of Sediment Contamination Have Little Influence on Estuarine Beach Fish Communities

PubMed Central

McKinley, Andrew C.; Dafforn, Katherine A.; Taylor, Matthew D.; Johnston, Emma L.

2011-01-01

While contaminants are predicted to have measurable impacts on fish assemblages, studies have rarely assessed this potential in the context of natural variability in physico-chemical conditions within and between estuaries. We investigated links between the distribution of sediment contamination (metals and PAHs), physico-chemical variables (pH, salinity, temperature, turbidity) and beach fish assemblages in estuarine environments. Fish communities were sampled using a beach seine within the inner and outer zones of six estuaries that were either heavily modified or relatively unmodified by urbanization and industrial activity. All sampling was replicated over two years with two periods sampled each year. Shannon diversity, biomass and abundance were all significantly higher in the inner zone of estuaries while fish were larger on average in the outer zone. Strong differences in community composition were also detected between the inner and outer zones. Few differences were detected between fish assemblages in heavily modified versus relatively unmodified estuaries despite high concentrations of sediment contaminants in the inner zones of modified estuaries that exceeded recognized sediment quality guidelines. Trends in species distributions, community composition, abundance, Shannon diversity, and average fish weight were strongly correlated to physico-chemical variables and showed a weaker relationship to sediment metal contamination. Sediment PAH concentrations were not significantly related to the fish assemblage. These findings suggest that variation in some physico-chemical factors (salinity, temperature, pH) or variables that co-vary with these factors (e.g., wave activity or grain size) have a much greater influence on this fish assemblage than anthropogenic stressors such as contamination. PMID:22039470

Fluorophore labeling of a cell-penetrating peptide induces differential effects on its cellular distribution and affects cell viability.

PubMed

Birch, Ditlev; Christensen, Malene Vinther; Staerk, Dan; Franzyk, Henrik; Nielsen, Hanne Mørck

2017-12-01

Cell-penetrating peptides constitute efficient delivery vectors, and studies of their uptake and mechanism of translocation typically involve fluorophore-labeled conjugates. In the present study, the influence of a number of specific fluorophores on the physico-chemical properties and uptake-related characteristics of penetratin were studied. An array of seven fluorophores belonging to distinct structural classes was examined, and the impact of fluorophore labeling on intracellular distribution and cytotoxicity was correlated to the physico-chemical properties of the conjugates. Exposure of several mammalian cell types to fluorophore-penetratin conjugates revealed a strong structure-dependent reduction in viability (1.5- to 20-fold lower IC 50 values as compared to those of non-labeled penetratin). Also, the degree of less severe effects on membrane integrity, as well as intracellular distribution patterns differed among the conjugates. Overall, neutral hydrophobic fluorophores or negatively charged fluorophores conferred less cytotoxicity as compared to the effect exerted by positively charged, hydrophobic fluorophores. The latter conjugates, however, exhibited less membrane association and more clearly defined intracellular distribution patterns. Thus, selection of the appropriate flurophore is critical. Copyright © 2017 Elsevier B.V. All rights reserved.

Variation of Water Quality Parameters with Siltation Depth for River Ichamati Along International Border with Bangladesh Using Multivariate Statistical Techniques

NASA Astrophysics Data System (ADS)

Roy, P. K.; Pal, S.; Banerjee, G.; Biswas Roy, M.; Ray, D.; Majumder, A.

2014-12-01

River is considered as one of the main sources of freshwater all over the world. Hence analysis and maintenance of this water resource is globally considered a matter of major concern. This paper deals with the assessment of surface water quality of the Ichamati river using multivariate statistical techniques. Eight distinct surface water quality observation stations were located and samples were collected. For the samples collected statistical techniques were applied to the physico-chemical parameters and depth of siltation. In this paper cluster analysis is done to determine the relations between surface water quality and siltation depth of river Ichamati. Multiple regressions and mathematical equation modeling have been done to characterize surface water quality of Ichamati river on the basis of physico-chemical parameters. It was found that surface water quality of the downstream river was different from the water quality of the upstream. The analysis of the water quality parameters of the Ichamati river clearly indicate high pollution load on the river water which can be accounted to agricultural discharge, tidal effect and soil erosion. The results further reveal that with the increase in depth of siltation, water quality degraded.

Real-Time Optical Monitoring of Pt Catalyst Under the Potentiodynamic Conditions

NASA Astrophysics Data System (ADS)

Song, Hyeon Don; Lee, Minzae; Kim, Gil-Pyo; Choi, Inhee; Yi, Jongheop

2016-12-01

In situ monitoring of electrode materials reveals detailed physicochemical transition in electrochemical device. The key challenge is to explore the localized features of electrode surfaces, since the performance of an electrochemical device is determined by the summation of local architecture of the electrode material. Adaptive in situ techniques have been developed for numerous investigations; however, they require restricted measurement environments and provide limited information, which has impeded their widespread application. In this study, we realised an optics-based electrochemical in situ monitoring system by combining a dark-field micro/spectroscopy with an electrochemical workstation to investigate the physicochemical behaviours of Pt catalyst. We found that the localized plasmonic trait of a Pt-decorated Au nanoparticle as a model system varied in terms of its intensity and wavelength during the iterations of a cyclic voltammetry test. Furthermore, we show that morphological and compositional changes of the Pt catalyst can be traced in real time using changes in quantified plasmonic characteristics, which is a distinct advantage over the conventional electrochemistry-based in situ monitoring systems. These results indicate the substantial promise of online operando observation in a wide range of electrical energy conversion systems and electrochemical sensing areas.

ADVANCED MOLECULAR DESIGN OF BIOPOLYMERS FOR TRANSMUCOSAL AND INTRACELLULAR DELIVERY OF CHEMOTHERAPEUTIC AGENTS AND BIOLOGICAL THERAPEUTICS

PubMed Central

Liechty, William B.; Caldorera-Moore, Mary; Phillips, Margaret A.; Schoener, Cody; Peppas, Nicholas A.

2011-01-01

Hydrogels have been instrumental in the development of polymeric systems for controlled release of therapeutic agents. These materials are attractive for transmucosal and intracellular drug delivery because of their facile synthesis, inherent biocompatibility, tunable physicochemical properties, and capacity to respond to various physiological stimuli. In this contribution, we outline a multifaceted hydrogel-based approach for expanding the range of therapeutics in oral formulations from classical small-molecule drugs to include proteins, chemotherapeutics, and nucleic acids. Through judicious materials selection and careful design of copolymer composition and molecular architecture, we can engineer systems capable of responding to distinct physiological cues, with tunable physicochemical properties that are optimized to load, protect, and deliver valuable macromolecular payloads to their intended site of action. These hydrogel carriers, including complexation hydrogels, tethered hydrogels, interpenetrating networks, nanoscale hydrogels, and hydrogels with decorated structures are investigated for their ability respond to changes in pH, to load and release insulin and fluorescein, and remain non-toxic to Caco-2 cells. Our results suggest these novel hydrogel networks have great potential for controlled delivery of proteins, chemotherapeutics, and nucleic acids. PMID:21699934

Assessment of a geochemical extraction procedure to determine the solid phase fractionation and bioaccessibility of potentially harmful elements in soils: a case study using the NIST 2710 reference soil.

PubMed

Wragg, Joanna; Cave, Mark

2012-04-13

Three mineral acid sequential extraction regimes (HNO(3) only, HNO(3) followed by HCl and aqua regia) were applied to the NIST 2710 contaminated reference soil. The major and trace element chemical analysis data from the extractions were subjected to a chemometric self-modelling mixture resolution procedure which identified that 12 distinct physico-chemical components were extracted. The fractionation of As, Cd, Ni and Pb between these components were determined. Tentative assignments of the mineralogical sources of the components were made. The human ingestion bioaccessible fraction of As, Cd and Pb were determined using the in vitro BARGE UBM bioaccessibility test and were found to be 51.6%, 68.0% and 68.4% respectively. The relationship between the lability of the physico-chemical components and the bioaccessible fraction of the soils was investigated and the bioaccessible fractions were assigned to specific components. The extraction scheme using aqua regia was found to be the most suitable as it was the only one which extracted the iron sulphide phase in the soil. Copyright © 2012 Elsevier B.V. All rights reserved.

[Physicochemical properties of suplatast tosilate racemate and enantiomers].

PubMed

Ushio, T; Endo, K; Yamamoto, K

1996-11-01

The physicochemical properties of the enantiomer and racemates of suplatast tosilate (ST) were investigated by means of infrared spectroscopy, solid-state 13C CP/MAS NMR spectroscopy, thermal analysis, and X-ray diffraction analysis, and by measuring the solubility and hygroscopy. The infrared and NMR spectra and X-ray diffraction pattern of the enantiomer were distinctly different from those of the racemate. The melting point of the enantiomer was lower than that of the racemate by 5 degrees C, while the solubility of the enantiomer was 1.3 times higher than that of the racemate. The hygroscopic rate of the enantiomer was greater than that of the racemate. These results suggested that ST was classified into a racemic compound crystal. Furthermore, by comparing the relative peak intensity ratios on X-ray diffraction patterns of the crystals with various optical purities prepared by recrystallization, it was found that a mixture of racemic compound crystals and either of racemic mixture crystals or racemic solid solutions was obtained by recrystallization of ST in the content of 0 to 64%ee, while the recrystallization of ST in the content of more than 64%ee led to the formation of racemic mixture crystals or racemic solid solutions.

Drug Distribution. Part 1. Models to Predict Membrane Partitioning.

PubMed

Nagar, Swati; Korzekwa, Ken

2017-03-01

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

The mystery of membrane organization: composition, regulation and physiological relevance of lipid rafts

PubMed Central

Sezgin, Erdinc; Levental, Ilya; Mayor, Satyajit; Eggeling, Christian

2017-01-01

Cellular plasma membranes are laterally heterogeneous, featuring a variety of distinct subcompartments that differ in their biophysical properties and composition. A large body of research has focused on understanding the basis for this heterogeneity and its physiological relevance. The membrane raft hypothesis formalized a physicochemical principle for a subtype of such lateral membrane heterogeneity, wherein the preferential associations of cholesterol and saturated lipids drives the formation of relatively packed (ordered) membrane domains that selectively recruit certain lipids and proteins. Recent years have yielded new insights into this concept and its in vivo relevance, primarily owing to the development of biochemical and biophysical technologies. PMID:28356571

Multiscale Simulations of Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, D. M.; Bakarji, J.

2014-12-01

Discrete, particle-based simulations offer distinct advantages when modeling solute transport and chemical reactions. For example, Brownian motion is often used to model diffusion in complex pore networks, and Gillespie-type algorithms allow one to handle multicomponent chemical reactions with uncertain reaction pathways. Yet such models can be computationally more intensive than their continuum-scale counterparts, e.g., advection-dispersion-reaction equations. Combining the discrete and continuum models has a potential to resolve the quantity of interest with a required degree of physicochemical granularity at acceptable computational cost. We present computational examples of such "hybrid models" and discuss the challenges associated with coupling these two levels of description.

Protein-Protein Interface Predictions by Data-Driven Methods: A Review

PubMed Central

Xue, Li C; Dobbs, Drena; Bonvin, Alexandre M.J.J.; Honavar, Vasant

2015-01-01

Reliably pinpointing which specific amino acid residues form the interface(s) between a protein and its binding partner(s) is critical for understanding the structural and physicochemical determinants of protein recognition and binding affinity, and has wide applications in modeling and validating protein interactions predicted by high-throughput methods, in engineering proteins, and in prioritizing drug targets. Here, we review the basic concepts, principles and recent advances in computational approaches to the analysis and prediction of protein-protein interfaces. We point out caveats for objectively evaluating interface predictors, and discuss various applications of data-driven interface predictors for improving energy model-driven protein-protein docking. Finally, we stress the importance of exploiting binding partner information in reliably predicting interfaces and highlight recent advances in this emerging direction. PMID:26460190

Biogeographical patterns of bacterial and archaeal communities from distant hypersaline environments.

PubMed

Mora-Ruiz, M Del R; Cifuentes, A; Font-Verdera, F; Pérez-Fernández, C; Farias, M E; González, B; Orfila, A; Rosselló-Móra, R

2018-03-01

Microorganisms are globally distributed but new evidence shows that the microbial structure of their communities can vary due to geographical location and environmental parameters. In this study, 50 samples including brines and sediments from Europe, Spanish-Atlantic and South America were analysed by applying the operational phylogenetic unit (OPU) approach in order to understand whether microbial community structures in hypersaline environments exhibited biogeographical patterns. The fine-tuned identification of approximately 1000 OPUs (almost equivalent to "species") using multivariate analysis revealed regionally distinct taxa compositions. This segregation was more diffuse at the genus level and pointed to a phylogenetic and metabolic redundancy at the higher taxa level, where their different species acquired distinct advantages related to the regional physicochemical idiosyncrasies. The presence of previously undescribed groups was also shown in these environments, such as Parcubacteria, or members of Nanohaloarchaeota in anaerobic hypersaline sediments. Finally, an important OPU overlap was observed between anoxic sediments and their overlaying brines, indicating versatile metabolism for the pelagic organisms. Copyright © 2017 Elsevier GmbH. All rights reserved.

Bioinspired Functionalized Melanin Nanovariants with a Range of Properties Provide Effective Color Matched Photoprotection in Skin.

PubMed

Vij, Manika; Grover, Ritika; Gotherwal, Vishvabandhu; Wani, Naiem Ahmad; Joshi, Prashant; Gautam, Hemlata; Sharma, Kanupriya; Chandna, Sudhir; Gokhale, Rajesh S; Rai, Rajkishor; Ganguli, Munia; Natarajan, Vivek T

2016-09-12

Melanin and related polydopamine hold great promise; however, restricted fine-tunabilility limits their usefulness in biocompatible applications. In the present study, by taking a biomimetic approach, we synthesize peptide-derived melanin with a range of physicochemical properties. Characterization of these melanin polymers indicates that they exist as nanorange materials with distinct size distribution, shapes, and surface charges. These variants demonstrate similar absorption spectra but have different optical properties that correlate with particle size. Our approach enables incorporation of chemical groups to create functionalized polyvalent organic nanomaterials and enables customization of melanin. Further, we establish that these synthetic variants are efficiently taken up by the skin keratinocytes, display appreciable photoprotection with minimal cytotoxicity, and thereby function as effective color matched photoprotective agents. In effect we demonstrate that an array of functionalized melanins with distinct properties could be synthesized using bioinspired green chemistry, and these are of immense utility in generating customized melanin/polydopamine like materials.

[A comparison of the properties of bacteriocins formed by Lactococcus lactis subsp. lactis strains of diverse origin].

PubMed

Stoianova, L G; Egorov, N S; Fedorova, G B; Katrukha, G S; Netrusov, A I

2007-01-01

Bacteriocins formed by four strains of Lactococcus lactis subsp. lactis have been studied and compared: 729 (a natural strain isolated from milk), 1605 (a mutant of strain 729), F-116 (a recombinant obtained by fusing of protoplasts of the two related strain 729 and 1605), and a nisin-forming strain obtained by adaptive selection at Moscow State University. Antimicrobial activity studies revealed differences between the strains in the effects on individual groups of microorganisms; the activities of the strains were also distinct from that of Nisaplin (a commercial preparation of the bacteriocin nisin). Methods for isolation and purification of bacteriocins have been developed, making it possible to obtain individual components of antibiotic complexes as chromatographically pure preparations. Bacteriocins formed by the strains of Lactococcus lactis subsp. lactis have been identified and differences in their biological and physicochemical properties, established. A novel potent broad-spectrum antibiotic substance distinct from nisin has been isolated from the recombinant strain F-116.

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

Experimental determination of solvent-water partition coefficients and Abraham parameters for munition constituents.

PubMed

Liang, Yuzhen; Kuo, Dave T F; Allen, Herbert E; Di Toro, Dominic M

2016-10-01

There is concern about the environmental fate and effects of munition constituents (MCs). Polyparameter linear free energy relationships (pp-LFERs) that employ Abraham solute parameters can aid in evaluating the risk of MCs to the environment. However, poor predictions using pp-LFERs and ABSOLV estimated Abraham solute parameters are found for some key physico-chemical properties. In this work, the Abraham solute parameters are determined using experimental partition coefficients in various solvent-water systems. The compounds investigated include hexahydro-1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX), hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine (MNX), hexahydro-1,3,5-trinitroso-1,3,5-triazine (TNX), hexahydro-1,3-dinitroso-5- nitro-1,3,5-triazine (DNX), 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitrobenzene (TNB), and 4-nitroanisole. The solvents in the solvent-water systems are hexane, dichloromethane, trichloromethane, octanol, and toluene. The only available reported solvent-water partition coefficients are for octanol-water for some of the investigated compounds and they are in good agreement with the experimental measurements from this study. Solvent-water partition coefficients fitted using experimentally derived solute parameters from this study have significantly smaller root mean square errors (RMSE = 0.38) than predictions using ABSOLV estimated solute parameters (RMSE = 3.56) for the investigated compounds. Additionally, the predictions for various physico-chemical properties using the experimentally derived solute parameters agree with available literature reported values with prediction errors within 0.79 log units except for water solubility of RDX and HMX with errors of 1.48 and 2.16 log units respectively. However, predictions using ABSOLV estimated solute parameters have larger prediction errors of up to 7.68 log units. This large discrepancy is probably due to the missing R2NNO2 and R2NNO2 functional groups in the ABSOLV fragment database. Copyright © 2016. Published by Elsevier Ltd.

Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure - Activity Relationships (PCSAR).

PubMed

Kamath, Padmaja; Fernandez, Alberto; Giralt, Francesc; Rallo, Robert

2015-01-01

Nanoparticles are likely to interact in real-case application scenarios with mixtures of proteins and biomolecules that will absorb onto their surface forming the so-called protein corona. Information related to the composition of the protein corona and net cell association was collected from literature for a library of surface-modified gold and silver nanoparticles. For each protein in the corona, sequence information was extracted and used to calculate physicochemical properties and statistical descriptors. Data cleaning and preprocessing techniques including statistical analysis and feature selection methods were applied to remove highly correlated, redundant and non-significant features. A weighting technique was applied to construct specific signatures that represent the corona composition for each nanoparticle. Using this basic set of protein descriptors, a new Protein Corona Structure-Activity Relationship (PCSAR) that relates net cell association with the physicochemical descriptors of the proteins that form the corona was developed and validated. The features that resulted from the feature selection were in line with already published literature, and the computational model constructed on these features had a good accuracy (R(2)LOO=0.76 and R(2)LMO(25%)=0.72) and stability, with the advantage that the fingerprints based on physicochemical descriptors were independent of the specific proteins that form the corona.

Estimation of Melting Points of Organics.

PubMed

Yalkowsky, Samuel H; Alantary, Doaa

2018-05-01

Unified physicochemical property estimation relationships is a system of empirical and theoretical relationships that relate 20 physicochemical properties of organic molecules to each other and to chemical structure. Melting point is a key parameter in the unified physicochemical property estimation relationships scheme because it is a determinant of several other properties including vapor pressure, and solubility. This review describes the first-principals calculation of the melting points of organic compounds from structure. The calculation is based on the fact that the melting point, T m , is equal to the ratio of the heat of melting, ΔH m , to the entropy of melting, ΔS m . The heat of melting is shown to be an additive constitutive property. However, the entropy of melting is not entirely group additive. It is primarily dependent on molecular geometry, including parameters which reflect the degree of restriction of molecular motion in the crystal to that of the liquid. Symmetry, eccentricity, chirality, flexibility, and hydrogen bonding, each affect molecular freedom in different ways and thus make different contributions to the total entropy of fusion. The relationships of these entropy determining parameters to chemical structure are used to develop a reasonably accurate means of predicting the melting points over 2000 compounds. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

The effects of distinctiveness on memory and metamemory for face-name associations.

PubMed

Watier, Nicholas; Collin, Charles

2012-01-01

We examined the influence of face and name distinctiveness on memory and metamemory for face-name associations. Four types of monitoring judgements were solicited during encoding and retrieval of face-name pairs that contained distinct or typical faces (Experiment 1) or names (Experiment 2). The beneficial effects of distinctiveness on associative memory were symmetrical between faces and names, such that relative to their typical counterparts, distinct faces enhanced memory for names, and distinct names enhanced memory for faces. These effects were also apparent in metamemory. Estimates of prospective and retrospective memory performance were greater for face-name associations that contained a distinct face or name compared with a typical face or name, regardless of whether the distinct item was a cue or target. Moreover, the predictive validity of prospective monitoring improved with name distinctiveness, whereas the predictive validity of retrospective monitoring improved with facial distinctiveness. Our results indicate that distinctiveness affects not only the strength of the association between a face and a name, but also the ability to monitor that association.

Fast, Low-Cost and Non-Destructive Physico-Chemical Analysis of Virgin Olive Oils Using Near-Infrared Reflectance Spectroscopy

PubMed Central

Garrido-Varo, Ana; Sánchez, María-Teresa; De la Haba, María-José; Torres, Irina; Pérez-Marín, Dolores

2017-01-01

Near-Infrared (NIR) Spectroscopy was used for the non-destructive assessment of physico-chemical quality parameters in olive oil. At the same time, the influence of the sample presentation mode (spinning versus static cup) was evaluated using two spectrophotometers with similar optical characteristics. A total of 478 olive oil samples were used to develop calibration models, testing various spectral signal pre-treatments. The models obtained by applying MPLS regression to spectroscopic data yielded promising results for olive oil quality measurements, particularly for acidity, the peroxide index and alkyl and ethyl ester content. The results obtained indicate that this non-invasive technology can be used successfully by the olive oil sector to categorize olive oils, to detect potential fraud and to provide consumers with more reliable information. Although both sample presentation modes yielded comparable results, equations constructed with samples scanned using the spinning mode provided greater predictive capacity. PMID:29144417

Classification of fracture and non-fracture groups by analysis of coherent X-ray scatter

PubMed Central

Dicken, A. J.; Evans, J. P. O.; Rogers, K. D.; Stone, N.; Greenwood, C.; Godber, S. X.; Clement, J. G.; Lyburn, I. D.; Martin, R. M.; Zioupos, P.

2016-01-01

Osteoporotic fractures present a significant social and economic burden, which is set to rise commensurately with the aging population. Greater understanding of the physicochemical differences between osteoporotic and normal conditions will facilitate the development of diagnostic technologies with increased performance and treatments with increased efficacy. Using coherent X-ray scattering we have evaluated a population of 108 ex vivo human bone samples comprised of non-fracture and fracture groups. Principal component fed linear discriminant analysis was used to develop a classification model to discern each condition resulting in a sensitivity and specificity of 93% and 91%, respectively. Evaluating the coherent X-ray scatter differences from each condition supports the hypothesis that a causal physicochemical change has occurred in the fracture group. This work is a critical step along the path towards developing an in vivo diagnostic tool for fracture risk prediction. PMID:27363947

DEGAS: sharing and tracking target compound ideas with external collaborators.

PubMed

Lee, Man-Ling; Aliagas, Ignacio; Dotson, Jennafer; Feng, Jianwen A; Gobbi, Alberto; Heffron, Timothy

2012-02-27

To minimize the risk of failure in clinical trials, drug discovery teams must propose active and selective clinical candidates with good physicochemical properties. An additional challenge is that today drug discovery is often conducted by teams at different geographical locations. To improve the collaborative decision making on which compounds to synthesize, we have implemented DEGAS, an application which enables scientists from Genentech and from collaborating external partners to instantly access the same data. DEGAS was implemented to ensure that only the best target compounds are made and that they are made without duplicate effort. Physicochemical properties and DMPK model predictions are computed for each compound to allow the team to make informed decisions when prioritizing. The synthesis progress can be easily tracked. While developing DEGAS, ease of use was a particular goal in order to minimize the difficulty of training and supporting remote users.

Mining for osteogenic surface topographies: In silico design to in vivo osseo-integration.

PubMed

Hulshof, Frits F B; Papenburg, Bernke; Vasilevich, Aliaksei; Hulsman, Marc; Zhao, Yiping; Levers, Marloes; Fekete, Natalie; de Boer, Meint; Yuan, Huipin; Singh, Shantanu; Beijer, Nick; Bray, Mark-Anthony; Logan, David J; Reinders, Marcel; Carpenter, Anne E; van Blitterswijk, Clemens; Stamatialis, Dimitrios; de Boer, Jan

2017-08-01

Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distinct respiratory responses of soils to complex organic substrate are governed predominantly by soil architecture and its microbial community.

PubMed

Fraser, F C; Todman, L C; Corstanje, R; Deeks, L K; Harris, J A; Pawlett, M; Whitmore, A P; Ritz, K

2016-12-01

Factors governing the turnover of organic matter (OM) added to soils, including substrate quality, climate, environment and biology, are well known, but their relative importance has been difficult to ascertain due to the interconnected nature of the soil system. This has made their inclusion in mechanistic models of OM turnover or nutrient cycling difficult despite the potential power of these models to unravel complex interactions. Using high temporal-resolution respirometery (6 min measurement intervals), we monitored the respiratory response of 67 soils sampled from across England and Wales over a 5 day period following the addition of a complex organic substrate (green barley powder). Four respiratory response archetypes were observed, characterised by different rates of respiration as well as different time-dependent patterns. We also found that it was possible to predict, with 95% accuracy, which type of respiratory behaviour a soil would exhibit based on certain physical and chemical soil properties combined with the size and phenotypic structure of the microbial community. Bulk density, microbial biomass carbon, water holding capacity and microbial community phenotype were identified as the four most important factors in predicting the soils' respiratory responses using a Bayesian belief network. These results show that the size and constitution of the microbial community are as important as physico-chemical properties of a soil in governing the respiratory response to OM addition. Such a combination suggests that the 'architecture' of the soil, i.e. the integration of the spatial organisation of the environment and the interactions between the communities living and functioning within the pore networks, is fundamentally important in regulating such processes.

Effect of cell physicochemical characteristics and motility on bacterial transport in groundwater

USGS Publications Warehouse

Becker, M.W.; Collins, S.A.; Metge, D.W.; Harvey, R.W.; Shapiro, A.M.

2004-01-01

The influence of physicochemical characteristics and motility on bacterial transport in groundwater were examined in flow-through columns. Four strains of bacteria isolated from a crystalline rock groundwater system were investigated, with carboxylate-modified and amidine-modified latex microspheres and bromide as reference tracers. The bacterial isolates included a gram-positive rod (ML1), a gram-negative motile rod (ML2), a nonmotile mutant of ML2 (ML2m), and a gram-positive coccoid (ML3). Experiments were repeated at two flow velocities, in a glass column packed with glass beads, and in another packed with iron-oxyhydroxide coated glass beads. Bacteria breakthrough curves were interpreted using a transport equation that incorporates a sorption model from microscopic observation of bacterial deposition in flow-cell experiments. The model predicts that bacterial desorption rate will decrease exponentially with the amount of time the cell is attached to the solid surface. Desorption kinetics appeared to influence transport at the lower flow rate, but were not discernable at the higher flow rate. Iron-oxyhydroxide coatings had a lower-than-expected effect on bacterial breakthrough and no effect on the microsphere recovery in the column experiments. Cell wall type and shape also had minor effects on breakthrough. Motility tended to increase the adsorption rate, and decrease the desorption rate. The transport model predicts that at field scale, desorption rate kinetics may be important to the prediction of bacteria transport rates. ?? 2003 Elsevier B.V. All rights reserved.

A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

PubMed

Grimm, Fabian A; Iwata, Yasuhiro; Sirenko, Oksana; Chappell, Grace A; Wright, Fred A; Reif, David M; Braisted, John; Gerhold, David L; Yeakley, Joanne M; Shepard, Peter; Seligmann, Bruce; Roy, Tim; Boogaard, Peter J; Ketelslegers, Hans B; Rohde, Arlean M; Rusyn, Ivan

2016-08-21

Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of U nknown or V ariable composition, C omplex reaction products, and B iological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments. Here, we present a comprehensive experimental and computational approach to categorize UVCBs according to global similarities in their bioactivity using a suite of in vitro models. We used petroleum substances, an important group of UVCBs which are grouped for regulatory approval and read-across primarily on physico-chemical properties and the manufacturing process, and only partially based on toxicity data, as a case study. We exposed induced pluripotent stem cell-derived cardiomyocytes and hepatocytes to DMSO-soluble extracts of 21 petroleum substances from five product groups. Concentration-response data from high-content imaging in cardiomyocytes and hepatocytes, as well as targeted high-throughput transcriptomic analysis of the hepatocytes, revealed distinct groups of petroleum substances. Data integration showed that bioactivity profiling affords clustering of petroleum substances in a manner similar to the manufacturing process-based categories. Moreover, we observed a high degree of correlation between bioactivity profiles and physico-chemical properties, as well as improved groupings when chemical and biological data were combined. Altogether, we demonstrate how novel in vitro screening approaches can be effectively utilized in combination with physico-chemical characteristics to group complex substances and enable read-across. This approach allows for rapid and scientifically-informed evaluation of health impacts of both existing substances and their chemical alternatives.

Investigation of physicochemical factors affecting the stability of a pH-modulated solid dispersion and a tablet during storage.

PubMed

Tran, Phuong Ha-Lien; Tran, Thao Truong-Dinh; Park, Jun-Bom; Min, Dong Hun; Choi, Han-Gon; Han, Hyo-Kyung; Rhee, Yun-Seok; Lee, Beom-Jin

2011-07-29

The stability of solid dispersions (SD) during storage is of concern. We prepared the pH-modulated SD (pSD) and compressed tablets consisting of polyethylene glycol (PEG) 6000 as a carrier, drug and MgO (alkalizer). Telmisartan (TEL), an ionizable poorly water-soluble drug, was chosen as a model drug. The changes in physicochemical factors such as the dissolution rate, drug crystallinity, microenvironmental pH (pH(M)) and intermolecular interactions of the pSD and the tablets were investigated over 3 months under different temperature and relative humidity (RH) conditions: refrigerator (5-8 °C), 25 °C/32% RH, 25 °C/55% RH, 25 °C/75% RH, 40°C/32% RH, 40 °C/55% RH, and 40 °C/75% RH. Differential scanning calorimetry (DSC) analysis of all samples revealed no distinct changes in the drug melting point. In contrast, powder X-ray diffraction (PXRD) diffractograms revealed that samples stored at 40 °C/75% RH for 1 month, 25 °C/75% RH for 3 months and 40 °C at all humidity conditions for 3 months showed gradual recrystallization of the drug. Fourier transform infrared (FTIR) spectra indicated a reduced intensity of intermolecular interactions between TEL and MgO in the pSD and tablet. The pH(M) also gradually decreased. These altered physicochemical factors under the stressed conditions resulted in decreased dissolution profiles in intestinal fluid (pH 6.8). In contrast, the dissolution rate in gastric fluid (pH 1.2) was almost unchanged because of the high intrinsic solubility of TEL at this pH. Copyright © 2011 Elsevier B.V. All rights reserved.

Horizontal and Vertical Cultural Differences in the Content of Advertising Appeals

PubMed Central

Shavitt, Sharon; Johnson, Timothy P.; Zhang, Jing

2014-01-01

The distinction between vertical (emphasizing hierarchy) and horizontal (valuing equality) cultures yields novel predictions regarding the prevalence of advertising appeals. A content analysis of 1211 magazine advertisements in five countries (Denmark, Korea, Poland, Russia, U.S.) revealed differences in ad content that underscore the value of this distinction. Patterns in the degree to which ads emphasized status benefits and uniqueness benefits corresponded to the countries' vertical/horizontal cultural classification. These and other patterns of ad benefits are analyzed and the predictions afforded by the vertical/horizontal distinction versus the broader individualism-collectivism distinction are compared and tested. PMID:25554720

Horizontal and Vertical Cultural Differences in the Content of Advertising Appeals.

PubMed

Shavitt, Sharon; Johnson, Timothy P; Zhang, Jing

2011-05-01

The distinction between vertical (emphasizing hierarchy) and horizontal (valuing equality) cultures yields novel predictions regarding the prevalence of advertising appeals. A content analysis of 1211 magazine advertisements in five countries (Denmark, Korea, Poland, Russia, U.S.) revealed differences in ad content that underscore the value of this distinction. Patterns in the degree to which ads emphasized status benefits and uniqueness benefits corresponded to the countries' vertical/horizontal cultural classification. These and other patterns of ad benefits are analyzed and the predictions afforded by the vertical/horizontal distinction versus the broader individualism-collectivism distinction are compared and tested.

Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou's pseudo amino acid composition.

PubMed

Chen, Yen-Kuang; Li, Kuo-Bin

2013-02-07

The type information of un-annotated membrane proteins provides an important hint for their biological functions. The experimental determination of membrane protein types, despite being more accurate and reliable, is not always feasible due to the costly laboratory procedures, thereby creating a need for the development of bioinformatics methods. This article describes a novel computational classifier for the prediction of membrane protein types using proteins' sequences. The classifier, comprising a collection of one-versus-one support vector machines, makes use of the following sequence attributes: (1) the cationic patch sizes, the orientation, and the topology of transmembrane segments; (2) the amino acid physicochemical properties; (3) the presence of signal peptides or anchors; and (4) the specific protein motifs. A new voting scheme was implemented to cope with the multi-class prediction. Both the training and the testing sequences were collected from SwissProt. Homologous proteins were removed such that there is no pair of sequences left in the datasets with a sequence identity higher than 40%. The performance of the classifier was evaluated by a Jackknife cross-validation and an independent testing experiments. Results show that the proposed classifier outperforms earlier predictors in prediction accuracy in seven of the eight membrane protein types. The overall accuracy was increased from 78.3% to 88.2%. Unlike earlier approaches which largely depend on position-specific substitution matrices and amino acid compositions, most of the sequence attributes implemented in the proposed classifier have supported literature evidences. The classifier has been deployed as a web server and can be accessed at http://bsaltools.ym.edu.tw/predmpt. Copyright © 2012 Elsevier Ltd. All rights reserved.

Classification and Analysis of Regulatory Pathways Using Graph Property, Biochemical and Physicochemical Property, and Functional Property

PubMed Central

Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418

Predicting Drug Concentration‐Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically‐Based Pharmacokinetic Model

PubMed Central

Yamamoto, Yumi; Välitalo, Pyry A.; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Beukers, Margot W.; van den Berg, Dirk‐Jan; Hartman, Robin; Wong, Yin Cheong; Danhof, Meindert; van Hasselt, John G. C.

2017-01-01

Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System‐specific and drug‐specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration‐time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration‐time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was <91%). In conclusion, the developed PBPK model can be used to predict temporal concentration profiles of drugs in multiple relevant CNS compartments, which we consider valuable information for efficient CNS drug development. PMID:28891201

An In-Depth Investigation into the Physicochemical, Thermal, Microstructural, and Rheological Properties of Petroleum and Natural Asphalts.

PubMed

Nciri, Nader; Kim, Jeonghyun; Kim, Namho; Cho, Namjun

2016-10-21

Over the last decade, unexpected and sudden pavement failures have occurred in several provinces in South Korea. Some of these failures remain unexplained, further illustrating the gaps in our knowledge about binder chemistry. To prevent premature pavement distress and enhance road performance, it is imperative to provide an adequate characterization of asphalt. For this purpose, the current research aims at inspecting the chemistry, microstructure, thermal, and physico-rheological properties of two types of asphalt, namely petroleum asphalt (PA) and natural asphalt (NA). The binders were extensively investigated by using elemental analysis, thin-layer chromatography with flame ionization detection (TLC-FID), matrix-assisted laser desorption ionization time-of-fight mass spectroscopy (MALDI-TOF-MS), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy (RS), Nuclear magnetic resonance spectroscopy (¹H-NMR), ultraviolet and visible spectroscopy (UV-VIS), X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), penetration, softening point, ductility, and viscosity tests. The findings of this research have revealed the distinct variations between the chemical compositions, microstructures, and thermo-rheological properties of the two asphalts and provided valuable knowledge into the characteristics of the binders. Such insight has been effective in predicting the performance or distress of road pavement. This paper will, therefore, be of immediate interest to materials engineers in state highway agencies and asphalt industries.

Long-Term Transport of Cryptosporidium Parvum

NASA Astrophysics Data System (ADS)

Andrea, C.; Harter, T.; Hou, L.; Atwill, E. R.; Packman, A.; Woodrow-Mumford, K.; Maldonado, S.

2005-12-01

The protozoan pathogen Cryptosporidium parvum is a leading cause of waterborne disease. Subsurface transport and filtration in natural and artificial porous media are important components of the environmental pathway of this pathogen. It has been shown that the oocysts of C. parvum show distinct colloidal properties. We conducted a series of laboratory studies on sand columns (column length: 10 cm - 60 cm, flow rates: 0.7 m/d - 30 m/d, ionic strength: 0.01 - 100 mM, filter grain size: 0.2 - 2 mm, various solution chemistry). Breakthrough curves were measured over relatively long time-periods (hundreds to thousands of pore volumes). We show that classic colloid filtration theory is a reasonable tool for predicting the initial breakthrough, but it is inadequate to explain the significant tailing observed in the breakthrough of C. parvum oocyst through sand columns. We discuss the application of the Continuous Time Random Walk approach to account for the strong tailing that was observed in our experiments. The CTRW is generalized transport modeling framework, which includes the classic advection-dispersion equation (ADE), the fractional ADE, and the multi-rate mass transfer model as special cases. Within this conceptual framework, it is possible to distinguish between the contributions of pore-scale geometrical (physical) disorder and of pore-scale physico-chemical heterogeneities (e.g., of the filtration, sorption, desorption processes) to the transport of C. parvum oocysts.

Towards the development of multifunctional molecular indicators combining soil biogeochemical and microbiological variables to predict the ecological integrity of silvicultural practices.

PubMed

Peck, Vincent; Quiza, Liliana; Buffet, Jean-Philippe; Khdhiri, Mondher; Durand, Audrey-Anne; Paquette, Alain; Thiffault, Nelson; Messier, Christian; Beaulieu, Nadyre; Guertin, Claude; Constant, Philippe

2016-05-01

The impact of mechanical site preparation (MSP) on soil biogeochemical structure in young larch plantations was investigated. Soil samples were collected in replicated plots comprising simple trenching, double trenching, mounding and inverting site preparation. Unlogged natural mixed forest areas were used as a reference. Analysis of soil nutrients, abundance of bacteria and gas exchanges unveiled no significant difference among the plots. However, inverting site preparation resulted in higher variations of gas exchanges when compared with trenching, mounding and unlogged natural forest. A combination of the biological and physicochemical variables was used to define a multifunctional classification of the soil samples into four distinct groups categorized as a function of their deviation from baseline ecological conditions. According to this classification model, simple trenching was the approach that represented the lowest ecological risk potential at the microsite level. No relationship was observed between MSP method and soil bacterial community structure as assessed by high-throughput sequencing of bacterial 16S rRNA gene; however, indicator genotypes were identified for each multifunctional soil class. This is the first identification of multifunctional molecular indicators for baseline and disturbed ecological conditions in soil, demonstrating the potential of applied microbial ecology to guide silvicultural practices and ecological risk assessment. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

An In-Depth Investigation into the Physicochemical, Thermal, Microstructural, and Rheological Properties of Petroleum and Natural Asphalts

PubMed Central

Nciri, Nader; Kim, Jeonghyun; Kim, Namho; Cho, Namjun

2016-01-01

Over the last decade, unexpected and sudden pavement failures have occurred in several provinces in South Korea. Some of these failures remain unexplained, further illustrating the gaps in our knowledge about binder chemistry. To prevent premature pavement distress and enhance road performance, it is imperative to provide an adequate characterization of asphalt. For this purpose, the current research aims at inspecting the chemistry, microstructure, thermal, and physico-rheological properties of two types of asphalt, namely petroleum asphalt (PA) and natural asphalt (NA). The binders were extensively investigated by using elemental analysis, thin-layer chromatography with flame ionization detection (TLC-FID), matrix-assisted laser desorption ionization time-of-fight mass spectroscopy (MALDI-TOF-MS), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy (RS), Nuclear magnetic resonance spectroscopy (1H-NMR), ultraviolet and visible spectroscopy (UV-VIS), X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), penetration, softening point, ductility, and viscosity tests. The findings of this research have revealed the distinct variations between the chemical compositions, microstructures, and thermo-rheological properties of the two asphalts and provided valuable knowledge into the characteristics of the binders. Such insight has been effective in predicting the performance or distress of road pavement. This paper will, therefore, be of immediate interest to materials engineers in state highway agencies and asphalt industries. PMID:28773979

Ion-ion correlation, solvent excluded volume and pH effects on physicochemical properties of spherical oxide nanoparticles.

PubMed

Ovanesyan, Zaven; Aljzmi, Amal; Almusaynid, Manal; Khan, Asrar; Valderrama, Esteban; Nash, Kelly L; Marucho, Marcelo

2016-01-15

One major source of complexity in the implementation of nanoparticles in aqueous electrolytes arises from the strong influence that biological environments has on their physicochemical properties. A key parameter for understanding the molecular mechanisms governing the physicochemical properties of nanoparticles is the formation of the surface charge density. In this article, we present an efficient and accurate approach that combines a recently introduced classical solvation density functional theory for spherical electrical double layers with a surface complexation model to account for ion-ion correlation and excluded volume effects on the surface titration of spherical nanoparticles. We apply the proposed computational approach to account for the charge-regulated mechanisms on the surface chemistry of spherical silica (SiO2) nanoparticles. We analyze the effects of the nanoparticle size, as well as pH level and electrolyte concentration of the aqueous solution on the nanoparticle's surface charge density and Zeta potential. We validate our predictions for 580Å and 200Å nanoparticles immersed in acid, neutral and alkaline mono-valent aqueous electrolyte solutions against experimental data. Our results on mono-valent electrolyte show that the excluded volume and ion-ion correlations contribute significantly to the surface charge density and Zeta potential of the nanoparticle at high electrolyte concentration and pH levels, where the solvent crowding effects and electrostatic screening have shown a profound influence on the protonation/deprotonation reactions at the liquid/solute interface. The success of this approach in describing physicochemical properties of silica nanoparticles supports its broader application to study other spherical metal oxide nanoparticles. Copyright © 2015 Elsevier Inc. All rights reserved.

iNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical Properties

PubMed Central

Feng, Peng-Mian; Ding, Chen; Zuo, Yong-Chun; Chou, Kuo-Chen

2012-01-01

Nucleosome positioning has important roles in key cellular processes. Although intensive efforts have been made in this area, the rules defining nucleosome positioning is still elusive and debated. In this study, we carried out a systematic comparison among the profiles of twelve DNA physicochemical features between the nucleosomal and linker sequences in the Saccharomyces cerevisiae genome. We found that nucleosomal sequences have some position-specific physicochemical features, which can be used for in-depth studying nucleosomes. Meanwhile, a new predictor, called iNuc-PhysChem, was developed for identification of nucleosomal sequences by incorporating these physicochemical properties into a 1788-D (dimensional) feature vector, which was further reduced to a 884-D vector via the IFS (incremental feature selection) procedure to optimize the feature set. It was observed by a cross-validation test on a benchmark dataset that the overall success rate achieved by iNuc-PhysChem was over 96% in identifying nucleosomal or linker sequences. As a web-server, iNuc-PhysChem is freely accessible to the public at http://lin.uestc.edu.cn/server/iNuc-PhysChem. For the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented just for the integrity in developing the predictor. Meanwhile, for those who prefer to run predictions in their own computers, the predictor's code can be easily downloaded from the web-server. It is anticipated that iNuc-PhysChem may become a useful high throughput tool for both basic research and drug design. PMID:23144709

Prediction of Physicochemical Properties of Energetic Materials for Identification of Treatment Technologies for Waste Streams

DTIC Science & Technology

2010-11-01

estimate the pharmacokinetics of potential drugs (Horning and Klamt 2005). QSPR/ QSARs also have potential applications in the fuel science field...group contribution methods, and (2) quantitative structure-property/activity relationships (QSPR/ QSAR ). The group contribution methods are primarily...development of QSPR/ QSARs is the identification of the ap- propriate set of descriptors that allow the desired attribute of the compound to be adequately

Calculation of the octanol-water partition coefficient of armchair polyhex BN nanotubes

NASA Astrophysics Data System (ADS)

Mohammadinasab, E.; Pérez-Sánchez, H.; Goodarzi, M.

2017-12-01

A predictive model for determination partition coefficient (log P) of armchair polyhex BN nanotubes by using simple descriptors was built. The relationship between the octanol-water log P and quantum chemical descriptors, electric moments, and topological indices of some armchair polyhex BN nanotubes with various lengths and fixed circumference are represented. Based on density functional theory electric moments and physico-chemical properties of those nanotubes are calculated.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

On the binding affinity of macromolecular interactions: daring to ask why proteins interact

PubMed Central

Kastritis, Panagiotis L.; Bonvin, Alexandre M. J. J.

2013-01-01

Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant (Kd), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition. PMID:23235262

Nanometer Scale Titanium Surface Texturing Are Detected by Signaling Pathways Involving Transient FAK and Src Activations

PubMed Central

Zambuzzi, Willian F.; Bonfante, Estevam A.; Jimbo, Ryo; Hayashi, Mariko; Andersson, Martin; Alves, Gutemberg; Takamori, Esther R.; Beltrão, Paulo J.; Coelho, Paulo G.; Granjeiro, José M.

2014-01-01

Background It is known that physico/chemical alterations on biomaterial surfaces have the capability to modulate cellular behavior, affecting early tissue repair. Such surface modifications are aimed to improve early healing response and, clinically, offer the possibility to shorten the time from implant placement to functional loading. Since FAK and Src are intracellular proteins able to predict the quality of osteoblast adhesion, this study evaluated the osteoblast behavior in response to nanometer scale titanium surface texturing by monitoring FAK and Src phosphorylations. Methodology Four engineered titanium surfaces were used for the study: machined (M), dual acid-etched (DAA), resorbable media microblasted and acid-etched (MBAA), and acid-etch microblasted (AAMB). Surfaces were characterized by scanning electron microscopy, interferometry, atomic force microscopy, x-ray photoelectron spectroscopy and energy dispersive X-ray spectroscopy. Thereafter, those 4 samples were used to evaluate their cytotoxicity and interference on FAK and Src phosphorylations. Both Src and FAK were investigated by using specific antibody against specific phosphorylation sites. Principal Findings The results showed that both FAK and Src activations were differently modulated as a function of titanium surfaces physico/chemical configuration and protein adsorption. Conclusions It can be suggested that signaling pathways involving both FAK and Src could provide biomarkers to predict osteoblast adhesion onto different surfaces. PMID:24999733

Recovering actives in multi-antitarget and target design of analogs of the myosin II inhibitor blebbistatin

NASA Astrophysics Data System (ADS)

Roman, Bart I.; Guedes, Rita C.; Stevens, Christian V.; García-Sosa, Alfonso T.

2018-05-01

In multitarget drug design, it is critical to identify active and inactive compounds against a variety of targets and antitargets. Multitarget strategies thus test the limits of available technology, be that in screening large databases of compounds versus a large number of targets, or in using in silico methods for understanding and reliably predicting these pharmacological outcomes. In this paper, we have evaluated the potential of several in silico approaches to predict the target, antitarget and physicochemical profile of (S)-blebbistatin, the best-known myosin II ATPase inhibitor, and a series of analogs thereof. Standard and augmented structure-based design techniques could not recover the observed activity profiles. A ligand-based method using molecular fingerprints was, however, able to select actives for myosin II inhibition. Using further ligand- and structure-based methods, we also evaluated toxicity through androgen receptor binding, affinity for an array of antitargets and the ADME profile (including assay-interfering compounds) of the series. In conclusion, in the search for (S)-blebbistatin analogs, the dissimilarity distance of molecular fingerprints to known actives and the computed antitarget and physicochemical profile of the molecules can be used for compound design for molecules with potential as tools for modulating myosin II and motility-related diseases.

Quantitative models for predicting adsorption of oxytetracycline, ciprofloxacin and sulfamerazine to swine manures with contrasting properties.

PubMed

Cheng, Dengmiao; Feng, Yao; Liu, Yuanwang; Li, Jinpeng; Xue, Jianming; Li, Zhaojun

2018-09-01

Understanding antibiotic adsorption in livestock manures is crucial to assess the fate and risk of antibiotics in the environment. In this study, three quantitative models developed with swine manure-water distribution coefficients (LgK d ) for oxytetracycline (OTC), ciprofloxacin (CIP) and sulfamerazine (SM1) in swine manures. Physicochemical parameters (n=12) of the swine manure were used as independent variables using partial least-squares (PLSs) analysis. The cumulative cross-validated regression coefficients (Q 2 cum ) values, standard deviations (SDs) and external validation coefficient (Q 2 ext ) ranged from 0.761 to 0.868, 0.027 to 0.064, and 0.743 to 0.827 for the three models; as such, internal and external predictability of the models were strong. The pH, soluble organic carbon (SOC) and nitrogen (SON), and Ca were important explanatory variables for the OTC-Model, pH, SOC, and SON for the CIP-model, and pH, total organic nitrogen (TON), and SOC for the SM1-model. The high VIPs (variable importance in the projections) of pH (1.178-1.396), SOC (0.968-1.034), and SON (0.822 and 0.865) established these physicochemical parameters as likely being dominant (associatively) in affecting transport of antibiotics in swine manures. Copyright © 2018 Elsevier B.V. All rights reserved.

Bacterial biofilm under flow: First a physical struggle to stay, then a matter of breathing.

PubMed

Thomen, Philippe; Robert, Jérôme; Monmeyran, Amaury; Bitbol, Anne-Florence; Douarche, Carine; Henry, Nelly

2017-01-01

Bacterial communities attached to surfaces under fluid flow represent a widespread lifestyle of the microbial world. Through shear stress generation and molecular transport regulation, hydrodynamics conveys effects that are very different by nature but strongly coupled. To decipher the influence of these levers on bacterial biofilms immersed in moving fluids, we quantitatively and simultaneously investigated physicochemical and biological properties of the biofilm. We designed a millifluidic setup allowing to control hydrodynamic conditions and to monitor biofilm development in real time using microscope imaging. We also conducted a transcriptomic analysis to detect a potential physiological response to hydrodynamics. We discovered that a threshold value of shear stress determined biofilm settlement, with sub-piconewton forces sufficient to prevent biofilm initiation. As a consequence, distinct hydrodynamic conditions, which set spatial distribution of shear stress, promoted distinct colonization patterns with consequences on the growth mode. However, no direct impact of mechanical forces on biofilm growth rate was observed. Consistently, no mechanosensing gene emerged from our differential transcriptomic analysis comparing distinct hydrodynamic conditions. Instead, we found that hydrodynamic molecular transport crucially impacts biofilm growth by controlling oxygen availability. Our results shed light on biofilm response to hydrodynamics and open new avenues to achieve informed design of fluidic setups for investigating, engineering or fighting adherent communities.

Bacterial biofilm under flow: First a physical struggle to stay, then a matter of breathing

PubMed Central

Thomen, Philippe; Robert, Jérôme; Monmeyran, Amaury; Bitbol, Anne-Florence; Douarche, Carine; Henry, Nelly

2017-01-01

Bacterial communities attached to surfaces under fluid flow represent a widespread lifestyle of the microbial world. Through shear stress generation and molecular transport regulation, hydrodynamics conveys effects that are very different by nature but strongly coupled. To decipher the influence of these levers on bacterial biofilms immersed in moving fluids, we quantitatively and simultaneously investigated physicochemical and biological properties of the biofilm. We designed a millifluidic setup allowing to control hydrodynamic conditions and to monitor biofilm development in real time using microscope imaging. We also conducted a transcriptomic analysis to detect a potential physiological response to hydrodynamics. We discovered that a threshold value of shear stress determined biofilm settlement, with sub-piconewton forces sufficient to prevent biofilm initiation. As a consequence, distinct hydrodynamic conditions, which set spatial distribution of shear stress, promoted distinct colonization patterns with consequences on the growth mode. However, no direct impact of mechanical forces on biofilm growth rate was observed. Consistently, no mechanosensing gene emerged from our differential transcriptomic analysis comparing distinct hydrodynamic conditions. Instead, we found that hydrodynamic molecular transport crucially impacts biofilm growth by controlling oxygen availability. Our results shed light on biofilm response to hydrodynamics and open new avenues to achieve informed design of fluidic setups for investigating, engineering or fighting adherent communities. PMID:28403171

Towards the discovery of drug-like RNA ligands?

PubMed

Foloppe, Nicolas; Matassova, Natalia; Aboul-Ela, Fareed

2006-11-01

Targeting RNA with small molecule drugs is an area of great potential for therapeutic treatment of infections and possibly genetic and autoimmune diseases. However, a mature set of precedents and established methodology is lacking. The physicochemical properties of RNA raise specific issues and obstacles to development, and contribute to explain the distinct characteristics of natural RNA ligands, including antibiotics. Yet, RNA-targeting strategies are being implemented to reinvigorate antibacterial discovery by using the ribosomal X-ray structures to modify known antibiotics. To exploit further these structures, we suggest the use of existing protein kinase-directed libraries of drug-like compounds to target the A-site of the bacterial ribosome, on the basis of a specific structural hypothesis.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

Chemistry explained by topology: an alternative approach.

PubMed

Galvez, Jorge; Villar, Vincent M; Galvez-Llompart, Maria; Amigó, José M

2011-05-01

Molecular topology can be considered an application of graph theory in which the molecular structure is characterized through a set of graph-theoretical descriptors called topological indices. Molecular topology has found applications in many different fields, particularly in biology, chemistry, and pharmacology. The first topological index was introduced by H. Wiener in 1947 [1]. Although its very first application was the prediction of the boiling points of the alkanes, the Wiener index has demonstrated since then a predictive capability far beyond that. Along with the Wiener index, in this paper we focus on a few pioneering topological indices, just to illustrate the connection between physicochemical properties and molecular connectivity.

Comparative pharmacognostic evaluation of some species of the genera Suaeda and Salsola leaf (Chenopodiaceae).

PubMed

Munir, Uzma; Perveen, Anjum; Qamarunnisa, Syeda

2014-09-01

The genera Suaeda and Salsola are halophytic plants belong to the family Chenopodiaceae. Species of these genera have been extensively used in traditional medicines against many diseases due to their various bioactive compounds such as carotenoids, vitamins, sterol, phenolic compounds etc. The present research was carried out to establish detailed pharmacognosy of Suaeda fruticosa, Suaeda monoica, Salsola imbricata and Salsola tragus, which included macroscopy, microscopy, physico-chemical parameters and qualitative phytochemical screening of leaf samples extracted with methanol and chloroform. It was observed that macroscopic and microscopic characteristics were diagnostic features and can be used for distinction and identification of these closely related plant species. Phytochemically, these plant species are rich in constituents like anthraquinones, alkaloids, carbohydrates, cardiac glycosides, flavonoids, saponins, phenolic compounds and terpenoids. Physico-chemical parameters revealed that in all investigated plant species; methanol extractive values were higher than that of chloroform. Moreover, total ash values were found to be higher than other acid insoluble and water-soluble ash values, while a considerable amount of moisture was present in the species of both genera. On the basis of pharmacognosy, species of Suaeda were found to be more promising than Salsola. Present investigation will contribute towards establishment of pharmacognostic profile of these medicinally effective plants species.

Water characterization and seasonal heavy metal distribution in the Odiel River (Huelva, Spain) by means of principal component analysis.

PubMed

Montes-Botella, C; Tenorio, M D

2003-11-01

The Iberian Pyrite Belt is the largest mass of sulfide and manganese ores in Western Europe. Its sulfide oxidation is the origin of a heavily acidic drainage that affects the Odiel River in southwestern Huelva (Spain). To assess physicochemical, contamination parameters, heavy metal distribution and its seasonal variation in the upper Odiel River and in El Lomero mines, three water samplings were undertaken and analyzed between July 1998 and November 1999. Water from the Odiel River in the polluted zone showed low pH values (2.76-3.51), high heavy metal content, and high values of conductivity (1410-3648 microS/cm) and dissolved solids (1484-5602 mg/L). Principal Component Analysis (PCA) showed that variables related with the products of the pyrite oxidation and the salts that are solubilized by the high acidity generated in the oxidation of sulfides, grouped in the first component, accounted for 40.88% of total variance, and were the main influential factor in physicochemical water sample properties. The second influential factor was minority metals (nickel, cobalt, cadmium). Heavy metals showed three different seasonal patterns, closely related with saline efflorescences formed next to the river bed: majority metals (iron, copper, manganese, zinc); minority metals (lead, nickel, cobalt, cadmium); and chromium, which had a distinctive behavior.

Effects of indigenous yeasts on physicochemical and microbial properties of Korean soy sauce prepared by low-salt fermentation.

PubMed

Song, Young-Ran; Jeong, Do-Youn; Baik, Sang-Ho

2015-10-01

This study deals with understanding the effects of salt reduction on both the physicochemical and microbiological properties of soy sauce fermentation and also the application of indigenous yeast starters to compensate for undesirable changes occurring in salt-reduced processes. Fermentation was tested in situ at a Korean commercial soy sauce processing unit. Salt reduction resulted in higher acidity as well as lower pH and contents of residual sugar and ethanol. Moreover, undesired flavor characteristics, due to a lack of distinctive compounds, was observed. In addition, putrefactive Staphylococcus and Enterococcus spp. were present only during salt-reduced fermentation. To control these adverse effects, a single or mixed culture of two indigenous yeasts, Torulaspora delbrueckii and Pichia guilliermondii, producing high ethanol and 3-methyl-1-butanol, respectively, were tested. Overall, all types of yeast applications inhibited undesirable bacterial growth despite salt reduction. Of the starter cultures tested, the mixed culture resulted in a balance of more complex and richer flavors with an identical flavor profile pattern to that obtained from high salt soy sauce. Hence, this strategy using functional yeast cultures offers a technological option to manufacture salt-reduced soy sauce while preserving its typical sensory characteristics without affecting safety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preparation and characterization of adefovir dipivoxil-stearic acid cocrystal with enhanced physicochemical properties.

PubMed

Seo, Jeong-Woong; Hwang, Kyu-Min; Lee, Sung-Hoon; Kim, Dong-Wook; Park, Eun-Seok

2017-06-11

The objectives of this study were to prepare cocrystal composed of adefovir dipivoxil (AD) and stearic acid (SA) and to investigate the enhanced properties of the cocrystal. The cocrystal was prepared by antisolvent precipitation and characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray powder diffraction (XRPD), and differential scanning calorimetry (DSC). The enhanced properties were evaluated by dissolution testing, permeability studies, and powder rheology analysis. The AD raw material has a cuboid-like crystal and the cocrystal has a needle shape. In the FT-IR study, there were bathochromic shifts caused by the hydrogen bonding. The melting point of the cocrystal was 52.9 °C, which was lower than that of AD. The XRPD pattern also had distinct differences, supporting the formation of a new crystalline form. The cocrystal showed changes in the lattice energy and the solvation strength, which caused an enhanced dissolution. The permeability was increased due to the SA, which acts as a P-gp inhibitor. The tabletability was enhanced due to the altered crystal habit. In conclusion, cocrystal containing AD and SA was successfully prepared, presenting advantages such as enhanced solubility, tabletability, and permeability. The use of the cocrystal is a desirable approach for the improved physicochemical properties.

Polyethylene Films Containing Silver Nanoparticles for Applications in Food Packaging: Characterization of Physico-Chemical and Anti-Microbial Properties.

PubMed

Becaro, Aline A; Puti, Fernanda C; Correa, Daniel S; Paris, Elaine C; Marconcini, José M; Ferreira, Marcos D

2015-03-01

This paper reports the antibacterial effect and physico-chemical characterization of films containing silver nanoparticles for use as food packaging. Two masterbatches (named PEN and PEC) con- taining silver nanoparticles embedded in distinct carriers (silica and titanium dioxide) were mixed with low-density polyethylene (LDPE) in different compositions and extruded to produce plain films. These films were characterized by Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), Differential Scanning Calorimetry (DSC), Thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR). The morphology of the films showed the formation of agglomerates of nanoparticles in both PEN and PEC composites. X-ray analyses confirmed the presence of SiO2 in PEN samples and TiO2 in PEC samples. Thermal analyses indicated an increase in thermal stability of the PEC compositions. The antimicrobial efficacy was determined by applying the test strain for Escherichia coli and Staphylococcus aureus, according to the Japanese Industrial Standard Method (JIS Z 2801:2000). The films analyzed showed antimicrobial properties against the tested microorganisms, presenting better activity against the S. aureus than E. Coli. These findings suggest that LDPE films with silver nanoparticles are promising to provide a significant contribution to the quality and safety of packaged food.

Phytoecdysteroids and flavonoid glycosides among Chilean and commercial sources of Chenopodium quinoa: variation and correlation to physicochemical characteristics

PubMed Central

Graf, Brittany; Rojo, Leonel E.; Delatorre-Herrera, Jose; Poulev, Alexander; Calfio, Camila; Raskin, Ilya

2015-01-01

BACKGROUND Little is known about varietal differences in the content of bioactive phytoecdysteroids (PE) and flavonoid glycosides (FG) from quinoa (Chenopodium quinoa Willd.). The aim of this study was to determine the variation in PE and FG content among seventeen distinct quinoa sources and identify correlations to genotypic (highland vs. lowland) and physicochemical characteristics (seed color, 100-seed weight, protein content, oil content). RESULTS PE and FG concentrations exhibited over 4-fold differences across quinoa sources, ranging from 138 ± 11 μg/g to 570 ± 124 μg/g total PE content and 192 ± 24 μg/g to 804 ± 91 μg/g total FG content. Mean FG content was significantly higher in highland Chilean varieties (583.6 ± 148.9 μg/g) versus lowland varieties (228.2 ± 63.1 μg/g) grown under the same environmental conditions (P = 0.0046; t-test). Meanwhile, PE content was positively and significantly correlated with oil content across all quinoa sources (r = 0.707, P = 0.002; Pearson correlation). CONCLUSION FG content may be genotypically regulated in quinoa. PE content may be increased via enhancement of oil content. These findings may open new avenues for the improvement and development of quinoa as a functional food. PMID:25683633

Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.

PubMed

Sorich, Michael J; McKinnon, Ross A; Miners, John O; Winkler, David A; Smith, Paul A

2004-10-07

This study aimed to evaluate in silico models based on quantum chemical (QC) descriptors derived using the electronegativity equalization method (EEM) and to assess the use of QC properties to predict chemical metabolism by human UDP-glucuronosyltransferase (UGT) isoforms. Various EEM-derived QC molecular descriptors were calculated for known UGT substrates and nonsubstrates. Classification models were developed using support vector machine and partial least squares discriminant analysis. In general, the most predictive models were generated with the support vector machine. Combining QC and 2D descriptors (from previous work) using a consensus approach resulted in a statistically significant improvement in predictivity (to 84%) over both the QC and 2D models and the other methods of combining the descriptors. EEM-derived QC descriptors were shown to be both highly predictive and computationally efficient. It is likely that EEM-derived QC properties will be generally useful for predicting ADMET and physicochemical properties during drug discovery.

Patterns of Limnohabitans Microdiversity across a Large Set of Freshwater Habitats as Revealed by Reverse Line Blot Hybridization

PubMed Central

Jezbera, Jan; Jezberová, Jitka; Kasalický, Vojtěch; Šimek, Karel; Hahn, Martin W.

2013-01-01

Among abundant freshwater Betaproteobacteria, only few groups are considered to be of central ecological importance. One of them is the well-studied genus Limnohabitans and mainly its R-BT subcluster, investigated previously mainly by fluorescence in situ hybridization methods. We designed, based on sequences from a large Limnohabitans culture collection, 18 RLBH (Reverse Line Blot Hybridization) probes specific for different groups within the genus Limnohabitans by targeting diagnostic sequences on their 16 S–23 S rRNA ITS regions. The developed probes covered in sum 92% of the available isolates. This set of probes was applied to environmental DNA originating from 161 different European standing freshwater habitats to reveal the microdiversity (intra-genus) patterns of the Limnohabitans genus along a pH gradient. Investigated habitats differed in various physicochemical parameters, and represented a very broad range of standing freshwater habitats. The Limnohabitans microdiversity, assessed as number of RLBH-defined groups detected, increased significantly along the gradient of rising pH of habitats. 14 out of 18 probes returned detection signals that allowed predictions on the distribution of distinct Limnohabitans groups. Most probe-defined Limnohabitans groups showed preferences for alkaline habitats, one for acidic, and some seemed to lack preferences. Complete niche-separation was indicated for some of the probe-targeted groups. Moreover, bimodal distributions observed for some groups of Limnohabitans, suggested further niche separation between genotypes within the same probe-defined group. Statistical analyses suggested that different environmental parameters such as pH, conductivity, oxygen and altitude influenced the distribution of distinct groups. The results of our study do not support the hypothesis that the wide ecological distribution of Limnohabitans bacteria in standing freshwater habitats results from generalist adaptations of these bacteria. Instead, our observations suggest that the genus Limnohabitans, as well as its R-BT subgroup, represent ecologically heterogeneous taxa, which underwent pronounced ecological diversification. PMID:23554898

A modeling assessment of the physicochemical properties and environmental fate of emerging and novel per- and polyfluoroalkyl substances.

PubMed

Gomis, Melissa Ines; Wang, Zhanyun; Scheringer, Martin; Cousins, Ian T

2015-02-01

Long-chain perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkane sulfonic acids (PFSAs) are persistent, bioaccumulative, and toxic contaminants that are globally present in the environment, wildlife and humans. Phase-out actions and use restrictions to reduce the environmental release of long-chain PFCAs, PFSAs and their precursors have been taken since 2000. In particular, long-chain poly- and perfluoroalkyl substances (PFASs) are being replaced with shorter-chain homologues or other fluorinated or non-fluorinated alternatives. A key question is: are these alternatives, particularly the structurally similar fluorinated alternatives, less hazardous to humans and the environment than the substances they replace? Several fluorinated alternatives including perfluoroether carboxylic acids (PFECAs) and perfluoroether sulfonic acids (PFESAs) have been recently identified. However, the scarcity of experimental data prevents hazard and risk assessments for these substances. In this study, we use state-of-the-art in silico tools to estimate key properties of these newly identified fluorinated alternatives. [i] COSMOtherm and SPARC are used to estimate physicochemical properties. The US EPA EPISuite software package is used to predict degradation half-lives in air, water and soil. [ii] In combination with estimated chemical properties, a fugacity-based multimedia mass-balance unit-world model - the OECD Overall Persistence (POV) and Long-Range Transport Potential (LRTP) Screening Tool - is used to assess the likely environmental fate of these alternatives. Even though the fluorinated alternatives contain some structural differences, their physicochemical properties are not significantly different from those of their predecessors. Furthermore, most of the alternatives are estimated to be similarly persistent and mobile in the environment as the long-chain PFASs. The models therefore predict that the fluorinated alternatives will become globally distributed in the environment similar to their predecessors. Although such in silico methods are coupled with uncertainties, this preliminary assessment provides enough cause for concern to warrant experimental work to better determine the properties of these fluorinated alternatives. Copyright © 2014 Elsevier B.V. All rights reserved.

Isolation and connectivity: Relationships between periodic connection to the ocean and environmental variables in intermittently closed estuaries

NASA Astrophysics Data System (ADS)

Lill, Adrian Wilfred Thomas; Schallenberg, Marc; Lal, Aparna; Savage, Candida; Closs, Gerard Patrick

2013-08-01

Morphometric and physicochemical variables are key determinants of biotic community structure in estuaries and are influenced by changes to estuary mouth state (open/closed). This study examined and compared the consequences of intermittent connection to the ocean on environmental gradients among estuaries; specifically, how estuary morphology and hydrology relate to physical connection to the sea, and the influence of this relationship on the physicochemical environment. By sampling 20 estuaries across New Zealand and using historical aerial photographs, a continuous index of estuarine connection to the ocean was developed and independently validated using berm elevation derived from Airborne Laser Scanning (ALS) data. Using published literature, this index was compared to equivalent indices in South Africa and Australia. A clear relationship between connections to the ocean, freshwater flow and productivity indices underlie the environmental differences between permanently open and intermittently closed estuaries. Consistent patterns across the Southern Hemisphere, albeit with regional variations in estuarine characteristics, suggest that remote sensing is useful for predicting the physicochemical environment of small estuaries across regions. Principal components analysis for Otago estuaries showed that 40% of measured variation in the environment could be attributed to the gradient of relative connectivity (EOI), or isolation (berm elevation) to the ocean. Evaluating these relationships is central to understanding how global and local environmental changes may affect estuarine connectivity regimes and, ultimately, the functioning of estuarine ecosystems.

Environmental risk assessment of selected organic chemicals based on TOC test and QSAR estimation models.

PubMed

Chi, Yulang; Zhang, Huanteng; Huang, Qiansheng; Lin, Yi; Ye, Guozhu; Zhu, Huimin; Dong, Sijun

2018-02-01

Environmental risks of organic chemicals have been greatly determined by their persistence, bioaccumulation, and toxicity (PBT) and physicochemical properties. Major regulations in different countries and regions identify chemicals according to their bioconcentration factor (BCF) and octanol-water partition coefficient (Kow), which frequently displays a substantial correlation with the sediment sorption coefficient (Koc). Half-life or degradability is crucial for the persistence evaluation of chemicals. Quantitative structure activity relationship (QSAR) estimation models are indispensable for predicting environmental fate and health effects in the absence of field- or laboratory-based data. In this study, 39 chemicals of high concern were chosen for half-life testing based on total organic carbon (TOC) degradation, and two widely accepted and highly used QSAR estimation models (i.e., EPI Suite and PBT Profiler) were adopted for environmental risk evaluation. The experimental results and estimated data, as well as the two model-based results were compared, based on the water solubility, Kow, Koc, BCF and half-life. Environmental risk assessment of the selected compounds was achieved by combining experimental data and estimation models. It was concluded that both EPI Suite and PBT Profiler were fairly accurate in measuring the physicochemical properties and degradation half-lives for water, soil, and sediment. However, the half-lives between the experimental and the estimated results were still not absolutely consistent. This suggests deficiencies of the prediction models in some ways, and the necessity to combine the experimental data and predicted results for the evaluation of environmental fate and risks of pollutants. Copyright © 2016. Published by Elsevier B.V.

Prediction of antiviral peptides derived from viral fusion proteins potentially active against herpes simplex and influenza A viruses

PubMed Central

Jesús, Torres; Rogelio, López; Abraham, Cetina; Uriel, López; J- Daniel, García; Alfonso, Méndez-Tenorio; Lilia, Barrón Blanca

2012-01-01

There are very few antiviral drugs available to fight viral infections and the appearance of viral strains resistant to these antivirals is not a rare event. Hence, the design of new antiviral drugs is important. We describe the prediction of peptides with antiviral activity (AVP) derived from the viral glycoproteins involved in the entrance of herpes simplex (HSV) and influenza A viruses into their host cells. It is known, that during this event viral glycoproteins suffer several conformational changes due to protein-protein interactions, which lead to membrane fusion between the viral envelope and the cellular membrane. Our hypothesis is that AVPs can be derived from these viral glycoproteins, specifically from regions highly conserved in amino acid sequences, which at the same time have the physicochemical properties of being highly exposed (antigenic), hydrophilic, flexible, and charged, since these properties are important for protein-protein interactions. For that, we separately analyzed the HSV glycoprotein H and B, and influenza A viruses hemagglutinin (HA), using several bioinformatics tools. A set of multiple alignments was carried out, to find the most conserved regions in the amino acid sequences. Then, the physicochemical properties indicated above were analyzed. We predicted several peptides 12-20 amino acid length which by docking analysis were able to interact with the fusion viral glycoproteins and thus may prevent conformational changes in them, blocking the viral infection. Our strategy to design AVPs seems to be very promising since the peptides were synthetized and their antiviral activities have produced very encouraging results. PMID:23144542

PETRORISK: a risk assessment framework for petroleum substances.

PubMed

Redman, Aaron D; Parkerton, Thomas F; Comber, Mike H I; Paumen, Miriam Leon; Eadsforth, Charles V; Dmytrasz, Bhodan; King, Duncan; Warren, Christopher S; den Haan, Klaas; Djemel, Nadia

2014-07-01

PETRORISK is a modeling framework used to evaluate environmental risk of petroleum substances and human exposure through these routes due to emissions under typical use conditions as required by the European regulation for the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH). Petroleum substances are often complex substances comprised of hundreds to thousands of individual hydrocarbons. The physicochemical, fate, and effects properties of the individual constituents within a petroleum substance can vary over several orders of magnitude, complicating risk assessment. PETRORISK combines the risk assessment strategies used on single chemicals with the hydrocarbon block approach to model complex substances. Blocks are usually defined by available analytical characterization data on substances that are expressed in terms of mass fractions for different structural chemical classes that are specified as a function of C number or boiling point range. The physicochemical and degradation properties of the blocks are determined by the properties of representative constituents in that block. Emissions and predicted exposure concentrations (PEC) are then modeled using mass-weighted individual representative constituents. Overall risk for various environmental compartments at the regional and local level is evaluated by comparing the PECs for individual representative constituents to corresponding predicted no-effect concentrations (PNEC) derived using the Target Lipid Model. Risks to human health are evaluated using the overall predicted human dose resulting from multimedia environmental exposure to a substance-specific derived no-effect level (DNEL). A case study is provided to illustrate how this modeling approach has been applied to assess the risks of kerosene manufacture and use as a fuel. © 2014 SETAC.

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures.

PubMed

Le Bihan, Thierry; Robinson, Mark D; Stewart, Ian I; Figeys, Daniel

2004-01-01

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.

Authentication of vegetable oils on the basis of their physico-chemical properties with the aid of chemometrics.

PubMed

Zhang, Guowen; Ni, Yongnian; Churchill, Jane; Kokot, Serge

2006-09-15

In food production, reliable analytical methods for confirmation of purity or degree of spoilage are required by growers, food quality assessors, processors, and consumers. Seven parameters of physico-chemical properties, such as acid number, colority, density, refractive index, moisture and volatility, saponification value and peroxide value, were measured for quality and adulterated soybean, as well as quality and rancid rapeseed oils. Chemometrics methods were then applied for qualitative and quantitative discrimination and prediction of the oils by methods such exploratory principal component analysis (PCA), partial least squares (PLS), radial basis function-artificial neural networks (RBF-ANN), and multi-criteria decision making methods (MCDM), PROMETHEE and GAIA. In general, the soybean and rapeseed oils were discriminated by PCA, and the two spoilt oils behaved differently with the rancid rapeseed samples exhibiting more object scatter on the PC-scores plot, than the adulterated soybean oil. For the PLS and RBF-ANN prediction methods, suitable training models were devised, which were able to predict satisfactorily the category of the four different oil samples in the verification set. Rank ordering with the use of MCDM models indicated that the oil types can be discriminated on the PROMETHEE II scale. For the first time, it was demonstrated how ranking of oil objects with the use of PROMETHEE and GAIA could be utilized as a versatile indicator of quality performance of products on the basis of a standard selected by the stakeholder. In principle, this approach provides a very flexible method for assessment of product quality directly from the measured data.

Physiologically based pharmacokinetic modeling of PLGA nanoparticles with varied mPEG content

PubMed Central

Li, Mingguang; Panagi, Zoi; Avgoustakis, Konstantinos; Reineke, Joshua

2012-01-01

Biodistribution of nanoparticles is dependent on their physicochemical properties (such as size, surface charge, and surface hydrophilicity). Clear and systematic understanding of nanoparticle properties’ effects on their in vivo performance is of fundamental significance in nanoparticle design, development and optimization for medical applications, and toxicity evaluation. In the present study, a physiologically based pharmacokinetic model was utilized to interpret the effects of nanoparticle properties on previously published biodistribution data. Biodistribution data for five poly(lactic-co-glycolic) acid (PLGA) nanoparticle formulations prepared with varied content of monomethoxypoly (ethyleneglycol) (mPEG) (PLGA, PLGA-mPEG256, PLGA-mPEG153, PLGA-mPEG51, PLGA-mPEG34) were collected in mice after intravenous injection. A physiologically based pharmacokinetic model was developed and evaluated to simulate the mass-time profiles of nanoparticle distribution in tissues. In anticipation that the biodistribution of new nanoparticle formulations could be predicted from the physiologically based pharmacokinetic model, multivariate regression analysis was performed to build the relationship between nanoparticle properties (size, zeta potential, and number of PEG molecules per unit surface area) and biodistribution parameters. Based on these relationships, characterized physicochemical properties of PLGA-mPEG495 nanoparticles (a sixth formulation) were used to calculate (predict) biodistribution profiles. For all five initial formulations, the developed model adequately simulates the experimental data indicating that the model is suitable for description of PLGA-mPEG nanoparticle biodistribution. Further, the predicted biodistribution profiles of PLGA-mPEG495 were close to experimental data, reflecting properly developed property–biodistribution relationships. PMID:22419876

Sweetness prediction of natural compounds.

PubMed

Chéron, Jean-Baptiste; Casciuc, Iuri; Golebiowski, Jérôme; Antonczak, Serge; Fiorucci, Sébastien

2017-04-15

Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450g·mol -1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feature Biases in Early Word Learning: Network Distinctiveness Predicts Age of Acquisition

ERIC Educational Resources Information Center

Engelthaler, Tomas; Hills, Thomas T.

2017-01-01

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge…

Distinctive Features Hold a Privileged Status in the Computation of Word Meaning: Implications for Theories of Semantic Memory

ERIC Educational Resources Information Center

Cree, George S.; McNorgan, Chris; McRae, Ken

2006-01-01

The authors present data from 2 feature verification experiments designed to determine whether distinctive features have a privileged status in the computation of word meaning. They use an attractor-based connectionist model of semantic memory to derive predictions for the experiments. Contrary to central predictions of the conceptual structure…

Spouses’ Attachment Pairings Predict Neuroendocrine, Behavioral, and Psychological Responses to Marital Conflict

PubMed Central

Beck, Lindsey A.; Pietromonaco, Paula R.; DeBuse, Casey J.; Powers, Sally I.; Sayer, Aline G.

2014-01-01

This research investigated how spouses’ attachment styles jointly contributed to their stress responses. Newlywed couples discussed relationship conflicts. Salivary cortisol indexed physiological stress; observer-rated behaviors indexed behavioral stress; self-reported distress indexed psychological stress. Multilevel modeling tested predictions that couples including one anxious and one avoidant partner or two anxious partners would show distinctive stress responses. As predicted, couples with anxious wives and avoidant husbands showed physiological reactivity in anticipation of conflict: Both spouses showed sharp increases in cortisol, followed by rapid declines. These couples also showed distinctive behaviors during conflict: Anxious wives had difficulty recognizing avoidant husbands’ distress, and avoidant husbands had difficulty approaching anxious wives for support. Contrary to predictions, couples including two anxious partners did not show distinctive stress responses. Findings suggest that the fit between partners’ attachment styles can improve understanding of relationships by specifying conditions under which partners’ attachment characteristics jointly influence individual and relationship outcomes. PMID:23773048

Electric field induced microstructures in thin films on physicochemically heterogeneous and patterned substrates.

PubMed

Srivastava, Samanvaya; Reddy, P Dinesh Sankar; Wang, Cindy; Bandyopadhyay, Dipankar; Sharma, Ashutosh

2010-05-07

We study by nonlinear simulations the electric field induced pattern formation in a thin viscous film resting on a topographically or chemically patterned substrate. The thin film microstructures can be aligned to the substrate patterns within a window of parameters where the spinodal length scale of the field induced instability is close to the substrate periodicity. We investigate systematically the change in the film morphology and order when (i) the substrate pattern periodicity is varied at a constant film thickness and (ii) the film thickness is varied at a constant substrate periodicity. Simulations show two distinct pathway of evolution when the substrate-topography changes from protrusions to cavities. The isolated substrate defects generate locally ordered ripplelike structures distinct from the structures on a periodically patterned substrate. In the latter case, film morphology is governed by a competition between the pattern periodicity and the length scale of instability. Relating the thin film morphologies to the underlying substrate pattern has implications for field induced patterning and robustness of inter-interface pattern transfer, e.g., coding-decoding of information printed on a substrate.

Is halogen content the most important factor in the removal of halogenated trace organics by MBR treatment?

PubMed

Hai, Faisal I; Tadkaew, Nichanan; McDonald, James A; Khan, Stuart J; Nghiem, Long D

2011-05-01

This study investigated the relationship between physicochemical properties (namely halogen content and hydrophobicity) of halogenated trace organics and their removal efficiencies by a laboratory scale membrane bioreactor (MBR) under stable operating conditions. The reported results demonstrated a combined effect of halogen content and hydrophobicity on the removal. Compounds with high halogen content (>0.3) were well removed (>85%) when they possessed high hydrophobicity (Log D>3.2), while those with lower Log D values were also well removed if they had low halogen content (<0.1). General indices such as the BIOWIN index (which is based on only biodegradation) or a more specific index such as the halogen content (which captures a chemical aspect) appeared insufficient to predict the removal efficiency of halogenated compounds in MBR. Experimental data confirmed that the ratio of halogen content and Log D, which incorporates two important physico-chemical properties, is comparatively more suitable. Copyright © 2011 Elsevier Ltd. All rights reserved.

Formalized classification of moss litters in swampy spruce forests of intermontane depressions of Kuznetsk Alatau

NASA Astrophysics Data System (ADS)

Efremova, T. T.; Avrova, A. F.; Efremov, S. P.

2016-09-01

The approaches of multivariate statistics have been used for the numerical classification of morphogenetic types of moss litters in swampy spruce forests according to their physicochemical properties (the ash content, decomposition degree, bulk density, pH, mass, and thickness). Three clusters of moss litters— peat, peaty, and high-ash peaty—have been specified. The functions of classification for identification of new objects have been calculated and evaluated. The degree of decomposition and the ash content are the main classification parameters of litters, though all other characteristics are also statistically significant. The final prediction accuracy of the assignment of a litter to a particular cluster is 86%. Two leading factors participating in the clustering of litters have been determined. The first factor—the degree of transformation of plant remains (quality)—specifies 49% of the total variance, and the second factor—the accumulation rate (quantity)— specifies 26% of the total variance. The morphogenetic structure and physicochemical properties of the clusters of moss litters are characterized.

Analysis of the interplay among charge, hydration and shape of proteins through the modeling of their CZE mobility data.

PubMed

Piaggio, Maria V; Peirotti, Marta B; Deiber, Julio A

2009-07-01

Electrophoretic mobility data of four proteins are analyzed and interpreted through a physicochemical CZE model, which provides estimates of quantities like equivalent hydrodynamic radius (size), effective charge number, shape orientation factor, hydration, actual pK values of ionizing groups, and pH near molecule, among others. Protein friction coefficients are simulated through the creeping flow theory of prolate spheroidal particles. The modeling of the effective electrophoretic mobility of proteins requires consideration of hydrodynamic size and shape coupled to hydration and effective charge. The model proposed predicts native protein hydration within the range of values obtained experimentally from other techniques. Therefore, this model provides consistently other physicochemical properties such as average friction and diffusion coefficients and packing fractal dimension. As the pH varies from native conditions to those that are denaturing the protein, hydration and packing fractal dimension change substantially. Needs for further research are also discussed and proposed.

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can.

PubMed

Roque, F O; Guimarães, E A; Ribeiro, M C; Escarpinati, S C; Suriano, M T; Siqueira, T

2014-11-01

Predicting how anthropogenic activities may influence the various components of biodiversity is essential for finding ways to reduce diversity loss. This challenge involves: a) understanding how environmental factors influence diversity across different spatial scales, and b) developing ways to measure these relationships in a way that is fast, economical, and easy to communicate. In this study, we investigate whether landscape and bioclimatic variables could explain variation in biodiversity indices in macroinvertebrate communities from 39 Atlantic Forest streams. In addition to traditional diversity measures, i.e., species richness, abundance and Shannon index, we used a taxonomic distinctness index that measures the degree of phylogenetic relationship among taxa. The amount of variation in the diversity measures that was explained by environmental and spatial variables was estimated using variation partitioning based on multiple regression. Our study demonstrates that taxonomic distinctness does not respond in the same way as the traditional used in biodiversity studies. We found no evidence that taxonomic distinctness responds predictably to variation in landscape metrics, indicating the need for the incorporation of predictors at multiple scales in this type of study. The lack of congruence between taxonomic distinctness and other indices and its low predictability may be related to the fact that this measure expresses long-term evolutionary adaptation to ecosystem conditions, while the other traditional biodiversity metrics respond to short-term environmental changes.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

Main controlling factors and forecasting models of lead accumulation in earthworms based on low-level lead-contaminated soils.

PubMed

Tang, Ronggui; Ding, Changfeng; Ma, Yibing; Wan, Mengxue; Zhang, Taolin; Wang, Xingxiang

2018-06-02

To explore the main controlling factors in soil and build a predictive model between the lead concentrations in earthworms (Pb earthworm ) and the soil physicochemical parameters, 13 soils with low level of lead contamination were used to conduct toxicity experiments using earthworms. The results indicated that a relatively high bioaccumulation factor appeared in the soils with low pH values. The lead concentrations between earthworms and soils after log transformation had a significantly positive correlation (R 2  = 0.46, P < 0.0001, n = 39). Stepwise multiple linear regression analysis derived a fitting empirical model between Pb earthworm and the soil physicochemical properties: log(Pb earthworm ) = 0.96log(Pb soil ) - 0.74log(OC) - 0.22pH + 0.95, (R 2  = 0.66, n = 39). Furthermore, path analysis confirmed that the Pb concentrations in the soil (Pb soil ), soil pH, and soil organic carbon (OC) were the primary controlling factors of Pb earthworm with high pathway parameters (0.71, - 0.51, and - 0.49, respectively). The predictive model based on Pb earthworm in a nationwide range of soils with low-level lead contamination could provide a reference for the establishment of safety thresholds in Pb-contaminated soils from the perspective of soil-animal systems.

Digital image processing and analysis for activated sludge wastewater treatment.

PubMed

Khan, Muhammad Burhan; Lee, Xue Yong; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Malik, Aamir Saeed

2015-01-01

Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

Quantifying the spoilage and shelf-life of yoghurt with fruits.

PubMed

Mataragas, M; Dimitriou, V; Skandamis, P N; Drosinos, E H

2011-05-01

The aim of the present study was to develop a predictive model to quantify the spoilage of yoghurt with fruits. Product samples were stored at various temperatures (5-20 °C). Samples were subjected to microbiological (total viable counts, lactic acid bacteria-LAB, yeasts and moulds) and physico-chemical analysis (pH, titratable acidity and sugars). LAB was the dominant micro-flora. Yeasts population increased at all temperatures but a delay was observed during the first days of storage. Titratable acidity and pH remained almost constant at low temperatures (5 and 10 °C). However, at higher temperatures (>10 °C), an increase in titratable acidity and reduction in pH was observed. Sugar concentration (fructose, lactose and glucose) decreased during storage. A mathematical model was developed for shelf-life determination of the product. It was successfully validated at a temperature (17 °C) not used during model development. The results showed that shelf-life of this product could not be established based only on microbiological data and use of other parameters such as sensory or/and physico-chemical analysis is required. Shelf-life determination by spoilage tests is time-consuming and the need for new rapid techniques has been raised. The developed model could help dairy industries to establish shelf-life predictions on yoghurt with fruits stored under constant temperature conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Probing binding hot spots at protein-RNA recognition sites.

PubMed

Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

PubMed

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Quantitative structure-retention relationship studies with immobilized artificial membrane chromatography II: partial least squares regression.

PubMed

Li, Jie; Sun, Jin; He, Zhonggui

2007-01-26

We aimed to establish quantitative structure-retention relationship (QSRR) with immobilized artificial membrane (IAM) chromatography using easily understood and obtained physicochemical molecular descriptors and to elucidate which descriptors are critical to affect the interaction process between solutes and immobilized phospholipid membranes. The retention indices (logk(IAM)) of 55 structurally diverse drugs were determined on an immobilized artificial membrane column (IAM.PC.DD2) directly or obtained by extrapolation method for highly hydrophobic compounds. Ten simple physicochemical property descriptors (clogP, rings, rotatory bond, hydro-bond counting, etc.) of these drugs were collected and used to establish QSRR and predict the retention data by partial least squares regression (PLSR). Five descriptors, clogP, rotatory bond (RotB), rings, molecular weight (MW) and total surface area (TSA), were reserved by using the Variable Importance for Projection (VIP) values as criterion to build the final PLSR model. An external test set was employed to verify the QSRR based on the training set with the five variables, and QSRR by PLSR exhibited a satisfying predictive ability with R(p)=0.902 and RMSE(p)=0.400. Comparison of coefficients of centered and scaled variables by PLSR demonstrated that, for the descriptors studied, clogP and TSA have the most significant positive effect but the rotatable bond has significant negative effect on drug IAM chromatographic retention.

Spatial and Temporal Correlates of Greenhouse Gas Diffusion from a Hydropower Reservoir in the Southern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mosher, Jennifer; Fortner, Allison M.; Phillips, Jana Randolph

Emissions of CO 2 and CH 4 from freshwater reservoirs constitute a globally significant source of atmospheric greenhouse gases (GHGs), but knowledge gaps remain with regard to spatiotemporal drivers of emissions. We document the spatial and seasonal variation in surface diffusion of CO 2 and CH 4 from Douglas Lake, a hydropower reservoir in Tennessee, USA. Monthly estimates across 13 reservoir sites from January to November 2010 indicated that surface diffusions ranged from 236 to 18,806 mg m -2 day -1 for CO 2 and 0 to 0.95 mg m -2 day -1 for CH 4. Next, we developed statisticalmore » models using spatial and physicochemical variables to predict surface diffusions of CO 2 and CH 4. Models explained 22.7 and 20.9% of the variation in CO 2 and CH4 diffusions, respectively, and identified pH, temperature, dissolved oxygen, and Julian day as the most informative important predictors. These findings provide baseline estimates of GHG emissions from a reservoir in eastern temperate North America a region for which estimates of reservoir GHGs emissions are limited. Our statistical models effectively characterized non-linear and threshold relationships between physicochemical predictors and GHG emissions. Further refinement of such models will aid in predicting current GHG emissions in unsampled reservoirs and forecasting future GHG emissions.« less

Spatial and Temporal Correlates of Greenhouse Gas Diffusion from a Hydropower Reservoir in the Southern United States

DOE PAGES

Mosher, Jennifer; Fortner, Allison M.; Phillips, Jana Randolph; ...

2015-10-29

Emissions of CO 2 and CH 4 from freshwater reservoirs constitute a globally significant source of atmospheric greenhouse gases (GHGs), but knowledge gaps remain with regard to spatiotemporal drivers of emissions. We document the spatial and seasonal variation in surface diffusion of CO 2 and CH 4 from Douglas Lake, a hydropower reservoir in Tennessee, USA. Monthly estimates across 13 reservoir sites from January to November 2010 indicated that surface diffusions ranged from 236 to 18,806 mg m -2 day -1 for CO 2 and 0 to 0.95 mg m -2 day -1 for CH 4. Next, we developed statisticalmore » models using spatial and physicochemical variables to predict surface diffusions of CO 2 and CH 4. Models explained 22.7 and 20.9% of the variation in CO 2 and CH4 diffusions, respectively, and identified pH, temperature, dissolved oxygen, and Julian day as the most informative important predictors. These findings provide baseline estimates of GHG emissions from a reservoir in eastern temperate North America a region for which estimates of reservoir GHGs emissions are limited. Our statistical models effectively characterized non-linear and threshold relationships between physicochemical predictors and GHG emissions. Further refinement of such models will aid in predicting current GHG emissions in unsampled reservoirs and forecasting future GHG emissions.« less

Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point.

PubMed

Dearden, John C

2003-08-01

Boiling point, vapor pressure, and melting point are important physicochemical properties in the modeling of the distribution and fate of chemicals in the environment. However, such data often are not available, and therefore must be estimated. Over the years, many attempts have been made to calculate boiling points, vapor pressures, and melting points by using quantitative structure-property relationships, and this review examines and discusses the work published in this area, and concentrates particularly on recent studies. A number of software programs are commercially available for the calculation of boiling point, vapor pressure, and melting point, and these have been tested for their predictive ability with a test set of 100 organic chemicals.

Motivation to hide emotion and children's understanding of the distinction between real and apparent emotions.

PubMed

Gosselin, Pierre; Warren, Madeleine; Diotte, Michèle

2002-12-01

The authors investigated the extent to which children's understanding of the distinction between real and apparent emotions varied according to the motivation to hide emotions. Children, aged 6-7 and 10-11 years, were read stories designed to elicit either prosocial or self-protective motivated display rules and were asked to predict the facial expressions the protagonists would make to hide felt emotions. Children were found to understand the distinction between real and apparent emotions very well, independently of the type of motivation. Contrary to predictions, boys understood this distinction better than did girls when the motivation to hide positive emotions was prosocial. Children perceived neutralization as the most appropriate strategy to hide felt emotions, followed by masking.

Preparation and Characterization of Mesoporous Nickel derived from Liquid crystalline Template and Evaluation of its Electro catalytic activity towards Methanol Oxidation

NASA Astrophysics Data System (ADS)

Mohanapriya, S.; Renuka devi, R.; Raj, V.

2018-02-01

Mesoporous Nickel has been prepared by electrodeposition using non-ionic surfactant based liquid crystalline template under optimized processing conditions. Physico-chemical properties of mesoporous nickel is systematically characterized through XRD, SEM and AFM analyses. Comparison of electrocatalytic activity of mesoporous nickel with smooth nickel was interrogated using cyclic voltammetry (CV), chronoamperometry (CA) and electrochemical impedance spectroscopy (EIS) analyses. Distinctly enhanced electrocatalytic activity with improved surface poisoning resistance related to mesoporous nickel electrode towards methanol oxidation stems from unique mesoporous morphology. This mesoporous morphology with high surface to volume ratio is highly beneficial to promote active catalytic centers to offer readily accessible Pt catalytic sites for MOR, through facilitating mass and electron transports.

Structural and functional studies on Ribonuclease S, retro S and retro-inverso S peptides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pal-Bhowmick, Ipsita; Pati Pandey, Ramendra; Jarori, Gotam K.

2007-12-21

Ribonuclease S peptide and S protein offer a unique complementation system to understand the finer features of molecular recognition. In the present study the S peptide (1-16), and its retro and retro-inverso analogs have been analyzed for their structural and biological attributes. RPHPLC, CD, and NMR analyses have revealed that the physicochemical and conformational properties of the S peptide are distinct from those of its retro and retro-inverso analogs. On the functional side, while the S peptide complemented the S protein to give RNase activity, was recognized by anti-S peptide antibodies and induced T cell proliferation, neither the retro normore » the retro-inverso S peptides could do so.« less

Hydraulic fracture and resilience of epithelial monolayers under stretch

NASA Astrophysics Data System (ADS)

Arroyo, Marino; Lucantonio, Alessandro; Noselli, Giovanni; Casares, Laura; Desimone, Antonio; Trepat, Xavier

Epithelial monolayers are very simple and prevalent tissues. Their functions include delimiting distinct physicochemical containers and protecting us from pathogens. Epithelial fracture disrupts the mechanical integrity of this barrier, and hence compromises these functions. Here, we show that in addition to the conventional fracture resulting from excessive tissue tension, epithelia can hydraulically fracture under stretch as a result of the poroelastic nature of the matrix. We will provide experimental evidence of this counterintuitive mechanism of fracture, in which cracks appear under compression. Intriguingly, unlike tensional fracture, which is localized and catastrophic, hydraulic epithelial fracture is distributed and reversible. We will also describe the active mechanisms responsible for crack healing, and the physical principles by which the poroelastic matrix contributes to this resilient behavior.

Discovery of a novel, CNS penetrant M4 PAM chemotype based on a 6-fluoro-4-(piperidin-1-yl)quinoline-3-carbonitrile core.

PubMed

Bewley, Blake R; Spearing, Paul K; Weiner, Rebecca L; Luscombe, Vincent B; Zhan, Xiaoyan; Chang, Sichen; Cho, Hyekyung P; Rodriguez, Alice L; Niswender, Colleen M; Conn, P Jeffrey; Bridges, Thomas M; Engers, Darren W; Lindsley, Craig W

2017-09-15

This Letter details the discovery and subsequent optimization of a novel M 4 PAM scaffold based on an 6-fluoro-4-(piperidin-1-yl)quinoline-3-carbonitrile core, which represents a distinct departure from the classical M 4 PAM chemotypes. Optimized compounds in this series demonstrated improved M 4 PAM potency on both human and rat M 4 (4 to 5-fold relative to HTS hit), and displayed attractive physicochemical and DMPK profiles, including good CNS penetration (rat brain:plasma K p =5.3, K p,uu =2.4; MDCK-MDR1 (P-gp) ER=1.1). Copyright © 2017 Elsevier Ltd. All rights reserved.

Detecting math problem solving strategies: an investigation into the use of retrospective self-reports, latency and fMRI data.

PubMed

Tenison, Caitlin; Fincham, Jon M; Anderson, John R

2014-02-01

This research explores how to determine when mathematical problems are solved by retrieval versus computation strategies. Past research has indicated that verbal reports, solution latencies, and neural imaging all provide imperfect indicators of this distinction. Participants in the current study solved mathematical problems involving two distinct problem types, called 'Pyramid' and 'Formula' problems. Participants were given extensive training solving 3 select Pyramid and 3 select Formula problems. Trained problems were highly practiced, whereas untrained problems were not. The distinction between untrained and trained problems was observed in the data. Untrained problems took longer to solve, more often used procedural strategies and showed a greater activation in the horizontal intraparietal sulcus (HIPS) when compared to trained problems. A classifier fit to the neural distinction between trained-untrained problems successfully predicted training within and between the two problem types. We employed this classifier to generate a prediction of strategy use. By combining evidence from the classifier, problem solving latencies, and retrospective reports, we predicted the strategy used to solve each problem in the scanner and gained unexpected insight into the distinction between different strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Recent advances in oral pulsatile drug delivery.

PubMed

Kalantzi, Lida E; Karavas, Evangelos; Koutris, Efthimios X; Bikiaris, Dimitrios N

2009-01-01

Pulsatile drug delivery aims to release drugs on a programmed pattern i.e.: at appropriate time and/or at appropriate site of action. Currently, it is gaining increasing attention as it offers a more sophisticated approach to the traditional sustained drug delivery i.e: a constant amount of drug released per unit time or constant blood levels. Technically, pulsatile drug delivery systems administered via the oral route could be divided into two distinct types, the time controlled delivery systems and the site-specific delivery systems. The simplest pulsatile formulation is a two layer press coated tablet consisted of polymers with different dissolution rates. Homogenicity of the coated barrier is mandatory in order to assure the predictability of the lag time. The disadvantage of such formulation is that the rupture time cannot be always adequately manipulated as it is strongly correlated with the physicochemical properties of the polymer. Gastric retentive systems, systems where the drug is released following a programmed lag phase, chronopharmaceutical drug delivery systems matching human circadian rhythms, multiunit or multilayer systems with various combinations of immediate and sustained-release preparation, are all classified under pulsatile drug delivery systems. On the other hand, site-controlled release is usually controlled by factors such as the pH of the target site, the enzymes present in the intestinal tract and the transit time/pressure of various parts of the intestine. In this review, recent patents on pulsatile drug delivery of oral dosage forms are summarized and discussed.

Relations between water physico-chemistry and benthic algal communities in a northern Canadian watershed: defining reference conditions using multiple descriptors of community structure.

PubMed

Thomas, Kathryn E; Hall, Roland I; Scrimgeour, Garry J

2015-09-01

Defining reference conditions is central to identifying environmental effects of anthropogenic activities. Using a watershed approach, we quantified reference conditions for benthic algal communities and their relations to physico-chemical conditions in rivers in the South Nahanni River watershed, NWT, Canada, in 2008 and 2009. We also compared the ability of three descriptors that vary in terms of analytical costs to define algal community structure based on relative abundances of (i) all algal taxa, (ii) only diatom taxa, and (iii) photosynthetic pigments. Ordination analyses showed that variance in algal community structure was strongly related to gradients in environmental variables describing water physico-chemistry, stream habitats, and sub-watershed structure. Water physico-chemistry and local watershed-scale descriptors differed significantly between algal communities from sites in the Selwyn Mountain ecoregion compared to sites in the Nahanni-Hyland ecoregions. Distinct differences in algal community types between ecoregions were apparent irrespective of whether algal community structure was defined using all algal taxa, diatom taxa, or photosynthetic pigments. Two algal community types were highly predictable using environmental variables, a core consideration in the development of Reference Condition Approach (RCA) models. These results suggest that assessments of environmental impacts could be completed using RCA models for each ecoregion. We suggest that use of algal pigments, a high through-put analysis, is a promising alternative compared to more labor-intensive and costly taxonomic approaches for defining algal community structure.

Atomistic Simulations of Pore Formation and Closure in Lipid Bilayers

PubMed Central

Bennett, W. F. Drew; Sapay, Nicolas; Tieleman, D. Peter

2014-01-01

Cellular membranes separate distinct aqueous compartments, but can be breached by transient hydrophilic pores. A large energetic cost prevents pore formation, which is largely dependent on the composition and structure of the lipid bilayer. The softness of bilayers and the disordered structure of pores make their characterization difficult. We use molecular-dynamics simulations with atomistic detail to study the thermodynamics, kinetics, and mechanism of pore formation and closure in DLPC, DMPC, and DPPC bilayers, with pore formation free energies of 17, 45, and 78 kJ/mol, respectively. By using atomistic computer simulations, we are able to determine not only the free energy for pore formation, but also the enthalpy and entropy, which yields what is believed to be significant new insights in the molecular driving forces behind membrane defects. The free energy cost for pore formation is due to a large unfavorable entropic contribution and a favorable change in enthalpy. Changes in hydrogen bonding patterns occur, with increased lipid-water interactions, and fewer water-water hydrogen bonds, but the total number of overall hydrogen bonds is constant. Equilibrium pore formation is directly observed in the thin DLPC lipid bilayer. Multiple long timescale simulations of pore closure are used to predict pore lifetimes. Our results are important for biological applications, including the activity of antimicrobial peptides and a better understanding of membrane protein folding, and improve our understanding of the fundamental physicochemical nature of membranes. PMID:24411253

The "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability.

PubMed

Derewenda, Zygmunt S; Godzik, Adam

2017-01-01

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e., crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure, and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular "sticky patch" model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer "sticky patches" which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the "sticky patch" model. We discuss state-of-the-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis.

The Curious Case of Orthographic Distinctiveness: Disruption of Categorical Processing

ERIC Educational Resources Information Center

McDaniel, Mark A.; Cahill, Michael J.; Bugg, Julie M.

2016-01-01

How does orthographic distinctiveness affect recall of structured (categorized) word lists? On one theory, enhanced item-specific information (e.g., more distinct encoding) in concert with robust relational information (e.g., categorical information) optimally supports free recall. This predicts that for categorically structured lists,…

Bacterial Composition and Survival on Sahara Dust Particles Transported to the European Alps

PubMed Central

Meola, Marco; Lazzaro, Anna; Zeyer, Josef

2015-01-01

Deposition of Sahara dust (SD) particles is a frequent phenomenon in Europe, but little is known about the viability and composition of the bacterial community transported with SD. The goal of this study was to characterize SD-associated bacteria transported to the European Alps, deposited and entrapped in snow. During two distinct events in February and May 2014, SD particles were deposited and promptly covered by falling snow, thus preserving them in distinct ochre layers within the snowpack. In June 2014, we collected samples at different depths from a snow profile at the Jungfraujoch (Swiss Alps; 3621 m a.s.l.). After filtration, we performed various microbiological and physicochemical analyses of the snow and dust particles therein that originated in Algeria. Our results show that bacteria survive and are metabolically active after the transport to the European Alps. Using high throughput sequencing, we observed distinct differences in bacterial community composition and structure in SD-layers as compared to clean snow layers. Sporulating bacteria were not enriched in the SD-layers; however, phyla with low abundance such as Gemmatimonadetes and Deinococcus-Thermus appeared to be specific bio-indicators for SD. Since many members of these phyla are known to be adapted to arid oligotrophic environments and UV radiation, they are well suited to survive the harsh conditions of long-range airborne transport. PMID:26733988

A mechanistic physicochemical model of carbon dioxide transport in blood.

PubMed

O'Neill, David P; Robbins, Peter A

2017-02-01

A number of mathematical models have been produced that, given the Pco 2 and Po 2 of blood, will calculate the total concentrations for CO 2 and O 2 in blood. However, all these models contain at least some empirical features, and thus do not represent all of the underlying physicochemical processes in an entirely mechanistic manner. The aim of this study was to develop a physicochemical model of CO 2 carriage by the blood to determine whether our understanding of the physical chemistry of the major chemical components of blood together with their interactions is sufficiently strong to predict the physiological properties of CO 2 carriage by whole blood. Standard values are used for the ionic composition of the blood, the plasma albumin concentration, and the hemoglobin concentration. All K m values required for the model are taken from the literature. The distribution of bicarbonate, chloride, and H + ions across the red blood cell membrane follows that of a Gibbs-Donnan equilibrium. The system of equations that results is solved numerically using constraints for mass balance and electroneutrality. The model reproduces the phenomena associated with CO 2 carriage, including the magnitude of the Haldane effect, very well. The structural nature of the model allows various hypothetical scenarios to be explored. Here we examine the effects of 1) removing the ability of hemoglobin to form carbamino compounds; 2) allowing a degree of Cl - binding to deoxygenated hemoglobin; and 3) removing the chloride (Hamburger) shift. The insights gained could not have been obtained from empirical models. This study is the first to incorporate a mechanistic model of chloride-bicarbonate exchange between the erythrocyte and plasma into a full physicochemical model of the carriage of carbon dioxide in blood. The mechanistic nature of the model allowed a theoretical study of the quantitative significance for carbon dioxide transport of carbamino compound formation; the putative binding of chloride to deoxygenated hemoglobin, and the chloride (Hamburger) shift. Copyright © 2017 the American Physiological Society.

A mechanistic physicochemical model of carbon dioxide transport in blood

PubMed Central

O’Neill, David P.

2017-01-01

A number of mathematical models have been produced that, given the Pco2 and Po2 of blood, will calculate the total concentrations for CO2 and O2 in blood. However, all these models contain at least some empirical features, and thus do not represent all of the underlying physicochemical processes in an entirely mechanistic manner. The aim of this study was to develop a physicochemical model of CO2 carriage by the blood to determine whether our understanding of the physical chemistry of the major chemical components of blood together with their interactions is sufficiently strong to predict the physiological properties of CO2 carriage by whole blood. Standard values are used for the ionic composition of the blood, the plasma albumin concentration, and the hemoglobin concentration. All Km values required for the model are taken from the literature. The distribution of bicarbonate, chloride, and H+ ions across the red blood cell membrane follows that of a Gibbs-Donnan equilibrium. The system of equations that results is solved numerically using constraints for mass balance and electroneutrality. The model reproduces the phenomena associated with CO2 carriage, including the magnitude of the Haldane effect, very well. The structural nature of the model allows various hypothetical scenarios to be explored. Here we examine the effects of 1) removing the ability of hemoglobin to form carbamino compounds; 2) allowing a degree of Cl− binding to deoxygenated hemoglobin; and 3) removing the chloride (Hamburger) shift. The insights gained could not have been obtained from empirical models. NEW & NOTEWORTHY This study is the first to incorporate a mechanistic model of chloride-bicarbonate exchange between the erythrocyte and plasma into a full physicochemical model of the carriage of carbon dioxide in blood. The mechanistic nature of the model allowed a theoretical study of the quantitative significance for carbon dioxide transport of carbamino compound formation; the putative binding of chloride to deoxygenated hemoglobin, and the chloride (Hamburger) shift. PMID:27881667

Assessing the risk of pH-dependent absorption for new molecular entities: a novel in vitro dissolution test, physicochemical analysis, and risk assessment strategy.

PubMed

Mathias, Neil R; Xu, Yan; Patel, Dhaval; Grass, Michael; Caldwell, Brett; Jager, Casey; Mullin, Jim; Hansen, Luke; Crison, John; Saari, Amy; Gesenberg, Christoph; Morrison, John; Vig, Balvinder; Raghavan, Krishnaswamy

2013-11-04

Weak base therapeutic agents can show reduced absorption or large pharmacokinetic variability when coadministered with pH-modifying agents, or in achlorhydria disease states, due to reduced dissolution rate and/or solubility at high gastric pH. This is often referred to as pH-effect. The goal of this study was to understand why some drugs exhibit a stronger pH-effect than others. To study this, an API-sparing, two-stage, in vitro microdissolution test was developed to generate drug dissolution, supersaturation, and precipitation kinetic data under conditions that mimic the dynamic pH changes in the gastrointestinal tract. In vitro dissolution was assessed for a chemically diverse set of compounds under high pH and low pH, analogous to elevated and normal gastric pH conditions observed in pH-modifier cotreated and untreated subjects, respectively. Represented as a ratio between the conditions, the in vitro pH-effect correlated linearly with clinical pH-effect based on the Cmax ratio and in a non-linear relationship based on AUC ratio. Additionally, several in silico approaches that use the in vitro dissolution data were found to be reasonably predictive of the clinical pH-effect. To explore the hypothesis that physicochemical properties are predictors of clinical pH-effect, statistical correlation analyses were conducted using linear sequential feature selection and partial least-squares regression. Physicochemical parameters did not show statistically significant linear correlations to clinical pH-effect for this data set, which highlights the complexity and poorly understood nature of the interplay between parameters. Finally, a strategy is proposed for implementation early in clinical development, to systematically assess the risk of clinical pH-effect for new molecular entities that integrates physicochemical analysis and in vitro, in vivo and in silico methods.

What does it take to turn a rock into a badlands material?

NASA Astrophysics Data System (ADS)

Kasanin-Grubin, Milica; Nadal Romero, Estela; Della Seta, Marta; Martinez-Murillo, Juan F.

2016-04-01

Badlands can develop under different climatic conditions ranging from arid to humid on materials that have a complex combination of physico-chemical properties. The aim of this study is to determine the critical material properties for badland development based on current knowledge and new data. For that purpose we analyzed, both using the existing and new data, the importance of the distribution of grain size, mineralogical composition, and physico-chemical properties. Generally, the badland materials are most commonly described as "fine - grained" however, the size of the dominant grain fractions is not the solely important parameter. We argue that there is a critical amount of each size fraction (sand, silt and clay) that makes these materials susceptible to erosion. Furthermore, sorting of the material is an important factor in material susceptibility to erosion. The well-sorted fine sediments are generally considered as materials prone to disintegration and piping, while sediments with a large range of sizes and higher degree of packing are more resistant. However, poorly sorted sediments can also be very erodible and are found in badlands. Besides quartz, feldspar and carbonates, clay minerals are always present in badland materials and these minerals are crucial for badland development.The dominant clay mineral determines the behaviour of badland material, regarding swelling/shrinking, dispersion and crust development. Previous studies have shown that pH, SAR (sodium adsorption ratio), TDS (total dissolved salts), PS (percentage of sodium) and ESP (exchangeable sodium percentage) are distinctive parameters for both eroded and non-eroded slopes in badlands. Furthermore, our findings prove that content of organic carbon (Corg) is also a very important parameter and that materials with high SAR are less dispersive if the Corg is above 3%. In conclusion, this study shows that there are a number of thresholds regarding grain size, mineralogical composition and physico-chemical parameters that have to be met to make sediment a badland material.

Enhancing physicochemical properties of emulsions by heteroaggregation of oppositely charged lactoferrin coated lutein droplets and whey protein isolate coated DHA droplets.

PubMed

Li, Xin; Wang, Xu; Xu, Duoxia; Cao, Yanping; Wang, Shaojia; Wang, Bei; Sun, Baoguo; Yuan, Fang; Gao, Yanxiang

2018-01-15

The formation and physicochemical stability of mixed functional components (lutein & DHA) emulsions through heteroaggregation were studied. It was formed by controlled heteroaggregation of oppositely charged lutein and DHA droplets coated by cationic lactoferrin (LF) and anionic whey protein isolate (WPI), respectively. Heteroaggregation was induced by mixing the oppositely charged LF-lutein and WPI-DHA emulsions together at pH 6.0. Droplet size, zeta-potential, transmission-physical stability, microrheological behavior and microstructure of the heteroaggregates formed were measured as a function of LF-lutein to WPI-DHA droplet ratio. Lutein degradation and DHA oxidation by measurement of lipid hydroperoxides and thiobarbituric acid reactive substances were determined. Upon mixing the two types of bioactive compounds droplets together, it was found that the largest aggregates and highest physical stability occurred at a droplet ratio of 40% LF-lutein droplets to 60% WPI-DHA droplets. Heteroaggregates formation altered the microrheological properties of the mixed emulsions mainly by the special network structure of the droplets. When LF-coated lutein droplets ratios were more than 30% and less than 60%, the mixed emulsions exhibited distinct decreases in the Mean Square Displacement, which indicated that their limited scope of Brownian motion and stable structure. Mixed emulsions with LF-lutein/WPI-DHA droplets ratio of 4:6 exhibited Macroscopic Viscosity Index with 13 times and Elasticity Index with 3 times of magnitudes higher than the individual emulsions from which they were prepared. Compared with the WPI-DHA emulsion or LF-lutein emulsion, the oxidative stability of the heteroaggregate of LF-lutein/WPI-DHA emulsions was improved. Heteroaggregates formed by oppositely charged bioactive compounds droplets may be useful for creating specific food structures that lead to desirable physicochemical properties, such as microrheological property, physical and chemical stabilities. Copyright © 2017 Elsevier Ltd. All rights reserved.

A chemical–biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6gc01147k Click here for additional data file.

PubMed Central

Grimm, Fabian A.; Iwata, Yasuhiro; Sirenko, Oksana; Chappell, Grace A.; Wright, Fred A.; Reif, David M.; Braisted, John; Gerhold, David L.; Yeakley, Joanne M.; Shepard, Peter; Seligmann, Bruce; Roy, Tim; Boogaard, Peter J.; Ketelslegers, Hans B.; Rohde, Arlean M.

2016-01-01

Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments. Here, we present a comprehensive experimental and computational approach to categorize UVCBs according to global similarities in their bioactivity using a suite of in vitro models. We used petroleum substances, an important group of UVCBs which are grouped for regulatory approval and read-across primarily on physico-chemical properties and the manufacturing process, and only partially based on toxicity data, as a case study. We exposed induced pluripotent stem cell-derived cardiomyocytes and hepatocytes to DMSO-soluble extracts of 21 petroleum substances from five product groups. Concentration-response data from high-content imaging in cardiomyocytes and hepatocytes, as well as targeted high-throughput transcriptomic analysis of the hepatocytes, revealed distinct groups of petroleum substances. Data integration showed that bioactivity profiling affords clustering of petroleum substances in a manner similar to the manufacturing process-based categories. Moreover, we observed a high degree of correlation between bioactivity profiles and physico-chemical properties, as well as improved groupings when chemical and biological data were combined. Altogether, we demonstrate how novel in vitro screening approaches can be effectively utilized in combination with physico-chemical characteristics to group complex substances and enable read-across. This approach allows for rapid and scientifically-informed evaluation of health impacts of both existing substances and their chemical alternatives. PMID:28035192

FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects.

PubMed

Lagorce, David; Sperandio, Olivier; Galons, Hervé; Miteva, Maria A; Villoutreix, Bruno O

2008-09-24

Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries. We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.

Implications of interfacial characteristics of food foaming agents in foam formulations.

PubMed

Rodríguez Patino, Juan M; Carrera Sánchez, Cecilio; Rodríguez Niño, Ma Rosario

2008-08-05

The manufacture of food dispersions (emulsions and foams) with specific quality attributes depends on the selection of the most appropriate raw materials and processing conditions. These dispersions being thermodynamically unstable require the use of emulsifiers (proteins, lipids, phospholipids, surfactants etc.). Emulsifiers typically coexist in the interfacial layer with specific functions in the processing and properties of the final product. The optimum use of emulsifiers depends on our knowledge of their interfacial physico-chemical characteristics - such as surface activity, amount adsorbed, structure, thickness, topography, ability to desorb (stability), lateral mobility, interactions between adsorbed molecules, ability to change conformation, interfacial rheological properties, etc. -, the kinetics of film formation and other associated physico-chemical properties at fluid interfaces. These monolayers constitute well defined systems for the analysis of food colloids at the micro- and nano-scale level, with several advantages for fundamental studies. In the present review we are concerned with the analysis of physico-chemical properties of emulsifier films at fluid interfaces in relation to foaming. Information about the above properties would be very helpful in the prediction of optimised formulations for food foams. We concluded that at surface pressures lower than that of monolayer saturation the foaming capacity is low, or even zero. A close relationship was observed between foaming capacity and the rate of diffusion of the foaming agent to the air-water interface. However, the foam stability correlates with the properties of the film at long-term adsorption.

A methodological approach to characterize the resilience of aquatic ecosystems with application to Lake Annecy, France

NASA Astrophysics Data System (ADS)

Pinault, J.-L.; Berthier, F.

2007-01-01

We propose a methodological approach to characterize the resilience of aquatic ecosystems with respect to the evolution of environmental parameters as well as their aptitude to adapt to forcings. This method that is applied to Lake Annecy, France, proceeds in three stages. First, according to the depth, variations of physicochemical parameters versus time are separated into three components related to (1) energy transfer through the surface of the lake, (2) the flow of rivers and springs that feed the lake, and (3) long-term evolution of the benthic zone as a consequence of mineral and organic matter loads. Second, dynamics of the lake are deduced by analyzing the physicochemical parameter components related to the three boundary conditions. Third, a stochastic process associated with the transfer models aims to characterize the resilience of the lakes according to forcings. For Lake Annecy, whose dynamics are representative of oligotrophic stratified lakes controlled by decarbonation processes where turnover and mixing occurring once a year in winter, the major consequence is the impoverishment of dissolved oxygen in deep water in autumn due to a temperature increase of the surface water in summer. The simulation raises relevant questions about whether a connection exists between physicochemical parameters and global warming, which should not induce harmful consequences on water quality and biodiversity in deep water. This methodological approach is general since it does not use any physical conceptual model to predict the hydrosystem behavior but uses directly observed data.

Development and Characterization of a Microemulsion System Containing Amphotericin B with Potential Ocular Applications.

PubMed

da Silveira, Walteçá Louis Lima; Damasceno, Bolivar P G L; Ferreira, Laura F; Ribeiro, Izabel L S; Silva, Karolyne S; Silva, André Leandro; Giannini, Maria José Mendes; da Silva-Júnior, Arnóbio Antônio; de Oliveira, Anselmo Gomes; do Egito, E Sócrates Tabosa

2016-01-01

Amphotericin B eye drops are widely used in the treatment of ocular infections. However, amphotericin's toxicity leads to low patient compliance and aggravation of symptoms. This work describes the development of a microemulsion system containing amphotericin B, aiming for its use in ocular applications. The microemulsion was developed by the titration technique. The physicochemical characteristics were determined with both loaded and unloaded amphotericin B-microemulsion. The nanostructures were analyzed by polarized light microscopy. The microdilution method was used to establish the minimum inhibitory concentration against fungal strains, and, therefore, evaluate the microemulsion activity. Additionally, in order to evaluate the microemulsion toxicity an in vitro toxicity assay against red blood cells was performed. The performed studies showed that the presence of amphotericin B loaded into the system did not induce serious changes in the physicochemical properties of the microemulsion when compared to the unloaded system. The spectrophotometric studies depicted amphotericin B-self-associated species, which allow predicting its behavior in vitro. The high pressure liquid chromatography results revealed high drug content entrapment in the microemulsion droplet. Finally, the amphotericin B-microemulsion in vitro susceptibility test showed high activity against Candida strains and a low toxicity profile against red blood cells when compared to Fungizone®. The physicochemical characterization of the microemulsion demonstrated that its characteristics are compatible with the topical ocular route, making it eligible for consideration as a new and interesting amphotericin B-deliverydosage form to be used as eye drop formulation.

Theoretical calculations of physico-chemical and spectroscopic properties of bioinorganic systems: current limits and perspectives.

PubMed

Rokob, Tibor András; Srnec, Martin; Rulíšek, Lubomír

2012-05-21

In the last decade, we have witnessed substantial progress in the development of quantum chemical methodologies. Simultaneously, robust solvation models and various combined quantum and molecular mechanical (QM/MM) approaches have become an integral part of quantum chemical programs. Along with the steady growth of computer power and, more importantly, the dramatic increase of the computer performance to price ratio, this has led to a situation where computational chemistry, when exercised with the proper amount of diligence and expertise, reproduces, predicts, and complements the experimental data. In this perspective, we review some of the latest achievements in the field of theoretical (quantum) bioinorganic chemistry, concentrating mostly on accurate calculations of the spectroscopic and physico-chemical properties of open-shell bioinorganic systems by wave-function (ab initio) and DFT methods. In our opinion, the one-to-one mapping between the calculated properties and individual molecular structures represents a major advantage of quantum chemical modelling since this type of information is very difficult to obtain experimentally. Once (and only once) the physico-chemical, thermodynamic and spectroscopic properties of complex bioinorganic systems are quantitatively reproduced by theoretical calculations may we consider the outcome of theoretical modelling, such as reaction profiles and the various decompositions of the calculated parameters into individual spatial or physical contributions, to be reliable. In an ideal situation, agreement between theory and experiment may imply that the practical problem at hand, such as the reaction mechanism of the studied metalloprotein, can be considered as essentially solved.

Virtual quantification of metabolites by capillary electrophoresis-electrospray ionization-mass spectrometry: predicting ionization efficiency without chemical standards.

PubMed

Chalcraft, Kenneth R; Lee, Richard; Mills, Casandra; Britz-McKibbin, Philip

2009-04-01

A major obstacle in metabolomics remains the identification and quantification of a large fraction of unknown metabolites in complex biological samples when purified standards are unavailable. Herein we introduce a multivariate strategy for de novo quantification of cationic/zwitterionic metabolites using capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) based on fundamental molecular, thermodynamic, and electrokinetic properties of an ion. Multivariate calibration was used to derive a quantitative relationship between the measured relative response factor (RRF) of polar metabolites with respect to four physicochemical properties associated with ion evaporation in ESI-MS, namely, molecular volume (MV), octanol-water distribution coefficient (log D), absolute mobility (mu(o)), and effective charge (z(eff)). Our studies revealed that a limited set of intrinsic solute properties can be used to predict the RRF of various classes of metabolites (e.g., amino acids, amines, peptides, acylcarnitines, nucleosides, etc.) with reasonable accuracy and robustness provided that an appropriate training set is validated and ion responses are normalized to an internal standard(s). The applicability of the multivariate model to quantify micromolar levels of metabolites spiked in red blood cell (RBC) lysates was also examined by CE-ESI-MS without significant matrix effects caused by involatile salts and/or major co-ion interferences. This work demonstrates the feasibility for virtual quantification of low-abundance metabolites and their isomers in real-world samples using physicochemical properties estimated by computer modeling, while providing deeper insight into the wide disparity of solute responses in ESI-MS. New strategies for predicting ionization efficiency in silico allow for rapid and semiquantitative analysis of newly discovered biomarkers and/or drug metabolites in metabolomics research when chemical standards do not exist.

MoRFPred-plus: Computational Identification of MoRFs in Protein Sequences using Physicochemical Properties and HMM profiles.

PubMed

Sharma, Ronesh; Bayarjargal, Maitsetseg; Tsunoda, Tatsuhiko; Patil, Ashwini; Sharma, Alok

2018-01-21

Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that permit interaction with structured protein regions. Upon interaction they undergo a disorder-to-order transition as a result of which their functionality arises. Predicting these MoRFs in disordered protein sequences is a challenging task. In this study, we present MoRFpred-plus, an improved predictor over our previous proposed predictor to identify MoRFs in disordered protein sequences. Two separate independent propensity scores are computed via incorporating physicochemical properties and HMM profiles, these scores are combined to predict final MoRF propensity score for a given residue. The first score reflects the characteristics of a query residue to be part of MoRF region based on the composition and similarity of assumed MoRF and flank regions. The second score reflects the characteristics of a query residue to be part of MoRF region based on the properties of flanks associated around the given residue in the query protein sequence. The propensity scores are processed and common averaging is applied to generate the final prediction score of MoRFpred-plus. Performance of the proposed predictor is compared with available MoRF predictors, MoRFchibi, MoRFpred, and ANCHOR. Using previously collected training and test sets used to evaluate the mentioned predictors, the proposed predictor outperforms these predictors and generates lower false positive rate. In addition, MoRFpred-plus is a downloadable predictor, which makes it useful as it can be used as input to other computational tools. https://github.com/roneshsharma/MoRFpred-plus/wiki/MoRFpred-plus:-Download. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of microbial metabolism and co-occurrence patterns in fracture groundwaters of deep crystalline bedrock at Olkiluoto, Finland

NASA Astrophysics Data System (ADS)

Bomberg, M.; Lamminmäki, T.; Itävaara, M.

2015-08-01

The microbial diversity in oligotrophic isolated crystalline Fennoscandian Shield bedrock fracture groundwaters is great but the core community has not been identified. Here we characterized the bacterial and archaeal communities in 12 water conductive fractures situated at depths between 296 and 798 m by high throughput amplicon sequencing using the Illumina HiSeq platform. The great sequencing depth revealed that up to 95 and 99 % of the bacterial and archaeal communities, respectively, were composed of only a few common species, i.e. the core microbiome. However, the remaining rare microbiome contained over 3 and 6 fold more bacterial and archaeal taxa. Several clusters of co-occurring rare taxa were identified, which correlated significantly with physicochemical parameters, such as salinity, concentration of inorganic or organic carbon, sulphur, pH and depth. The metabolic properties of the microbial communities were predicted using PICRUSt. The rough prediction showed that the metabolic pathways included commonly fermentation, fatty acid oxidation, glycolysis/gluconeogenesis, oxidative phosphorylation and methanogenesis/anaerobic methane oxidation, but carbon fixation through the Calvin cycle, reductive TCA cycle and the Wood-Ljungdahl pathway was also predicted. The rare microbiome is an unlimited source of genomic functionality in all ecosystems. It may consist of remnants of microbial communities prevailing in earlier conditions on Earth, but could also be induced again if changes in their living conditions occur. In this study only the rare taxa correlated with any physicochemical parameters. Thus these microorganisms can respond to environmental change caused by physical or biological factors that may lead to alterations in the diversity and function of the microbial communities in crystalline bedrock environments.

Hemolysis by surfactants--A review.

PubMed

Manaargadoo-Catin, Magalie; Ali-Cherif, Anaïs; Pougnas, Jean-Luc; Perrin, Catherine

2016-02-01

An overview of the use of surfactants for erythrocyte lysis and their cell membrane action mechanisms is given. Erythrocyte membrane characteristics and its association with the cell cytoskeleton are presented in order to complete understanding of the erythrocyte membrane distortion. Cell homeostasis disturbances caused by surfactants might induce changes starting from shape modification to cell lysis. Two main mechanisms are hypothesized in literature which are osmotic lysis and lysis by solubilization even if the boundary between them is not clearly defined. Another specific mechanism based on the formation of membrane pores is suggested in the particular case of saponins. The lytic potency of a surfactant is related to its affinity for the membrane and the modification of the lipid membrane curvature. This is to be related to the surfactant shape defined by its hydrophobic and hydrophilic moieties but also by experimental conditions. As a consequence, prediction of the hemolytic potency of a given surfactant is challenging. Several studies are focused on the relation between surfactant erythrolytic potency and their physico-chemical parameters such as the critical micellar concentration (CMC), the hydrophile-lipophile balance (HLB), the surfactant membrane/water partition coefficient (K) or the packing parameter (P). The CMC is one of the most important factors considered even if a lytic activity cut-off effect points out that the only consideration of CMC not enough predictive. The relation K.CMC must be considered in addition to the CMC to predict the surfactant lytic capacity within the same family of non ionic surfactant. Those surfactant structure/lytic activity studies demonstrate the requirement to take into account a combination of physico-chemical parameters to understand and foresee surfactant lytic potency. Copyright © 2015 Elsevier B.V. All rights reserved.

Chitosan encapsulation of essential oil "cocktails" with well-defined binary Zn(II)-Schiff base species targeting antibacterial medicinal nanotechnology.

PubMed

Halevas, Eleftherios; Nday, Christiane M; Chatzigeorgiou, Evanthia; Varsamis, Vasileios; Eleftheriadou, Despoina; Jackson, Graham E; Litsardakis, Georgios; Lazari, Diamanto; Ypsilantis, Konstantinos; Salifoglou, Athanasios

2017-11-01

The advent of biodegradable nanomaterials with enhanced antibacterial activity stands as a challenge to the global research community. In an attempt to pursue the development of novel antibacterial medicinal nanotechnology, we herein a) synthesized ionic-gelated chitosan nanoparticles, b) compared and evaluated the antibacterial activity of essential oils extracted from nine different herbs (Greek origin) and their combinations with a well-defined antibacterial Zn(II)-Schiff base compound, and c) encapsulated the most effective hybrid combination of Zn(II)-essential oils inside the chitosan matrix, thereby targeting well-formulated nanoparticles of distinct biological impact. The empty and loaded chitosan nanoparticles were physicochemically characterized by FT-IR, Thermogravimetric Analysis (TGA), Scanning Electron Microscopy (SEM), with the entrapment and drug release studies being conducted through UV-Visible and atomic absorption techniques. The antimicrobial properties of the novel hybrid materials were demonstrated against Gram positive (S. aureus, B. subtilis, and B. cereus) and Gram negative (E. coli and X. campestris) bacteria using modified agar diffusion methods. The collective physicochemical profile of the hybrid Zn(II)-essential oil cocktails, formulated so as to achieve optimal activity when loaded to chitosan nanoparticles, signifies the importance of design in the development of efficient nanomedicinal pharmaceuticals a) based on both natural products and biogenic metal ionic cofactors, and b) targeting bacterial infections and drug resistance. Copyright © 2017 Elsevier Inc. All rights reserved.

Bacterial structures and ecosystem functions in glaciated floodplains: contemporary states and potential future shifts

PubMed Central

Freimann, Remo; Bürgmann, Helmut; Findlay, Stuart EG; Robinson, Christopher T

2013-01-01

Glaciated alpine floodplains are responding quickly to climate change through shrinking ice masses. Given the expected future changes in their physicochemical environment, we anticipated variable shifts in structure and ecosystem functioning of hyporheic microbial communities in proglacial alpine streams, depending on present community characteristics and landscape structures. We examined microbial structure and functioning during different hydrologic periods in glacial (kryal) streams and, as contrasting systems, groundwater-fed (krenal) streams. Three catchments were chosen to cover an array of landscape features, including interconnected lakes, differences in local geology and degree of deglaciation. Community structure was assessed by automated ribosomal intergenic spacer analysis and microbial function by potential enzyme activities. We found each catchment to contain a distinct bacterial community structure and different degrees of separation in structure and functioning that were linked to the physicochemical properties of the waters within each catchment. Bacterial communities showed high functional plasticity, although achieved by different strategies in each system. Typical kryal communities showed a strong linkage of structure and function that indicated a major prevalence of specialists, whereas krenal sediments were dominated by generalists. With the rapid retreat of glaciers and therefore altered ecohydrological characteristics, lotic microbial structure and functioning are likely to change substantially in proglacial floodplains in the future. The trajectory of these changes will vary depending on contemporary bacterial community characteristics and landscape structures that ultimately determine the sustainability of ecosystem functioning. PMID:23842653

Towards a molecular understanding of cellulose dissolution in ionic liquids: anion/cation effect, synergistic mechanism and physicochemical aspects.

PubMed

Li, Yao; Wang, Jianji; Liu, Xiaomin; Zhang, Suojiang

2018-05-07

Cellulose is one of the most abundant bio-renewable materials on the earth and its conversion to biofuels provides an appealing way to satisfy the increasing global energy demand. However, before carrying out the process of enzymolysis to glucose or polysaccharides, cellulose needs to be pretreated to overcome its recalcitrance. In recent years, a variety of ionic liquids (ILs) have been found to be effective solvents for cellulose, providing a new, feasible pretreatment strategy. A lot of experimental and computational studies have been carried out to investigate the dissolution mechanism. However, many details are not fully understood, which highlights the necessity to overview the current knowledge of cellulose dissolution and identify the research trend in the future. This perspective summarizes the mechanistic studies and microscopic insights of cellulose dissolution in ILs. Recent investigations of the synergistic effect of cations/anions and the distinctive structural changes of cellulose microfibril in ILs are also reviewed. Besides, understanding the factors controlling the dissolution process, such as the structure of anions/cations, viscosity of ILs, pretreatment temperature, heating rate, etc. , has been discussed from a structural and physicochemical viewpoint. At the end, the existing problems are discussed and future prospects are given. We hope this article would be helpful for deeper understanding of the cellulose dissolution process in ILs and the rational design of more efficient and recyclable ILs.

A novel tri-layered buccal mucoadhesive patch for drug delivery: assessment of nicotine delivery.

PubMed

Rao, Shasha; Song, Yunmei; Peddie, Frank; Evans, Allan M

2011-06-01

The aim of this study was to assess the potential of a novel delivery device for administering drugs that suffer from a high degree of first-pass metabolism. A tri-layered buccal mucoadhesive patch, comprising a medicated dry tablet adhered to a mucoadhesive film, was prepared and characterized by its physicochemical properties and mucoadhesive strength. Nicotine was used as a model drug for the characterization of drug release and drug permeation. The influence of different adsorbents on the release of nicotine base from the patches was evaluated in vitro. Different molecular forms of nicotine (base and complex salt) were evaluated for their effect on release performance and permeation in vitro. Results demonstrated acceptable physicochemical and mucoadhesive properties for the tri-layered patch. Rapid release of nicotine was observed when nicotine base was incorporated with calcium sulfate dihydrate as the adsorbent. Patches incorporating nicotine base showed distinct advantages over those containing nicotine polacrilex, in terms of drug release (complete drug release achieved at 30 vs 60 min) and transmucosal permeation (37.28 ± 4.25 vs 2.87 ± 0.26% of the dose permeating through mucosa within 120 min). The novel tri-layered patch can effectively adhere to, and deliver an active ingredient through the buccal mucosa, confirming its potential for buccal mucoadhesive drug delivery. © 2011 The Authors. JPP © 2011 Royal Pharmaceutical Society.

Impact of protein modification on the protein corona on nanoparticles and nanoparticle-cell interactions.

PubMed

Treuel, Lennart; Brandholt, Stefan; Maffre, Pauline; Wiegele, Sarah; Shang, Li; Nienhaus, G Ulrich

2014-01-28

Recent studies have firmly established that cellular uptake of nanoparticles is strongly affected by the presence and the physicochemical properties of a protein adsorption layer around these nanoparticles. Here, we have modified human serum albumin (HSA), a serum protein often used in model studies of protein adsorption onto nanoparticles, to alter its surface charge distribution and investigated the consequences for protein corona formation around small (radius ∼5 nm), dihydrolipoic acid-coated quantum dots (DHLA-QDs) by using fluorescence correlation spectroscopy. HSA modified by succinic anhydride (HSAsuc) to generate additional carboxyl groups on the protein surface showed a 3-fold decreased binding affinity toward the nanoparticles. A 1000-fold enhanced affinity was observed for HSA modified by ethylenediamine (HSAam) to increase the number of amino functions on the protein surface. Remarkably, HSAsuc formed a much thicker protein adsorption layer (8.1 nm) than native HSA (3.3 nm), indicating that it binds in a distinctly different orientation on the nanoparticle, whereas the HSAam corona (4.6 nm) is only slightly thicker. Notably, protein binding to DHLA-QDs was found to be entirely reversible, independent of the modification. We have also measured the extent and kinetics of internalization of these nanoparticles without and with adsorbed native and modified HSA by HeLa cells. Pronounced variations were observed, indicating that even small physicochemical changes of the protein corona may affect biological responses.

Physicochemical properties and gasification reactivity of the ultrafine semi-char derived from a bench-scale fluidized bed gasifier

NASA Astrophysics Data System (ADS)

Zhang, Yukui; Zhang, Haixia; Zhu, Zhiping; Na, Yongjie; Lu, Qinggang

2017-08-01

Zhundong coalfield is the largest intact coalfield worldwide and fluidized bed gasification has been considered as a promising way to achieve its clean and efficient utilization. The purpose of this study is to investigate the physicochemical properties and gasification reactivity of the ultrafine semi-char, derived from a bench-scale fluidized bed gasifier, using Zhundong coal as fuel. The results obtained are as follows. In comparison to the raw coal, the carbon and ash content of the semi-char increase after partial gasification, but the ash fusion temperatures of them show no significant difference. Particularly, 76.53% of the sodium in the feed coal has released to the gas phase after fluidized bed gasification. The chemical compositions of the semi-char are closely related to its particle size, attributable to the distinctly different natures of diverse elements. The semi-char exhibits a higher graphitization degree, higher BET surface area, and richer meso- and macropores, which results in superior gasification reactivity than the coal char. The chemical reactivity of the semi-char is significantly improved by an increased gasification temperature, which suggests the necessity of regasification of the semi-char at a higher temperature. Consequently, it will be considered feasible that these carbons in the semi-char from fluidized bed gasifiers are reclaimed and reused for the gasification process.

Towards a molecular understanding of cellulose dissolution in ionic liquids: anion/cation effect, synergistic mechanism and physicochemical aspects

PubMed Central

Li, Yao; Wang, Jianji

2018-01-01

Cellulose is one of the most abundant bio-renewable materials on the earth and its conversion to biofuels provides an appealing way to satisfy the increasing global energy demand. However, before carrying out the process of enzymolysis to glucose or polysaccharides, cellulose needs to be pretreated to overcome its recalcitrance. In recent years, a variety of ionic liquids (ILs) have been found to be effective solvents for cellulose, providing a new, feasible pretreatment strategy. A lot of experimental and computational studies have been carried out to investigate the dissolution mechanism. However, many details are not fully understood, which highlights the necessity to overview the current knowledge of cellulose dissolution and identify the research trend in the future. This perspective summarizes the mechanistic studies and microscopic insights of cellulose dissolution in ILs. Recent investigations of the synergistic effect of cations/anions and the distinctive structural changes of cellulose microfibril in ILs are also reviewed. Besides, understanding the factors controlling the dissolution process, such as the structure of anions/cations, viscosity of ILs, pretreatment temperature, heating rate, etc., has been discussed from a structural and physicochemical viewpoint. At the end, the existing problems are discussed and future prospects are given. We hope this article would be helpful for deeper understanding of the cellulose dissolution process in ILs and the rational design of more efficient and recyclable ILs. PMID:29780532

Bacterial structures and ecosystem functions in glaciated floodplains: contemporary states and potential future shifts.

PubMed

Freimann, Remo; Bürgmann, Helmut; Findlay, Stuart E G; Robinson, Christopher T

2013-12-01

Glaciated alpine floodplains are responding quickly to climate change through shrinking ice masses. Given the expected future changes in their physicochemical environment, we anticipated variable shifts in structure and ecosystem functioning of hyporheic microbial communities in proglacial alpine streams, depending on present community characteristics and landscape structures. We examined microbial structure and functioning during different hydrologic periods in glacial (kryal) streams and, as contrasting systems, groundwater-fed (krenal) streams. Three catchments were chosen to cover an array of landscape features, including interconnected lakes, differences in local geology and degree of deglaciation. Community structure was assessed by automated ribosomal intergenic spacer analysis and microbial function by potential enzyme activities. We found each catchment to contain a distinct bacterial community structure and different degrees of separation in structure and functioning that were linked to the physicochemical properties of the waters within each catchment. Bacterial communities showed high functional plasticity, although achieved by different strategies in each system. Typical kryal communities showed a strong linkage of structure and function that indicated a major prevalence of specialists, whereas krenal sediments were dominated by generalists. With the rapid retreat of glaciers and therefore altered ecohydrological characteristics, lotic microbial structure and functioning are likely to change substantially in proglacial floodplains in the future. The trajectory of these changes will vary depending on contemporary bacterial community characteristics and landscape structures that ultimately determine the sustainability of ecosystem functioning.

Effects of dietary fibre on subjective appetite, energy intake and body weight: a systematic review of randomized controlled trials.

PubMed

Wanders, A J; van den Borne, J J G C; de Graaf, C; Hulshof, T; Jonathan, M C; Kristensen, M; Mars, M; Schols, H A; Feskens, E J M

2011-09-01

Dietary fibres are believed to reduce subjective appetite, energy intake and body weight. However, different types of dietary fibre may affect these outcomes differently. The aim of this review was to systematically investigate the available literature on the relationship between dietary fibre types, appetite, acute and long-term energy intake, and body weight. Fibres were grouped according to chemical structure and physicochemical properties (viscosity, solubility and fermentability). Effect rates were calculated as the proportion of all fibre-control comparisons that reduced appetite (n = 58 comparisons), acute energy intake (n = 26), long-term energy intake (n = 38) or body weight (n = 66). For appetite, acute energy intake, long-term energy intake and body weight, there were clear differences in effect rates depending on chemical structure. Interestingly, fibres characterized as being more viscous (e.g. pectins, β-glucans and guar gum) reduced appetite more often than those less viscous fibres (59% vs. 14%), which also applied to acute energy intake (69% vs. 30%). Overall, effects on energy intake and body weight were relatively small, and distinct dose-response relationships were not observed. Short- and long-term effects of dietary fibres appear to differ and multiple mechanisms relating to their different physicochemical properties seem to interplay. This warrants further exploration. © 2011 The Authors. obesity reviews © 2011 International Association for the Study of Obesity.

Agent-specific learning signals for self–other distinction during mentalising

PubMed Central

Dolan, Raymond J.; Kurth-Nelson, Zeb

2018-01-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self–other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self–other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self–other distinction also had a reduced behavioural capacity for self–other distinction and displayed more marked subclinical psychopathological traits. The neural self–other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self–other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker. PMID:29689053

Agent-specific learning signals for self-other distinction during mentalising.

PubMed

Ereira, Sam; Dolan, Raymond J; Kurth-Nelson, Zeb

2018-04-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Prediction error induced motor contagions in human behaviors.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar; Takeuchi, Tatsuya; Nakamoto, Hiroki

2018-05-29

Motor contagions refer to implicit effects on one's actions induced by observed actions. Motor contagions are believed to be induced simply by action observation and cause an observer's action to become similar to the action observed. In contrast, here we report a new motor contagion that is induced only when the observation is accompanied by prediction errors - differences between actions one observes and those he/she predicts or expects. In two experiments, one on whole-body baseball pitching and another on simple arm reaching, we show that the observation of the same action induces distinct motor contagions, depending on whether prediction errors are present or not. In the absence of prediction errors, as in previous reports, participants' actions changed to become similar to the observed action, while in the presence of prediction errors, their actions changed to diverge away from it, suggesting distinct effects of action observation and action prediction on human actions. © 2018, Ikegami et al.

A Unique Autothermal Thermophilic Aerobic Digestion Process Showing a Dynamic Transition of Physicochemical and Bacterial Characteristics from the Mesophilic to the Thermophilic Phase.

PubMed

Tashiro, Yukihiro; Kanda, Kosuke; Asakura, Yuya; Kii, Toshihiko; Cheng, Huijun; Poudel, Pramod; Okugawa, Yuki; Tashiro, Kosuke; Sakai, Kenji

2018-03-15

A unique autothermal thermophilic aerobic digestion (ATAD) process has been used to convert human excreta to liquid fertilizer in Japan. This study investigated the changes in physicochemical and bacterial community characteristics during the full-scale ATAD process operated for approximately 3 weeks in 2 different years. After initiating simultaneous aeration and mixing using an air-inducing circulator (aerator), the temperature autothermally increased rapidly in the first 1 to 2 days with exhaustive oxygen consumption, leading to a drastic decrease and gradual increase in oxidation-reduction potential in the first 2 days, reached >50°C in the middle 4 to 6 days, and remained steady in the final phase. Volatile fatty acids were rapidly consumed and diminished in the first 2 days, whereas the ammonia nitrogen concentration was relatively stable during the process, despite a gradual pH increase to 9.3. Principal-coordinate analysis of 16S rRNA gene amplicons using next-generation sequencing divided the bacterial community structures into distinct clusters corresponding to three phases, and they were similar in the final phase in both years despite different transitions in the middle phase. The predominant phyla (closest species, dominancy) in the initial, middle, and final phases were Proteobacteria ( Arcobacter trophiarum , 19 to 43%; Acinetobacter towneri , 6.3 to 30%), Bacteroidetes ( Moheibacter sediminis , 43 to 54%), and Firmicutes ( Thermaerobacter composti , 11 to 28%; Heliorestis baculata , 2.1 to 16%), respectively. Two predominant operational taxonomic units (OTUs) in the final phase showed very low similarities to the closest species, indicating that the process is unique compared with previously published ones. This unique process with three distinctive phases would be caused by the aerator with complete aeration. IMPORTANCE Although the autothermal thermophilic aerobic digestion (ATAD) process has several advantages, such as a high degradation capacity, a short treatment period, and inactivation of pathogens, one of the factors limiting its broad application is the high electric power consumption for aerators with a full-scale bioreactor. We elucidated the dynamics of the bacterial community structures, as well as the physicochemical characteristics, in the ATAD process with a full-scale bioreactor from human excreta for 3 weeks. Our results indicated that this unique process can be divided into three distinguishable phases by an aerator with complete aeration and showed a possibility of shortening the digestion period to approximately 10 days. This research not only helps to identify which bacteria play significant roles and how the process can be improved and controlled but also demonstrates an efficient ATAD process with less electric power consumption for worldwide application. Copyright © 2018 American Society for Microbiology.

Computational prediction of formulation strategies for beyond-rule-of-5 compounds.

PubMed

Bergström, Christel A S; Charman, William N; Porter, Christopher J H

2016-06-01

The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of 'formulate-ability' during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

PubMed

Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class.

Pre-selection and assessment of green organic solvents by clustering chemometric tools.

PubMed

Tobiszewski, Marek; Nedyalkova, Miroslava; Madurga, Sergio; Pena-Pereira, Francisco; Namieśnik, Jacek; Simeonov, Vasil

2018-01-01

The study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables - bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as "green". Values for logBCF, logK OW and logK OA were modelled for 43 rather nonpolar solvents and 69 polar ones. Application of multivariate statistics was also proved to be useful in the assessment of the obtained modelling results. The presented approach can be one of the first steps and support tools in the assessment of chemicals in terms of their greenness. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting ESI/MS Signal Change for Anions in Different Solvents.

PubMed

Kruve, Anneli; Kaupmees, Karl

2017-05-02

LC/ESI/MS is a technique widely used for qualitative and quantitative analysis in various fields. However, quantification is currently possible only for compounds for which the standard substances are available, as the ionization efficiency of different compounds in ESI source differs by orders of magnitude. In this paper we present an approach for quantitative LC/ESI/MS analysis without standard substances. This approach relies on accurately predicting the ionization efficiencies in ESI source based on a model, which uses physicochemical parameters of analytes. Furthermore, the model has been made transferable between different mobile phases and instrument setups by using a suitable set of calibration compounds. This approach has been validated both in flow injection and chromatographic mode with gradient elution.

pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

PubMed

Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

2017-12-05

In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.

Predicting hydration free energies of amphetamine-type stimulants with a customized molecular model

NASA Astrophysics Data System (ADS)

Li, Jipeng; Fu, Jia; Huang, Xing; Lu, Diannan; Wu, Jianzhong

2016-09-01

Amphetamine-type stimulants (ATS) are a group of incitation and psychedelic drugs affecting the central nervous system. Physicochemical data for these compounds are essential for understanding the stimulating mechanism, for assessing their environmental impacts, and for developing new drug detection methods. However, experimental data are scarce due to tight regulation of such illicit drugs, yet conventional methods to estimate their properties are often unreliable. Here we introduce a tailor-made multiscale procedure for predicting the hydration free energies and the solvation structures of ATS molecules by a combination of first principles calculations and the classical density functional theory. We demonstrate that the multiscale procedure performs well for a training set with similar molecular characteristics and yields good agreement with a testing set not used in the training. The theoretical predictions serve as a benchmark for the missing experimental data and, importantly, provide microscopic insights into manipulating the hydrophobicity of ATS compounds by chemical modifications.

Prediction of kinase-inhibitor binding affinity using energetic parameters

PubMed Central

Usha, Singaravelu; Selvaraj, Samuel

2016-01-01

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor. PMID:28149052

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

NASA Astrophysics Data System (ADS)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

PrAS: Prediction of amidation sites using multiple feature extraction.

PubMed

Wang, Tong; Zheng, Wei; Wuyun, Qiqige; Wu, Zhenfeng; Ruan, Jishou; Hu, Gang; Gao, Jianzhao

2017-02-01

Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users. The method incorporated four representative feature types, which are position-based features, physicochemical and biochemical properties features, predicted structure-based features and evolutionary information features. A novel feature selection method, positive contribution feature selection was proposed to optimize features. PrAS achieved AUC of 0.96, accuracy of 92.1%, sensitivity of 81.2%, specificity of 94.9% and MCC of 0.76 on the independent test set. PrAS is freely available at https://sourceforge.net/p/praspkg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigation of relationships between removals of tetracycline and degradation products and physicochemical parameters in municipal wastewater treatment plant.

PubMed

Topal, Murat; Uslu Şenel, Gülşad; Öbek, Erdal; Arslan Topal, E Işıl

2016-05-15

Determination of the effect of physicochemical parameters on the removal of tetracycline (TC) and degradation products is important because of the importance of the removal of antibiotics in Wastewater Treatment Plant (WWTP). Therefore, the purpose of this study was to investigate the relationships between removals of TC and degradation products and physicochemical parameters in Municipal Wastewater Treatment Plant (MWWTP). For this aim, (i) the removals of physicochemical parameters in a MWWTP located in Elazığ city (Turkey) were determined (ii) the removals of TC and degradation products in MWWTP were determined (iii) the relationships between removals of TC and degradation products and physicochemical parameters were investigated. TC, 4-epitetracycline (ETC), 4-epianhydrotetracycline (EATC), anhydrotetracycline (ATC), and physicochemical parameters (pH, temperature, electrical conductivity (EC), suspended solids (SS), BOD5, COD, total organic carbon (TOC), NH4(+)-N, NO2(-)-N, NO3(-)-N and O-PO4(-3)) were determined. The calculation of the correlation coefficients of relationships between the physicochemical parameters and TC, EATC, ATC showed that, among the investigated parameters, EATC and SS most correlated. The removals of other physicochemical parameters were not correlated with TC, EATC and ATC. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Study of Thrombus Formation and Clotting Factor Effects under Venous Flow Conditions

PubMed Central

Govindarajan, Vijay; Rakesh, Vineet; Reifman, Jaques; Mitrophanov, Alexander Y.

2016-01-01

A comprehensive understanding of thrombus formation as a physicochemical process that has evolved to protect the integrity of the human vasculature is critical to our ability to predict and control pathological states caused by a malfunctioning blood coagulation system. Despite numerous investigations, the spatial and temporal details of thrombus growth as a multicomponent process are not fully understood. Here, we used computational modeling to investigate the temporal changes in the spatial distributions of the key enzymatic (i.e., thrombin) and structural (i.e., platelets and fibrin) components within a growing thrombus. Moreover, we investigated the interplay between clot structure and its mechanical properties, such as hydraulic resistance to flow. Our model relied on the coupling of computational fluid dynamics and biochemical kinetics, and was validated using flow-chamber data from a previous experimental study. The model allowed us to identify the distinct patterns characterizing the spatial distributions of thrombin, platelets, and fibrin accumulating within a thrombus. Our modeling results suggested that under the simulated conditions, thrombin kinetics was determined predominantly by prothrombinase. Furthermore, our simulations showed that thrombus resistance imparted by fibrin was ∼30-fold higher than that imparted by platelets. Yet, thrombus-mediated bloodflow occlusion was driven primarily by the platelet deposition process, because the height of the platelet accumulation domain was approximately twice that of the fibrin accumulation domain. Fibrinogen supplementation in normal blood resulted in a nonlinear increase in thrombus resistance, and for a supplemented fibrinogen level of 48%, the thrombus resistance increased by ∼2.7-fold. Finally, our model predicted that restoring the normal levels of clotting factors II, IX, and X while simultaneously restoring fibrinogen (to 88% of its normal level) in diluted blood can restore fibrin generation to ∼78% of its normal level and hence improve clot formation under dilution. PMID:27119646

Charcoal disrupts cell-cell communication through multiple mechanisms

NASA Astrophysics Data System (ADS)

Gao, X.; Cheng, H. Y.; Liu, S.; Masiello, C. A.; Silberg, J. J.; Del Valle, I.

2016-12-01

Microbial cell-cell communication through the release and detection of small signaling molecules is employed by soil microbes to manage many biogeochemically relevant processes including production of biofilms, priming effects on native SOM, and management of methanogenesis and denitrification. Charcoal is a ubiquitous component of soil, entering soil either from natural fire or intentionally amended as biochar. Charcoal's presence in soil introduces spatial and temporal heterogeneity in nutrients and habitats for soil microbes and may trigger a range of biological effects not yet predictable, in part because it interferes with microbial cell-cell communication. We hypothesized that charcoal's alkalinity and large active surface area could affect the lifetime of some chemical compounds that microbes use for cell-cell signaling on times scales relevant to growth and communication. To test this idea, we examined the extent and rate of charcoal quenching of cell-cell communication caused by ten charcoals with a wide range of physicochemical properties. Our measurements focused on signaling mediated by an acyl-homoserine lactone (AHL), N-3-oxo-dodecanoyl-L-homoserine lactone, which is used by many gram-negative bacteria for quorum sensing. Our results from a bioassay and chemical sorption experiments revealed that charcoal can decrease the bioavailable level of AHL through a combination of sorption and pH-dependent hydrolysis of the lactone ring. We found that the kinetics of hydrolysis can exceed those of sorption. These findings implicate charcoal surface area and alkalinity as properties that could be tuned to regulate the degradation rates of cell-cell signaling molecules in soils. We then built a quantitative model that predicts the half-lives of different microbial signaling compounds in the presence of charcoals varying in pH and surface area. Our model results suggest that the effects of charcoal on pH-sensitive bacterial AHL signals will be fundamentally distinct from effects on pH-insensitive fungal signals, potentially leading to shifts in microbial community structures.

Quantifying Subsurface Water and Heat Distribution and its Linkage with Landscape Properties in Terrestrial Environment using Hydro-Thermal-Geophysical Monitoring and Coupled Inverse Modeling

NASA Astrophysics Data System (ADS)

Dafflon, B.; Tran, A. P.; Wainwright, H. M.; Hubbard, S. S.; Peterson, J.; Ulrich, C.; Williams, K. H.

2015-12-01

Quantifying water and heat fluxes in the subsurface is crucial for managing water resources and for understanding the terrestrial ecosystem where hydrological properties drive a variety of biogeochemical processes across a large range of spatial and temporal scales. Here, we present the development of an advanced monitoring strategy where hydro-thermal-geophysical datasets are continuously acquired and further involved in a novel inverse modeling framework to estimate the hydraulic and thermal parameter that control heat and water dynamics in the subsurface and further influence surface processes such as evapotranspiration and vegetation growth. The measured and estimated soil properties are also used to investigate co-interaction between subsurface and surface dynamics by using above-ground aerial imaging. The value of this approach is demonstrated at two different sites, one in the polygonal shaped Arctic tundra where water and heat dynamics have a strong impact on freeze-thaw processes, vegetation and biogeochemical processes, and one in a floodplain along the Colorado River where hydrological fluxes between compartments of the system (surface, vadose zone and groundwater) drive biogeochemical transformations. Results show that the developed strategy using geophysical, point-scale and aerial measurements is successful to delineate the spatial distribution of hydrostratigraphic units having distinct physicochemical properties, to monitor and quantify in high resolution water and heat distribution and its linkage with vegetation, geomorphology and weather conditions, and to estimate hydraulic and thermal parameters for enhanced predictions of water and heat fluxes as well as evapotranspiration. Further, in the Colorado floodplain, results document the potential presence of only periodic infiltration pulses as a key hot moment controlling soil hydro and biogeochemical functioning. In the arctic, results show the strong linkage between soil water content, thermal parameters, thaw layer thickness and vegetation distribution. Overall, results of these efforts demonstrate the value of coupling various datasets at high spatial and temporal resolution to improve predictive understanding of subsurface and surface dynamics.

Seasonal ionomic and metabolic changes in Aleppo pines growing on mine tailings under Mediterranean semi-arid climate.

PubMed

López-Orenes, Antonio; Bueso, María C; Conesa, Héctor; Calderón, Antonio A; Ferrer, María A

2018-05-11

Aleppo pine is the most abundant conifer species in Mediterranean basin. Knowledge of adaptive mechanisms to cope with different environmental stresses simultaneously is necessary to improve its resilience to the predicted climatic changes and anthropogenic stressors, such as heavy metal/metal(loid)s (HMMs) pollution. Here, one year-old needles and rhizosphere soil samples from five mining and non-mining (NM) populations of Aleppo pines grown spontaneously in SE Spain were sampled in two consecutive years during spring and summer. Quantitative determination of a wide suite of edaphic, biochemical, and physiological parameters was performed, including soil physicochemical properties, ionome profile, foliar redox components, primary and secondary metabolites. Mining rhizosphere soils were characterized by elevated contents of HMMs, particularly lead and zinc, and low carbon, nitrogen and potassium levels. Multivariate data analysis based on needle ionome and antioxidative/oxidative parameters revealed a clear distinction between seasons irrespective of the population considered. Spring needles were characterized by higher levels of HMMs, sulfur, glutathione (GSH), proanthocyanidins (PAs), and soluble phenols (TPC), whereas reduced chlorophylls and increased levels of carotenoids, relative water content and K + , Na + and Cl - typified summer needles. In general mining populations had higher levels of ascorbate, and TPC, and exhibited higher antioxidant activities than the NM population. This could contribute to prevent oxidative injury induced by HMMs. Taken together, results suggest that seasonal factors have a more marked effect on the metabolism of the Aleppo pine populations studied than that exerted by soil conditions. This effect could be mediated by water availability in surface soil layers. If this conclusion is right, predicted rainfall reduction and temperature increase in the Mediterranean basin associated to global climate change would lead to pine needle metabolism to express the summer pattern for more prolonged periods. This, in turn, could negatively affect the performance of Aleppo pine populations. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial assessment of soil organic carbon and physicochemical properties in a horticultural orchard at arid zone of India using geostatistical approaches.

PubMed

Singh, Akath; Santra, Priyabrata; Kumar, Mahesh; Panwar, Navraten; Meghwal, P R

2016-09-01

Soil organic carbon (SOC) is a major indicator of long-term sustenance of agricultural production system. Apart from sustaining productivity, SOC plays a crucial role in context of climate change. Keeping in mind these potentials, spatial variation of SOC contents of a fruit orchard comprising several arid fruit plantations located at arid region of India is assessed in this study through geostatistical approaches. For this purpose, surface and subsurface soil samples from 175 locations from a fruit orchard spreading over 14.33 ha area were collected along with geographical coordinates. SOC content and soil physicochemical properties of collected soil samples were determined followed by geostatistical analysis for mapping purposes. Average SOC stock density of the orchard was 14.48 Mg ha(-1) for 0- to 30-cm soil layer ranging from 9.01 Mg ha(-1) in Carissa carandas to 19.52 Mg ha(-1) in Prosopis cineraria block. Range of spatial variation of SOC content was found about 100 m, while two other soil physicochemical properties, e.g., pH and electrical conductivity (EC) also showed similar spatial trend. This indicated that minimum sampling distance for future SOC mapping programme may be kept lower than 100 m for better accuracy. Ordinary kriging technique satisfactorily predicted SOC contents (in percent) at unsampled locations with root-mean-squared residual (RMSR) of 0.35-0.37. Co-kriging approach was found slightly superior (RMSR = 0.26-0.28) than ordinary kriging for spatial prediction of SOC contents because of significant correlations of SOC contents with pH and EC. Uncertainty of SOC estimation was also presented in terms of 90 % confidence interval. Spatial estimates of SOC stock through ordinary kriging or co-kriging approach were also found with low uncertainty of estimation than non-spatial estimates, e.g., arithmetic averaging approach. Among different fruit block plantations of the orchard, the block with Prosopis cineraria ('khejri') has higher SOC stock density than others.

Psychological need-satisfaction and subjective well-being within social groups.

PubMed

Sheldon, Kennon M; Bettencourt, B Ann

2002-03-01

Five candidate measures of psychological need-satisfaction were evaluated as predictors of high positive and low negative mood within the group, intrinsic motivation for group activities, and high commitment to the group. Consistent with self-determination theory (Deci & Ryan, 1991), personal autonomy and interpersonal relatedness both predicted positive outcomes. Consistent with optimal distinctiveness theory (Brewer, 1991), feeling included within the group, feeling personally distinctive within the group, and feeling that the group is distinctive compared to other groups, also predicted positive outcomes. Simultaneous regression analyses indicated that the five needs were differentially related to the different well-being indicators, and also suggested that group inclusion may be the most important need to satisfy within group contexts. Supplementary analyses showed that members of formal groups felt less personal autonomy, but more group distinctiveness, compared to informal group members.

Serial recall and presentation schedule: a micro-analysis of local distinctiveness.

PubMed

Lewandowsky, Stephan; Brown, Gordon D A

2005-01-01

According to temporal distinctiveness theories, items that are temporally isolated from their neighbours during presentation are more distinct and thus are recalled better. Event-based theories, which deny that elapsed time plays a role at encoding, explain isolation effects by assuming that temporal isolation provides extra time for rehearsal or consolidation of encoding. The two classes of theories can be differentiated by examining the symmetry of isolation effects: Event-based accounts predict that performance should be affected only by pauses following item presentation (because they allow time for rehearsal or consolidation), whereas distinctiveness predicts that items should also benefit from preceding pauses. The first experiment manipulated inter-item intervals and showed an effect of intervals following but not preceding presentation, in line with event-based accounts. The second experiment showed that the effect of following interval was abolished by articulatory suppression. The data are consistent with event-based theories but can be handled by time-based distinctiveness models if they allow for additional encoding during inter-item pauses.

Preparation and characterization of an iron oxide-hydroxyapatite nanocomposite for potential bone cancer therapy.

PubMed

Sneha, Murugesan; Sundaram, Nachiappan Meenakshi

2015-01-01

Recently, multifunctional magnetic nanostructures have been found to have potential applications in biomedical and tissue engineering. Iron oxide nanoparticles are biocompatible and have distinctive magnetic properties that allow their use in vivo for drug delivery and hyperthermia, and as T2 contrast agents for magnetic resonance imaging. Hydroxyapatite is used frequently due to its well-known biocompatibility, bioactivity, and lack of toxicity, so a combination of iron oxide and hydroxyapatite materials could be useful because hydroxyapatite has better bone-bonding ability. In this study, we prepared nanocomposites of iron oxide and hydroxyapatite and analyzed their physicochemical properties. The results suggest that these composites have superparamagnetic as well as biocompatible properties. This type of material architecture would be well suited for bone cancer therapy and other biomedical applications.

Tomato bushy stunt virus (TBSV) infecting Lycopersicon esculentum.

PubMed

Hafez, El Sayed E; Saber, Ghada A; Fattouh, Faiza A

2010-01-01

Tomato bushy stunt virus (TBSV) was detected in tomato crop (Lycopersicon esculentum) in Egypt with characteristic mosaic leaf deformation, stunting, and bushy growth symptoms. TBSV infection was confirmed serologically by ELISA and calculated incidence was 25.5%. Basic physicochemical properties of a purified TBSV Egh isolate were identical to known properties of tombusviruses of isometric 30-nm diameter particles, 41-kDa coat protein and the genome of approximately 4800 nt. This is the first TBSV isolate reported in Egypt. Cloning and partial sequencing of the isolate showed that it is more closely related to TBSV-P and TBSV-Ch than TBSV-Nf and TBSV-S strains of the virus. However, it is distinct from the above strains and could be a new strain of the virus which further confirms the genetic diversity of tombusviruses.

Oxidation of municipal wastewater by free radicals mechanism. A UV/Vis spectroscopy study.

PubMed

Giannakopoulos, E; Isari, E; Bourikas, K; Karapanagioti, H K; Psarras, G; Oron, G; Kalavrouziotis, I K

2017-06-15

This study investigates the oxidation of municipal wastewater (WW) by complexation with natural polyphenols having radical scavenging activity, such as (3,4,5 tri-hydroxy-benzoic acid) gallic acid (GA) in alkaline pH (>7), under ambient O 2 and temperature. Physicochemical and structural characteristics of GA-WW complex-forming are evaluated by UV/Vis spectroscopy. The comparative analysis among UV/Vis spectra of GA monomer, GA-GA polymer, WW compounds, and GA-WW complex reveals significant differences within 350-450 and 500-900 nm. According to attenuated total reflectance (ATR) spectroscopy and thermogravimetric analysis (TGA), these spectra differences correspond to distinct complexes formed. This study suggests a novel role of natural polyphenols on the degradation and humification of wastes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Data Mining for Wine Quality Assessment

NASA Astrophysics Data System (ADS)

Cortez, Paulo; Teixeira, Juliana; Cerdeira, António; Almeida, Fernando; Matos, Telmo; Reis, José

Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal. Wine quality is modeled under a regression approach, which preserves the order of the grades. Explanatory knowledge is given in terms of a sensitivity analysis, which measures the response changes when a given input variable is varied through its domain. Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection and that is guided by the sensitivity analysis. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful for understanding how physicochemical tests affect the sensory preferences. Moreover, it can support the wine expert evaluations and ultimately improve the production.

Enrichment of wheat chips with omega-3 fatty acid by flaxseed addition: textural and some physicochemical properties.

PubMed

Yuksel, Ferhat; Karaman, Safa; Kayacier, Ahmed

2014-02-15

In the present study, wheat chips enriched with flaxseed flour were produced and response surface methodology was used for the studying the simultaneous effects of flaxseed level (10-20%), frying temperature (160-180 °C) and frying time (40-60 s) on some physicochemical, textural and sensorial properties and fatty acid composition of wheat chips. Ridge analysis was conducted to determine the optimum levels of processing variables. Predictive regression equations with adequate coefficients of determination (R² ≥ 0.705) to explain the effect of processing variables were constructed. Addition of flaxseed flour increased the dry matter and protein content of samples and increase of frying temperature decreased the hardness values of wheat chips samples. Increment in flaxseed level provided an increase in unsaturated fatty acid content namely omega-3 fatty acids of wheat chips samples. Overall acceptability of chips increased with the increase of frying temperature. Ridge analysis showed that maximum taste score would be at flaxseed level = 10%, frying temperature = 180 °C and frying time = 50 s. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mutagenic analysis of the nucleation propensity of oxidized Alzheimer's beta-amyloid peptide.

PubMed

Christopeit, Tony; Hortschansky, Peter; Schroeckh, Volker; Gührs, Karlheinz; Zandomeneghi, Giorgia; Fändrich, Marcus

2005-08-01

The formation of polypeptide aggregates represents a nucleated polymerization reaction in which an initial nucleation event (lag phase) is followed by the extension of newly formed nuclei into larger aggregates, including fibrils (growth phase). The efficiencies of these reactions relate to the lag time (lag phase) and to the rate of aggregation (growth phase), which can be determined from experimental aggregation curves. Here we present a mutagenic analysis in which we replace valine 18 of the Alzheimer's Abeta (1-40) peptide with 17 different amino acids and determine its effect on the lag time, and therefore, on the propensity of nucleation. Comparison with various physico-chemical properties shows that nucleation is affected in a predictable manner depending on the beta-sheet propensity and hydrophobicity of residue 18. In addition, we observe a direct proportionality between the lag time and the rate of aggregation. These data imply that the two reactions, nucleation and polymerization, are governed by very similar physicochemical principles and that they involve the formation of the same types of noncovalent interactions.

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

The Machine Learning (ML) is one of the fastest developing techniques in the prediction and evaluation of important pharmacokinetic properties such as absorption, distribution, metabolism and excretion. The availability of a large number of robust validation techniques for prediction models devoted to pharmacokinetics has significantly enhanced the trust and authenticity in ML approaches. There is a series of prediction models generated and used for rapid screening of compounds on the basis of absorption in last one decade. Prediction of absorption of compounds using ML models has great potential across the pharmaceutical industry as a non-animal alternative to predict absorption. However, these prediction models still have to go far ahead to develop the confidence similar to conventional experimental methods for estimation of drug absorption. Some of the general concerns are selection of appropriate ML methods and validation techniques in addition to selecting relevant descriptors and authentic data sets for the generation of prediction models. The current review explores published models of ML for the prediction of absorption using physicochemical properties as descriptors and their important conclusions. In addition, some critical challenges in acceptance of ML models for absorption are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Timeless Memory: Evidence against Temporal Distinctiveness Models of Short-Term Memory for Serial Order

ERIC Educational Resources Information Center

Lewandowsky, Stephan; Brown, Gordon D. A.; Wright, Tarryn; Nimmo, Lisa M.

2006-01-01

According to temporal distinctiveness models, items that are temporally isolated from their neighbors during list presentation are more distinct and thus should be recalled better. Event-based theories, by contrast, deny that time plays a role at encoding and predict no beneficial effect of temporal isolation, although they acknowledge that a…

Modelling of the physico-chemical behaviour of clay minerals with a thermo-kinetic model taking into account particles morphology in compacted material.

NASA Astrophysics Data System (ADS)

Sali, D.; Fritz, B.; Clément, C.; Michau, N.

2003-04-01

Modelling of fluid-mineral interactions is largely used in Earth Sciences studies to better understand the involved physicochemical processes and their long-term effect on the materials behaviour. Numerical models simplify the processes but try to preserve their main characteristics. Therefore the modelling results strongly depend on the data quality describing initial physicochemical conditions for rock materials, fluids and gases, and on the realistic way of processes representations. The current geo-chemical models do not well take into account rock porosity and permeability and the particle morphology of clay minerals. In compacted materials like those considered as barriers in waste repositories, low permeability rocks like mudstones or compacted powders will be used : they contain mainly fine particles and the geochemical models used for predicting their interactions with fluids tend to misjudge their surface areas, which are fundamental parameters in kinetic modelling. The purpose of this study was to improve how to take into account the particles morphology in the thermo-kinetic code KINDIS and the reactive transport code KIRMAT. A new function was integrated in these codes, considering the reaction surface area as a volume depending parameter and the calculated evolution of the mass balance in the system was coupled with the evolution of reactive surface areas. We made application exercises for numerical validation of these new versions of the codes and the results were compared with those of the pre-existing thermo-kinetic code KINDIS. Several points are highlighted. Taking into account reactive surface area evolution during simulation modifies the predicted mass transfers related to fluid-minerals interactions. Different secondary mineral phases are also observed during modelling. The evolution of the reactive surface parameter helps to solve the competition effects between different phases present in the system which are all able to fix the chemical elements mobilised by the water-minerals interaction processes. To validate our model we simulated the compacted bentonite (MX80) studied for engineered barriers for radioactive waste confinement and mainly composed of Na-Ca-montmorillonite. The study of particles morphology and reactive surfaces evolutions reveals that aqueous ions have a complex behaviour, especially when competitions between various mineral phases occur. In that case, our model predicts a preferential precipitation of finest particles, favouring smectites instead of zeolites. This work is a part of a PhD Thesis supported by Andra, the French Radioactive Waste Management Agency.

Property Changes in Aqueous Solutions due to Surfactant Treatment of PCE: Implications to Geophysical Measurements

NASA Astrophysics Data System (ADS)

Werkema, D. D.

2007-12-01

Select physicochemical properties of aqueous solutions composed of surfactants, dye, and perchloroethylene (PCE) were evaluated through a response surface quadratic design model of experiment. Nine surfactants, which are conventionally used in the remediation of PCE, were evaluated with varying concentrations of PCE and indicator dyes in aqueous solutions. Two hundred forty experiments were performed using PCE as a numerical factor (coded A) from 0 to 200 parts per million (ppm), dye type (coded B) as a 3-level categorical factor, and surfactant type (coded C) as a 10-level categorical factor. Five responses were measured: temperature (°C), pH, conductivity (μS/cm), dissolved oxygen (DO, mg/L), and density (g/mL). Diagnostics proved a normally distributed predictable response for all measured responses except pH. The Box-Cox plot for transforms recommended a power transform for the conductivity response with lambda (λ) = 0.50, and for the DO response, λ =2.2. The overall mean of the temperature response proved to be a better predictor than the linear model. The conductivity response is best fitted with a linear model using significant coded terms B and C. Both DO and density also showed a linear model with coded terms A, B, and C for DO; and terms A and C for density. Some of the surfactant treatments of PCE significantly alter the conductivity, DO, and density of the aqueous solution. However, the magnitude of the density response is so small that it does not exceed the instrument tolerance. Results for the conductivity and DO responses provide predictive models for the surfactant treatment of PCE and may be useful in determining the potential for geophysically monitoring surfactant enhanced aquifer remediation (SEAR) of PCE. As the aqueous physicochemical properties change due to surfactant remediation efforts, so will the properties of the subsurface pore water which are influential factors in geophysical measurements. Geoelectrical methods are potentially the best suited to measure SEAR alterations in the subsurface because the conductivity of the pore fluid has the largest relative change. This research has provided predictive models for alterations in the physicochemical properties of the pore fluid to SEAR of PCE. Future investigations should address the contribution of the solid matrix in the subsurface and the solid-fluid interaction during SEAR of PCE contamination. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation by EPA for use.

Saliva composition in three selected groups with normal stimulated salivary flow rates, but yet major differences in caries experience and dental erosion.

PubMed

Bardow, Allan; Lykkeaa, Joan; Qvist, Vibeke; Ekstrand, Kim; Twetman, Svante; Fiehn, Niels-Erik

2014-08-01

It was hypothesized that, by comparing matched subjects with major differences in these dental diseases, but yet normal saliva flow rates, it would be possible to obtain data on the effect of saliva composition on dental disease isolated from the effect of the flow rate. Thus, the aim of the study was to compare the major physicochemical characteristics of stimulated whole saliva in three groups of 85 subjects, each with normal saliva flow rates and at least 24 remaining teeth. A group with very little dental disease (healthy), a group with dental erosion (erosion) and a group with very high caries experience (caries) were chosen. Furthermore, the aim was to determine whether differences among groups could also be found on an individual level. Although it was not possible to retrieve three groups whose members were completely identical, the present study points in the direction that, on a group level, subjects with very little dental disease seemed to have a more favorable physicochemical saliva composition with respect to higher calcium, phosphate, bicarbonate, pH, degree of saturation with respect to hydroxyapatite and a lower critical pH (p < 0.05 or less). However, on an individual level the explanatory power for the saliva composition was only 10% for caries experience and only 11% for dental erosion (p < 0.001). The compositional analyses performed in this study on stimulated whole saliva, including major physicochemical characteristics of saliva, will most likely have little predictive value for future dental caries and erosion in single individuals.

Physicochemically Tunable Polyfunctionalized RNA Square Architecture with Fluorogenic and Ribozymatic Properties

PubMed Central

2015-01-01

Recent advances in RNA nanotechnology allow the rational design of various nanoarchitectures. Previous methods utilized conserved angles from natural RNA motifs to form geometries with specific sizes. However, the feasibility of producing RNA architecture with variable sizes using native motifs featuring fixed sizes and angles is limited. It would be advantageous to display RNA nanoparticles of diverse shape and size derived from a given primary sequence. Here, we report an approach to construct RNA nanoparticles with tunable size and stability. Multifunctional RNA squares with a 90° angle were constructed by tuning the 60° angle of the three-way junction (3WJ) motif from the packaging RNA (pRNA) of the bacteriophage phi29 DNA packaging motor. The physicochemical properties and size of the RNA square were also easily tuned by modulating the “core” strand and adjusting the length of the sides of the square via predictable design. Squares of 5, 10, and 20 nm were constructed, each showing diverse thermodynamic and chemical stabilities. Four “arms” extending from the corners of the square were used to incorporate siRNA, ribozyme, and fluorogenic RNA motifs. Unique intramolecular contact using the pre-existing intricacy of the 3WJ avoids relatively weaker intermolecular interactions via kissing loops or sticky ends. Utilizing the 3WJ motif, we have employed a modular design technique to construct variable-size RNA squares with controllable properties and functionalities for diverse and versatile applications with engineering, pharmaceutical, and medical potential. This technique for simple design to finely tune physicochemical properties adds a new angle to RNA nanotechnology. PMID:24971772

Deep-sea seabed habitats: Do they support distinct mega-epifaunal communities that have different vulnerabilities to anthropogenic disturbance?

NASA Astrophysics Data System (ADS)

Bowden, David A.; Rowden, Ashley A.; Leduc, Daniel; Beaumont, Jennifer; Clark, Malcolm R.

2016-01-01

Growing economic interest in seabed resources in the deep-sea highlights the need for information about the spatial distribution and vulnerability to disturbance of benthic habitats and fauna. Categorisation of seabed habitats for management is often based on topographic features such as canyons and seamounts that can be distinguished using regional bathymetry ('mega-habitats'). This is practical but because such habitats are contiguous with others, there is potential for overlap in the communities associated with them. Because concepts of habitat and community vulnerability are based on the traits of individual taxa, the nature and extent of differences between communities have implications for strategies to manage the environmental effects of resource use. Using towed video camera transects, we surveyed mega-epifaunal communities of three topographically-defined habitats (canyon, seamount or knoll, and continental slope) and two physico-chemically defined meso-scale habitats (cold seep and hydrothermal vent) in two regions off New Zealand to assess whether each supports a distinct type of community. Cold seep and hydrothermal vent communities were strongly distinct from those in other habitats. Across the other habitats, however, distinctions between communities were often weak and were not consistent between regions. Dissimilarities among communities across all habitats were stronger and the density of filter-feeding taxa was higher in the Bay of Plenty than on the Hikurangi Margin, whereas densities of predatory and scavenging taxa were higher on the Hikurangi Margin. Substratum diversity at small spatial scales (<1 km) and trawl history were significantly correlated with community composition in both regions. We conclude that, (1) a lack of consistent distinction between communities raises questions about the general utility of topographically-defined mega-habitats in environmental management, (2) fine-scale survey of individual features is necessary to identify the locations, characteristics, and extents of ecologically important or vulnerable seabed communities, and (3) evaluation of habitat vulnerability to future events should be in the context of previous and current disturbances.

The Science of Biometeorology

ERIC Educational Resources Information Center

Maxey, E. Stanton

1977-01-01

Biometeorology is the study of the relations between meteorological factors, physico-chemical systems and living organisms, and the indirect effects of the physical, chemical, and physico-chemical environments of the earth's atmosphere and of similar extraterrestrial space upon physico-chemical systems and living organisms. This article discusses…

An activity canyon characterization of the pharmacological topography.

PubMed

Kulkarni, Varsha S; Wild, David J

2016-01-01

Highly chemically similar drugs usually possess similar biological activities, but sometimes, small changes in chemistry can result in a large difference in biological effects. Chemically similar drug pairs that show extreme deviations in activity represent distinctive drug interactions having important implications. These associations between chemical and biological similarity are studied as discontinuities in activity landscapes. Particularly, activity cliffs are quantified by the drop in similar activity of chemically similar drugs. In this paper, we construct a landscape using a large drug-target network and consider the rises in similarity and variation in activity along the chemical space. Detailed analysis of structure and activity gives a rigorous quantification of distinctive pairs and the probability of their occurrence. We analyze pairwise similarity (s) and variation (d) in activity of drugs on proteins. Interactions between drugs are quantified by considering pairwise s and d weights jointly with corresponding chemical similarity (c) weights. Similarity and variation in activity are measured as the number of common and uncommon targets of two drugs respectively. Distinctive interactions occur between drugs having high c and above (below) average d (s). Computation of predicted probability of distinctiveness employs joint probability of c, s and of c, d assuming independence of structure and activity. Predictions conform with the observations at different levels of distinctiveness. Results are validated on the data used and another drug ensemble. In the landscape, while s and d decrease as c increases, d maintains value more than s. c ∈ [0.3, 0.64] is the transitional region where rises in d are significantly greater than drops in s. It is fascinating that distinctive interactions filtered with high d and low s are different in nature. It is crucial that high c interactions are more probable of having above average d than s. Identification of distinctive interactions is better with high d than low s. These interactions belong to diverse classes. d is greatest between drugs and analogs prepared for treatment of same class of ailments but with different therapeutic specifications. In contrast, analogs having low s would treat ailments from distinct classes. Intermittent spikes in d along the axis of c represent canyons in the activity landscape. This new representation accounts for distinctiveness through relative rises in s and d. It provides a mathematical basis for predicting the probability of occurrence of distinctiveness. It identifies the drug pairs at varying levels of distinctiveness and non-distinctiveness. The predicted probability formula is validated even if data approximately satisfy the conditions of its construction. Also, the postulated independence of structure and activity is of little significance to the overall assessment. The difference in distinctive interactions obtained by s and d highlights the importance of studying both of them, and reveals how the choice of measurement can affect the interpretation. The methods in this paper can be used to interpret whether or not drug interactions are distinctive and the probability of their occurrence. Practitioners and researchers can rely on this identification for quantitative modeling and assessment.

Microbial communities associated with wet flue gas desulfurization systems

PubMed Central

Brown, Bryan P.; Brown, Shannon R.; Senko, John M.

2012-01-01

Flue gas desulfurization (FGD) systems are employed to remove SOx gasses that are produced by the combustion of coal for electric power generation, and consequently limit acid rain associated with these activities. Wet FGDs represent a physicochemically extreme environment due to the high operating temperatures and total dissolved solids (TDS) of fluids in the interior of the FGD units. Despite the potential importance of microbial activities in the performance and operation of FGD systems, the microbial communities associated with them have not been evaluated. Microbial communities associated with distinct process points of FGD systems at several coal-fired electricity generation facilities were evaluated using culture-dependent and -independent approaches. Due to the high solute concentrations and temperatures in the FGD absorber units, culturable halothermophilic/tolerant bacteria were more abundant in samples collected from within the absorber units than in samples collected from the makeup waters that are used to replenish fluids inside the absorber units. Evaluation of bacterial 16S rRNA genes recovered from scale deposits on the walls of absorber units revealed that the microbial communities associated with these deposits are primarily composed of thermophilic bacterial lineages. These findings suggest that unique microbial communities develop in FGD systems in response to physicochemical characteristics of the different process points within the systems. The activities of the thermophilic microbial communities that develop within scale deposits could play a role in the corrosion of steel structures in FGD systems. PMID:23226147

Chitooligosaccharide: An evaluation of physicochemical and biological properties with the proposition for determination of thermal degradation products.

PubMed

Phil, Lucas; Naveed, Muhammad; Mohammad, Imran Shair; Bo, Li; Bin, Di

2018-06-01

Being the most versatile biopolymer, chitooligosaccharide/chitosan oligosaccharide (COS) has been extensively studied for a range of exceptional biological activities and potential developments of novel medical devices and systems in biomedical and pharmaceutical fields. While possessing intrinsic biocompatibility, mucoadhesiveness, and non-toxicity it gained more interests in the biomedical development of novel systems, devices, and pharmaceutical formulations. The bioactive relativity of chitosan and COS are of highly significant and thus explored in this paper while highlighting its multiple biological activities and promising biomedical applications. More emphasis is on the molecular weight, degree of acetylation/deacetylation, degree of polymerization and reactive groups in relation to chitin and chitosan. Despite COS wide acceptance and utilization, the associated viscosity and instability are crucial factors that posed a great challenge to researchers. The apparent reason attributed to instability and viscosity could be the presence intrinsic variable oligomers within COS. Due to lack of data on safety and impurity analysis of thermal exposure of COS, we hypothesized that different molecules could be generated with thermal treatment of COS, thus finally suggested a prospective determination of thermal degradation product(s)in COS. Hence the aim of this paper is to highlight COS physicochemical and biological significance with reference to its recent developments and propose a further chemical analysis thermal treated COS. This could trigger future researchers for possible isolation and characterization of distinct biomolecules from COS. Copyright © 2018. Published by Elsevier Masson SAS.

Assessment of Water Quality in Asa River (Nigeria) and Its Indigenous Clarias gariepinus Fish

PubMed Central

Kolawole, Olatunji M.; Ajayi, Kolawole T.; Olayemi, Albert B.; Okoh, Anthony I.

2011-01-01

Water is a valued natural resource for the existence of all living organisms. Management of the quality of this precious resource is, therefore, of special importance. In this study river water samples were collected and analysed for physicochemical and bacteriological evaluation of pollution in the Unity Road stream segment of Asa River in Ilorin, Nigeria. Juvenile samples of Clarias gariepinus fish were also collected from the experimental Asa River and from the control Asa Dam water and were analysed for comparative histological investigations and bacterial density in the liver and intestine in order to evaluate the impact of pollution on the aquatic biota. The water pH was found to range from 6.32 to 6.43 with a mean temperature range of 24.3 to 25.8 °C. Other physicochemical parameters monitored including total suspended solids, total dissolved solids, biochemical oxygen demand and chemical oxygen demand values exceeded the recommended level for surface water quality. Results of bacteriological analyses including total heterotrophic count, total coliform and thermotolerant coliform counts revealed a high level of faecal pollution of the river. Histological investigations revealed no significant alterations in tissue structure, but a notable comparative distinction of higher bacterial density in the intestine and liver tissues of Clarias gariepinus from Asa River than in those collected from the control. It was inferred that the downstream Asa River is polluted and its aquatic biota is bacteriologically contaminated and unsafe for human and animal consumption. PMID:22163210

Characterization of a new adenovirus isolated from black-tailed deer in California.

PubMed

Lehmkuhl, H D; Hobbs, L A; Woods, L W

2001-01-01

An adenovirus associated with systemic and localized vascular damage was demonstrated by transmission electron microscopy and immunohistochemistry in a newly recognized epizootic hemorrhagic disease in California black-tailed deer. In this study, we describe the cultural, physicochemical and serological characteristics of a virus isolated from lung using neonatal white-tail deer lung and turbinate cell cultures. The virus had the cultural, morphological and physicochemical characteristics of members of the Adenoviridae family. The virus would not replicate in low passage fetal bovine, caprine or ovine cells. Antiserum to the deer adenovirus, strain D94-2569, neutralized bovine adenovirus type-6 (BAdV-6), BAdV-7, and caprine adenovirus type-1 (GAdV-1). Antiserum to BAdV-6 did not neutralize the deer adenovirus but antiserum to BAdV-7 and GAdV-1 neutralized the deer adenovirus. Cross-neutralization with the other bovine, caprine and ovine adenovirus species was not observed. Restriction endonuclease patterns generated for the deer adenovirus were unique compared to those for the currently recognized bovine, caprine and ovine adenovirus types. Amino acid sequence alignments of the hexon gene from the deer adenovirus strain D94-2569 indicate that it is a member of the proposed new genus (Atadenovirus) of the Adenoviridae family. While closely related antigenically to BAdV-7 and GAdV-1, the deer adenovirus appears sufficiently distinct culturally and molecularly to justify consideration as a new adenovirus type.

Crystallization Kinetics of Indomethacin/Polyethylene Glycol Dispersions Containing High Drug Loadings.

PubMed

Duong, Tu Van; Van Humbeeck, Jan; Van den Mooter, Guy

2015-07-06

The reproducibility and consistency of physicochemical properties and pharmaceutical performance are major concerns during preparation of solid dispersions. The crystallization kinetics of drug/polyethylene glycol solid dispersions, an important factor that is governed by the properties of both drug and polymer has not been adequately explored, especially in systems containing high drug loadings. In this paper, by using standard and modulated differential scanning calorimetry and X-ray powder diffraction, we describe the influence of drug loading on crystallization behavior of dispersions made up of indomethacin and polyethylene glycol 6000. Higher drug loading increases the amorphicity of the polymer and inhibits the crystallization of PEG. At 52% drug loading, polyethylene glycol was completely transformed to the amorphous state. To the best of our knowledge, this is the first detailed investigation of the solubilization effect of a low molecular weight drug on a semicrystalline polymer in their dispersions. In mixtures containing up to 55% indomethacin, the dispersions exhibited distinct glass transition events resulting from amorphous-amorphous phase separation which generates polymer-rich and drug-rich domains upon the solidification of supercooled polyethylene glycol, whereas samples containing at least 60% drug showed a single amorphous phase during the period in which crystallization normally occurs. The current study demonstrates a wide range in physicochemical properties of drug/polyethylene glycol solid dispersions as a result of the complex nature in crystallization of this system, which should be taken into account during preparation and storage.

Assessment of wastewater effluent quality in Thessaly region, Greece, for determining its irrigation reuse potential.

PubMed

Bakopoulou, S; Emmanouil, C; Kungolos, A

2011-02-01

The objective of the present study is to assess wastewater effluent quality in Thessaly region, Greece, in relation to its physicochemical and microbiological burden as well as its toxic potential on a number of organisms. Wastewater may be used for agricultural as well as for landscape irrigation purposes; therefore, its toxicity potential is quite important. Thessaly region has been chosen since this region suffers from a distinct water shortage in summer period necessitating alternative water resources. During our research, treated effluents from four wastewater treatment plants operating in the region (Larissa, Volos, Karditsa, and Tirnavos) were tested for specific physicochemical and microbiological parameters [biochemical oxygen demand (BOD(5)), chemical oxygen demand (COD), total suspended solids (TSS), pH, electrical conductivity, selected metals presence (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn, As), and fecal coliforms' (FC) number]. The effluents were also tested for their toxicity using two different bioassays (Daphnia magna immobilization test and Phytotoxkit microbiotest). The findings were compared to relative regulations and guidelines regarding wastewater reuse for irrigation. The results overall show that secondary effluents in Thessaly region are generally acceptable for reuse for irrigation purposes according to limits set by legislation, if effective advanced treatment methods are applied prior to reuse. However, their potential toxicity should be closely monitored, since it was found that it may vary significantly in relation to season and location, when indicator plant and zooplankton organisms are used. Copyright © 2010 Elsevier Inc. All rights reserved.

Sea surface microlayers: A unified physicochemical and biological perspective of the air-ocean interface

NASA Astrophysics Data System (ADS)

Cunliffe, Michael; Engel, Anja; Frka, Sanja; Gašparović, Blaženka; Guitart, Carlos; Murrell, J. Colin; Salter, Matthew; Stolle, Christian; Upstill-Goddard, Robert; Wurl, Oliver

2013-02-01

The sea surface microlayer (SML) covers more than 70% of the Earth's surface and is the boundary layer interface between the ocean and the atmosphere. This important biogeochemical and ecological system is critical to a diverse range of Earth system processes, including the synthesis, transformation and cycling of organic material, and the air-sea exchange of gases, particles and aerosols. In this review we discuss the SML paradigm, taking into account physicochemical and biological characteristics that define SML structure and function. These include enrichments in biogenic molecules such as carbohydrates, lipids and proteinaceous material that contribute to organic carbon cycling, distinct microbial assemblages that participate in air-sea gas exchange, the generation of climate-active aerosols and the accumulation of anthropogenic pollutants with potentially serious implications for the health of the ocean. Characteristically large physical, chemical and biological gradients thus separate the SML from the underlying water and the available evidence implies that the SML retains its integrity over wide ranging environmental conditions. In support of this we present previously unpublished time series data on bacterioneuston composition and SML surfactant activity immediately following physical SML disruption; these imply timescales of the order of minutes for the reestablishment of the SML following disruption. A progressive approach to understanding the SML and hence its role in global biogeochemistry can only be achieved by considering as an integrated whole, all the key components of this complex environment.

Peptides, polypeptides and peptide-polymer hybrids as nucleic acid carriers.

PubMed

Ahmed, Marya

2017-10-24

Cell penetrating peptides (CPPs), and protein transduction domains (PTDs) of viruses and other natural proteins serve as a template for the development of efficient peptide based gene delivery vectors. PTDs are sequences of acidic or basic amphipathic amino acids, with superior membrane trespassing efficacies. Gene delivery vectors derived from these natural, cationic and cationic amphipathic peptides, however, offer little flexibility in tailoring the physicochemical properties of single chain peptide based systems. Owing to significant advances in the field of peptide chemistry, synthetic mimics of natural peptides are often prepared and have been evaluated for their gene expression, as a function of amino acid functionalities, architecture and net cationic content of peptide chains. Moreover, chimeric single polypeptide chains are prepared by a combination of multiple small natural or synthetic peptides, which imparts distinct physiological properties to peptide based gene delivery therapeutics. In order to obtain multivalency and improve the gene delivery efficacies of low molecular weight cationic peptides, bioactive peptides are often incorporated into a polymeric architecture to obtain novel 'polymer-peptide hybrids' with improved gene delivery efficacies. Peptide modified polymers prepared by physical or chemical modifications exhibit enhanced endosomal escape, stimuli responsive degradation and targeting efficacies, as a function of physicochemical and biological activities of peptides attached onto a polymeric scaffold. The focus of this review is to provide comprehensive and step-wise progress in major natural and synthetic peptides, chimeric polypeptides, and peptide-polymer hybrids for nucleic acid delivery applications.

Evaluation of three activated carbons for combined adsorption and biodegradation of PCBs in aquatic sediment.

PubMed

Mercier, Anne; Joulian, Catherine; Michel, Caroline; Auger, Pascal; Coulon, Stéphanie; Amalric, Laurence; Morlay, Catherine; Battaglia-Brunet, Fabienne

2014-08-01

Three commercial granular activated carbons (GACs) were studied at laboratory scale with a view to the combined adsorption and biodegradation of PCBs in aquatic sediment. The three GACs, with contrasting physico-chemical characteristics, all show a high adsorption of PCBs and are thus capable of reducing aqueous pollutant concentrations. After a one-month incubation with 'Aroclor 1242'-spiked sediment, the three GACs were each colonized by a multispecies biofilm, although with different amounts of attached bacterial biomass and significantly distinct genetic bacterial communities; interestingly, the highest bacterial biomass was attached to the microporous vegetable GAC. The multispecies biofilms developed on the three GACs were all predominantly composed of Proteobacteria, especially the β-, γ- and δ- subclasses, Chloroflexi and Acidobacteria, with genera previously found in environments containing PCBs or biphenyls, or able to perform cometabolic and direct PCB degradation. After an eight-month incubation under aerobic conditions, it was only the vegetable Picabiol GAC, with its low microporous volume, high total surface area and acidic property, that showed a significant (21%) reduction of tri- through penta-CB. Our results suggest that PCB bio-transformation by the bacterial community attached to the GAC is influenced by GAC's physico-chemical characteristics. Thus, a properly selected GAC could effectively be used to a) sequestrate and concentrate PCB from contaminated aquatic sediment and b) act as a support for efficient PCB degradation by an autochthonous bacterial biofilm. Copyright © 2014 Elsevier Ltd. All rights reserved.

Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

PubMed

Al-Masri, Ihab M; Mohammad, Mohammad K; Taha, Mutasem O

2008-11-01

Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

Chemical and toxicological evaluation of underground coal gasification (UCG) effluents. The coal rank effect.

PubMed

Kapusta, Krzysztof; Stańczyk, Krzysztof

2015-02-01

The effect of coal rank on the composition and toxicity of water effluents resulting from two underground coal gasification experiments with distinct coal samples (lignite and hard coal) was investigated. A broad range of organic and inorganic parameters was determined in the sampled condensates. The physicochemical tests were supplemented by toxicity bioassays based on the luminescent bacteria Vibrio fischeri as the test organism. The principal component analysis and Pearson correlation analysis were adopted to assist in the interpretation of the raw experimental data, and the multiple regression statistical method was subsequently employed to enable predictions of the toxicity based on the values of the selected parameters. Significant differences in the qualitative and quantitative description of the contamination profiles were identified for both types of coal under study. Independent of the coal rank, the most characteristic organic components of the studied condensates were phenols, naphthalene and benzene. In the inorganic array, ammonia, sulphates and selected heavy metals and metalloids were identified as the dominant constituents. Except for benzene with its alkyl homologues (BTEX), selected polycyclic aromatic hydrocarbons (PAHs), zinc and selenium, the values of the remaining parameters were considerably greater for the hard coal condensates. The studies revealed that all of the tested UCG condensates were extremely toxic to V. fischeri; however, the average toxicity level for the hard coal condensates was approximately 56% higher than that obtained for the lignite. The statistical analysis provided results supporting that the toxicity of the condensates was most positively correlated with the concentrations of free ammonia, phenols and certain heavy metals. Copyright © 2014 Elsevier Inc. All rights reserved.

DFT computations on: Crystal structure, vibrational studies and optical investigations of a luminescent self-assembled material

NASA Astrophysics Data System (ADS)

Kessentini, A.; Ben Ahmed, A.; Dammak, T.; Belhouchet, M.

2018-02-01

The current work undertakes the growth and the physicochemical properties of a novel green-yellow luminescence semi-organic material, the 3-picolylammonium bromide abbreviated (Pico-Br). In this paper, we report the X-ray diffraction measurements which show that the crystal lattice consists of distinct 3-picolylammonium cations and free bromide anions connected via Nsbnd H ⋯ Br and Nsbnd H ⋯ N hydrogen bonds leading to form a two dimensional frameworks. Molecular geometry compared with its optimized counterpart shows that the quantum chemical calculations carried out with density functional method (DFT) well produce the perceived structure by X-ray resolution of the studied material. To provide further insight into the spectroscopic properties, additional characterization of this material have been performed with Raman and infrared studies at room temperature. Theoretical computations have been computed using the (DFT) method at B3LYP/LanL2DZ level of theory implemented within Gaussian 03 program to study the vibrational spectra of the investigated molecule in the ground state. Optical absorption spectrum inspected by UV-visible absorption reveals the appearance of sharp optical gap of 280 nm (4.42 eV) as well as a strong green photoluminescence emission at 550 nm (2.25 eV) is detected on the photoluminescence (PL) spectrum at room temperature. Using the TD/DFT method, HOMO-LUMO energy gap and the Mulliken atomic charges were calculated in order to get an insight into the material. Good agreement between the theoretical results and the experimental ones was predicted.

Optimization of ultrasonic circulating extraction of samara oil from Acer saccharum using combination of Plackett-Burman design and Box-Behnken design.

PubMed

Chen, Fengli; Zhang, Qiang; Fei, Shimin; Gu, Huiyan; Yang, Lei

2017-03-01

In this study, ultrasonic circulating extraction (UCE) technique was firstly and successfully applied for extraction of samara oil from Acer saccharum. The extraction kinetics were fitted and described, and the extraction mechanism was discussed. Through comparison, n-hexane was selected as the extraction solvent, the influence of solvent type on the responses was detailedly interpreted based on the influence of their properties on the occurrence and intensity of cavitation. Seven parameters potentially influencing the extraction yield of samara oil and content of nervonic acid, including ultrasound irradiation time, ultrasound irradiation power, ultrasound temperature, liquid-solid ratio, soaking time, particle size and stirring rate, were screened through Plackett-Burman design to determine the significant variables. Then, three parameters performed statistically significant, including liquid-solid ratio, ultrasound irradiation time and ultrasound irradiation power, were further optimized using Box-Behnken design to predict optimum extraction conditions. Satisfactory yield of samara oil (11.72±0.38%) and content of nervonic acid (5.28±0.18%) were achieved using the optimal conditions. 1% proportion of ethanol in extraction solvent, 120°C of drying temperature and 6.4% moisture were selected and applied for effective extraction. There were no distinct differences in the physicochemical properties of samara oil obtained by UCE and Soxhlet extraction, and the samara oil obtained by UCE exhibited better antioxidant activities. Therefore, UCE method has enormous potential for efficient extraction of edible oil with high quality from plant materials. Copyright © 2016 Elsevier B.V. All rights reserved.

A Group 6 Late Embryogenesis Abundant Protein from Common Bean Is a Disordered Protein with Extended Helical Structure and Oligomer-forming Properties*

PubMed Central

Rivera-Najera, Lucero Y.; Saab-Rincón, Gloria; Battaglia, Marina; Amero, Carlos; Pulido, Nancy O.; García-Hernández, Enrique; Solórzano, Rosa M.; Reyes, José L.; Covarrubias, Alejandra A.

2014-01-01

Late embryogenesis-abundant proteins accumulate to high levels in dry seeds. Some of them also accumulate in response to water deficit in vegetative tissues, which leads to a remarkable association between their presence and low water availability conditions. A major sub-group of these proteins, also known as typical LEA proteins, shows high hydrophilicity and a high percentage of glycine and other small amino acid residues, distinctive physicochemical properties that predict a high content of structural disorder. Although all typical LEA proteins share these characteristics, seven groups can be distinguished by sequence similarity, indicating structural and functional diversity among them. Some of these groups have been extensively studied; however, others require a more detailed analysis to advance in their functional understanding. In this work, we report the structural characterization of a group 6 LEA protein from a common bean (Phaseolus vulgaris L.) (PvLEA6) by circular dichroism and nuclear magnetic resonance showing that it is a disordered protein in aqueous solution. Using the same techniques, we show that despite its unstructured nature, the addition of trifluoroethanol exhibited an intrinsic potential in this protein to gain helicity. This property was also promoted by high osmotic potentials or molecular crowding. Furthermore, we demonstrate that PvLEA6 protein is able to form soluble homo-oligomeric complexes that also show high levels of structural disorder. The association between PvLEA6 monomers to form dimers was shown to occur in plant cells by bimolecular fluorescence complementation, pointing to the in vivo functional relevance of this association. PMID:25271167

The ‘Sticky Patch’ Model of Crystallization and Modification of Proteins for Enhanced Crystallizability

PubMed Central

Derewenda, Zygmunt S.; Godzik, Adam

2017-01-01

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e. crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular ‘sticky patch’ model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer ‘sticky patches’ which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the ‘sticky patch’ model. We discuss state-of-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design of variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis. PMID:28573570

A zeta potential value determines the aggregate's size of penta-substituted [60]fullerene derivatives in aqueous suspension whereas positive charge is required for toxicity against bacterial cells.

PubMed

Deryabin, Dmitry G; Efremova, Ludmila V; Vasilchenko, Alexey S; Saidakova, Evgeniya V; Sizova, Elena A; Troshin, Pavel A; Zhilenkov, Alexander V; Khakina, Ekaterina A; Khakina, Ekaterina E

2015-08-08

The cause-effect relationships between physicochemical properties of amphiphilic [60]fullerene derivatives and their toxicity against bacterial cells have not yet been clarified. In this study, we report how the differences in the chemical structure of organic addends in 10 originally synthesized penta-substituted [60]fullerene derivatives modulate their zeta potential and aggregate's size in salt-free and salt-added aqueous suspensions as well as how these physicochemical characteristics affect the bioenergetics of freshwater Escherichia coli and marine Photobacterium phosphoreum bacteria. Dynamic light scattering, laser Doppler micro-electrophoresis, agarose gel electrophoresis, atomic force microscopy, and bioluminescence inhibition assay were used to characterize the fullerene aggregation behavior in aqueous solution and their interaction with the bacterial cell surface, following zeta potential changes and toxic effects. Dynamic light scattering results indicated the formation of self-assembled [60]fullerene aggregates in aqueous suspensions. The measurement of the zeta potential of the particles revealed that they have different surface charges. The relationship between these physicochemical characteristics was presented as an exponential regression that correctly described the dependence of the aggregate's size of penta-substituted [60]fullerene derivatives in salt-free aqueous suspension from zeta potential value. The prevalence of DLVO-related effects was shown in salt-added aqueous suspension that decreased zeta potential values and affected the aggregation of [60]fullerene derivatives expressed differently for individual compounds. A bioluminescence inhibition assay demonstrated that the toxic effect of [60]fullerene derivatives against E. coli cells was strictly determined by their positive zeta potential charge value being weakened against P. phosphoreum cells in an aquatic system of high salinity. Atomic force microscopy data suggested that the activity of positively charged [60]fullerene derivatives against bacterial cells required their direct interaction. The following zeta potential inversion on the bacterial cells surface was observed as an early stage of toxicity mechanism that violates the membrane-associated energetic functions. The novel data about interrelations between physicochemical parameters and toxic properties of amphiphilic [60]fullerene derivatives make possible predicting their behavior in aquatic environment and their activity against bacterial cells.

Physicochemical properties of quinoa starch.

PubMed

Li, Guantian; Wang, Sunan; Zhu, Fan

2016-02-10

Physicochemical properties of quinoa starches isolated from 26 commercial samples from a wide range of collection were studied. Swelling power (SP), water solubility index (WSI), amylose leaching (AML), enzyme susceptibility, pasting, thermal and textural properties were analyzed. Apparent amylose contents (AAM) ranged from 7.7 to 25.7%. Great variations in the diverse physicochemical properties were observed. Correlation analysis showed that AAM was the most significant factor related to AML, WSI, and pasting parameters. Correlations among diverse physicochemical parameters were analyzed. Principal component analysis using twenty three variables were used to visualize the difference among samples. Six principal components were extracted which could explain 88.8% of the total difference. The wide variations in physicochemical properties could contribute to innovative utilization of quinoa starch for food and non-food applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Can benthic foraminifera be used as bio-indicators of pollution in areas with a wide range of physicochemical variability?

NASA Astrophysics Data System (ADS)

Martins, Maria Virgínia Alves; Pinto, Anita Fernandes Souza; Frontalini, Fabrizio; da Fonseca, Maria Clara Machado; Terroso, Denise Lara; Laut, Lazaro Luiz Mattos; Zaaboub, Noureddine; da Conceição Rodrigues, Maria Antonieta; Rocha, Fernando

2016-12-01

The Ria de Aveiro, a lagoon located in the NW coast of Portugal, presents a wide range of changes to the natural hydrodynamical and physicochemical conditions induced for instance by works of port engineering and pollution. In order to evaluate the response of living benthic foraminifera to the fluctuations in physicochemical parameters and pollution (metals and TOC), eight sediment samples were collected from canals and salt pans within the Aveiro City, in four different sampling events. During the sampling events, salinity showed the most significant fluctuations among the physicochemical parameters with the maximum range of variation at Troncalhada and Santiago salt pans. Species such as Haynesina germanica, Trochammina inflata and Entzia macrescens were found inhabiting these hypersaline environments with the widest fluctuations of physicochemical parameters. In contrast, Ammonia tepida dominated zones with high concentrations of metals and organic matter and in lower salinity waters. Parameters related to benthic foraminiferal assemblages (i.e., diversity and evenness) were found to significantly decline in stations polluted by metals and characterized by higher TOC content. Foraminiferal density reduced significantly in locations with a wide range of physicochemical temporal variability. This work shows that, even under extreme conditions caused by highly variable physicochemical parameters, benthic foraminiferal assemblages might be used as valuable bioindicators of environmental stress.

The Predictive Utility of Narcissism among Children and Adolescents: Evidence for a Distinction between Adaptive and Maladaptive Narcissism

ERIC Educational Resources Information Center

Barry, Christopher T.; Frick, Paul J.; Adler, Kristy K.; Grafeman, Sarah J.

2007-01-01

We examined the predictive utility of narcissism among a community sample of children and adolescents (N=98) longitudinally. Analyses focused on the differential utility between maladaptive and adaptive narcissism for predicting later delinquency. Maladaptive narcissism significantly predicted self-reported delinquency at one-, two-, and…

Multivariate neural biomarkers of emotional states are categorically distinct

PubMed Central

Kragel, Philip A.

2015-01-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. PMID:25813790

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

PubMed

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Comprehensive ripeness-index for prediction of ripening level in mangoes by multivariate modelling of ripening behaviour

NASA Astrophysics Data System (ADS)

Eyarkai Nambi, Vijayaram; Thangavel, Kuladaisamy; Manickavasagan, Annamalai; Shahir, Sultan

2017-01-01

Prediction of ripeness level in climacteric fruits is essential for post-harvest handling. An index capable of predicting ripening level with minimum inputs would be highly beneficial to the handlers, processors and researchers in fruit industry. A study was conducted with Indian mango cultivars to develop a ripeness index and associated model. Changes in physicochemical, colour and textural properties were measured throughout the ripening period and the period was classified into five stages (unripe, early ripe, partially ripe, ripe and over ripe). Multivariate regression techniques like partial least square regression, principal component regression and multi linear regression were compared and evaluated for its prediction. Multi linear regression model with 12 parameters was found more suitable in ripening prediction. Scientific variable reduction method was adopted to simplify the developed model. Better prediction was achieved with either 2 or 3 variables (total soluble solids, colour and acidity). Cross validation was done to increase the robustness and it was found that proposed ripening index was more effective in prediction of ripening stages. Three-variable model would be suitable for commercial applications where reasonable accuracies are sufficient. However, 12-variable model can be used to obtain more precise results in research and development applications.

Non-animal methods to predict skin sensitization (I): the Cosmetics Europe database.

PubMed

Hoffmann, Sebastian; Kleinstreuer, Nicole; Alépée, Nathalie; Allen, David; Api, Anne Marie; Ashikaga, Takao; Clouet, Elodie; Cluzel, Magalie; Desprez, Bertrand; Gellatly, Nichola; Goebel, Carsten; Kern, Petra S; Klaric, Martina; Kühnl, Jochen; Lalko, Jon F; Martinozzi-Teissier, Silvia; Mewes, Karsten; Miyazawa, Masaaki; Parakhia, Rahul; van Vliet, Erwin; Zang, Qingda; Petersohn, Dirk

2018-05-01

Cosmetics Europe, the European Trade Association for the cosmetics and personal care industry, is conducting a multi-phase program to develop regulatory accepted, animal-free testing strategies enabling the cosmetics industry to conduct safety assessments. Based on a systematic evaluation of test methods for skin sensitization, five non-animal test methods (DPRA (Direct Peptide Reactivity Assay), KeratinoSens TM , h-CLAT (human cell line activation test), U-SENS TM , SENS-IS) were selected for inclusion in a comprehensive database of 128 substances. Existing data were compiled and completed with newly generated data, the latter amounting to one-third of all data. The database was complemented with human and local lymph node assay (LLNA) reference data, physicochemical properties and use categories, and thoroughly curated. Focused on the availability of human data, the substance selection resulted nevertheless resulted in a high diversity of chemistries in terms of physico-chemical property ranges and use categories. Predictivities of skin sensitization potential and potency, where applicable, were calculated for the LLNA as compared to human data and for the individual test methods compared to both human and LLNA reference data. In addition, various aspects of applicability of the test methods were analyzed. Due to its high level of curation, comprehensiveness, and completeness, we propose our database as a point of reference for the evaluation and development of testing strategies, as done for example in the associated work of Kleinstreuer et al. We encourage the community to use it to meet the challenge of conducting skin sensitization safety assessment without generating new animal data.

Study of degradation behaviour of montelukast sodium and its marketed formulation in oxidative and accelerated test conditions and prediction of physicochemical and ADMET properties of its degradation products using ADMET Predictor™.

PubMed

Tiwari, Shobhit Kumar; Singh, Dilip Kumar; Ladumor, Mayurbhai Kathadbhai; Chakraborti, Asit K; Singh, Saranjit

2018-05-26

Study of oxidative stability of pharmaceutical actives and formulations is important as oxidation pathway is the second most significant route for the decay of pharmaceuticals. Montelukast sodium, a leukotriene receptor antagonist, is prone to oxidation reactions owing to sensitive moieties in its structure. It is also known to be light sensitive. This study was aimed to understand the degradation behaviour of the drug in different oxidative media containing hydrogen peroxide, AIBN, Fe 3+ , Fenton's reagent and O 2 environment under normal laboratory light conditions. The degradation behaviour of the drug was also evaluated in solid sate under ICH recommended accelerated stability condition of 40 °C/75% RH to correlate with the degradation products (DPs) formed in a solid oral formulation. A total of nine DPs (MTK 1 to MTK 9) were formed from both the drug substance and the marketed tablet formulation on storage under controlled oxygen environment in normal laboratory light and temperature conditions. These DPs were well separated on a C-18 column using a gradient HPLC method. The characterization of DPs was done based on HRMS and multi-stage tandem mass spectrometric (MS n ) data. The knowledge of the structure of DPs helped in laying down degradation pathway of the drug. Also, mechanism for the formation of each DP was postulated. Finally, physicochemical as well as absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of the DPs were predicted by ADMET Predictor™ software. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

Taxonomic and functional characteristics of microbial communities and their correlation with physicochemical properties of four geothermal springs in Odisha, India

PubMed Central

Badhai, Jhasketan; Ghosh, Tarini S.; Das, Subrata K.

2015-01-01

This study describes microbial diversity in four tropical hot springs representing moderately thermophilic environments (temperature range: 40–58°C; pH: 7.2–7.4) with discrete geochemistry. Metagenome sequence data showed a dominance of Bacteria over Archaea; the most abundant phyla were Chloroflexi and Proteobacteria, although other phyla were also present, such as Acetothermia, Nitrospirae, Acidobacteria, Firmicutes, Deinococcus-Thermus, Bacteroidetes, Thermotogae, Euryarchaeota, Verrucomicrobia, Ignavibacteriae, Cyanobacteria, Actinobacteria, Planctomycetes, Spirochaetes, Armatimonadetes, Crenarchaeota, and Aquificae. The distribution of major genera and their statistical correlation analyses with the physicochemical parameters predicted that the temperature, aqueous concentrations of ions (such as sodium, chloride, sulfate, and bicarbonate), total hardness, dissolved solids and conductivity were the main environmental variables influencing microbial community composition and diversity. Despite the observed high taxonomic diversity, there were only little variations in the overall functional profiles of the microbial communities in the four springs. Genes involved in the metabolism of carbohydrates and carbon fixation were the most abundant functional class of genes present in these hot springs. The distribution of genes involved in carbon fixation predicted the presence of all the six known autotrophic pathways in the metagenomes. A high prevalence of genes involved in membrane transport, signal transduction, stress response, bacterial chemotaxis, and flagellar assembly were observed along with genes involved in the pathways of xenobiotic degradation and metabolism. The analysis of the metagenomic sequences affiliated to the candidate phylum Acetothermia from spring TB-3 provided new insight into the metabolism and physiology of yet-unknown members of this lineage of bacteria. PMID:26579081

Taxonomic and functional characteristics of microbial communities and their correlation with physicochemical properties of four geothermal springs in Odisha, India.

PubMed

Badhai, Jhasketan; Ghosh, Tarini S; Das, Subrata K

2015-01-01

This study describes microbial diversity in four tropical hot springs representing moderately thermophilic environments (temperature range: 40-58°C; pH: 7.2-7.4) with discrete geochemistry. Metagenome sequence data showed a dominance of Bacteria over Archaea; the most abundant phyla were Chloroflexi and Proteobacteria, although other phyla were also present, such as Acetothermia, Nitrospirae, Acidobacteria, Firmicutes, Deinococcus-Thermus, Bacteroidetes, Thermotogae, Euryarchaeota, Verrucomicrobia, Ignavibacteriae, Cyanobacteria, Actinobacteria, Planctomycetes, Spirochaetes, Armatimonadetes, Crenarchaeota, and Aquificae. The distribution of major genera and their statistical correlation analyses with the physicochemical parameters predicted that the temperature, aqueous concentrations of ions (such as sodium, chloride, sulfate, and bicarbonate), total hardness, dissolved solids and conductivity were the main environmental variables influencing microbial community composition and diversity. Despite the observed high taxonomic diversity, there were only little variations in the overall functional profiles of the microbial communities in the four springs. Genes involved in the metabolism of carbohydrates and carbon fixation were the most abundant functional class of genes present in these hot springs. The distribution of genes involved in carbon fixation predicted the presence of all the six known autotrophic pathways in the metagenomes. A high prevalence of genes involved in membrane transport, signal transduction, stress response, bacterial chemotaxis, and flagellar assembly were observed along with genes involved in the pathways of xenobiotic degradation and metabolism. The analysis of the metagenomic sequences affiliated to the candidate phylum Acetothermia from spring TB-3 provided new insight into the metabolism and physiology of yet-unknown members of this lineage of bacteria.

Some pungent arguments against the physico-chemical theories of the origin of the genetic code and corroborating the coevolution theory.

PubMed

Di Giulio, Massimo

2017-02-07

Whereas it is extremely easy to prove that "if the biosynthetic relationships between amino acids were fundamental in the structuring of the genetic code, then their physico-chemical properties might also be revealed in the genetic code table"; it is, on the contrary, impossible to prove that "if the physico-chemical properties of amino acids were fundamental in the structuring of the genetic code, then the presence of the biosynthetic relationships between amino acids should not be revealed in the genetic code". And, given that in the genetic code table are mirrored both the biosynthetic relationships between amino acids and their physico-chemical properties, all this would be a test that would falsify the physico-chemical theories of the origin of the genetic code. That is to say, if the physico-chemical properties of amino acids had a fundamental role in organizing the genetic code, then we would not have duly revealed the presence - in the genetic code - of the biosynthetic relationships between amino acids, and on the contrary this has been observed. Therefore, this falsifies the physico-chemical theories of genetic code origin. Whereas, the coevolution theory of the origin of the genetic code would be corroborated by this analysis, because it would be able to give a description of evolution of the genetic code more coherent with the indisputable empirical observations that link both the biosynthetic relationships of amino acids and their physico-chemical properties to the evolutionary organization of the genetic code. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning and Motivational Processes Contributing to Pavlovian-Instrumental Transfer and Their Neural Bases: Dopamine and Beyond.

PubMed

Corbit, Laura H; Balleine, Bernard W

2016-01-01

Pavlovian stimuli exert a range of effects on behavior from simple conditioned reflexes, such as salivation, to altering the vigor and direction of instrumental actions. It is currently accepted that these distinct behavioral effects stem from two sources (i) the various associative connections between predictive stimuli and the component features of the events that these stimuli predict and (ii) the distinct motivational and cognitive functions served by cues, particularly their arousing and informational effects on the selection and performance of specific actions. Here, we describe studies that have assessed these latter phenomena using a paradigm that has come to be called Pavlovian-instrumental transfer. We focus first on behavioral experiments that have described distinct sources of stimulus control derived from the general affective and outcome-specific predictions of conditioned stimuli, referred to as general transfer and specific transfer, respectively. Subsequently, we describe research efforts attempting to establish the neural bases of these transfer effects, largely in the afferent and efferent connections of the nucleus accumbens (NAc) core and shell. Finally, we examine the role of predictive cues in examples of aberrant stimulus control associated with psychiatric disorders and addiction.

Predicting protein amidation sites by orchestrating amino acid sequence features

NASA Astrophysics Data System (ADS)

Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

2017-08-01

Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

Effect of infrared and conventional drying methods on physicochemical characteristics of stored white rice

USDA-ARS?s Scientific Manuscript database

The objective of this study was to investigate the effect of infrared (IR) drying followed by tempering and natural cooling on the change of physicochemical characteristics of white rice during up to 10 months of storage. The physicochemical characteristics of IR dried rice was also compared with th...

Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states

PubMed Central

Chandrasekaran, Sriram; Ament, Seth A.; Eddy, James A.; Rodriguez-Zas, Sandra L.; Schatz, Bruce R.; Price, Nathan D.; Robinson, Gene E.

2011-01-01

Using brain transcriptomic profiles from 853 individual honey bees exhibiting 48 distinct behavioral phenotypes in naturalistic contexts, we report that behavior-specific neurogenomic states can be inferred from the coordinated action of transcription factors (TFs) and their predicted target genes. Unsupervised hierarchical clustering of these transcriptomic profiles showed three clusters that correspond to three ecologically important behavioral categories: aggression, maturation, and foraging. To explore the genetic influences potentially regulating these behavior-specific neurogenomic states, we reconstructed a brain transcriptional regulatory network (TRN) model. This brain TRN quantitatively predicts with high accuracy gene expression changes of more than 2,000 genes involved in behavior, even for behavioral phenotypes on which it was not trained, suggesting that there is a core set of TFs that regulates behavior-specific gene expression in the bee brain, and other TFs more specific to particular categories. TFs playing key roles in the TRN include well-known regulators of neural and behavioral plasticity, e.g., Creb, as well as TFs better known in other biological contexts, e.g., NF-κB (immunity). Our results reveal three insights concerning the relationship between genes and behavior. First, distinct behaviors are subserved by distinct neurogenomic states in the brain. Second, the neurogenomic states underlying different behaviors rely upon both shared and distinct transcriptional modules. Third, despite the complexity of the brain, simple linear relationships between TFs and their putative target genes are a surprisingly prominent feature of the networks underlying behavior. PMID:21960440

Seasonal succession of estuarine fish, shrimps, macrozoobenthos and plankton: Physico-chemical and trophic influence. The Gironde estuary as a case study

NASA Astrophysics Data System (ADS)

Selleslagh, Jonathan; Lobry, Jérémy; N'Zigou, Aimé Roger; Bachelet, Guy; Blanchet, Hugues; Chaalali, Aurélie; Sautour, Benoît; Boët, Philippe

2012-10-01

Characterization of the structure and seasonal variability of biotic communities is essential for a better understanding of estuarine ecosystem functioning and in order to manage these highly fluctuating and naturally stressed systems. Numerous studies have investigated the role of environmental factors in controlling temporal variations in biotic communities. However, most have concluded that the explanatory power of physico-chemical variables was significant but not sufficient to explain ecological dynamics. The present study aimed to propose the importance of trophic interactions as an additional structuring factor of species seasonal variability by examining simultaneous dynamics of all estuarine biotic communities, using the oligo-mesohaline area of the Gironde estuary (SW France) as a case study. Data on the main biological groups (fish, shrimps, macrozoobenthos and plankton) sampled during a five-year period (2004-2008) at monthly intervals using a well standardized protocol, as well as data on environmental variables, were compiled here for the first time. According to species composition, the Gironde estuary is used as a nursery, feeding, resident and migratory habitat. For almost all species, strong seasonal fluctuations occurred with a succession of species, indicating an optimization of the use of the available resources over a typical year by estuarine biological communities. Multivariate analyses discriminated four seasonal groups of species with two distinctive ecological seasons. A clear shift in July indicated a biomass transfer from a "planktonic phase" to a "bentho-demersal phase", corresponding to spring and summer-autumn periods, respectively. With regard to the temporal fluctuations of dominant species of all biological groups, this study highlighted the possible influence of trophic relationships, predation in particular, on seasonal variations in species abundance, in addition to the physico-chemical influence. This study enabled us to collate important seasonal data and to discuss their integration into seasonal models of estuarine functioning and/or specific prey-predator models. In a global change context, prey abundance variations could generate changes in the temporal dynamics of their predators (and conversely), and potentially in the functioning of the whole estuarine system.

Pectin is not pectin: a randomized trial on the effect of different physicochemical properties of dietary fiber on appetite and energy intake.

PubMed

Wanders, Anne J; Feskens, Edith J M; Jonathan, Melliana C; Schols, Henk A; de Graaf, Cees; Mars, Monica

2014-04-10

An increased intake of dietary fiber has been associated with reduced appetite and reduced energy intake. Research on the effects of seemingly identical classes of dietary fiber on appetite has, however, resulted in conflicting findings. The present study investigated the effects of different fiber properties, including methods of supplementation, on appetite and energy intake. This was a randomized crossover study with 29 subjects (21±2 y, BMI: 21.9±1.8 kg/m(2)) consuming dairy based liquid test products (1.5 MJ, 435 g) containing either: no pectin, bulking pectin (10 g), viscous pectin (10 g), or gelled pectin (10 g). The gelled pectin was also supplemented as capsules (10 g), and as liquid (10 g). Physicochemical properties of the test products were assessed. Appetite, glucose, insulin and gastric emptying were measured before ingestion and after fixed time intervals. Energy intake was measured after 3 h. Preload viscosity was larger for gelled>viscous>bulking>no pectin, and was larger for gelled>liquid>capsules. Appetite was reduced after ingestion of gelled pectin compared to bulking (p<0.0001), viscous (p=0.005) and no pectin (p<0.0001), without differences in subsequent energy intake (p=0.32). Gastric emptying rate was delayed after gelled pectin (82±18 min) compared to no pectin (70±19 min, p=0.015). Furthermore, gelled (p=0.002) and viscous (p<0.0001) pectin lowered insulin responses compared to no pectin, with minor reductions in glucose response. Regarding methods of supplementation, appetite was reduced after ingestion of the gelled test product compared to after capsules (p<0.0001) and liquid (p<0.0001). Energy intake was lower after ingestion of capsules compared to liquid (-12.4%, p=0.03). Different methods of supplementation resulted in distinct metabolic parameters. Results suggest that different physicochemical properties of pectin, including methods of supplementation, impact appetite and energy intake differently. Reduced appetite was probably mediated by preload physical properties, whereas inconsistent associations with metabolic parameters were found. Copyright © 2014 Elsevier Inc. All rights reserved.

Data on changes in red wine phenolic compounds, headspace aroma compounds and sensory profile after treatment of red wines with activated carbons with different physicochemical characteristics.

PubMed

Filipe-Ribeiro, Luís; Milheiro, Juliana; Matos, Carlos C; Cosme, Fernanda; Nunes, Fernando M

2017-06-01

Data in this article presents the changes on phenolic compounds, headspace aroma composition and sensory profile of a red wine spiked with 4-ethylphenol and 4-ethylguaiacol and treated with seven activated carbons with different physicochemical characteristics, namely surface area, micropore volume and mesopore volume ("Reduction of 4-ethylphenol and 4-ethylguaiacol in red wine by activated carbons with different physicochemical characteristics: impact on wine quality" Filipe-Ribeiro et al. (2017) [1]). Data on the physicochemical characteristics of the activated carbons are shown. Statistical data on the sensory expert panel consistency by General Procrustes Analysis is shown. Statistical data is also shown, which correlates the changes in chemical composition of red wines with the physicochemical characteristics of activated carbons used.

Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes.

PubMed

Berthod, L; Whitley, D C; Roberts, G; Sharpe, A; Greenwood, R; Mills, G A

2017-02-01

Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (K d ). Experimental K d values (n=297) for active pharmaceutical ingredients (n=148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions). Univariate models relating log K d to log K ow for each charge class showed weak correlations (maximum R 2 =0.51 for positively charged) with no overall correlation for the combined dataset (R 2 =0.04). Weaker correlations were found when relating log K d to log D ow . Three sets of molecular descriptors (Molecular Operating Environment, VolSurf and ParaSurf) encoding a range of physico-chemical properties were used to derive multivariate models using stepwise regression, partial least squares and Bayesian artificial neural networks (ANN). The best predictive performance was obtained with ANN, with R 2 =0.62-0.69 for these descriptors using the complete dataset. Use of more complex Vsurf and ParaSurf descriptors showed little improvement over Molecular Operating Environment descriptors. The most influential descriptors in the ANN models, identified by automatic relevance determination, highlighted the importance of hydrophobicity, charge and molecular shape effects in these sorbate-sorbent interactions. The heterogeneous nature of the different sewage sludges used to measure K d limited the predictability of sorption from physico-chemical properties of the pharmaceuticals alone. Standardization of test materials for the measurement of K d would improve comparability of data from different studies, in the long-term leading to better quality environmental risk assessments. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Combination of partial least squares regression and design of experiments to model the retention of pharmaceutical compounds in supercritical fluid chromatography.

PubMed

Andri, Bertyl; Dispas, Amandine; Marini, Roland Djang'Eing'a; Hubert, Philippe; Sassiat, Patrick; Al Bakain, Ramia; Thiébaut, Didier; Vial, Jérôme

2017-03-31

This work presents a first attempt to establish a model of the retention behaviour for pharmaceutical compounds in gradient mode SFC. For this purpose, multivariate statistics were applied on the basis of data gathered with the Design of Experiment (DoE) methodology. It permitted to build optimally the experiments needed, and served as a basis for providing relevant physicochemical interpretation of the effects observed. Data gathered over a broad experimental domain enabled the establishment of well-fit linear models of the retention of the individual compounds in presence of methanol as co-solvent. These models also allowed the appreciation of the impact of each experimental parameter and their factorial combinations. This approach was carried out with two organic modifiers (i.e. methanol and ethanol) and provided comparable results. Therefore, it demonstrates the feasibility to model retention in gradient mode SFC for individual compounds as a function of the experimental conditions. This approach also permitted to highlight the predominant effect of some parameters (e.g. gradient slope and pressure) on the retention of compounds. Because building of individual models of retention was possible, the next step considered the establishment of a global model of the retention to predict the behaviour of given compounds on the basis of, on the one side, the physicochemical descriptors of the compounds (e.g. Linear Solvation Energy Relationship (LSER) descriptors) and, on the other side, of the experimental conditions. This global model was established by means of partial least squares regression for the selected compounds, in an experimental domain defined by the Design of Experiment (DoE) methodology. Assessment of the model's predictive capabilities revealed satisfactory agreement between predicted and actual retention (i.e. R 2 =0.942, slope=1.004) of the assessed compounds, which is unprecedented in the field. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion.

PubMed

Solon, Kimberly; Flores-Alsina, Xavier; Mbamba, Christian Kazadi; Volcke, Eveline I P; Tait, Stephan; Batstone, Damien; Gernaey, Krist V; Jeppsson, Ulf

2015-03-01

Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections) and ion pairing on modelling of anaerobic digestion processes in such plant-wide models of wastewater treatment. Using the BSM2 as a case study with a number of model variants and cationic load scenarios, this paper presents the effects of an improved physico-chemical description on model predictions and overall plant performance indicators, namely effluent quality index (EQI) and operational cost index (OCI). The acid-base equilibria implemented in the Anaerobic Digestion Model No. 1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. A speciation sub-routine based on a multi-dimensional Newton-Raphson (NR) iteration method is developed to address algebraic interdependencies. The model also includes ion pairs that play an important role in wastewater treatment. The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength demonstrate that corrections to account for non-ideal conditions lead to significant differences in predicted process performance (up to 18% for effluent quality and 7% for operational cost) but that for pH prediction, activity corrections are more important than ion pairing effects. Both are likely to be required when precipitation is to be modelled. Copyright © 2014 Elsevier Ltd. All rights reserved.

Implementation of the effects of physicochemical properties on the foliar penetration of pesticides and its potential for estimating pesticide volatilization from plants.

PubMed

Lichiheb, Nebila; Personne, Erwan; Bedos, Carole; Van den Berg, Frederik; Barriuso, Enrique

2016-04-15

Volatilization from plant foliage is known to have a great contribution to pesticide emission to the atmosphere. However, its estimation is still difficult because of our poor understanding of processes occurring at the leaf surface. A compartmental approach for dissipation processes of pesticides applied on the leaf surface was developed on the base of experimental study performed under controlled conditions using laboratory volatilization chamber. This approach was combined with physicochemical properties of pesticides and was implemented in SURFATM-Pesticides model in order to predict pesticide volatilization from plants in a more mechanistic way. The new version of SURFATM-Pesticide model takes into account the effect of formulation on volatilization and leaf penetration. The model was evaluated in terms of 3 pesticides applied on plants at the field scale (chlorothalonil, fenpropidin and parathion) which display a wide range of volatilization rates. The comparison of modeled volatilization fluxes with measured ones shows an overall good agreement for the three tested compounds. Furthermore the model confirms the considerable effect of the formulation on the rate of the decline in volatilization fluxes especially for systemic products. However, due to the lack of published information on the substances in the formulations, factors accounting for the effect of formulation are described empirically. A sensitivity analysis shows that in addition to vapor pressure, the octanol-water partition coefficient represents important physicochemical properties of pesticides affecting pesticide volatilization from plants. Finally the new version of SURFATM-Pesticides is a prospecting tool for key processes involved in the description of pesticide volatilization from plants. Copyright © 2016 Elsevier B.V. All rights reserved.

Thermal and physicochemical properties important for the long term behavior of nuclear waste glasses

NASA Astrophysics Data System (ADS)

Matzke, Hj.; Vernaz, E.

High level nuclear waste from reprocessing of spent nuclear fuel has to be solidified in a stable matrix for safe long-time storage. Vitrification in borosilicate glasses is the technique accepted worldwide as the best combination of engineering constraints from fabrication and physicochemical properties of the matrix. A number of different glasses was developed in different national programs. The criteria and the reasons for selecting the final compositions are described briefly. Emphasis is placed on the French product R7T7 and on thermal and physicochemical properties though glasses developed in other national projects (e.g., the German product GP 98/12, etc.) are also treated. The basic physical and mechanical properties and the chemical durability of the glass in contact with water are described. The basic mechanisms of aqueous corrosion are discussed and the evolving modelling of the leaching process is dealt with, as well as effects of container material, backfill, etc. The thermal behavior has also been studied and extensive data exist on diffusion of glass constituents (Na) and of interesting elements of the waste such as the alkalis Rb and Cs or the actinides U and Pu, as well as on crystallization processes in the glass during storage at elevated temperatures. Emphasis is placed on the radiation stability of the glasses, based on extensive studies using short-lived actinides (e.g., 244Cm) or ion implantation to produce the damage expected during long storage at an accelerated rate. The radiation stability is shown to be very good, if realistic damage conditions are used. The knowledge accumulated in the past years is used to evaluate and predict the long-term evolution of the glass under storage conditions.

The nematode Caenorhabditis elegans as an integrated toxicological tool to assess water quality and pollution.

PubMed

Clavijo, Araceli; Kronberg, María Florencia; Rossen, Ariana; Moya, Aldana; Calvo, Daniel; Salatino, Santa Esmeralda; Pagano, Eduardo Antonio; Morábito, José Antonio; Munarriz, Eliana Rosa

2016-11-01

Determination of water quality status in rivers is critical to establish a sustainable water management policy. For this reason, over the last decades it has been recommended to perform integrated water assessments that include water quantities and physicochemical, ecological and toxicological tests. However, sometimes resources are limited and it is not possible to perform large-scale chemical determinations of pollutants or conduct numerous ecotoxicological tests. To overcome this problem we use and measure the growth, as a response parameter, of the soil nematode Caenorhabditis elegans to assess water quality in rivers. The C. elegans is a ubiquitous organism that has emerged as an important model organism in aquatic and soil toxicology research. The Tunuyán River Basin (Province of Mendoza, Argentina) has been selected as a representative traditional water monitoring system to test the applicability of the C. elegans toxicological bioassay to generate an integrated water quality evaluation. Jointly with the C. elegans toxic assays, physicochemical and bacteriological parameters were determined for each monitoring site. C. elegans bioassays help to identify different water qualities in the river basin. Multivariate statistical analysis (PCA and linear regression models) has allowed us to confirm that traditional water quality studies do not predict potential toxic effects on living organisms. On the contrary, physicochemical and bacteriological analyzes explain <62% of the C. elegans growth response variability, showing that ecotoxicological bioassays are important to obtain a realistic scenario of water quality threats. Our results confirm that the C. elegans bioassay is a sensible and suitable tool to assess toxicity and should be implemented in routine water quality monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.

Vegetation/soil distribution of semivolatile organic compounds in relation to their physicochemical properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weiss, P.

The concentrations (C) of several semivolatile organic compounds (SOCs) in Norway spruce needles (N) and in the local humus horizon (O) of 25 remote Austrian forest sites were used to calculate an ecosystem-oriented partition coefficient needles/humus horizon (C{sub N}/C{sub O}). Between 66 and 78% of the compounds' variation of this quotient could be explained by each of the following physicochemical parameters: vapor pressure (p{sub s}) and the partition coefficients n-octanol/water (K{sub OW}), n-octanol/air (K{sub OA}), and adsorbed/ dissolved in soil (K{sub OC}) of the compounds. This result further underlines the usefulness of these parameters for predicting the behavior of SOCsmore » in terrestrial ecosystems. Compounds with low p{sub s} and high K{sub OW}, K{sub OA}, and K{sub OC} show a very low C{sub N}/C{sub O} quotient, which implies a higher accumulation of these compounds in the O horizon than in the needles. The role of forest soils as sink for these SOCs is demonstrated. Alternatively, C{sub N}/C{sub O} > 1, due to higher concentrations in the needles than in the O horizon, have been shown for SOCs with comparably high p{sub s} and low K{sub OW}, K{sub OA}, and K{sub OC}. In this respect, the possible role of revolatilization of the more volatile SOCs from soils to needles is discussed. In the mineral soil layers below the O horizon, SOCs with lower K{sub OC} and better water solubility tend to be less accumulated. However, if all investigated compounds are taken into consideration, accumulation in the mineral soil layers showed no general trend in relation to the selected physicochemical parameters.« less

Physicochemical Characterization of Iron Carbohydrate Colloid Drug Products.

PubMed

Zou, Peng; Tyner, Katherine; Raw, Andre; Lee, Sau

2017-09-01

Iron carbohydrate colloid drug products are intravenously administered to patients with chronic kidney disease for the treatment of iron deficiency anemia. Physicochemical characterization of iron colloids is critical to establish pharmaceutical equivalence between an innovator iron colloid product and generic version. The purpose of this review is to summarize literature-reported techniques for physicochemical characterization of iron carbohydrate colloid drug products. The mechanisms, reported testing results, and common technical pitfalls for individual characterization test are discussed. A better understanding of the physicochemical characterization techniques will facilitate generic iron carbohydrate colloid product development, accelerate products to market, and ensure iron carbohydrate colloid product quality.

Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

PubMed

de Kanter, Ruben; Sidharta, Patricia N; Delahaye, Stéphane; Gnerre, Carmela; Segrestaa, Jerome; Buchmann, Stephan; Kohl, Christopher; Treiber, Alexander

2016-03-01

Macitentan is a novel dual endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). It is metabolized by cytochrome P450 (CYP) enzymes, mainly CYP3A4, to its active metabolite ACT-132577. A physiological-based pharmacokinetic (PBPK) model was developed by combining observations from clinical studies and physicochemical parameters as well as absorption, distribution, metabolism and excretion parameters determined in vitro. The model predicted the observed pharmacokinetics of macitentan and its active metabolite ACT-132577 after single and multiple dosing. It performed well in recovering the observed effect of the CYP3A4 inhibitors ketoconazole and cyclosporine, and the CYP3A4 inducer rifampicin, as well as in predicting interactions with S-warfarin and sildenafil. The model was robust enough to allow prospective predictions of macitentan-drug combinations not studied, including an alternative dosing regimen of ketoconazole and nine other CYP3A4-interacting drugs. Among these were the HIV drugs ritonavir and saquinavir, which were included because HIV infection is a known risk factor for the development of PAH. This example of the application of PBPK modeling to predict drug-drug interactions was used to support the labeling of macitentan (Opsumit).

QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

PubMed Central

Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

2009-01-01

A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

Microbial Survey of Pennsylvania Surface Water Used for Irrigating Produce Crops.

PubMed

Draper, Audrey D; Doores, Stephanie; Gourama, Hassan; LaBorde, Luke F

2016-06-01

Recent produce-associated foodborne illness outbreaks have been attributed to contaminated irrigation water. This study examined microbial levels in Pennsylvania surface waters used for irrigation, relationships between microbial indicator organisms and water physicochemical characteristics, and the potential use of indicators for predicting the presence of human pathogens. A total of 153 samples taken from surface water sources used for irrigation in southeastern Pennsylvania were collected from 39 farms over a 2-year period. Samples were analyzed for six microbial indicator organisms (aerobic plate count, Enterobacteriaceae, coliform, fecal coliforms, Escherichia coli, and enterococci), two human pathogens (Salmonella and E. coli O157), and seven physical and environmental characteristics (pH, conductivity, turbidity, air and water temperature, and sampling day and 3-day-accumulated precipitation levels). Indicator populations were highly variable and not predicted by water and environmental characteristics. Only five samples were confirmed positive for Salmonella, and no E. coli O157 was detected in any samples. Predictive relationships between microbial indicators and the occurrence of pathogens could therefore not be determined.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Creation of Novel Cores for β-Secretase (BACE-1) Inhibitors: A Multiparameter Lead Generation Strategy

PubMed Central

2014-01-01

In order to find optimal core structures as starting points for lead optimization, a multiparameter lead generation workflow was designed with the goal of finding BACE-1 inhibitors as a treatment for Alzheimer’s disease. De novo design of core fragments was connected with three predictive in silico models addressing target affinity, permeability, and hERG activity, in order to guide synthesis. Taking advantage of an additive SAR, the prioritized cores were decorated with a few, well-characterized substituents from known BACE-1 inhibitors in order to allow for core-to-core comparisons. Prediction methods and analyses of how physicochemical properties of the core structures correlate to in vitro data are described. The syntheses and in vitro data of the test compounds are reported in a separate paper by Ginman et al. [J. Med. Chem.2013, 56, 4181–4205]. The affinity predictions are described in detail by Roos et al. [J. Chem. Inf.2014, DOI: 10.1021/ci400374z]. PMID:24900855

Creation of Novel Cores for β-Secretase (BACE-1) Inhibitors: A Multiparameter Lead Generation Strategy.

PubMed

Viklund, Jenny; Kolmodin, Karin; Nordvall, Gunnar; Swahn, Britt-Marie; Svensson, Mats; Gravenfors, Ylva; Rahm, Fredrik

2014-04-10

In order to find optimal core structures as starting points for lead optimization, a multiparameter lead generation workflow was designed with the goal of finding BACE-1 inhibitors as a treatment for Alzheimer's disease. De novo design of core fragments was connected with three predictive in silico models addressing target affinity, permeability, and hERG activity, in order to guide synthesis. Taking advantage of an additive SAR, the prioritized cores were decorated with a few, well-characterized substituents from known BACE-1 inhibitors in order to allow for core-to-core comparisons. Prediction methods and analyses of how physicochemical properties of the core structures correlate to in vitro data are described. The syntheses and in vitro data of the test compounds are reported in a separate paper by Ginman et al. [J. Med. Chem. 2013, 56, 4181-4205]. The affinity predictions are described in detail by Roos et al. [J. Chem. Inf. 2014, DOI: 10.1021/ci400374z].

Slow pyrolysis polygeneration of bamboo (Phyllostachys pubescens): Product yield prediction and biochar formation mechanism.

PubMed

Wang, Huihui; Wang, Xin; Cui, Yanshan; Xue, Zhongcai; Ba, Yuxin

2018-05-11

Slow pyrolysis of bamboo was conducted at 400-600 °C and pyrolysis products were characterized with FTIR, BET, XRD, SEM, EDS and GC to establish a pyrolysis product yield prediction model and biochar formation mechanism. Pyrolysis biochar yield was predicted based on content of cellulose, hemicellulose and lignin in biomass with their carbonization index of 0.20, 0.35 and 0.45. The formation mechanism of porous structure in pyrolysis biochar was established based on its physicochemical property evolution and emission characteristics of pyrolysis gas. The main components (cellulose, hemicellulose and lignin) had different pyrolysis or chemical reaction pathways to biochar. Lignin had higher aromatic structure, which resulted higher biochar yield. It was the main biochar precursor during biomass pyrolysis. Cellulose was likely to improve porous structure of pyrolysis biochar due to its high mass loss percentage. Higher pyrolysis temperatures (600 °C) promoted inter- and intra-molecular condensation reactions and aromaticity in biochar. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predictive model for ionic liquid extraction solvents for rare earth elements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grabda, Mariusz; Oleszek, Sylwia; Institute of Environmental Engineering of the Polish Academy of Sciences, ul. M. Sklodowskiej-Curie 34, 41-819, Zabrze

2015-12-31

The purpose of our study was to select the most effective ionic liquid extraction solvents for dysprosium (III) fluoride using a theoretical approach. Conductor-like Screening Model for Real Solvents (COSMO-RS), based on quantum chemistry and the statistical thermodynamics of predefined DyF{sub 3}-ionic liquid systems, was applied to reach the target. Chemical potentials of the salt were predicted in 4,400 different ionic liquids. On the base of these predictions set of ionic liquids’ ions, manifesting significant decrease of the chemical potentials, were selected. Considering the calculated physicochemical properties (hydrophobicity, viscosity) of the ionic liquids containing these specific ions, the most effectivemore » extraction solvents for liquid-liquid extraction of DyF{sub 3} were proposed. The obtained results indicate that the COSMO-RS approach can be applied to quickly screen the affinity of any rare earth element for a large number of ionic liquid systems, before extensive experimental tests.« less

A hierarchical clustering methodology for the estimation of toxicity.

PubMed

Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

2008-01-01

ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpy of vaporization.

PubMed

Puri, Swati; Chickos, James S; Welsh, William J

2002-01-01

Three-dimensional Quantitative Structure-Property Relationship (QSPR) models have been derived using Comparative Molecular Field Analysis (CoMFA) to correlate the vaporization enthalpies of a representative set of polychlorinated biphenyls (PCBs) at 298.15 K with their CoMFA-calculated physicochemical properties. Various alignment schemes, such as inertial, as is, and atom fit, were employed in this study. The CoMFA models were also developed using different partial charge formalisms, namely, electrostatic potential (ESP) charges and Gasteiger-Marsili (GM) charges. The most predictive model for vaporization enthalpy (Delta(vap)H(m)(298.15 K)), with atom fit alignment and Gasteiger-Marsili charges, yielded r2 values 0.852 (cross-validated) and 0.996 (conventional). The vaporization enthalpies of PCBs increased with the number of chlorine atoms and were found to be larger for the meta- and para-substituted isomers. This model was used to predict Delta(vap)H(m)(298.15 K) of the entire set of 209 PCB congeners.

Childhood peer reputation as a predictor of competence and symptoms 10 years later.

PubMed

Gest, Scott D; Sesma, Arturo; Masten, Ann S; Tellegen, Auke

2006-08-01

This study examined the differential developmental significance of multiple domains of peer reputation in childhood for current and future competence and symptoms. Participants were 205 children from a normative school cohort who completed assessments in grades 3-6 and then again 10 years later. Through re-analysis of original data from the Revised Class Play (RCP; N=612), new narrow-band subscales were examined as distinct correlates and predictors of competence in age-relevant developmental tasks and psychological well being as indexed by internalizing symptoms. Findings support the differentiation of peer exclusion, withdrawal, and sadness within the broad sensitive-isolated domain of reputation, as well as the distinctive meaning of reputations for Popularity-Leadership and Prosocial Behavior within the broad Sociable-Leader domain. When the Sensitive-Isolated predictors were considered, academic and job competence at the 10-year follow-up were predicted uniquely and negatively by peer exclusion, problems in the social and romantic domains were predicted distinctively by withdrawal from peers, and internalizing symptoms were uniquely predicted by childhood reputation as Sad-Sensitive. When the Sociable-Leader predictors were considered, academic and (for ethnic minority youth) job success was predicted by a Prosocial reputation, social success was forecasted by Popularity-Leadership, and romantic competence was predicted positively by Popularity-Leadership and negatively by Prosocial reputation. Negative academic and job outcomes were also predicted by a childhood reputation as Aggressive-Disruptive. Results are discussed in relation to conceptualizing and measuring peer social competence and its relation to later adaptation.

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Optimisation of Microwave-Assisted Extraction of Pomegranate (Punica granatum L.) Seed Oil and Evaluation 
of Its Physicochemical and Bioactive Properties.

PubMed

Çavdar, Hasene Keskin; Yanık, Derya Koçak; Gök, Uğur; Göğüş, Fahrettin

2017-03-01

Pomegranate seed oil was extracted in a closed-vessel high-pressure microwave system. The characteristics of the obtained oil, such as fatty acid composition, free fatty acidity, total phenolic content, antioxidant activity and colour, were compared to those of the oil obtained by cold solvent extraction. Response surface methodology was applied to optimise extraction conditions: power (176-300 W), time (5-20 min), particle size ( d =0.125-0.800 mm) and solvent to sample ratio (2:1, 6:1 and 10:1, by mass). The predicted highest extraction yield (35.19%) was obtained using microwave power of 220 W, particle size in the range of d =0.125-0.450 mm and solvent-to-sample ratio of 10:1 (by mass) in 5 min extraction time. Microwave-assisted solvent extraction (MASE) resulted in higher extraction yield than that of Soxhlet (34.70% in 8 h) or cold (17.50% in 8 h) extraction. The dominant fatty acid of pomegranate seed oil was punicic acid (86%) irrespective of the extraction method. Oil obtained by MASE had better physicochemical properties, total phenolic content and antioxidant activity than the oil obtained by cold solvent extraction.

Chemistry of berkelium: A review

NASA Astrophysics Data System (ADS)

Hobart, D. E.; Peterson, J. R.

Element 97 was first produced in December 1949, by the bombardment of americium-241 with accelerated alpha particles. This new element was named berkelium (Bk) after Berkeley, California, the city of its discovery. In the 36 years since the discovery of Bk, a substantial amount of knowledge concerning the physicochemical properties of this relatively scarce transplutonium element was acquired. All of the Bk isotopes of mass numbers 240 and 242 through 251 are presently known, but only berkelium-249 is available in sufficient quantities for bulk chemical studies. About 0.7 gram of this isotope was isolated at the HFIR/TRU Complex in Oak Ridge, Tennessee in the last 18 years. Over the same time period, the scale of experimental work using berkelium-249 has increased from the tracer level to bulk studies at the microgram level to solution and solid state investigations with milligram quantities. Extended knowledge of the physicochemical behavior of berkelium is important in its own right, because Bk is the first member of the second half of the actinide series. In addition, such information should enable more accurate extrapolations to the predicted behavior of heavier elements for which experimental studies are severely limited by lack of material and/or by intense radioactivity.

Black Carbon (Biochar) In Water/Soil Environments: Molecular Structure, Sorption, Stability, and Potential Risk.

PubMed

Lian, Fei; Xing, Baoshan

2017-12-05

Black carbon (BC) is ubiquitous in the environments and participates in various biogeochemical processes. Both positive and negative effects of BC (especially biochar) on the ecosystem have been identified, which are mainly derived from its diverse physicochemical properties. Nevertheless, few studies systematically examined the linkage between the evolution of BC molecular structure with the resulted BC properties, environmental functions as well as potential risk, which is critical for understanding the BC environmental behavior and utilization as a multifunctional product. Thus, this review highlights the molecular structure evolution of BC during pyrolysis and the impact of BC physicochemical properties on its sorption behavior, stability, and potential risk in terrestrial and aqueous ecosystems. Given the wide application of BC and its important role in biogeochemical processes, future research should focus on the following: (1) establishing methodology to more precisely predict and design BC properties on the basis of pyrolysis and phase transformation of biomass; (2) developing an assessment system to evaluate the long-term effect of BC on stabilization and bioavailability of contaminants, agrochemicals, and nutrient elements in soils; and (3) elucidating the interaction mechanisms of BC with plant roots, microorganisms, and soil components.

Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach.

PubMed

Armah, Frederick Ato; Paintsil, Arnold; Yawson, David Oscar; Adu, Michael Osei; Odoi, Justice O

2017-08-01

Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F's demonstrating that 'physical properties and chalcophilic elements' was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health.

Groundwater oxygen isotope anomaly before the M6.6 Tottori earthquake in Southwest Japan.

PubMed

Onda, Satoki; Sano, Yuji; Takahata, Naoto; Kagoshima, Takanori; Miyajima, Toshihiro; Shibata, Tomo; Pinti, Daniele L; Lan, Tefang; Kim, Nak Kyu; Kusakabe, Minoru; Nishio, Yoshiro

2018-03-19

Geochemical monitoring of groundwater in seismically-active regions has been carried out since 1970s. Precursors were well documented, but often criticized for anecdotal or fragmentary signals, and for lacking a clear physico-chemical explanation for these anomalies. Here we report - as potential seismic precursor - oxygen isotopic ratio anomalies of +0.24‰ relative to the local background measured in groundwater, a few months before the Tottori earthquake (M 6.6) in Southwest Japan. Samples were deep groundwater located 5 km west of the epicenter, packed in bottles and distributed as drinking water between September 2015 and July 2017, a time frame which covers the pre- and post-event. Small but substantial increase of 0.07‰ was observed soon after the earthquake. Laboratory crushing experiments of aquifer rock aimed to simulating rock deformation under strain and tensile stresses were carried out. Measured helium degassing from the rock and 18 O-shift suggest that the co-seismic oxygen anomalies are directly related to volumetric strain changes. The findings provide a plausible physico-chemical basis to explain geochemical anomalies in water and may be useful in future earthquake prediction research.

Review on occurrence and behavior of PCDD/Fs and dl-PCBs in atmosphere of East Asia

NASA Astrophysics Data System (ADS)

Trinh, Minh Man; Chang, Moo Been

2018-05-01

This paper reviews the data from studies mainly published after 2000 to provide the current understanding of the physicochemical properties, atmospheric occurrence, gas/particle partitioning, fate and temporal trends in atmospheric matrix of PCDD/Fs and dl-PCBs of East Asia. Ambient PCDD/Fs and dl-PCBs concentrations in East Asia are found to be tens to hundreds times higher than that measured in Europe and North America. After strict regulations on PCDD/Fs and dl-PCBs emissions are enacted, the concentrations of these compounds decrease dramatically in Eastern Asian countries. In general, most of PCDD/Fs distribute in particle phase while dl-PCBs majorly exist in gas phase. Three main factors including physicochemical properties of the compounds, properties of particle and atmospheric condition affect the gas/particle partitioning of PCDD/Fs and dl-PCBs. The accuracy of absorption and adsorption models on predicting gas/particle partitioning of PCDD/Fs and dl-PCBs is evaluated. Gas-phase compounds are mostly removed from the atmosphere via reactions with OH radicals while those in particle phase are majorly removed by wet/dry deposition processes. The effects of removing processes and long-range transport on gas/particle partitioning are also discussed.

Modelling the influence of inulin as a fat substitute in comminuted meat products on their physico-chemical characteristics and eating quality using a mixture design approach.

PubMed

Keenan, Derek F; Resconi, Virginia C; Kerry, Joseph P; Hamill, Ruth M

2014-03-01

The effects of fat substitution using two commercial inulin products on the physico-chemical properties and eating quality of a comminuted meat product (breakfast sausage) were modelled using a specialised response surface experiment specially developed for mixtures. 17 treatments were assigned representing a different substitution level for fat with inulin. Sausages were formulated to contain pork shoulder, back fat/inulin, water, rusk and seasoning (44.3, 18.7, 27.5, 7 and 2.5% w/w). Composition, sensory, instrumental texture and colour characteristics were assessed. Fructan analysis showed that inulin was unaffected by heat or processing treatments. Models showed increasing inulin inclusions decreased cook loss (p<0.0017) and improved emulsion stability (p<0.0001) but also resulted in greater textural and eating quality modification of sausages. Hardness values increased (p<0.0001) with increasing inulin concentration, with panellists also scoring products containing inulin as less tender (p<0.0112). Optimisation predicted two acceptable sausage formulations with significantly lower fat levels than the control, which would contain sufficient inulin to deliver a prebiotic health effect. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bio-preservative effect of the essential oil of the endemic Mentha piperita used alone and in combination with BacTN635 in stored minced beef meat.

PubMed

Smaoui, Slim; Hsouna, Anis Ben; Lahmar, Aida; Ennouri, Karim; Mtibaa-Chakchouk, Ahlem; Sellem, Imen; Najah, Soumaya; Bouaziz, Mohamed; Mellouli, Lotfi

2016-07-01

The major compounds in Mentha piperita essential oil (EOMP) were menthol (33.59%) and iso-menthone (33%). The biopreservative effect of EOMP used alone at 0.25 or 0.5% and in combination with the semi-purified bacteriocin BacTN635 at 500 or 1000AU/g, on minced beef meat was evaluated by microbiological, physicochemical and sensory analyses during storage at 4°C for 21days. EOMP used alone limited the microbial deterioration of minced meat (P<0.05). Furthermore, the combination between EOMP and BacTN635 led to a decrease in TBARS values and slowed down the accumulation of MetMb. This combination was more efficient (P<0.05) against microflora proliferation and enhanced the sensory acceptability extending thus the shelf life of meat beef by approximately 7days. On the basis of these results, physicochemical and sensorial parameters could be used for constructing regression models to predict overall acceptability. Overall, the strongest preservative effect was achieved by using the combination of EOMP at 0.5% with BacTN535 at 1000AU/g. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tensile properties of cooked meat sausages and their correlation with texture profile analysis (TPA) parameters and physico-chemical characteristics.

PubMed

Herrero, A M; de la Hoz, L; Ordóñez, J A; Herranz, B; Romero de Ávila, M D; Cambero, M I

2008-11-01

The possibilities of using breaking strength (BS) and energy to fracture (EF) for monitoring textural properties of some cooked meat sausages (chopped, mortadella and galantines) were studied. Texture profile analysis (TPA), folding test and physico-chemical measurements were also performed. Principal component analysis enabled these meat products to be grouped into three textural profiles which showed significant (p<0.05) differences mainly for BS, hardness, adhesiveness and cohesiveness. Multivariate analysis indicated that BS, EF and TPA parameters were correlated (p<0.05) for every individual meat product (chopped, mortadella and galantines) and all products together. On the basis of these results, TPA parameters could be used for constructing regression models to predict BS. The resulting regression model for all cooked meat products was BS=-0.160+6.600∗cohesiveness-1.255∗adhesiveness+0.048∗hardness-506.31∗springiness (R(2)=0.745, p<0.00005). Simple linear regression analysis showed significant coefficients of determination between BS (R(2)=0.586, p<0.0001) versus folding test grade (FG) and EF versus FG (R(2)=0.564, p<0.0001).

Thermodynamic and transport properties of spiro-(1,1')-bipyrrolidinium tetrafluoroborate and acetonitrile mixtures: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Qing-Yin, Zhang; Peng, Xie; Xin, Wang; Xue-Wen, Yu; Zhi-Qiang, Shi; Shi-Huai, Zhao

2016-06-01

Organic salts such as spiro-(1,1')-bipyrrolidinium tetrafluoroborate ([SBP][BF4]) dissolved in liquid acetonitrile (ACN) are a new kind of organic salt solution, which is expected to be used as an electrolyte in electrical double layer capacitors (EDLCs). To explore the physicochemical properties of the solution, an all-atom force field is established on the basis of AMBER parameter values and quantum mechanical calculations. Molecular dynamics (MD) simulations are carried out to explore the liquid structure and physicochemical properties of [SBP][BF4] electrolyte at room temperature. The computed thermodynamic and transport properties match the available experimental results very well. The microscopic structures of [SBP][BF4] salt solution are also discussed in detail. The method used in this work provides an efficient way of predicting the properties of organic salt solvent as an electrolyte in EDLCs. Project supported by the National Natural Science Foundation of China (Grant Nos. 21476172 and 51172160), the National High Technology Research and Development Program of China (Grant No. 2013AA050905), and the Natural Science Foundation of Tianjin, China (Grant Nos. 12JCZDJC28400, 14RCHZGX00859, 14JCTPJC00484, and 14JCQNJC07200).

A Study of Physicochemical Properties of Subcutaneous Fat of the Abdomen and its Implication in Abdominal Obesity.

PubMed

Pandey, Arvind Kumar; Kumar, Pramod; Kodavoor, Srinivas Aithal; Kotian, Sushma Rama; Yathdaka, Sudhakar Narahari; Nayak, Dayanand; Souza, Anne D; Souza, Antony Sylvan D

2016-05-01

The lower abdominal obesity is more resistant to absorption as compared to that of upper abdomen. Differences in the physicochemical properties of the subcutaneous fat of the upper and lower abdomen may be responsible for this variation. There is paucity of the scientific literature on the physicochemical properties of the subcutaneous fat of abdomen. The present study was undertaken to create a database of physicochemical properties of abdominal subcutaneous fat. The samples of subcutaneous fat from upper and lower abdomen were collected from 40 fresh autopsied bodies (males 33, females 7). The samples were prepared for physicochemical analysis using organic and inorganic solvents. Various physicochemical properties of the fat samples analysed were surface tension, viscosity, specific gravity, specific conductivity, iodine value and thermal properties. Data was analysed by paired and independent sample t-tests. There was a statistically significant difference in all the physicochemical parameters between males and females except surface tension (organic) and surface tension (inorganic) of upper abdominal fat, and surface tension (organic) of lower abdominal fat. In males, viscosity of upper abdominal fat was more compared to that of lower abdomen (both organic and inorganic) unlike the specific conductivity that was higher for the lower abdominal fat as compared to that of the upper abdomen. In females there were statistically significant higher values of surface tension (inorganic) and specific gravity (organic) of the upper abdomen fat as compared to that of lower abdomen. The initial and final weight loss of the lower abdominal fat as indicated by Thermo Gravimetric Analysis was significantly more in males than in female. The difference in the physicochemical properties of subcutaneous fat between upper and lower abdomen and between males and females could be responsible for the variant behaviour of subcutaneous abdominal fat towards resorption.

Investigating the biometric and physicochemical characteristics of freshly harvested Pacific white shrimp (Litopenaeus vannamei): a comparative approach.

PubMed

Okpala, Charles Odilichukwu R; Bono, Gioacchino

2016-03-15

The practicality of biometrics of seafood cannot be overemphasized, particularly for competent authorities of the shrimp industry. However, there is a paucity of relevant literature on the relationship between biometric and physicochemical indices of freshly harvested shrimp. This work therefore investigated the relationship between biometric (standard length (SL), total weight (TW) and condition factor (CF)) and physicochemical (moisture content, pH, titratable acidity, water activity, water retention index, colour values and fracturability) characteristics of freshly harvested Pacific white shrimp (Litopenaeus vannamei) obtained from three different farms. The relationships between these parameters were determined using correlation and regression analyses. No significant correlation (P > 0.05) was found between the biometric and physicochemical indices of the sampled L. vannamei specimens. Possibly the lack of post-mortem and physical change(s) at day of harvest together with the absence of temporal variable may have collectively limited the degree of any significant correlation between biometric and physicochemical data points measured in this study. Although the TWs of freshly harvested L. vannamei shrimp resembled (P > 0.05), SL and CF differed significantly (P < 0.05) with minimal explained variance. Moreover, some biometric and physicochemical variables were independently correlated (P < 0.05). Data indicated that no significant correlation existed between biometric and physicochemical characteristics of freshly harvested L. vannamei shrimp. Across the farms studied, however, the biometric data were comparable. To best knowledge, this is the first study to investigate the biometric and physicochemical properties of freshly harvested shrimp using a comparative approach, which is also applicable to other economically important aquaculture species. Overall, this work provides useful information for competent authorities/stakeholders of the fishery industry and serves as a baseline for preservative treatments. © 2015 Society of Chemical Industry.

Design, synthesis, anticancer screening, docking studies and in silico ADME prediction of some β-carboline derivatives.

PubMed

Abdelsalam, Mohamed A; AboulWafa, Omaima M; M Badawey, El-Sayed A; El-Shoukrofy, Mai S; El-Miligy, Mostafa M; Gouda, Noha; Elaasser, Mahmoud M

2018-05-22

Medicinal interest has focused on β-carbolines as anticancer agents. Several β-carbolines were designed, synthesized and evaluated for their cytotoxic activity against MCF-7 and A-549 cancer cell lines using MTT assay. Compounds 13a, 13c, 13d and 20a were the most promising showing high selectivity indices. Compounds 13c and 20a showed potent inhibition of topoisomerase (topo-I) and kinesin spindle protein (KSP/Eg5 ATPase) which was confirmed by their docking results into the active site of both enzymes. In silico physicochemical calculations predicted that compounds 13a, 13d and 20a obeyed Lipinski's rule of five. Compounds 13c and 20a are multitarget anticancer leads that act as potent inhibitors for both topo-I and/or KSP ATPase.

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Clay facial masks: physicochemical stability at different storage temperatures.

PubMed

Zague, Vivian; de Almeida Silva, Diego; Baby, André Rolim; Kaneko, Telma Mary; Velasco, Maria Valéria Robles

2007-01-01

Clay facial masks--formulations that contain a high percentage of solids dispersed in a liquid vehicle--have become of special interest due to specific properties presented by clays, such as particle size, cooling index, high adsorption capacity, and plasticity. Although most of the physicochemical properties of clay dispersions have been studied, specific aspects concerning the physicochemical stability of clay mask products remain unclear. This work aimed at investigating the accelerated physicochemical stability of clay mask formulations stored at different temperatures. Formulations were subjected to centrifuge testing and to thermal treatment for 15 days, during which temperature was varied from -5.0 degrees to 45.0 degrees C. The apparent viscosity and visual aspect (homogeneity) of all formulations were affected by temperature variation, whereas color, odor, and pH value remained unaltered. These results, besides the estimation of physicochemical stability under aging, can be useful in determining the best storage conditions for clay-based formulations.

[Analysis and research on the degradation and migration of organic pollutants in textile wastewater treatment process by GC-MS].

PubMed

Liu, Wei-jing; Zhang, Long; Wu, Wei; Tu, Yong

2010-04-01

In order to analyze the advantages/disadvantages of the combined treatment process between "physicochemical + biochemical" and "biochemical + physicochemical" in treatment of textile wastewater, gas chromatography-mass spectrometry (GC-MS) was used to determine the degradation process of organic pollutants in this two totally different treatment processes. The same analysis was also conducted to the sludge and discharged water. The results showed that the "physicochemical + biochemical" process displayed a poorer effect than "biochemical + physicochemical" in degrading the organic pollutants. The latter was 6.2% higher than the former in removing the organic pollutants averagely. The difference was mainly manifested in the efficiency of anaerobic hydrolysis in the two coupled processes. Moreover, the implement of "physicochemical + biochemical" process resulted in the migration of plenty of typical organic pollutants to sludge from primary coagulation sedimentation process and to the discharged water, which would cause secondary pollution easily.

Bacterial diversity and composition of an alkaline uranium mine tailings-water interface.

PubMed

Khan, Nurul H; Bondici, Viorica F; Medihala, Prabhakara G; Lawrence, John R; Wolfaardt, Gideon M; Warner, Jeff; Korber, Darren R

2013-10-01

The microbial diversity and biogeochemical potential associated with a northern Saskatchewan uranium mine water-tailings interface was examined using culture-dependent and -independent techniques. Morphologically-distinct colonies from uranium mine water-tailings and a reference lake (MC) obtained using selective and non-selective media were selected for 16S rRNA gene sequencing and identification, revealing that culturable organisms from the uranium tailings interface were dominated by Firmicutes and Betaproteobacteria; whereas, MC organisms mainly consisted of Bacteroidetes and Gammaproteobacteria. Ion Torrent (IT) 16S rRNA metagenomic analysis carried out on extracted DNA from tailings and MC interfaces demonstrated the dominance of Firmicutes in both of the systems. Overall, the tailings-water interface environment harbored a distinct bacterial community relative to the MC, reflective of the ambient conditions (i.e., total dissolved solids, pH, salinity, conductivity, heavy metals) dominating the uranium tailings system. Significant correlations among the physicochemical data and the major bacterial groups present in the tailings and MC were also observed. Presence of sulfate reducing bacteria demonstrated by culture-dependent analyses and the dominance of Desulfosporosinus spp. indicated by Ion Torrent analyses within the tailings-water interface suggests the existence of anaerobic microenvironments along with the potential for reductive metabolic processes.

Linking microbial diversity and functionality of arctic glacial surface habitats.

PubMed

Lutz, Stefanie; Anesio, Alexandre M; Edwards, Arwyn; Benning, Liane G

2017-02-01

Distinct microbial habitats on glacial surfaces are dominated by snow and ice algae, which are the critical players and the dominant primary colonisers and net producers during the melt season. Here for the first time we have evaluated the role of these algae in association with the full microbial community composition (i.e., algae, bacteria, archaea) in distinct surface habitats and on 12 glaciers and permanent snow fields in Svalbard and Arctic Sweden. We cross-correlated these data with the analyses of specific metabolites such as fatty acids and pigments, and a full suite of potential critical physico-chemical parameters including major and minor nutrients, and trace metals. It has been shown that correlations between single algal species, metabolites, and specific geochemical parameters can be used to unravel mixed metabolic signals in complex communities, further assign them to single species and infer their functionality. The data also clearly show that the production of metabolites in snow and ice algae is driven mainly by nitrogen and less so by phosphorus limitation. This is especially important for the synthesis of secondary carotenoids, which cause a darkening of glacial surfaces leading to a decrease in surface albedo and eventually higher melting rates. © 2016 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

Escherichia coli's water load affects zebrafish (Danio rerio) behavior.

PubMed

Amorim, João; Fernandes, Miguel; Abreu, Isabel; Tavares, Fernando; Oliva-Teles, Luis

2018-05-01

Traditional physico-chemical sensors are becoming an obsolete tool for environmental quality assessment. Biomonitoring techniques, such as biological early warning systems present the advantage of being sensitivity, fast, non-invasive and ecologically relevant. In this work, we applied a video tracking system, developed with zebrafish (Danio rerio), to detect microbiological contamination in water. Using the fishs' behavior response, the system was able to detect the presence of a non-pathogenic environmental strain of Escherichia coli, at three different levels of contamination: 600, 1800 and 5000 CFU/100 mL (colony forming units/100 mL). Data was collected during 50 min of exposure and analyzed with the artificial neural networks Self-organizing Map and Multi-layer Perceptron. The behavior of exposed fish was more erratic, with pronounced and rapid changes on movement direction and with significant less exploratory activity. The accuracy, sensitivity and specificity values regarding the detection capability (distinction between presence or absence of contamination) ranged from 89 to 100%. Regarding the classification capability (distinction between experimental conditions), the values ranged from 67 to 89%. This research may be a valuable contribution to improve water monitoring and management strategies, by taking as reference the effects on biosensors, without a biased anthropocentric perspective. Copyright © 2018 Elsevier B.V. All rights reserved.

Advances in combination therapy of lung cancer: Rationales, delivery technologies and dosage regimens.

PubMed

Wu, Lan; Leng, Donglei; Cun, Dongmei; Foged, Camilla; Yang, Mingshi

2017-08-28

Lung cancer is a complex disease caused by a multitude of genetic and environmental factors. The progression of lung cancer involves dynamic changes in the genome and a complex network of interactions between cancer cells with multiple, distinct cell types that form tumors. Combination therapy using different pharmaceuticals has been proven highly effective due to the ability to affect multiple cellular pathways involved in the disease progression. However, the currently used drug combination designs are primarily based on empirical clinical studies, and little attention has been given to dosage regimens, i.e. how administration routes, onsets, and durations of the combinations influence the therapeutic outcome. This is partly because combination therapy is challenged by distinct physicochemical properties and in vivo pharmacokinetics/pharmacodynamics of the individual pharmaceuticals, including small molecule drugs and biopharmaceuticals, which make the optimization of dosing and administration schedule challenging. This article reviews the recent advances in the design and development of combinations of pharmaceuticals for the treatment of lung cancer. Focus is primarily on rationales for the selection of specific combination therapies for lung cancer treatment, and state of the art of delivery technologies and dosage regimens for the combinations, tested in preclinical and clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.

The isolated MUC5AC gene product from human ocular mucin displays intramolecular conformational heterogeneity.

PubMed

Round, Andrew N; McMaster, Terence J; Miles, Mervyn J; Corfield, Anthony P; Berry, Monica

2007-06-01

Atomic force microscopy (AFM) has been used to show that human ocular mucins contain at least three distinct polymer conformations, separable by isopycnic density gradient centrifugation. In this work we have used affinity purification against the anti(mucin peptide core) monoclonal antibody 45M1 to isolate MUC5AC gene products, a major component of human ocular mucins. AFM images confirm that the affinity-purified polymers adopt distinct conformations that coidentify with two of those observed in the parent population, and further reveal that these two different conformations can be present within the same polymer. AFM images of the complexes formed after incubation of 45M1 with the parent sample reveal different rates of binding to the two MUC5AC polymer types. The variability of gene products within a mucin population was revealed by analyzing the height distributions along the polymer contour and periodicities in distances between occupied antibody binding sites. AFM analysis of mucin polymers at the single molecule level provides new information about the genetic origins of individual polymers and the contributions of glycosylation to the physicochemical properties of mucins, which can be correlated with information obtained from biochemistry, antibody binding assays, and molecular biology techniques.

Nitrification rates in Arctic soils are associated with functionally distinct populations of ammonia-oxidizing archaea

PubMed Central

Alves, Ricardo J Eloy; Wanek, Wolfgang; Zappe, Anna; Richter, Andreas; Svenning, Mette M; Schleper, Christa; Urich, Tim

2013-01-01

The functioning of Arctic soil ecosystems is crucially important for global climate, and basic knowledge regarding their biogeochemical processes is lacking. Nitrogen (N) is the major limiting nutrient in these environments, and its availability is strongly dependent on nitrification. However, microbial communities driving this process remain largely uncharacterized in Arctic soils, namely those catalyzing the rate-limiting step of ammonia (NH3) oxidation. Eleven Arctic soils were analyzed through a polyphasic approach, integrating determination of gross nitrification rates, qualitative and quantitative marker gene analyses of ammonia-oxidizing archaea (AOA) and bacteria (AOB) and enrichment of AOA in laboratory cultures. AOA were the only NH3 oxidizers detected in five out of 11 soils and outnumbered AOB in four of the remaining six soils. The AOA identified showed great phylogenetic diversity and a multifactorial association with the soil properties, reflecting an overall distribution associated with tundra type and with several physico-chemical parameters combined. Remarkably, the different gross nitrification rates between soils were associated with five distinct AOA clades, representing the great majority of known AOA diversity in soils, which suggests differences in their nitrifying potential. This was supported by selective enrichment of two of these clades in cultures with different NH3 oxidation rates. In addition, the enrichments provided the first direct evidence for NH3 oxidation by an AOA from an uncharacterized Thaumarchaeota–AOA lineage. Our results indicate that AOA are functionally heterogeneous and that the selection of distinct AOA populations by the environment can be a determinant for nitrification activity and N availability in soils. PMID:23466705

The lack of foundation in the mechanism on which are based the physico-chemical theories for the origin of the genetic code is counterposed to the credible and natural mechanism suggested by the coevolution theory.

PubMed

Di Giulio, Massimo

2016-06-21

I analyze the mechanism on which are based the majority of theories that put to the center of the origin of the genetic code the physico-chemical properties of amino acids. As this mechanism is based on excessive mutational steps, I conclude that it could not have been operative or if operative it would not have allowed a full realization of predictions of these theories, because this mechanism contained, evidently, a high indeterminacy. I make that disapproving the four-column theory of the origin of the genetic code (Higgs, 2009) and reply to the criticism that was directed towards the coevolution theory of the origin of the genetic code. In this context, I suggest a new hypothesis that clarifies the mechanism by which the domains of codons of the precursor amino acids would have evolved, as predicted by the coevolution theory. This mechanism would have used particular elongation factors that would have constrained the evolution of all amino acids belonging to a given biosynthetic family to the progenitor pre-tRNA, that for first recognized, the first codons that evolved in a certain codon domain of a determined precursor amino acid. This happened because the elongation factors recognized two characteristics of the progenitor pre-tRNAs of precursor amino acids, which prevented the elongation factors from recognizing the pre-tRNAs belonging to biosynthetic families of different precursor amino acids. Finally, I analyze by means of Fisher's exact test, the distribution, within the genetic code, of the biosynthetic classes of amino acids and the ones of polarity values of amino acids. This analysis would seem to support the biosynthetic classes of amino acids over the ones of polarity values, as the main factor that led to the structuring of the genetic code, with the physico-chemical properties of amino acids playing only a subsidiary role in this evolution. As a whole, the full analysis brings to the conclusion that the coevolution theory of the origin of the genetic code would be a theory highly corroborated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adhesion Potential of Intestinal Microbes Predicted by Physico-Chemical Characterization Methods

PubMed Central

Niederberger, Tobias; Fischer, Peter; Rühs, Patrick Alberto

2015-01-01

Bacterial adhesion to epithelial surfaces affects retention time in the human gastro-intestinal tract and therefore significantly contributes to interactions between bacteria and their hosts. Bacterial adhesion among other factors is strongly influenced by physico-chemical factors. The accurate quantification of these physico-chemical factors in adhesion is however limited by the available measuring techniques. We evaluated surface charge, interfacial rheology and tensiometry (interfacial tension) as novel approaches to quantify these interactions and evaluated their biological significance via an adhesion assay using intestinal epithelial surface molecules (IESM) for a set of model organisms present in the human gastrointestinal tract. Strain pairs of Lactobacillus plantarum WCFS1 with its sortase knockout mutant Lb. plantarum NZ7114 and Lb. rhamnosus GG with Lb. rhamnosus DSM 20021T were used with Enterococcus faecalis JH2-2 as control organism. Intra-species comparison revealed significantly higher abilities for Lb. plantarum WCSF1 and Lb. rhamnosus GG vs. Lb. plantarum NZ7114 and Lb. rhamnosus DSM 20021T to dynamically increase interfacial elasticity (10−2 vs. 10−3 Pa*m) and reduce interfacial tension (32 vs. 38 mN/m). This further correlated for Lb. plantarum WCSF1 and Lb. rhamnosus GG vs. Lb. plantarum NZ7114 and Lb. rhamnosus DSM 20021T with the decrease of relative hydrophobicity (80–85% vs. 57–63%), Zeta potential (-2.9 to -4.5 mV vs. -8.0 to -13.8 mV) and higher relative adhesion capacity to IESM (3.0–5.0 vs 1.5–2.2). Highest adhesion to the IESM collagen I and fibronectin was found for Lb. plantarum WCFS1 (5.0) and E. faecalis JH2-2 (4.2) whereas Lb. rhamnosus GG showed highest adhesion to type II mucus (3.8). Significantly reduced adhesion (2 fold) to the tested IESM was observed for Lb. plantarum NZ7114 and Lb. rhamnosus DSM 20021T corresponding with lower relative hydrophobicity, Zeta potential and abilities to modify interfacial elasticity and tension. Conclusively, the use of Zeta potential, interfacial elasticity and interfacial tension are proposed as suitable novel descriptive and predictive parameters to study the interactions of intestinal microbes with their hosts. PMID:26295945

Are abrupt climate changes predictable?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2013-04-01

It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope record is presented. The result of the analysis points to a fundamental limitation in predictability of the third kind. Reference: P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, 2010

Nanoparticles for Imaging, Sensing, and Therapeutic Intervention

PubMed Central

2014-01-01

Nanoparticles have the potential to contribute to new modalities in molecular imaging and sensing as well as in therapeutic interventions. In this Nano Focus article, we identify some of the current challenges and knowledge gaps that need to be confronted to accelerate the developments of various applications. Using specific examples, we journey from the characterization of these complex hybrid nanomaterials; continue with surface design and (bio)physicochemical properties, their fate in biological media and cells, and their potential for cancer treatment; and finally reflect on the role of animal models to predict their behavior in humans. PMID:24641589

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jordan, Amy B.; Boukhalfa, Hakim; Caporuscio, Florie Andre

To gain confidence in the predictive capability of numerical models, experimental validation must be performed to ensure that parameters and processes are correctly simulated. The laboratory investigations presented herein aim to address knowledge gaps for heat-generating nuclear waste (HGNW) disposal in bedded salt that remain after examination of prior field and laboratory test data. Primarily, we are interested in better constraining the thermal, hydrological, and physicochemical behavior of brine, water vapor, and salt when moist salt is heated. The target of this work is to use run-of-mine (RoM) salt; however during FY2015 progress was made using high-purity, granular sodium chloride.

A generalized graph-theoretical matrix of heterosystems and its application to the VMV procedure.

PubMed

Mozrzymas, Anna

2011-12-14

The extensions of generalized (molecular) graph-theoretical matrix and vector-matrix-vector procedure are considered. The elements of the generalized matrix are redefined in order to describe molecules containing heteroatoms and multiple bonds. The adjacency, distance, detour and reciprocal distance matrices of heterosystems, and corresponding vectors are derived from newly defined generalized graph matrix. The topological indices, which are most widely used in predicting physicochemical and biological properties/activities of various compounds, can be calculated from the new generalized vector-matrix-vector invariant. Copyright © 2011 Elsevier Ltd. All rights reserved.

Predicting Error Bars for QSAR Models

NASA Astrophysics Data System (ADS)

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches.

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

PubMed

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Predictive Management of Asian Carps in the Upper Mississippi River System

USGS Publications Warehouse

Vondracek, Bruce C.; Carlson, Andrew K.

2014-01-01

Prolific non-native organisms pose serious threats to ecosystems and economies worldwide. Nonnative bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix), collectively referred to as Asian carps, continue to colonize aquatic ecosystems throughout the central United States. These species are r-selected, exhibiting iteroparous spawning, rapid growth, broad environmental tolerance, high density, and long-distance movement. Hydrological, thermal, and physicochemical conditions are favorable for establishment beyond the current range, rendering containment and control imperative. Ecological approaches to confine Asian carp populations and prevent colonization characterize contemporary management in the United States. Foraging and reproduction of Asian carps govern habitat selection and movement, providing valuable insight for predictive control. Current management approaches are progressive and often anticipatory but deficient in human dimensions. We define predictive management of Asian carps as synthesis of ecology and human dimensions at regional and local scales to develop strategies for containment and control. We illustrate predictive management in the Upper Mississippi River System and suggest resource managers integrate predictive models, containment paradigms, and human dimensions to design effective, socially acceptable management strategies. Through continued research, university-agency collaboration, and public engagement, predictive management of Asian carps is an auspicious paradigm for preventing and alleviating consequences of colonization in the United States.

Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex.

PubMed

Nee, Derek Evan; Kastner, Sabine; Brown, Joshua W

2011-01-01

The last decade has seen considerable discussion regarding a theoretical account of medial prefrontal cortex (mPFC) function with particular focus on the anterior cingulate cortex. The proposed theories have included conflict detection, error likelihood prediction, volatility monitoring, and several distinct theories of error detection. Arguments for and against particular theories often treat mPFC as functionally homogeneous, or at least nearly so, despite some evidence for distinct functional subregions. Here we used functional magnetic resonance imaging (fMRI) to simultaneously contrast multiple effects of error, conflict, and task-switching that have been individually construed in support of various theories. We found overlapping yet functionally distinct subregions of mPFC, with activations related to dominant error, conflict, and task-switching effects successively found along a rostral-ventral to caudal-dorsal gradient within medial prefrontal cortex. Activations in the rostral cingulate zone (RCZ) were strongly correlated with the unexpectedness of outcomes suggesting a role in outcome prediction and preparing control systems to deal with anticipated outcomes. The results as a whole support a resolution of some ongoing debates in that distinct theories may each pertain to corresponding distinct yet overlapping subregions of mPFC. Copyright © 2010 Elsevier Inc. All rights reserved.

Super Memory Bros.: going from mirror patterns to concordant patterns via similarity enhancements.

PubMed

Ozubko, Jason D; Joordens, Steve

2008-12-01

When memory is contrasted for stimuli belonging to distinct stimulus classes, one of two patterns is observed: a mirror pattern, in which one stimulus gives rise to higher hits but lower false alarms (e.g., the frequency-based mirror effect) or a concordant pattern, in which one stimulus class gives rise both to higher hits and to higher false alarms (e.g., the pseudoword effect). On the basis of the dual-process account proposed by Joordens and Hockley (2000), we predict that mirror patterns occur when one stimulus class is more familiar and less distinctive than another, whereas concordant patterns occur when one stimulus class is more familiar than another. We tested these assumptions within a video game paradigm using novel stimuli that allow manipulations in terms of distinctiveness and familiarity (via similarity). When more distinctive, less familiar items are contrasted with less distinctive, more familiar items, a mirror pattern is observed. Systematically enhancing the familiarity of stimuli transforms the mirror pattern to a concordant pattern as predicted. Although our stimuli differ considerably from those used in examinations of the frequency-based mirror effect and the pseudoword effect, the implications of our findings with respect to those phenomena are also discussed.

Seasonal variations of Saanen goat milk composition and the impact of climatic conditions.

PubMed

Kljajevic, Nemanja V; Tomasevic, Igor B; Miloradovic, Zorana N; Nedeljkovic, Aleksandar; Miocinovic, Jelena B; Jovanovic, Snezana T

2018-01-01

The aim of this research was to investigate the effect of climatic conditions and their impact on seasonal variations of physico-chemical characteristics of Saanen goat milk produced over a period of 4 years. Lactation period (early, mid and late) and year were considered as factors that influence physico-chemical composition of milk. Pearson's coefficient of correlation was calculated between the physico-chemical characteristics of milk (fat, proteins, lactose, non-fat dry matter, density, freezing point, pH, titrable acidity) and climatic condition parameters (air temperature, temperature humidity index-THI, solar radiation duration, relative humidity). Results showed that all physico-chemical characteristics of Saanen goat milk varied significantly throughout the lactation period and years. The decrease of fat, protein, non-fat dry matter and lactose content in goat milk during the mid-lactation period was more pronounced than was previously reported in the literature. The highest values for these characteristics were recorded in the late lactation period. Observed variations were explained by negative correlation between THI and the physico-chemical characteristics of Saanen goat milk. This indicated that Saanen goats were very prone to heat stress, which implied the decrease of physico-chemical characteristics during hot summers.

Health effects of residential wood smoke particles: the importance of combustion conditions and physicochemical particle properties

PubMed Central

Kocbach Bølling, Anette; Pagels, Joakim; Yttri, Karl Espen; Barregard, Lars; Sallsten, Gerd; Schwarze, Per E; Boman, Christoffer

2009-01-01

Background Residential wood combustion is now recognized as a major particle source in many developed countries, and the number of studies investigating the negative health effects associated with wood smoke exposure is currently increasing. The combustion appliances in use today provide highly variable combustion conditions resulting in large variations in the physicochemical characteristics of the emitted particles. These differences in physicochemical properties are likely to influence the biological effects induced by the wood smoke particles. Outline The focus of this review is to discuss the present knowledge on physicochemical properties of wood smoke particles from different combustion conditions in relation to wood smoke-induced health effects. In addition, the human wood smoke exposure in developed countries is explored in order to identify the particle characteristics that are relevant for experimental studies of wood smoke-induced health effects. Finally, recent experimental studies regarding wood smoke exposure are discussed with respect to the applied combustion conditions and particle properties. Conclusion Overall, the reviewed literature regarding the physicochemical properties of wood smoke particles provides a relatively clear picture of how these properties vary with the combustion conditions, whereas particle emissions from specific classes of combustion appliances are less well characterised. The major gaps in knowledge concern; (i) characterisation of the atmospheric transformations of wood smoke particles, (ii) characterisation of the physicochemical properties of wood smoke particles in ambient and indoor environments, and (iii) identification of the physicochemical properties that influence the biological effects of wood smoke particles. PMID:19891791

Regret as Autobiographical Memory

ERIC Educational Resources Information Center

Davison, Ian M.; Feeney, Aidan

2008-01-01

We apply an autobiographical memory framework to the study of regret. Focusing on the distinction between regrets for specific and general events we argue that the temporal profile of regret, usually explained in terms of the action-inaction distinction, is predicted by models of autobiographical memory. In two studies involving participants in…

Distinctiveness of Adolescent and Emerging Adult Romantic Relationship Features in Predicting Externalizing Behavior Problems

ERIC Educational Resources Information Center

van Dulmen, Manfred H. M.; Goncy, Elizabeth A.; Haydon, Katherine C.; Collins, W. Andrew

2008-01-01

Romantic relationship involvement has repeatedly been associated with the incidence of externalizing behavior problems, but little is known about the nature and developmental significance of this relation. The current study extends previous research by investigating whether and through what processes romantic relationships distinctively predict…

Pregnancy-Related Anxiety: Evidence of Distinct Clinical Significance from a Prospective Longitudinal Study

PubMed Central

Blackmore, Emma Robertson; Gustafsson, Hanna; Gilchrist, Michelle; Wyman, Claire; O’Connor, Thomas G

2016-01-01

Background Pregnancy-related anxiety (PrA) has attracted considerable research attention, but questions remain about its distinctiveness from conventional constructs and measures. In a high psychosocial risk, ethnically diverse sample, we examine the degree to which PrA is distinct from continuous and diagnostic measures of anxiety and worry in terms of longitudinal course, associations with psychosocial and perinatal risk, and prediction of postnatal mood disturbance. Methods 345 women oversampled for prenatal anxiety and depression were selected from an urban obstetrics clinic serving a predominantly low-income, ethnically diverse population. PrA was assessed at 20 and 32 weeks gestation; anxiety and depression symptoms were assessed from questionnaire and from clinical interview at 20 and 32 weeks gestation and again at 2 and 6 months postnatally. Data relevant to psychosocial and obstetric risks were ascertained from interview, medical exam, and chart review. Results Two distinct factors of PrA were identified, indexing specific concerns about the child’s health and about the birth; these two PrA factors showed distinct longitudinal patterns in the prenatal period, and modest associations with general measures of anxiety and depression from questionnaire and clinical interview. PrA was also distinguished from conventional symptom measures in its associated features and prediction of birth weight and postnatal mood. Limitations The sample was at high psychosocial risk and ethnically diverse; findings may not generalize to other samples. Conclusions PrA can be distinguished from general measures of anxiety in pregnancy in terms of longitudinal course, associated features, and prediction to postnatal mood disturbance, and may warrant specific clinical attention. PMID:26999549

Multivariate neural biomarkers of emotional states are categorically distinct.

PubMed

Kragel, Philip A; LaBar, Kevin S

2015-11-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Quantifying tolerance indicator values for common stream fish species of the United States

USGS Publications Warehouse

Meador, M.R.; Carlisle, D.M.

2007-01-01

The classification of fish species tolerance to environmental disturbance is often used as a means to assess ecosystem conditions. Its use, however, may be problematic because the approach to tolerance classification is based on subjective judgment. We analyzed fish and physicochemical data from 773 stream sites collected as part of the U.S. Geological Survey's National Water-Quality Assessment Program to calculate tolerance indicator values for 10 physicochemical variables using weighted averaging. Tolerance indicator values (TIVs) for ammonia, chloride, dissolved oxygen, nitrite plus nitrate, pH, phosphorus, specific conductance, sulfate, suspended sediment, and water temperature were calculated for 105 common fish species of the United States. Tolerance indicator values for specific conductance and sulfate were correlated (rho = 0.87), and thus, fish species may be co-tolerant to these water-quality variables. We integrated TIVs for each species into an overall tolerance classification for comparisons with judgment-based tolerance classifications. Principal components analysis indicated that the distinction between tolerant and intolerant classifications was determined largely by tolerance to suspended sediment, specific conductance, chloride, and total phosphorus. Factors such as water temperature, dissolved oxygen, and pH may not be as important in distinguishing between tolerant and intolerant classifications, but may help to segregate species classified as moderate. Empirically derived tolerance classifications were 58.8% in agreement with judgment-derived tolerance classifications. Canonical discriminant analysis revealed that few TIVs, primarily chloride, could discriminate among judgment-derived tolerance classifications of tolerant, moderate, and intolerant. To our knowledge, this is the first empirically based understanding of fish species tolerance for stream fishes in the United States.

Deterministic influences exceed dispersal effects on hydrologically-connected microbiomes: Deterministic assembly of hyporheic microbiomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Emily B.; Crump, Alex R.; Resch, Charles T.

2017-03-28

Subsurface zones of groundwater and surface water mixing (hyporheic zones) are regions of enhanced rates of biogeochemical cycling, yet ecological processes governing hyporheic microbiome composition and function through space and time remain unknown. We sampled attached and planktonic microbiomes in the Columbia River hyporheic zone across seasonal hydrologic change, and employed statistical null models to infer mechanisms generating temporal changes in microbiomes within three hydrologically-connected, physicochemically-distinct geographic zones (inland, nearshore, river). We reveal that microbiomes remain dissimilar through time across all zones and habitat types (attached vs. planktonic) and that deterministic assembly processes regulate microbiome composition in all data subsets.more » The consistent presence of heterotrophic taxa and members of the Planctomycetes-Verrucomicrobia-Chlamydiae (PVC) superphylum nonetheless suggests common selective pressures for physiologies represented in these groups. Further, co-occurrence networks were used to provide insight into taxa most affected by deterministic assembly processes. We identified network clusters to represent groups of organisms that correlated with seasonal and physicochemical change. Extended network analyses identified keystone taxa within each cluster that we propose are central in microbiome composition and function. Finally, the abundance of one network cluster of nearshore organisms exhibited a seasonal shift from heterotrophic to autotrophic metabolisms and correlated with microbial metabolism, possibly indicating an ecological role for these organisms as foundational species in driving biogeochemical reactions within the hyporheic zone. Taken together, our research demonstrates a predominant role for deterministic assembly across highly-connected environments and provides insight into niche dynamics associated with seasonal changes in hyporheic microbiome composition and metabolism.« less

The Inter-Valley Soil Comparative Survey: the ecology of Dry Valley edaphic microbial communities

PubMed Central

Lee, Charles K; Barbier, Béatrice A; Bottos, Eric M; McDonald, Ian R; Cary, Stephen Craig

2012-01-01

Recent applications of molecular genetics to edaphic microbial communities of the McMurdo Dry Valleys and elsewhere have rejected a long-held belief that Antarctic soils contain extremely limited microbial diversity. The Inter-Valley Soil Comparative Survey aims to elucidate the factors shaping these unique microbial communities and their biogeography by integrating molecular genetic approaches with biogeochemical analyses. Although the microbial communities of Dry Valley soils may be complex, there is little doubt that the ecosystem's food web is relatively simple, and evidence suggests that physicochemical conditions may have the dominant role in shaping microbial communities. To examine this hypothesis, bacterial communities from representative soil samples collected in four geographically disparate Dry Valleys were analyzed using molecular genetic tools, including pyrosequencing of 16S rRNA gene PCR amplicons. Results show that the four communities are structurally and phylogenetically distinct, and possess significantly different levels of diversity. Strikingly, only 2 of 214 phylotypes were found in all four valleys, challenging a widespread assumption that the microbiota of the Dry Valleys is composed of a few cosmopolitan species. Analysis of soil geochemical properties indicated that salt content, alongside altitude and Cu2+, was significantly correlated with differences in microbial communities. Our results indicate that the microbial ecology of Dry Valley soils is highly localized and that physicochemical factors potentially have major roles in shaping the microbiology of ice-free areas of Antarctica. These findings hint at links between Dry Valley glacial geomorphology and microbial ecology, and raise previously unrecognized issues related to environmental management of this unique ecosystem. PMID:22170424

Solid state, thermal synthesis of site-specific protein-boron cluster conjugates and their physicochemical and biochemical properties.

PubMed

Goszczyński, Tomasz M; Kowalski, Konrad; Leśnikowski, Zbigniew J; Boratyński, Janusz

2015-02-01

Boron clusters represent a vast family of boron-rich compounds with extraordinary properties that provide the opportunity of exploitation in different areas of chemistry and biology. In addition, boron clusters are clinically used in boron neutron capture therapy (BNCT) of tumors. In this paper, a novel, in solid state (solvent free), thermal method for protein modification with boron clusters has been proposed. The method is based on a cyclic ether ring opening in oxonium adduct of cyclic ether and a boron cluster with nucleophilic centers of the protein. Lysozyme was used as the model protein, and the physicochemical and biological properties of the obtained conjugates were characterized. The main residues of modification were identified as arginine-128 and threonine-51. No significant changes in the secondary or tertiary structures of the protein after tethering of the boron cluster were found using mass spectrometry and circular dichroism measurements. However, some changes in the intermolecular interactions and hydrodynamic and catalytic properties were observed. To the best of our knowledge, we have described the first example of an application of cyclic ether ring opening in the oxonium adducts of a boron cluster for protein modification. In addition, a distinctive feature of the proposed approach is performing the reaction in solid state and at elevated temperature. The proposed methodology provides a new route to protein modification with boron clusters and extends the range of innovative molecules available for biological and medical testing. Copyright © 2014 Elsevier B.V. All rights reserved.

Diversity of culturable filamentous Ascomycetes in the eastern South Pacific Ocean off Chile.

PubMed

Vera, Jeanett; Gutiérrez, Marcelo H; Palfner, Götz; Pantoja, Silvio

2017-08-01

Our study reports the diversity of culturable mycoplankton in the eastern South Pacific Ocean off Chile to contribute with novel knowledge on taxonomy of filamentous fungi isolated from distinct physicochemical and biological marine environments. We characterized spatial distribution of isolates, evaluated their viability and assessed the influence of organic substrate availability on fungal development. Thirty-nine Operational Taxonomic Units were identified from 99 fungal strains isolated from coastal and oceanic waters by using Automatic Barcode Gap Discovery. All Operational Taxonomic Units belonged to phylum Ascomycota and orders Eurotiales, Dothideales, Sordariales and Hypocreales, mainly Penicillium sp. (82%); 11 sequences did not match existing species in GenBank, suggesting occurrence of novel fungal taxa. Our results suggest that fungal communities in the South Pacific Ocean off Chile appear to thrive in a wide range of environmental conditions in the ocean and that substrate availability may be a factor influencing fungal viability in the ocean.

The effect of polymorphism on powder compaction and dissolution properties of chemically equivalent oxytetracycline hydrochloride powders.

PubMed

Liebenberg, W; de Villiers, M M; Wurster, D E; Swanepoel, E; Dekker, T G; Lötter, A P

1999-09-01

In South Africa, oxytetracycline is identified as an essential drug; many generic products are on the market, and many more are being developed. In this study, six oxytetracycline hydrochloride powders were obtained randomly from manufacturers, and suppliers were compared. It was found that compliance to a pharmacopoeial monograph was insufficient to ensure the optimum dissolution performance of a simple tablet formulation. Comparative physicochemical raw material analysis showed no major differences with regard to differential scanning calorimetry (DSC), infrared (IR) spectroscopy, powder dissolution, and particle size. However, the samples could be divided into two distinct types with respect to X-ray powder diffraction (XRD) and thus polymorphism. The two polymorphic forms had different dissolution properties in water or 0.1 N hydrochloride acid. This difference became substantial when the dissolution from tablets was compared. The powders containing form A were less soluble than that containing form B.

Pectin-modifying enzymes and pectin-derived materials: applications and impacts.

PubMed

Bonnin, Estelle; Garnier, Catherine; Ralet, Marie-Christine

2014-01-01

Pectins are complex branched polysaccharides present in primary cell walls. As a distinctive feature, they contain high amount of partly methyl-esterified galacturonic acid and low amount of rhamnose and carry arabinose and galactose as major neutral sugars. Due to their structural complexity, they are modifiable by many different enzymes, including hydrolases, lyases, and esterases. Their peculiar structure is the origin of their physicochemical properties. Among others, their remarkable gelling properties make them a key additive for food industries. Pectin-degrading enzymes and -modifying enzymes may be used in a wide variety of applications to modulate pectin properties or produce pectin derivatives and oligosaccharides with functional as well as nutritional interests. This paper reviews the scientific information available on pectin structure, pectin-modifying enzymes, and the use of enzymes to produce pectin with controlled structure or pectin-derived oligosaccharides, with functional or nutritional interesting properties.

Understanding Structure and Bonding of Multilayered Metal–Organic Nanostructures

PubMed Central

2013-01-01

For organic and hybrid electronic devices, the physicochemical properties of the contained interfaces play a dominant role. To disentangle the various interactions occurring at such heterointerfaces, we here model a complex, yet prototypical, three-component system consisting of a Cu–phthalocyanine (CuPc) film on a 3,4,9,10-perylene-tetracarboxylic-dianhydride (PTCDA) monolayer adsorbed on Ag(111). The two encountered interfaces are similar, as in both cases there would be no bonding without van der Waals interactions. Still, they are also distinctly different, as only at the Ag(111)–PTCDA interface do massive charge-rearrangements occur. Using recently developed theoretical tools, we show that it has become possible to provide atomistic insight into the physical and chemical processes in this comparatively complex nanostructure distinguishing between interactions involving local rearrangements of the charge density and long-range van der Waals attraction. PMID:23447750

Porphyrins at interfaces

NASA Astrophysics Data System (ADS)

Auwärter, Willi; Écija, David; Klappenberger, Florian; Barth, Johannes V.

2015-02-01

Porphyrins and other tetrapyrrole macrocycles possess an impressive variety of functional properties that have been exploited in natural and artificial systems. Different metal centres incorporated within the tetradentate ligand are key for achieving and regulating vital processes, including reversible axial ligation of adducts, electron transfer, light-harvesting and catalytic transformations. Tailored substituents optimize their performance, dictating their arrangement in specific environments and mediating the assembly of molecular nanoarchitectures. Here we review the current understanding of these species at well-defined interfaces, disclosing exquisite insights into their structural and chemical properties, and also discussing methods by which to manipulate their intramolecular and organizational features. The distinct characteristics arising from the interfacial confinement offer intriguing prospects for molecular science and advanced materials. We assess the role of surface interactions with respect to electronic and physicochemical characteristics, and describe in situ metallation pathways, molecular magnetism, rotation and switching. The engineering of nanostructures, organized layers, interfacial hybrid and bio-inspired systems is also addressed.

Nanosize effect: Enhanced compensation temperature and existence of magnetodielectric coupling in SmFe O3

NASA Astrophysics Data System (ADS)

Chaturvedi, Smita; Shyam, Priyank; Bag, Rabindranath; Shirolkar, Mandar M.; Kumar, Jitender; Kaur, Harleen; Singh, Surjeet; Awasthi, A. M.; Kulkarni, Sulabha

2017-07-01

In transition metal oxides, quantum confinement arising from a large surface to volume ratio often gives rise to novel physicochemical properties at nanoscale. Their size-dependent properties have potential applications in diverse areas, including therapeutics, imaging, electronic devices, communication systems, sensors, and catalysis. We have analyzed the structural, magnetic, dielectric, and thermal properties of weakly ferromagnetic SmFe O3 nanoparticles of sizes of about 55 and 500 nm. The nanometer-size particles exhibit several distinct features that are neither observed in their larger-size variants nor reported previously for the single crystals. In particular, for the 55-nm particle, we observe a sixfold enhancement of compensation temperature, an unusual rise in susceptibility in the temperature range 550 to 630 K due to spin pinning, and a coupled antiferromagnetic-ferroelectric transition, directly observed in the dielectric constant.

The Structure–Function Relationships of Classical Cannabinoids: CB1/CB2 Modulation

PubMed Central

Bow, Eric W.; Rimoldi, John M.

2016-01-01

The cannabinoids are members of a deceptively simple class of terpenophenolic secondary metabolites isolated from Cannabis sativa highlighted by (−)-Δ9-tetrahydrocannabinol (THC), eliciting distinct pharmacological effects mediated largely by cannabinoid receptor (CB1 or CB2) signaling. Since the initial discovery of THC and related cannabinoids, synthetic and semisynthetic classical cannabinoid analogs have been evaluated to help define receptor binding modes and structure–CB1/CB2 functional activity relationships. This perspective will examine the classical cannabinoids, with particular emphasis on the structure–activity relationship of five regions: C3 side chain, phenolic hydroxyl, aromatic A-ring, pyran B-ring, and cyclohexenyl C-ring. Cumulative structure–activity relationship studies to date have helped define the critical structural elements required for potency and selectivity toward CB1 and CB2 and, more importantly, ushered the discovery and development of contemporary nonclassical cannabinoid modulators with enhanced physicochemical and pharmacological profiles. PMID:27398024

Clay minerals in primitive meteorites and interplanetary dust 1

NASA Technical Reports Server (NTRS)

Zolensky, M. E.; Keller, L. P.

1991-01-01

Many meteorites and interplanetary dust particles (IDPs) with primitive compositions contain significant amounts of phyllosilicate minerals, which are generally interpreted as evidence of protoplanetary aqueous alteration at an early period of the solar system. These meteorites are chondrites (near solar composition) of the carbonaceous and ordinary varieties. The former are subdivided (according to bulk composition and petrology) into CI, CM, CV, CO, CR, and ungrouped classes. IDPs are extraterrestrial particulates, collected in stratosphere, which have chemical compositions indicative of a primitive origin; they are typically distinct from the primitive meteorites. Characterization of phyllosilicates in these materials is a high priority because of the important physico-chemical information they hold. The most common phyllosilicates present in chondritic extraterrestrial materials are serpentine-group minerals, smectites, and micas. We discuss these phyllosilicates and describe the interpretation of their occurrence in meteorites and IDPs and what this indicates about history of their parent bodies, which are probably the hydrous asteroids.

Creating fair lineups for suspects with distinctive features.

PubMed

Zarkadi, Theodora; Wade, Kimberley A; Stewart, Neil

2009-12-01

In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineups--without increasing the incorrect identification of foils in target-absent lineups--than did concealment. This pattern, and only this pattern, is predicted by the hybrid-similarity model of recognition.

Mesoscopic modeling of multi-physicochemical transport phenomena in porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Qinjin; Wang, Moran; Mukherjee, Partha P

2009-01-01

We present our recent progress on mesoscopic modeling of multi-physicochemical transport phenomena in porous media based on the lattice Boltzmann method. Simulation examples include injection of CO{sub 2} saturated brine into a limestone rock, two-phase behavior and flooding phenomena in polymer electrolyte fuel cells, and electroosmosis in homogeneously charged porous media. It is shown that the lattice Boltzmann method can account for multiple, coupled physicochemical processes in these systems and can shed some light on the underlying physics occuning at the fundamental scale. Therefore, it can be a potential powerful numerical tool to analyze multi-physicochemical processes in various energy, earth,more » and environmental systems.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pawlowski, L.; Lacy, W.J.; Dlugosz, J.J.

This book contains the Proceedings from an International Conference on Chemistry for the Protection of the Environment held in Lublin, Poland, September 4-7, 1989. It opens with a tribute to Andre Van Haute who was a member of the Committee on the title subject and who died in 1989. This is followed by a preface by the editors and 70 chapters, which are grouped under the following headings: General Problems; Monitoring Methods for Surface and Ground water and Analysis of Pollutants; Pathways of Chemicals in the Environment; Physicochemical Treatment: Ion Exchange; Physicochemical Treatment: Coagulation, Flocculation and Sorption; Physicochemical Treatment: Oxidation-Reductionmore » Processes; Physicochemical Treatment; Membrane Processes; and Miscellaneous Methods for Removal of Pollutants. There is a brief subject index.« less

Particle Size, Surface Area, and Amorphous Content as Predictors of Solubility and Bioavailability for Five Commercial Sources of Ferric Orthophosphate in Ready-To-Eat Cereal.

PubMed

Dickmann, Robin S; Strasburg, Gale M; Romsos, Dale R; Wilson, Lori A; Lai, Grace H; Huang, Hsimin

2016-03-01

Ferric orthophosphate (FePO₄) has had limited use as an iron fortificant in ready-to-eat (RTE) cereal because of its variable bioavailability, the mechanism of which is poorly understood. Even though FePO₄ has desirable sensory properties as compared to other affordable iron fortificants, few published studies have well-characterized its physicochemical properties. Semi-crystalline materials such as FePO₄ have varying degrees of molecular disorder, referred to as amorphous content, which is hypothesized to be an important factor in bioavailability. The objective of this study was to systematically measure the physicochemical factors of particle size, surface area, amorphous content, and solubility underlying the variation in FePO₄ bioavailability. Five commercial FePO₄ sources and ferrous sulfate were added to individual batches of RTE cereal. The relative bioavailability value (RBV) of each iron source, determined using the AOAC Rat Hemoglobin Repletion Bioassay, ranged from 51% to 99% (p < 0.05), which is higher than typically reported. Solubility in dilute HCl accurately predicted RBV (R² = 0.93, p = 0.008). Amorphous content measured by Dynamic Vapor Sorption ranged from 1.7% to 23.8% and was a better determinant of solubility (R² = 0.91; p = 0.0002) than surface area (R² = 0.83; p = 0.002) and median particle size (R² = 0.59; p = 0.12). The results indicate that while solubility of FePO₄ is highly predictive of RBV, solubility, in turn, is strongly linked to amorphous content and surface area. This information may prove useful for the production of FePO₄ with the desired RBV.

Particle Size, Surface Area, and Amorphous Content as Predictors of Solubility and Bioavailability for Five Commercial Sources of Ferric Orthophosphate in Ready-To-Eat Cereal

PubMed Central

Dickmann, Robin S.; Strasburg, Gale M.; Romsos, Dale R.; Wilson, Lori A.; Lai, Grace H.; Huang, Hsimin

2016-01-01

Ferric orthophosphate (FePO4) has had limited use as an iron fortificant in ready-to-eat (RTE) cereal because of its variable bioavailability, the mechanism of which is poorly understood. Even though FePO4 has desirable sensory properties as compared to other affordable iron fortificants, few published studies have well-characterized its physicochemical properties. Semi-crystalline materials such as FePO4 have varying degrees of molecular disorder, referred to as amorphous content, which is hypothesized to be an important factor in bioavailability. The objective of this study was to systematically measure the physicochemical factors of particle size, surface area, amorphous content, and solubility underlying the variation in FePO4 bioavailability. Five commercial FePO4 sources and ferrous sulfate were added to individual batches of RTE cereal. The relative bioavailability value (RBV) of each iron source, determined using the AOAC Rat Hemoglobin Repletion Bioassay, ranged from 51% to 99% (p < 0.05), which is higher than typically reported. Solubility in dilute HCl accurately predicted RBV (R2 = 0.93, p = 0.008). Amorphous content measured by Dynamic Vapor Sorption ranged from 1.7% to 23.8% and was a better determinant of solubility (R2 = 0.91; p = 0.0002) than surface area (R2 = 0.83; p = 0.002) and median particle size (R2 = 0.59; p = 0.12). The results indicate that while solubility of FePO4 is highly predictive of RBV, solubility, in turn, is strongly linked to amorphous content and surface area. This information may prove useful for the production of FePO4 with the desired RBV. PMID:26938556

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

Mail-Order Microfluidics: Evaluation of Stereolithography for the Production of Microfluidic Devices

PubMed Central

Au, Anthony K.; Lee, Wonjae; Folch, Albert

2015-01-01

The vast majority of microfluidic devices are developed in PDMS by molding (“soft lithography”) because PDMS is an inexpensive material, has physicochemical properties that are well suited for biomedical and physical sciences applications, and design cycle lengths are generally adequate for prototype development. However, PDMS molding is tediously slow and thus cannot provide the high- or medium-volume production required for the commercialization of devices. While high-throughput plastic molding techniques (e.g. injection molding) exist, the exorbitant cost of the molds and/or the equipment can be a serious obstacle for device commercialization, especially for small startups. High-volume production is not required to reach niche markets such as clinical trials, biomedical research supplies, customized research equipment, and classroom projects. Crucially, both PDMS and plastic molding are layer-by-layer techniques where each layer is produced as a result of physicochemical processes not specified in the initial photomask(s) and where the final device requires assembly by bonding, all resulting in a cost that is very hard to predict at the start of the project. By contrast, stereolithography (SL) is an automated fabrication technique that allows for the production of quasi-arbitrary 3D shapes in a single polymeric material at medium-volume throughputs (ranging from a single part to hundreds of parts). Importantly, SL devices can be designed between several groups using CAD tools, conveniently ordered by mail, and their cost precisely predicted via a web interface. Here we evaluate the resolution of an SL mail-order service and the main causes of resolution loss; the optical clarity of the devices and how to address the lack of clarity for imaging in the channels; and the future role that SL could play in the commercialization of microfluidic devices. PMID:24510161

Mail-order microfluidics: evaluation of stereolithography for the production of microfluidic devices.

PubMed

Au, Anthony K; Lee, Wonjae; Folch, Albert

2014-04-07

The vast majority of microfluidic devices are developed in PDMS by molding ("soft lithography") because PDMS is an inexpensive material, has physicochemical properties that are well suited for biomedical and physical sciences applications, and design cycle lengths are generally adequate for prototype development. However, PDMS molding is tediously slow and thus cannot provide the high- or medium-volume production required for the commercialization of devices. While high-throughput plastic molding techniques (e.g. injection molding) exist, the exorbitant cost of the molds and/or the equipment can be a serious obstacle for device commercialization, especially for small startups. High-volume production is not required to reach niche markets such as clinical trials, biomedical research supplies, customized research equipment, and classroom projects. Crucially, both PDMS and plastic molding are layer-by-layer techniques where each layer is produced as a result of physicochemical processes not specified in the initial photomask(s) and where the final device requires assembly by bonding, all resulting in a cost that is very hard to predict at the start of the project. By contrast, stereolithography (SL) is an automated fabrication technique that allows for the production of quasi-arbitrary 3D shapes in a single polymeric material at medium-volume throughputs (ranging from a single part to hundreds of parts). Importantly, SL devices can be designed between several groups using CAD tools, conveniently ordered by mail, and their cost precisely predicted via a web interface. Here we evaluate the resolution of an SL mail-order service and the main causes of resolution loss; the optical clarity of the devices and how to address the lack of clarity for imaging in the channels; and the future role that SL could play in the commercialization of microfluidic devices.

Partitioning behavior of aromatic components in jet fuel into diverse membrane-coated fibers.

PubMed

Baynes, Ronald E; Xia, Xin-Rui; Barlow, Beth M; Riviere, Jim E

2007-11-01

Jet fuel components are known to partition into skin and produce occupational irritant contact dermatitis (OICD) and potentially adverse systemic effects. The purpose of this study was to determine how jet fuel components partition (1) from solvent mixtures into diverse membrane-coated fibers (MCFs) and (2) from biological media into MCFs to predict tissue distribution. Three diverse MCFs, polydimethylsiloxane (PDMS, lipophilic), polyacrylate (PA, polarizable), and carbowax (CAR, polar), were selected to simulate the physicochemical properties of skin in vivo. Following an appropriate equilibrium time between the MCF and dosing solutions, the MCF was injected directly into a gas chromatograph/mass spectrometer (GC-MS) to quantify the amount that partitioned into the membrane. Three vehicles (water, 50% ethanol-water, and albumin-containing media solution) were studied for selected jet fuel components. The more hydrophobic the component, the greater was the partitioning into the membranes across all MCF types, especially from water. The presence of ethanol as a surrogate solvent resulted in significantly reduced partitioning into the MCFs with discernible differences across the three fibers based on their chemistries. The presence of a plasma substitute (media) also reduced partitioning into the MCF, with the CAR MCF system being better correlated to the predicted partitioning of aromatic components into skin. This study demonstrated that a single or multiple set of MCF fibers may be used as a surrogate for octanol/water systems and skin to assess partitioning behavior of nine aromatic components frequently formulated with jet fuels. These diverse inert fibers were able to assess solute partitioning from a blood substitute such as media into a membrane possessing physicochemical properties similar to human skin. This information may be incorporated into physiologically based pharmacokinetic (PBPK) models to provide a more accurate assessment of tissue dosimetry of related toxicants.

Abbott Physicochemical Tiering (APT)--a unified approach to HTS triage.

PubMed

Cox, Philip B; Gregg, Robert J; Vasudevan, Anil

2012-07-15

The selection of the highest quality chemical matter from high throughput screening (HTS) is the ultimate aim of any triage process. Typically there are many hundreds or thousands of hits capable of modulating a given biological target in HTS with a wide range of physicochemical properties that should be taken into consideration during triage. Given the multitude of physicochemical properties that define drug-like space, a system needs to be in place that allows for a rapid selection of chemical matter based on a prioritized range of these properties. With this goal in mind, we have developed a tool, coined Abbott Physicochemical Tiering (APT) that enables hit prioritization based on ranges of these important physicochemical properties. This tool is now used routinely at Abbott to help prioritize hits out of HTS during the triage process. Herein we describe how this tool was developed and validated using Abbott internal high throughput ADME data (HT-ADME). Copyright © 2012 Elsevier Ltd. All rights reserved.

Bacterial diversity differences along an epigenic cave stream reveal evidence of community dynamics, succession, and stability.

PubMed

Brannen-Donnelly, Kathleen; Engel, Annette S

2015-01-01

Unchanging physicochemical conditions and nutrient sources over long periods of time in cave and karst subsurface habitats, particularly aquifers, can support stable ecosystems, termed autochthonous microbial endokarst communities (AMEC). AMEC existence is unknown for other karst settings, such as epigenic cave streams. Conceptually, AMEC should not form in streams due to faster turnover rates and seasonal disturbances that have the capacity to transport large quantities of water and sediment and to change allochthonous nutrient and organic matter sources. Our goal was to investigate whether AMEC could form and persist in hydrologically active, epigenic cave streams. We analyzed bacterial diversity from cave water, sediments, and artificial substrates (Bio-Traps®) placed in the cave at upstream and downstream locations. Distinct communities existed for the water, sediments, and Bio-Trap® samplers. Throughout the study period, a subset of community members persisted in the water, regardless of hydrological disturbances. Stable habitat conditions based on flow regimes resulted in more than one contemporaneous, stable community throughout the epigenic cave stream. However, evidence for AMEC was insufficient for the cave water or sediments. Community succession, specifically as predictable exogenous heterotrophic microbial community succession, was evident from decreases in community richness from the Bio-Traps®, a peak in Bio-Trap® community biomass, and from changes in the composition of Bio-Trap® communities. The planktonic community was compositionally similar to Bio-Trap® initial colonizers, but the downstream Bio-Trap® community became more similar to the sediment community at the same location. These results can help in understanding the diversity of planktonic and attached microbial communities from karst, as well as microbial community dynamics, stability, and succession during disturbance or contamination responses over time.

Component characterization and predictive modeling for green roof substrates optimized to adsorb P and improve runoff quality: A review.

PubMed

Jennett, Tyson S; Zheng, Youbin

2018-06-01

This review is a synthesis of the current knowledge regarding the effects of green roof substrate components and their retentive capacity for nutrients, particularly phosphorus (P). Substrates may behave as either sources or sinks of P depending on the components they are formulated from, and to date, the total P-adsorbing capacity of a substrate has not been quantified as the sum of the contributions of its components. Few direct links have been established among substrate components and their physicochemical characteristics that would affect P-retention. A survey of recent literature presented herein highlights the trends within individual component selection (clays and clay-like material, organics, conventional soil and sands, lightweight inorganics, and industrial wastes and synthetics) for those most common during substrate formulation internationally. Component selection will vary with respect to ease of sourcing component materials, cost of components, nutrient-retention capacity, and environmental sustainability. However, the number of distinct components considered for inclusion in green roof substrates continues to expand, as the desires of growers, material suppliers, researchers and industry stakeholders are incorporated into decision-making. Furthermore, current attempts to characterize the most often used substrate components are also presented whereby runoff quality is correlated to entire substrate performance. With the use of well-described characterization (constant capacitance model) and modeling techniques (the soil assemblage model), it is proposed that substrates optimized for P adsorption may be developed through careful selection of components with prior knowledge of their chemical properties, that may increase retention of P in plant-available forms, thereby reducing green roof fertilizer requirements and P losses in roof runoff. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationship between performance deterioration of a polyamide reverse osmosis membrane used in a seawater desalination plant and changes in its physicochemical properties.

PubMed

Suzuki, Tasuma; Tanaka, Ryohei; Tahara, Marina; Isamu, Yuya; Niinae, Masakazu; Lin, Lin; Wang, Jingbo; Luh, Jeanne; Coronell, Orlando

2016-09-01

While it is known that the performance of reverse osmosis membranes is dependent on their physicochemical properties, the existing literature studying membranes used in treatment facilities generally focuses on foulant layers or performance changes due to fouling, not on the performance and physicochemical changes that occur to the membranes themselves. In this study, the performance and physicochemical properties of a polyamide reverse osmosis membrane used for three years in a seawater desalination plant were compared to those of a corresponding unused membrane. The relationship between performance changes during long-term use and changes in physicochemical properties was evaluated. The results showed that membrane performance deterioration (i.e., reduced water flux, reduced contaminant rejection, and increased fouling propensity) occurred as a result of membrane use in the desalination facility, and that the main physicochemical changes responsible for performance deterioration were reduction in PVA coating coverage and bromine uptake by polyamide. The latter was likely promoted by oxidant residual in the membrane feed water. Our findings indicate that the optimization of membrane materials and processes towards maximizing the stability of the PVA coating and ensuring complete removal of oxidants in feed waters would minimize membrane performance deterioration in water purification facilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Physicochemical water quality of the Mfoundi River watershed at Yaoundé, Cameroon, and its relevance to the distribution of bacterial indicators of faecal contamination.

PubMed

Djuikom, E; Jugnia, L B; Nola, M; Foto, S; Sikati, V

2009-01-01

Water quality of the Mfoundi River and four of its tributaries was studied by assessing some physicochemical variables (temperature, pH, conductivity, chlorides, phosphates and nitrogen ammonia, dissolved oxygen and carbon dioxide, organic matter content and Biological Oxygen Demand) and their influence on the distribution of bacterial indicators of faecal contamination (total coliform, faecal coliform and faecal streptococci). For this, standard methods for the examination of physicochemical parameters in water were followed, and statistical analysis (Pearson correlations) used to establish any relationships between physicochemical and biological variables. Our results revealed that almost all of the examined physicochemical variables exceeded World Health Organization (WHO) guidelines for recreational water. This was in agreement with a previous microbiological study indicating that these waters were not safe for human use or primary contact according to water quality standards established by the WHO. Results of our correlation analysis suggested that physicochemical and biological variables interact in complicated ways reflecting the complex processes occurring in the natural environment. It was also concluded that pollution in the Mfoundi River watershed poses an increased risk of infection for users and there exists an urgent need to control dumping of wastewater into this watershed.

A study on the electrical, optical, and physicochemical properties of poly(MMA-co-MAA)/ poly(3,4-ethylenedioxythiophene) hybrid thin films.

PubMed

Han, Yong-Hyeon; Kim, Hyeong Eun; Hwangbo, Kyung-Hee; Yim, Jin-Heong; Cho, Kuk Young

2013-08-01

Poly(3,4-ethylenedioxythiophene) (PEDOT) has good properties as a conductive polymer such as high conductivity, optical transmittance, and chemical stability, while offering relatively weak physicochemical properties. The main purpose of this paper is to improve physicochemical properties such as solvent resistance and pencil hardness of PEDOT. Carboxyl groups in the poly(MMA-co-MAA) polymer chains can effectively crosslink each other in the presence of aziridine, resulting in physicochemically robust PEDOT/poly(MMA-co-MAA) hybrid conductive films. The electrical conductivity, optical properties, and physicochemical properties of the hybrid conductive film were compared by varying the solid content and poly(MMA-co-MAA) portion in the coating precursor solution. From the results, the transparency and surface resistance of the hybrid film show a tendency to decrease with increasing solid content in the coating precursor. Moreover, solvent resistance and hardness were dramatically enhanced by hybridization of PEDOT and crosslinked poly(MMA-co-MAA) due to curing reactions between carboxyl groups. The chemical composition of 30 wt-% of poly(MMA-co-MAA) (MMA:MAA mole ratio 9:1) and 3 wt-% - 5 wt-% of aziridine yields the best physicochemical properties of poly(MMA-co-MAA)/PEDOT hybrid thin films.

Evaluation of metal removal efficiency and its influence in the physicochemical parameters at two sewage treatment plants.

PubMed

Pipi, Angelo R F; Magdalena, Aroldo G; Giafferis, Giselda P; da Silva, Gustavo H R; Piacenti-Silva, Marina

2018-04-03

In sewage treatment plants, physicochemical parameters are highly controlled since treated sewage can be returned to water bodies or reused. In addition, pollutants such as heavy metals also deserve attention due to their potential toxicity. In general, these characteristics of sewage and treated water are evaluated independently, with the support of Brazilian legislation that does not require a routine for the analysis of metals as frequent as for the physicochemical parameters. In this work, 66 samples of raw sewage, treated sewage, and effluents from two treatment plants in the city of Bauru, São Paulo, Brazil, were evaluated to assess the efficiency of the treatment plants in the removal of metals. In addition, the influence of these pollutants on the quantification of physicochemical parameters was evaluated. The quantification of metals was performed using inductively coupled plasma optical spectroscopy (ICP-OES), and Spearman's test was applied to evaluate correlation between physicochemical parameters and metal content. The main metals found in the samples were Ba, Mn, Zn, Cu, Se, Fe, and Al. The results indicate that concentrations of metals in the aquatic environment can significantly affect the physicochemical parameters, since high concentrations of metals can interfere mainly in the pH, chemical oxygen demand, and dissolved oxygen.

Physicochemical Characteristics of Larval Habitat Waters of Mosquitoes (Diptera: Culicidae) in Qom Province, Central Iran

PubMed Central

Abai, Mohammad Reza; Saghafipour, Abedin; Ladonni, Hossein; Jesri, Nahid; Omidi, Saeed; Azari-Hamidian, Shahyad

2016-01-01

Background: Mosquitoes lay eggs in a wide range of habitats with different physicochemical parameters. Ecological data, including physicochemical factors of oviposition sites, play an important role in integrated vector management. Those data help the managers to make the best decision in controlling the aquatic stages of vectors especially using source reduction. Methods: To study some physicochemical characteristics of larval habitat waters, an investigation was carried out in Qom Province, central Iran, during spring and summer 2008 and 2009. Water samples were collected during larval collection from ten localities. The chemical parameters of water samples were analyzed based on mg/l using standard methods. Water temperature (°C), turbidity (NTU), total dissolved solids (ppm), electrical conductivity (μS/cm), and acidity (pH) were measured using digital testers. Thermotolerant coliforms of water samples were analyzed based on MPN/100ml. Data were assessed by Kruskal-Wallis test and Spearman Correlation analysis. Results: In total, 371 mosquito larvae were collected including 14 species representing four genera. Some physicochemical parameters of water in Emamzadeh Esmail, Qomrood, Qom City, and Rahjerd showed significant differences among localities (P< 0.05). The physicochemical and microbial parameters did not show any significant differences among different species (P> 0.05). There was no significant correlation between the abundance of larvae and the different physicochemical and microbial parameters (P> 0.05). Conclusion: The means of EC, TDS, and phosphate of localities and species were remarkably higher than those of the previous studies. Other parameters seem to be in the range of other investigations. PMID:27047973

Physicochemical Characteristics of Larval Habitat Waters of Mosquitoes (Diptera: Culicidae) in Qom Province, Central Iran.

PubMed

Abai, Mohammad Reza; Saghafipour, Abedin; Ladonni, Hossein; Jesri, Nahid; Omidi, Saeed; Azari-Hamidian, Shahyad

2016-03-01

Mosquitoes lay eggs in a wide range of habitats with different physicochemical parameters. Ecological data, including physicochemical factors of oviposition sites, play an important role in integrated vector management. Those data help the managers to make the best decision in controlling the aquatic stages of vectors especially using source reduction. To study some physicochemical characteristics of larval habitat waters, an investigation was carried out in Qom Province, central Iran, during spring and summer 2008 and 2009. Water samples were collected during larval collection from ten localities. The chemical parameters of water samples were analyzed based on mg/l using standard methods. Water temperature (°C), turbidity (NTU), total dissolved solids (ppm), electrical conductivity (μS/cm), and acidity (pH) were measured using digital testers. Thermotolerant coliforms of water samples were analyzed based on MPN/100ml. Data were assessed by Kruskal-Wallis test and Spearman Correlation analysis. In total, 371 mosquito larvae were collected including 14 species representing four genera. Some physicochemical parameters of water in Emamzadeh Esmail, Qomrood, Qom City, and Rahjerd showed significant differences among localities (P< 0.05). The physicochemical and microbial parameters did not show any significant differences among different species (P> 0.05). There was no significant correlation between the abundance of larvae and the different physicochemical and microbial parameters (P> 0.05). The means of EC, TDS, and phosphate of localities and species were remarkably higher than those of the previous studies. Other parameters seem to be in the range of other investigations.

Social class, power, and selfishness: when and why upper and lower class individuals behave unethically.

PubMed

Dubois, David; Rucker, Derek D; Galinsky, Adam D

2015-03-01

Are the rich more unethical than the poor? To answer this question, the current research introduces a key conceptual distinction between selfish and unethical behavior. Based on this distinction, the current article offers 2 novel findings that illuminate the relationship between social class and unethical behavior. First, the effects of social class on unethical behavior are not invariant; rather, the effects of social class are moderated by whether unethical behavior benefits the self or others. Replicating past work, social class positively predicted unethical behavior; however, this relationship was only observed when that behavior was self-beneficial. When unethical behavior was performed to benefit others, social class negatively predicted unethical behavior; lower class individuals were more likely than upper class individuals to engage in unethical behavior. Overall, social class predicts people's tendency to behave selfishly, rather than predicting unethical behavior per se. Second, individuals' sense of power drove the effects of social class on unethical behavior. Evidence for this relationship was provided in three forms. First, income, but not education level, predicted unethical behavior. Second, feelings of power mediated the effect of social class on unethical behavior, but feelings of status did not. Third, two distinct manipulations of power produced the same moderation by self-versus-other beneficiary as was found with social class. The current theoretical framework and data both synthesize and help to explain a range of findings in the social class and power literatures. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A Study of Physicochemical Properties of Subcutaneous Fat of the Abdomen and its Implication in Abdominal Obesity

PubMed Central

Kumar, Pramod; Kodavoor, Srinivas Aithal; Kotian, Sushma Rama; Yathdaka, Sudhakar Narahari; Nayak, Dayanand; Souza, Anne D; Souza, Antony Sylvan D

2016-01-01

Introduction The lower abdominal obesity is more resistant to absorption as compared to that of upper abdomen. Differences in the physicochemical properties of the subcutaneous fat of the upper and lower abdomen may be responsible for this variation. There is paucity of the scientific literature on the physicochemical properties of the subcutaneous fat of abdomen. Aim The present study was undertaken to create a database of physicochemical properties of abdominal subcutaneous fat. Materials and Methods The samples of subcutaneous fat from upper and lower abdomen were collected from 40 fresh autopsied bodies (males 33, females 7). The samples were prepared for physicochemical analysis using organic and inorganic solvents. Various physicochemical properties of the fat samples analysed were surface tension, viscosity, specific gravity, specific conductivity, iodine value and thermal properties. Data was analysed by paired and independent sample t-tests. Results There was a statistically significant difference in all the physicochemical parameters between males and females except surface tension (organic) and surface tension (inorganic) of upper abdominal fat, and surface tension (organic) of lower abdominal fat. In males, viscosity of upper abdominal fat was more compared to that of lower abdomen (both organic and inorganic) unlike the specific conductivity that was higher for the lower abdominal fat as compared to that of the upper abdomen. In females there were statistically significant higher values of surface tension (inorganic) and specific gravity (organic) of the upper abdomen fat as compared to that of lower abdomen. The initial and final weight loss of the lower abdominal fat as indicated by Thermo Gravimetric Analysis was significantly more in males than in female Conclusion The difference in the physicochemical properties of subcutaneous fat between upper and lower abdomen and between males and females could be responsible for the variant behaviour of subcutaneous abdominal fat towards resorption. PMID:27437272

Improving transmembrane protein consensus topology prediction using inter-helical interaction.

PubMed

Wang, Han; Zhang, Chao; Shi, Xiaohu; Zhang, Li; Zhou, You

2012-11-01

Alpha helix transmembrane proteins (αTMPs) represent roughly 30% of all open reading frames (ORFs) in a typical genome and are involved in many critical biological processes. Due to the special physicochemical properties, it is hard to crystallize and obtain high resolution structures experimentally, thus, sequence-based topology prediction is highly desirable for the study of transmembrane proteins (TMPs), both in structure prediction and function prediction. Various model-based topology prediction methods have been developed, but the accuracy of those individual predictors remain poor due to the limitation of the methods or the features they used. Thus, the consensus topology prediction method becomes practical for high accuracy applications by combining the advances of the individual predictors. Here, based on the observation that inter-helical interactions are commonly found within the transmembrane helixes (TMHs) and strongly indicate the existence of them, we present a novel consensus topology prediction method for αTMPs, CNTOP, which incorporates four top leading individual topology predictors, and further improves the prediction accuracy by using the predicted inter-helical interactions. The method achieved 87% prediction accuracy based on a benchmark dataset and 78% accuracy based on a non-redundant dataset which is composed of polytopic αTMPs. Our method derives the highest topology accuracy than any other individual predictors and consensus predictors, at the same time, the TMHs are more accurately predicted in their length and locations, where both the false positives (FPs) and the false negatives (FNs) decreased dramatically. The CNTOP is available at: http://ccst.jlu.edu.cn/JCSB/cntop/CNTOP.html. Copyright © 2012 Elsevier B.V. All rights reserved.

Remembered study mode: support for the distinctiveness account of the production effect.

PubMed

Ozubko, Jason D; Major, Jennifer; MacLeod, Colin M

2014-01-01

The production effect is the finding that words spoken aloud at study are subsequently remembered better than are words read silently at study. According to the distinctiveness account, aloud words are remembered better because the act of speaking those words aloud is encoded and later recovery of this information can be used to infer that those words were studied. An alternative account (the strength-based account) is that memory strength is simply greater for words read aloud. To discriminate these two accounts, we investigated study mode judgements (i.e., "aloud"/"silent"/"new" ratings): The strength-based account predicts that "aloud" responses should positively correlate with memory strength, whereas the distinctiveness account predicts that accuracy of study mode judgements will be independent of memory strength. Across three experiments, where the strength of some silent words was increased by repetition, study mode was discriminable regardless of strength-even when the strength of aloud and repeated silent items was equivalent. Consistent with the distinctiveness account, we conclude that memory for "aloudness" is independent of memory strength and a likely candidate to explain the production effect.

Conceptual Distinctiveness Supports Detailed Visual Long-Term Memory for Real-World Objects

PubMed Central

Konkle, Talia; Brady, Timothy F.; Alvarez, George A.; Oliva, Aude

2012-01-01

Humans have a massive capacity to store detailed information in visual long-term memory. The present studies explored the fidelity of these visual long-term memory representations and examined how conceptual and perceptual features of object categories support this capacity. Observers viewed 2,800 object images with a different number of exemplars presented from each category. At test, observers indicated which of 2 exemplars they had previously studied. Memory performance was high and remained quite high (82% accuracy) with 16 exemplars from a category in memory, demonstrating a large memory capacity for object exemplars. However, memory performance decreased as more exemplars were held in memory, implying systematic categorical interference. Object categories with conceptually distinctive exemplars showed less interference in memory as the number of exemplars increased. Interference in memory was not predicted by the perceptual distinctiveness of exemplars from an object category, though these perceptual measures predicted visual search rates for an object target among exemplars. These data provide evidence that observers’ capacity to remember visual information in long-term memory depends more on conceptual structure than perceptual distinctiveness. PMID:20677899

GCPred: a web tool for guanylyl cyclase functional centre prediction from amino acid sequence.

PubMed

Xu, Nuo; Fu, Dongfang; Li, Shiang; Wang, Yuxuan; Wong, Aloysius

2018-06-15

GCPred is a webserver for the prediction of guanylyl cyclase (GC) functional centres from amino acid sequence. GCs are enzymes that generate the signalling molecule cyclic guanosine 3', 5'-monophosphate from guanosine-5'-triphosphate. A novel class of GC centres (GCCs) has been identified in complex plant proteins. Using currently available experimental data, GCPred is created to automate and facilitate the identification of similar GCCs. The server features GCC values that consider in its calculation, the physicochemical properties of amino acids constituting the GCC and the conserved amino acids within the centre. From user input amino acid sequence, the server returns a table of GCC values and graphs depicting deviations from mean values. The utility of this server is demonstrated using plant proteins and the human interleukin-1 receptor-associated kinase family of proteins as example. The GCPred server is available at http://gcpred.com. Supplementary data are available at Bioinformatics online.

A topologically related singularity suggests a maximum preferred size for protein domains.

PubMed

Zbilut, Joseph P; Chua, Gek Huey; Krishnan, Arun; Bossa, Cecilia; Rother, Kristian; Webber, Charles L; Giuliani, Alessandro

2007-02-15

A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction. 2006 Wiley-Liss, Inc.

Rapid hybridization of nucleic acids using isotachophoresis

PubMed Central

Bercovici, Moran; Han, Crystal M.; Liao, Joseph C.; Santiago, Juan G.

2012-01-01

We use isotachophoresis (ITP) to control and increase the rate of nucleic acid hybridization reactions in free solution. We present a new physical model, validation experiments, and demonstrations of this assay. We studied the coupled physicochemical processes of preconcentration, mixing, and chemical reaction kinetics under ITP. Our experimentally validated model enables a closed form solution for ITP-aided reaction kinetics, and reveals a new characteristic time scale which correctly predicts order 10,000-fold speed-up of chemical reaction rate for order 100 pM reactants, and greater enhancement at lower concentrations. At 500 pM concentration, we measured a reaction time which is 14,000-fold lower than that predicted for standard second-order hybridization. The model and method are generally applicable to acceleration of reactions involving nucleic acids, and may be applicable to a wide range of reactions involving ionic reactants. PMID:22733732