Antinociceptive Grayanoids from the Roots of Rhododendron molle.

PubMed

Li, Yong; Liu, Yun-Bao; Zhang, Jian-Jun; Liu, Yang; Ma, Shuang-Gang; Qu, Jing; Lv, Hai-Ning; Yu, Shi-Shan

2015-12-24

Nine new grayanoids (1-9), together with 11 known compounds, were isolated from the roots of Rhododendron molle. The structures of the new compounds (1-9) were determined on the basis of spectroscopic analysis, including HRESIMS, and 1D and 2D NMR data. Compounds 4, 6, 12, and 14-20 showed significant antinociceptive activities in an acetic acid-induced writhing test. In particular, 14 and 15 were found to be more potent than morphine for both acute and inflammatory pain models and 100-fold more potent than gabapentin in a diabetic neuropathic pain model.

Effects of Vanadium-Containing Compounds on Membrane Lipids and on Microdomains Used in Receptor-Mediated Signaling

PubMed Central

Roess, Deborah A.; Smith, Steven M. L.; Winter, Peter; Zhou, Jun; Dou, Ping; Baruah, Bharat; Trujillo, Alejandro M.; Levinger, Nancy E.; Yang, Xioda; Barisas, B. George; Crans, Debbie C.

2011-01-01

There is increasing evidence for the involvement of plasma membrane microdomains in insulin receptor function. Moreover, disruption of these structures, which are typically enriched in sphingomyelin and cholesterol, results in insulin resistance. Treatment strategies for insulin resistance include the use of vanadium compounds which have been shown in animal models to enhance insulin responsiveness. One possible mechanism for insulin-enhancing effects might involve direct effects of vanadium compounds on membrane lipid organization. These changes in lipid organization promote the partitioning of insulin receptors and other receptors into membrane microdomains where receptors are optimally functional. To explore this possibility, we have used several strategies involving vanadium complexes such as [VO2dipic]− (pyridin-2,6-dicarboxylatodioxovanadium(V)), decavanadate (V10O286−, V10), BMOV (bis(maltolato)oxovanadium(IV)) and [VO(saltris)]2 (2-salicylideniminato-2-(hydroxymethyl)-1,3-dihydroxypropane-oxovanadium(V)). Our strategies include an evaluation of interactions between vanadium-containing compounds and model lipid systems, an evaluation of the effects of vanadium compounds on lipid fluidity in erythrocyte membranes, and studies of the effects of vanadium-containing compounds on signaling events initiated by receptors known to use membrane microdomains as signaling platforms. PMID:18729092

Drosophila melanogaster as a model system for the evaluation of anti-aging compounds.

PubMed

Jafari, Mahtab

2010-01-01

Understanding the causes of aging is a complex problem due to the multiple factors that influence aging, which include genetics, environment, metabolism and reproduction, among others. These multiple factors create logistical difficulties in the evaluation of anti-aging agents. There is a need for good model systems to evaluate potential anti-aging compounds. The model systems used should represent the complexities of aging in humans, so that the findings may be extrapolated to human studies, but they should also present an opportunity to minimize the variables so that the experimental results can be accurately interpreted. In addition to positively affecting lifespan, the impact of the compound on the physiologic confounders of aging, including fecundity and the health span--the period of life where an organism is generally healthy and free from serious or chronic illness--of the model organism needs to be evaluated. Fecundity is considered a major confounder of aging in fruit flies. It is well established that female flies that are exposed to toxic substances typically reduce their dietary intake and their reproductive output and display an artifactual lifespan extension. As a result, drugs that achieve longevity benefits by reducing fecundity as a result of diminished food intake are probably not useful candidates for eventual treatment of aging in humans and should be eliminated during the screening process. Drosophila melanogaster provides a suitable model system for the screening of anti-aging compounds as D. melanogaster and humans have many conserved physiological and biological pathways. In this paper, I propose an algorithm to screen anti-aging compounds using Drosophila melanogaster as a model system.

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

Large-Scale Phenotype-Based Antiepileptic Drug Screening in a Zebrafish Model of Dravet Syndrome1,2,3

PubMed Central

Dinday, Matthew T.

2015-01-01

Abstract Mutations in a voltage-gated sodium channel (SCN1A) result in Dravet Syndrome (DS), a catastrophic childhood epilepsy. Zebrafish with a mutation in scn1Lab recapitulate salient phenotypes associated with DS, including seizures, early fatality, and resistance to antiepileptic drugs. To discover new drug candidates for the treatment of DS, we screened a chemical library of ∼1000 compounds and identified 4 compounds that rescued the behavioral seizure component, including 1 compound (dimethadione) that suppressed associated electrographic seizure activity. Fenfluramine, but not huperzine A, also showed antiepileptic activity in our zebrafish assays. The effectiveness of compounds that block neuronal calcium current (dimethadione) or enhance serotonin signaling (fenfluramine) in our zebrafish model suggests that these may be important therapeutic targets in patients with DS. Over 150 compounds resulting in fatality were also identified. We conclude that the combination of behavioral and electrophysiological assays provide a convenient, sensitive, and rapid basis for phenotype-based drug screening in zebrafish mimicking a genetic form of epilepsy. PMID:26465006

A Screening Assay Based on Host-Pathogen Interaction Models Identifies a Set of Novel Antifungal Benzimidazole Derivatives▿

PubMed Central

Burger-Kentischer, Anke; Finkelmeier, Doris; Keller, Petra; Bauer, Jörg; Eickhoff, Holger; Kleymann, Gerald; Abu Rayyan, Walid; Singh, Anurag; Schröppel, Klaus; Lemuth, Karin; Wiesmüller, Karl-Heinz; Rupp, Steffen

2011-01-01

Fungal infections are a serious health problem in clinics, especially in the immune-compromised patient. Disease ranges from widespread superficial infections like vulvovaginal infections to life-threatening systemic candidiasis. Especially for systemic mycoses, only a limited arsenal of antifungals is available. The most commonly used classes of antifungal compounds used include azoles, polyenes, and echinocandins. Due to emerging resistance to standard therapy, significant side effects, and high costs for several antifungals, there is a medical need for new antifungals in the clinic and general practice. In order to expand the arsenal of compounds with antifungal activities, we screened a compound library including more than 35,000 individual compounds derived from organic synthesis as well as combinatorial compound collections representing mixtures of compounds for antimycotic activity. In total, more than 100,000 compounds were screened using a new type of activity-selectivity assay, analyzing both the antifungal activity and the compatibility with human cells at the same time. One promising hit, an (S)-2-aminoalkyl benzimidazole derivative, was developed among a series of lead compounds showing potent antifungal activity. (S)-2-(1-Aminoisobutyl)-1-(3-chlorobenzyl) benzimidazole showed the highest antifungal activity and the best compatibility with human cells in several cell culture models and against a number of clinical isolates of several species of pathogenic Candida yeasts. Transcriptional profiling indicates that the newly discovered compound is a potential inhibitor of the ergosterol pathway, in contrast to other benzimidazole derivatives, which target microtubules. PMID:21746957

A MODEL FOR DIFFUSION CONTROLLED BIOAVAILABILITY OF CRUDE OIL COMPONENTS

EPA Science Inventory

Crude oil is a complex mixture of several different structural classes of compounds including alkanes, aromatics, heterocyclic polar compounds, and asphaltenes. The rate and extent of microbial degradation of crude oil depends on the interaction between the physical and biochemi...

Antitumor activity of a novel and orally available inhibitor of serine palmitoyltransferase

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

Yaguchi, Masahiro; Shibata, Sachio; Satomi, Yoshinori

Metabolic reprogramming is an essential hallmark of neoplasia. Therefore, targeting cancer metabolism, including lipid synthesis, has attracted much interest in recent years. Serine palmitoyltransferase (SPT) plays a key role in the initial and rate-limiting step of de novo sphingolipid biosynthesis, and inhibiting SPT activity prevents the proliferation of certain cancer cells. Here, we identified a novel and orally available SPT inhibitor, compound-2. Compound-2 showed an anti-proliferative effect in several cancer cell models, reducing the levels of the sphingolipids ceramide and sphingomyelin. In the presence of compound-2, exogenously added S1P partially compensated the intracellular sphingolipid levels through the salvage pathway bymore » partially rescuing compound-2-induced cytotoxicity. This suggested that the mechanism underlying the anti-proliferative effect of compound-2 involved the reduction of sphingolipid levels. Indeed, compound-2 promoted multinuclear formation with reduced endogenous sphingomyelin levels specifically in a compound-2-sensitive cell line, indicating that the effect was induced by sphingolipid reduction. Furthermore, compound-2 showed potent antitumor activity without causing significant body weight loss in the PL-21 acute myeloid leukemia mouse xenograft model. Therefore, SPT may be an attractive therapeutic anti-cancer drug target for which compound-2 may be a promising new drug. - Highlights: • We discovered compound-2, a novel and orally available SPT inhibitor. • Compound-2 was cytotoxic against PL-21 acute myeloid leukemia cells. • Compound-2 showed antitumor activity in the PL-21 mouse xenograft model.« less

Tackling the conformational sampling of larger flexible compounds and macrocycles in pharmacology and drug discovery.

PubMed

Chen, I-Jen; Foloppe, Nicolas

2013-12-15

Computational conformational sampling underpins much of molecular modeling and design in pharmaceutical work. The sampling of smaller drug-like compounds has been an active area of research. However, few studies have tested in details the sampling of larger more flexible compounds, which are also relevant to drug discovery, including therapeutic peptides, macrocycles, and inhibitors of protein-protein interactions. Here, we investigate extensively mainstream conformational sampling methods on three carefully curated compound sets, namely the 'Drug-like', larger 'Flexible', and 'Macrocycle' compounds. These test molecules are chemically diverse with reliable X-ray protein-bound bioactive structures. The compared sampling methods include Stochastic Search and the recent LowModeMD from MOE, all the low-mode based approaches from MacroModel, and MD/LLMOD recently developed for macrocycles. In addition to default settings, key parameters of the sampling protocols were explored. The performance of the computational protocols was assessed via (i) the reproduction of the X-ray bioactive structures, (ii) the size, coverage and diversity of the output conformational ensembles, (iii) the compactness/extendedness of the conformers, and (iv) the ability to locate the global energy minimum. The influence of the stochastic nature of the searches on the results was also examined. Much better results were obtained by adopting search parameters enhanced over the default settings, while maintaining computational tractability. In MOE, the recent LowModeMD emerged as the method of choice. Mixed torsional/low-mode from MacroModel performed as well as LowModeMD, and MD/LLMOD performed well for macrocycles. The low-mode based approaches yielded very encouraging results with the flexible and macrocycle sets. Thus, one can productively tackle the computational conformational search of larger flexible compounds for drug discovery, including macrocycles. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hepatocyte-based in vitro model for assessment of drug-induced cholestasis

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

Chatterjee, Sagnik, E-mail: Sagnik.Chatterjee@pharm.kuleuven.be; Richert, Lysiane, E-mail: l.richert@kaly-cell.com; Augustijns, Patrick, E-mail: Patrick.Augustijns@pharm.kuleuven.be

Early detection of drug-induced cholestasis remains a challenge during drug development. We have developed and validated a biorelevant sandwich-cultured hepatocytes- (SCH) based model that can identify compounds causing cholestasis by altering bile acid disposition. Human and rat SCH were exposed (24–48 h) to known cholestatic and/or hepatotoxic compounds, in the presence or in the absence of a concentrated mixture of bile acids (BAs). Urea assay was used to assess (compromised) hepatocyte functionality at the end of the incubations. The cholestatic potential of the compounds was expressed by calculating a drug-induced cholestasis index (DICI), reflecting the relative residual urea formation bymore » hepatocytes co-incubated with BAs and test compound as compared to hepatocytes treated with test compound alone. Compounds with clinical reports of cholestasis, including cyclosporin A, troglitazone, chlorpromazine, bosentan, ticlopidine, ritonavir, and midecamycin showed enhanced toxicity in the presence of BAs (DICI ≤ 0.8) for at least one of the tested concentrations. In contrast, the in vitro toxicity of compounds causing hepatotoxicity by other mechanisms (including diclofenac, valproic acid, amiodarone and acetaminophen), remained unchanged in the presence of BAs. A safety margin (SM) for drug-induced cholestasis was calculated as the ratio of lowest in vitro concentration for which was DICI ≤ 0.8, to the reported mean peak therapeutic plasma concentration. SM values obtained in human SCH correlated well with reported % incidence of clinical drug-induced cholestasis, while no correlation was observed in rat SCH. This in vitro model enables early identification of drug candidates causing cholestasis by disturbed BA handling. - Highlights: • Novel in vitro assay to detect drug-induced cholestasis • Rat and human sandwich-cultured hepatocytes (SCH) as in vitro models • Cholestatic compounds sensitize SCH to toxic effects of accumulating bile acids • Drug-induced cholestasis index (DICI) as measure of a drug's cholestatic signature • In vitro findings correlate well with clinical reports on cholestasis.« less

A case study on the influences of long-range transport to Taiwan`s acid deposition using Taiwan air quality model

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

Ken-Hui Chang; Fu-Tien Jeng

1996-12-31

The long-range and transboundary transport of precursors of add deposition in East Asia became important due to the industrial development around this area. We started to develop Taiwan Air Quality Model (TAQM) system since 1992, which is based on regional Acid Deposition Model (RADM) system. A typical episode in Mei-Yu season has been selected to study. A case considering all emissions within simulated domain has been run as a reference case, and another perturbed case, not including Taiwan`s emission, has been also run for analyzing quantitatively the influence of long-range transport to Taiwan`s wet deposition during the episode are 31%more » and 24% for total sulfur compounds and total nitrogen compounds respectively; but for dry deposition, only 6% is contributed by long range transport for sulfur compounds and 29% for total nitrogen compounds. Therefore, the percentages of total acid deposition contributed by long-range transport are 27% and 25% for total sulfur compounds and total nitrogen compounds, respectively.« less

Measurement of infrared refractive indices of organic and organophosphorous compounds for optical modeling

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

Tonkyn, Russell G.; Danby, Tyler O.; Birnbaum, Jerome C.

The complex optical refractive index contains the optical constants, n(more » $$\\tilde{u}$$)and k($$\\tilde{u}$$), which correspond to the dispersion and absorption of light within a medium, respectively. By obtaining the optical constants one can in principle model most optical phenomena in media and at interfaces including reflection, refraction and dispersion. We have developed improved protocols based on the use of multiple path lengths to determine the optical constants for dozens of liquids, including organic and organophosphorous compounds. Detailed description of the protocols to determine the infrared indices will be presented, along with preliminary results using the constants with their applications to optical modeling.« less

The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.

An Improved Small-Molecule Inhibitor of FtsZ with Superior In Vitro Potency, Drug-Like Properties, and In Vivo Efficacy

PubMed Central

Baker, Nicola; Bennett, James M.; Berry, Joanne; Collins, Ian; Czaplewski, Lloyd G.; Logan, Alastair; Macdonald, Rebecca; MacLeod, Leanne; Peasley, Hilary; Mitchell, Jeffrey P.; Nayal, Narendra; Yadav, Anju; Srivastava, Anil; Haydon, David J.

2013-01-01

The bacterial cell division protein FtsZ is an attractive target for small-molecule antibacterial drug discovery. Derivatives of 3-methoxybenzamide, including compound PC190723, have been reported to be potent and selective antistaphylococcal agents which exert their effects through the disruption of intracellular FtsZ function. Here, we report the further optimization of 3-methoxybenzamide derivatives towards a drug candidate. The in vitro and in vivo characterization of a more advanced lead compound, designated compound 1, is described. Compound 1 was potently antibacterial, with an average MIC of 0.12 μg/ml against all staphylococcal species, including methicillin- and multidrug-resistant Staphylococcus aureus and Staphylococcus epidermidis. Compound 1 inhibited an S. aureus strain carrying the G196A mutation in FtsZ, which confers resistance to PC190723. Like PC190723, compound 1 acted on whole bacterial cells by blocking cytokinesis. No interactions between compound 1 and a diverse panel of antibiotics were measured in checkerboard experiments. Compound 1 displayed suitable in vitro pharmaceutical properties and a favorable in vivo pharmacokinetic profile following intravenous and oral administration, with a calculated bioavailability of 82.0% in mice. Compound 1 demonstrated efficacy in a murine model of systemic S. aureus infection and caused a significant decrease in the bacterial load in the thigh infection model. A greater reduction in the number of S. aureus cells recovered from infected thighs, equivalent to 3.68 log units, than in those recovered from controls was achieved using a succinate prodrug of compound 1, which was designated compound 2. In summary, optimized derivatives of 3-methoxybenzamide may yield a first-in-class FtsZ inhibitor for the treatment of antibiotic-resistant staphylococcal infections. PMID:23114779

Anticancer activity of seaweeds.

PubMed

Gutiérrez-Rodríguez, Anllely G; Juárez-Portilla, Claudia; Olivares-Bañuelos, Tatiana; Zepeda, Rossana C

2018-02-01

Cancer is a major health problem worldwide and still lacks fully effective treatments. Therefore, alternative therapies, using natural products, have been proposed. Marine algae are an important component of the marine environment, with high biodiversity, and contain a huge number of functional compounds, including terpenes, polyphenols, phlorotannins, and polysaccharides, among others. These compounds have complex structures that have shown several biological activities, including anticancer activity, using in vitro and in vivo models. Moreover, seaweed-derived compounds target important molecules that regulate cancer processes. Here, we review our current understanding of the anticancer activity of seaweeds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Recent trends in the development of nanophytobioactive compounds and delivery systems for their possible role in reducing oxidative stress in Parkinson's disease models.

PubMed

Ganesan, Palanivel; Ko, Hyun-Myung; Kim, In-Su; Choi, Dong-Kug

2015-01-01

Oxidative stress plays a very critical role in neurodegenerative diseases, such as Parkinson's disease (PD), which is the second most common neurodegenerative disease among elderly people worldwide. Increasing evidence has suggested that phytobioactive compounds show enhanced benefits in cell and animal models of PD. Curcumin, resveratrol, ginsenosides, quercetin, and catechin are phyto-derived bioactive compounds with important roles in the prevention and treatment of PD. However, in vivo studies suggest that their concentrations are very low to cross blood-brain barrier thereby it limits bioavailability, stability, and dissolution at target sites in the brain. To overcome these problems, nanophytomedicine with the controlled size of 1-100 nm is used to maximize efficiency in the treatment of PD. Nanosizing of phytobioactive compounds enhances the permeability into the brain with maximized efficiency and stability. Several nanodelivery techniques, including solid lipid nanoparticles, nanostructured lipid carriers, nanoliposomes, and nanoniosomes can be used for controlled delivery of nanobioactive compounds to brain. Nanocompounds, such as ginsenosides (19.9 nm) synthesized using a nanoemulsion technique, showed enhanced bioavailability in the rat brain. Here, we discuss the most recent trends and applications in PD, including 1) the role of phytobioactive compounds in reducing oxidative stress and their bioavailability; 2) the role of nanotechnology in reducing oxidative stress during PD; 3) nanodelivery systems; and 4) various nanophytobioactive compounds and their role in PD.

Identifying natural compounds as multi-target-directed ligands against Alzheimer's disease: an in silico approach.

PubMed

Ambure, Pravin; Bhat, Jyotsna; Puzyn, Tomasz; Roy, Kunal

2018-04-23

Alzheimer's disease (AD) is a multi-factorial disease, which can be simply outlined as an irreversible and progressive neurodegenerative disorder with an unclear root cause. It is a major cause of dementia in old aged people. In the present study, utilizing the structural and biological activity information of ligands for five important and mostly studied vital targets (i.e. cyclin-dependant kinase 5, β-secretase, monoamine oxidase B, glycogen synthase kinase 3β, acetylcholinesterase) that are believed to be effective against AD, we have developed five classification models using linear discriminant analysis (LDA) technique. Considering the importance of data curation, we have given more attention towards the chemical and biological data curation, which is a difficult task especially in case of big data-sets. Thus, to ease the curation process we have designed Konstanz Information Miner (KNIME) workflows, which are made available at http://teqip.jdvu.ac.in/QSAR_Tools/ . The developed models were appropriately validated based on the predictions for experiment derived data from test sets, as well as true external set compounds including known multi-target compounds. The domain of applicability for each classification model was checked based on a confidence estimation approach. Further, these validated models were employed for screening of natural compounds collected from the InterBioScreen natural database ( https://www.ibscreen.com/natural-compounds ). Further, the natural compounds that were categorized as 'actives' in at least two classification models out of five developed models were considered as multi-target leads, and these compounds were further screened using the drug-like filter, molecular docking technique and then thoroughly analyzed using molecular dynamics studies. Finally, the most potential multi-target natural compounds against AD are suggested.

Isolation and Quantification of Ginsenoside Rh23, a New Anti-Melanogenic Compound from the Leaves of Panax ginseng.

PubMed

Lee, Dae Young; Kim, Hyoung-Geun; Lee, Yeong-Geun; Kim, Jin Hee; Lee, Jae Won; Choi, Bo-Ram; Jang, In-Bae; Kim, Geum-Soog; Baek, Nam-In

2018-01-29

A new ginsenoside, named ginsenoside Rh23 ( 1 ), and 20- O -β-d-glucopyranosyl-3β,6α,12β,20β,25-pentahydroxydammar-23-ene ( 2 ) were isolated from the leaves of hydroponic Panax ginseng . Compounds were isolated by various column chromatography and their structures were determined based on spectroscopic methods, including high resolution quadrupole/time of flight mass spectrometry (HR-QTOF/MS), nuclear magnetic resonance (NMR) spectroscopy, and infrared (IR) spectroscopy. To determine anti-melanogenic activity, the change in the melanin content in melan-a cells treated with identified compounds was tested. Additionally, we investigated the melanin inhibitory effects of ginsenoside Rh23 on pigmentation in a zebrafish in vivo model. Compound 1 inhibited potent melanogenesis in melan-a cells with 37.0% melanogenesis inhibition at 80 µM and also presented inhibition on the body pigmentation in zebrafish model. Although compound 2 showed slightly lower inhibitory activity than compound 1 , it also showed significantly decreased melanogenesis in melan-a cell and in zebrafish model. These results indicated that compounds isolated from hydroponic P. ginseng may be used as new skin whitening compound through the in vitro and in vivo systems. Furthermore, this study demonstrated the utility of MS-based compound 1 for the quantitative analysis. Ginsenoside Rh23 ( 1 ) was found at a level of 0.31 mg/g in leaves of hydroponic P. ginseng .

Quantitative prediction of solvation free energy in octanol of organic compounds.

PubMed

Delgado, Eduardo J; Jaña, Gonzalo A

2009-03-01

The free energy of solvation, DeltaGS0, in octanol of organic compounds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a DeltaGS0 range from about -50 to 0 kJ.mol(-1). The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ.mol(-1), just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set.

Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.

PubMed

Soto, Fabian A; Gershman, Samuel J; Niv, Yael

2014-07-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here, we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed long-standing problems for rational theories of associative and causal learning. (c) 2014 APA, all rights reserved.

Explaining Compound Generalization in Associative and Causal Learning Through Rational Principles of Dimensional Generalization

PubMed Central

Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael

2014-01-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates.

PubMed

Focks, Andreas; Belgers, Dick; Boerwinkel, Marie-Claire; Buijse, Laura; Roessink, Ivo; Van den Brink, Paul J

2018-05-01

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

Autoignition Studies of Diesel Alternative Biofuels

NASA Astrophysics Data System (ADS)

Wang, Weijing

The autoignition of biofuel compounds that offer potential as diesel fuel alternatives was studied under high-pressure engine-like conditions using the shock tube technique. Ignition delay times were determined in reflected shock experiments using measured pressure and electronically-excited OH emission. Measurements were made at conditions ranging from 650 to 1350 K, pressures from 6 to 50 atm, and for fuel/air/diluent mixtures at equivalence ratios from 0.5 to 2. The wide range of temperatures examined provides observation of autoignition in three reactivity regimes, including the negative temperature coefficient (NTC) regime which is characteristic of fuels containing alkyl functionalities. Compounds studied include biodiesel-related compounds and real biodiesel fuels, dimethyl ether, and 3-methylheptane which is representative of compounds found in synthetic diesel fuels produced using the Fischer-Tropsch and hydrotreatment processes. Biodiesel compounds studied include biodiesel surrogates, methyl decanoate, methyl-5-decenoate, and methyl-9-decenoate; compounds found in large quantities in biodiesels, methyl palmitate, methyl stearate, methyl oleate, and methyl linoleate; and soy-based and animal fat based methyl ester biodiesels. Comparison of biodiesel compounds illustrates the influence of molecular structure (e.g., chain length, double bonds, and ester functionality) on reactivity. For methyl decanoate, the effect of high pressure exhaust gas recirculation (EGR) conditions relevant to internal combustion engines was also determined. Results showed that the first-order influence of EGR by displacing fuel and O2 to decrease radical branching. Measurements were compared to kinetic modeling results from models available in the literature providing varying degrees of model validation. Reaction flux analyses were also carried out to further examine the kinetic differences in different temperature regimes for fuel compounds. For example, reaction flux analyses illustrates the importance of the long alkyl chain in controlling the overall reactivity of methyl ester biodiesel compounds and the subtle role the ester group has on inhibiting low-temperature reactivity as well as the influence of branching on reactivity for lightly branched alkanes. This thesis work provides a rich database of kinetic information for biofuel-related compounds at conditions relevant to real engine operations, offering quantitative kinetic targets for the development and evaluation of future kinetic models for important alternative fuel compounds. The results quantify the reactivity variability of biodiesel alternatives and illustrate that at temperature greater than 900 to 1000 K fuel structure has little influence on reactivity, as fuel fragmentation results in an intermediate pool that is largely the same for the fuels studied. On the other hand at temperature lower than 900 K, where fuel-specific low-temperature chemistry plays a role, different fuel structures can result in vast differences in reactivity, up to factors of three or more in ignition delay.

Structural basis for the enhanced stability of protein model compounds and peptide backbone unit in ammonium ionic liquids.

PubMed

Vasantha, T; Attri, Pankaj; Venkatesu, Pannuru; Devi, R S Rama

2012-10-04

Protein folding/unfolding is a fascinating study in the presence of cosolvents, which protect/disrupt the native structure of protein, respectively. The structure and stability of proteins and their functional groups may be modulated by the addition of cosolvents. Ionic liquids (ILs) are finding a vast array of applications as novel cosolvents for a wide variety of biochemical processes that include protein folding. Here, the systematic and quantitative apparent transfer free energies (ΔG'(tr)) of protein model compounds from water to ILs through solubility measurements as a function of IL concentration at 25 °C have been exploited to quantify and interpret biomolecular interactions between model compounds of glycine peptides (GPs) with ammonium based ILs. The investigated aqueous systems consist of zwitterionic glycine peptides: glycine (Gly), diglycine (Gly(2)), triglycine (Gly(3)), tetraglycine (Gly(4)), and cyclic glycylglycine (c(GG)) in the presence of six ILs such as diethylammonium acetate (DEAA), diethylammonium hydrogen sulfate (DEAS), triethylammonium acetate (TEAA), triethylammonium hydrogen sulfate (TEAS), triethylammonium dihydrogen phosphate (TEAP), and trimethylammonium acetate (TMAA). We have observed positive values of ΔG'(tr) for GPs from water to ILs, indicating that interactions between ILs and GPs are unfavorable, which leads to stabilization of the structure of model protein compounds. Moreover, our experimental data ΔG'(tr) is used to obtain transfer free energies (Δg'(tr)) of the peptide backbone unit (or glycyl unit) (-CH(2)C═ONH-), which is the most numerous group in globular proteins, from water to IL solutions. To obtain the mechanism events of the ILs' role in enhancing the stability of the model compounds, we have further obtained m-values for GPs from solubility limits. These results explicitly elucidate that all alkyl ammonium ILs act as stabilizers for model compounds through the exclusion of ILs from model compounds of proteins and also reflect the effect of alkyl chain on the stability of protein model compounds.

Evaluation of Biogenic and Fire Emissions in a Global Chemistry Model with NOMADSS, DC3 and SEAC4RS observations

NASA Astrophysics Data System (ADS)

Emmons, L. K.; Wiedinmyer, C.; Park, M.; Kaser, L.; Apel, E. C.; Guenther, A. B.

2014-12-01

Numerous measurements of compounds produced by biogenic and fire emissions were made during several recent field campaigns in the southeast United States, providing a unique data set for emissions and chemical model evaluation. The NCAR Community Atmosphere Model with Chemistry (CAM-chem) is coupled to the Community Land Model (CLM), which includes the biogenic emissions model MEGAN-v2.1, allowing for online calculation of emissions from vegetation for 150 compounds. Simulations of CAM-chem for summers 2012 and 2013 are evaluated with the aircraft and ground-based observations from DC3, NOMADSS and SEAC4RS. Comparison of directly emitted biogenic species, such as isoprene, terpenes, methanol and acetone, are used to evaluate the MEGAN emissions. Evaluation of oxidation products, including methyl vinyl ketone (MVK), methacrolein, formaldehyde, and other oxygenated VOCs are used to test the model chemistry mechanism. In addition, several biomass burning inventories are used in the model, including FINN, QFED, and FLAMBE, and are compared for their impact on atmospheric composition and ozone production, and evaluated with the aircraft observations.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Synthesis, Structural Studies and Biological Evaluation of Connections of Thiosemicarbazide, 1,2,4-Triazole and 1,3,4-Thiadiazole with Palmitic Acid.

PubMed

Jóźwiak, Michał; Stępień, Karolina; Wrzosek, Małgorzata; Olejarz, Wioletta; Kubiak-Tomaszewska, Grażyna; Filipowska, Anna; Filipowski, Wojciech; Struga, Marta

2018-04-03

Thirty new derivatives of palmitic acid were efficiently synthesized. All obtained compounds can be divided into three groups of derivatives: Thiosemicarbazides (compounds 1 - 10 ), 1,2,4-triazoles (compounds 1a - 10a ) and 1,3,4-thiadiazoles (compounds 1b - 10b ) moieties. ¹H-NMR, 13 C-NMR and MS methods were used to confirm the structure of derivatives. All obtained compounds were tested in vitro against a number of microorganisms, including Gram-positive cocci, Gram-negative rods and Candida albicans . Compounds 4 , 5 , 6 , 8 showed significant inhibition against C. albicans . The range of MIC values was 50-1.56 μg/mL. The halogen atom, especially at the 3rd position of the phenyl group was significantly important for antifungal activity. The biological activity against Candida albicans and selected molecular descriptors were used as a basis for QSAR models, that have been determined by means of multiple linear regression. The models have been validated by means of the Leave-One-Out Cross Validation. The obtained QSAR models were characterized by high determination coefficients and good prediction power.

Microwave-assisted chemical pre-treatment of waste sorghum leaves: Process optimization and development of an intelligent model for determination of volatile compound fractions.

PubMed

Rorke, Daneal C S; Suinyuy, Terence N; Gueguim Kana, E B

2017-01-01

This study reports the profiling of volatile compounds generated during microwave-assisted chemical pre-treatment of sorghum leaves. Compounds including acetic acid (0-186.26ng/g SL), furfural (0-240.80ng/g SL), 5-hydroxymethylfurfural (HMF) (0-19.20ng/g SL) and phenol (0-7.76ng/g SL) were detected. The reducing sugar production was optimized. An intelligent model based on Artificial Neural Networks (ANNs) was developed and validated to predict a profile of 21 volatile compounds under novel pre-treatment conditions. This model gave R 2 -values of up to 0.93. Knowledge extraction revealed furfural and phenol exhibited high sensitivity to acid- and alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity. Furthermore, furfural production was majorly dependent on acid concentration and fit a dosage-response relationship model with a 2.5% HCl threshold. Significant non-linearities were observed between pre-treatment conditions and the profile of various compounds. This tool reduces analytical costs through virtual analytical instrumentation, improving process economics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.

PubMed

Chen, Meimei; Yang, Fafu; Kang, Jie; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

2016-11-29

In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.

Impact of aromatics and monoterpenes on simulated tropospheric ozone and total OH reactivity

NASA Astrophysics Data System (ADS)

Porter, William C.; Safieddine, Sarah A.; Heald, Colette L.

2017-11-01

The accurate representation of volatile organic compounds (VOCs) in models is an important step towards the goal of understanding and predicting many changes in atmospheric constituents relevant to climate change and human health. While isoprene is the most abundant non-methane VOC, many other compounds play a large role in governing pollutant formation and the overall oxidative capacity of the atmosphere. We quantify the impacts of aromatics and monoterpenes, two classes of VOC not included in the standard gas-phase chemistry of the chemical transport model GEOS-Chem, on atmospheric composition. We find that including these compounds increases mean total summer OH reactivity by an average of 11% over the United States, Europe, and Asia. This increased reactivity results in higher simulated levels of O3, raising maximum daily 8-h average O3 in the summer by up to 14 ppb at some NOx-saturated locations.

Advanced waste management technology evaluation

NASA Technical Reports Server (NTRS)

Couch, H.; Birbara, P.

1996-01-01

The purpose of this program is to evaluate the feasibility of steam reforming spacecraft wastes into simple recyclable inorganic salts, carbon dioxide and water. Model waste compounds included cellulose, urea, methionine, Igapon TC-42, and high density polyethylenes. These are compounds found in urine, feces, hygiene water, etc. The gasification and steam reforming process used the addition of heat and low quantities of oxygen to oxidize and reduce the model compounds.The studied reactions were aimed at recovery of inorganic residues that can be recycled into a closed biologic system. Results indicate that even at very low concentrations of oxygen (less than 3%) the formation of a carbonaceous residue was suppressed. The use of a nickel/cobalt reforming catalyst at reaction temperature of 1600 degrees yielded an efficient destruction of the organic effluents, including methane and ammonia. Additionally, the reforming process with nickel/cobalt catalyst diminished the noxious odors associated with butyric acid, methionine and plastics.

Synthesis, biological evaluation and molecular modeling of novel series of pyridine derivatives as anticancer, anti-inflammatory and analgesic agents

NASA Astrophysics Data System (ADS)

Helal, M. H.; El-Awdan, S. A.; Salem, M. A.; Abd-elaziz, T. A.; Moahamed, Y. A.; El-Sherif, A. A.; Mohamed, G. A. M.

2015-01-01

This paper presents a combined synthesis; characterization, computational and biological activity studies of novel series of pyridines heterocyclic compounds. The compounds have been characterized by elemental analyses and spectral like IR, 1H NMR, 13C NMR and MS studies. Michael addition of substituted-2-methoxycarbonylacetanilide 2a,b on the α-substituted cinnamonitriles 3a-d gave the corresponding 2-pyridone derivatives 5-10. Structures of the titled compounds cited in this article were elucidated by spectrometric data (IR, 1H NMR, 13C NMR and MS). The molecular modeling of the synthesized compounds has been drawn and their molecular parameters were calculated. Also, valuable information is obtained from the calculation of molecular parameters including electronegativity, net dipole moment of the compounds, total energy, electronic energy, binding energy, HOMO and LUMO energy. Various in vitro antitumor as well as in vivo anti-inflammatory and analgesic activities of the synthesized compounds were investigated. Evaluation of anti-inflammatory activity of test compounds was performed using carrageenan induced paw edema in rats. All the tested compounds showed moderate to good activity. The SAR results indicate that all compounds showed moderate to good activity, among these 7 and 10 compounds having -N(CH3)2 group are most effective.

QSAR models for degradation of organic pollutants in ozonation process under acidic condition.

PubMed

Zhu, Huicen; Guo, Weimin; Shen, Zhemin; Tang, Qingli; Ji, Wenchao; Jia, Lijuan

2015-01-01

Although some researches about the degradation of organic pollutants have been carried out during recent years, reaction rate constants are available only for homologue compounds with similar structures or components. Therefore, it is of great significance to find a universal relationship between reaction rate and certain parameters of several diverse organic pollutants. In this study, removal ratio and kinetics of 33 kinds of organic substances were investigated by ozonation process, including azo dyes, heterocyclic compounds, ionic compounds and so on. Most quantum chemical parameters were conducted by using Gaussian 09 at the DFT B3LYP/6-311G level, including μ, q H(+), q(C)minq(C)max, ELUMO and EHOMO. Other descriptors, bond order (BO) as well as Fukui indices (f(+), f(-) and f(0)), were calculated by Material Studio 6.1 at Dmol(3)/GGA-BLYP/DNP(3.5) basis for each organic compound. The recommended model for predicting rate constants was lnk'=1.978-95.484f(0)x-3.350q(C)min+38.221f(+)x, which had the squared regression coefficient R(2)=0.763 and standard deviation SD=0.716. The results of t test and the Fisher test suggested that the model exhibited optimum stability. Also, the model was validated by internal and external validations. Recommended QSAR model showed that the highest f(0) value of main-chain carbons (f(0)x) is more closely related to lnk' than other quantum descriptors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Recent trends in the development of nanophytobioactive compounds and delivery systems for their possible role in reducing oxidative stress in Parkinson’s disease models

PubMed Central

Ganesan, Palanivel; Ko, Hyun-Myung; Kim, In-Su; Choi, Dong-Kug

2015-01-01

Oxidative stress plays a very critical role in neurodegenerative diseases, such as Parkinson’s disease (PD), which is the second most common neurodegenerative disease among elderly people worldwide. Increasing evidence has suggested that phytobioactive compounds show enhanced benefits in cell and animal models of PD. Curcumin, resveratrol, ginsenosides, quercetin, and catechin are phyto-derived bioactive compounds with important roles in the prevention and treatment of PD. However, in vivo studies suggest that their concentrations are very low to cross blood–brain barrier thereby it limits bioavailability, stability, and dissolution at target sites in the brain. To overcome these problems, nanophytomedicine with the controlled size of 1–100 nm is used to maximize efficiency in the treatment of PD. Nanosizing of phytobioactive compounds enhances the permeability into the brain with maximized efficiency and stability. Several nanodelivery techniques, including solid lipid nanoparticles, nanostructured lipid carriers, nanoliposomes, and nanoniosomes can be used for controlled delivery of nanobioactive compounds to brain. Nanocompounds, such as ginsenosides (19.9 nm) synthesized using a nanoemulsion technique, showed enhanced bioavailability in the rat brain. Here, we discuss the most recent trends and applications in PD, including 1) the role of phytobioactive compounds in reducing oxidative stress and their bioavailability; 2) the role of nanotechnology in reducing oxidative stress during PD; 3) nanodelivery systems; and 4) various nanophytobioactive compounds and their role in PD. PMID:26604750

Catalytic Upgrading of Biomass Pyrolysis Oxygenates with Vacuum Gas Oil Using a Davison Circulating Riser Reactor

DOE PAGES

Jarvis, Mark W.; Olstad, Jessica; Parent, Yves; ...

2018-01-02

We investigate and quantitate the changes in hydrocarbon product composition while evaluating the performance and operability of the National Renewable Energy Laboratory's Davison Circulating Riser (DCR) reactor system when biomass model compounds are cofed with traditional fluid catalyst cracking (FCC) feeds and catalyst: vacuum gas oil (VGO) and equilibrium zeolite catalyst (E-Cat). Three compounds (acetic acid, guaiacol, and sorbitan monooleate) were selected to represent the major classes of oxygenates present in biomass pyrolysis vapors. These vapors can contain 30-50% oxygen as oxygenates, which create conversion complications (increased reactivity and coking) when integrating biomass vapors and liquids into fuel and chemicalmore » processes long dominated by petroleum feedstocks. We used these model compounds to determine the appropriate conditions for coprocessing with petroleum and ultimately pure pyrolysis vapors only as compared with standard baseline conditions obtained with VGO and E-Cat only in the DCR. Model compound addition decreased the DCR catalyst circulation rate, which controls reactor temperature and measures reaction heat demand, while increasing catalyst coking rates. Liquid product analyses included 2-dimensional gas chromatography time-of-flight mass spectroscopy (2D GCxGC TOFS), simulated distillation (SIM DIST), 13C NMR, and carbonyl content. Aggregated results indicated that the model compounds were converted during reaction, and despite functional group differences, product distributions for each model compound were very similar. In addition, we determined that adding model compounds to the VGO feed did not significantly affect the DCR's operability or performance. Future work will assess catalytic upgrading of biomass pyrolysis vapor to fungible hydrocarbon products using upgrading catalysts currently being developed at NREL and at Johnson Matthey.« less

Catalytic Upgrading of Biomass Pyrolysis Oxygenates with Vacuum Gas Oil Using a Davison Circulating Riser Reactor

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

Jarvis, Mark W.; Olstad, Jessica; Parent, Yves

We investigate and quantitate the changes in hydrocarbon product composition while evaluating the performance and operability of the National Renewable Energy Laboratory's Davison Circulating Riser (DCR) reactor system when biomass model compounds are cofed with traditional fluid catalyst cracking (FCC) feeds and catalyst: vacuum gas oil (VGO) and equilibrium zeolite catalyst (E-Cat). Three compounds (acetic acid, guaiacol, and sorbitan monooleate) were selected to represent the major classes of oxygenates present in biomass pyrolysis vapors. These vapors can contain 30-50% oxygen as oxygenates, which create conversion complications (increased reactivity and coking) when integrating biomass vapors and liquids into fuel and chemicalmore » processes long dominated by petroleum feedstocks. We used these model compounds to determine the appropriate conditions for coprocessing with petroleum and ultimately pure pyrolysis vapors only as compared with standard baseline conditions obtained with VGO and E-Cat only in the DCR. Model compound addition decreased the DCR catalyst circulation rate, which controls reactor temperature and measures reaction heat demand, while increasing catalyst coking rates. Liquid product analyses included 2-dimensional gas chromatography time-of-flight mass spectroscopy (2D GCxGC TOFS), simulated distillation (SIM DIST), 13C NMR, and carbonyl content. Aggregated results indicated that the model compounds were converted during reaction, and despite functional group differences, product distributions for each model compound were very similar. In addition, we determined that adding model compounds to the VGO feed did not significantly affect the DCR's operability or performance. Future work will assess catalytic upgrading of biomass pyrolysis vapor to fungible hydrocarbon products using upgrading catalysts currently being developed at NREL and at Johnson Matthey.« less

Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

PubMed

Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

2013-08-01

To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

Polyphenolic compounds with antioxidant potential and neuro-protective effect from Cimicifuga dahurica (Turcz.) Maxim.

PubMed

Qin, Rulan; Zhao, Ying; Zhao, Yudan; Zhou, Wanrong; Lv, Chongning; Lu, Jincai

2016-12-01

Three new phenolic compounds (1-3), along with five known compounds (4-8) were isolated from the rhizome of Cimicifuga dahurica (Turcz.) Maxim. Their structures were elucidated by spectroscopic methods including 1D-NMR, 2D-NMR and HR-MS techniques. DPPH method and protective effect on PC12 cells against H 2 O 2 -induced oxidative damage model were carried to evaluate the antioxidant capability of these compounds. Compound 5 showed significant antioxidant activity with IC 50 values 9.33μM in DPPH assay and compound 2 displayed marked neuro-protective effect with 87.65% cell viability at the concentration of 10μM. Additionally, the possible structure-activity relationships of these phenolic compounds were tentatively discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling of adipose/blood partition coefficient for environmental chemicals.

PubMed

Papadaki, K C; Karakitsios, S P; Sarigiannis, D A

2017-12-01

A Quantitative Structure Activity Relationship (QSAR) model was developed in order to predict the adipose/blood partition coefficient of environmental chemical compounds. The first step of QSAR modeling was the collection of inputs. Input data included the experimental values of adipose/blood partition coefficient and two sets of molecular descriptors for 67 organic chemical compounds; a) the descriptors from Linear Free Energy Relationship (LFER) and b) the PaDEL descriptors. The datasets were split to training and prediction set and were analysed using two statistical methods; Genetic Algorithm based Multiple Linear Regression (GA-MLR) and Artificial Neural Networks (ANN). The models with LFER and PaDEL descriptors, coupled with ANN, produced satisfying performance results. The fitting performance (R 2 ) of the models, using LFER and PaDEL descriptors, was 0.94 and 0.96, respectively. The Applicability Domain (AD) of the models was assessed and then the models were applied to a large number of chemical compounds with unknown values of adipose/blood partition coefficient. In conclusion, the proposed models were checked for fitting, validity and applicability. It was demonstrated that they are stable, reliable and capable to predict the values of adipose/blood partition coefficient of "data poor" chemical compounds that fall within the applicability domain. Copyright © 2017. Published by Elsevier Ltd.

INTERCOMPARISON OF ALTERNATIVE VEGETATION DATABASES FOR REGIONAL AIR QUALITY MODELING

EPA Science Inventory

Vegetation cover data are used to characterize several regional air quality modeling processes, including the calculation of heat, moisture, and momentum fluxes with the Mesoscale Meteorological Model (MM5) and the estimate of biogenic volatile organic compound and nitric oxide...

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

Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh

NASA Astrophysics Data System (ADS)

Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro

2017-08-01

Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global-scale or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

Sensitivity of Aerosol Mass and Microphysics to varying treatments of Condensational Growth of Secondary Organic Compounds in a regional model

NASA Astrophysics Data System (ADS)

Lowe, Douglas; Topping, David; McFiggans, Gordon

2017-04-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight. For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin VBS treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organics compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased. This work was supported by the Natural Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Sensitivity of Aerosol Mass and Microphysics to Treatments of Condensational Growth of Secondary Organic Compounds in a Regional Model

NASA Astrophysics Data System (ADS)

Topping, D. O.; Lowe, D.; McFiggans, G.; Zaveri, R. A.

2016-12-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight.For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin volatility basis set (VBS) treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organic compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased.This work was supported by the Nature Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Mathematical modeling of atmospheric fine particle-associated primary organic compound concentrations

NASA Astrophysics Data System (ADS)

Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

1996-08-01

An atmospheric transport model has been used to explore the relationship between source emissions and ambient air quality for individual particle phase organic compounds present in primary aerosol source emissions. An inventory of fine particulate organic compound emissions was assembled for the Los Angeles area in the year 1982. Sources characterized included noncatalyst- and catalyst-equipped autos, diesel trucks, paved road dust, tire wear, brake lining dust, meat cooking operations, industrial oil-fired boilers, roofing tar pots, natural gas combustion in residential homes, cigarette smoke, fireplaces burning oak and pine wood, and plant leaf abrasion products. These primary fine particle source emissions were supplied to a computer-based model that simulates atmospheric transport, dispersion, and dry deposition based on the time series of hourly wind observations and mixing depths. Monthly average fine particle organic compound concentrations that would prevail if the primary organic aerosol were transported without chemical reaction were computed for more than 100 organic compounds within an 80 km × 80 km modeling area centered over Los Angeles. The monthly average compound concentrations predicted by the transport model were compared to atmospheric measurements made at monitoring sites within the study area during 1982. The predicted seasonal variation and absolute values of the concentrations of the more stable compounds are found to be in reasonable agreement with the ambient observations. While model predictions for the higher molecular weight polycyclic aromatic hydrocarbons (PAH) are in agreement with ambient observations, lower molecular weight PAH show much higher predicted than measured atmospheric concentrations in the particle phase, indicating atmospheric decay by chemical reactions or evaporation from the particle phase. The atmospheric concentrations of dicarboxylic acids and aromatic polycarboxylic acids greatly exceed the contributions that are due to direct emissions from primary sources, confirming that these compounds are principally formed by atmospheric chemical reactions.

PHYSIOLOGICALLY-BASED PHARMACOKINETIC ( PBPK ) MODEL FOR METHYL TERTIARY BUTYL ETHER ( MTBE ): A REVIEW OF EXISTING MODELS

EPA Science Inventory

MTBE is a volatile organic compound used as an oxygenate additive to gasoline, added to comply with the 1990 Clean Air Act. Previous PBPK models for MTBE were reviewed and incorporated into the Exposure Related Dose Estimating Model (ERDEM) software. This model also included an e...

Polycyclic aromatic hydrocarbons - fate and long-range atmospheric transport studied using a global model, EMAC-SVOC

NASA Astrophysics Data System (ADS)

Octaviani, Mega; Tost, Holger; Lammel, Gerhard

2017-04-01

Polycyclic aromatic hydrocarbons (PAHs) are emitted by incomplete combustion from fossil fuel, vehicles, and biomass burning. They may persist in environmental compartments, pose a health hazard and may bio accumulate along food chains. The ECHAM/MESSy Atmospheric Chemistry (EMAC) model had been used to simulate global tropospheric, stratospheric chemistry and climate. In this study, we improve the model to include simulations of the transport and fate of semi-volatile organic compounds (SVOC). The EMAC-SVOC model takes into account essential environmental processes including gas-particle partitioning, dry and wet deposition, chemical and bio-degradation, and volatilization from sea surface, soils, vegetation, and snow. The model was evaluated against observational data in the Arctic, mid-latitudes, and tropics, and further applied to study total environmental lifetime and long-range transport potential (LRTP) of PAHs. We selected four compounds for study, spanning a wide range of volatility, i.e., phenanthrene, fluoranthene, pyrene, and benzo[a]pyrene. Several LRTP indicators were investigated, including the Arctic contamination potential, meridional spreading, and zonal and meridional fluxes to remote regions.

2 H-fractionations during the biosynthesis of carbohydrates and lipids imprint a metabolic signal on the δ2 H values of plant organic compounds.

PubMed

Cormier, Marc-André; Werner, Roland A; Sauer, Peter E; Gröcke, Darren R; Leuenberger, Markus C; Wieloch, Thomas; Schleucher, Jürgen; Kahmen, Ansgar

2018-04-01

Hydrogen (H) isotope ratio (δ 2 H) analyses of plant organic compounds have been applied to assess ecohydrological processes in the environment despite a large part of the δ 2 H variability observed in plant compounds not being fully elucidated. We present a conceptual biochemical model based on empirical H isotope data that we generated in two complementary experiments that clarifies a large part of the unexplained variability in the δ 2 H values of plant organic compounds. The experiments demonstrate that information recorded in the δ 2 H values of plant organic compounds goes beyond hydrological signals and can also contain important information on the carbon and energy metabolism of plants. Our model explains where 2 H-fractionations occur in the biosynthesis of plant organic compounds and how these 2 H-fractionations are tightly coupled to a plant's carbon and energy metabolism. Our model also provides a mechanistic basis to introduce H isotopes in plant organic compounds as a new metabolic proxy for the carbon and energy metabolism of plants and ecosystems. Such a new metabolic proxy has the potential to be applied in a broad range of disciplines, including plant and ecosystem physiology, biogeochemistry and palaeoecology. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

From Omics to Drug Metabolism and High Content Screen of Natural Product in Zebrafish: A New Model for Discovery of Neuroactive Compound

PubMed Central

Hung, Ming Wai; Zhang, Zai Jun; Li, Shang; Lei, Benson; Yuan, Shuai; Cui, Guo Zhen; Man Hoi, Pui; Chan, Kelvin; Lee, Simon Ming Yuen

2012-01-01

The zebrafish (Danio rerio) has recently become a common model in the fields of genetics, environmental science, toxicology, and especially drug screening. Zebrafish has emerged as a biomedically relevant model for in vivo high content drug screening and the simultaneous determination of multiple efficacy parameters, including behaviour, selectivity, and toxicity in the content of the whole organism. A zebrafish behavioural assay has been demonstrated as a novel, rapid, and high-throughput approach to the discovery of neuroactive, psychoactive, and memory-modulating compounds. Recent studies found a functional similarity of drug metabolism systems in zebrafish and mammals, providing a clue with why some compounds are active in zebrafish in vivo but not in vitro, as well as providing grounds for the rationales supporting the use of a zebrafish screen to identify prodrugs. Here, we discuss the advantages of the zebrafish model for evaluating drug metabolism and the mode of pharmacological action with the emerging omics approaches. Why this model is suitable for identifying lead compounds from natural products for therapy of disorders with multifactorial etiopathogenesis and imbalance of angiogenesis, such as Parkinson's disease, epilepsy, cardiotoxicity, cerebral hemorrhage, dyslipidemia, and hyperlipidemia, is addressed. PMID:22919414

Comprehensive atmospheric modeling of reactive cyclic siloxanes and their oxidation products

NASA Astrophysics Data System (ADS)

Janechek, Nathan J.; Hansen, Kaj M.; Stanier, Charles O.

2017-07-01

Cyclic volatile methyl siloxanes (cVMSs) are important components in personal care products that transport and react in the atmosphere. Octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5), dodecamethylcyclohexasiloxane (D6), and their gas-phase oxidation products have been incorporated into the Community Multiscale Air Quality (CMAQ) model. Gas-phase oxidation products, as the precursor to secondary organic aerosol from this compound class, were included to quantify the maximum potential for aerosol formation from gas-phase reactions with OH. Four 1-month periods were modeled to quantify typical concentrations, seasonal variability, spatial patterns, and vertical profiles. Typical model concentrations showed parent compounds were highly dependent on population density as cities had monthly averaged peak D5 concentrations up to 432 ng m-3. Peak oxidized D5 concentrations were significantly less, up to 9 ng m-3, and were located downwind of major urban areas. Model results were compared to available measurements and previous simulation results. Seasonal variation was analyzed and differences in seasonal influences were observed between urban and rural locations. Parent compound concentrations in urban and peri-urban locations were sensitive to transport factors, while parent compounds in rural areas and oxidized product concentrations were influenced by large-scale seasonal variability in OH.

Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

DOE PAGES

Das, Dhrubajyoti D.; St. John, Peter C.; McEnally, Charles S.; ...

2017-12-27

Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveragingmore » the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.« less

Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

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

Das, Dhrubajyoti D.; St. John, Peter C.; McEnally, Charles S.

Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveragingmore » the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.« less

[Discovery of potential LXRβ agonists from Chinese herbs using molecular simulation methods].

PubMed

Luo, Gang-Gang; Lu, Fang; Qiao, Lian-Sheng; Li, Yong; Zhang, Yan-Ling

2016-08-01

Liver X receptor β (LXRβ) has been a new target in the treatment of hyperlipemia, which was related to the cholesterol homeostasis. In this study, the quantitative pharmacophores were constructed by 3D-QSAR pharmacophore (Hypogen) method based on the LXRβ agonists. The optimal pharmacophore model containing one hydrogen bond acceptor, two hydrophobics and one ring aromatic was obtained based on five assessment indictors, including the correlation between predicted value and experimental value of the compounds in training set (correlation), Δcost of the models (Δcost), hit rate of active compounds (HRA), identification of effectiveness index (IEI) and comprehensive evaluation index (CAI). And the values of the five assessment indicators were 0.95, 128.65, 84.44%, 2.58 and 2.18 respectively. The best model as a query to screen the traditional Chinese medicine database (TCMD), a list of 309 compounds was obtained andwere then refined using Libdock program. Finally, based on the screening rules of the Libdock score of initial compound and the key interactions between initial compound and receptor, four compounds, demethoxycurcumin, isolicoflavonol, licochalcone E and silydianin, were selected as potential LXRβ agonists. The molecular simulation methods were high-efficiency and time-saving to obtainthe potential LXRβ agonists, which could provide assistance for further researchingnovel anti-hyperlipidemia drugs. Copyright© by the Chinese Pharmaceutical Association.

Solid-phase cadmium speciation in soil using L3-edge XANES spectroscopy with partial least-squares regression.

PubMed

Siebers, Nina; Kruse, Jens; Eckhardt, Kai-Uwe; Hu, Yongfeng; Leinweber, Peter

2012-07-01

Cadmium (Cd) has a high toxicity and resolving its speciation in soil is challenging but essential for estimating the environmental risk. In this study partial least-square (PLS) regression was tested for its capability to deconvolute Cd L(3)-edge X-ray absorption near-edge structure (XANES) spectra of multi-compound mixtures. For this, a library of Cd reference compound spectra and a spectrum of a soil sample were acquired. A good coefficient of determination (R(2)) of Cd compounds in mixtures was obtained for the PLS model using binary and ternary mixtures of various Cd reference compounds proving the validity of this approach. In order to describe complex systems like soil, multi-compound mixtures of a variety of Cd compounds must be included in the PLS model. The obtained PLS regression model was then applied to a highly Cd-contaminated soil revealing Cd(3)(PO(4))(2) (36.1%), Cd(NO(3))(2)·4H(2)O (24.5%), Cd(OH)(2) (21.7%), CdCO(3) (17.1%) and CdCl(2) (0.4%). These preliminary results proved that PLS regression is a promising approach for a direct determination of Cd speciation in the solid phase of a soil sample.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates source contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates sours; contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution:; from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

A generic biokinetic model for carbon-14 labelled compounds

NASA Astrophysics Data System (ADS)

Manger, Ryan Paul

Carbon-14, a radioactive nuclide, is used in many industrial applications. Due to its wide range of uses in industry, many workers are at risk of accidental internal exposure to 14C. Being a low energy beta emitter, 14C is not a significant external radiation hazard, but the internal consequences posed by 14C are important, especially because of its long half life of 5730 years [46]. The current biokinetic model recommended by the International Commission on Radiological Protection (ICRP) is a conservative estimate of how radiocarbon is treated by the human body. The ICRP generic radiocarbon model consists of a single compartment representing the entire human body. This compartment has a biological half life of 40 days yielding an effective dose coefficient of 5.8x10-10 Sv B q-1 [44, 45, 49, 53, 54]. This overestimates the dose of all radiocarbon compounds that have been studied [96]. An improved model has been developed that includes and alimentary tract, a urinary bladder, CO2 model, and an "Other" compartment used to model systemic tissues. The model can be adapted to replicate any excretion curve and excretion pattern. In addition, the effective dose coefficient produced by the updated model is near the mean effective dose coefficient of carbon compounds that have been considered in this research. The major areas of improvement are: more anatomically significant, a less conservative dose coefficient, and the ability to manipulate the model for known excretion data. Due to the wide variety of carbon compounds, it is suggested that specific biokinetic models be implemented for known radiocarbon substances. If the source of radiocarbon is dietary, then the physiologically based model proposed by Whillans [102] that splits all ingested radiocarbon compounds into carbohydrates, fats, and proteins should be used.

QSAR modeling and chemical space analysis of antimalarial compounds

NASA Astrophysics Data System (ADS)

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including 3000 molecules tested in one or several of 17 anti- Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

QSAR modeling and chemical space analysis of antimalarial compounds.

PubMed

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

High-intensity ultrasound production of Maillard reaction flavor compounds in a cysteine-xylose model system.

PubMed

Ong, Olivia X H; Seow, Yi-Xin; Ong, Peter K C; Zhou, Weibiao

2015-09-01

Application of high intensity ultrasound has shown potential in the production of Maillard reaction odor-active flavor compounds in model systems. The impact of initial pH, sonication duration, and ultrasound intensity on the production of Maillard reaction products (MRPs) by ultrasound processing in a cysteine-xylose model system were evaluated using Response Surface Methodology (RSM) with a modified mathematical model. Generation of selected MRPs, 2-methylthiophene and tetramethyl pyrazine, was optimal at an initial pH of 6.00, accompanied with 78.1 min of processing at an ultrasound intensity of 19.8 W cm(-2). However, identification of volatiles using gas chromatography-mass spectrometry (GC/MS) revealed that ultrasound-assisted Maillard reactions generated fewer sulfur-containing volatile flavor compounds as compared to conventional heat treatment of the model system. Likely reasons for this difference in flavor profile include the expulsion of H2S due to ultrasonic degassing and inefficient transmission of ultrasonic energy. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving compound-protein interaction prediction by building up highly credible negative samples.

PubMed

Liu, Hui; Sun, Jianjiang; Guan, Jihong; Zheng, Jie; Zhou, Shuigeng

2015-06-15

Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods. This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein-protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans. We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new interactions by training an support vector machine classifier on the positive interactions annotated in DrugBank and our screened negative interactions. The screened negative samples and the predicted interactions provide the research community with a useful resource for identifying new drug targets and a helpful supplement to the current curated compound-protein databases. Supplementary files are available at: http://admis.fudan.edu.cn/negative-cpi/. © The Author 2015. Published by Oxford University Press.

Modification of ginseng flavors by bitter compounds found in chocolate and coffee.

PubMed

Sook Chung, Hee; Lee, Soo-Yeun

2012-06-01

Ginseng is not widely accepted by U.S. consumers due to its unfamiliar flavors, despite its numerous health benefits. Previous studies have suggested that the bitter compounds in chocolate and coffee may mask the off-flavors of ginseng. The objectives of this study were to: (1) profile sensory characteristics of ginseng extract solution, caffeine solution, cyclo (L-Pro-L-Val) solution, theobromine solution, and 2 model solutions simulating chocolate bitterness; and (2) determine the changes in the sensory characteristics of ginseng extract solution by the addition of the bitter compounds found in chocolate and coffee. Thirteen solutions were prepared in concentrations similar to the levels of the bitter compounds found in coffee and chocolate products. Twelve panelists participated in a descriptive analysis panel which included time-intensity ratings. Ginseng extract was characterized as sweeter, starchier, and more green tea than the other sample solutions. Those characteristics of ginseng extract were effectively modified by the addition of caffeine, cyclo (L-Pro-L-Val), and 2 model solutions. A model solution simulating dark chocolate bitterness was the least influenced in intensities of bitterness by the addition of ginseng extract. Results from time-intensity ratings show that the addition of ginseng extract increased duration time in certain bitterness of the 2 model solutions. Bitter compounds found in dark chocolate could be proposed to effectively mask the unique flavors of ginseng. Future studies blending aroma compounds of chocolate and coffee into such model solutions may be conducted to investigate the influence on the perception of the unique flavors through the congruent flavors. © 2012 Institute of Food Technologists®

Modeling nasopharyngeal carcinoma in three dimensions

PubMed Central

Siva Sankar, Prabu; Che Mat, Mohd Firdaus; Muniandy, Kalaivani; Xiang, Benedict Lian Shi; Ling, Phang Su; Hoe, Susan Ling Ling; Khoo, Alan Soo-Beng; Mohana-Kumaran, Nethia

2017-01-01

Nasopharyngeal carcinoma (NPC) is a type of cancer endemic in Asia, including Malaysia, Southern China, Hong Kong and Taiwan. Treatment resistance, particularly in recurring cases, remains a challenge. Thus, studies to develop novel therapeutic agents are important. Potential therapeutic compounds may be effectively examined using two-dimensional (2D) cell culture models, three-dimensional (3D) spheroid models or in vivo animal models. The majority of drug assessments for cancers, including for NPC, are currently performed with 2D cell culture models. This model offers economical and high-throughput screening advantages. However, 2D cell culture models cannot recapitulate the architecture and the microenvironment of a tumor. In vivo models may recapitulate certain architectural and microenvironmental conditions of a tumor, however, these are not feasible for the screening of large numbers of compounds. By contrast, 3D spheroid models may be able to recapitulate a physiological microenvironment not observed in 2D cell culture models, in addition to avoiding the impediments of in vivo animal models. Thus, the 3D spheroid model offers a more representative model for the study of NPC growth, invasion and drug response, which may be cost-effective without forgoing quality. PMID:28454359

Profiling of nonvolatiles in whiskeys using ultra high pressure liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS).

PubMed

Collins, Thomas S; Zweigenbaum, Jerry; Ebeler, Susan E

2014-11-15

Commercial samples of 63 American whiskeys, including bourbon whiskeys, Tennessee whiskeys, rye whiskeys and other blended whiskeys were analysed using ultra high pressure liquid chromatography (UHPLC) coupled with quadrupole time-of-flight (QTOF) mass spectrometry (MS). The non-volatile composition of the whiskeys was used to model differences among the samples using discriminant analysis. The blended American whiskeys were readily distinguished from the remaining types. Additionally, most Tennessee whiskeys could be differentiated from bourbon and rye whiskeys. Similarly, younger (<4 years old) and older (>8 years old) whiskeys could be separated. The compounds important for differentiating among these whiskeys included wood derived phenolic compounds, lignan derived compounds and several C8 and larger lipids. A number of additional compounds differentiated the whiskeys but could not be identified using MS and MS/MS data alone. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Plant leaf traits, canopy processes, and global atmospheric chemistry interactions.

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2017-12-01

Plants produce and emit a diverse array of volatile metabolites into the atmosphere that participate in chemical reactions that influence distributions of air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. It is now widely accepted that accurate estimates of these emissions are required as inputs for regional air quality and global climate models. Predicting these emissions is complicated by the large number of volatile organic compounds, driving variables (e.g., temperature, solar radiation, abiotic and biotic stresses) and processes operating across a range of scales. Modeling efforts to characterize emission magnitude and variations will be described along with an assessment of the observations available for parameterizing and evaluating these models including discussion of the limitations and challenges associated with existing model approaches. A new approach for simulating canopy scale organic emissions on regional to global scales will be described and compared with leaf, canopy and regional scale flux measurements. The importance of including additional compounds and processes as well as improving estimates of existing ones will also be discussed.

Predictions of new AB O3 perovskite compounds by combining machine learning and density functional theory

NASA Astrophysics Data System (ADS)

Balachandran, Prasanna V.; Emery, Antoine A.; Gubernatis, James E.; Lookman, Turab; Wolverton, Chris; Zunger, Alex

2018-04-01

We apply machine learning (ML) methods to a database of 390 experimentally reported A B O3 compounds to construct two statistical models that predict possible new perovskite materials and possible new cubic perovskites. The first ML model classified the 390 compounds into 254 perovskites and 136 that are not perovskites with a 90% average cross-validation (CV) accuracy; the second ML model further classified the perovskites into 22 known cubic perovskites and 232 known noncubic perovskites with a 94% average CV accuracy. We find that the most effective chemical descriptors affecting our classification include largely geometric constructs such as the A and B Shannon ionic radii, the tolerance and octahedral factors, the A -O and B -O bond length, and the A and B Villars' Mendeleev numbers. We then construct an additional list of 625 A B O3 compounds assembled from charge conserving combinations of A and B atoms absent from our list of known compounds. Then, using the two ML models constructed on the known compounds, we predict that 235 of the 625 exist in a perovskite structure with a confidence greater than 50% and among them that 20 exist in the cubic structure (albeit, the latter with only ˜50 % confidence). We find that the new perovskites are most likely to occur when the A and B atoms are a lanthanide or actinide, when the A atom is an alkali, alkali earth, or late transition metal atom, or when the B atom is a p -block atom. We also compare the ML findings with the density functional theory calculations and convex hull analyses in the Open Quantum Materials Database (OQMD), which predicts the T =0 K ground-state stability of all the A B O3 compounds. We find that OQMD predicts 186 of 254 of the perovskites in the experimental database to be thermodynamically stable within 100 meV/atom of the convex hull and predicts 87 of the 235 ML-predicted perovskite compounds to be thermodynamically stable within 100 meV/atom of the convex hull, including 6 of these to be in cubic structures. We suggest these 87 as the most promising candidates for future experimental synthesis of novel perovskites.

Antiepileptic Drugs in Clinical Development: Differentiate or Die?

PubMed

Zaccara, Gaetano; Schmidt, D

2017-01-01

Animal models when carefully selected, designed and conducted, are important parts of any translational drug development strategy. However, research of new compounds for patients with drugresistant epilepsies is still based on animal experiments, mostly in rodents, which are far from being a model of chronic human epilepsy and have failed to differentiate the efficacy of new compounds versus standard drug treatment. The objective was identification and description of compounds in clinical development in 2016. Search was conducted from the website of the U.S. National Institutes of Health and from literature. Identified compounds have been divided in two groups: 1) compounds initially developed for the treatment of diseases other than epilepsy: biperiden, bumetanide, everolimus, fenfluramine, melatonin, minocycline, verapamil. 2) Compounds specifically developed for the treatment of epilepsy: allopregnanolone, cannabidiol, cannabidivarin, ganaxolone, nalutozan, PF-06372865, UCB0942, and cenobamate. Everolimus, and perhaps, fenfluramine are effective in specific epileptic diseases and may be considered as true disease modifying antiepileptic drugs. These are tuberous sclerosis complex for everolimus and Dravet syndrome for fenfluramine. With the exception of a few other compounds such as cannabinidiol, cannabidivarin and minocycline, the vast majority of other compounds had mechanisms of action which are similar to the mechanism of action of the anti-seizure drugs already in the market. Substantial improvements in the efficacy, specifically as pharmacological treatment of drug-resistant epilepsy is regarded, are not expected. New drugs should be developed to specifically target the biochemical alteration which characterizes the underlying disease and also include targets that contribute to epileptogenesis in relevant epilepsy models. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Identification and hit-to-lead optimization of a novel class of CB1 antagonists.

PubMed

Letourneau, Jeffrey J; Jokiel, Patrick; Olson, John; Riviello, Christopher M; Ho, Koc-Kan; McAleer, Lihong; Yang, Jingchun; Swanson, Robert N; Baker, James; Cowley, Phillip; Edwards, Darren; Ward, Nick; Ohlmeyer, Michael H J; Webb, Maria L

2010-09-15

The discovery, synthesis and preliminary structure-activity relationships (SARs) of a novel class of CB1 antagonists is described. Initial optimization of benzimidazole-based screening hit 4 led to the identification of 'inverted' indole-based lead compound 18c with improved properties versus compound 4 including reduced AlogP, improved microsomal stability and improved aqueous solubility. Compound 18c demonstrates in vivo CB1 antagonist efficacy (CB1 agonist induced hypothermia model) and is orally bioavailable in rat. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Alchemical and structural distribution based representation for universal quantum machine learning

NASA Astrophysics Data System (ADS)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

PubMed Central

Romero Durán, Francisco J.; Alonso, Nerea; Caamaño, Olga; García-Mera, Xerardo; Yañez, Matilde; Prado-Prado, Francisco J.; González-Díaz, Humberto

2014-01-01

In a multi-target complex network, the links (Lij) represent the interactions between the drug (di) and the target (tj), characterized by different experimental measures (Ki, Km, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (cj). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%–90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally. PMID:25255029

Quantitative Prediction of Solvation Free Energy in Octanol of Organic Compounds

PubMed Central

Delgado, Eduardo J.; Jaña, Gonzalo A.

2009-01-01

The free energy of solvation, ΔGS0, in octanol of organic compunds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a ΔGS0 range from about −50 to 0 kJ·mol−1. The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ·mol−1, just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set. PMID:19399236

Chapter 8: Pyrolysis Mechanisms of Lignin Model Compounds Using a Heated Micro-Reactor

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

Robichaud, David J.; Nimlos, Mark R.; Ellison, G. Barney

2015-10-03

Lignin is an important component of biomass, and the decomposition of its thermal deconstruction products is important in pyrolysis and gasification. In this chapter, we investigate the unimolecular pyrolysis chemistry through the use of singly and doubly substituted benzene molecules that are model compounds representative of lignin and its primary pyrolysis products. These model compounds are decomposed in a heated micro-reactor, and the products, including radicals and unstable intermediates, are measured using photoionization mass spectrometry and matrix isolation infrared spectroscopy. We show that the unimolecular chemistry can yield insight into the initial decomposition of these species. At pyrolysis and gasificationmore » severities, singly substituted benzenes typically undergo bond scission and elimination reactions to form radicals. Some require radical-driven chain reactions. For doubly substituted benzenes, proximity effects of the substituents can change the reaction pathways.« less

Construction and Optimization of a Heterologous Pathway for Protocatechuate Catabolism in Escherichia coli Enables Bioconversion of Model Aromatic Compounds

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

Clarkson, Sonya M.; Giannone, Richard J.; Kridelbaugh, Donna M.

The production of biofuels from lignocellulose yields a substantial lignin by-product stream that currently has few applications. Biological conversion of lignin-derived compounds into chemicals and fuels has the potential to improve the economics of lignocellulose-derived biofuels, but few microbes are able both to catabolize lignin-derived aromatic compounds and to generate valuable products. WhileEscherichia colihas been engineered to produce a variety of fuels and chemicals, it is incapable of catabolizing most aromatic compounds. Therefore, we engineeredE. colito catabolize protocatechuate, a common intermediate in lignin degradation, as the sole source of carbon and energy via heterologous expression of a nine-gene pathway fromPseudomonasmore » putidaKT2440. Then, we used experimental evolution to select for mutations that increased growth with protocatechuate more than 2-fold. Increasing the strength of a single ribosome binding site in the heterologous pathway was sufficient to recapitulate the increased growth. After optimization of the core pathway, we extended the pathway to enable catabolism of a second model compound, 4-hydroxybenzoate. These engineered strains will be useful platforms to discover, characterize, and optimize pathways for conversions of lignin-derived aromatics. IMPORTANCELignin is a challenging substrate for microbial catabolism due to its polymeric and heterogeneous chemical structure. Therefore, engineering microbes for improved catabolism of lignin-derived aromatic compounds will require the assembly of an entire network of catabolic reactions, including pathways from genetically intractable strains. By constructing defined pathways for aromatic compound degradation in a model host would allow rapid identification, characterization, and optimization of novel pathways. Finally, we constructed and optimized one such pathway inE. colito enable catabolism of a model aromatic compound, protocatechuate, and then extended the pathway to a related compound, 4-hydroxybenzoate. This optimized strain can now be used as the basis for the characterization of novel pathways.« less

Construction and Optimization of a Heterologous Pathway for Protocatechuate Catabolism in Escherichia coli Enables Bioconversion of Model Aromatic Compounds.

PubMed

Clarkson, Sonya M; Giannone, Richard J; Kridelbaugh, Donna M; Elkins, James G; Guss, Adam M; Michener, Joshua K

2017-09-15

The production of biofuels from lignocellulose yields a substantial lignin by-product stream that currently has few applications. Biological conversion of lignin-derived compounds into chemicals and fuels has the potential to improve the economics of lignocellulose-derived biofuels, but few microbes are able both to catabolize lignin-derived aromatic compounds and to generate valuable products. While Escherichia coli has been engineered to produce a variety of fuels and chemicals, it is incapable of catabolizing most aromatic compounds. Therefore, we engineered E. coli to catabolize protocatechuate, a common intermediate in lignin degradation, as the sole source of carbon and energy via heterologous expression of a nine-gene pathway from Pseudomonas putida KT2440. We next used experimental evolution to select for mutations that increased growth with protocatechuate more than 2-fold. Increasing the strength of a single ribosome binding site in the heterologous pathway was sufficient to recapitulate the increased growth. After optimization of the core pathway, we extended the pathway to enable catabolism of a second model compound, 4-hydroxybenzoate. These engineered strains will be useful platforms to discover, characterize, and optimize pathways for conversions of lignin-derived aromatics. IMPORTANCE Lignin is a challenging substrate for microbial catabolism due to its polymeric and heterogeneous chemical structure. Therefore, engineering microbes for improved catabolism of lignin-derived aromatic compounds will require the assembly of an entire network of catabolic reactions, including pathways from genetically intractable strains. Constructing defined pathways for aromatic compound degradation in a model host would allow rapid identification, characterization, and optimization of novel pathways. We constructed and optimized one such pathway in E. coli to enable catabolism of a model aromatic compound, protocatechuate, and then extended the pathway to a related compound, 4-hydroxybenzoate. This optimized strain can now be used as the basis for the characterization of novel pathways. Copyright © 2017 American Society for Microbiology.

Orthotopic mouse models for the preclinical and translational study of targeted therapies against metastatic human thyroid carcinoma with BRAFV600E or wild-type BRAF

PubMed Central

Antonello, ZA; Nucera, C

2015-01-01

Molecular signature of advanced and metastatic thyroid carcinoma involves deregulation of multiple fundamental pathways activated in the tumor microenvironment. They include BRAFV600E and AKT that affect tumor initiation, progression and metastasis. Human thyroid cancer orthotopic mouse models are based on human cell lines that generally harbor genetic alterations found in human thyroid cancers. They can reproduce in vivo and in situ (into the thyroid) many features of aggressive and refractory human advanced thyroid carcinomas, including local invasion and metastasis. Humanized orthotopic mouse models seem to be ideal and commonly used for preclinical and translational studies of compounds and therapies not only because they may mimic key aspects of human diseases (e.g. metastasis), but also for their reproducibility. In addition, they might provide the possibility to evaluate systemic effects of treatments. So far, human thyroid cancer in vivo models were mainly used to test single compounds, non selective and selective. Despite the greater antitumor activity and lower toxicity obtained with different selective drugs in respect to non-selective ones, most of them are only able to delay disease progression, which ultimately could restart with similar aggressive behavior. Aggressive thyroid tumors (for example, anaplastic or poorly differentiated thyroid carcinoma) carry several complex genetic alterations that are likely cooperating to promote disease progression and might confer resistance to single-compound approaches. Orthotopic models of human thyroid cancer also hold the potential to be good models for testing novel combinatorial therapies. In this article, we will summarize results on preclinical testing of selective and nonselective single compounds in orthotopic mouse models based on validated human thyroid cancer cell lines harboring the BRAFV600E mutation or with wild-type BRAF. Furthermore, we will discuss the potential use of this model also for combinatorial approaches, which are expected to take place in the upcoming human thyroid cancer basic and clinical research. PMID:24362526

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease

PubMed Central

Karagiannis, Tom C.; Ververis, Katherine

2012-01-01

Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes. PMID:22953035

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease.

PubMed

Karagiannis, Tom C; Ververis, Katherine

2012-01-01

Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes.

A method to calculate fission-fragment yields Y(Z,N) versus proton and neutron number in the Brownian shape-motion model

DOE PAGES

Moller, Peter; Ichikawa, Takatoshi

2015-12-23

In this study, we propose a method to calculate the two-dimensional (2D) fission-fragment yield Y(Z,N) versus both proton and neutron number, with inclusion of odd-even staggering effects in both variables. The approach is to use the Brownian shape-motion on a macroscopic-microscopic potential-energy surface which, for a particular compound system is calculated versus four shape variables: elongation (quadrupole moment Q 2), neck d, left nascent fragment spheroidal deformation ϵ f1, right nascent fragment deformation ϵ f2 and two asymmetry variables, namely proton and neutron numbers in each of the two fragments. The extension of previous models 1) introduces a method tomore » calculate this generalized potential-energy function and 2) allows the correlated transfer of nucleon pairs in one step, in addition to sequential transfer. In the previous version the potential energy was calculated as a function of Z and N of the compound system and its shape, including the asymmetry of the shape. We outline here how to generalize the model from the “compound-system” model to a model where the emerging fragment proton and neutron numbers also enter, over and above the compound system composition.« less

Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models

NASA Astrophysics Data System (ADS)

Basheer, Loai; Schultz, Keren; Kerem, Zohar

2016-08-01

Many dietary compounds, including resveratrol, are potent inhibitors of CYP3A4. Here we examined the potential to predict inhibition capacity of dietary polyphenolics using an in silico and in vitro approaches and synthetic model compounds. Mono, di, and tri-acetoxy resveratrol were synthesized, a cell line of human intestine origin and microsomes from rat liver served to determine their in vitro inhibition of CYP3A4, and compared to that of resveratrol. Docking simulation served to predict the affinity of the synthetic model compounds to the enzyme. Modelling of the enzyme’s binding site revealed three types of interaction: hydrophobic, electrostatic and H-bonding. The simulation revealed that each of the examined acetylations of resveratrol led to the loss of important interactions of all types. Tri-acetoxy resveratrol was the weakest inhibitor in vitro despite being the more lipophilic and having the highest affinity for the binding site. The simulation demonstrated exclusion of all interactions between tri-acetoxy resveratrol and the heme due to distal binding, highlighting the complexity of the CYP3A4 binding site, which may allow simultaneous accommodation of two molecules. Finally, the use of computational modelling may serve as a quick predictive tool to identify potential harmful interactions between dietary compounds and prescribed drugs.

Transformations of Model Organic Compounds on Snow Grains at Summit, Greenland

NASA Astrophysics Data System (ADS)

Galbavy, E. S.; Ram, K.; Anastasio, C.

2005-12-01

Photochemical reactions in snowpacks produce a number of chemicals species that can significantly impact the overlying atmosphere and transform many organic pollutants. During this past summer's field season at Summit we examined the kinetics for the disappearance of a suite of model organic compounds in surface snowpack. Our compounds (2-nitrobenzaldehyde, sodium benzoate, syringol, 4-chlorophenol, 2-oxo-butanoic acid, and phenanthrene) were chosen because they represent markers from several different emission sources and because they have a range of expected fates, i.e., their lifetimes will be determined by different processes. These processes include direct photolysis and reactions with oxidants such as hydroxyl radical (OH) and singlet molecular oxygen (1O2*) In addition to measuring the rates of loss of the model organics, we also measured concentrations of OH and 1O2* in the snow samples, as well as rates of direct photolysis of the organics in frozen, purified water. Our goal was to compare the measured lifetimes of the organic compounds with calculated lifetimes based on reactions with OH and 1O2* and direct photolysis. While certain compounds behaved as expected, others decayed more slowly, or more rapidly, than expected, indicating that other, unidentified, snow grain reactions and/or mechanisms are significant. The rates of organic compound loss, the potential reasons for the observed differences, and the implications for lifetimes of trace organic pollutants in polar regions will be discussed.

Parallel screening of drug-like natural compounds using Caco-2 cell permeability QSAR model with applicability domain, lipophilic ligand efficiency index and shape property: A case study of HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Patel, Rikin D.; Kumar, Sivakumar Prasanth; Patel, Chirag N.; Shankar, Shetty Shilpa; Pandya, Himanshu A.; Solanki, Hitesh A.

2017-10-01

The traditional drug design strategy centrally focuses on optimizing binding affinity with the receptor target and evaluates pharmacokinetic properties at a later stage which causes high rate of attrition in clinical trials. Alternatively, parallel screening allows evaluation of these properties and affinity simultaneously. In a case study to identify leads from natural compounds with experimental HIV-1 reverse transcriptase (RT) inhibition, we integrated various computational approaches including Caco-2 cell permeability QSAR model with applicability domain (AD) to recognize drug-like natural compounds, molecular docking to study HIV-1 RT interactions and shape similarity analysis with known crystal inhibitors having characteristic butterfly-like model. Further, the lipophilic properties of the compounds refined from the process with best scores were examined using lipophilic ligand efficiency (LLE) index. Seven natural compound hits viz. baicalien, (+)-calanolide A, mniopetal F, fagaronine chloride, 3,5,8-trihydroxy-4-quinolone methyl ether derivative, nitidine chloride and palmatine, were prioritized based on LLE score which demonstrated Caco-2 well absorption labeling, encompassment in AD structural coverage, better receptor affinity, shape adaptation and permissible AlogP value. We showed that this integrative approach is successful in lead exploration of natural compounds targeted against HIV-1 RT enzyme.

Evaluation of an 18-year CMAQ simulation: Seasonal variations and long-term temporal changes in sulfate and nitrate

NASA Astrophysics Data System (ADS)

Civerolo, Kevin; Hogrefe, Christian; Zalewsky, Eric; Hao, Winston; Sistla, Gopal; Lynn, Barry; Rosenzweig, Cynthia; Kinney, Patrick L.

2010-10-01

This paper compares spatial and seasonal variations and temporal trends in modeled and measured concentrations of sulfur and nitrogen compounds in wet and dry deposition over an 18-year period (1988-2005) over a portion of the northeastern United States. Substantial emissions reduction programs occurred over this time period, including Title IV of the Clean Air Act Amendments of 1990 which primarily resulted in large decreases in sulfur dioxide (SO 2) emissions by 1995, and nitrogen oxide (NO x) trading programs which resulted in large decreases in warm season NO x emissions by 2004. Additionally, NO x emissions from mobile sources declined more gradually over this period. The results presented here illustrate the use of both operational and dynamic model evaluation and suggest that the modeling system largely captures the seasonal and long-term changes in sulfur compounds. The modeling system generally captures the long-term trends in nitrogen compounds, but does not reproduce the average seasonal variation or spatial patterns in nitrate.

Modeling prescribed burning experiments and assessing the fire impacts on local to regional air quality

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.

2016-12-01

Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.

Constructing an atomic-resolution model of human P2X7 receptor followed by pharmacophore modeling to identify potential inhibitors.

PubMed

Ahmadi, Mehdi; Nowroozi, Amin; Shahlaei, Mohsen

2015-09-01

The P2X purinoceptor 7 (P2X7R) is a trimeric ATP-activated ion channel gated by extracellular ATP. P2X7R has important role in numerous diseases including pain, neurodegeneration, and inflammatory diseases such as rheumatoid arthritis and osteoarthritis. In this prospective, the discovery of small-molecule inhibitors for P2X7R as a novel therapeutic target has received considerable attention in recent years. At first, 3D structure of P2X7R was built by using homology modeling (HM) and a 50ns molecular dynamics simulation (MDS). Ligand-based quantitative pharmacophore modeling methodology of P2X7R antagonists were developed based on training set of 49 compounds. The best four-feature pharmacophore model, includes two hydrophobic aromatic, one hydrophobic and one aromatic ring features, has the highest correlation coefficient (0.874), cost difference (368.677), low RMSD (2.876), as well as it shows a high goodness of fit and enrichment factor. Consequently, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. Among these compounds, six potential molecule were identified as potential virtual leads which, as such or upon further optimization, can be used to design novel P2X7R inhibitors. Copyright © 2015 Elsevier Inc. All rights reserved.

Exchange interactions and magnetic properties of hexagonal rare-earth-cobalt compounds

NASA Astrophysics Data System (ADS)

Burzo, E.

2018-03-01

The magnetic properties of some GdxY1-xCo4A compounds with A = Co, Si or B are analysed including the pressure effects. Isomorphous structure transitions, parallelly with changes of cobalt moments from high spin states to low spin states, were shown as pressure increases. The magnetic data, obtained from band structures, were compared with those predicted by the mean field model.

Biogenic organic emissions, air quality and climate

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2015-12-01

Living organisms produce copious amounts of a diverse array of metabolites including many volatile organic compounds that are released into the atmosphere. These compounds participate in numerous chemical reactions that influence the atmospheric abundance of important air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. The production and release of these organics are strongly influenced by environmental conditions including air pollution, temperature, solar radiation, and water availability and they are highly sensitive to stress and extreme events. As a result, releases of biogenic organics to the atmosphere have an impact on, and are sensitive to, air quality and climate leading to potential feedback couplings. Their role in linking air quality and climate is conceptually clear but an accurate quantitative representation is needed for predictive models. Progress towards this goal will be presented including numerical model development and assessments of the predictive capability of the Model of Emission of Gases and Aerosols from Nature (MEGAN). Recent studies of processes controlling the magnitude and variations in biogenic organic emissions will be described and observations of their impact on atmospheric composition will be shown. Recent advances and priorities for future research will be discussed including laboratory process studies, long-term measurements, multi-scale regional studies, global satellite observations, and the development of a next generation model for simulating land-atmosphere chemical exchange.

Wet scrubbing of biomass producer gas tars using vegetable oil

NASA Astrophysics Data System (ADS)

Bhoi, Prakashbhai Ramabhai

The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.

Electrophysiological evidence for the morpheme-based combinatoric processing of English compounds

PubMed Central

Fiorentino, Robert; Naito-Billen, Yuka; Bost, Jamie; Fund-Reznicek, Ella

2014-01-01

The extent to which the processing of compounds (e.g., “catfish”) makes recourse to morphological-level representations remains a matter of debate. Moreover, positing a morpheme-level route to complex word recognition entails not only access to morphological constituents, but also combinatoric processes operating on the constituent representations; however, the neurophysiological mechanisms subserving decomposition, and in particular morpheme combination, have yet to be fully elucidated. The current study presents electrophysiological evidence for the morpheme-based processing of both lexicalized (e.g., “teacup”) and novel (e.g., “tombnote”) visually-presented English compounds; these brain responses appear prior to and are dissociable from the eventual overt lexical decision response. The electrophysiological results reveal increased negativities for conditions with compound structure, including effects shared by lexicalized and novel compounds, as well as effects unique to each compound type, which may be related to aspects of morpheme combination. These findings support models positing across-the-board morphological decomposition, counter to models proposing that putatively complex words are primarily or solely processed as undecomposed representations, and motivate further electrophysiological research toward a more precise characterization of the nature and neurophysiological instantiation of complex word recognition. PMID:24279696

Identification of small molecule lead compounds for visceral leishmaniasis using a novel ex vivo splenic explant model system.

PubMed

Osorio, Yaneth; Travi, Bruno L; Renslo, Adam R; Peniche, Alex G; Melby, Peter C

2011-02-15

New drugs are needed to treat visceral leishmaniasis (VL) because the current therapies are toxic, expensive, and parasite resistance may weaken drug efficacy. We established a novel ex vivo splenic explant culture system from hamsters infected with luciferase-transfected Leishmania donovani to screen chemical compounds for anti-leishmanial activity. THIS MODEL HAS ADVANTAGES OVER IN VITRO SYSTEMS IN THAT IT: 1) includes the whole cellular population involved in the host-parasite interaction; 2) is initiated at a stage of infection when the immunosuppressive mechanisms that lead to progressive VL are evident; 3) involves the intracellular form of Leishmania; 4) supports parasite replication that can be easily quantified by detection of parasite-expressed luciferase; 5) is adaptable to a high-throughput screening format; and 6) can be used to identify compounds that have both direct and indirect anti-parasitic activity. The assay showed excellent discrimination between positive (amphotericin B) and negative (vehicle) controls with a Z' Factor >0.8. A duplicate screen of 4 chemical libraries containing 4,035 compounds identified 202 hits (5.0%) with a Z score of <-1.96 (p<0.05). Eighty-four (2.1%) of the hits were classified as lead compounds based on the in vitro therapeutic index (ratio of the compound concentration causing 50% cytotoxicity in the HepG(2) cell line to the concentration that caused 50% reduction in the parasite load). Sixty-nine (82%) of the lead compounds were previously unknown to have anti-leishmanial activity. The most frequently identified lead compounds were classified as quinoline-containing compounds (14%), alkaloids (10%), aromatics (11%), terpenes (8%), phenothiazines (7%) and furans (5%). The ex vivo splenic explant model provides a powerful approach to identify new compounds active against L. donovani within the pathophysiologic environment of the infected spleen. Further in vivo evaluation and chemical optimization of these lead compounds may generate new candidates for preclinical studies of treatment for VL.

Emissions of organic compounds from produced water ponds II: Evaluation of flux chamber measurements with inverse-modeling techniques.

PubMed

Tran, Huy N Q; Lyman, Seth N; Mansfield, Marc L; O'Neil, Trevor; Bowers, Richard L; Smith, Ann P; Keslar, Cara

2018-07-01

In this study, the authors apply two different dispersion models to evaluate flux chamber measurements of emissions of 58 organic compounds, including C2-C11 hydrocarbons and methanol, ethanol, and isopropanol from oil- and gas-produced water ponds in the Uintah Basin. Field measurement campaigns using the flux chamber technique were performed at a limited number of produced water ponds in the basin throughout 2013-2016. Inverse-modeling results showed significantly higher emissions than were measured by the flux chamber. Discrepancies between the two methods vary across hydrocarbon compounds and are largest in alcohols due to their physical chemistries. This finding, in combination with findings in a related study using the WATER9 wastewater emission model, suggests that the flux chamber technique may underestimate organic compound emissions, especially alcohols, due to its limited coverage of the pond area and alteration of environmental conditions, especially wind speed. Comparisons of inverse-model estimations with flux chamber measurements varied significantly with the complexity of pond facilities and geometries. Both model results and flux chamber measurements suggest significant contributions from produced water ponds to total organic compound emission from oil and gas productions in the basin. This research is a component of an extensive study that showed significant amount of hydrocarbon emissions from produced water ponds in the Uintah Basin, Utah. Such findings have important meanings to air quality management agencies in developing control strategies for air pollution in oil and gas fields, especially for the Uintah Basin in which ozone pollutions frequently occurred in winter seasons.

Predicting concentrations of trace organic compounds in municipal wastewater treatment plant sludge and biosolids using the PhATE™ model.

PubMed

Cunningham, Virginia L; D'Aco, Vincent J; Pfeiffer, Danielle; Anderson, Paul D; Buzby, Mary E; Hannah, Robert E; Jahnke, James; Parke, Neil J

2012-07-01

This article presents the capability expansion of the PhATE™ (pharmaceutical assessment and transport evaluation) model to predict concentrations of trace organics in sludges and biosolids from municipal wastewater treatment plants (WWTPs). PhATE was originally developed as an empirical model to estimate potential concentrations of active pharmaceutical ingredients (APIs) in US surface and drinking waters that could result from patient use of medicines. However, many compounds, including pharmaceuticals, are not completely transformed in WWTPs and remain in biosolids that may be applied to land as a soil amendment. This practice leads to concerns about potential exposures of people who may come into contact with amended soils and also about potential effects to plants and animals living in or contacting such soils. The model estimates the mass of API in WWTP influent based on the population served, the API per capita use, and the potential loss of the compound associated with human use (e.g., metabolism). The mass of API on the treated biosolids is then estimated based on partitioning to primary and secondary solids, potential loss due to biodegradation in secondary treatment (e.g., activated sludge), and potential loss during sludge treatment (e.g., aerobic digestion, anaerobic digestion, composting). Simulations using 2 surrogate compounds show that predicted environmental concentrations (PECs) generated by PhATE are in very good agreement with measured concentrations, i.e., well within 1 order of magnitude. Model simulations were then carried out for 18 APIs representing a broad range of chemical and use characteristics. These simulations yielded 4 categories of results: 1) PECs are in good agreement with measured data for 9 compounds with high analytical detection frequencies, 2) PECs are greater than measured data for 3 compounds with high analytical detection frequencies, possibly as a result of as yet unidentified depletion mechanisms, 3) PECs are less than analytical reporting limits for 5 compounds with low analytical detection frequencies, and 4) the PEC is greater than the analytical method reporting limit for 1 compound with a low analytical detection frequency, possibly again as a result of insufficient depletion data. Overall, these results demonstrate that PhATE has the potential to be a very useful tool in the evaluation of APIs in biosolids. Possible applications include: prioritizing APIs for assessment even in the absence of analytical methods; evaluating sludge processing scenarios to explore potential mitigation approaches; using in risk assessments; and developing realistic nationwide concentrations, because PECs can be represented as a cumulative probability distribution. Finally, comparison of PECs to measured concentrations can also be used to identify the need for fate studies of compounds of interest in biosolids. Copyright © 2011 SETAC.

Mouse Xenograft Model for Mesothelioma | NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute is seeking parties interested in collaborative research to co-develop, evaluate, or commercialize a new mouse model for monoclonal antibodies and immunoconjugates that target malignant mesotheliomas. Applications of the technology include models for screening compounds as potential therapeutics for mesothelioma and for studying the pathology of mesothelioma.

An Effective Model to Increase Student Attitude and Achievement: Narrative Including Analogies

ERIC Educational Resources Information Center

Akkuzu, Nalan; Akcay, Husamettin

2011-01-01

This study describes the analogical models and narratives used to introduce and teach Grade 9 chemical covalent compounds which are relatively abstract and difficult for students. We explained each model's development during the lessons and analyzed understanding students derived from these learning materials. In this context, achievement,…

Standardized Competencies for Parenteral Nutrition Order Review and Parenteral Nutrition Preparation, Including Compounding: The ASPEN Model.

PubMed

Boullata, Joseph I; Holcombe, Beverly; Sacks, Gordon; Gervasio, Jane; Adams, Stephen C; Christensen, Michael; Durfee, Sharon; Ayers, Phil; Marshall, Neil; Guenter, Peggi

2016-08-01

Parenteral nutrition (PN) is a high-alert medication with a complex drug use process. Key steps in the process include the review of each PN prescription followed by the preparation of the formulation. The preparation step includes compounding the PN or activating a standardized commercially available PN product. The verification and review, as well as preparation of this complex therapy, require competency that may be determined by using a standardized process for pharmacists and for pharmacy technicians involved with PN. An American Society for Parenteral and Enteral Nutrition (ASPEN) standardized model for PN order review and PN preparation competencies is proposed based on a competency framework, the ASPEN-published interdisciplinary core competencies, safe practice recommendations, and clinical guidelines, and is intended for institutions and agencies to use with their staff. © 2016 American Society for Parenteral and Enteral Nutrition.

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates

NASA Astrophysics Data System (ADS)

Crivori, Patrizia; Zamora, Ismael; Speed, Bill; Orrenius, Christian; Poggesi, Italo

2004-03-01

A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME - absorption, distribution, metabolism and excretion; CYP - cytochrome P450; MIFs - molecular interaction fields; HTS - high throughput screening; DDI - drug-drug interactions; 3D - three-dimensional; PCA - principal components analysis; CPCA - consensus principal components analysis; PLS - partial least squares; PLSD - partial least squares discriminant; GRIND - grid independent descriptors; GRID - software originally created and developed by Professor Peter Goodford.

Using a Mechanistic Reactive Transport Model to Represent Soil Organic Matter Dynamics and Climate Sensitivity

NASA Astrophysics Data System (ADS)

Guerry, N.; Riley, W. J.; Maggi, F.; Torn, M. S.; Kleber, M.

2011-12-01

The nature of long term Soil Organic Matter (SOM) dynamics is uncertain and the mechanisms involved are crudely represented in site, regional, and global models. Recent work challenging the paradigm that SOM is stabilized because of its sequential transformations to more intrinsically recalcitrant compounds motivated us to develop a mechanistic modeling framework that can be used to test hypotheses of SOM dynamics. We developed our C cycling model in TOUGHREACT, an established 3-dimensional reactive transport solver that accounts for multiple phases (aqueous, gaseous, sorbed), multiple species, advection and diffusion, and multiple microbial populations. Energy and mass exchange through the soil boundaries are accounted for via ground heat flux, rainfall, C sources (e.g., exudation, woody, leaf, root litter) and C losses (e.g., CO2 emissions and DOC deep percolation). SOM is categorized according to the various types of compounds commonly found in the above mentioned C sources and microbial byproducts, including poly- and monosaccharides, lignin, amino compounds, organic acids, nucleic acids, lipids, and phenols. Each of these compounds is accounted for by one or more representative species in the model. A reaction network was developed to describe the microbially-mediated processes and chemical interactions of these species, including depolymerization, microbial assimilation, respiration and deposition of byproducts, and incorporation of dead biomass into SOM stocks. Enzymatic reactions are characterized by Michaelis-Menten kinetics, with maximum reaction rates determined by the species' O/C ratio. Microbial activity is further regulated by soil moisture content, O2 availability, pH, and temperature. For the initial set of simulations, literature values were used to constrain microbial Monod parameters, Michaelis-Menten parameters, sorption parameters, physical protection, partitioning of microbial byproducts, and partitioning of litter inputs, although there is substantial uncertainty in how these relationships should be represented. We also developed several other model formulations, including one that represents SOM in pools of varying decomposability, but lacking explicit protection mechanisms. We tested the model against several observational and experimental datasets. An important conclusion of our analysis is that although several of the model structural formulations were able to represent the bulk SOM observations, including 14C vertical profiles, the temperature, moisture, and soil chemistry sensitivity of decomposition varied strongly between each formulation. Finally, we applied the model to design observations that would be required to better constrain process representation and improve predictions of changes in SOM under changing climate.

Chemometric studies on potential larvicidal compounds against Aedes aegypti.

PubMed

Scotti, Luciana; Scotti, Marcus Tullius; Silva, Viviane Barros; Santos, Sandra Regina Lima; Cavalcanti, Sócrates C H; Mendonça, Francisco J B

2014-03-01

The mosquito Aedes aegypti (Diptera, Culicidae) is the vector of yellow and dengue fever. In this study, chemometric tools, such as, Principal Component Analysis (PCA), Consensus PCA (CPCA), and Partial Least Squares Regression (PLS), were applied to a set of fifty five active compounds against Ae. aegypti larvae, which includes terpenes, cyclic alcohols, phenolic compounds, and their synthetic derivatives. The calculations were performed using the VolSurf+ program. CPCA analysis suggests that the higher weight blocks of descriptors were SIZE/SHAPE, DRY, and H2O. The PCA was generated with 48 descriptors selected from the previous blocks. The scores plot showed good separation between more and less potent compounds. The first two PCs accounted for over 60% of the data variance. The best model obtained in PLS, after validation leave-one-out, exhibited q(2) = 0.679 and r(2) = 0.714. External prediction model was R(2) = 0.623. The independent variables having a hydrophobic profile were strongly correlated to the biological data. The interaction maps generated with the GRID force field showed that the most active compounds exhibit more interaction with the DRY probe.

Optimization of a Small Tropomyosin-related Kinase B (TrkB) Agonist 7,8-Dihydroxyflavone Active in Mouse Models of Depression

PubMed Central

Liu, Xia; Chan, Chi-Bun; Qi, Qi; Xiao, Ge; Luo, Hongbo R.; He, Xiaolin; Ye, Keqiang

2012-01-01

Structure-activity relationship study shows that the catechol group in 7,8-dihdyroxyflavone, a selective small TrkB receptor agonist, is critical for the agonistic activity. To improve the poor pharmacokinetic profiles intrinsic to catechol-containing molecules and elevate the agonistic effect of the lead compound, we initiated the lead optimization campaign by synthesizing various bioisosteric derivatives. Here we show that the optimized 2-methyl-8-(4′-(pyrrolidin-1-yl)phenyl)chromeno[7,8-d]imidazol-6(1H)-one derivative possesses the enhanced TrkB stimulatory activity. Chronic oral administration of this compound significantly reduces the immobility in forced swim test and tail suspension test, two classical antidepressant behavioral animal models, which is accompanied by robust TrkB activation in hippocampus of mouse brain. Further, in vitro ADMET studies demonstrate that this compound possesses the improved features compared to the previous lead compound. Hence, this optimized compound may act as a promising lead candidate for in-depth drug development for treating various neurological disorders including depression. PMID:22984948

Discovery of nonsteroidal 17beta-hydroxysteroid dehydrogenase 1 inhibitors by pharmacophore-based screening of virtual compound libraries.

PubMed

Schuster, Daniela; Nashev, Lyubomir G; Kirchmair, Johannes; Laggner, Christian; Wolber, Gerhard; Langer, Thierry; Odermatt, Alex

2008-07-24

17Beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) plays a pivotal role in the local synthesis of the most potent estrogen estradiol. Its expression is a prognostic marker for the outcome of patients with breast cancer and inhibition of 17beta-HSD1 is currently under consideration for breast cancer prevention and treatment. We aimed to identify nonsteroidal 17beta-HSD1 inhibitor scaffolds by virtual screening with pharmacophore models built from crystal structures containing steroidal compounds. The most promising model was validated by comparing predicted and experimentally determined inhibitory activities of several flavonoids. Subsequently, a virtual library of nonsteroidal compounds was screened against the 3D pharmacophore. Analysis of 14 selected compounds yielded four that inhibited the activity of human 17beta-HSD1 (IC 50 below 50 microM). Specificity assessment of identified 17beta-HSD1 inhibitors emphasized the importance of including related short-chain dehydrogenase/reductase (SDR) members to analyze off-target effects. Compound 29 displayed at least 10-fold selectivity over the related SDR enzymes tested.

Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure-activity relationships.

PubMed

Chen, Shaodan; Li, Xiangmin; Yong, Tianqiao; Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B

2017-02-07

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure-activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds.

Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure–activity relationships

PubMed Central

Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B.

2017-01-01

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure–activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds. PMID:28052025

Discovery of Novel, Orally Bioavailable β-Amino Acid Azaindole Inhibitors of Influenza PB2

PubMed Central

2017-01-01

In our efforts to develop novel small-molecule inhibitors for the treatment of influenza, we utilized molecular modeling and the X-ray crystal structure of the PB2 subunit of the influenza polymerase to optimize a series of acyclic β-amino acid inhibitors, highlighted by compound 4. Compound 4 showed good oral exposure in both rat and mouse. More importantly, it showed strong potency versus multiple influenza-A strains, including pandemic 2009 H1N1 and avian H5N1 strains and showed a strong efficacy profile in a mouse influenza model even when treatment was initiated 48 h after infection. Compound 4 offers good oral bioavailability with great potential for the treatment of both pandemic and seasonal influenza. PMID:28197322

Elucidation of key aroma compounds in traditional dry fermented sausages using different extraction techniques.

PubMed

Corral, Sara; Salvador, Ana; Flores, Mónica

2015-04-01

The use of different extraction techniques - solid phase microextraction (SPME) and solvent assisted flavour evaporation (SAFE) - can deliver different aroma profiles and it is essential to determine which is most suitable to extract the aroma compounds from dry fermented sausages. Forty-five aroma-active compounds were detected by SPME and SAFE, with 11 of them reported for the first time as aroma compounds in dry fermented sausages: ethyl 3-hydroxy butanoate, trimethyl pyrazine, D-pantolactone, isobutyl hexanoate, ethyl benzoate, α-terpineol, ethyl 3-pyridinecarboxylate, benzothiazole, 2,3-dihydrothiophene, methyl eugenol, γ-nonalactone. The aroma concentration and odour activity values (OAVs) were calculated. Flavour reconstitution analyses were performed using 20 odorants with OAVs above 1 obtained from the SAFE and SPME extracts to prepare the aroma model. SPME and SAFE techniques were complementary and necessary to reproduce the overall dry fermented sausage aroma. The final aroma model included the odorants from both extraction techniques (SPME and SAFE) but it was necessary to incorporate the compounds 2,4-decadienal (E,E), benzothiazole, methyl eugenol, α-terpineol, and eugenol to the final aroma model to evoked the fresh sausage aroma although a lowest cured meat aroma note was perceived. © 2014 Society of Chemical Industry.

An In Ovo Model for Testing Insulin-mimetic Compounds.

PubMed

Haselgrübler, Renate; Stübl, Flora; Stadlbauer, Verena; Lanzerstorfer, Peter; Weghuber, Julian

2018-04-23

Elevated blood glucose levels in type 2 diabetes mellitus (T2DM), a complex and multifactorial metabolic disease, are caused by insulin resistance and β-cell failure. Various strategies, including the injection of insulin or the usage of insulin-sensitizing drugs, were pursued to treat T2DM or at least reduce the symptoms. In addition, the application of herbal compounds has attracted increasing attention. Thus, it is necessary to find efficient test systems to identify and characterize insulin-mimetic compounds. Here we developed a modified chick embryo model, which enables testing of synthetic compounds and herbal extracts with insulin-mimetic properties. Using a fluorescence microscopy-based primary screen, which quantifies the translocation of Glucose transporter 4 (Glut4) to the plasma membrane, we were able to identify compounds, mainly herbal extracts, which lead to an increase of intracellular glucose concentrations in adipocytes. However, the efficacy of these substances requires further verification in a living organism. Thus, we used an in-ovo approach to identify their blood glucose-reducing properties. The approval by an ethics committee is not needed since the use of chicken embryos during the first two-thirds of embryonic development is not considered an animal experiment. Here, the application of this model is described in detail.

Screening of benzamidine-based thrombin inhibitors via a linear interaction energy in continuum electrostatics model

NASA Astrophysics Data System (ADS)

Nicolotti, Orazio; Giangreco, Ilenia; Miscioscia, Teresa Fabiola; Convertino, Marino; Leonetti, Francesco; Pisani, Leonardo; Carotti, Angelo

2010-02-01

A series of 27 benzamidine inhibitors covering a wide range of biological activity and chemical diversity was analysed to derive a Linear Interaction Energy in Continuum Electrostatics (LIECE) model for analysing the thrombin inhibitory activity. The main interactions occurring at the thrombin binding site and the preferred binding conformations of inhibitors were explicitly biased by including into the LIECE model 10 compounds extracted from X-ray solved thrombin-inhibitor complexes available from the Protein Data Bank (PDB). Supported by a robust statistics ( r 2 = 0.698; q 2 = 0.662), the LIECE model was successful in predicting the inhibitory activity for about 76% of compounds ( r ext 2 ≥ 0.600) from a larger external test set encompassing 88 known thrombin inhibitors and, more importantly, in retrieving, at high sensitivity and with better performance than docking and shape-based methods, active compounds from a thrombin combinatorial library of 10240 mimetic chemical products. The herein proposed LIECE model has the potential for successfully driving the design of novel thrombin inhibitors with benzamidine and/or benzamidine-like chemical structure.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

The Yucatan miniature swine as an in vivo model for screening skin depigmentation.

PubMed

Nair, X; Tramposch, K M

1991-12-01

The usefulness of the Yucatan miniature pig as a screen for skin dipigmenting activity by topical application was evaluated with standard compounds. This is a naturally occurring breed of swine with light brown to dark brown skin that is relatively hairless. The skin morphology, including the pattern of pigment distribution, in this breed of swine closely resembles the human skin. Test compounds examined in this study included the three standard compounds with known clinical depigmenting activity, hydroquinone (HQ), 4-hydroxyanisole (4HA) and tert-butyl catechol (TBC), each at a 5% concentration. Test materials in 25 microliters of propylene glycol/ethanol (50:50) were applied topically twice daily, 7 days a week for 90 days to test sites on each side of the dorsal mid-line. Test sites were graded weekly for variation in pigmentation and local irritation. After 90 days of test material application, skin biopsies of the test sites were taken for histological evaluation. Topical application of HQ, 4HA and TBC promoted marked skin depigmentation which was substantiated by reductions of pigment and melanocytes observed on microscopic examination. While both HQ and TBC produced marked local irritation, 4HA was only mildly irritating. These results suggest that the Yucatan pig, could be a potentially useful model for screening compounds with skin depigmenting activity.

Quest for consistent modelling of statistical decay of the compound nucleus

NASA Astrophysics Data System (ADS)

Banerjee, Tathagata; Nath, S.; Pal, Santanu

2018-01-01

A statistical model description of heavy ion induced fusion-fission reactions is presented where shell effects, collective enhancement of level density, tilting away effect of compound nuclear spin and dissipation are included. It is shown that the inclusion of all these effects provides a consistent picture of fission where fission hindrance is required to explain the experimental values of both pre-scission neutron multiplicities and evaporation residue cross-sections in contrast to some of the earlier works where a fission hindrance is required for pre-scission neutrons but a fission enhancement for evaporation residue cross-sections.

Evaluation of unsaturated-zone solute-transport models for studies of agricultural chemicals

USGS Publications Warehouse

Nolan, Bernard T.; Bayless, E. Randall; Green, Christopher T.; Garg, Sheena; Voss, Frank D.; Lampe, David C.; Barbash, Jack E.; Capel, Paul D.; Bekins, Barbara A.

2005-01-01

Of the models tested, RZWQM, HYDRUS2D, VS2DT, GLEAMS and PRZM had graphical user interfaces. Extensive documentation was available for RZWQM, HYDRUS2D, and VS2DT. RZWQM can explicitly simulate water and solute flux in macropores, and both HYDRUS2D and VS2DT can simulate water and solute flux in two dimensions. The version of RZWQM tested had a maximum simulation depth of 3 meters. The complex models simulate the formation, transport, and fate of degradates of up to three to five compounds including the parent, with the exception of VS2DT, which simulates the transport and fate of a single compound.

Prediction of pH-Dependent Hydrophobic Profiles of Small Molecules from Miertus-Scrocco-Tomasi Continuum Solvation Calculations.

PubMed

Zamora, William J; Curutchet, Carles; Campanera, Josep M; Luque, F Javier

2017-10-26

Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (P N ) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log P N values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (P I ). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.

Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

PubMed

Wicht, Kathryn J; Combrinck, Jill M; Smith, Peter J; Egan, Timothy J

2015-08-15

A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this respect, methods that allow such data to be used for virtual screening maximise efficiency and reduce costs. In this study both in vitro antimalarial activity and inhibitory data for β-haematin formation, largely obtained from publically available sources, has been used to develop Bayesian models for inhibitors of β-haematin formation and in vitro antimalarial activity. These models were used to screen two in silico compound libraries. In the first, the 1510 U.S. Food and Drug Administration approved drugs available on PubChem were ranked from highest to lowest Bayesian score based on a training set of β-haematin inhibiting compounds active against Plasmodium falciparum that did not include any of the clinical antimalarials or close analogues. The six known clinical antimalarials that inhibit β-haematin formation were ranked in the top 2.1% of compounds. Furthermore, the in vitro antimalarial hit-rate for this prioritised set of compounds was found to be 81% in the case of the subset where activity data are available in PubChem. In the second, a library of about 5000 commercially available compounds (Aldrich(CPR)) was virtually screened for ability to inhibit β-haematin formation and then for in vitro antimalarial activity. A selection of 34 compounds was purchased and tested, of which 24 were predicted to be β-haematin inhibitors. The hit rate for inhibition of β-haematin formation was found to be 25% and a third of these were active against P. falciparum, corresponding to enrichments estimated at about 25- and 140-fold relative to random screening, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Discovery of a Potent, Dual Serotonin and Norepinephrine Reuptake Inhibitor

PubMed Central

2013-01-01

The objective of the described research effort was to identify a novel serotonin and norepinephrine reuptake inhibitor (SNRI) with improved norepinephrine transporter activity and acceptable metabolic stability and exhibiting minimal drug–drug interaction. We describe herein the discovery of a series of 3-substituted pyrrolidines, exemplified by compound 1. Compound 1 is a selective SNRI in vitro and in vivo, has favorable ADME properties, and retains inhibitory activity in the formalin model of pain behavior. Compound 1 thus represents a potential new probe to explore utility of SNRIs in central nervous system disorders, including chronic pain conditions. PMID:24900709

Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method

NASA Astrophysics Data System (ADS)

Gee, Veronica M. W.; Wong, Fiona S. L.; Ramachandran, Lalitha; Sethi, Gautam; Kumar, Alan Prem; Yap, Chun Wei

2014-11-01

Peroxisome proliferator-activated receptor-gamma (PPARγ) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPARγ, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPARγ agonists from the ZINC library, and 10,000 of these were selected for docking with PPARγ based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 μM.

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds.

PubMed

de Jong, Maarten; Chen, Wei; Notestine, Randy; Persson, Kristin; Ceder, Gerbrand; Jain, Anubhav; Asta, Mark; Gamst, Anthony

2016-10-03

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

PubMed Central

de Jong, Maarten; Chen, Wei; Notestine, Randy; Persson, Kristin; Ceder, Gerbrand; Jain, Anubhav; Asta, Mark; Gamst, Anthony

2016-01-01

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials. PMID:27694824

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

DOE PAGES

de Jong, Maarten; Chen, Wei; Notestine, Randy; ...

2016-10-03

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. Themore » approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.« less

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Systems and methods for modeling and analyzing networks

DOEpatents

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

SAR studies on truxillic acid mono esters as a new class of antinociceptive agents targeting fatty acid binding proteins.

PubMed

Yan, Su; Elmes, Matthew W; Tong, Simon; Hu, Kongzhen; Awwa, Monaf; Teng, Gary Y H; Jing, Yunrong; Freitag, Matthew; Gan, Qianwen; Clement, Timothy; Wei, Longfei; Sweeney, Joseph M; Joseph, Olivia M; Che, Joyce; Carbonetti, Gregory S; Wang, Liqun; Bogdan, Diane M; Falcone, Jerome; Smietalo, Norbert; Zhou, Yuchen; Ralph, Brian; Hsu, Hao-Chi; Li, Huilin; Rizzo, Robert C; Deutsch, Dale G; Kaczocha, Martin; Ojima, Iwao

2018-05-24

Fatty acid binding proteins (FABPs) serve as critical modulators of endocannabinoid signaling by facilitating the intracellular transport of anandamide and whose inhibition potentiates anandamide signaling. Our previous work has identified a novel small-molecule FABP inhibitor, α-truxillic acid 1-naphthyl monoester (SB-FI-26, 3) that has shown efficacy as an antinociceptive and anti-inflammatory agent in rodent models. In the present work, we have performed an extensive SAR study on a series of 3-analogs as novel FABP inhibitors based on computer-aided inhibitor drug design and docking analysis, chemical synthesis and biological evaluations. The prediction of binding affinity of these analogs to target FABP3, 5 and 7 isoforms was performed using the AutoDock 4.2 program, using the recently determined co-crystal structures of 3 with FABP5 and FABP7. The compounds with high docking scores were synthesized and evaluated for their activities using a fluorescence displacement assay against FABP3, 5 and 7. During lead optimization, compound 3l emerged as a promising compound with the Ki value of 0.21 μM for FABP 5, 4-fold more potent than 3 (Ki, 0.81 μM). Nine compounds exhibit similar or better binding affinity than 3, including compounds 4b (Ki, 0.55 μM) and 4e (Ki, 0.68 μM). Twelve compounds are selective for FABP5 and 7 with >10 μM Ki values for FABP3, indicating a safe profile to avoid potential cardiotoxicity concerns. Compounds 4f, 4j and 4k showed excellent selectivity for FABP5 and would serve as other new lead compounds. Compound 3a possessed high affinity and high selectivity for FABP7. Compounds with moderate to high affinity for FABP5 displayed antinociceptive effects in mice while compounds with low FABP5 affinity lacked in vivo efficacy. In vivo pain model studies in mice revealed that exceeding hydrophobicity significantly affects the efficacy. Thus, among the compounds with high affinity to FABP5 in vitro, the compounds with moderate hydrophobicity were identified as promising new lead compounds for the next round of optimization, including compounds 4b and 4j. For select cases, computational analysis of the observed SAR, especially the selectivity of new inhibitors to particular FABP isoforms, by comparing docking poses, interaction map, and docking energy scores has provided useful insights. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

The DrugAge database of aging-related drugs.

PubMed

Barardo, Diogo; Thornton, Daniel; Thoppil, Harikrishnan; Walsh, Michael; Sharifi, Samim; Ferreira, Susana; Anžič, Andreja; Fernandes, Maria; Monteiro, Patrick; Grum, Tjaša; Cordeiro, Rui; De-Souza, Evandro Araújo; Budovsky, Arie; Araujo, Natali; Gruber, Jan; Petrascheck, Michael; Fraifeld, Vadim E; Zhavoronkov, Alexander; Moskalev, Alexey; de Magalhães, João Pedro

2017-06-01

Aging is a major worldwide medical challenge. Not surprisingly, identifying drugs and compounds that extend lifespan in model organisms is a growing research area. Here, we present DrugAge (http://genomics.senescence.info/drugs/), a curated database of lifespan-extending drugs and compounds. At the time of writing, DrugAge contains 1316 entries featuring 418 different compounds from studies across 27 model organisms, including worms, flies, yeast and mice. Data were manually curated from 324 publications. Using drug-gene interaction data, we also performed a functional enrichment analysis of targets of lifespan-extending drugs. Enriched terms include various functional categories related to glutathione and antioxidant activity, ion transport and metabolic processes. In addition, we found a modest but significant overlap between targets of lifespan-extending drugs and known aging-related genes, suggesting that some but not most aging-related pathways have been targeted pharmacologically in longevity studies. DrugAge is freely available online for the scientific community and will be an important resource for biogerontologists. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

A review of catalytic hydrodeoxygenation of lignin-derived phenols from biomass pyrolysis.

PubMed

Bu, Quan; Lei, Hanwu; Zacher, Alan H; Wang, Lu; Ren, Shoujie; Liang, Jing; Wei, Yi; Liu, Yupeng; Tang, Juming; Zhang, Qin; Ruan, Roger

2012-11-01

Catalytic hydrodeoxygenation (HDO) of lignin-derived phenols which are the lowest reactive chemical compounds in biomass pyrolysis oils has been reviewed. The hydrodeoxygenation (HDO) catalysts have been discussed including traditional HDO catalysts such as CoMo/Al(2)O(3) and NiMo/Al(2)O(3) catalysts and transition metal catalysts (noble metals). The mechanism of HDO of lignin-derived phenols was analyzed on the basis of different model compounds. The kinetics of HDO of different lignin-derived model compounds has been investigated. The diversity of bio-oils leads to the complexities of HDO kinetics. The techno-economic analysis indicates that a series of major technical and economical efforts still have to be investigated in details before scaling up the HDO of lignin-derived phenols in existed refinery infrastructure. Examples of future investigation of HDO include significant challenges of improving catalysts and optimum operation conditions, further understanding of kinetics of complex bio-oils, and the availability of sustainable and cost-effective hydrogen source. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clay for Little Fingers.

ERIC Educational Resources Information Center

Koster, Joan Bouza

1999-01-01

Discusses the renewed interest in clay as a modeling compound in early childhood programs; describes the nature of clay and presents a working vocabulary. Suggests methods of working with clay, including introducing clay to children, discovering its uses, clean up, firing clay, and finishing baked clay. Includes activity suggestions and…

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods.

PubMed

Legrain, Fleur; Carrete, Jesús; van Roekeghem, Ambroise; Madsen, Georg K H; Mingo, Natalio

2018-01-18

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD. The ML model is then employed to screen 71 178 different 1:1:1 compositions, yielding 481 likely stable candidates. The predicted stability of HH compounds from three previous high-throughput ab initio studies is critically analyzed from the perspective of the alternative ML approach. The incomplete consistency among the three separate ab initio studies and between them and the ML predictions suggests that additional factors beyond those considered by ab initio phase stability calculations might be determinant to the stability of the compounds. Such factors can include configurational entropies and quasiharmonic contributions.

Evaluation of Marijuana Compounds on Neuroimmune Endpoints in Experimental Autoimmune Encephalomyelitis.

PubMed

Kaplan, Barbara L F

2018-02-21

Cannabinoid compounds refer to a group of more than 60 plant-derived compounds in Cannabis sativa, more commonly known as marijuana. Exposure to marijuana and cannabinoid compounds has been increasing due to increased societal acceptance for both recreational and possible medical use. Cannabinoid compounds suppress immune function, and while this could compromise one's ability to fight infections, immune suppression is the desired effect for therapies for autoimmune diseases. It is critical, therefore, to understand the effects and mechanisms by which cannabinoid compounds alter immune function, especially immune responses induced in autoimmune disease. Therefore, this unit will describe induction and assessment of the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS), and its potential alteration by cannabinoid compounds. The unit includes three approaches to induce EAE, two of which provide correlations to two forms of MS, and the third specifically addresses the role of autoreactive T cells in EAE. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

PubMed Central

Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

2014-01-01

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Atmospheric transport of persistent organic pollutants - development of a 3-d dynamical transport model covering the northern hemisphere

NASA Astrophysics Data System (ADS)

Hansen, K. M.; Christensen, J. H.; Geels, C.; Frohn, L. M.; Brandt, J.

2003-04-01

The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur, lead, and mercury to the Arctic. The model has been validated carefully for these compounds. A new version of DEHM is currently being developed to describe the atmospheric transport of persistent organic pollutants (POPs) which are toxic, lipophilic and bio-accumulating compounds showing great persistence in the environment. The model has a horizontal resolution of 150 km x 150 km and 18 vertical layers, and it is driven by meteorological data from the numerical weather prediction model MM5V2. During environmental cycling POPs can be deposited and re-emitted several times before reaching a final destination. A description of the exchange processes between the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The present model version describes the atmospheric transport of the pesticide alpha-hexachlorocyclohexane (alpha-HCH). Other POPs may be included when proper data on emissions and physical-chemical parameters becomes available. The model-processes and the first model results are presented. The atmospheric transport of alpha-HCH for the 1990s is well described by the model.

A quantum chemical study of molecular properties and QSPR modeling of oximes, amidoximes and hydroxamic acids with nucleophilic activity against toxic organophosphorus agents

NASA Astrophysics Data System (ADS)

Alencar Filho, Edilson B.; Santos, Aline A.; Oliveira, Boaz G.

2017-04-01

The proposal of this work includes the use of quantum chemical methods and cheminformatics strategies in order to understand the structural profile and reactivity of α-nucleophiles compounds such as oximes, amidoximes and hydroxamic acids, related to hydrolysis rate of organophosphates. Theoretical conformational study of 41 compounds were carried out through the PM3 semiempirical Hamiltonian, followed by the geometry optimization at the B3LYP/6-31+G(d,p) level of theory, complemented by Polarized Continuum Model (PCM) to simulate the aqueous environment. In line with the experimental hypothesis about hydrolytic power, the strength of the Intramolecular Hydrogen Bonds (IHBs) at light of the Bader's Quantum Theory of Atoms in Molecules (QTAIM) is related to the preferential conformations of α-nucleophiles. A set of E-Dragon descriptors (1,666) were submitted to a variable selection through Ordered Predictor Selection (OPS) algorithm. Five descriptors, including atomic charges obtained from the Natural Bond Orbitals (NBO) protocol jointly with a fragment index associated to the presence/absence of IHBs, provided a Quantitative Structure-Property Relationship (QSPR) model via Multiple Linear Regression (MLR). This model showed good validation parameters (R2 = 0.80, Qloo2 = 0.67 and Qext2 = 0.81) and allowed the identification of significant physicochemical features on the molecular scaffold in order to design compounds potentially more active against organophosphorus poisoning.

Prediction of multi-target networks of neuroprotective compounds with entropy indices and synthesis, assay, and theoretical study of new asymmetric 1,2-rasagiline carbamates.

PubMed

Romero Durán, Francisco J; Alonso, Nerea; Caamaño, Olga; García-Mera, Xerardo; Yañez, Matilde; Prado-Prado, Francisco J; González-Díaz, Humberto

2014-09-24

In a multi-target complex network, the links (L(ij)) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K(i), K(m), IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Dermal uptake of phthalates from clothing: Comparison of model to human participant results.

PubMed

Morrison, G C; Weschler, C J; Bekö, G

2017-05-01

In this research, we extend a model of transdermal uptake of phthalates to include a layer of clothing. When compared with experimental results, this model better estimates dermal uptake of diethylphthalate and di-n-butylphthalate (DnBP) than a previous model. The model predictions are consistent with the observation that previously exposed clothing can increase dermal uptake over that observed in bare-skin participants for the same exposure air concentrations. The model predicts that dermal uptake from clothing of DnBP is a substantial fraction of total uptake from all sources of exposure. For compounds that have high dermal permeability coefficients, dermal uptake is increased for (i) thinner clothing, (ii) a narrower gap between clothing and skin, and (iii) longer time intervals between laundering and wearing. Enhanced dermal uptake is most pronounced for compounds with clothing-air partition coefficients between 10 4 and 10 7 . In the absence of direct measurements of cotton cloth-air partition coefficients, dermal exposure may be predicted using equilibrium data for compounds in equilibrium with cellulose and water, in combination with computational methods of predicting partition coefficients. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Lecithin:Cholesterol Acyltransferase Activation by Sulfhydryl-Reactive Small Molecules: Role of Cysteine-31

PubMed Central

Freeman, Lita A.; Demosky, Stephen J.; Konaklieva, Monika; Kuskovsky, Rostislav; Aponte, Angel; Ossoli, Alice F.; Gordon, Scott M.; Koby, Ross F.; Manthei, Kelly A.; Shen, Min; Vaisman, Boris L.; Shamburek, Robert D.; Jadhav, Ajit; Calabresi, Laura; Gucek, Marjan; Tesmer, John J.G.; Levine, Rodney L.

2017-01-01

Lecithin:cholesterol acyltransferase (LCAT) catalyzes plasma cholesteryl ester formation and is defective in familial lecithin:cholesterol acyltransferase deficiency (FLD), an autosomal recessive disorder characterized by low high-density lipoprotein, anemia, and renal disease. This study aimed to investigate the mechanism by which compound A [3-(5-(ethylthio)-1,3,4-thiadiazol-2-ylthio)pyrazine-2-carbonitrile], a small heterocyclic amine, activates LCAT. The effect of compound A on LCAT was tested in human plasma and with recombinant LCAT. Mass spectrometry and nuclear magnetic resonance were used to determine compound A adduct formation with LCAT. Molecular modeling was performed to gain insight into the effects of compound A on LCAT structure and activity. Compound A increased LCAT activity in a subset (three of nine) of LCAT mutations to levels comparable to FLD heterozygotes. The site-directed mutation LCAT-Cys31Gly prevented activation by compound A. Substitution of Cys31 with charged residues (Glu, Arg, and Lys) decreased LCAT activity, whereas bulky hydrophobic groups (Trp, Leu, Phe, and Met) increased activity up to 3-fold (P < 0.005). Mass spectrometry of a tryptic digestion of LCAT incubated with compound A revealed a +103.017 m/z adduct on Cys31, consistent with the addition of a single hydrophobic cyanopyrazine ring. Molecular modeling identified potential interactions of compound A near Cys31 and structural changes correlating with enhanced activity. Functional groups important for LCAT activation by compound A were identified by testing compound A derivatives. Finally, sulfhydryl-reactive β-lactams were developed as a new class of LCAT activators. In conclusion, compound A activates LCAT, including some FLD mutations, by forming a hydrophobic adduct with Cys31, thus providing a mechanistic rationale for the design of future LCAT activators. PMID:28576974

Cheminformatics Analysis of EPA ToxCast Chemical Libraries ...

EPA Pesticide Factsheets

An important goal of toxicology research is the development of robust methods that use in vitro and chemical structure information to predict in vivo toxicity endpoints. The US EPA ToxCast program is addressing this goal using ~600 in vitro assays to create bioactivity profiles on a set of 320 compounds, mostly pesticide actives, that have well characterized in vivo toxicity. These 320 compounds (EPA-320 set evaluated in Phase I of ToxCast) are a subset of a much larger set of ~10,000 candidates that are of interest to the EPA (called here EPA-10K). Predictive models of in vivo toxicity are being constructed from the in vitro assay data on the EPA-320 chemical set. These models require validation on additional chemicals prior to wide acceptance, and this will be carried out by evaluating compounds from EPA-10K in Phase II of ToxCast. We have used cheminformatics approaches including clustering, data visualization, and QSAR to develop models for EPA-320 that could help prioritizing EPA-10K validation chemicals. Both chemical descriptors, as well as calculated physicochemical properties have been used. Compounds from EPA-10K are prioritized based on their similarity to EPA-320 using different similarity metrics, with similarity thresholds defining the domain of applicability for the predictive models built for EPA-320 set. In addition, prioritized lists of compounds of increasing dissimilarity from the EPA-320 have been produced, to test the ability of the EPA-320

Novel Vitamin K analogs suppress seizures in zebrafish and mouse models of epilepsy.

PubMed

Rahn, J J; Bestman, J E; Josey, B J; Inks, E S; Stackley, K D; Rogers, C E; Chou, C J; Chan, S S L

2014-02-14

Epilepsy is a debilitating disease affecting 1-2% of the world's population. Despite this high prevalence, 30% of patients suffering from epilepsy are not successfully managed by current medication suggesting a critical need for new anti-epileptic drugs (AEDs). In an effort to discover new therapeutics for the management of epilepsy, we began our study by screening drugs that, like some currently used AEDs, inhibit histone deacetylases (HDACs) using a well-established larval zebrafish model. In this model, 7-day post fertilization (dpf) larvae are treated with the widely used seizure-inducing compound pentylenetetrazol (PTZ) which stimulates a rapid increase in swimming behavior previously determined to be a measurable manifestation of seizures. In our first screen, we tested a number of different HDAC inhibitors and found that one, 2-benzamido-1 4-naphthoquinone (NQN1), significantly decreased swim activity to levels equal to that of valproic acid, 2-n-propylpentanoic acid (VPA). We continued to screen structurally related compounds including Vitamin K3 (VK3) and a number of novel Vitamin K (VK) analogs. We found that VK3 was a robust inhibitor of the PTZ-induced swim activity, as were several of our novel compounds. Three of these compounds were subsequently tested on mouse seizure models at the National Institute of Neurological Disorders and Stroke (NINDS) Anticonvulsant Screening Program. Compound 2h reduced seizures particularly well in the minimal clonic seizure (6Hz) and corneal-kindled mouse models of epilepsy, with no observable toxicity. As VK3 affects mitochondrial function, we tested the effects of our compounds on mitochondrial respiration and ATP production in a mouse hippocampal cell line. We demonstrate that these compounds affect ATP metabolism and increase total cellular ATP. Our data indicate the potential utility of these and other VK analogs for the prevention of seizures and suggest the potential mechanism for this protection may lie in the ability of these compounds to affect energy production. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Global simulation of aromatic volatile organic compounds in the atmosphere

NASA Astrophysics Data System (ADS)

Cabrera Perez, David; Taraborrelli, Domenico; Pozzer, Andrea

2015-04-01

Among the large number of chemical compounds in the atmosphere, the organic group plays a key role in the tropospheric chemistry. Specifically the subgroup called aromatics is of great interest. Aromatics are the predominant trace gases in urban areas due to high emissions, primarily by vehicle exhausts and fuel evaporation. They are also present in areas where biofuel is used (i.e residential wood burning). Emissions of aromatic compounds are a substantial fraction of the total emissions of the volatile organic compounds (VOC). Impact of aromatics on human health is very important, as they do not only contribute to the ozone formation in the urban environment, but they are also highly toxic themselves, especially in the case of benzene which is able to trigger a range of illness under long exposure, and of nitro-phenols which cause detrimental for humans and vegetation even at very low concentrations. The aim of this work is to assess the atmospheric impacts of aromatic compounds on the global scale. The main goals are: lifetime and budget estimation, mixing ratios distribution, net effect on ozone production and OH loss for the most emitted aromatic compounds (benzene, toluene, xylenes, ethylbenzene, styrene and trimethylbenzenes). For this purpose, we use the numerical chemistry and climate simulation ECHAM/MESSy Atmospheric Chemistry (EMAC) model to build the global atmospheric budget for the most emitted and predominant aromatic compounds in the atmosphere. A set of emissions was prepared in order to include biomass burning, vegetation and anthropogenic sources of aromatics into the model. A chemical mechanism based on the Master Chemical Mechanism (MCM) was developed to describe the chemical oxidation in the gas phase of these aromatic compounds. MCM have been reduced in terms of number of chemical equation and species in order to make it affordable in a 3D model. Additionally other features have been added, for instance the production of HONO via ortho-nitrophenols photolysis. The model results are compared with observations from different surface and aircraft campaigns in order to estimate the accuracy of the model.

Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models

PubMed Central

Basheer, Loai; Schultz, Keren; Kerem, Zohar

2016-01-01

Many dietary compounds, including resveratrol, are potent inhibitors of CYP3A4. Here we examined the potential to predict inhibition capacity of dietary polyphenolics using an in silico and in vitro approaches and synthetic model compounds. Mono, di, and tri-acetoxy resveratrol were synthesized, a cell line of human intestine origin and microsomes from rat liver served to determine their in vitro inhibition of CYP3A4, and compared to that of resveratrol. Docking simulation served to predict the affinity of the synthetic model compounds to the enzyme. Modelling of the enzyme’s binding site revealed three types of interaction: hydrophobic, electrostatic and H-bonding. The simulation revealed that each of the examined acetylations of resveratrol led to the loss of important interactions of all types. Tri-acetoxy resveratrol was the weakest inhibitor in vitro despite being the more lipophilic and having the highest affinity for the binding site. The simulation demonstrated exclusion of all interactions between tri-acetoxy resveratrol and the heme due to distal binding, highlighting the complexity of the CYP3A4 binding site, which may allow simultaneous accommodation of two molecules. Finally, the use of computational modelling may serve as a quick predictive tool to identify potential harmful interactions between dietary compounds and prescribed drugs. PMID:27530542

StreamVOC - A deterministic source-apportionment model to estimate volatile organic compound concentrations in rivers and streams

USGS Publications Warehouse

Asher, William E.; Bender, David A.; Zogorski, John S.; Bartholomay, Roy C.

2006-01-01

This report documents the construction and verification of the model, StreamVOC, that estimates (1) the time- and position-dependent concentrations of volatile organic compounds (VOCs) in rivers and streams as well as (2) the source apportionment (SA) of those concentrations. The model considers how different types of sources and loss processes can act together to yield a given observed VOC concentration. Reasons for interest in the relative and absolute contributions of different sources to contaminant concentrations include the need to apportion: (1) the origins for an observed contamination, and (2) the associated human and ecosystem risks. For VOCs, sources of interest include the atmosphere (by absorption), as well as point and nonpoint inflows of VOC-containing water. Loss processes of interest include volatilization to the atmosphere, degradation, and outflows of VOC-containing water from the stream to local ground water. This report presents the details of StreamVOC and compares model output with measured concentrations for eight VOCs found in the Aberjona River at Winchester, Massachusetts. Input data for the model were obtained during a synoptic study of the stream system conducted July 11-13, 2001, as part of the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey. The input data included a variety of basic stream characteristics (for example, flows, temperature, and VOC concentrations). The StreamVOC concentration results agreed moderately well with the measured concentration data for several VOCs and provided compound-dependent SA estimates as a function of longitudinal distance down the river. For many VOCs, the quality of the agreement between the model-simulated and measured concentrations could be improved by simple adjustments of the model input parameters. In general, this study illustrated: (1) the considerable difficulty of quantifying correctly the locations and magnitudes of ground-water-related sources of contamination in streams; and (2) that model-based estimates of stream VOC concentrations are likely to be most accurate when the major sources are point sources or tributaries where the spatial extent and magnitude of the sources are tightly constrained and easily determined.

Structure-activity relationship of antiparasitic and cytotoxic indoloquinoline alkaloids, and their tricyclic and bicyclic analogues.

PubMed

Van Baelen, Gitte; Hostyn, Steven; Dhooghe, Liene; Tapolcsányi, Pál; Mátyus, Péter; Lemière, Guy; Dommisse, Roger; Kaiser, Marcel; Brun, Reto; Cos, Paul; Maes, Louis; Hajós, György; Riedl, Zsuzsanna; Nagy, Ildikó; Maes, Bert U W; Pieters, Luc

2009-10-15

Based on the indoloquinoline alkaloids cryptolepine (1), neocryptolepine (2), isocryptolepine (3) and isoneocryptolepine (4), used as lead compounds for new antimalarial agents, a series of tricyclic and bicyclic analogues, including carbolines, azaindoles, pyrroloquinolines and pyrroloisoquinolines was synthesized and biologically evaluated. None of the bicyclic compounds was significantly active against the chloroquine-resistant strain Plasmodium falciparum K1, in contrast to the tricyclic derivatives. The tricyclic compound 2-methyl-2H-pyrido[3,4-b]indole (9), or 2-methyl-beta-carboline, showed the best in vitro activity, with an IC(50) value of 0.45 microM against P. falciparum K1, without apparent cytotoxicity against L6 cells (SI>1000). However, this compound was not active in the Plasmodium berghei mouse model. Structure-activity relationships are discussed and compared with related naturally occurring compounds.

Evaluation of land use regression models (LURs) for nitrogen dioxide and benzene in four U.S. Cities.

EPA Science Inventory

Spatial analysis studies have included application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks ...

Modeling the effect of snow and ice on the global environmental fate and long-range transport potential of semivolatile organic compounds.

PubMed

Stocker, Judith; Scheringer, Martin; Wegmann, Fabio; Hungerbuhler, Konrad

2007-09-01

Snow and ice have been implemented in a global multimedia box model to investigate the influence of these media on the environmental fate and long-range transport (LRT) of semivolatile organic compounds (SOCs). Investigated compounds include HCB, PCB28, PCB180, PBDE47, PBDE209, alpha-HCH, and dacthal. In low latitudes, snow acts as a transfer medium taking up chemicals from air and releasing them to water or soil during snowmelt. In high latitudes, snow and ice shield water, soil, and vegetation from chemical deposition. In the model version including snow and ice (scenario 2), the mass of chemicals in soil in high latitudes is between 27% (HCB) and 97% (alpha-HCH) of the mass calculated with the model version without snow and ice (scenario 1). Amounts in Arctic seawater in scenario 2 are 8% (alpha-HCH) to 21% (dacthal) of the amounts obtained in scenario 1. For all investigated chemicals except alpha-HCH, presence of snow and ice in the model increases the concentration in air by a factor of 2 (HCB)to 10 (PBDE209). Because of reduced net deposition to snow-covered surfaces in high latitudes, LRT to the Arctic is reduced for most chemicals whereas transport to the south is more pronounced than in scenario 1 ("southward shift"). The presence of snow and ice thus considerably changes the environmental fate of SOCs.

Design, synthesis, biological evaluation, and molecular modeling studies of chalcone-rivastigmine hybrids as cholinesterase inhibitors.

PubMed

Wang, Ling; Wang, Yu; Tian, Yiguang; Shang, Jinling; Sun, Xiaoou; Chen, Hongzhuan; Wang, Hao; Tan, Wen

2017-01-01

A series of novel chalcone-rivastigmine hybrids were designed, synthesized, and tested in vitro for their ability to inhibit human acetylcholinesterase and butyrylcholinesterase. Most of the target compounds showed hBChE selective activity in the micro- and submicromolar ranges. The most potent compound 3 exhibited comparable IC 50 to the commercially available drug (rivastigmine). To better understand their structure activity relationships (SAR) and mechanisms of enzyme-inhibitor interactions, kinetic and molecular modeling studies including molecular docking and molecular dynamics (MD) simulations were carried out. Furthermore, compound 3 blocks the formation of reactive oxygen species (ROS) in SH-SY5Y cells and shows the required druggability and low cytotoxicity, suggesting this hybrid is a promising multifunctional drug candidate for Alzheimer's disease (AD) treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Unusual mode of protein binding by a cytotoxic π-arene ruthenium(ii) piano-stool compound containing an O,S-chelating ligand.

PubMed

Hildebrandt, Jana; Görls, Helmar; Häfner, Norman; Ferraro, Giarita; Dürst, Matthias; Runnebaum, Ingo B; Weigand, Wolfgang; Merlino, Antonello

2016-08-02

A new pseudo-octahedral π-arene ruthenium(ii) piano-stool compound, containing an O,S-bidentate ligand (compound 1) and showing significant cytotoxic activity in vitro, was synthesized and characterized. In solution stability and interaction with the model protein bovine pancreatic ribonuclease (RNase A) were investigated by using UV-Vis absorption spectroscopy. Its crystal structure and that of the adduct formed upon reaction with RNase A were obtained by X-ray crystallography. The comparison between the structure of purified compound 1 and that of the fragment bound to RNase A reveals an unusual mode of protein binding that includes ligand exchange and alteration of coordination sphere geometry.

Modeling Free Energies of Solvation in Olive Oil

PubMed Central

Chamberlin, Adam C.; Levitt, David G.; Cramer, Christopher J.; Truhlar, Donald G.

2009-01-01

Olive oil partition coefficients are useful for modeling the bioavailability of drug-like compounds. We have recently developed an accurate solvation model called SM8 for aqueous and organic solvents (Marenich, A. V.; Olson, R. M.; Kelly, C. P.; Cramer, C. J.; Truhlar, D. G. J. Chem. Theory Comput. 2007, 3, 2011) and a temperature-dependent solvation model called SM8T for aqueous solution (Chamberlin, A. C.; Cramer, C. J.; Truhlar, D. G. J. Phys. Chem. B 2008, 112, 3024). Here we describe an extension of SM8T to predict air–olive oil and water–olive oil partitioning for drug-like solutes as functions of temperature. We also describe the database of experimental partition coefficients used to parameterize the model; this database includes 371 entries for 304 compounds spanning the 291–310 K temperature range. PMID:19434923

Modeling Organochlorine Compounds and the σ-Hole Effect Using a Polarizable Multipole Force Field

PubMed Central

2015-01-01

The charge distribution of halogen atoms on organochlorine compounds can be highly anisotropic and even display a so-called σ-hole, which leads to strong halogen bonds with electron donors. In this paper, we have systematically investigated a series of chloromethanes with one to four chloro substituents using a polarizable multipole-based molecular mechanics model. The atomic multipoles accurately reproduced the ab initio electrostatic potential around chloromethanes, including CCl4, which has a prominent σ-hole on the Cl atom. The van der Waals parameters for Cl were fitted to the experimental density and heat of vaporization. The calculated hydration free energy, solvent reaction fields, and interaction energies of several homo- and heterodimer of chloromethanes are in good agreement with experimental and ab initio data. This study suggests that sophisticated electrostatic models, such as polarizable atomic multipoles, are needed for accurate description of electrostatics in organochlorine compounds and halogen bonds, although further improvement is necessary for better transferability. PMID:24484473

Modelling of human transplacental transport as performed in Copenhagen, Denmark.

PubMed

Mathiesen, Line; Mørck, Thit Aarøe; Zuri, Giuseppina; Andersen, Maria Helena; Pehrson, Caroline; Frederiksen, Marie; Mose, Tina; Rytting, Erik; Poulsen, Marie S; Nielsen, Jeanette K S; Knudsen, Lisbeth E

2014-07-01

Placenta perfusion models are very effective when studying the placental mechanisms in order to extrapolate to real-life situations. The models are most often used to investigate the transport of substances between mother and foetus, including the potential metabolism of these. We have studied the relationships between maternal and foetal exposures to various compounds including pollutants such as polychlorinated biphenyls, polybrominated flame retardants, nanoparticles as well as recombinant human antibodies. The compounds have been studied in the human placenta perfusion model and to some extent in vitro with an established human monolayer trophoblast cell culture model. Results from our studies distinguish placental transport of substances by physicochemical properties, adsorption to placental tissue, binding to transport and receptor proteins and metabolism. We have collected data from different classes of chemicals and nanoparticles for comparisons across chemical structures as well as different test systems. Our test systems are based on human material to bypass the extrapolation from animal data. By combining data from our two test systems, we are able to rank and compare the transport of different classes of substances according to their transport ability. Ultimately, human data including measurements in cord blood contribute to the study of placental transport. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

The Involvement of Morphological Information in the Memorization of Chinese Compound Words: Evidence from Memory Errors.

PubMed

Liu, Duo

2016-02-01

The processing of morphological information during Chinese word memorization was investigated in the present study. Participants were asked to study words presented to them on a computer screen in the studying phase and then judge whether presented words were old or new in the test phase. In addition to parent words (i.e. the words studied in the study phase), the test phase also included conjunction lures (constructed out of morphemes in the parent words) and new words (constructed out of entirely new morphemes). Three kinds of words (i.e. subordinate compounds, coordinative compounds, and single-morpheme words) were involved. In both two experiments, performance on lures worsened when both parent words and lures were coordinative compounds, compared to the condition when both were subordinate compounds. The different performance between compounds with different compounding structures in the test phase suggests the involvement of morphological information in the memorization of Chinese compound words. The spreading activation theory for memory and the interactive activation model for the processing of morphologically complex words were referred to for interpreting the results.

Chemistry Notes.

ERIC Educational Resources Information Center

School Science Review, 1981

1981-01-01

Describes 13 activities, experiments and demonstrations, including the preparation of iron (III) chloride, simple alpha-helix model, investigating camping gas, redox reactions of some organic compounds, a liquid crystal thermometer, and the oxidation number concept in organic chemistry. (JN)

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm

PubMed Central

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request. PMID:26955638

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

Plant phenolics and their potential role in mitigating iron overload disorder in wild animals.

PubMed

Lavin, Shana R

2012-09-01

Phenolic compounds are bioactive chemicals found in all vascular plants but are difficult to characterize and quantify, and comparative analyses on these compounds are challenging due to chemical structure complexity and inconsistent laboratory methodologies employed historically. These chemicals can elicit beneficial or toxic effects in consumers, depending on the compound, dose and the species of the consumer. In particular, plant phenolic compounds such as tannins can reduce the utilization of iron in mammalian and avian consumers. Multiple zoo-managed wild animal species are sensitive to iron overload, and these species tend to be offered diets higher in iron than most of the plant browse consumed by these animals in the wild and in captivity. Furthermore, these animals likely consume diets higher in polyphenols in the wild as compared with in managed settings. Thus, in addition to reducing dietary iron concentrations in captivity, supplementing diets with phenolic compounds capable of safely chelating iron in the intestinal lumen may reduce the incidence of iron overload in these animal species. It is recommended to investigate various sources and types of phenolic compounds for use in diets intended for iron-sensitive species. Candidate compounds should be screened both in vitro and in vivo using model species to reduce the risk of toxicity in target species. In particular, it would be important to assess potential compounds in terms of 1) biological activity including iron-binding capacity, 2) accessibility, 3) palatability, and 4) physiological effects on the consumer, including changes in nutritional and antioxidant statuses.

Modeling the gas-phase thermochemistry of organosulfur compounds.

PubMed

Vandeputte, Aäron G; Sabbe, Maarten K; Reyniers, Marie-Françoise; Marin, Guy B

2011-06-27

Key to understanding the involvement of organosulfur compounds in a variety of radical chemistries, such as atmospheric chemistry, polymerization, pyrolysis, and so forth, is knowledge of their thermochemical properties. For organosulfur compounds and radicals, thermochemical data are, however, much less well documented than for hydrocarbons. The traditional recourse to the Benson group additivity method offers no solace since only a very limited number of group additivity values (GAVs) is available. In this work, CBS-QB3 calculations augmented with 1D hindered rotor corrections for 122 organosulfur compounds and 45 organosulfur radicals were used to derive 93 Benson group additivity values, 18 ring-strain corrections, 2 non-nearest-neighbor interactions, and 3 resonance corrections for standard enthalpies of formation, standard molar entropies, and heat capacities for organosulfur compounds and organosulfur radicals. The reported GAVs are consistent with previously reported GAVs for hydrocarbons and hydrocarbon radicals and include 77 contributions, among which 26 radical contributions, which, to the best of our knowledge, have not been reported before. The GAVs allow one to estimate the standard enthalpies of formation at 298 K, the standard entropies at 298 K, and standard heat capacities in the temperature range 300-1500 K for a large set of organosulfur compounds, that is, thiols, thioketons, polysulfides, alkylsulfides, thials, dithioates, and cyclic sulfur compounds. For a validation set of 26 organosulfur compounds, the mean absolute deviation between experimental and group additively modeled enthalpies of formation amounts to 1.9  kJ  mol(-1). For an additional set of 14 organosulfur compounds, it was shown that the mean absolute deviations between calculated and group additively modeled standard entropies and heat capacities are restricted to 4 and 2 J  mol(-1)  K(-1), respectively. As an alternative to Benson GAVs, 26 new hydrogen-bond increments are reported, which can also be useful for the prediction of radical thermochemistry. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The use of high-throughput screening techniques to evaluate mitochondrial toxicity.

PubMed

Wills, Lauren P

2017-11-01

Toxicologists and chemical regulators depend on accurate and effective methods to evaluate and predict the toxicity of thousands of current and future compounds. Robust high-throughput screening (HTS) experiments have the potential to efficiently test large numbers of chemical compounds for effects on biological pathways. HTS assays can be utilized to examine chemical toxicity across multiple mechanisms of action, experimental models, concentrations, and lengths of exposure. Many agricultural, industrial, and pharmaceutical chemicals classified as harmful to human and environmental health exert their effects through the mechanism of mitochondrial toxicity. Mitochondrial toxicants are compounds that cause a decrease in the number of mitochondria within a cell, and/or decrease the ability of mitochondria to perform normal functions including producing adenosine triphosphate (ATP) and maintaining cellular homeostasis. Mitochondrial dysfunction can lead to apoptosis, necrosis, altered metabolism, muscle weakness, neurodegeneration, decreased organ function, and eventually disease or death of the whole organism. The development of HTS techniques to identify mitochondrial toxicants will provide extensive databases with essential connections between mechanistic mitochondrial toxicity and chemical structure. Computational and bioinformatics approaches can be used to evaluate compound databases for specific chemical structures associated with toxicity, with the goal of developing quantitative structure-activity relationship (QSAR) models and mitochondrial toxicophores. Ultimately these predictive models will facilitate the identification of mitochondrial liabilities in consumer products, industrial compounds, pharmaceuticals and environmental hazards. Copyright © 2017 Elsevier B.V. All rights reserved.

Benefits of polidocanol endovenous microfoam (Varithena®) compared with physician-compounded foams

PubMed Central

Carugo, Dario; Ankrett, Dyan N; Zhao, Xuefeng; Zhang, Xunli; Hill, Martyn; O’Byrne, Vincent; Hoad, James; Arif, Mehreen; Wright, David DI

2015-01-01

Objective To compare foam bubble size and bubble size distribution, stability, and degradation rate of commercially available polidocanol endovenous microfoam (Varithena®) and physician-compounded foams using a number of laboratory tests. Methods Foam properties of polidocanol endovenous microfoam and physician-compounded foams were measured and compared using a glass-plate method and a Sympatec QICPIC image analysis method to measure bubble size and bubble size distribution, Turbiscan™ LAB for foam half time and drainage and a novel biomimetic vein model to measure foam stability. Physician-compounded foams composed of polidocanol and room air, CO2, or mixtures of oxygen and carbon dioxide (O2:CO2) were generated by different methods. Results Polidocanol endovenous microfoam was found to have a narrow bubble size distribution with no large (>500 µm) bubbles. Physician-compounded foams made with the Tessari method had broader bubble size distribution and large bubbles, which have an impact on foam stability. Polidocanol endovenous microfoam had a lower degradation rate than any physician-compounded foams, including foams made using room air (p < 0.035). The same result was obtained at different liquid to gas ratios (1:4 and 1:7) for physician-compounded foams. In all tests performed, CO2 foams were the least stable and different O2:CO2 mixtures had intermediate performance. In the biomimetic vein model, polidocanol endovenous microfoam had the slowest degradation rate and longest calculated dwell time, which represents the length of time the foam is in contact with the vein, almost twice that of physician-compounded foams using room air and eight times better than physician-compounded foams prepared using equivalent gas mixes. Conclusion Bubble size, bubble size distribution and stability of various sclerosing foam formulations show that polidocanol endovenous microfoam results in better overall performance compared with physician-compounded foams. Polidocanol endovenous microfoam offers better stability and cohesive properties in a biomimetic vein model compared to physician-compounded foams. Polidocanol endovenous microfoam, which is indicated in the United States for treatment of great saphenous vein system incompetence, provides clinicians with a consistent product with enhanced handling properties. PMID:26036246

Benefits of polidocanol endovenous microfoam (Varithena®) compared with physician-compounded foams.

PubMed

Carugo, Dario; Ankrett, Dyan N; Zhao, Xuefeng; Zhang, Xunli; Hill, Martyn; O'Byrne, Vincent; Hoad, James; Arif, Mehreen; Wright, David D I; Lewis, Andrew L

2016-05-01

To compare foam bubble size and bubble size distribution, stability, and degradation rate of commercially available polidocanol endovenous microfoam (Varithena®) and physician-compounded foams using a number of laboratory tests. Foam properties of polidocanol endovenous microfoam and physician-compounded foams were measured and compared using a glass-plate method and a Sympatec QICPIC image analysis method to measure bubble size and bubble size distribution, Turbiscan™ LAB for foam half time and drainage and a novel biomimetic vein model to measure foam stability. Physician-compounded foams composed of polidocanol and room air, CO2, or mixtures of oxygen and carbon dioxide (O2:CO2) were generated by different methods. Polidocanol endovenous microfoam was found to have a narrow bubble size distribution with no large (>500 µm) bubbles. Physician-compounded foams made with the Tessari method had broader bubble size distribution and large bubbles, which have an impact on foam stability. Polidocanol endovenous microfoam had a lower degradation rate than any physician-compounded foams, including foams made using room air (p < 0.035). The same result was obtained at different liquid to gas ratios (1:4 and 1:7) for physician-compounded foams. In all tests performed, CO2 foams were the least stable and different O2:CO2 mixtures had intermediate performance. In the biomimetic vein model, polidocanol endovenous microfoam had the slowest degradation rate and longest calculated dwell time, which represents the length of time the foam is in contact with the vein, almost twice that of physician-compounded foams using room air and eight times better than physician-compounded foams prepared using equivalent gas mixes. Bubble size, bubble size distribution and stability of various sclerosing foam formulations show that polidocanol endovenous microfoam results in better overall performance compared with physician-compounded foams. Polidocanol endovenous microfoam offers better stability and cohesive properties in a biomimetic vein model compared to physician-compounded foams. Polidocanol endovenous microfoam, which is indicated in the United States for treatment of great saphenous vein system incompetence, provides clinicians with a consistent product with enhanced handling properties. © The Author(s) 2015.

Final Report: Process Models of the Equilibrium Size & State of Organic/Inorganic Aerosols for the Development of Large Scale Atmospheric Models & the Analysis of Field Data

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

Wexler, Anthony Stein; Clegg, Simon Leslie

2013-10-26

Our work addressed the following elements of the Call for Proposals: (i) “to improve the theoretical representation of aerosol processes studied in ASP laboratory or field studies”, (ii) “to enhance the incorporation of aerosol process information into modules suitable for large-scale or global atmospheric models”, and (iii) “provide systematic experimental validation of process model predictions ... using data from targeted laboratory and field experiments”. Achievements to the end of 2012 are described in four previous reports, and include: new models of densities and surface tensions of pure (single solute) and mixed aqueous solutions of typical aerosol composition under all atmosphericmore » conditions (0 to 100% RH and T > 150 K); inclusion of these models into the widely used Extended Aerosol Inorganics model (E-AIM, http://www.aim.env.uea.ac.uk/aim/aim.php); the addition of vapor pressure calculators for organic compounds to the E-AIM website; the ability of include user-defined organic compounds and/or lumped surrogates in gas/aerosol partitioning calculations; the development of new equations to represent the properties of soluble aerosols over the entire concentration range (using methods based upon adsorption isotherms, and derived using statistical mechanics), including systems at close to zero RH. These results are described in publications 1-6 at the end of this report, and on the “News” page of the E-AIM website (http://www.aim.env.uea.ac.uk/aim/info/news.html). During 2012 and 2013 we have collaborated in a combined observation and lab-based study of the water uptake of the organic component of atmospheric aerosols (PI Gannet Hallar, of the Desert Research Institute). The aerosol samples were analyzed using several complementary techniques (GC/MS, FT-ICR MS, and ion chromatography) to produce a very complete organic “speciation” including both polar and non-polar compounds. Hygroscopic growth factors of the samples were measured, and we have just completed comparisons of the data with our process model predictions based upon the inorganic and organic composition of the samples.« less

Effects of Gas-Wall Partitioning in Teflon Tubing, Instrumentation and Other Materials on Time-Resolved Measurements of Gas-Phase Organic Compounds

NASA Astrophysics Data System (ADS)

Pagonis, D.; Deming, B.; Krechmer, J. E.; De Gouw, J. A.; Jimenez, J. L.; Ziemann, P. J.

2017-12-01

Recently it has been shown that gas-phase organic compounds partition to and from the walls of Teflon environmental chambers. This process is fast, reversible, and can be modeled as absorptive partitioning. Here these studies were extended to investigate gas-wall partitioning inside Teflon tubing by introducing step function changes in the concentration of compounds being sampled and measuring the delay in the response of a proton transfer reaction-mass spectrometer (PTR-MS). We find that these delays are significant for compounds with a saturation vapor concentration (c*) below 106 μg m-3, and that the Teflon tubing and the PTR-MS both contribute to the delays. Tubing delays range from minutes to hours under common sampling conditions and can be accurately predicted by a simple chromatography model across a range of tubing lengths and diameters, flow rates, compound functional groups, and c*. This method also allows one to determine the volatility-dependent response function of an instrument, which can be convolved with the output of the tubing model to correct for delays in instrument response time for these "sticky" compounds. This correction is expected to be of particular interest to researchers utilizing and developing chemical ionization mass spectrometry (CIMS) techniques, since many of the multifunctional organic compounds detected by CIMS show significant tubing and instrument delays. These results also enable better design of sampling systems, in particular when fast instrument response is needed, such as for rapid transients, aircraft, or eddy covariance measurements. Additional results presented here extend this method to quantify the relative sorptive capacities for other commonly used tubing materials, including PFA, FEP, PTFE, PEEK, glass, copper, stainless steel, and passivated steel.

Gas-phase organics in environmental tobacco smoke. 1. Effects of smoking rate, ventilation, and furnishing level on emission factors.

PubMed

Singer, Brett C; Hodgson, Alfred T; Guevarra, Karla S; Hawley, Elisabeth L; Nazaroff, William W

2002-03-01

We measured the emissions of 26 gas-phase organic compounds in environmental tobacco smoke (ETS) using a model room that simulates realistic conditions in residences and offices. Exposure-relevant emission factors (EREFs), which include the effects of sorption and re-emission over a 24-h period, were calculated by mass balance from measured compound concentrations and chamber ventilation rates in a 50-m3 room constructed and furnished with typical materials. Experiments were conducted at three smoking rates (5, 10, and 20 cigarettes day(-1)), three ventilation rates (0.3, 0.6, and 2 h(-1)), and three furnishing levels (wallboard with aluminum flooring, wallboard with carpet, and full furnishings). Smoking rate did not affect EREFs, suggesting that sorption was linearly related to gas-phase concentration. Furnishing level and ventilation rate in the model room had little effect on EREFs of several ETS compounds including 1,3-butadiene, acrolein, acrylonitrile, benzene, toluene, and styrene. However, sorptive losses at low ventilation with full furnishings reduced EREFs for the ETS tracers nicotine and 3-ethenylpyridine by as much as 90 and 65% as compared to high ventilation, wallboard/aluminum experiments. Likewise, sorptive losses were 40-70% for phenol, cresols, naphthalene, and methylnaphthalenes. Sorption persisted for many compounds; for example, almost all of the sorbed nicotine and most of the sorbed cresol remained sorbed 3 days after smoking. EREFs can be used in models and with ETS tracer-based methods to refine and improve estimates of exposures to ETS constituents.

Probabilistic neural networks modeling of the 48-h LC50 acute toxicity endpoint to Daphnia magna.

PubMed

Niculescu, S P; Lewis, M A; Tigner, J

2008-01-01

Two modeling experiments based on the maximum likelihood estimation paradigm and targeting prediction of the Daphnia magna 48-h LC50 acute toxicity endpoint for both organic and inorganic compounds are reported. The resulting models computational algorithms are implemented as basic probabilistic neural networks with Gaussian kernel (statistical corrections included). The first experiment uses strictly D. magna information for 971 structures as training/learning data and the resulting model targets practical applications. The second experiment uses the same training/learning information plus additional data on another 29 compounds whose endpoint information is originating from D. pulex and Ceriodaphnia dubia. It only targets investigation of the effect of mixing strictly D. magna 48-h LC50 modeling information with small amounts of similar information estimated from related species, and this is done as part of the validation process. A complementary 81 compounds dataset (involving only strictly D. magna information) is used to perform external testing. On this external test set, the Gaussian character of the distribution of the residuals is confirmed for both models. This allows the use of traditional statistical methodology to implement computation of confidence intervals for the unknown measured values based on the models predictions. Examples are provided for the model targeting practical applications. For the same model, a comparison with other existing models targeting the same endpoint is performed.

Preliminary model and validation of molten carbonate fuel cell kinetics under sulphur poisoning

NASA Astrophysics Data System (ADS)

Audasso, E.; Nam, S.; Arato, E.; Bosio, B.

2017-06-01

MCFC represents an effective technology to deal with CO2 capture and relative applications. If used for these purposes, due to the working conditions and the possible feeding, MCFC must cope with a different number of poisoning gases such as sulphur compounds. In literature, different works deal with the development of kinetic models to describe MCFC performance to help both industrial applications and laboratory simulations. However, in literature attempts to realize a proper model able to consider the effects of poisoning compounds are scarce. The first aim of the present work is to provide a semi-empirical kinetic formulation capable to take into account the effects that sulphur compounds (in particular SO2) have on the MCFC performance. The second aim is to provide a practical example of how to effectively include the poisoning effects in kinetic models to simulate fuel cells performances. To test the reliability of the proposed approach, the obtained formulation is implemented in the kinetic core of the SIMFC (SIMulation of Fuel Cells) code, an MCFC 3D model realized by the Process Engineering Research Team (PERT) of the University of Genova. Validation is performed through data collected at the Korea Institute of Science and Technology in Seoul.

Modeling the Gas Nitriding Process of Low Alloy Steels

NASA Astrophysics Data System (ADS)

Yang, M.; Zimmerman, C.; Donahue, D.; Sisson, R. D.

2013-07-01

The effort to simulate the nitriding process has been ongoing for the last 20 years. Most of the work has been done to simulate the nitriding process of pure iron. In the present work a series of experiments have been done to understand the effects of the nitriding process parameters such as the nitriding potential, temperature, and time as well as surface condition on the gas nitriding process for the steels. The compound layer growth model has been developed to simulate the nitriding process of AISI 4140 steel. In this paper the fundamentals of the model are presented and discussed including the kinetics of compound layer growth and the determination of the nitrogen diffusivity in the diffusion zone. The excellent agreements have been achieved for both as-washed and pre-oxided nitrided AISI 4140 between the experimental data and simulation results. The nitrogen diffusivity in the diffusion zone is determined to be constant and only depends on the nitriding temperature, which is ~5 × 10-9 cm2/s at 548 °C. It proves the concept of utilizing the compound layer growth model in other steels. The nitriding process of various steels can thus be modeled and predicted in the future.

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

PubMed

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Elimination of quiescent slow-cycling cells via reducing quiescence depth by natural compounds purified from Ganoderma lucidum

PubMed Central

Dai, Jian; Miller, Matthew A.; Everetts, Nicholas J.; Wang, Xia; Li, Peng; Li, Ye; Xu, Jian-Hua; Yao, Guang

2017-01-01

The medical mushroom Ganoderma lucidum has long been used in traditional Chinese medicine and shown effective in the treatment of many diseases including cancer. Here we studied the cytotoxic effects of two natural compounds purified from Ganoderma lucidum, ergosterol peroxide and ganodermanondiol. We found that these two compounds exhibited cytotoxicity not only against fast proliferating cells, but on quiescent, slow-cycling cells. Using a fibroblast cell-quiescence model, we found that the cytotoxicity on quiescent cells was due to induced apoptosis, and was associated with a shallower quiescent state in compound-treated cells, resultant from the increased basal activity of an Rb-E2F bistable switch that controls quiescence exit. Accordingly, we showed that quiescent breast cancer cells (MCF7), compared to its non-transformed counterpart (MCF10A), were preferentially killed by ergosterol peroxide and ganodermanondiol treatment presumably due to their already less stable quiescent state. The cytotoxic effect of natural Ganoderma lucidum compounds against quiescent cells, preferentially on quiescent cancer cells vs. non-cancer cells, may help future antitumor development against the slow-cycling cancer cell subpopulations including cancer stem and progenitor cells. PMID:28099150

Elimination of quiescent slow-cycling cells via reducing quiescence depth by natural compounds purified from Ganoderma lucidum.

PubMed

Dai, Jian; Miller, Matthew A; Everetts, Nicholas J; Wang, Xia; Li, Peng; Li, Ye; Xu, Jian-Hua; Yao, Guang

2017-02-21

The medical mushroom Ganoderma lucidum has long been used in traditional Chinese medicine and shown effective in the treatment of many diseases including cancer. Here we studied the cytotoxic effects of two natural compounds purified from Ganoderma lucidum, ergosterol peroxide and ganodermanondiol. We found that these two compounds exhibited cytotoxicity not only against fast proliferating cells, but on quiescent, slow-cycling cells. Using a fibroblast cell-quiescence model, we found that the cytotoxicity on quiescent cells was due to induced apoptosis, and was associated with a shallower quiescent state in compound-treated cells, resultant from the increased basal activity of an Rb-E2F bistable switch that controls quiescence exit. Accordingly, we showed that quiescent breast cancer cells (MCF7), compared to its non-transformed counterpart (MCF10A), were preferentially killed by ergosterol peroxide and ganodermanondiol treatment presumably due to their already less stable quiescent state. The cytotoxic effect of natural Ganoderma lucidum compounds against quiescent cells, preferentially on quiescent cancer cells vs. non-cancer cells, may help future antitumor development against the slow-cycling cancer cell subpopulations including cancer stem and progenitor cells.

Multi-instrument comparison and compilation of non-methane organic gas emissions from biomass burning and implications for smoke-derived secondary organic aerosol precursors

NASA Astrophysics Data System (ADS)

Hatch, Lindsay E.; Yokelson, Robert J.; Stockwell, Chelsea E.; Veres, Patrick R.; Simpson, Isobel J.; Blake, Donald R.; Orlando, John J.; Barsanti, Kelley C.

2017-01-01

Multiple trace-gas instruments were deployed during the fourth Fire Lab at Missoula Experiment (FLAME-4), including the first application of proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOFMS) and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) for laboratory biomass burning (BB) measurements. Open-path Fourier transform infrared spectroscopy (OP-FTIR) was also deployed, as well as whole-air sampling (WAS) with one-dimensional gas chromatography-mass spectrometry (GC-MS) analysis. This combination of instruments provided an unprecedented level of detection and chemical speciation. The chemical composition and emission factors (EFs) determined by these four analytical techniques were compared for four representative fuels. The results demonstrate that the instruments are highly complementary, with each covering some unique and important ranges of compositional space, thus demonstrating the need for multi-instrument approaches to adequately characterize BB smoke emissions. Emission factors for overlapping compounds generally compared within experimental uncertainty, despite some outliers, including monoterpenes. Data from all measurements were synthesized into a single EF database that includes over 500 non-methane organic gases (NMOGs) to provide a comprehensive picture of speciated, gaseous BB emissions. The identified compounds were assessed as a function of volatility; 6-11 % of the total NMOG EF was associated with intermediate-volatility organic compounds (IVOCs). These atmospherically relevant compounds historically have been unresolved in BB smoke measurements and thus are largely missing from emission inventories. Additionally, the identified compounds were screened for published secondary organic aerosol (SOA) yields. Of the total reactive carbon (defined as EF scaled by the OH rate constant and carbon number of each compound) in the BB emissions, 55-77 % was associated with compounds for which SOA yields are unknown or understudied. The best candidates for future smog chamber experiments were identified based on the relative abundance and ubiquity of the understudied compounds, and they included furfural, 2-methyl furan, 2-furan methanol, and 1,3-cyclopentadiene. Laboratory study of these compounds will facilitate future modeling efforts.

The First Cell Membranes

NASA Technical Reports Server (NTRS)

Deamer, David; Dworkin, Jason P.; Sandford, Scott A.; Bernstein, Max P.; Allamandola, Louis J.

2004-01-01

Organic compounds are synthesized in the interstellar medium and can be delivered to planetary surfaces such as the early Earth, where they mix with endogenous organic mixtures. Some of these compounds are amphiphilic, having polar and non-polar groups on the same molecule. Amphiphilic compounds spontaneously self-assembly into more complex structures such as bimolecular layers, which in turn form closed membranous vesicles. The first forms of cellular life required self-assembled membranes that were likely to be available on the prebiotic Earth. Laboratory simulations show that such vesicles readily encapsulate functional macromolecules, including nucleic acids and polymerases. A goal of future investigations is to fabricate artificial cells as models of the origin of life.

Magnetism in Chemistry

ERIC Educational Resources Information Center

Brookes, R. W.; McFadyen, W. D.

1975-01-01

Discusses the technical aspects of paramagnetism and an electrostatic model called Crystal Field Theory (CFT), very often used in the case of transition metal compounds. Suggests that this discussion be included as an option for college chemistry courses. (MLH)

Agricultural Compounds in Water and Birth Defects.

PubMed

Brender, Jean D; Weyer, Peter J

2016-06-01

Agricultural compounds have been detected in drinking water, some of which are teratogens in animal models. The most commonly detected agricultural compounds in drinking water include nitrate, atrazine, and desethylatrazine. Arsenic can also be an agricultural contaminant, although arsenic often originates from geologic sources. Nitrate has been the most studied agricultural compound in relation to prenatal exposure and birth defects. In several case-control studies published since 2000, women giving birth to babies with neural tube defects, oral clefts, and limb deficiencies were more likely than control mothers to be exposed to higher concentrations of drinking water nitrate during pregnancy. Higher concentrations of atrazine in drinking water have been associated with abdominal defects, gastroschisis, and other defects. Elevated arsenic in drinking water has also been associated with birth defects. Since these compounds often occur as mixtures, it is suggested that future research focus on the impact of mixtures, such as nitrate and atrazine, on birth defects.

Botanical Compounds: Effects on Major Eye Diseases

PubMed Central

Huynh, Tuan-Phat; Mann, Shivani N.; Mandal, Nawajes A.

2013-01-01

Botanical compounds have been widely used throughout history as cures for various diseases and ailments. Many of these compounds exhibit strong antioxidative, anti-inflammatory, and antiapoptotic properties. These are also common damaging mechanisms apparent in several ocular diseases, including age-related macular degeneration (AMD), glaucoma, diabetic retinopathy, cataract, and retinitis pigmentosa. In recent years, there have been many epidemiological and clinical studies that have demonstrated the beneficial effects of plant-derived compounds, such as curcumin, lutein and zeaxanthin, danshen, ginseng, and many more, on these ocular pathologies. Studies in cell cultures and animal models showed promising results for their uses in eye diseases. While there are many apparent significant correlations, further investigation is needed to uncover the mechanistic pathways of these botanical compounds in order to reach widespread pharmaceutical use and provide noninvasive alternatives for prevention and treatments of the major eye diseases. PMID:23843879

Ligand-based virtual screening and in silico design of new antimalarial compounds using nonstochastic and stochastic total and atom-type quadratic maps.

PubMed

Marrero-Ponce, Yovani; Iyarreta-Veitía, Maité; Montero-Torres, Alina; Romero-Zaldivar, Carlos; Brandt, Carlos A; Avila, Priscilla E; Kirchgatter, Karin; Machado, Yanetsy

2005-01-01

Malaria has been one of the most significant public health problems for centuries. It affects many tropical and subtropical regions of the world. The increasing resistance of Plasmodium spp. to existing therapies has heightened alarms about malaria in the international health community. Nowadays, there is a pressing need for identifying and developing new drug-based antimalarial therapies. In an effort to overcome this problem, the main purpose of this study is to develop simple linear discriminant-based quantitative structure-activity relationship (QSAR) models for the classification and prediction of antimalarial activity using some of the TOMOCOMD-CARDD (TOpological MOlecular COMputer Design-Computer Aided "Rational" Drug Design) fingerprints, so as to enable computational screening from virtual combinatorial datasets. In this sense, a database of 1562 organic chemicals having great structural variability, 597 of them antimalarial agents and 965 compounds having other clinical uses, was analyzed and presented as a helpful tool, not only for theoretical chemists but also for other researchers in this area. This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. Afterward, two linear classification functions were derived in order to discriminate between antimalarial and nonantimalarial compounds. The models (including nonstochastic and stochastic indices) correctly classify more than 93% of the compound set, in both training and external prediction datasets. They showed high Matthews' correlation coefficients, 0.889 and 0.866 for the training set and 0.855 and 0.857 for the test one. The models' predictivity was also assessed and validated by the random removal of 10% of the compounds to form a new test set, for which predictions were made using the models. The overall means of the correct classification for this process (leave group 10% full-out cross validation) using the equations with nonstochastic and stochastic atom-based quadratic fingerprints were 93.93% and 92.77%, respectively. The quadratic maps-based TOMOCOMD-CARDD approach implemented in this work was successfully compared with four of the most useful models for antimalarials selection reported to date. The developed models were then used in a simulation of a virtual search for Ras FTase (FTase = farnesyltransferase) inhibitors with antimalarial activity; 70% and 100% of the 10 inhibitors used in this virtual search were correctly classified, showing the ability of the models to identify new lead antimalarials. Finally, these two QSAR models were used in the identification of previously unknown antimalarials. In this sense, three synthetic intermediaries of quinolinic compounds were evaluated as active/inactive ones using the developed models. The synthesis and biological evaluation of these chemicals against two malaria strains, using chloroquine as a reference, was performed. An accuracy of 100% with the theoretical predictions was observed. Compound 3 showed antimalarial activity, being the first report of an arylaminomethylenemalonate having such behavior. This result opens a door to a virtual study considering a higher variability of the structural core already evaluated, as well as of other chemicals not included in this study. We conclude that the approach described here seems to be a promising QSAR tool for the molecular discovery of novel classes of antimalarial drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of malaria illnesses.

Modelling the contribution of biogenic VOCs to new particle formation in the Jülich plant atmosphere chamber

NASA Astrophysics Data System (ADS)

Liao, L.; Dal Maso, M.; Mogensen, D.; Roldin, P.; Rusanen, A.; Kerminen, V.-M.; Mentel, T. F.; Wildt, J.; Kleist, E.; Kiendler-Scharr, A.; Tillmann, R.; Ehn, M.; Kulmala, M.; Boy, M.

2014-11-01

We used the MALTE-BOX model including near-explicit air chemistry and detailed aerosol dynamics to study the mechanisms of observed new particle formation events in the Jülich Plant Atmosphere Chamber. The modelled and measured H2SO4 (sulfuric acid) concentrations agreed within a factor of two. The modelled total monoterpene concentration was in line with PTR-MS observations, and we provided the distributions of individual isomers of terpenes, when no measurements were available. The aerosol dynamic results supported the hypothesis that H2SO4 is one of the critical compounds in the nucleation process. However, compared to kinetic H2SO4 nucleation, nucleation involving OH oxidation products of monoterpenes showed a better agreement with the measurements, with R2 up to 0.97 between modelled and measured total particle number concentrations. The nucleation coefficient for kinetic H2SO4 nucleation was 2.1 × 10-11 cm3 s-1, while the organic nucleation coefficient was 9.0 × 10-14 cm3 s-1. We classified the VOC oxidation products into two sub-groups including extremely low-volatility organic compounds (ELVOCs) and semi-volatile organic compounds (SVOCs). These ELVOCs and SVOCs contributed approximately equally to the particle volume production, whereas only ELVOCs made the smallest particles to grow in size. The model simulations revealed that the chamber walls constitute a major net sink of SVOCs on the first experiment day. However, the net wall SVOC uptake was gradually reduced because of SVOC desorption during the following days. Thus, in order to capture the observed temporal evolution of the particle number size distribution, the model needs to consider reversible gas-wall partitioning.

Predicting cytotoxicity from heterogeneous data sources with Bayesian learning.

PubMed

Langdon, Sarah R; Mulgrew, Joanna; Paolini, Gaia V; van Hoorn, Willem P

2010-12-09

We collected data from over 80 different cytotoxicity assays from Pfizer in-house work as well as from public sources and investigated the feasibility of using these datasets, which come from a variety of assay formats (having for instance different measured endpoints, incubation times and cell types) to derive a general cytotoxicity model. Our main aim was to derive a computational model based on this data that can highlight potentially cytotoxic series early in the drug discovery process. We developed Bayesian models for each assay using Scitegic FCFP_6 fingerprints together with the default physical property descriptors. Pairs of assays that are mutually predictive were identified by calculating the ROC score of the model derived from one predicting the experimental outcome of the other, and vice versa. The prediction pairs were visualised in a network where nodes are assays and edges are drawn for ROC scores >0.60 in both directions. We observed that, if assay pairs (A, B) and (B, C) were mutually predictive, this was often not the case for the pair (A, C). The results from 48 assays connected to each other were merged in one training set of 145590 compounds and a general cytotoxicity model was derived. The model has been cross-validated as well as being validated with a set of 89 FDA approved drug compounds. We have generated a predictive model for general cytotoxicity which could speed up the drug discovery process in multiple ways. Firstly, this analysis has shown that the outcomes of different assay formats can be mutually predictive, thus removing the need to submit a potentially toxic compound to multiple assays. Furthermore, this analysis enables selection of (a) the easiest-to-run assay as corporate standard, or (b) the most descriptive panel of assays by including assays whose outcomes are not mutually predictive. The model is no replacement for a cytotoxicity assay but opens the opportunity to be more selective about which compounds are to be submitted to it. On a more mundane level, having data from more than 80 assays in one dataset answers, for the first time, the question - "what are the known cytotoxic compounds from the Pfizer compound collection?" Finally, having a predictive cytotoxicity model will assist the design of new compounds with a desired cytotoxicity profile, since comparison of the model output with data from an in vitro safety/toxicology assay suggests one is predictive of the other.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

PubMed Central

Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O’Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. PMID:27029624

An insect-tapeworm model as a proxy for anthelminthic effects in the mammalian host.

PubMed

Woolsey, Ian David; Fredensborg, Brian L; Jensen, Per M; Kapel, Christian M O; Meyling, Nicolai V

2015-07-01

Invertebrate models provide several important advantages over their vertebrate counterparts including fewer legislative stipulations and faster, more cost-effective experimental procedures. Furthermore, various similarities between insect and mammalian systems have been highlighted. To obtain maximum use of invertebrate models in pharmacology, their fidelity as analogues of vertebrate systems requires verification. We utilised a flour beetle (Tenebrio molitor)-tapeworm (Hymenolepis diminuta) model to evaluate the efficacy of known anthelmintic compounds, praziquantel, mebendazole and levamisole against H. diminuta cysticercoid larvae in vitro. Inhibition of cysticercoid activity during the excystation procedure was used as a proxy for worm removal. The effects of the three compounds mirrored their relative efficacy in treatment against adult worms in mammalian systems; however, further study is required to determine the fidelity of this model in relation to dose administered. The model precludes comparison of consecutive daily administration of pharmaceuticals in mammals due to cysticercoids not surviving outside of the host for multiple days. Treatment of beetles in vivo, followed by excystation of cysticercoids postdissection could potentially allow for such comparisons. Further model validation will include analysis of pharmaceutical efficacy in varying H. diminuta isolates and pharmaceutical dilution in solvents other than water. Notwithstanding, our results demonstrate that this model holds promise as a method to efficiently identify promising new cestocidal candidates.

Regional atmospheric emissions determined from measurements at Jeju Island, Korea: Halogenated compounds from China

NASA Astrophysics Data System (ADS)

Kim, Jooil; Li, Shanlan; Kim, Kyung-Ryul; Stohl, Andreas; Mühle, Jens; Kim, Seung-Kyu; Park, Mi-Kyung; Kang, Dong-Jin; Lee, Gangwoong; Harth, Christina M.; Salameh, Peter K.; Weiss, Ray F.

2010-06-01

High-frequency in-situ measurements of a wide range of halogenated compounds including chlorofluorocarbons (CFCs), halons, hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs), perfluorinated compounds (PFCs), sulfur hexafluoride (SF6), and other chlorinated and brominated compounds have been made at Gosan (Jeju Island, Korea). Regional emissions of HCFC-22 (CHClF2) calculated from inverse modeling were combined with interspecies correlation methods to estimate national emissions for China, a major emitter of industrial halogenated gases. Our results confirm the signs of successful phase-out of primary ozone-depleting species such as CFCs, halons and many chlorinated or brominated compounds, along with substantial emissions of replacement HCFCs. Emissions derived for HFCs, PFCs, and SF6 were compared to published estimates and found to be a significant fraction of global totals. Overall, Chinese emissions of the halogenated compounds discussed here represent 19(14-17)% and 20(15-26)% of global emissions when evaluated in terms of their Ozone Depletion Potentials and 100-year Global Warming Potentials, respectively.

Roller bearing geometry design

NASA Technical Reports Server (NTRS)

Savage, M.; Pinkston, B. H. W.

1976-01-01

A theory of kinematic stabilization of rolling cylinders is extended and applied to the design of cylindrical roller bearings. The kinematic stabilization mechanism puts a reverse skew into the rolling elements by changing the roller taper. Twelve basic bearing modification designs are identified amd modeled. Four have single transverse convex curvature in their rollers while eight have rollers which have compound transverse curvature made up of a central cylindrical band surrounded by symmetric bands with slope and transverse curvature. The bearing designs are modeled for restoring torque per unit axial displacement, contact stress capacity, and contact area including dynamic loading, misalignment sensitivity and roller proportion. Design programs are available which size the single transverse curvature roller designs for a series of roller slopes and load separations and which design the compound roller bearings for a series of slopes and transverse radii of curvature. The compound rollers are proportioned to have equal contact stresses and minimum size. Design examples are also given.

Production of extremely low volatile organic compounds from biogenic emissions: Measured yields and atmospheric implications

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

Jokinen, Tuija; Berndt, Torsten; Makkonen, Risto

2015-06-09

Extremely low volatility organic compounds (ELVOC) are suggested to promote aerosol particle formation and cloud condensation nuclei (CCN) production in the atmosphere. We show that the capability of biogenic VOC (BVOC) to produce ELVOC depends strongly on their chemical structure and relative oxidant levels. BVOC with an endocyclic double bond, representative emissions from, e.g., boreal forests, efficiently produce ELVOC from ozonolysis. Compounds with exocyclic double bonds or acyclic compounds including isoprene, emission representative of the tropics, produce minor quantities of ELVOC, and the role of OH radical oxidation is relatively larger. Implementing these findings into a global modeling framework showsmore » that detailed assessment of ELVOC production pathways is crucial for understanding biogenic secondary organic aerosol and atmospheric CCN formation.« less

The pheromone production of female Plodia interpunctella is inhibited by tyraminergic antagonists.

PubMed

Hirashima, Akinori; Kimizu, Megumi; Shigeta, Yoko; Matsugu, Sachiko; Eiraku, Tomohiko; Kuwano, Eiichi; Eto, Morifusa

2004-11-01

Several compounds were found to suppress the calling behavior and in vitro pheromone biosynthesis of the Indian meal moth, Plodia interpunctella. The compounds were screened by means of a calling-behavior bioassay with female P. interpunctella. Five derivatives with activities in the nanomolar range were identified, in order of decreasing pheromonostatic activity: 4-hydroxybenzaldehyde semicarbazone (42) > 5-(4-methoxyphenyl)-1,3-oxazole (38) > 5-[4-(tert-butyl)phenyl]-1,3-oxazole (40) > 5-(3-methoxyphenyl)-1,3-oxazole (35) > 5-(4-cyanophenyl)-1,3-oxazole (36). These compounds also showed in vitro inhibitory activity in intracellular de novo pheromone biosynthesis, as determined with isolated pheromone-gland preparations that incorporated [1-(14)C]sodium acetate in the presence of the so-called pheromone-biosynthesis-activating neuropeptide (PBAN). The non-additive effect of the inhibitor with antagonist (yohimbine) for the tyramine (TA) receptor suggests that it could be a tyraminergic antagonist. Three-dimensional (3D) computer models were built from a set of compounds. Among the common-featured models generated by the program Catalyst/HipHop, aromatic-ring (AR) and H-bond-acceptor-lipophilic (HBAl) features were considered to be essential for inhibitory activity in the calling behavior and in vitro pheromone biosynthesis. Active compounds, including yohimbine, mapped well onto all the AR and HBAl features of the hypothesis. Less-active compounds were shown to be unable to achieve an energetically favorable conformation, consistent with our 3D common-feature pharmacophore models. The present hypothesis demonstrates that calling behavior and PBAN-stimulated incorporation of radioactivity are inhibited by tyraminergic antagonists.

"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.

PubMed

Crisman, Thomas J; Jenkins, Jeremy L; Parker, Christian N; Hill, W Adam G; Bender, Andreas; Deng, Zhan; Nettles, James H; Davies, John W; Glick, Meir

2007-04-01

This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per plate basis (instead of a per compound basis), 25% of the 1,000,000-compound screening was optimized for general initial HTS. Statistical models are then generated from target-specific primary results (percentage inhibition data) to drive the cherry picking and testing from the entire collection. Using retrospective analysis of 11 HTS campaigns, the authors show that this method would have captured on average two thirds of the active compounds (IC(50) < 10 microM) and three fourths of the active Murcko scaffolds while decreasing screening expenditure by nearly 75%. This result is true for a wide variety of targets, including G-protein-coupled receptors, chemokine receptors, kinases, metalloproteinases, pathway screens, and protein-protein interactions. Unlike time-consuming "classic" sequential approaches that require multiple iterations of cherry picking, testing, and building statistical models, here individual compounds are cherry picked just once, based directly on primary screening data. Strikingly, the authors demonstrate that models built from primary data are as robust as models built from IC(50) data. This is true for all HTS campaigns analyzed, which represent a wide variety of target classes and assay types.

QSAR study on the removal efficiency of organic pollutants in supercritical water based on degradation temperature.

PubMed

Jiang, Ai; Cheng, Zhiwen; Shen, Zhemin; Guo, Weimin

2018-02-13

This paper aims to study temperature-dependent quantitative structure activity relationship (QSAR) models of supercritical water oxidation (SCWO) process which were developed based on Arrhenius equation between oxidation reaction rate and temperature. Through exploring SCWO process, each kinetic rate constant was studied for 21 organic substances, including azo dyes, heterocyclic compounds and ionic compounds. We propose the concept of T R95 , which is defined as the temperature at removal ratio of 95%, it is a key indicator to evaluate compounds' complete oxidation. By using Gaussian 09 and Material Studio 7.0, quantum chemical parameters were conducted for each organic compound. The optimum model is T R95  = 654.775 + 1761.910f(+) n  - 177.211qH with squared regression coefficient R 2  = 0.620 and standard error SE = 35.1. Nearly all the compounds could obtain accurate predictions of their degradation rate. Effective QSAR model exactly reveals three determinant factors, which are directly related to degradation rules. Specifically, the lowest f(+) value of main-chain atoms (f(+) n ) indicates the degree of affinity for nucleophilic attack. qH shows the ease or complexity of valence-bond breakage of organic molecules. BO x refers to the stability of a bond. Coincidentally, the degradation mechanism could reasonably be illustrated from each perspective, providing a deeper insight of universal and propagable oxidation rules. Besides, the satisfactory results of internal and external validations suggest the stability, reliability and predictive ability of optimum model.

Inhibitors of calling behavior of Plodia interpunctella.

PubMed

Hirashima, Akinori; Shigeta, Yoko; Eiraku, Tomohiko; Kuwano, Eiichi

2003-01-01

Some octopamine agonists were found to suppress the calling behavior of the stored product Indian meal moth, Plodia interpunctella. Compounds were screened using a calling behavior bioassay using female P. interpunctella. Four active derivatives, with inhibitory activity at the nanomolar range, were identified in order of decreasing activity: 2-(1-phenylethylamino)-2-oxazoline > 2-(2-ethyl,6-methylanilino)oxazolidine > 2-(2-methyl benzylamino)-2-thiazoline > 2-(2,6-diethylanilino)thiazolidine. Three-dimensional pharmacophore hypotheses were built from a set of 15 compounds. Among the ten common-featured models generated by the program Catalyst/HipHop, a hypothesis including a hydrogen-bond acceptor lipid, a hydrophobic aromatic and two hydrophobic aliphatic features was considered to be essential for inhibitory activity in the calling behavior. Active compounds mapped well onto all the hydrogen-bond acceptor lipid, hydrophobic aromatic and hydrophobic aliphatic features of the hypothesis. On the other hand, less active compounds were shown not to achieve the energetically favorable conformation that is found in the active molecules in order to fit the 3D common-feature pharmacophore models. The present studies demonstrate that inhibition of calling behavior is via an octopamine receptor.

Characterization of chemical ingredients and anticonvulsant activity of American skullcap (Scutellaria lateriflora).

PubMed

Zhang, Zhizhen; Lian, Xiao-yuan; Li, Shiyou; Stringer, Janet L

2009-05-01

American skullcap (the aerial part of Scutellaria lateriflora L.) has been traditionally used by Native Americans and Europeans as a nerve tonic, sedative, and anticonvulsant. However, despite some previous studies, the quality and safety, the bioactive ingredients, and the pharmacological properties of American skullcap are not fully understood. The aims of this study were to characterize the chemical ingredients of American skullcap and to evaluate its anticonvulsant activity. Twelve phenolic compounds including 10 flavonoids and two phenylethanoid glycosides were isolated and identified from American skullcap and used as marker compounds. An HPLC analytic method for analyzing these marker compounds in commercial American skullcap products from different sources was established and validated. The anticonvulsant activity of American skullcap was determined in rat models of acute seizures induced by pilocarpine and pentylenetetrazol. The results from this study indicate that (1) phenolic compounds, especially flavonoids, are the predominant constituents in American skullcap; (2) American skullcap products have similar constituents, but the content and relative proportions of the individual constituents varies widely; and (3) American skullcap has anticonvulsant activity in rodent models of acute seizures.

Sorption of organic gases in a furnished room

NASA Astrophysics Data System (ADS)

Singer, Brett C.; Revzan, Kenneth L.; Hotchi, Toshifumi; Hodgson, Alfred T.; Brown, Nancy J.

We present experimental data and semi-empirical models describing the sorption of organic gases in a simulated indoor residential environment. Two replicate experiments were conducted with 20 volatile organic compounds (VOCs) in a 50-m 3 room finished with painted wallboard, carpet and cushion, draperies and furnishings. The VOCs span a wide volatility range and include ten hazardous air pollutants. VOCs were introduced to the static chamber as a pulse and their gas-phase concentrations were measured during a net adsorption period and a subsequent net desorption period. Three sorption models were fit to the measured concentrations for each compound to determine the simplest formulation needed to adequately describe the observed behavior. Sorption parameter values were determined by fitting the models to adsorption period data then checked by comparing measured and predicted behavior during desorption. The adequacy of each model was evaluated using a goodness of fit parameter calculated for each period. Results indicate that sorption usually does not greatly affect indoor concentrations of methyl- tert-butyl ether, 2-butanone, isoprene and benzene. In contrast, sorption appears to be a relevant indoor process for many of the VOCs studied, including C 8-C 10 aromatic hydrocarbons (HC), terpenes, and pyridine. These compounds sorbed at rates close to typical residential air change rates and exhibited substantial sorptive partitioning at equilibrium. Polycyclic aromatic HCs, aromatic alcohols, ethenylpyridine and nicotine initially adsorbed to surfaces at rates of 1.5->6 h -1 and partitioned 95->99% in the sorbed phase at equilibrium.

Structure-based virtual screening and characterization of a novel IL-6 antagonistic compound from synthetic compound database.

PubMed

Wang, Jing; Qiao, Chunxia; Xiao, He; Lin, Zhou; Li, Yan; Zhang, Jiyan; Shen, Beifen; Fu, Tinghuan; Feng, Jiannan

2016-01-01

According to the three-dimensional (3D) complex structure of (hIL-6⋅hIL-6R⋅gp 130) 2 and the binding orientation of hIL-6, three compounds with high affinity to hIL-6R and bioactivity to block hIL-6 in vitro were screened theoretically from the chemical databases, including 3D-Available Chemicals Directory (ACD) and MDL Drug Data Report (MDDR), by means of the computer-guided virtual screening method. Using distance geometry, molecular modeling and molecular dynamics trajectory analysis methods, the binding mode and binding energy of the three compounds were evaluated theoretically. Enzyme-linked immunosorbent assay analysis demonstrated that all the three compounds could block IL-6 binding to IL-6R specifically. However, only compound 1 could effectively antagonize the function of hIL-6 and inhibit the proliferation of XG-7 cells in a dose-dependent manner, whereas it showed no cytotoxicity to SP2/0 or L929 cells. These data demonstrated that the compound 1 could be a promising candidate of hIL-6 antagonist.

Antibacterial Evaluation of Synthetic Thiazole Compounds In Vitro and In Vivo in a Methicillin-Resistant Staphylococcus aureus (MRSA) Skin Infection Mouse Model.

PubMed

Mohammad, Haroon; Cushman, Mark; Seleem, Mohamed N

2015-01-01

The emergence of community-associated methicillin-resistant Staphylococcus aureus (MRSA), including strains resistant to current antibiotics, has contributed to an increase in the number of skin infections reported in humans in recent years. New therapeutic options are needed to counter this public health challenge. The aim of the present study was to examine the potential of thiazole compounds synthesized by our research group to be used topically to treat MRSA skin and wound infections. The broth microdilution method confirmed that the lead thiazole compound and four analogues are capable of inhibiting MRSA growth at concentrations as low as 1.3 μg/mL. Additionally, three compounds exhibited a synergistic relationship when combined with the topical antibiotic mupirocin against MRSA in vitro via the checkerboard assay. Thus the thiazole compounds have potential to be used alone or in combination with mupirocin against MRSA. When tested against human keratinocytes, four derivatives of the lead compound demonstrated an improved toxicity profile (were found to be non-toxic up to a concentration of 20 μg/mL). Utilizing a murine skin infection model, we confirmed that the lead compound and three analogues exhibited potent antimicrobial activity in vivo, with similar capability as the antibiotic mupirocin, as they reduced the burden of MRSA present in skin wounds by more than 90%. Taken altogether, the present study provides important evidence that these thiazole compounds warrant further investigation for development as novel topical antimicrobials to treat MRSA skin infections.

Modeling Compound Flood Hazards in Coastal Embayments

NASA Astrophysics Data System (ADS)

Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

2017-12-01

Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the strengths/weaknesses of each approach and helps modelers choose the appropriate scenario that best fit to the needs of their project. The proposed risk assessment approach can help flood hazard modeling practitioners achieve a more reliable estimate of risk, by cautiously reducing the dimensionality of the hazard analysis.

Has an Angel Shown the Way? Etiological and Therapeutic Implications of the PCP/NMDA Model of Schizophrenia

PubMed Central

Javitt, Daniel C.

2012-01-01

Over the last 20 years, glutamatergic models of schizophrenia have become increasingly accepted as etiopathological models of schizophrenia, based on the observation that phencyclidine (PCP) induces a schizophrenia-like psychosis by blocking neurotransmission at N-methyl-D-aspartate (NMDA)-type glutamate receptors. This article reviews developments in two key predictions of the model: first, that neurocognitive deficits in schizophrenia should follow the pattern of deficit predicted based on underlying NMDAR dysfunction and, second, that agents that stimulate NMDAR function should be therapeutically beneficial. As opposed to dopamine receptors, NMDAR are widely distributed throughout the brain, including subcortical as well as cortical brain regions, and sensory as well as association cortex. Studies over the past 20 years have documented severe sensory dysfunction in schizophrenia using behavioral, neurophysiological, and functional brain imaging approaches, including impaired generation of key sensory-related potentials such as mismatch negativity and visual P1 potentials. Similar deficits are observed in humans following administration of NMDAR antagonists such as ketamine in either humans or animal models. Sensory dysfunction, in turn, predicts impairments in higher order cognitive functions such as auditory or visual emotion recognition. Treatment studies have been performed with compounds acting directly at the NMDAR glycine site, such as glycine, D-serine, or D-cycloserine, and, more recently, with high-affinity glycine transport inhibitors such as RG1678 (Roche). More limited studies have been performed with compounds targeting the redox site. Overall, these compounds have been found to induce significant beneficial effects on persistent symptoms, suggesting novel approaches for treatment and prevention of schizophrenia. PMID:22987851

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

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

St. John, Peter C.; Kairys, Paul; Das, Dhrubajyoti D.

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yieldmore » sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.« less

Relative effects on stratospheric ozone of halogenated methanes and ethanes of social and industrial interest

NASA Technical Reports Server (NTRS)

Fisher, Donald A.; Hales, Charles H.; Filkin, David L.; Ko, Malcolm K. W.; Sze, N. Dak; Connell, Peter S.; Wuebbles, Donald J.; Isaksen, Ivar S. A.; Stordal, Frode

1990-01-01

Four atmospheric modeling groups have calculated relative effects of several halocarbons (chlorofluorocarbons (CFC's)-11, 12, 113, 114, and 115; hydrochlorofluorocarbons (HCFC's) 22, 123, 124, 141b, and 142b; hydrofluorocarbons (HFC's) 125, 134a, 143a, and 152a, carbon tetrachloride; and methyl chloroform) on stratospheric ozone. Effects on stratospheric ozone were calculated for each compound and normalized relative to the effect of CFC-11. These models include the representations for homogeneous physical and chemical processes in the middle atmosphere but do no account for either heterogeneous chemistry or polar dynamics which are important in the spring time loss of ozone over Antarctica. Relative calculated effects using a range of models compare reasonably well. Within the limits of the uncertainties of these model results, compounds now under consideration as functional replacements for fully halogenated compounds have modeled stratospheric ozone reductions of 10 percent or less of that of CFC-11. Sensitivity analyses examined the sensitivity of relative calculated effects to levels of other trace gases, assumed transport in the models, and latitudinal and seasonal local dependencies. Relative effects on polar ozone are discussed in the context of evolving information on the special processes affecting ozone, especially during polar winter-springtime. Lastly, the time dependency of relative effects were calculated.

Biological activity of aldose reductase and lipophilicity of pyrrolyl-acetic acid derivatives

NASA Astrophysics Data System (ADS)

Kumari, A.; Kumari, R.; Kumar, R.; Gupta, M.

2011-12-01

Quantitative Structure-Activity Relationship modeling is a powerful approach for correlating an organic compound to its lipophilicity. In this paper QSAR models are established for estimation of correlation of the lipophilicity of a series of pyrrolyl-acetic acid derivatives, inhibitors of the aldose reductase enzyme, in the n-octanol-water system with biological activity of aldose reductase. Lipophilicity, expressed by the logarithm of n-octnol-water partition coefficient log P and biological activity of aldose reductase inhibitory activity by log it. Result obtained by QSAR modeling of compound series reveal a definite trend in biological activity and a further improvement in quantitative relationships are established if, beside log P, Hammett electronic constant σ and connectivity index chi-3 (3 χ) term included in the regression equation. The tri-parametric model with log P, 3 χ and σ as correlating parameters have been found to be the best which gives a variance of 87% ( R 2 = 0.8743). A compound has been found to be serious outlier and when the same has been excluded the model explains about 94% variance of the data set ( R 2 = 0.9447). The topological index (3 χ) has been found to be a good parameter for modeling the biological activity.

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

DOE PAGES

St. John, Peter C.; Kairys, Paul; Das, Dhrubajyoti D.; ...

2017-07-24

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yieldmore » sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.« less

Linear solvation energy relationships (LSER) for adsorption of organic compounds by carbon nanotubes.

PubMed

Ersan, Gamze; Apul, Onur G; Karanfil, Tanju

2016-07-01

The objective of this paper was to create a comprehensive database for the adsorption of organic compounds by carbon nanotubes (CNTs) and to use the Linear Solvation Energy Relationship (LSER) technique for developing predictive adsorption models of organic compounds (OCs) by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Adsorption data for 123 OCs by MWCNTs and 48 OCs by SWCNTs were compiled from the literature, including some experimental results obtained in our laboratory. The roles of selected OCs properties and CNT types were examined with LSER models. The results showed that the r(2) values of the LSER models displayed small variability for aromatic compounds smaller than 220 g/mol, after which a decreasing trend was observed. The data available for aliphatics was mainly for molecular weights smaller than 250 g/mol, which showed a similar trend to that of aromatics. The r(2) values for the LSER model on the adsorption of aromatic and aliphatic OCs by SWCNTs and MWCNTs were relatively similar indicating the linearity of LSER models did not depend on the CNT types. Among all LSER model descriptors, V term (molecular volume) for aromatic OCs and B term (basicity) for aliphatic OCs were the most predominant descriptors on both type of CNTs. The presence of R term (excess molar refractivity) in LSER model equations resulted in decreases for both V and P (polarizability) parameters without affecting the r(2) values. Overall, the results demonstrate that successful predictive models can be developed for the adsorption of OCs by MWCNTs and SWCNTs with LSER techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Zebrafish: A Model for the Study of Toxicants Affecting Muscle Development and Function

PubMed Central

Dubińska-Magiera, Magda; Daczewska, Małgorzata; Lewicka, Anna; Migocka-Patrzałek, Marta; Niedbalska-Tarnowska, Joanna; Jagla, Krzysztof

2016-01-01

The rapid progress in medicine, agriculture, and allied sciences has enabled the development of a large amount of potentially useful bioactive compounds, such as drugs and pesticides. However, there is another side of this phenomenon, which includes side effects and environmental pollution. To avoid or minimize the uncontrollable consequences of using the newly developed compounds, researchers seek a quick and effective means of their evaluation. In achieving this goal, the zebrafish (Danio rerio) has proven to be a highly useful tool, mostly because of its fast growth and development, as well as the ability to absorb the molecules diluted in water through its skin and gills. In this review, we focus on the reports concerning the application of zebrafish as a model for assessing the impact of toxicants on skeletal muscles, which share many structural and functional similarities among vertebrates, including zebrafish and humans. PMID:27869769

Segregation Phenomena on the Crystal Surface of Chemical Compounds

NASA Astrophysics Data System (ADS)

Tomashpol'skii, Yu. Ya.

2018-06-01

The current state of the theoretical and experimental studies of changes in the chemical structure and composition caused by segregation phenomena on the surface of chemical compounds was reviewed. The review considers the experimental data obtained exclusively on single crystals, which were studied by modern instrumental methods, including in situ Auger electron spectrometry, X-ray spectral microanalysis, high-resolution scanning and transmission electron microscopy, secondary electron emission, and atomic force microscopy. The models that suggest the crystal-chemical diffusion and liquid-phase mechanisms of segregation were described. The parameters of the theory include the type of chemical bond, elastic constants, and crystal-chemical characteristics of substances. The models make it possible to predict the nature of changes in the surface composition: segregation tendency, segregant type, and degree of nonstoichiometry. A new direction in surface segregation was considered, which is promising for nanoelectronics and emission electronics.

Endocrine disruptors and prostate cancer risk

PubMed Central

Prins, Gail S

2010-01-01

There is increasing evidence both from epidemiology studies and animal models that specific endocrine-disrupting compounds may influence the development or progression of prostate cancer. In large part, these effects appear to be linked to interference with estrogen signaling, either through interacting with ERs or by influencing steroid metabolism and altering estrogen levels within the body. In humans, epidemiologic evidence links specific pesticides, PCBs and inorganic arsenic exposures to elevated prostate cancer risk. Studies in animal models also show augmentation of prostate carcinogenesis with several other environmental estrogenic compounds including cadmium, UV filters and BPA. Importantly, there appears to be heightened sensitivity of the prostate to these endocrine disruptors during the critical developmental windows including in utero and neonatal time points as well as during puberty. Thus infants and children may be considered a highly susceptible population for ED exposures and increased risk of prostate cancers with aging. PMID:18524946

Discovering new mTOR inhibitors for cancer treatment through virtual screening methods and in vitro assays

NASA Astrophysics Data System (ADS)

Wang, Ling; Chen, Lei; Yu, Miao; Xu, Li-Hui; Cheng, Bao; Lin, Yong-Sheng; Gu, Qiong; He, Xian-Hui; Xu, Jun

2016-01-01

Mammalian target of rapamycin (mTOR) is an attractive target for new anticancer drug development. We recently developed in silico models to distinguish mTOR inhibitors and non-inhibitors. In this study, we developed an integrated strategy for identifying new mTOR inhibitors using cascaded in silico screening models. With this strategy, fifteen new mTOR kinase inhibitors including four compounds with IC50 values below 10 μM were discovered. In particular, compound 17 exhibited potent anticancer activities against four tumor cell lines, including MCF-7, HeLa, MGC-803, and C6, with IC50 values of 1.90, 2.74, 3.50 and 11.05 μM. Furthermore, cellular studies and western blot analyses revealed that 17 induces cell death via apoptosis by targeting both mTORC1 and mTORC2 within cells and arrests the cell cycle of HeLa at the G1/G0-phase. Finally, multi-nanosecond explicit solvent simulations and MM/GBSA analyses were carried out to study the inhibitory mechanisms of 13, 17, and 40 for mTOR. The potent compounds presented here are worthy of further investigation.

Mixed raster content (MRC) model for compound image compression

NASA Astrophysics Data System (ADS)

de Queiroz, Ricardo L.; Buckley, Robert R.; Xu, Ming

1998-12-01

This paper will describe the Mixed Raster Content (MRC) method for compressing compound images, containing both binary test and continuous-tone images. A single compression algorithm that simultaneously meets the requirements for both text and image compression has been elusive. MRC takes a different approach. Rather than using a single algorithm, MRC uses a multi-layered imaging model for representing the results of multiple compression algorithms, including ones developed specifically for text and for images. As a result, MRC can combine the best of existing or new compression algorithms and offer different quality-compression ratio tradeoffs. The algorithms used by MRC set the lower bound on its compression performance. Compared to existing algorithms, MRC has some image-processing overhead to manage multiple algorithms and the imaging model. This paper will develop the rationale for the MRC approach by describing the multi-layered imaging model in light of a rate-distortion trade-off. Results will be presented comparing images compressed using MRC, JPEG and state-of-the-art wavelet algorithms such as SPIHT. MRC has been approved or proposed as an architectural model for several standards, including ITU Color Fax, IETF Internet Fax, and JPEG 2000.

Chemical transport model simulations of organic aerosol in ...

EPA Pesticide Factsheets

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data

A European model and case studies for aggregate exposure assessment of pesticides.

PubMed

Kennedy, Marc C; Glass, C Richard; Bokkers, Bas; Hart, Andy D M; Hamey, Paul Y; Kruisselbrink, Johannes W; de Boer, Waldo J; van der Voet, Hilko; Garthwaite, David G; van Klaveren, Jacob D

2015-05-01

Exposures to plant protection products (PPPs) are assessed using risk analysis methods to protect public health. Traditionally, single sources, such as food or individual occupational sources, have been addressed. In reality, individuals can be exposed simultaneously to multiple sources. Improved regulation therefore requires the development of new tools for estimating the population distribution of exposures aggregated within an individual. A new aggregate model is described, which allows individual users to include as much, or as little, information as is available or relevant for their particular scenario. Depending on the inputs provided by the user, the outputs can range from simple deterministic values through to probabilistic analyses including characterisations of variability and uncertainty. Exposures can be calculated for multiple compounds, routes and sources of exposure. The aggregate model links to the cumulative dietary exposure model developed in parallel and is implemented in the web-based software tool MCRA. Case studies are presented to illustrate the potential of this model, with inputs drawn from existing European data sources and models. These cover exposures to UK arable spray operators, Italian vineyard spray operators, Netherlands users of a consumer spray and UK bystanders/residents. The model could also be adapted to handle non-PPP compounds. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil.

PubMed

Olivero, J; Gracia, T; Payares, P; Vivas, R; Díaz, D; Daza, E; Geerlings, P

1997-05-01

Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).

Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.

PubMed

Han, Lianyi; Wang, Yanli; Bryant, Stephen H

2008-09-25

Recent advances in high-throughput screening (HTS) techniques and readily available compound libraries generated using combinatorial chemistry or derived from natural products enable the testing of millions of compounds in a matter of days. Due to the amount of information produced by HTS assays, it is a very challenging task to mine the HTS data for potential interest in drug development research. Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced. In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system http://pubchem.ncbi.nlm.nih.gov. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2 approximately 80.5%, 97.3 approximately 99.0%, 0.4 approximately 0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7. Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.

A PHARMACOKINETIC MODEL FOR ESTIMATING ...

EPA Pesticide Factsheets

Empirical evidence suggests that exposure of Americans to dioxin-like compounds was low during the early decades of the 20th century, then increased during the 1940s and 1950s reaching a peak in the 1960s and 1970s, and progressively decreased to lower levels in the 1980s and 1990s. Such evidence includes dioxin analysis of carbon-dated sediment cores of lakes and rivers, preserved meat samples from different decades of the 20th century, and limited body burden measurements of dioxin-like compounds. Pinsky and Lorber (1998) summarized studies measuring 2,3,7,8-TCDD in blood and adipose tissue finding a range of 10-20 pg/g (ppt) lipid during the 1970s, and 2-10 ppt lipid during the 1980s. This study reviews body burdens of dioxin toxic equivalents, TEQs, to find a range from about 50-80 ppt lipid during the 1970s, 30-50 ppt lipid during the 1980s, and 10-20 ppt lipid during the 1990s (TEQs comprised of the 17 dioxin and furan congeners only). Pinsky and Lorber (1998) investigated historical exposure trends for 2,3,7,8-TCDD by using a single-compartment, first-order pharmacokinetic model. The current study extends this prior effort by modeling dioxin TEQs instead of the single compound, 2,3,7,8-TCDD. TEQs are modeled as though they are a single compound, in contrast to an approach where the individual dioxin and furan congeners are modeled separately. It was found that body burdens of TEQs during the 1970s, 80s, and 90s could be modeled by assuming a histor

Thermal Studies of Ammonium Cyanide Reactions: A Model for Thermal Alteration of Prebiotic Compounds in Meteorite Parent Bodies

NASA Technical Reports Server (NTRS)

Hammer, P. G.; Locke, D. R.; Burton, A. S.; Callahan, M. P.

2017-01-01

Organic compounds in carbonaceous chondrites were likely transformed by a variety of parent body processes including thermal and aqueous processing. Here, we analyzed ammonium cyanide reactions that were heated at different temperatures and times by multiple analytical techniques. The goal of this study is to better understand the effect of hydrothermal alteration on cyanide chemistry, which is believed to be responsible for the abiotic synthesis of purine nucleobases and their structural analogs detected in carbonaceous chondrites.

Lignans and aromatic glycosides from Piper wallichii and their antithrombotic activities.

PubMed

Shi, Yan-Ni; Shi, Yi-Ming; Yang, Lian; Li, Xing-Cong; Zhao, Jin-Hua; Qu, Yan; Zhu, Hong-Tao; Wang, Dong; Cheng, Rong-Rong; Yang, Chong-Ren; Xu, Min; Zhang, Ying-Jun

2015-03-13

Piper wallichii (Miq.) Hand.-Mazz. is a medicinal plant used widely for the treatment of rheumatoid arthritis, inflammatory diseases, cerebral infarction and angina in China. Previous study showed that lignans and neolignans from Piper spp. had potential inhibitory activities on platelet aggregation. In the present study, we investigated the chemical constituents of Piper wallichii and their antithrombotic activities, to support its traditional uses. The methanolic extract of the air-dried stems of Piper wallichii was separated and purified using various chromatographic methods, including semi-preparative HPLC. The chemical structures of the isolates were determined by detailed spectroscopic analysis, and acidic hydrolysis in case of the new glycoside 2. Determination of absolute configurations of the new compound 1 was facilitated by calculated electronic circular dichroism using time-dependent density-functional theory. All compounds were tested for their inhibitory effects on platelet aggregation induced by platelet activating factor (PAF) in rabbits׳ blood model, from which the active ones were further evaluated the in vivo antithrombotic activity in zebrafish model. A new neolignan, piperwalliol A (1), and four new aromatic glycosides, piperwalliosides A-D (2-5) were isolated from the stems of Piper wallichii, along with 25 known compounds, including 13 lignans, six aromatic glycosides, two phenylpropyl aldehydes, and four biphenyls. Five known compounds (6-10) showed in vitro antiplatelet aggregation activities. Among them, (-)-syringaresinol (6) was the most active compound with an IC50 value of 0.52 mM. It is noted that in zebrafish model, the known lignan 6 showed good in vivo antithrombotic effect with a value of 37% at a concentration of 30 μM, compared with the positive control aspirin with the inhibitory value of 74% at a concentration of 125μM. This study demonstrated that lignans, phenylpropanoid and biphenyl found in Piper wallichii may be responsible for antithrombotic effect of the titled plant. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Design, synthesis, and biological evaluation of 6-methoxy-2-arylquinolines as potential P-glycoprotein inhibitors.

PubMed

Aboutorabzadeh, Sayyed Mohammad; Mosaffa, Fatemeh; Hadizadeh, Farzin; Ghodsi, Razieh

2018-01-01

In the present study, a new series of 6-methoxy-2-arylquinoline analogues was designed and synthesized as P-glycoprotein (P-gp) inhibitors using quinine and flavones as the lead compounds. The cytotoxic activity of the synthesized compounds was evaluated against two human cancer cell lines including EPG85-257RDB, multidrug-resistant gastric carcinoma cells (P-gp-positive gastric carcinoma cell line), and EPG85-257P, drug-sensitive gastric carcinoma cells. Compounds showing low to moderate toxicity in the MTT test were selected to investigate their P-gp inhibition activity. Moreover, trying to explain the results of biological experiments, docking studies of the selected compounds into the homology-modeled human P-gp, were carried out. The physicochemical and ADME properties of the compounds as drug candidate were also predicted. Most of our compounds exhibited negligible or much lower cytotoxic effect in both cancer cells. Among the series, 5a and 5b, alcoholic quinoline derivatives were found to inhibit the efflux of rhodamine 123 at the concentration of 10 μM significantly. Among the tested quinolines, 5a and 5b showed the most potent P-gp inhibitory activity in the series and were 1.3-fold and 2.1-fold stronger than verapamil, respectively. SAR data revealed that hydroxyl methyl in position 4 of quinolines has a key role in P-gp efflux inhibition of our compounds. ADME studies suggested that all of the compounds included in this study may have a good human intestinal absorption.

A database of 629 English compound words: ratings of familiarity, lexeme meaning dominance, semantic transparency, age of acquisition, imageability, and sensory experience.

PubMed

Juhasz, Barbara J; Lai, Yun-Hsuan; Woodcock, Michelle L

2015-12-01

Since the work of Taft and Forster (1976), a growing literature has examined how English compound words are recognized and organized in the mental lexicon. Much of this research has focused on whether compound words are decomposed during recognition by manipulating the word frequencies of their lexemes. However, many variables may impact morphological processing, including relational semantic variables such as semantic transparency, as well as additional form-related and semantic variables. In the present study, ratings were collected on 629 English compound words for six variables [familiarity, age of acquisition (AoA), semantic transparency, lexeme meaning dominance (LMD), imageability, and sensory experience ratings (SER)]. All of the compound words selected for this study are contained within the English Lexicon Project (Balota et al., 2007), which made it possible to use a regression approach to examine the predictive power of these variables for lexical decision and word naming performance. Analyses indicated that familiarity, AoA, imageability, and SER were all significant predictors of both lexical decision and word naming performance when they were added separately to a model containing the length and frequency of the compounds, as well as the lexeme frequencies. In addition, rated semantic transparency also predicted lexical decision performance. The database of English compound words should be beneficial to word recognition researchers who are interested in selecting items for experiments on compound words, and it will also allow researchers to conduct further analyses using the available data combined with word recognition times included in the English Lexicon Project.

Thick target total bremsstrahlung spectra of lead compounds in the photon energy region 1-10keV by 90Sr beta particles.

PubMed

Sharma, Suhansar Jit; Singh, Tajinder; Singh, Doordarshi; Singh, Amrit; Dhaliwal, A S

2017-12-01

Total bremsstrahlung spectral photon distribution generated in thick targets of lead compounds Pb(CH 3 COO) 2 ·3H 2 O, Pb(NO 3 ) 2 and PbCl 2 by 90 Sr beta particles has been investigated theoretically and experimentally in the photon energy region 1-10keV. The experimental results are compared with the theoretical models describing ordinary bremsstrahlung and the theoretical model which includes polarization bremsstrahlung into ordinary bremsstrahlung, in stripped approximation. It is observed that the experimental results show better agreement with the model which describes bremsstrahlung in stripped approximation in the energy range 3-10keV. However, the results show positive deviation in the photon energy region of 1-3keV. Further, it has been found that there is a continuous decrease of polarization bremsstrahlung contribution into ordinary bremsstrahlung in the formation of total bremsstrahlung spectra with increase in photon energy. The suppression of polarization bremsstrahlung has been observed due to the presence of large fraction of low Z elements in the compounds. The results clearly indicate that polarization bremsstrahlung plays an important role in the formation of total bremsstrahlung spectra in compounds in the studied energy region. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nanoengineering Testbed for Nanosolar Cell and Piezoelectric Compounds

DTIC Science & Technology

2012-02-29

element mesh. The third model was a 3D finite element mesh that included complete geometric representation of Berkovich tip. This model allows for a...height of the specimen. These simulations suggest the proper specimen size to approximate a body of semi-infinite extent for a given indentation depth...tip nanoindentation model was the third and final finite element mesh created for analysis and comparison. The material model and the finite element

Improvement of the Pharmacokinetics and In Vivo Antibacterial Efficacy of a Novel Type IIa Topoisomerase Inhibitor by Formulation in Liposomes

PubMed Central

Newman, Joseph; Goteti, Kosalaram; Beaudoin, Marie-Eve; Harrison, Rane; Hopkins, Sussie; Agrawal, Nikunj; Rivin, Olga

2013-01-01

Several useful properties of liposome-based formulations of various existing antibacterial drugs have been reported. These properties include lower MICs, improved pharmacokinetics, lower toxicity, selective distribution to infected tissues, and enhanced in vivo efficacy. Here we report in vivo studies of a liposomal formulation of a member of a novel class of antibacterial type II topoisomerase inhibitors, others of which have progressed to early phases of clinical trials. The free (i.e., nonliposomal) compound has broad-spectrum MICs but suboptimal pharmacokinetics in rats and mice, characterized by a high volume of distribution and rapid clearance. The liposomal formulation of the compound had essentially unchanged MICs but greatly reduced volume of distribution and clearance in rats and mice. In an in vivo mouse model of Staphylococcus aureus infection of one thigh, the liposomal compound localized preferentially to the infected thigh, whereas the free compound showed no preference for the infected versus the uninfected thigh. Most importantly, the liposomal compound had enhanced efficacy at clearing the infection compared with the free compound. Delivery of this class of compounds as liposomal formulations may offer clinical advantages compared with free compounds. PMID:23877679

Zebrafish Caudal Fin Angiogenesis Assay—Advanced Quantitative Assessment Including 3-Way Correlative Microscopy

PubMed Central

Correa Shokiche, Carlos; Schaad, Laura; Triet, Ramona; Jazwinska, Anna; Tschanz, Stefan A.; Djonov, Valentin

2016-01-01

Background Researchers evaluating angiomodulating compounds as a part of scientific projects or pre-clinical studies are often confronted with limitations of applied animal models. The rough and insufficient early-stage compound assessment without reliable quantification of the vascular response counts, at least partially, to the low transition rate to clinics. Objective To establish an advanced, rapid and cost-effective angiogenesis assay for the precise and sensitive assessment of angiomodulating compounds using zebrafish caudal fin regeneration. It should provide information regarding the angiogenic mechanisms involved and should include qualitative and quantitative data of drug effects in a non-biased and time-efficient way. Approach & Results Basic vascular parameters (total regenerated area, vascular projection area, contour length, vessel area density) were extracted from in vivo fluorescence microscopy images using a stereological approach. Skeletonization of the vasculature by our custom-made software Skelios provided additional parameters including “graph energy” and “distance to farthest node”. The latter gave important insights into the complexity, connectivity and maturation status of the regenerating vascular network. The employment of a reference point (vascular parameters prior amputation) is unique for the model and crucial for a proper assessment. Additionally, the assay provides exceptional possibilities for correlative microscopy by combining in vivo-imaging and morphological investigation of the area of interest. The 3-way correlative microscopy links the dynamic changes in vivo with their structural substrate at the subcellular level. Conclusions The improved zebrafish fin regeneration model with advanced quantitative analysis and optional 3-way correlative morphology is a promising in vivo angiogenesis assay, well-suitable for basic research and preclinical investigations. PMID:26950851

QSAR-like models: a potential tool for the selection of PhACs and EDCs for monitoring purposes in drinking water treatment systems--a review.

PubMed

Delgado, Luis F; Charles, Philippe; Glucina, Karl; Morlay, Catherine

2012-12-01

Recent studies have demonstrated the presence of trace-level pharmaceutically active compounds (PhACs) and endocrine disrupting compounds (EDCs) in a number of finished drinking waters (DWs). Since there is sparse knowledge currently available on the potential effects on human health associated with the chronic exposure to trace levels of these Emerging Contaminants (ECs) through routes such as DW, it is suggested that the most appropriate criterion is a treatment criterion in order to prioritize ECs to be monitored during DW preparation. Hence, only the few ECs showing the lowest removals towards a given DW Treatment (DWT) process would serve as indicators of the overall efficiency of this process and would be relevant for DW quality monitoring. In addition, models should be developed for estimating the removal of ECs in DWT processes, thereby overcoming the practical difficulties of experimentally assessing each compound. Therefore, the present review has two objectives: (1) to provide an overview of the recent scientific surveys on the occurrence of PhACs and EDCs in finished DWs; and (2) to propose the potential of Quantitative-Structure-Activity-Relationship-(QSAR)-like models to rank ECs found in environmental waters, including parent compounds, metabolites and transformation products, in order to select the most relevant compounds to be considered as indicators for monitoring purposes in DWT systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Antimycobacterial drug discovery using Mycobacteria-infected amoebae identifies anti-infectives and new molecular targets.

PubMed

Trofimov, Valentin; Kicka, Sébastien; Mucaria, Sabrina; Hanna, Nabil; Ramon-Olayo, Fernando; Del Peral, Laura Vela-Gonzalez; Lelièvre, Joël; Ballell, Lluís; Scapozza, Leonardo; Besra, Gurdyal S; Cox, Jonathan A G; Soldati, Thierry

2018-03-02

Tuberculosis remains a serious threat to human health world-wide, and improved efficiency of medical treatment requires a better understanding of the pathogenesis and the discovery of new drugs. In the present study, we performed a whole-cell based screen in order to complete the characterization of 168 compounds from the GlaxoSmithKline TB-set. We have established and utilized novel previously unexplored host-model systems to characterize the GSK compounds, i.e. the amoeboid organisms D. discoideum and A. castellanii, as well as a microglial phagocytic cell line, BV2. We infected these host cells with Mycobacterium marinum to monitor and characterize the anti-infective activity of the compounds with quantitative fluorescence measurements and high-content microscopy. In summary, 88.1% of the compounds were confirmed as antibiotics against M. marinum, 11.3% and 4.8% displayed strong anti-infective activity in, respectively, the mammalian and protozoan infection models. Additionally, in the two systems, 13-14% of the compounds displayed pro-infective activity. Our studies underline the relevance of using evolutionarily distant pathogen and host models in order to reveal conserved mechanisms of virulence and defence, respectively, which are potential "universal" targets for intervention. Subsequent mechanism of action studies based on generation of over-expresser M. bovis BCG strains, generation of spontaneous resistant mutants and whole genome sequencing revealed four new molecular targets, including FbpA, MurC, MmpL3 and GlpK.

In vivo screening and discovery of novel candidate thalidomide analogs in the zebrafish embryo and chicken embryo model systems

PubMed Central

Beedie, Shaunna L.; Rore, Holly M.; Barnett, Shelby; Chau, Cindy H.; Luo, Weiming; Greig, Nigel H.; Figg, William D.; Vargesson, Neil

2016-01-01

Thalidomide, a drug known for its teratogenic side-effects, is used successfully to treat a variety of clinical conditions including leprosy and multiple myeloma. Intense efforts are underway to synthesize and identify safer, clinically relevant analogs. Here, we conduct a preliminary in vivo screen of a library of new thalidomide analogs to determine which agents demonstrate activity, and describe a cohort of compounds with anti-angiogenic properties, anti-inflammatory properties and some compounds which exhibited both. The combination of the in vivo zebrafish and chicken embryo model systems allows for the accelerated discovery of new, potential therapies for cancerous and inflammatory conditions. PMID:27120781

Modeling mass transfer and reaction of dilute solutes in a ternary phase system by the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Fu, Yu-Hang; Bai, Lin; Luo, Kai-Hong; Jin, Yong; Cheng, Yi

2017-04-01

In this work, we propose a general approach for modeling mass transfer and reaction of dilute solute(s) in incompressible three-phase flows by introducing a collision operator in lattice Boltzmann (LB) method. An LB equation was used to simulate the solute dynamics among three different fluids, in which the newly expanded collision operator was used to depict the interface behavior of dilute solute(s). The multiscale analysis showed that the presented model can recover the macroscopic transport equations derived from the Maxwell-Stefan equation for dilute solutes in three-phase systems. Compared with the analytical equation of state of solute and dynamic behavior, these results are proven to constitute a generalized framework to simulate solute distributions in three-phase flows, including compound soluble in one phase, compound adsorbed on single-interface, compound in two phases, and solute soluble in three phases. Moreover, numerical simulations of benchmark cases, such as phase decomposition, multilayered planar interfaces, and liquid lens, were performed to test the stability and efficiency of the model. Finally, the multiphase mass transfer and reaction in Janus droplet transport in a straight microchannel were well reproduced.

Pharmacological and structure-activity relationship evaluation of 4-aryl-1-diphenylacetyl(thio)semicarbazides.

PubMed

Wujec, Monika; Kędzierska, Ewa; Kuśmierz, Edyta; Plech, Tomasz; Wróbel, Andrzej; Paneth, Agata; Orzelska, Jolanta; Fidecka, Sylwia; Paneth, Piotr

2014-04-16

This article describes the synthesis of six 4-aryl-(thio)semicarbazides (series a and b) linked with diphenylacetyl moiety along with their pharmacological evaluation on the central nervous system in mice and computational studies, including conformational analysis and electrostatic properties. All thiosemicarbazides (series b) were found to exhibit strong antinociceptive activity in the behavioural model. Among them, compound 1-diphenylacetyl-4-(4-methylphenyl)thiosemicarbazide 1b was found to be the most potent analgesic agent, whose activity is connected with the opioid system. For compounds from series a significant anti-serotonergic effect, especially for compound 1-diphenylacetyl-4-(4-methoxyphenyl)semicarbazide 2b was observed. The computational studies strongly support the obtained results.

Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures

PubMed Central

Baxendale, Sarah; Holdsworth, Celia J.; Meza Santoscoy, Paola L.; Harrison, Michael R. M.; Fox, James; Parkin, Caroline A.; Ingham, Philip W.; Cunliffe, Vincent T.

2012-01-01

SUMMARY The availability of animal models of epileptic seizures provides opportunities to identify novel anticonvulsants for the treatment of people with epilepsy. We found that exposure of 2-day-old zebrafish embryos to the convulsant agent pentylenetetrazole (PTZ) rapidly induces the expression of synaptic-activity-regulated genes in the CNS, and elicited vigorous episodes of calcium (Ca2+) flux in muscle cells as well as intense locomotor activity. We then screened a library of ∼2000 known bioactive small molecules and identified 46 compounds that suppressed PTZ-inducedtranscription of the synaptic-activity-regulated gene fos in 2-day-old (2 dpf) zebrafish embryos. Further analysis of a subset of these compounds, which included compounds with known and newly identified anticonvulsant properties, revealed that they exhibited concentration-dependent inhibition of both locomotor activity and PTZ-induced fos transcription, confirming their anticonvulsant characteristics. We conclude that this in situ hybridisation assay for fos transcription in the zebrafish embryonic CNS is a robust, high-throughput in vivo indicator of the neural response to convulsant treatment and lends itself well to chemical screening applications. Moreover, our results demonstrate that suppression of PTZ-induced fos expression provides a sensitive means of identifying compounds with anticonvulsant activities. PMID:22730455

RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

PubMed

Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

2015-01-01

Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

Molecular diversity management strategies for building and enhancement of diverse and focused lead discovery compound screening collections.

PubMed

Schuffenhauer, A; Popov, M; Schopfer, U; Acklin, P; Stanek, J; Jacoby, E

2004-12-01

This publication describes processes for the selection of chemical compounds for the building of a high-throughput screening (HTS) collection for drug discovery, using the currently implemented process in the Discovery Technologies Unit of the Novartis Institute for Biomedical Research, Basel Switzerland as reference. More generally, the currently existing compound acquisition models and practices are discussed. Our informatics, chemistry and biology-driven compound selection consists of two steps: 1) The individual compounds are filtered and grouped into three priority classes on the basis of their individual structural properties. Substructure filters are used to eliminate or penalize compounds based on unwanted structural properties. The similarity of the structures to reference ligands of the main proven druggable target families is computed, and drug-similar compounds are prioritized for the following diversity analysis. 2) The compounds are compared to the archive compounds and a diversity analysis is performed. This is done separately for the prioritized, regular and penalized compounds with increasingly stringent dissimilarity criterion. The process includes collecting vendor catalogues and monitoring the availability of samples together with the selection and purchase decision points. The development of a corporate vendor catalogue database is described. In addition to the selection methods on a per single molecule basis, selection criteria for scaffold and combinatorial chemistry projects in collaboration with compound vendors are discussed.

2-(Hetero(aryl)methylene)hydrazine-1-carbothioamides as potent urease inhibitors.

PubMed

Saeed, Aamer; Imran, Aqeel; Channar, Pervaiz A; Shahid, Mohammad; Mahmood, Wajahat; Iqbal, Jamshed

2015-02-01

A small series of 2-(hetero(aryl)methylene) hydrazine-1-carbothioamides including two aryl derivatives was synthesized and tested for their inhibitory activity against urease. Compound (E)-2-(Furan-2-ylmethylene) hydrazine-1-carbothioamide (3f), having a furan ring, was the most potent inhibitor of urease with an IC50 value of 0.58 μM. Molecular modeling was carried out through docking the designed compounds into the urease binding site to predict whether these derivatives have analogous binding mode to the urease inhibitors. The study revealed that all of the tested compounds bind with both metal atoms at the active site of the enzyme. The aromatic ring of the compounds forms ionic interactions with the residues, Ala(440), Asp(494), Ala(636), and Met(637). © 2014 John Wiley & Sons A/S.

Developing a novel dual PI3K–mTOR inhibitor from the prodrug of a metabolite

PubMed Central

Zhou, Yan; Zhang, Genyan; Wang, Feng; Wang, Jin; Ding, Yanwei; Li, Xinyu; Shi, Chongtie; Li, Jiakui; Shih, Chengkon; You, Song

2017-01-01

This study presents a process of developing a novel PI3K–mTOR inhibitor through the prodrug of a metabolite. The lead compound (compound 1) was identified with similar efficacy as that of NVP-BEZ235 in a tumor xenograft model, but the exposure of compound 1 was much lower than that of NVP-BEZ235. After reanalysis of the blood sample, a major metabolite (compound 2) was identified. Compound 2 exerted similar in vitro activity as compound 1, which indicated that compound 2 was an active metabolite and that the in vivo efficacy in the animal model came from compound 2 instead of compound 1. However, compound 1 was metabolized into compound 2 predominantly in the liver microsomes of mouse, but not in the liver microsomes of rat, dog, or human. In order to translate the efficacy in the animal model into clinical development or predict the pharmacokinetic/pharmacodynamic parameters in the clinical study using a preclinical model, we developed the metabolite (compound 2) instead of compound 1. Due to the low bioavailability of compound 2, its prodrug (compound 3) was designed and synthesized to improve the solubility. The prodrug was quickly converted to compound 2 through both intravenous and oral administrations. Because the prodrug (compound 3) did not improve the oral exposure of compound 2, developing compound 3 as an intravenous drug was considered by our team, and the latest results will be reported in the future. PMID:29118584

Writing and overwriting short-term memory

PubMed Central

Killeen, Peter R.

2008-01-01

An integrative account of short-term memory is based on data from pigeons trained to report the majority color in a sequence of lights. Performance showed strong recency effects, was invariant over changes in the interstimulus interval, and improved with increases in the intertrial interval. A compound model of binomial variance around geometrically decreasing memory described the data; a logit transformation rendered it isomorphic with other memory models. The model was generalized for variance in the parameters, where it was shown that averaging exponential and power functions from individuals or items with different decay rates generates new functions that are hyperbolic in time and in log time, respectively. The compound model provides a unified treatment of both the accrual and the dissipation of memory and is consistent with data from various experiments, including the choose-short bias in delayed recall, multielement stimuli, and Rubin and Wenzel’s (1996) meta-analyses of forgetting. PMID:11340865

Interstellar Polycyclic Aromatic Compounds and Astrophysics

NASA Technical Reports Server (NTRS)

Hudgins, Douglas M.; DeVincenzi, Donald (Technical Monitor)

2001-01-01

Over the past fifteen years, thanks to significant, parallel advancements in observational, experimental, and theoretical techniques, tremendous strides have been made in our understanding of the role polycyclic aromatic compounds (PAC) in the interstellar medium (ISM). Twenty years ago, the notion of an abundant population of large, carbon rich molecules in the ISM was considered preposterous. Today, the unmistakable spectroscopic signatures of PAC - shockingly large molecules by previous interstellar chemistry standards - are recognized throughout the Universe. In this paper, we will examine the interstellar PAC model and its importance to astrophysics, including: (1) the evidence which led to inception of the model; (2) the ensuing laboratory and theoretical studies of the fundamental spectroscopic properties of PAC by which the model has been refined and extended; and (3) a few examples of how the model is being exploited to derive insight into the nature of the interstellar PAC population.

Partitioning of polar and non-polar neutral organic chemicals into human and cow milk.

PubMed

Geisler, Anett; Endo, Satoshi; Goss, Kai-Uwe

2011-10-01

The aim of this work was to develop a predictive model for milk/water partition coefficients of neutral organic compounds. Batch experiments were performed for 119 diverse organic chemicals in human milk and raw and processed cow milk at 37°C. No differences (<0.3 log units) in the partition coefficients of these types of milk were observed. The polyparameter linear free energy relationship model fit the calibration data well (SD=0.22 log units). An experimental validation data set including hormones and hormone active compounds was predicted satisfactorily by the model. An alternative modelling approach based on log K(ow) revealed a poorer performance. The model presented here provides a significant improvement in predicting enrichment of potentially hazardous chemicals in milk. In combination with physiologically based pharmacokinetic modelling this improvement in the estimation of milk/water partitioning coefficients may allow a better risk assessment for a wide range of neutral organic chemicals. Copyright © 2011 Elsevier Ltd. All rights reserved.

Advanced Characterization of Semivolatile Organic Compounds Emitted from Biomass Burning

NASA Astrophysics Data System (ADS)

Hatch, L. E.; Liu, Y.; Rivas-Ubach, A.; Shaw, J. B.; Lipton, M. S.; Barsanti, K. C.

2016-12-01

Biomass burning (BB) emits large amounts of non-methane organic gases (NMOGs) and primary (directly emitted) particulate matter (PM). NMOGs also react in plume to form secondary PM (i.e., SOA) and ozone. BB-PM has been difficult to represent accurately in models used for chemistry and climate predictions, including for air quality and fire management purposes. Much recent research supports that many previously unconsidered SOA precursors exist, including oxidation of semivolatile compounds (SVOCs). Although many recent studies have characterized relatively volatile BB-derived NMOGs and relatively non-volatile particle-phase organic species, comparatively few studies have performed detailed characterization of SVOCs emitted from BB. Here we present efforts to expand the volatility and compositional ranges of compounds measured in BB smoke. In this work, samples of SVOCs in gas and particle phases were collected from 18 fires representing a range of fuel types during the 2016 FIREX fire laboratory campaign; samples were analyzed by two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS) and Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). Hundreds of compounds were detectable in both gas and particle phases by GCxGC-TOFMS whereas thousands of peaks were present in the FTICR mass spectra. Data from both approaches highlight that chemical fingerprints of smoke are fuel/burn-dependent. These efforts support our continued research in building the understanding and model representation of BB emissions and BB-derived SOA.

Advanced Characterization of Semivolatile Organic Compounds Emitted from Biomass Burning

NASA Astrophysics Data System (ADS)

Hatch, L. E.; Liu, Y.; Rivas-Ubach, A.; Shaw, J. B.; Lipton, M. S.; Barsanti, K. C.

2017-12-01

Biomass burning (BB) emits large amounts of non-methane organic gases (NMOGs) and primary (directly emitted) particulate matter (PM). NMOGs also react in plume to form secondary PM (i.e., SOA) and ozone. BB-PM has been difficult to represent accurately in models used for chemistry and climate predictions, including for air quality and fire management purposes. Much recent research supports that many previously unconsidered SOA precursors exist, including oxidation of semivolatile compounds (SVOCs). Although many recent studies have characterized relatively volatile BB-derived NMOGs and relatively non-volatile particle-phase organic species, comparatively few studies have performed detailed characterization of SVOCs emitted from BB. Here we present efforts to expand the volatility and compositional ranges of compounds measured in BB smoke. In this work, samples of SVOCs in gas and particle phases were collected from 18 fires representing a range of fuel types during the 2016 FIREX fire laboratory campaign; samples were analyzed by two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS) and Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). Hundreds of compounds were detectable in both gas and particle phases by GCxGC-TOFMS whereas thousands of peaks were present in the FTICR mass spectra. Data from both approaches highlight that chemical fingerprints of smoke are fuel/burn-dependent. These efforts support our continued research in building the understanding and model representation of BB emissions and BB-derived SOA.

Predictive teratology: teratogenic risk-hazard identification partnered in the discovery process.

PubMed

Augustine-Rauch, K A

2008-11-01

Unexpected teratogenicity is ranked as one of the most prevalent causes for toxicity-related attrition of drug candidates. Without proactive assessment, the liability tends to be identified relatively late in drug development, following significant investment in compound and engagement in pre clinical and clinical studies. When unexpected teratogenicity occurs in pre-clinical development, three principle questions arise: Can clinical trials that include women of child bearing populations be initiated? Will all compounds in this pharmacological class produce the same liability? Could this effect be related to the chemical structure resulting in undesirable off-target adverse effects? The first question is typically addressed at the time of the unexpected finding and involves considering the nature of the teratogenicity, whether or not maternal toxicity could have had a role in onset, human exposure margins and therapeutic indication. The latter two questions can be addressed proactively, earlier in the discovery process as drug target profiling and lead compound optimization is taking place. Such proactive approaches include thorough assessment of the literature for identification of potential liabilities and follow-up work that can be conducted on the level of target expression and functional characterization using molecular biology and developmental model systems. Developmental model systems can also be applied in the form of in vitro teratogenicity screens, and show potential for effective hazard identification or issue resolution on the level of characterizing teratogenic mechanism. This review discusses approaches that can be applied for proactive assessment of compounds for teratogenic liability.

In silico target prediction for elucidating the mode of action of herbicides including prospective validation.

PubMed

Chiddarwar, Rucha K; Rohrer, Sebastian G; Wolf, Antje; Tresch, Stefan; Wollenhaupt, Sabrina; Bender, Andreas

2017-01-01

The rapid emergence of pesticide resistance has given rise to a demand for herbicides with new mode of action (MoA). In the agrochemical sector, with the availability of experimental high throughput screening (HTS) data, it is now possible to utilize in silico target prediction methods in the early discovery phase to suggest the MoA of a compound via data mining of bioactivity data. While having been established in the pharmaceutical context, in the agrochemical area this approach poses rather different challenges, as we have found in this work, partially due to different chemistry, but even more so due to different (usually smaller) amounts of data, and different ways of conducting HTS. With the aim to apply computational methods for facilitating herbicide target identification, 48,000 bioactivity data against 16 herbicide targets were processed to train Laplacian modified Naïve Bayesian (NB) classification models. The herbicide target prediction model ("HerbiMod") is an ensemble of 16 binary classification models which are evaluated by internal, external and prospective validation sets. In addition to the experimental inactives, 10,000 random agrochemical inactives were included in the training process, which showed to improve the overall balanced accuracy of our models up to 40%. For all the models, performance in terms of balanced accuracy of≥80% was achieved in five-fold cross validation. Ranking target predictions was addressed by means of z-scores which improved predictivity over using raw scores alone. An external testset of 247 compounds from ChEMBL and a prospective testset of 394 compounds from BASF SE tested against five well studied herbicide targets (ACC, ALS, HPPD, PDS and PROTOX) were used for further validation. Only 4% of the compounds in the external testset lied in the applicability domain and extrapolation (and correct prediction) was hence impossible, which on one hand was surprising, and on the other hand illustrated the utilization of using applicability domains in the first place. However, performance better than 60% in balanced accuracy was achieved on the prospective testset, where all the compounds fell within the applicability domain, and which hence underlines the possibility of using target prediction also in the area of agrochemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

[Identification of alkylbenzenes being formed in the model reaction of ribose with lysine].

PubMed

Biller, Elzbieta

2012-01-01

While studying volatile compounds in model experiments which simulated the broiling of meat (the reactions of ribose with lysine), there were alkylbenzenes identified. They belong to food contaminants and they could be originated from the detergents and petroleum as well as geochemical samples, but they were also obtained in Maillard reactions. The aim of the studies was the attempt of the alkylbenzenes identification being formed in the model reaction of ribose with lysine. Aqueous solutions of ribose and lysine (at concentration of 0.1 mol/dm3 each) were mixed in equal volumes 10 cm3 + 10 cm3. The pH of the mixtures were adjusted to 5.6 using citrate-phosphorous buffer. In that way conditions simulating pH of meat were obtained. The mixtures were heated inside the gastronomic roaster during 0, 5, 10, 15, 30, 45 and 60 minutes respectively, at the temperature 185 +/- 5 degrees C. After reactions, in the mixtures, the profiles of volatile compounds, including alkylbenzenes, were analyzed by GC-MS method. The compounds were being identified by: comparing each mass spectrum (MS) with spectra from the known libraries of MS; calculating the linear retention indexes (LRI); seeking similar LRI values of analogue compounds in literature. Amounts of volatiles were calculated in relation to amount of internal standard (IS) [-], dividing the area of the compound by area of IS. The kinds and amounts of alkylbenzenes depended on the duration of the reaction time. Maximally 16 various alkylbenzenes were developed. More of these compounds could be identified with the probability of 85-90%, using only MS, because of the lack information in literature. Moreover, the multi-dimensional GCxGC-MS or other chromatographic methods in order to make these compounds being better explored seems to be advisable. The identification of the compounds being formed during broiling of meat is very important, because of the fact that many of arising substances are considered to be unhealthy and undesirable food contaminants. Thus these compounds should be routinely investigated in food products.

Qualitative and quantitative prediction of volatile compounds from initial amino acid profiles in Korean rice wine (makgeolli) model.

PubMed

Kang, Bo-Sik; Lee, Jang-Eun; Park, Hyun-Jin

2014-06-01

In Korean rice wine (makgeolli) model, we tried to develop a prediction model capable of eliciting a quantitative relationship between initial amino acids in makgeolli mash and major aromatic compounds, such as fusel alcohols, their acetate esters, and ethyl esters of fatty acids, in makgeolli brewed. Mass-spectrometry-based electronic nose (MS-EN) was used to qualitatively discriminate between makgeollis made from makgeolli mashes with different amino acid compositions. Following this measurement, headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (GC-MS) combined with partial least-squares regression (PLSR) method was employed to quantitatively correlate amino acid composition of makgeolli mash with major aromatic compounds evolved during makgeolli fermentation. In qualitative prediction with MS-EN analysis, the makgeollis were well discriminated according to the volatile compounds derived from amino acids of makgeolli mash. Twenty-seven ion fragments with mass-to-charge ratio (m/z) of 55 to 98 amu were responsible for the discrimination. In GC-MS combined with PLSR method, a quantitative approach between the initial amino acids of makgeolli mash and the fusel compounds of makgeolli demonstrated that coefficient of determination (R(2)) of most of the fusel compounds ranged from 0.77 to 0.94 in good correlation, except for 2-phenylethanol (R(2) = 0.21), whereas R(2) for ethyl esters of MCFAs including ethyl caproate, ethyl caprylate, and ethyl caprate was 0.17 to 0.40 in poor correlation. The amino acids have been known to affect the aroma in alcoholic beverages. In this study, we demonstrated that an electronic nose qualitatively differentiated Korean rice wines (makgeollis) by their volatile compounds evolved from amino acids with rapidity and reproducibility and successively, a quantitative correlation with acceptable R2 between amino acids and fusel compounds could be established via HS-SPME GC-MS combined with partial least-squares regression. Our approach for predicting the quantities of volatile compounds in the finished product from initial condition of fermentation will give an insight to food researchers to modify and optimize the qualities of the corresponding products. © 2014 Institute of Food Technologists®

QSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening

DTIC Science & Technology

2012-09-26

test set molecules that were not used to train the models . This allowed us to more accurately estimate the prediction power of the models . As...pathogens and deposited in PubChem Bioassays. Ultimately, the main purpose of this model is to make predictions , based on known antibacterial and non...the model built form the remaining compounds is used to predict the left out compound. Once all the compounds pass through this cycle of prediction , a

Modeling impacts of cold climates on vehicle emissions : final report.

DOT National Transportation Integrated Search

2017-01-20

Vehicle emissions include carbon monoxide (CO), nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), and air toxics such as benzene. Each of these pollutants is linked to adverse human health effects. To evaluate the contributions of ...

Development of an Analytic Method for Sulfur Compounds in Aged Garlic Extract with the Use of a Postcolumn High Performance Liquid Chromatography Method with Sulfur-Specific Detection.

PubMed

Matsutomo, Toshiaki; Kodera, Yukihiro

2016-02-01

Garlic and its processed preparations contain numerous sulfur compounds that are difficult to analyze in a single run using HPLC. The aim of this study was to develop a rapid and convenient sulfur-specific HPLC method to analyze sulfur compounds in aged garlic extract (AGE). We modified a conventional postcolumn HPLC method by employing a hexaiodoplatinate reagent. Identification and structural analysis of sulfur compounds were conducted by LC-mass spectrometry (LC-MS) and nuclear magnetic resonance. The production mechanisms of cis-S-1-propenylcysteine (cis-S1PC) and S-allylmercaptocysteine (SAMC) were examined by model reactions. Our method has the following advantages: less interference from nonsulfur compounds, high sensitivity, good correlation coefficients (r > 0.98), and high resolution that can separate >20 sulfur compounds, including several isomers, in garlic preparations in a single run. This method was adapted for LC-MS analysis. We identified cis-S1PC and γ-glutamyl-S-allyl-mercaptocysteine in AGE. The results of model reactions suggest that cis-S1PC is produced from trans-S1PC through an isomerization reaction and that SAMC is produced by a reaction involving S-allylcysteine/S1PC and diallyldisulfide during the aging period. We developed a rapid postcolumn HPLC method for both qualitative and quantitative analyses of sulfur compounds, and this method helped elucidate a potential mechanism of cis-S1PC and SAMC action in AGE. © 2016 American Society for Nutrition.

Therapeutic effect of the natural compounds baicalein and baicalin on autoimmune diseases.

PubMed

Xu, Jian; Liu, Jinlong; Yue, Guolin; Sun, Mingqiang; Li, Jinliang; Xiu, Xia; Gao, Zhenzhong

2018-05-23

A series of natural compounds have been implicated to be useful in regulating the pathogenesis of various autoimmune diseases. The present study demonstrated that the Scutellariae radix compounds baicalein and baicalin may serve as drugs for the treatment of autoimmune diseases, including rheumatoid arthritis and inflammatory bowel disease. Following the administration of baicalein and baicalin in vivo, T cell‑mediated autoimmune diseases in the mouse model were profoundly ameliorated: In the collagen‑induced arthritis model (CIA), the severity of the disease was reduced by baicalein and, consistently, baicalein was demonstrated to suppress T cell proliferation in CIA mice. In the dextran sodium sulfate (DSS)‑induced colitis model, the disease was attenuated by baicalin, and baicalin promoted colon epithelial cell (CEC) proliferation in vitro. The present study further revealed that the mRNA expression of signal transducer and activator of transcription (STAT)3 and STAT4 in the tyrosine‑protein kinase JAK‑STAT signaling pathway in T cells was downregulated by baicalein, contributing to its regulation of T cell proliferation. However, in the DSS model, the STAT4 transcription in CECs, which are the target cells of activated T cells in the gut, was downregulated by baicalin, suggesting that baicalein and baicalin mediated similar STAT expression in different cell types in autoimmune diseases. In conclusion, the similarly structured compounds baicalein and baicalin selectively exhibited therapeutic effects on autoimmune diseases by regulating cell proliferation and STAT gene expression, albeit in different cell types.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Identification of Catechin, Syringic Acid, and Procyanidin B2 in Wine as Stimulants of Gastric Acid Secretion.

PubMed

Liszt, Kathrin Ingrid; Eder, Reinhard; Wendelin, Sylvia; Somoza, Veronika

2015-09-09

Organic acids of wine, in addition to ethanol, have been identified as stimulants of gastric acid secretion. This study characterized the influence of other wine compounds, particularly phenolic compounds, on proton secretion. Forty wine parameters were determined in four red wines and six white wines, including the contents of organic acids and phenolic compounds. The secretory activity of the wines was determined in a gastric cell culture model (HGT-1 cells) by means of a pH-sensitive fluorescent dye. Red wines stimulated proton secretion more than white wines. Lactic acid and the phenolic compounds syringic acid, catechin, and procyanidin B2 stimulated proton secretion and correlated with the pro-secretory effect of the wines. Addition of the phenolic compounds to the least active white wine sample enhanced its proton secretory effect by 65 ± 21% (p < 0.05). These results indicate that not only malic and lactic acid but also bitter and astringent tasting phenolic compounds in wine contribute to its stimulatory effect on gastric acid secretion.

Substituted Caffeic and Ferulic Acid Phenethyl Esters: Synthesis, Leukotrienes Biosynthesis Inhibition, and Cytotoxic Activity.

PubMed

Morin, Pier; St-Coeur, Patrick-Denis; Doiron, Jérémie A; Cormier, Marc; Poitras, Julie J; Surette, Marc E; Touaibia, Mohamed

2017-07-06

Glioblastoma multiforme (GBM) is an aggressive brain tumor that correlates with short patient survival and for which therapeutic options are limited. Polyphenolic compounds, including caffeic acid phenethyl ester (CAPE, 1a ), have been investigated for their anticancer properties in several types of cancer. To further explore these properties in brain cancer cells, a series of caffeic and ferulic acid esters bearing additional oxygens moieties (OH or OCH₃) were designed and synthesized. (CAPE, 1a ), but not ferulic acid phenethyl ester (FAPE, 1b ), displayed substantial cytotoxicity against two glioma cell lines. Some but not all selected compounds derived from both (CAPE, 1a ) and (FAPE, 1b ) also displayed cytotoxicity. All CAPE-derived compounds were able to significantly inhibit 5-lipoxygenase (5-LO), however FAPE-derived compounds were largely ineffective 5-LO inhibitors. Molecular docking revealed new hydrogen bonds and π-π interactions between the enzyme and some of the investigated compounds. Overall, this work highlights the relevance of exploring polyphenolic compounds in cancer models and provides additional leads in the development of novel therapeutic strategies in gliomas.

MDN-0170, a New Napyradiomycin from Streptomyces sp. Strain CA-271078

PubMed Central

Lacret, Rodney; Pérez-Victoria, Ignacio; Oves-Costales, Daniel; de la Cruz, Mercedes; Domingo, Elizabeth; Martín, Jesús; Díaz, Caridad; Vicente, Francisca; Genilloud, Olga; Reyes, Fernando

2016-01-01

A new napyradiomycin, MDN-0170 (1), was isolated from the culture broth of the marine-derived actinomycete strain CA-271078, together with three known related compounds identified as 4-dehydro-4a-dechloronapyradiomycin A1 (2), napyradiomycin A1 (3) and 3-chloro-6,8-dihydroxy-8-α-lapachone (4). The structure of the new compound was determined using a combination of spectroscopic techniques, including 1D and 2D NMR and electrospray-time of flight mass spectrometry (ESI-TOF MS). The relative configuration of compound 1, which contains two independent stereoclusters, has been established by molecular modelling in combination with nOe and coupling constant analyses. Biosynthetic arguments also allowed us to propose its absolute stereochemistry. The antimicrobial properties of the compounds isolated were evaluated against methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli, Aspergillus fumigatus, and Candida albicans. The potent bioactivity previously reported for compounds 2 and 3 against methicillin-sensitive S. aureus has been extended to methicillin-resistant strains in this report. PMID:27763545

Docking and Hydropathic Scoring of Polysubstituted Pyrrole Compounds with Anti-Tubulin Activity

PubMed Central

Tripathi, Ashutosh; Fornabaio, Micaela; Kellogg, Glen E.; Gupton, John T.; Gewirtz, David A.; Yeudall, W. Andrew; Vega, Nina E.; Mooberry, Susan L.

2008-01-01

Compounds that bind at the colchicine site of tubulin have drawn considerable attention with studies indicating that these agents suppress microtubule dynamics and inhibit tubulin polymerization. Data for eighteen polysubstituted pyrrole compounds are reported, including antiproliferative activity against human MDA-MB-435 cells and calculated free energies of binding following docking the compounds into models of αβ-tubulin. These docking calculations coupled with HINT interaction analyses are able to represent the complex structures and the binding modes of inhibitors such that calculated and measured free energies of binding correlate with an r2 of 0.76. Structural analysis of the binding pocket identifies important intermolecular contacts that mediate binding. As seen experimentally, the complex with JG-03-14 (3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2- carboxylic acid ethyl ester) is the most stable. These results illuminate the binding process and should be valuable in the design of new pyrrole-based colchicine site inhibitors as these compounds have very accessible syntheses. PMID:18083520

Discovery of potent cytotoxic ortho-aryl chalcones as new scaffold targeting tubulin and mitosis with affinity-based fluorescence.

PubMed

Zhu, Cuige; Zuo, Yinglin; Wang, Ruimin; Liang, Baoxia; Yue, Xin; Wen, Gesi; Shang, Nana; Huang, Lei; Chen, Yu; Du, Jun; Bu, Xianzhang

2014-08-14

A series of new ortho-aryl chalcones have been designed and synthesized. Many of these compounds were found to exhibit significant antiproliferation activity toward a panel of cancer cell lines. Selected compounds show potent cytotoxicity against several drug resistant cell lines including paclitaxel (Taxol) resistant human ovarian carcinoma cells, vincristine resistant human ileocecum carcinoma cells, and doxorubicin resistant human breast carcinoma cells. Further investigation revealed that active analogues could inhibit the microtubule polymerization by binding to colchicine site and thus induce multipolar mitosis, G2/M phase arrest, and apoptosis of cancer cells. Furthermore, affinity-based fluorescence enhancement was observed during the binding of active compounds with tubulin, which greatly facilitated the determination of tubulin binding site of the compounds. Finally, selected compound 26 was found to exhibit obvious in vivo antitumor activity in A549 tumor xenografts model. Our systematic studies implied a new scaffold targeting tubulin and mitosis for novel antitumor drug discovery.

Interspecies interactions stimulate diversification of the Streptomyces coelicolor secreted metabolome.

PubMed

Traxler, Matthew F; Watrous, Jeramie D; Alexandrov, Theodore; Dorrestein, Pieter C; Kolter, Roberto

2013-08-20

Soils host diverse microbial communities that include filamentous actinobacteria (actinomycetes). These bacteria have been a rich source of useful metabolites, including antimicrobials, antifungals, anticancer agents, siderophores, and immunosuppressants. While humans have long exploited these compounds for therapeutic purposes, the role these natural products may play in mediating interactions between actinomycetes has been difficult to ascertain. As an initial step toward understanding these chemical interactions at a systems level, we employed the emerging techniques of nanospray desorption electrospray ionization (NanoDESI) and matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) imaging mass spectrometry to gain a global chemical view of the model bacterium Streptomyces coelicolor interacting with five other actinomycetes. In each interaction, the majority of secreted compounds associated with S. coelicolor colonies were unique, suggesting an idiosyncratic response from S. coelicolor. Spectral networking revealed a family of unknown compounds produced by S. coelicolor during several interactions. These compounds constitute an extended suite of at least 12 different desferrioxamines with acyl side chains of various lengths; their production was triggered by siderophores made by neighboring strains. Taken together, these results illustrate that chemical interactions between actinomycete bacteria exhibit high complexity and specificity and can drive differential secondary metabolite production. Actinomycetes, filamentous actinobacteria from the soil, are the deepest natural source of useful medicinal compounds, including antibiotics, antifungals, and anticancer agents. There is great interest in developing new strategies that increase the diversity of metabolites secreted by actinomycetes in the laboratory. Here we used several metabolomic approaches to examine the chemicals made by these bacteria when grown in pairwise coculture. We found that these interspecies interactions stimulated production of numerous chemical compounds that were not made when they grew alone. Among these compounds were at least 12 different versions of a molecule called desferrioxamine, a siderophore used by the bacteria to gather iron. Many other compounds of unknown identity were also observed, and the pattern of compound production varied greatly among the interaction sets. These findings suggest that chemical interactions between actinomycetes are surprisingly complex and that coculture may be a promising strategy for finding new molecules from actinomycetes.

QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity.

PubMed

Sousa, Inês J; Ferreira, Maria-José U; Molnár, Joseph; Fernandes, Miguel X

2013-02-14

Multidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatrophane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure-activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to determine which structural modifications can be performed to improve their activity. Using experimental biological data at two concentrations (4 and 40 μg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for biological activities at compound concentrations of 4 and 40 μg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R²(pred) values of 0.765 and 0.534 for biological activities at compound concentrations of 4 and 40 μg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 μg/ml concentrations, respectively. For the same concentrations, the obtained R²(pred) values for jatrophanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability. Copyright © 2012 Elsevier B.V. All rights reserved.

Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.

PubMed

Catana, Cornel; Gao, Hua; Orrenius, Christian; Stouten, Pieter F W

2005-01-01

Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys. It has a correlation coefficient (r2) of 0.935 and a root-mean-square error (RMSE) of 0.468 log molar solubility (log S(w)). The model validated on a test set of 177 compounds not included in the training set has r2 0.911 and RMSE 0.475 log S(w). The descriptors were ranked according to their importance, and at the top of the list have been found the 22 MOE descriptors. The CR model produced results as good as PLS, and because of the way in which cross-validation has been done it is expected to be a valuable tool in prediction besides PLS model. The statistics obtained using nonlinear methods did not surpass those got with linear ones. The good statistic obtained for linear PLS and CR recommends these models to be used in prediction when it is difficult or impossible to make experimental measurements, for virtual screening, combinatorial library design, and efficient leads optimization.

Calculating pKa values for substituted phenols and hydration energies for other compounds with the first-order Fuzzy-Border continuum solvation model

PubMed Central

Sharma, Ity; Kaminski, George A.

2012-01-01

We have computed pKa values for eleven substituted phenol compounds using the continuum Fuzzy-Border (FB) solvation model. Hydration energies for 40 other compounds, including alkanes, alkenes, alkynes, ketones, amines, alcohols, ethers, aromatics, amides, heterocycles, thiols, sulfides and acids have been calculated. The overall average unsigned error in the calculated acidity constant values was equal to 0.41 pH units and the average error in the solvation energies was 0.076 kcal/mol. We have also reproduced pKa values of propanoic and butanoic acids within ca. 0.1 pH units from the experimental values by fitting the solvation parameters for carboxylate ion carbon and oxygen atoms. The FB model combines two distinguishing features. First, it limits the amount of noise which is common in numerical treatment of continuum solvation models by using fixed-position grid points. Second, it employs either second- or first-order approximation for the solvent polarization, depending on a particular implementation. These approximations are similar to those used for solute and explicit solvent fast polarization treatment which we developed previously. This article describes results of employing the first-order technique. This approximation places the presented methodology between the Generalized Born and Poisson-Boltzmann continuum solvation models with respect to their accuracy of reproducing the many-body effects in modeling a continuum solvent. PMID:22815192

Bivalent compound 17MN exerts neuroprotection through interaction at multiple sites in a cellular model of Alzheimer’s disease

PubMed Central

Liu, Kai; Chojnacki, Jeremy E.; Wade, Emily E.; Saathoff, John M.; Lesnefsky, Edward J.; Chen, Qun; Zhang, Shijun

2016-01-01

Multiple pathogenic factors have been suggested in playing a role in the development of Alzheimer’s disease (AD). The multifactorial nature of AD also suggests the potential use of compounds with polypharmacology as effective disease-modifying agents. Recently, we have developed a bivalent strategy to include cell membrane anchorage into the molecular design. Our results demonstrated that the bivalent compounds exhibited multifunctional properties and potent neuroprotection in a cellular AD model. Herein, we report the mechanistic exploration of one of the representative bivalent compounds, 17MN, in MC65 cells. Our results established that MC65 cells die through a necroptotic mechanism upon the removal of tetracycline (TC). Furthermore, we have shown that mitochondrial membrane potential (MMP) and cytosolic Ca2+ levels are increased upon removal of TC. Our bivalent compound 17MN can reverse such changes and protect MC65 cells from TC removal induced cytotoxicity. The results also suggest that 17MN may function between the Aβ species and RIPK1 in producing its neuroprotection. Colocalization studies employing a fluorescent analog of 17MN and confocal microscopy demonstrated the interactions of 17MN with both mitochondria and endoplasmic reticulum (ER), thus suggesting that 17MN exerts its neuroprotection via a multiple-site mechanism in MC65 cells. Collectively, these results strongly support our original design rationale of bivalent compounds and encourage further optimization of this bivalent strategy to develop more potent analogs as novel disease-modifying agents for AD. PMID:26401780

High performance addition-type thermoplastics (ATTs) - Evidence for the formation of a Diels-Alder adduct in the reaction of an acetylene-terminated material and a bismaleimide

NASA Technical Reports Server (NTRS)

Pater, R. H.; Soucek, M. D.; Chang, A. C.; Partos, R. D.

1991-01-01

Recently, the concept and demonstration of a new versatile synthetic reaction for making a large number of high-performance addition-type thermoplastics (ATTs) were reported. The synthesis shows promise for providing polymers having an attractive combination of easy processability, good toughness, respectable high temperature mechanical performance, and excellent thermo-oxidative stability. The new chemistry involves the reaction of an acetylene-terminated material with a bismaleimide or benzoquinone. In order to clarify the reaction mechanism, model compound studies were undertaken in solutions as well as in the solid state. The reaction products were purified by flash chromatography and characterized by conventional analytical techniques including NMR, FT-IR, UV-visible, mass spectroscopy, and high pressure liquid chromatography. The results are presented of the model compound studies which strongly support the formation of a Diels-Alder adduct in the reaction of an acetylene-terminated compound and a bismaleimide or benzoquinone.

pH-sensitive Eudragit nanoparticles for mucosal drug delivery.

PubMed

Yoo, Jin-Wook; Giri, Namita; Lee, Chi H

2011-01-17

Drug delivery via vaginal epithelium has suffered from lack of stability due to acidic and enzymatic environments. The biocompatible pH-sensitive nanoparticles composed of Eudragit S-100 (ES) were developed to protect loaded compounds from being degraded under the rigorous vaginal conditions and achieve their therapeutically effective concentrations in the mucosal epithelium. ES nanoparticles containing a model compound (sodium fluorescein (FNa) or nile red (NR)) were prepared by the modified quasi-emulsion solvent diffusion method. Loading efficiencies were found to be 26% and 71% for a hydrophilic and a hydrophobic compound, respectively. Both hydrophilic and hydrophobic model drugs remained stable in nanoparticles at acidic pH, whereas they are quickly released from nanoparticles upon exposure at physiological pH. The confocal study revealed that ES nanoparticles were taken up by vaginal cells, followed by pH-responsive drug release, with no cytotoxic activities. The pH-sensitive nanoparticles would be a promising carrier for the vaginal-specific delivery of various therapeutic drugs including microbicides and peptides/proteins. Published by Elsevier B.V.

Topoisomerase I and II inhibitors: chemical structure, mechanisms of action and role in cancer chemotherapy

NASA Astrophysics Data System (ADS)

Dezhenkova, L. G.; Tsvetkov, V. B.; Shtil, A. A.

2014-01-01

The review summarizes and analyzes recent published data on topoisomerase I and II inhibitors as potential antitumour agents. Functions and the mechanism of action of topoisomerases are considered. The molecular mechanism of interactions between low-molecular-weight compounds and these proteins is discussed. Topoisomerase inhibitors belonging to different classes of chemical compounds are systematically covered. Assays for the inhibition of topoisomerases and the possibilities of using the computer-aided modelling for the rational design of novel drugs for cancer chemotherapy are presented. The bibliography includes 127 references.

Oral Administration of the Broad-Spectrum Antibiofilm Compound Toremifene Inhibits Candida albicans and Staphylococcus aureus Biofilm Formation In Vivo

PubMed Central

De Cremer, Kaat; Delattin, Nicolas; De Brucker, Katrijn; Peeters, Annelies; Kucharíková, Soña; Gerits, Evelien; Verstraeten, Natalie; Michiels, Jan; Van Dijck, Patrick; Thevissen, Karin

2014-01-01

We here report on the in vitro activity of toremifene to inhibit biofilm formation of different fungal and bacterial pathogens, including Candida albicans, Candida glabrata, Candida dubliniensis, Candida krusei, Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis. We validated the in vivo efficacy of orally administered toremifene against C. albicans and S. aureus biofilm formation in a rat subcutaneous catheter model. Combined, our results demonstrate the potential of toremifene as a broad-spectrum oral antibiofilm compound. PMID:25288093

Machine learning models for lipophilicity and their domain of applicability.

PubMed

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Laak, Antonius Ter; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-01-01

Unfavorable lipophilicity and water solubility cause many drug failures; therefore these properties have to be taken into account early on in lead discovery. Commercial tools for predicting lipophilicity usually have been trained on small and neutral molecules, and are thus often unable to accurately predict in-house data. Using a modern Bayesian machine learning algorithm--a Gaussian process model--this study constructs a log D7 model based on 14,556 drug discovery compounds of Bayer Schering Pharma. Performance is compared with support vector machines, decision trees, ridge regression, and four commercial tools. In a blind test on 7013 new measurements from the last months (including compounds from new projects) 81% were predicted correctly within 1 log unit, compared to only 44% achieved by commercial software. Additional evaluations using public data are presented. We consider error bars for each method (model based error bars, ensemble based, and distance based approaches), and investigate how well they quantify the domain of applicability of each model.

Osmotic Compounds Enhance Antibiotic Efficacy against Acinetobacter baumannii Biofilm Communities

PubMed Central

Falghoush, Azeza; Beyenal, Haluk; Besser, Thomas E.; Omsland, Anders

2017-01-01

ABSTRACT Biofilm-associated infections are a clinical challenge, in part because a hydrated matrix protects the bacterial community from antibiotics. Herein, we evaluated how different osmotic compounds (maltodextrin, sucrose, and polyethylene glycol [PEG]) enhance antibiotic efficacy against Acinetobacter baumannii biofilm communities. Established (24-h) test tube biofilms (strain ATCC 17978) were treated with osmotic compounds in the presence or absence of 10× the MIC of different antibiotics (50 μg/ml tobramycin, 20 μg/ml ciprofloxacin, 300 μg/ml chloramphenicol, 30 μg/ml nalidixic acid, or 100 μg/ml erythromycin). Combining antibiotics with hypertonic concentrations of the osmotic compounds for 24 h reduced the number of biofilm bacteria by 5 to 7 log (P < 0.05). Increasing concentrations of osmotic compounds improved the effect, but there was a trade-off with increasing solution viscosity, whereby low-molecular-mass compounds (sucrose, 400-Da PEG) worked better than higher-mass compounds (maltodextrin, 3,350-Da PEG). Ten other A. baumannii strains were similarly treated with 400-Da PEG and tobramycin, resulting in a mean 2.7-log reduction in recoverable bacteria compared with tobramycin treatment alone. Multivariate regression models with data from different osmotic compounds and nine antibiotics demonstrated that the benefit from combining hypertonic treatments with antibiotics is a function of antibiotic mass and lipophilicity (r2 > 0.82; P < 0.002), and the relationship was generalizable for biofilms formed by A. baumannii and Escherichia coli K-12. Augmenting topical antibiotic therapies with a low-mass hypertonic treatment may enhance the efficacy of antibiotics against wound biofilms, particularly when using low-mass hydrophilic antibiotics. IMPORTANCE Biofilms form a barrier that protects bacteria from environmental insults, including exposure to antibiotics. We demonstrated that multiple osmotic compounds can enhance antibiotic efficacy against Acinetobacter baumannii biofilm communities, but viscosity is a limiting factor, and the most effective compounds have lower molecular mass. The synergism between osmotic compounds and antibiotics is also dependent on the hydrophobicity and mass of the antibiotics. The statistical models presented herein provide a basis for predicting the optimal combination of osmotic compounds and antibiotics against surface biofilms communities. PMID:28733283

Excavating Anticonvulsant Compounds from Prescriptions of Traditional Chinese Medicine in the Treatment of Epilepsy.

PubMed

Zhao, Zefeng; He, Xirui; Ma, Cuixia; Wu, Shaoping; Cuan, Ye; Sun, Ying; Bai, Yajun; Huang, Linhong; Chen, Xufei; Gao, Tian; Zheng, Xiaohui

2018-05-08

Traditional Chinese medicine (TCM) has a long history and been widely used in prevention and treatment of epilepsy in China. This paper is intended to review the advances in the active anticonvulsant compounds isolated from herbs in the prescription of TCM in the treatment of epilepsy. These compounds were introduced with the details including classification, CAS number specific structure and druggability data. Meanwhile, much of the research in these compounds in the last two decades has shown that they exhibited favorable pharmacological properties in treatment of epilepsy both in in vivo and in vitro models. In addition, in this present review, the evaluation of the effects of the anticonvulsant classical TCM prescriptions is discussed. According to these rewarding pharmacological effects and chemical substances, the prescription of TCM herbs could be an effective therapeutic strategy for epilepsy patients, and also could be a promising source for the development of new drugs.

Optimization of conditions for thermal treatment of rice bran using an accelerator including an organo-iron compound.

PubMed

Kanno, Hikari; Tachibana, Naoya; Fukushima, Masami

2011-02-01

A method for thermal conversion of raw organic waste (ROW) to a compost-like material (CLM) with higher levels of unsaturated carbohydrates, nitrogen- and oxygen-containing compounds was developed, in which rice bran and an organo-iron compound were employed as a model ROW and the accelerator, respectively. To evaluate the qualities of CLMs, organic substances of an acid insoluble fraction of alkaline extracts (AIAEs) from a CLM were structurally characterized by elemental analysis, pyrolysis-gas chromatography/mass spectrometry and FT-IR. The levels of unsaturated carbohydrates, and nitrogen- and oxygen-containing compounds in the CLM samples were increased by long-term treatment (60°C for 5 days, 170°C for 3 days). In particular, the high lipid content of the AIAEs, which was indicative of inadequate digestion of CLM components, was dramatically reduced in the presence of the accelerator. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development and Validation of an Automated High-Throughput System for Zebrafish In Vivo Screenings

PubMed Central

Virto, Juan M.; Holgado, Olaia; Diez, Maria; Izpisua Belmonte, Juan Carlos; Callol-Massot, Carles

2012-01-01

The zebrafish is a vertebrate model compatible with the paradigms of drug discovery. The small size and transparency of zebrafish embryos make them amenable for the automation necessary in high-throughput screenings. We have developed an automated high-throughput platform for in vivo chemical screenings on zebrafish embryos that includes automated methods for embryo dispensation, compound delivery, incubation, imaging and analysis of the results. At present, two different assays to detect cardiotoxic compounds and angiogenesis inhibitors can be automatically run in the platform, showing the versatility of the system. A validation of these two assays with known positive and negative compounds, as well as a screening for the detection of unknown anti-angiogenic compounds, have been successfully carried out in the system developed. We present a totally automated platform that allows for high-throughput screenings in a vertebrate organism. PMID:22615792

A practical drug discovery project at the undergraduate level.

PubMed

Fray, M Jonathan; Macdonald, Simon J F; Baldwin, Ian R; Barton, Nick; Brown, Jack; Campbell, Ian B; Churcher, Ian; Coe, Diane M; Cooper, Anthony W J; Craven, Andrew P; Fisher, Gail; Inglis, Graham G A; Kelly, Henry A; Liddle, John; Maxwell, Aoife C; Patel, Vipulkumar K; Swanson, Stephen; Wellaway, Natalie

2013-12-01

In this article, we describe a practical drug discovery project for third-year undergraduates. No previous knowledge of medicinal chemistry is assumed. Initial lecture workshops cover the basic principles; then students, in teams, seek to improve the profile of a weakly potent, insoluble phosphatidylinositide 3-kinase delta (PI3Kδ) inhibitor (1) through compound array design, molecular modelling, screening data analysis and the synthesis of target compounds in the laboratory. The project benefits from significant industrial support, including lectures, student mentoring and consumables. The aim is to make the learning experience as close as possible to real-life industrial situations. In total, 48 target compounds were prepared, the best of which (5b, 5j, 6b and 6ap) improved the potency and aqueous solubility of the lead compound (1) by 100-1000 fold and ≥tenfold, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

A direct and fast method to monitor lipid oxidation progress in model fatty acid methyl esters by high-performance size-exclusion chromatography.

PubMed

Márquez-Ruiz, G; Holgado, F; García-Martínez, M C; Dobarganes, M C

2007-09-21

A new method based on high-performance size-exclusion chromatography (HPSEC) is proposed to quantitate primary and secondary oxidation compounds in model fatty acid methyl esters (FAMEs). The method consists on simply injecting an aliquot sample in HPSEC, without preliminary isolation procedures neither addition of standard internal. Four groups of compounds can be quantified, namely, unoxidised FAME, oxidised FAME monomers including hydroperoxides, FAME dimers and FAME polymers. Results showed high repeatability and sensitivity, and substantial advantages versus determination of residual substrate by gas-liquid chromatography. Applicability of the method is shown through selected data obtained by numerous oxidation experiments on pure FAME, mainly methyl linoleate, at ambient and moderate temperatures.

Neuroprotective Effects of the Securinine-Analogues: Identification of Allomargaritarine as a Lead Compound.

PubMed

Neganova, Margarita E; Klochkov, Sergei G; Afanasieva, Svetlana V; Serkova, Tatiana P; Chudinova, Ekaterina S; Bachurin, Sergei O; Reddy, V Prakash; Aliev, Gjumrakch; Shevtsova, Elena F

2016-01-01

Oxidative stress and mitochondrial disturbances are the common and important causative factors of aging, and play an important role in the late onset of sporadic neurodegenerative diseases, including Alzheimer disease (AD). Furthermore, emerging evidence from in vitro and in vivo disease models suggests that oxidative stress and increased vulnerability to induction of mitochondrial permeability transition leads to the pathogenesis of the neurological disorders. Towards the goals of developing effective neuroprotectors, this article describes the synthesis and neuroprotective studies of various derivatives of the naturally occurring alkaloid securinine, based on which a lead compound, allomargaritarine (a diastereomer of margaritarine), was identified as an effective therapeutic for neuroprotection. Allomargaritarine exhibits high antioxidant activity, and has significant mitoprotective effect on cellular models of neurodegeneration.

Large unexplained suite of chemically reactive compounds present in ambient air due to biomass fires.

PubMed

Kumar, V; Chandra, B P; Sinha, V

2018-01-12

Biomass fires impact global atmospheric chemistry. The reactive compounds emitted and formed due to biomass fires drive ozone and organic aerosol formation, affecting both air quality and climate. Direct hydroxyl (OH) Reactivity measurements quantify total gaseous reactive pollutant loadings and comparison with measured compounds yields the fraction of unmeasured compounds. Here, we quantified the magnitude and composition of total OH reactivity in the north-west Indo-Gangetic Plain. More than 120% increase occurred in total OH reactivity (28 s -1 to 64 s -1 ) and from no missing OH reactivity in the normal summertime air, the missing OH reactivity fraction increased to ~40 % in the post-harvest summertime period influenced by large scale biomass fires highlighting presence of unmeasured compounds. Increased missing OH reactivity between the two summertime periods was associated with increased concentrations of compounds with strong photochemical source such as acetaldehyde, acetone, hydroxyacetone, nitromethane, amides, isocyanic acid and primary emissions of acetonitrile and aromatic compounds. Currently even the most detailed state-of-the art atmospheric chemistry models exclude formamide, acetamide, nitromethane and isocyanic acid and their highly reactive precursor alkylamines (e.g. methylamine, ethylamine, dimethylamine, trimethylamine). For improved understanding of atmospheric chemistry-air quality-climate feedbacks in biomass-fire impacted atmospheric environments, future studies should include these compounds.

Nature as a source of metabolites with cholinesterase-inhibitory activity: an approach to Alzheimer's disease treatment.

PubMed

Pinho, Brígida R; Ferreres, Federico; Valentão, Patrícia; Andrade, Paula B

2013-12-01

Alzheimer's disease (AD) is the most common cause of dementia, being responsible for high healthcare costs and familial hardships. Despite the efforts of researchers, no treatment able to delay or stop AD progress exists. Currently, the available treatments are only symptomatic, cholinesterase inhibitors being the most widely used drugs. Here we describe several natural compounds with anticholinesterase (acetylcholinesterase and butyrylcholinesterase) activity and also some synthetic compounds whose structures are based on those of natural compounds. Galantamine and rivastigmine are two cholinesterase inhibitors used in therapeutics: galantamine is a natural alkaloid that was extracted for the first time from Galanthus nivalis L., while rivastigmine is a synthetic alkaloid, the structure of which is modelled on that of natural physostigmine. Alkaloids include a high number of compounds with anticholinesterases activity at the submicromolar range. Quinones and stilbenes are less well studied regarding cholinesterase inhibition, although some of them, such as sargaquinoic acid or (+)-α-viniferin, show promising activity. Among flavonoids, flavones and isoflavones are the most potent compounds. Xanthones and monoterpenes are generally weak cholinesterase inhibitors. Nature is an almost endless source of bioactive compounds. Several natural compounds have anticholinesterase activity and others can be used as leader compounds for the synthesis of new drugs. © 2013 Royal Pharmaceutical Society.

Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.

Small constrained SP1-7 analogs bind to a unique site and promote anti-allodynic effects following systemic injection in mice.

PubMed

Jonsson, A; Fransson, R; Haramaki, Y; Skogh, A; Brolin, E; Watanabe, H; Nordvall, G; Hallberg, M; Sandström, A; Nyberg, F

2015-07-09

Previous results have shown that the substance P (SP) N-terminal fragment SP1-7 may attenuate hyperalgesia and produce anti-allodynia in animals using various experimental models for neuropathic pain. The heptapeptide was found to induce its effects through binding to and activating specific sites apart from any known neurokinin or opioid receptor. Furthermore, we have applied a medicinal chemistry program to develop lead compounds mimicking the effect of SP1-7. The present study was designed to evaluate the pharmacological effect of these compounds using the mouse spared nerve injury (SNI) model of chronic neuropathic pain. Also, as no comprehensive screen with the aim to identify the SP1-7 target has yet been performed we screened our lead compound H-Phe-Phe-NH2 toward a panel of drug targets. The extensive target screen, including 111 targets, did not reveal any hit for the binding site among a number of known receptors or enzymes involved in pain modulation. Our animal studies confirmed that SP1-7, but also synthetic analogs thereof, possesses anti-allodynic effects in the mouse SNI model of neuropathic pain. One of the lead compounds, a constrained H-Phe-Phe-NH2 analog, was shown to exhibit a significant anti-allodynic effect. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

eBASIS (Bioactive Substances in Food Information Systems) and Bioactive Intakes: Major Updates of the Bioactive Compound Composition and Beneficial Bioeffects Database and the Development of a Probabilistic Model to Assess Intakes in Europe.

PubMed

Plumb, Jenny; Pigat, Sandrine; Bompola, Foteini; Cushen, Maeve; Pinchen, Hannah; Nørby, Eric; Astley, Siân; Lyons, Jacqueline; Kiely, Mairead; Finglas, Paul

2017-03-23

eBASIS (Bioactive Substances in Food Information Systems), a web-based database that contains compositional and biological effects data for bioactive compounds of plant origin, has been updated with new data on fruits and vegetables, wheat and, due to some evidence of potential beneficial effects, extended to include meat bioactives. eBASIS remains one of only a handful of comprehensive and searchable databases, with up-to-date coherent and validated scientific information on the composition of food bioactives and their putative health benefits. The database has a user-friendly, efficient, and flexible interface facilitating use by both the scientific community and food industry. Overall, eBASIS contains data for 267 foods, covering the composition of 794 bioactive compounds, from 1147 quality-evaluated peer-reviewed publications, together with information from 567 publications describing beneficial bioeffect studies carried out in humans. This paper highlights recent updates and expansion of eBASIS and the newly-developed link to a probabilistic intake model, allowing exposure assessment of dietary bioactive compounds to be estimated and modelled in human populations when used in conjunction with national food consumption data. This new tool could assist small- and medium-sized enterprises (SMEs) in the development of food product health claim dossiers for submission to the European Food Safety Authority (EFSA).

Homology modeling and virtual screening to discover potent inhibitors targeting the imidazole glycerophosphate dehydratase protein in Staphylococcus xylosus

NASA Astrophysics Data System (ADS)

Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

2017-11-01

The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus (S. xylosus) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus. Nine hits were identified from 2500 compounds by docking studies. Then, these 9 compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus. Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

Homology Modeling and Virtual Screening to Discover Potent Inhibitors Targeting the Imidazole Glycerophosphate Dehydratase Protein in Staphylococcus xylosus.

PubMed

Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

2017-01-01

The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus ( S. xylosus ) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus . Nine hits were identified from 2,500 compounds by docking studies. Then, these nine compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus . Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

Emissions databases for polycyclic aromatic compounds in the Canadian Athabasca oil sands region - development using current knowledge and evaluation with passive sampling and air dispersion modelling data

NASA Astrophysics Data System (ADS)

Qiu, Xin; Cheng, Irene; Yang, Fuquan; Horb, Erin; Zhang, Leiming; Harner, Tom

2018-03-01

Two speciated and spatially resolved emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada-Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes (DBTs), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model-measurement agreement in the total PAH concentrations and for most PAH species concentrations compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emissions estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

PubMed

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

PubMed Central

2017-01-01

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

Recent Research Progress on Garlic (大蒜 dà suàn) as a Potential Anticarcinogenic Agent Against Major Digestive Cancers

PubMed Central

Raghu, Rajasekaran; Lu, Kuan-Hung; Sheen, Lee-Yan

2012-01-01

Garlic (大蒜 dà suàn; the bulb of Allium sativum), bestowed with an array of organosulfur compounds finds its application in treating many ailments including cardiovascular problems, common cold, bacterial and fungal infections and cancer. Numerous epidemiological evidences document the beneficial effects of various bioactive organosulfur compounds of garlic against different types of cancer. Studies involving the animal and cell models indicate garlic bioactive compounds could be effective in treating all the stages of cancer. This review gives an update on the recent pre-clinical and clinical trials, carried out to evaluate the efficacy of various garlic bioactive compounds along with the mechanism of action pertaining to major digestive cancers including liver, gastric and colorectal cancers. The major anti-carcinogenic mechanisms are caspase dependent and/or independent induction of apoptosis, anti-proliferative, anti-metastasis, anti-oxidant and immunomodulative properties. Form the clinical trials an increase in the garlic consumption of 20 g/day reduced the risk of gastric and colorectal cancer. In summary, increased uptake of garlic in diet may prevent the incidence of digestive cancers. PMID:24716132

Multidrug-Resistant Enterococcal Infections: New Compounds, Novel Antimicrobial Therapies?

PubMed

van Harten, Roel M; Willems, Rob J L; Martin, Nathaniel I; Hendrickx, Antoni P A

2017-06-01

Over the past two decades infections due to antibiotic-resistant bacteria have escalated world-wide, affecting patient morbidity, mortality, and health care costs. Among these bacteria, Enterococcus faecium and Enterococcus faecalis represent opportunistic nosocomial pathogens that cause difficult-to-treat infections because of intrinsic and acquired resistance to a plethora of antibiotics. In recent years, a number of novel antimicrobial compound classes have been discovered and developed that target Gram-positive bacteria, including E. faecium and E. faecalis. These new antibacterial agents include teixobactin (targeting lipid II and lipid III), lipopeptides derived from nisin (targeting lipid II), dimeric vancomycin analogues (targeting lipid II), sortase transpeptidase inhibitors (targeting the sortase enzyme), alanine racemase inhibitors, lipoteichoic acid synthesis inhibitors (targeting LtaS), various oxazolidinones (targeting the bacterial ribosome), and tarocins (interfering with teichoic acid biosynthesis). The targets of these novel compounds and mode of action make them very promising for further antimicrobial drug development and future treatment of Gram-positive bacterial infections. Here we review current knowledge of the most favorable anti-enterococcal compounds along with their implicated modes of action and efficacy in animal models to project their possible future use in the clinical setting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Magnetic and magnetocaloric properties in Gd1-yPryNi2 compounds

NASA Astrophysics Data System (ADS)

Alho, B. P.; Lopes, P. H. O.; Ribeiro, P. O.; Alvarenga, T. S. T.; Nóbrega, E. P.; de Sousa, V. S. R.; Carvalho, A. M. G.; Caldas, A.; Tedesco, J. C. G.; Coelho, A. A.; de Oliveira, N. A.; von Ranke, P. J.

2018-03-01

In this work, we report the magnetic and magnetocaloric properties of the Gd1-yPryNi2 compounds from both experimental and theoretical points of view. It is worth noting that this series shows a variety of magnetic arrangements depending on the Pr concentration, including paramagnetism, ferrimagnetism and ferromagnetism. Our experimental work consists of the systematic analysis of the magnetic properties of the compounds with y = 0.0, 0.25, 0.5, 0.75 and 1.0, which includes temperature and magnetic field dependence of the magnetization, heat capacity and isothermal entropy change obtained by isothermal magnetization curves. Also, we developed a model Hamiltonian, which takes into account the exchange interactions among Gd-Gd, Gd-Pr and Pr-Pr ions, the Zeeman interaction for both ions and the crystalline electrical field interaction for the Pr ions. We systematically investigated the magnetic properties of the series and obtained a good agreement when compared with our experimental data.

Machine learning of atmospheric chemistry. Applications to a global chemistry transport model.

NASA Astrophysics Data System (ADS)

Evans, M. J.; Keller, C. A.

2017-12-01

Atmospheric chemistry is central to many environmental issues such as air pollution, climate change, and stratospheric ozone loss. Chemistry Transport Models (CTM) are a central tool for understanding these issues, whether for research or for forecasting. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (mili-seconds for O(1D) to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a CTM.We have investigated a machine learning approach to solving the differential equations instead of solving them numerically. From an annual simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (random regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, centennial scale climate simulations etc. We discuss our approches' speed and accuracy, and highlight some potential future directions for improving this approach.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

PubMed Central

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

PubMed Central

Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-01-01

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions. PMID:28657595

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds.

PubMed

Spinelle, Laurent; Gerboles, Michel; Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-06-28

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.

How desert varnish forms?

NASA Astrophysics Data System (ADS)

Perry, Randall S.; Kolb, Vera M.; Lynne, Bridget Y.; Sephton, Mark A.; Mcloughlin, Nicola; Engel, Michael H.; Olendzenski, Lorraine; Brasier, Martin; Staley, James T., Jr.

2005-09-01

Desert varnish is a black, manganese-rich rock coating that is widespread on Earth. The mechanism underlying its formation, however, has remained unresolved. We present here new data and an associated model for how desert varnish forms, which substantively challenges previously accepted models. We tested both inorganic processes (e.g. clays and oxides cementing coatings) and microbial methods of formation. Techniques used in this preliminary study include SEM-EDAX with backscatter, HRTEM of focused ion beam prepared (FIB) wafers and several other methods including XRPD, Raman spectroscopy, XPS and Tof-SIMS. The only hypothesis capable of explaining a high water content, the presence of organic compounds, an amorphous silica phase (opal-A) and lesser quantities of clays than previously reported, is a mechanism involving the mobilization and redistribution of silica. The discovery of silica in desert varnish suggests labile organics are preserved by interaction with condensing silicic acid. Organisms are not needed for desert varnish formation but Bacteria, Archaea, Eukarya, and other organic compounds are passively incorporated and preserved as organominerals. The rock coatings thus provide useful records of past environments on Earth and possibly other planets. Additionally this model also helps to explain the origin of key varnish and rock glaze features, including their hardness, the nature of the "glue" that binds heterogeneous components together, its layered botryoidal morphology, and its slow rate of formation.

Thermal Decomposition Mechanisms of Lignin Model Compounds: From Phenol to Vanillin

NASA Astrophysics Data System (ADS)

Scheer, Adam Michael

Lignin is a complex, aromatic polymer abundant in cellulosic biomass (trees, switchgrass etc.). Thermochemical breakdown of lignin for liquid fuel production results in undesirable polycyclic aromatic hydrocarbons that lead to tar and soot byproducts. The fundamental chemistry governing these processes is not well understood. We have studied the unimolecular thermal decomposition mechanisms of aromatic lignin model compounds using a miniature SiC tubular reactor. Products are detected and characterized using time-of-flight mass spectrometry with both single photon (118.2 nm; 10.487 eV) and 1 + 1 resonance-enhanced multiphoton ionization (REMPI) as well as matrix isolation infrared spectroscopy. Gas exiting the heated reactor (300 K--1600 K) is subject to a free expansion after a residence time of approximately 100 micros. The expansion into vacuum rapidly cools the gas mixture and allows the detection of radicals and other highly reactive intermediates. By understanding the unimolecular fragmentation patterns of phenol (C6H5OH), anisole (C6H 5OCH3) and benzaldehyde (C6H5CHO), the more complicated thermocracking processes of the catechols (HO-C 6H4-OH), methoxyphenols (HO-C6H4-OCH 3) and hydroxybenzaldehydes (HO-C6H4-CHO) can be interpreted. These studies have resulted in a predictive model that allows the interpretation of vanillin, a complex phenolic ether containing methoxy, hydroxy and aldehyde functional groups. This model will serve as a guide for the pyrolyses of larger systems including lignin monomers such as coniferyl alcohol. The pyrolysis mechanisms of the dimethoxybenzenes (H3C-C 6H4-OCH3) and syringol, a hydroxydimethoxybenzene have also been studied. These results will aid in the understanding of the thermal fragmentation of sinapyl alcohol, the most complex lignin monomer. In addition to the model compound work, pyrolyisis of biomass has been studied via the pulsed laser ablation of poplar wood. With the REMPI scheme, aromatic lignin decomposition products are directly and selectively detected. A number of these products are the lignin model compounds listed above, providing a direct link between the model compound studies and the pyrolysis of actual biomass.

Chemical and biomedical motifs of the reactions of hydroxymethylphosphines with amines, amino acids, and model peptides

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

Berning, D.E.; Katti, K.V.; Barnes, C.L.

1999-03-03

The reactions of tris(hydroxymethyl)phosphine (THP, 1), 1,2-bis(bis(hydroxymethyl)phosphino)benzene (HMPB, 2), and 1,2-bis(bis(hydroxymethyl)phosphino)ethane (HMPE, 3) with various amines including amino acids and model peptides have been explored. The reactions of these multifunctional phosphines with excess amino acids unexpectedly produced monomeric products. The reaction of THP with excess glycine produced THP(glycine){sub 3} (4) in high yield. The reactions of HMPB with the secondary amines N-methylaniline and diethylamine produced the compounds HMPB(N-methylaniline){sub 4} (5) and HMPB(diethylamine){sub 4} (6), respectively. However, the reactions of HMPB and HMPE with excess glycine produced trans annular-bonded bicyclic compounds HMPB(glycine){sub 2} (7) and HMPE(glycine){sub 2} (10). The reactions ofmore » HMPB with excess alanine and glycylglycylglycine were also explored to determine the generality of the reactions and correspondingly yielded the novel heterocyclic compounds HMPB(alanine){sub 2} (8) and HMPB(gly-gly-gly){sub 2} (9), respectively. The products are oxidatively stable in air and under a wide pH range. All of the new compounds have been characterized by a combination of analytical and spectroscopic techniques, and the molecular structures of compounds 4, 5, 7, and 10 have been confirmed by single-crystal X-ray diffraction studies.« less

Three-dimensional common-feature hypotheses of inhibitors of calling behaviour and in vitro [14C]acetate incorporation by pheromone glands of Plodia interpunctella.

PubMed

Hirashima, Akinori; Eiraku, Tomohiko; Shigeta, Yoko; Kuwano, Eiichi; Taniguchi, Eiji; Eto, Morifusa

2002-11-01

Some octopamine (OA) agonists were found to suppress the calling behaviour and pheromone biosynthesis in vitro of the Indian meal moth, Plodia interpunctella (Hübner), a stored-product pest. Compounds were screened using a calling behaviour bioassay of female P interpunctella. Three active derivatives, with activity at the nanomolar level, were identified. In order of decreasing pheromonostatic activity these were: 2-(2-ethyl-6-methylanilino)oxazolidine > 2-(2,6-diethylanilino)thiazolidine > 2-(2,6-diethylanilino)oxazolidine. These compounds showed also in vitro inhibitory activities in de novo pheromone biosynthesis. Three-dimensional pharmacophore hypotheses were built from a set of 19 compounds. Among the ten common-featured models generated by the program Catalyst/HipHop, a hypothesis including a ring aromatic group (RA), a positive ionizable group (PI) and two hydrophobic aliphatic (HpA1) features was considered to be essential for inhibitory activity in the calling behaviour and pheromone biosynthesis in vitro. Active compounds mapped well onto all the RA, PI and HpA1 features of the hypothesis. Less-active compounds were shown not to achieve the energetically favourable conformation which was found in the active molecules in order to fit the 3-D common-feature pharmacophore models. The present studies demonstrate that inhibition of calling behaviour and PBAN-stimulated incorporation of radioactivity is by OA-agonistic activity.

Theoretical Studies of the Extraterrestrial Chemistry of Biogenic Elements and Compounds

NASA Technical Reports Server (NTRS)

Woon, D. E.

1998-01-01

The report discusses modeling gas-grain chemistry with ab initio quantum chemical cluster calculations which include heterogeneous hydrogenation of CO and H2CO on icy grain mantles, and ammonia-catalyzed, water-enhanced polymerization of formaldehyde in laboratory studies of astrophysical ices.

Development of an Active Topical Skin Protectant (aTSP)

DTIC Science & Technology

2016-02-01

therapeutic compounds was clearly needed. Euthymic hairless guinea pigs [Crl:IAF/HA(hr/hr)Br] were selected for development at the USAMRICD. Vapor HD...hairless guinea pig offered several advantages over haired guinea pigs as a cutaneous vesicant animal model. These advantages included greater...the hairless guinea pig model. Many TSP formulations were evaluated and rank ordered. The supply of hairless guinea pigs , however, was interrupted

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

PubMed Central

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-01-01

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors. PMID:26307982

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.

PubMed

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-08-25

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q(2) (cross-validated correlation coefficient) = 0.557, R(2)ncv (non-cross-validated correlation coefficient) = 0.740, R(2)pre (predicted correlation coefficient) = 0.749 and Q(2) = 0.598, R(2)ncv = 0.767, R(2)pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

Screening a repurposing library for potentiators of antibiotics against Staphylococcus aureus biofilms.

PubMed

Van den Driessche, Freija; Brackman, Gilles; Swimberghe, Rosalie; Rigole, Petra; Coenye, Tom

2017-03-01

Staphylococcus aureus biofilms are involved in a wide range of infections that are extremely difficult to treat with conventional antibiotic therapy. We aimed to identify potentiators of antibiotics against mature biofilms of S. aureus Mu50, a methicillin-resistant and vancomycin-intermediate-resistant strain. Over 700 off-patent drugs from a repurposing library were screened in combination with vancomycin in a microtitre plate (MTP)-based biofilm model system. This led to the identification of 25 hit compounds, including four phenothiazines among which thioridazine was the most potent. Their activity was evaluated in combination with other antibiotics both against planktonic and biofilm-grown S. aureus cells. The most promising combinations were subsequently tested in an in vitro chronic wound biofilm infection model. Although no synergistic activity was observed against planktonic cells, thioridazine potentiated the activity of tobramycin, linezolid and flucloxacillin against S. aureus biofilm cells. However, this effect was only observed in a general biofilm model and not in a chronic wound model of biofilm infection. Several drug compounds were identified that potentiated the activity of vancomycin against biofilms formed in a MTP-based biofilm model. A selected hit compound lost its potentiating activity in a model that mimics specific aspects of wound biofilms. This study provides a platform for discovering and evaluating potentiators against bacterial biofilms and highlights the necessity of using relevant in vitro biofilm model systems. Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

PubMed

Romero-Durán, Francisco J; Alonso, Nerea; Yañez, Matilde; Caamaño, Olga; García-Mera, Xerardo; González-Díaz, Humberto

2016-04-01

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Artificial Neural Network (ANN) algorithms may help us predict the interactions of drugs and targets in CNS interactome. In this work, we trained different ANN models able to predict a large number of drug-target interactions. These models predict a dataset of thousands of interactions of central nervous system (CNS) drugs characterized by > 30 different experimental measures in >400 different experimental protocols for >150 molecular and cellular targets present in 11 different organisms (including human). The model was able to classify cases of non-interacting vs. interacting drug-target pairs with satisfactory performance. A second aim focus on two main directions: the synthesis and assay of new derivatives of TVP1022 (S-analogues of rasagiline) and the comparison with other rasagiline derivatives recently reported. Finally, we used the best of our models to predict drug-target interactions for the best new synthesized compound against a large number of CNS protein targets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model for High-Throughput Screening of Multitarget Drugs in Chemical Neurosciences: Synthesis, Assay, and Theoretic Study of Rasagiline Carbamates

PubMed Central

2013-01-01

The disappointing results obtained in recent clinical trials renew the interest in experimental/computational techniques for the discovery of neuroprotective drugs. In this context, multitarget or multiplexing QSAR models (mt-QSAR/mx-QSAR) may help to predict neurotoxicity/neuroprotective effects of drugs in multiple assays, on drug targets, and in model organisms. In this work, we study a data set downloaded from CHEMBL; each data point (>8000) contains the values of one out of 37 possible measures of activity, 493 assays, 169 molecular or cellular targets, and 11 different organisms (including human) for a given compound. In this work, we introduce the first mx-QSAR model for neurotoxicity/neuroprotective effects of drugs based on the MARCH-INSIDE (MI) method. First, we used MI to calculate the stochastic spectral moments (structural descriptors) of all compounds. Next, we found a model that classified correctly 2955 out of 3548 total cases in the training and validation series with Accuracy, Sensitivity, and Specificity values > 80%. The model also showed excellent results in Computational-Chemistry simulations of High-Throughput Screening (CCHTS) experiments, with accuracy = 90.6% for 4671 positive cases. Next, we reported the synthesis, characterization, and experimental assays of new rasagiline derivatives. We carried out three different experimental tests: assay (1) in the absence of neurotoxic agents, assay (2) in the presence of glutamate, and assay (3) in the presence of H2O2. Compounds 11 with 27.4%, 8 with 11.6%, and 9 with 15.4% showed the highest neuroprotective effects in assays (1), (2), and (3), respectively. After that, we used the mx-QSAR model to carry out a CCHTS of the new compounds in >400 unique pharmacological tests not carried out experimentally. Consequently, this model may become a promising auxiliary tool for the discovery of new drugs for the treatment of neurodegenerative diseases. PMID:23855599

Identification of compounds protective against G93A-SOD1 toxicity for the treatment of amyotrophic lateral sclerosis.

PubMed

Benmohamed, Radhia; Arvanites, Anthony C; Kim, Jinho; Ferrante, Robert J; Silverman, Richard B; Morimoto, Richard I; Kirsch, Donald R

2011-03-01

The underlying cause of amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disorder, remains unknown. However, there is strong evidence that one pathophysiological mechanism, toxic protein misfolding and/or aggregation, may trigger motor neuron dysfunction and loss. Since the clinical and pathological features of sporadic and familial ALS are indistinguishable, all forms of the disease may be better understood and ultimately treated by studying pathogenesis and therapy in models expressing mutant forms of SOD1. We developed a cellular model in which cell death depended on the expression of G93A-SOD1, a mutant form of superoxide dismutase found in familial ALS patients that produces toxic protein aggregates. This cellular model was optimized for high throughput screening to identify protective compounds from a >50,000 member chemical library. Three novel chemical scaffolds were selected for further study following screen implementation, counter-screening and secondary testing, including studies with purchased analogs. All three scaffolds blocked SOD1 aggregation in high content screening assays and data on the optimization and further characterization of these compounds will be reported separately. These data suggest that optimization of these chemicals scaffolds may produce therapeutic candidates for ALS patients.

MICROBIAL DEGRADATION OF NITROGEN, OXYGEN AND SULFUR HETEROCYCLIC COMPOUNDS UNDER ANAEROBIC CONDITIONS: STUDIES WITH AQUIFER SAMPLES

EPA Science Inventory

The potential for anaerobic biodegradation of 12 heterocyclic model compounds was studied. Nine of the model compounds were biotransformed in aquifer slurries under sulfate-reducing or methanogenic conditions. The nitrogen and oxygen heterocyclic compounds were more susceptible t...

In Vitro Evaluation of Antileishmanial Activity of Computationally Screened Compounds against Ascorbate Peroxidase To Combat Amphotericin B Drug Resistance

PubMed Central

Mansuri, Rani; Kumar, Ashish; Rana, Sindhuprava; Panthi, Bhavana; Ansari, M. Yousuf; Das, Sushmita; Dikhit, Manas Ranjan

2017-01-01

ABSTRACT In visceral leishmaniasis (VL), the host macrophages generate oxidative stress to destroy the pathogen, while Leishmania combats the harmful effect of radicals by redox homeostasis through its unique trypanothione cascade. Leishmania donovani ascorbate peroxidase (LdAPx) is a redox enzyme that regulates the trypanothione cascade and detoxifies the effect of H2O2. The absence of an LdAPx homologue in humans makes it an excellent drug target. In this study, the homology model of LdAPx was built, including heme, and diverse compounds were prefiltered (PAINS, ADMET, and Lipinski's rule of five) and thereafter screened against the LdAPx model. Compounds having good affinity in terms of the Glide XP (extra precision) score were clustered to select diverse compounds for experimental validation. A total of 26 cluster representatives were procured and tested on promastigote culture, yielding 12 compounds with good antileishmanial activity. Out of them, six compounds were safer on the BALB/c peritoneal macrophages and were also effective against disease-causing intracellular amastigotes. Three out of six compounds inhibited recombinant LdAPx in a noncompetitive manner and also demonstrated partial reversion of the resistance property in an amphotericin B (AmB)-resistant strain, which may be due to an increased level of reactive oxygen species (ROS) and decrease of glutathione (GSH) content. However, inhibition of LdAPx in resistant parasites enhanced annexin V staining and activation of metacaspase-like protease activity, which may help in DNA fragmentation and apoptosis-like cell death. Thus, the present study will help in the search for specific hits and templates of potential therapeutic interest and therefore may facilitate the development of new drugs for combination therapy against VL. PMID:28461317

Using box models to quantify zonal distributions and emissions of halocarbons in the background atmosphere.

NASA Astrophysics Data System (ADS)

Elkins, J. W.; Nance, J. D.; Dutton, G. S.; Montzka, S. A.; Hall, B. D.; Miller, B.; Butler, J. H.; Mondeel, D. J.; Siso, C.; Moore, F. L.; Hintsa, E. J.; Wofsy, S. C.; Rigby, M. L.

2015-12-01

The Halocarbons and other Atmospheric Trace Species (HATS) of NOAA's Global Monitoring Division started measurements of the major chlorofluorocarbons and nitrous oxide in 1977 from flask samples collected at five remote sites around the world. Our program has expanded to over 40 compounds at twelve sites, which includes six in situ instruments and twelve flask sites. The Montreal Protocol for Substances that Deplete the Ozone Layer and its subsequent amendments has helped to decrease the concentrations of many of the ozone depleting compounds in the atmosphere. Our goal is to provide zonal emission estimates for these trace gases from multi-box models and their estimated atmospheric lifetimes in this presentation and make the emission values available on our web site. We plan to use our airborne measurements to calibrate the exchange times between the boxes for 5-box and 12-box models using sulfur hexafluoride where emissions are better understood.

Nanopyroxene Grafting with β-Cyclodextrin Monomer for Wastewater Applications.

PubMed

Nafie, Ghada; Vitale, Gerardo; Carbognani Ortega, Lante; Nassar, Nashaat N

2017-12-06

Emerging nanoparticle technology provides opportunities for environmentally friendly wastewater treatment applications, including those in the large liquid tailings containments in the Alberta oil sands. In this study, we synthesize β-cyclodextrin grafted nanopyroxenes to offer an ecofriendly platform for the selective removal of organic compounds typically present in these types of applications. We carry out computational modeling at the micro level through molecular mechanics and molecular dynamics simulations and laboratory experiments at the macro level to understand the interactions between the synthesized nanomaterials and two-model naphthenic acid molecules (cyclopentanecarboxylic and trans-4-pentylcyclohexanecarboxylic acids) typically existing in tailing ponds. The proof-of-concept computational modeling and experiments demonstrate that monomer grafted nanopyroxene  or nano-AE of the sodium iron-silicate aegirine are found to be promising candidates for the removal of polar organic compounds from wastewater, among other applications. These nano-AE offer new possibilities for treating tailing ponds generated by the oil sands industry.

Thermodynamic assessment of oxygen diffusion in non-stoichiometric UO2±x from experimental data and Frenkel pair modeling

NASA Astrophysics Data System (ADS)

Berthinier, C.; Rado, C.; Chatillon, C.; Hodaj, F.

2013-02-01

The self and chemical diffusion of oxygen in the non-stoichiometric domain of the UO2 compound is analyzed from the point of view of experimental determinations and modeling from Frenkel pair defects. The correlation between the self-diffusion and the chemical diffusion coefficients is analyzed using the Darken coefficient calculated from a thermodynamic description of the UO2±x phase. This description was obtained from an optimization of thermodynamic and phase diagram data and modeling with different point defects, including the Frenkel pair point defects. The proposed diffusion coefficients correspond to the 300-2300 K temperature range and to the full composition range of the non stoichiometric UO2 compound. These values will be used for the simulation of the oxidation and ignition of the uranium carbide in different oxygen atmospheres that starts at temperatures as low as 400 K.

Basic studies on the pyrolysis of lignin compounds

Treesearch

Byung-ho Hwang

2003-01-01

By pyrolyzing lignin model compounds 1-lV at 315°C, an investigation was carried out with some results. In the pyrolysis of lignin model compound I and 11, 0.47 mol of guaiacol, 0.57 mol of dimethoxyphenol (DMP), and 0.12 and 0.23 mol of dimethoxyaceton ophenone (DMAP) were produced respectively. In the pyrolysis of lignin model compound lll and lV, 0.26 mol of...

Anti-inflammatory Effects of Fungal Metabolites in Mouse Intestine as Revealed by In vitro Models

PubMed Central

Schreiber, Dominik; Marx, Lisa; Felix, Silke; Clasohm, Jasmin; Weyland, Maximilian; Schäfer, Maximilian; Klotz, Markus; Lilischkis, Rainer; Erkel, Gerhard; Schäfer, Karl-Herbert

2017-01-01

Inflammatory bowel diseases (IBD), which include Crohn's disease and ulcerative colitis, are chronic inflammatory disorders that can affect the whole gastrointestinal tract or the colonic mucosal layer. Current therapies aiming to suppress the exaggerated immune response in IBD largely rely on compounds with non-satisfying effects or side-effects. Therefore, new therapeutical options are needed. In the present study, we investigated the anti-inflammatory effects of the fungal metabolites, galiellalactone, and dehydrocurvularin in both an in vitro intestinal inflammation model, as well as in isolated myenteric plexus and enterocyte cells. Administration of a pro-inflammatory cytokine mix through the mesenteric artery of intestinal segments caused an up-regulation of inflammatory marker genes. Treatment of the murine intestinal segments with galiellalactone or dehydrocurvularin by application through the mesenteric artery significantly prevented the expression of pro-inflammatory marker genes on the mRNA and the protein level. Comparable to the results in the perfused intestine model, treatment of primary enteric nervous system (ENS) cells from the murine intestine with the fungal compounds reduced expression of cytokines such as IL-6, TNF-α, IL-1β, and inflammatory enzymes such as COX-2 and iNOS on mRNA and protein levels. Similar anti-inflammatory effects of the fungal metabolites were observed in the human colorectal adenocarcinoma cell line DLD-1 after stimulation with IFN-γ (10 ng/ml), TNF-α (10 ng/ml), and IL-1β (5 ng/ml). Our results show that the mesenterially perfused intestine model provides a reliable tool for the screening of new therapeutics with limited amounts of test compounds. Furthermore, we could characterize the anti-inflammatory effects of two novel active compounds, galiellalactone, and dehydrocurvularin which are interesting candidates for studies with chronic animal models of IBD. PMID:28824460

QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

PubMed

Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

2006-11-30

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

Physiologically based pharmacokinetic model for quinocetone in pigs and extrapolation to mequindox.

PubMed

Zhu, Xudong; Huang, Lingli; Xu, Yamei; Xie, Shuyu; Pan, Yuanhu; Chen, Dongmei; Liu, Zhenli; Yuan, Zonghui

2017-02-01

Physiologically based pharmacokinetic (PBPK) models are scientific methods used to predict veterinary drug residues that may occur in food-producing animals, and which have powerful extrapolation ability. Quinocetone (QCT) and mequindox (MEQ) are widely used in China for the prevention of bacterial infections and promoting animal growth, but their abuse causes a potential threat to human health. In this study, a flow-limited PBPK model was developed to simulate simultaneously residue depletion of QCT and its marker residue dideoxyquinocetone (DQCT) in pigs. The model included compartments for blood, liver, kidney, muscle and fat and an extra compartment representing the other tissues. Physiological parameters were obtained from the literature. Plasma protein binding rates, renal clearances and tissue/plasma partition coefficients were determined by in vitro and in vivo experiments. The model was calibrated and validated with several pharmacokinetic and residue-depletion datasets from the literature. Sensitivity analysis and Monte Carlo simulations were incorporated into the PBPK model to estimate individual variation of residual concentrations. The PBPK model for MEQ, the congener compound of QCT, was built through cross-compound extrapolation based on the model for QCT. The QCT model accurately predicted the concentrations of QCT and DQCT in various tissues at most time points, especially the later time points. Correlation coefficients between predicted and measured values for all tissues were greater than 0.9. Monte Carlo simulations showed excellent consistency between estimated concentration distributions and measured data points. The extrapolation model also showed good predictive power. The present models contribute to improve the residue monitoring systems of QCT and MEQ, and provide evidence of the usefulness of PBPK model extrapolation for the same kinds of compounds.

Investigation of the Anti-Prostate Cancer Properties of Marine-Derived Compounds

PubMed Central

Fan, Meiqi; Nath, Amit Kumar; Tang, Yujiao; Choi, Young-Jin; Debnath, Trishna; Choi, Eun-Ju

2018-01-01

This review focuses on marine compounds with anti-prostate cancer properties. Marine species are unique and have great potential for the discovery of anticancer drugs. Marine sources are taxonomically diverse and include bacteria, cyanobacteria, fungi, algae, and mangroves. Marine-derived compounds, including nucleotides, amides, quinones, polyethers, and peptides are biologically active compounds isolated from marine organisms such as sponges, ascidians, gorgonians, soft corals, and bryozoans, including those mentioned above. Several compound classes such as macrolides and alkaloids include drugs with anti-cancer mechanisms, such as antioxidants, anti-angiogenics, antiproliferatives, and apoptosis-inducing drugs. Despite the diversity of marine species, most marine-derived bioactive compounds have not yet been evaluated. Our objective is to explore marine compounds to identify new treatment strategies for prostate cancer. This review discusses chemically and pharmacologically diverse marine natural compounds and their sources in the context of prostate cancer drug treatment. PMID:29757237

Compound prioritization methods increase rates of chemical probe discovery in model organisms

PubMed Central

Wallace, Iain M; Urbanus, Malene L; Luciani, Genna M; Burns, Andrew R; Han, Mitchell KL; Wang, Hao; Arora, Kriti; Heisler, Lawrence E; Proctor, Michael; St. Onge, Robert P; Roemer, Terry; Roy, Peter J; Cummins, Carolyn L; Bader, Gary D; Nislow, Corey; Giaever, Guri

2011-01-01

SUMMARY Pre-selection of compounds that are more likely to induce a phenotype can increase the efficiency and reduce the costs for model organism screening. To identify such molecules, we screened ~81,000 compounds in S. cerevisiae and identified ~7,500 that inhibit cell growth. Screening these growth-inhibitory molecules across a diverse panel of model organisms resulted in an increased phenotypic hit-rate. This data was used to build a model to predict compounds that inhibit yeast growth. Empirical and in silico application of the model enriched the discovery of bioactive compounds in diverse model organisms. To demonstrate the potential of these molecules as lead chemical probes we used chemogenomic profiling in yeast and identified specific inhibitors of lanosterol synthase and of stearoyl-CoA 9-desaturase. As community resources, the ~7,500 growth-inhibitory molecules has been made commercially available and the computational model and filter used are provided. PMID:22035796

High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (SOT)

EPA Science Inventory

Chemical components of consumer products and articles of commerce such as carpet and clothing are key drivers of exposure in the near-field environment. These chemicals include semi-volatile organic compounds (SVOCs), some of which have been shown to alter endocrine functionality...

Speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) in a pine forest during BEACHON-RoMBAS 2011

DOE PAGES

Chan, A. W. H.; Kreisberg, N. M.; Hohaus, T.; ...

2016-02-02

Understanding organic composition of gases and particles is essential to identifying sources and atmospheric processing leading to organic aerosols (OA), but atmospheric chemical complexity and the analytical techniques available often limit such analysis. Here we present speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) using a novel dual-use instrument (SV-TAG-AMS) deployed at Manitou Forest, CO, during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H 2O, Organics & Nitrogen – Rocky Mountain Biogenic Aerosol Study (BEACHON-RoMBAS) 2011 campaign. This instrument provides on-line speciation of ambient organic compounds with 2 h time resolution. The species in this volatility range aremore » complex in composition, but their chemical identities reveal potential sources. Observed compounds of biogenic origin include sesquiterpenes with molecular formula C 15H 24 (e.g., β-caryophyllene and longifolene), which were most abundant at night. A variety of other biogenic compounds were observed, including sesquiterpenoids with molecular formula C 15H 22, abietatriene and other terpenoid compounds. Many of these compounds have been identified in essential oils and branch enclosure studies but were observed in ambient air for the first time in our study. Semivolatile polycyclic aromatic hydrocarbons (PAHs) and alkanes were observed with highest concentrations during the day and the dependence on temperature suggests the role of an evaporative source. Using statistical analysis by positive matrix factorization (PMF), we classify observed S/IVOCs by their likely sources and processes, and characterize them based on chemical composition. The total mass concentration of elutable S/IVOCs was estimated to be on the order of 0.7 µg m –3 and their volatility distributions are estimated for modeling aerosol formation chemistry.« less

N-nitrosodimethylamine (NDMA) formation from the ozonation of model compounds.

PubMed

Marti, Erica J; Pisarenko, Aleksey N; Peller, Julie R; Dickenson, Eric R V

2015-04-01

Nitrosamines are a class of toxic disinfection byproducts commonly associated with chloramination, of which several were included on the most recent U.S. EPA Contaminant Candidate List. Nitrosamine formation may be a significant barrier to ozonation in water reuse applications, particularly for direct or indirect potable reuse, since recent studies show direct formation during ozonation of natural water and treated wastewaters. Only a few studies have identified precursors which react with ozone to form N-nitrosodimethylamine (NDMA). In this study, several precursor compound solutions, prepared in ultrapure water and treated wastewater, were subjected to a 10 M excess of ozone. In parallel experiments, the precursor solutions in ultrapure water were exposed to gamma radiation to determine NDMA formation as a byproduct of reactions of precursor compounds with hydroxyl radicals. The results show six new NDMA precursor compounds that have not been previously reported in the literature, including compounds with hydrazone and carbamate moieties. Molar yields in deionized water were 61-78% for 3 precursors, 12-23% for 5 precursors and <4% for 2 precursors. Bromide concentration was important for three compounds (1,1-dimethylhydrazine, acetone dimethylhydrazone and dimethylsulfamide), but did not enhance NDMA formation for the other precursors. NDMA formation due to chloramination was minimal compared to formation due to ozonation, suggesting distinct groups of precursor compounds for these two oxidants. Hydroxyl radical reactions with the precursors will produce NDMA, but formation is much greater in the presence of molecular ozone. Also, hydroxyl radical scavenging during ozonation leads to increased NDMA formation. Molar conversion yields were higher for several precursors in wastewater as compared to deionized water, which could be due to catalyzed reactions with constituents found in wastewater or hydroxyl radical scavenging. Copyright © 2014 Elsevier Ltd. All rights reserved.

Speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) in a pine forest during BEACHON-RoMBAS 2011

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

Chan, A. W. H.; Kreisberg, N. M.; Hohaus, T.

Understanding organic composition of gases and particles is essential to identifying sources and atmospheric processing leading to organic aerosols (OA), but atmospheric chemical complexity and the analytical techniques available often limit such analysis. Here we present speciated measurements of semivolatile and intermediate volatility organic compounds (S/IVOCs) using a novel dual-use instrument (SV-TAG-AMS) deployed at Manitou Forest, CO, during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H 2O, Organics & Nitrogen – Rocky Mountain Biogenic Aerosol Study (BEACHON-RoMBAS) 2011 campaign. This instrument provides on-line speciation of ambient organic compounds with 2 h time resolution. The species in this volatility range aremore » complex in composition, but their chemical identities reveal potential sources. Observed compounds of biogenic origin include sesquiterpenes with molecular formula C 15H 24 (e.g., β-caryophyllene and longifolene), which were most abundant at night. A variety of other biogenic compounds were observed, including sesquiterpenoids with molecular formula C 15H 22, abietatriene and other terpenoid compounds. Many of these compounds have been identified in essential oils and branch enclosure studies but were observed in ambient air for the first time in our study. Semivolatile polycyclic aromatic hydrocarbons (PAHs) and alkanes were observed with highest concentrations during the day and the dependence on temperature suggests the role of an evaporative source. Using statistical analysis by positive matrix factorization (PMF), we classify observed S/IVOCs by their likely sources and processes, and characterize them based on chemical composition. The total mass concentration of elutable S/IVOCs was estimated to be on the order of 0.7 µg m –3 and their volatility distributions are estimated for modeling aerosol formation chemistry.« less

A Comprehensive Study on Pyrolysis Mechanism of Substituted β-O-4 Type Lignin Dimers.

PubMed

Jiang, Xiaoyan; Lu, Qiang; Hu, Bin; Liu, Ji; Dong, Changqing; Yang, Yongping

2017-11-09

In order to understand the pyrolysis mechanism of β- O -4 type lignin dimers, a pyrolysis model is proposed which considers the effects of functional groups (hydroxyl, hydroxymethyl and methoxyl) on the alkyl side chain and aromatic ring. Furthermore, five specific β- O -4 type lignin dimer model compounds are selected to investigate their integrated pyrolysis mechanism by density functional theory (DFT) methods, to further understand and verify the proposed pyrolysis model. The results indicate that a total of 11 pyrolysis mechanisms, including both concerted mechanisms and homolytic mechanisms, might occur for the initial pyrolysis of the β- O -4 type lignin dimers. Concerted mechanisms are predominant as compared with homolytic mechanisms throughout unimolecular decomposition pathways. The competitiveness of the eleven pyrolysis mechanisms are revealed via different model compounds, and the proposed pyrolysis model is ranked in full consideration of functional groups effects. The proposed pyrolysis model can provide a theoretical basis to predict the reaction pathways and products during the pyrolysis process of β- O -4 type lignin dimers.

A Comprehensive Study on Pyrolysis Mechanism of Substituted β-O-4 Type Lignin Dimers

PubMed Central

Jiang, Xiaoyan; Lu, Qiang; Hu, Bin; Liu, Ji; Dong, Changqing; Yang, Yongping

2017-01-01

In order to understand the pyrolysis mechanism of β-O-4 type lignin dimers, a pyrolysis model is proposed which considers the effects of functional groups (hydroxyl, hydroxymethyl and methoxyl) on the alkyl side chain and aromatic ring. Furthermore, five specific β-O-4 type lignin dimer model compounds are selected to investigate their integrated pyrolysis mechanism by density functional theory (DFT) methods, to further understand and verify the proposed pyrolysis model. The results indicate that a total of 11 pyrolysis mechanisms, including both concerted mechanisms and homolytic mechanisms, might occur for the initial pyrolysis of the β-O-4 type lignin dimers. Concerted mechanisms are predominant as compared with homolytic mechanisms throughout unimolecular decomposition pathways. The competitiveness of the eleven pyrolysis mechanisms are revealed via different model compounds, and the proposed pyrolysis model is ranked in full consideration of functional groups effects. The proposed pyrolysis model can provide a theoretical basis to predict the reaction pathways and products during the pyrolysis process of β-O-4 type lignin dimers. PMID:29120350

Pro-osteogenic effects of fibrin glue in treatment of avascular necrosis of the femoral head in vivo by hepatocyte growth factor-transgenic mesenchymal stem cells

PubMed Central

2014-01-01

Background Autologous transplantation of modified mesenchymal stem cells (MSCs) is a promising candidate for the treatment of the refractory clinical disease, avascular necrosis of the femoral head (ANFH). Our previous attempts by compounding MSCs with medical fibrin glue to treat ANFH in animal model have achieved excellent effects. However, the underlying molecular mechanism is unclear, especially on the transgenic gene expression. Methods Rabbit MSCs were isolated and compounded with fibrin glue. Following degrading of fibrin glue, proliferation, viability, expression of transgenic hepatocyte growth factor gene as well as osteogenic differentiation of MSCs were evaluated together with that of uncompounded MSCs. Fibrin glue-compounded MSCs were transplanted into the lesion of ANFH model, and the therapeutic efficacy was compared with uncompounded MSCs. One-Way ANOVA was used to determine the statistical significance among treatment groups. Results Fibrin glue compounding will not affect molecular activities of MSCs, including hepatocyte growth factor (HGF) secretion, cell proliferation and viability, and osteogenic differentiation in vitro. When applying fibrin glue-compounded MSCs for the therapy of ANFH in vivo, fibrin glue functioned as a drug delivery system and provided a sustaining microenvironment for MSCs which helped the relatively long-term secretion of HGF in the femoral head lesion and resulted in improved therapeutic efficacy when compared with uncompounded MSCs as indicated by hematoxylin-eosin staining and immunohistochemistry of osteocalcin, CD105 and HGF. Conclusion Transplantation of fibrin glue-compounding MSCs is a promising novel method for ANFH therapy. PMID:24885252

Medicinal Plants from Mexico, Central America, and the Caribbean Used as Immunostimulants

PubMed Central

Juárez-Vázquez, María del Carmen; Campos-Xolalpa, Nimsi

2016-01-01

A literature review was undertaken by analyzing distinguished books, undergraduate and postgraduate theses, and peer-reviewed scientific articles and by consulting worldwide accepted scientific databases, such as SCOPUS, Web of Science, SCIELO, Medline, and Google Scholar. Medicinal plants used as immunostimulants were classified into two categories: (1) plants with pharmacological studies and (2) plants without pharmacological research. Medicinal plants with pharmacological studies of their immunostimulatory properties were subclassified into four groups as follows: (a) plant extracts evaluated for in vitro effects, (b) plant extracts with documented in vivo effects, (c) active compounds tested on in vitro studies, and (d) active compounds assayed in animal models. Pharmacological studies have been conducted on 29 of the plants, including extracts and compounds, whereas 75 plants lack pharmacological studies regarding their immunostimulatory activity. Medicinal plants were experimentally studied in vitro (19 plants) and in vivo (8 plants). A total of 12 compounds isolated from medicinal plants used as immunostimulants have been tested using in vitro (11 compounds) and in vivo (2 compounds) assays. This review clearly indicates the need to perform scientific studies with medicinal flora from Mexico, Central America, and the Caribbean, to obtain new immunostimulatory agents. PMID:27042188

Effect of Vanadyl Rosiglitazone, a New Insulin-Mimetic Vanadium Complexes, on Glucose Homeostasis of Diabetic Mice.

PubMed

Jiang, Pingzhe; Dong, Zhen; Ma, Baicheng; Ni, Zaizhong; Duan, Huikun; Li, Xiaodan; Wang, Bin; Ma, Xiaofeng; Wei, Qian; Ji, Xiangzhen; Li, Minggang

2016-11-01

Diabetes has been cited as the most challenging health problem in the twenty-first century. Accordingly, it is urgent to develop a new type of efficient and low-toxic antidiabetic medication. Since vanadium compounds have insulin-mimetic and potential hypoglycemic activities for type 1 and type 2 diabetes, a new trend has been developed using vanadium and organic ligands to form a new compound in order to increase the intestinal absorption and reduce the toxicity of vanadium compound. In the current investigation, a new organic vanadium compounds, vanadyl rosiglitazone, was synthesized and determined by infrared spectra. Vanadyl rosiglitazone and three other organic vanadium compounds were administered to the diabetic mice through oral administration for 5 weeks. The results of mouse model test indicated that vanadyl rosiglitazone could regulate the blood glucose level and relieve the symptoms of polydipsia, polyphagia, polyuria, and weight loss without side effects and was more effective than the other three organic vanadium compounds including vanadyl trehalose, vanadyl metformin, and vanadyl quercetin. The study indicated that vanadyl rosiglitazone presents insulin-mimetic activities, and it will be a good potential candidate for the development of a new type of oral drug for type 2 diabetes.

Oxidative versus Non-oxidative Decarboxylation of Amino Acids: Conditions for the Preferential Formation of Either Strecker Aldehydes or Amines in Amino Acid/Lipid-Derived Reactive Carbonyl Model Systems.

PubMed

Zamora, Rosario; León, M Mercedes; Hidalgo, Francisco J

2015-09-16

Comparative formation of both 2-phenylethylamine and phenylacetaldehyde as a consequence of phenylalanine degradation by carbonyl compounds was studied in an attempt to understand if the amine/aldehyde ratio can be changed as a function of reaction conditions. The assayed carbonyl compounds were selected because of the presence in the chain of both electron-donating and electron-withdrawing groups and included alkenals, alkadienals, epoxyalkenals, oxoalkenals, and hydroxyalkenals as well as lipid hydroperoxides. The obtained results showed that the 2-phenylethylamine/phenylacetaldehyde ratio depended upon both the carbonyls and the reaction conditions. Thus, it can be increased using electron-donating groups in the chain of the carbonyl compound, small amounts of carbonyl compound, low oxygen content, increasing the pH, or increasing the temperature at pH 6. Opposed conditions (use of electron-withdrawing groups in the chain of the carbonyl compound, large amounts of carbonyl compound, high oxygen contents, low pH values, and increasing temperatures at low pH values) would decrease the 2-phenylethylamine/phenylacetaldehyde ratio, and the formation of aldehydes over amines in amino acid degradations would be favored.

The influence of natural organic matter and cations on the rejection of endocrine disrupting and pharmaceutically active compounds by nanofiltration.

PubMed

Comerton, Anna M; Andrews, Robert C; Bagley, David M

2009-02-01

The impact of natural organic matter (NOM) and cations on the rejection of five endocrine disrupting compounds (EDCs) and pharmaceutically active compounds (PhACs) (acetaminophen, carbamazepine, estrone, gemfibrozil, oxybenzone) by nanofiltration (NF) was examined. The water matrices included membrane bioreactor (MBR) effluent, Lake Ontario water and laboratory-prepared waters modelled to represent the characteristics of the Lake Ontario water. The impact of cations in natural waters on compound rejection was also examined by doubling the natural cation concentration (calcium, magnesium, sodium) in both the Lake Ontario water and the MBR effluent. The presence of Suwannee River NOM spiked into laboratory-grade water was found to cause an increase in compound NF rejection. In addition, the presence of cations alone in laboratory-grade water did not have a significant impact on rejection with the exception of the polar compound gemfibrozil. However, when cation concentration in natural waters was increased, a significant decrease in the rejection of EDCs and PhACs was observed. This suggests that the presence of cations may result in a reduction in the association of EDCs and PhACs with NOM.

Medicinal Plants from Mexico, Central America, and the Caribbean Used as Immunostimulants.

PubMed

Alonso-Castro, Angel Josabad; Juárez-Vázquez, María Del Carmen; Campos-Xolalpa, Nimsi

2016-01-01

A literature review was undertaken by analyzing distinguished books, undergraduate and postgraduate theses, and peer-reviewed scientific articles and by consulting worldwide accepted scientific databases, such as SCOPUS, Web of Science, SCIELO, Medline, and Google Scholar. Medicinal plants used as immunostimulants were classified into two categories: (1) plants with pharmacological studies and (2) plants without pharmacological research. Medicinal plants with pharmacological studies of their immunostimulatory properties were subclassified into four groups as follows: (a) plant extracts evaluated for in vitro effects, (b) plant extracts with documented in vivo effects, (c) active compounds tested on in vitro studies, and (d) active compounds assayed in animal models. Pharmacological studies have been conducted on 29 of the plants, including extracts and compounds, whereas 75 plants lack pharmacological studies regarding their immunostimulatory activity. Medicinal plants were experimentally studied in vitro (19 plants) and in vivo (8 plants). A total of 12 compounds isolated from medicinal plants used as immunostimulants have been tested using in vitro (11 compounds) and in vivo (2 compounds) assays. This review clearly indicates the need to perform scientific studies with medicinal flora from Mexico, Central America, and the Caribbean, to obtain new immunostimulatory agents.

Selective cleavage of the C(α)-C(β) linkage in lignin model compounds via Baeyer-Villiger oxidation.

PubMed

Patil, Nikhil D; Yao, Soledad G; Meier, Mark S; Mobley, Justin K; Crocker, Mark

2015-03-21

Lignin is an amorphous aromatic polymer derived from plants and is a potential source of fuels and bulk chemicals. Herein, we present a survey of reagents for selective stepwise oxidation of lignin model compounds. Specifically, we have targeted the oxidative cleavage of Cα-Cβ bonds as a means to depolymerize lignin and obtain useful aromatic compounds. In this work, we prepared several lignin model compounds that possess structures, characteristic reactivity, and linkages closely related to the parent lignin polymer. We observed that selective oxidation of benzylic hydroxyl groups, followed by Baeyer-Villiger oxidation of the resulting ketones, successfully cleaves the Cα-Cβ linkage in these model compounds.

Perspectives on zebrafish models of hallucinogenic drugs and related psychotropic compounds.

PubMed

Neelkantan, Nikhil; Mikhaylova, Alina; Stewart, Adam Michael; Arnold, Raymond; Gjeloshi, Visar; Kondaveeti, Divya; Poudel, Manoj K; Kalueff, Allan V

2013-08-21

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs' action. The utility of zebrafish ( Danio rerio ) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans.

Perspectives on Zebrafish Models of Hallucinogenic Drugs and Related Psychotropic Compounds

PubMed Central

2013-01-01

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs’ action. The utility of zebrafish (Danio rerio) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans. PMID:23883191

Numerical Modeling of High-Temperature Corrosion Processes

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

1995-01-01

Numerical modeling of the diffusional transport associated with high-temperature corrosion processes is reviewed. These corrosion processes include external scale formation and internal subscale formation during oxidation, coating degradation by oxidation and substrate interdiffusion, carburization, sulfidation and nitridation. The studies that are reviewed cover such complexities as concentration-dependent diffusivities, cross-term effects in ternary alloys, and internal precipitation where several compounds of the same element form (e.g., carbides of Cr) or several compounds exist simultaneously (e.g., carbides containing varying amounts of Ni, Cr, Fe or Mo). In addition, the studies involve a variety of boundary conditions that vary with time and temperature. Finite-difference (F-D) techniques have been applied almost exclusively to model either the solute or corrodant transport in each of these studies. Hence, the paper first reviews the use of F-D techniques to develop solutions to the diffusion equations with various boundary conditions appropriate to high-temperature corrosion processes. The bulk of the paper then reviews various F-D modeling studies of diffusional transport associated with high-temperature corrosion.

Antioxidant therapy for treatment of inflammatory bowel disease: Does it work?

PubMed Central

Moura, Fabiana Andréa; de Andrade, Kívia Queiroz; dos Santos, Juliana Célia Farias; Araújo, Orlando Roberto Pimentel; Goulart, Marília Oliveira Fonseca

2015-01-01

Oxidative stress (OS) is considered as one of the etiologic factors involved in several signals and symptoms of inflammatory bowel diseases (IBD) that include diarrhea, toxic megacolon and abdominal pain. This systematic review discusses approaches, challenges and perspectives into the use of nontraditional antioxidant therapy on IBD, including natural and synthetic compounds in both human and animal models. One hundred and thirty four papers were identified, of which only four were evaluated in humans. Some of the challenges identified in this review can shed light on this fact: lack of standardization of OS biomarkers, absence of safety data and clinical trials for the chemicals and biological molecules, as well as the fact that most of the compounds were not repeatedly tested in several situations, including acute and chronic colitis. This review hopes to stimulate researchers to become more involved in this fruitful area, to warrant investigation of novel, alternative and efficacious antioxidant-based therapies. PMID:26520808

Screening of synthetic and natural product databases: Identification of novel androgens and antiandrogens.

PubMed

Bobach, Claudia; Tennstedt, Stephanie; Palberg, Kristin; Denkert, Annika; Brandt, Wolfgang; de Meijere, Armin; Seliger, Barbara; Wessjohann, Ludger A

2015-01-27

The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Phenolic Molding Compounds

NASA Astrophysics Data System (ADS)

Koizumi, Koji; Charles, Ted; de Keyser, Hendrik

Phenolic Molding Compounds continue to exhibit well balanced properties such as heat resistance, chemical resistance, dimensional stability, and creep resistance. They are widely applied in electrical, appliance, small engine, commutator, and automotive applications. As the focus of the automotive industry is weight reduction for greater fuel efficiency, phenolic molding compounds become appealing alternatives to metals. Current market volumes and trends, formulation components and its impact on properties, and a review of common manufacturing methods are presented. Molding processes as well as unique advanced techniques such as high temperature molding, live sprue, and injection/compression technique provide additional benefits in improving the performance characterisitics of phenolic molding compounds. Of special interest are descriptions of some of the latest innovations in automotive components, such as the phenolic intake manifold and valve block for dual clutch transmissions. The chapter also characterizes the most recent developments in new materials, including long glass phenolic molding compounds and carbon fiber reinforced phenolic molding compounds exhibiting a 10-20-fold increase in Charpy impact strength when compared to short fiber filled materials. The role of fatigue testing and fatigue fracture behavior presents some insight into long-term reliability and durability of glass-filled phenolic molding compounds. A section on new technology outlines the important factors to consider in modeling phenolic parts by finite element analysis and flow simulation.

DEVELOPMENT AND VALIDATION OF AN AIR-TO-BEEF FOOD CHAIN MODEL FOR DIOXIN-LIKE COMPOUNDS

EPA Science Inventory

A model for predicting concentrations of dioxin-like compounds in beef is developed and tested. The key premise of the model is that concentrations of these compounds in air are the source term, or starting point, for estimating beef concentrations. Vapor-phase concentrations t...

Influence of mastication rate on dynamic flavour release analysed by combined model mouth/proton transfer reaction-mass spectrometry

NASA Astrophysics Data System (ADS)

van Ruth, Saskia M.; Buhr, Katja

2004-12-01

The influence of mastication rate on the dynamic release of seven volatile flavour compounds from sunflower oil was evaluated by combined model mouth/proton transfer reaction-mass spectrometry (PTR-MS). Air/oil partition coefficients were measured by static headspace gas chromatography. The dynamic release of the seven volatile flavour compounds from sunflower oil was significantly affected by the compounds' hydrophobicity and the mastication rate employed in the model mouth. The more hydrophobic compounds were released at a higher rate than their hydrophilic counterparts. Increase in mastication rate increased the maximum concentration measured by 36% on average, and the time to reach this maximum by 35% on average. Mastication affected particularly the release of the hydrophilic compounds. The maximum concentration of the compounds correlated significantly with the compounds' air/oil partition coefficients. The initial release rates over the first 15 s were affected by the type of compound, but not by the mastication rate. During the course of release, the proportions of the hydrophilic compounds to the overall flavour mixture in air decreased. The contribution of the hydrophobic compounds increased. Higher mastication rates, however, increased the proportions of the hydrophilic compounds and decreased those of the hydrophobic compounds.

The role of multidrug resistance protein (MRP-1) as an active efflux transporter on blood-brain barrier (BBB) permeability.

PubMed

Lingineni, Karthik; Belekar, Vilas; Tangadpalliwar, Sujit R; Garg, Prabha

2017-05-01

Drugs acting on central nervous system (CNS) may take longer duration to reach the market as these compounds have a higher attrition rate in clinical trials due to the complexity of the brain, side effects, and poor blood-brain barrier (BBB) permeability compared to non-CNS-acting compounds. The roles of active efflux transporters with BBB are still unclear. The aim of the present work was to develop a predictive model for BBB permeability that includes the MRP-1 transporter, which is considered as an active efflux transporter. A support vector machine model was developed for the classification of MRP-1 substrates and non-substrates, which was validated with an external data set and Y-randomization method. An artificial neural network model has been developed to evaluate the role of MRP-1 on BBB permeation. A total of nine descriptors were selected, which included molecular weight, topological polar surface area, ClogP, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, P-gp, BCRP, and MRP-1 substrate probabilities for model development. We identified 5 molecules that fulfilled all criteria required for passive permeation of BBB, but they all have a low logBB value, which suggested that the molecules were effluxed by the MRP-1 transporter.

Selective Sorbents For Purification Of Hydrocarbons

DOEpatents

Yang, Ralph T.; Yang, Frances H.; Takahashi, Akira; Hernandez-Maldonado, Arturo J.

2006-04-18

A method for removing thiophene and thiophene compounds from liquid fuel includes contacting the liquid fuel with an adsorbent which preferentially adsorbs the thiophene and thiophene compounds. The adsorption takes place at a selected temperature and pressure, thereby producing a non-adsorbed component and a thiophene/thiophene compound-rich adsorbed component. The adsorbent includes either a metal or a metal ion that is adapted to form p-complexation bonds with the thiophene and/or thiophene compounds, and the preferential adsorption occurs by p-complexation. A further method includes selective removal of aromatic compounds from a mixture of aromatic and aliphatic compounds.

Selective sorbents for purification of hydrocarbons

DOEpatents

Yang, Ralph T.; Hernandez-Maldonado, Arturo J.; Yang, Frances H.; Takahashi, Akira

2006-08-22

A method for removing thiophene and thiophene compounds from liquid fuel includes contacting the liquid fuel with an adsorbent which preferentially adsorbs the thiophene and thiophene compounds. The adsorption takes place at a selected temperature and pressure, thereby producing a non-adsorbed component and a thiophene/thiophene compound-rich adsorbed component. The adsorbent includes either a metal or a metal cation that is adapted to form .pi.-complexation bonds with the thiophene and/or thiophene compounds, and the preferential adsorption occurs by .pi.-complexation. A further method includes selective removal of aromatic compounds from a mixture of aromatic and aliphatic compounds.

Selective sorbents for purification of hydrocarbons

DOEpatents

Yang, Ralph T.; Yang, Frances H.; Takahashi, Akira; Hernandez-Maldonado, Arturo J.

2006-05-30

A method for removing thiophene and thiophene compounds from liquid fuel includes contacting the liquid fuel with an adsorbent which preferentially adsorbs the thiophene and thiophene compounds. The adsorption takes place at a selected temperature and pressure, thereby producing a non-adsorbed component and a thiophene/thiophene compound-rich adsorbed component. The adsorbent includes either a metal or a metal cation that is adapted to form .pi.-complexation bonds with the thiophene and/or thiophene compounds, and the preferential adsorption occurs by .pi.-complexation. A further method includes selective removal of aromatic compounds from a mixture of aromatic and aliphatic compounds.

Selective sorbents for purification of hydrocartons

DOEpatents

Yang, Ralph T.; Yang, Frances H.; Takahashi, Akira; Hermandez-Maldonado, Arturo J.

2006-12-12

A method for removing thiophene and thiophene compounds from liquid fuel includes contacting the liquid fuel with an adsorbent which preferentially adsorbs the thiophene and thiophene compounds. The adsorption takes place at a selected temperature and pressure, thereby producing a non-adsorbed component and a thiophene/thiophene compound-rich adsorbed component. The adsorbent includes either a metal or a metal ion that is adapted to form .pi.-complexation bonds with the thiophene and/or thiophene compounds, and the preferential adsorption occurs by .pi.-complexation. A further method includes selective removal of aromatic compounds from a mixture of aromatic and aliphatic compounds.

Alleviation of Multiple Asthmatic Pathologic Features with Orally Available and Subtype Selective GABAA Receptor Modulators.

PubMed

Forkuo, Gloria S; Nieman, Amanda N; Yuan, Nina Y; Kodali, Revathi; Yu, Olivia B; Zahn, Nicolas M; Jahan, Rajwana; Li, Guanguan; Stephen, Michael Rajesh; Guthrie, Margaret L; Poe, Michael M; Hartzler, Benjamin D; Harris, Ted W; Yocum, Gene T; Emala, Charles W; Steeber, Douglas A; Stafford, Douglas C; Cook, James M; Arnold, Leggy A

2017-06-05

We describe pharmacokinetic and pharmacodynamic properties of two novel oral drug candidates for asthma. Phenolic α 4 β 3 γ 2 GABA A R selective compound 1 and acidic α 5 β 3 γ 2 selective GABA A R positive allosteric modulator compound 2 relaxed airway smooth muscle ex vivo and attenuated airway hyperresponsiveness (AHR) in a murine model of asthma. Importantly, compound 2 relaxed acetylcholine contracted human tracheal airway smooth muscle strips. Oral treatment of compounds 1 and 2 decreased eosinophils in bronchoalveolar lavage fluid in ovalbumin sensitized and challenged mice, thus exhibiting anti-inflammatory properties. Additionally, compound 1 reduced the number of lung CD4 + T lymphocytes and directly modulated their transmembrane currents by acting on GABA A Rs. Excellent pharmacokinetic properties were observed, including long plasma half-life (up to 15 h), oral availability, and extremely low brain distribution. In conclusion, we report the selective targeting of GABA A Rs expressed outside the brain and demonstrate reduction of AHR and airway inflammation with two novel orally available GABA A R ligands.

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

Derenzo, Stephen E.; Moses, William W.

An embodiment of a liquid chromatography detection unit includes a fluid channel and a radiation detector. The radiation detector is operable to image a distribution of a radiolabeled compound as the distribution travels along the fluid channel. An embodiment of a liquid chromatography system includes an injector, a separation column, and a radiation detector. The injector is operable to inject a sample that includes a radiolabeled compound into a solvent stream. The position sensitive radiation detector is operable to image a distribution of the radiolabeled compound as the distribution travels along a fluid channel. An embodiment of a method ofmore » liquid chromatography includes injecting a sample that comprises radiolabeled compounds into a solvent. The radiolabeled compounds are then separated. A position sensitive radiation detector is employed to image distributions of the radiolabeled compounds as the radiolabeled compounds travel along a fluid channel.« less

Phonon properties of lutetium pnictides

NASA Astrophysics Data System (ADS)

Arya, Balwant Singh; Aynyas, Mahendra; Sanyal, Sankar P.

2018-05-01

Phonon properties of Lutetium pnictides (LuX : X = P, As) have been studied by using breathing shell model (BSM) which includes breathing motion of electrons of the Lu atoms due to f-d hybridization to establish their predominant ionic nature. The calculated phonon dispersion curves of these compounds are presented follow the same trend as observed in ytterbium pnictides (YbP and YbAs). We also report one phonon density of states and specific heat for these compounds. We discuss the significance of this approach in predicting the phonon dispersion curves and examine the role of electron-phonon interaction.

Aromatic ring generation as a dust precursor in acetylene discharges

NASA Astrophysics Data System (ADS)

De Bleecker, Kathleen; Bogaerts, Annemie; Goedheer, Wim

2006-04-01

Production of aromatic hydrocarbon compounds as an intermediate step for particle formation in low-pressure acetylene discharges is investigated via a kinetic approach. The detailed chemical reaction mechanism contains 140 reactions among 55 species. The cyclic hydrocarbon chemistry is mainly based on studies of polycyclic aromatic hydrocarbon formation in cosmic environments. The model explicitly includes organic chain, cyclic molecules, radicals, and ions up to a size of 12 carbon atoms. The calculated density profiles show that the aromatic formation yields are quite significant, suggesting that aromatic compounds play a role in the underlying mechanisms of particle formation in hydrocarbon plasmas.

Neuroprotective Effect of Antioxidants and Moderate Hypoxia as Combined Preconditioning in Cerebral Ischemia.

PubMed

Levchenkova, O S; Novikov, V E; Parfenov, E A; Kulagin, K N

2016-12-01

We studied combined effect of moderate hypoxia and compounds pQ-4, pQ-915, pQ-1032, and pQ-1104 on neurological deficit and survival of rats after bilateral ligation of common carotid arteries. Preconditioning including moderate hypoxia and treatment with compound pQ-4 produced a neuroprotective effect and increased animal survival during the early (by 51%) and late (by 33.5%) periods of modeled ischemia and reduced neurological deficit (by 50% and 41%, respectively). Moreover, this combination of preconditioning factors prevented postischemic excessive activation of free radical oxidation in brain hemispheres and blood serum.

Development and Evaluation of Topical Gabapentin Formulations

PubMed Central

Alcock, Natalie; Hiom, Sarah; Birchall, James C.

2017-01-01

Topical delivery of gabapentin is desirable to treat peripheral neuropathic pain conditions whilst avoiding systemic side effects. To date, reports of topical gabapentin delivery in vitro have been variable and dependent on the skin model employed, primarily involving rodent and porcine models. In this study a variety of topical gabapentin formulations were investigated, including Carbopol® hydrogels containing various permeation enhancers, and a range of proprietary bases including a compounded Lipoderm® formulation; furthermore microneedle facilitated delivery was used as a positive control. Critically, permeation of gabapentin across a human epidermal membrane in vitro was assessed using Franz-type diffusion cells. Subsequently this data was contextualised within the wider scope of the literature. Although reports of topical gabapentin delivery have been shown to vary, largely dependent upon the skin model used, this study demonstrated that 6% (w/w) gabapentin 0.75% (w/w) Carbopol® hydrogels containing 5% (w/w) DMSO or 70% (w/w) ethanol and a compounded 10% (w/w) gabapentin Lipoderm® formulation were able to facilitate permeation of the molecule across human skin. Further pre-clinical and clinical studies are required to investigate the topical delivery performance and pharmacodynamic actions of prospective formulations. PMID:28867811

From small sweeteners to sweet proteins: anatomy of the binding sites of the human T1R2_T1R3 receptor.

PubMed

Morini, Gabriella; Bassoli, Angela; Temussi, Piero A

2005-08-25

The sweet taste receptor, a heterodimeric G protein coupled receptor (GPCR) protein, formed by the T1R2 and T1R3 subunits, recognizes several sweet compounds including carbohydrates, amino acids, peptides, proteins, and synthetic sweeteners. Its similarity with the metabotropic glutamate mGluR1 receptor allowed us to build homology models. All possible dimers formed by combinations of the human T1R2 and T1R3 subunits, modeled on the A (closed) or B (open) chains of the extracellular ligand binding domain of the mGluR1 template, yield four ligand binding sites for low-molecular-weight sweeteners. These sites were probed by docking a set of molecules representative of all classes of sweet compounds and calculating the free energy of ligand binding. These sites are not easily accessible to sweet proteins, but docking experiments in silico showed that sweet proteins can bind to a secondary site without entering the deep cleft. Our models account for many experimental observations on the tastes of sweeteners, including sweetness synergy, and can help to design new sweeteners.

Sorption of bisphenol A, 17a-ethinyl estradiol and phenanthrene on thermally and hydrothermally produced biochars

USDA-ARS?s Scientific Manuscript database

In this study, organic contaminant removal potential of biochars made from various agricultural residuals was investigated through sorption experiments. The model pollutants include endocrine disrupting chemicals (EDCs) such as common estrogenic compounds, bisphenol A (BPA) and 17a-ethinyl estradiol...

A PBPK MODEL FOR EVALUATING THE IMPACT OF ALDEHYDE DEHYDROGENASE POLYMORPHISMS ON COMPARATIVE RAT AND HUMAN NASAL TISSUE ACETALDEHYDE DOSIMETRY

EPA Science Inventory

ABSTRACT: Acetaldehyde is an important intermediate in chemical synthesis and a byproduct of normal oxidative metabolism of several industrially important compounds including ethanol, ethyl acetate and vinyl acetate. Chronic inhalation of acetaldehyde leads to degeneratio...

COMPUTATIONAL CHEMISTRY METHOD FOR PREDICTING VAPOR PRESSURES AND ACTIVITY COEFFICIENTS OF POLAR ORGANIC OXYGENATES IN PM2.5

EPA Science Inventory

Parameterizations of interactions of polar multifunctional organic oxygenates in PM2.5 must be included in aerosol chemistry models for evaluating control strategies for reducing ambient concentrations of PM2.5 compounds. Vapor pressures and activity coefficients of these compo...

A PBPK model for evaluating the impact of aldehyde dehydrogenase polymorphisms on comparative rat and human nasal tissue acetaldehyde dosimetry*

EPA Science Inventory

Acetaldehyde is an important intermediate in the chemical synthesis and normal oxidative metabolism of several industrially important compounds, including ethanol, ethyl acetate, and vinyl acetate. Chronic inhalation of acetaldehyde leads to degeneration of the olfactory and resp...

Role of natural attenuation in modeling the leaching of contaminants in the risk analysis framework.

PubMed

Verginelli, Iason; Baciocchi, Renato

2013-01-15

Natural attenuation (NA) processes occurring in the subsurface can significantly affect the impact on groundwater from contamination sources located in the vadose zone, especially when mobile and readily biodegradable compounds, such as BTEX, are present. Besides, in the last decades several studies have shown natural attenuation to take place also for more persistent compounds, such as Polycyclic Aromatic Hydrocarbons (PAHs). Nevertheless, common risk analysis frameworks, based on the ASTM RBCA (Risk Based Corrective Action) approach, do not include NA pathways in the fate and transport models, thus possibly leading to an overestimation of the calculated risk. The aim of this study was to provide an insight on the relevance of the different key natural attenuation processes usually taking place in the subsurface and to highlight for which contamination scenarios their inclusion in the risk-analysis framework could provide a more realistic risk assessment. To this end, an analytical model accounting for source depletion and biodegradation, dispersion and diffusion during leaching was developed and applied to several contamination scenarios. These scenarios included contamination by BTEX, characterized by relatively high mobility and biodegradation rate, and PAHs, i.e. a more persistent class of compounds. The obtained results showed that BTEX are likely to be attenuated in the source zone due to their mobility and ready biodegradation (assuming biodegradation constant rates in the order of 0.01-1 d(-1)). Instead, attenuation along transport through the vadose zone was found to be less important, as the residence time of the contaminant in the unsaturated zone is often too low with respect to the time required to get a relevant biodegradation of BTEX. On the other hand, heavier compounds such as PAHs, were found to be attenuated during leaching since the residence time in the vadose zone can reach values up to thousands of years. In these cases, even with the relatively slow biodegradation rate of PAHs, in the order of 0.0001-0.001 d(-1), attenuation can result significant. These conclusions were also confirmed by comparing the model results with experimental data collected at an hydrocarbon-contaminated site. The proposed model, that neglects the transport of NAPLs, could be easily included in the risk-analysis framework, allowing to get a more realistic assessment of risks, while keeping the intrinsic simplicity of the ASTM-RBCA approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

Seaweed and human health.

PubMed

Brown, Emma S; Allsopp, Philip J; Magee, Pamela J; Gill, Chris I R; Nitecki, Sonja; Strain, Conall R; McSorley, Emeir M

2014-03-01

Seaweeds may have an important role in modulating chronic disease. Rich in unique bioactive compounds not present in terrestrial food sources, including different proteins (lectins, phycobiliproteins, peptides, and amino acids), polyphenols, and polysaccharides, seaweeds are a novel source of compounds with potential to be exploited in human health applications. Purported benefits include antiviral, anticancer, and anticoagulant properties as well as the ability to modulate gut health and risk factors for obesity and diabetes. Though the majority of studies have been performed in cell and animal models, there is evidence of the beneficial effect of seaweed and seaweed components on markers of human health and disease status. This review is the first to critically evaluate these human studies, aiming to draw attention to gaps in current knowledge, which will aid the planning and implementation of future studies.

eBASIS (Bioactive Substances in Food Information Systems) and Bioactive Intakes: Major Updates of the Bioactive Compound Composition and Beneficial Bioeffects Database and the Development of a Probabilistic Model to Assess Intakes in Europe

PubMed Central

Plumb, Jenny; Pigat, Sandrine; Bompola, Foteini; Cushen, Maeve; Pinchen, Hannah; Nørby, Eric; Astley, Siân; Lyons, Jacqueline; Kiely, Mairead; Finglas, Paul

2017-01-01

eBASIS (Bioactive Substances in Food Information Systems), a web-based database that contains compositional and biological effects data for bioactive compounds of plant origin, has been updated with new data on fruits and vegetables, wheat and, due to some evidence of potential beneficial effects, extended to include meat bioactives. eBASIS remains one of only a handful of comprehensive and searchable databases, with up-to-date coherent and validated scientific information on the composition of food bioactives and their putative health benefits. The database has a user-friendly, efficient, and flexible interface facilitating use by both the scientific community and food industry. Overall, eBASIS contains data for 267 foods, covering the composition of 794 bioactive compounds, from 1147 quality-evaluated peer-reviewed publications, together with information from 567 publications describing beneficial bioeffect studies carried out in humans. This paper highlights recent updates and expansion of eBASIS and the newly-developed link to a probabilistic intake model, allowing exposure assessment of dietary bioactive compounds to be estimated and modelled in human populations when used in conjunction with national food consumption data. This new tool could assist small- and medium-sized enterprises (SMEs) in the development of food product health claim dossiers for submission to the European Food Safety Authority (EFSA). PMID:28333085

Comparison of in vitro and in vivo bioassays to measure thyroid hormone disrupting activity in water extracts.

PubMed

Leusch, Frederic D L; Aneck-Hahn, Natalie H; Cavanagh, Jo-Anne E; Du Pasquier, David; Hamers, Timo; Hebert, Armelle; Neale, Peta A; Scheurer, Marco; Simmons, Steven O; Schriks, Merijn

2018-01-01

Environmental chemicals can induce thyroid disruption through a number of mechanisms including altered thyroid hormone biosynthesis and transport, as well as activation and inhibition of the thyroid receptor. In the current study six in vitro bioassays indicative of different mechanisms of thyroid disruption and one whole animal in vivo assay were applied to 9 model compounds and 4 different water samples (treated wastewater, surface water, drinking water and ultra-pure lab water; both unspiked and spiked with model compounds) to determine their ability to detect thyroid active compounds. Most assays correctly identified and quantified the model compounds as agonists or antagonists, with the reporter gene assays being the most sensitive. However, the reporter gene assays did not detect significant thyroid activity in any of the water samples, suggesting that activation or inhibition of the thyroid hormone receptor is not a relevant mode of action for thyroid endocrine disruptors in water. The thyroperoxidase (TPO) inhibition assay and transthyretin (TTR) displacement assay (FITC) detected activity in the surface water and treated wastewater samples, but more work is required to assess if this activity is a true measure of thyroid activity or matrix interference. The whole animal Xenopus Embryonic Thyroid Assay (XETA) detected some activity in the unspiked surface water and treated wastewater extracts, but not in unspiked drinking water, and appears to be a suitable assay to detect thyroid activity in environmental waters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determination of the n-octanol/water partition coefficients of weakly ionizable basic compounds by reversed-phase high-performance liquid chromatography with neutral model compounds.

PubMed

Liang, Chao; Han, Shu-ying; Qiao, Jun-qin; Lian, Hong-zhen; Ge, Xin

2014-11-01

A strategy to utilize neutral model compounds for lipophilicity measurement of ionizable basic compounds by reversed-phase high-performance liquid chromatography is proposed in this paper. The applicability of the novel protocol was justified by theoretical derivation. Meanwhile, the linear relationships between logarithm of apparent n-octanol/water partition coefficients (logKow '') and logarithm of retention factors corresponding to the 100% aqueous fraction of mobile phase (logkw ) were established for a basic training set, a neutral training set and a mixed training set of these two. As proved in theory, the good linearity and external validation results indicated that the logKow ''-logkw relationships obtained from a neutral model training set were always reliable regardless of mobile phase pH. Afterwards, the above relationships were adopted to determine the logKow of harmaline, a weakly dissociable alkaloid. As far as we know, this is the first report on experimental logKow data for harmaline (logKow = 2.28 ± 0.08). Introducing neutral compounds into a basic model training set or using neutral model compounds alone is recommended to measure the lipophilicity of weakly ionizable basic compounds especially those with high hydrophobicity for the advantages of more suitable model compound choices and convenient mobile phase pH control. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electromembrane extraction of zwitterionic compounds as acid or base: comparison of extraction behavior at acidic and basic pHs.

PubMed

Nojavan, Saeed; Pourahadi, Ahmad; Hosseiny Davarani, Saied Saeed; Morteza-Najarian, Amin; Beigzadeh Abbassi, Mojtaba

2012-10-01

This study has performed on electromembrane extraction (EME) of some zwitterionic compounds based on their acidic and basic properties. High performance liquid chromatography (HPLC) equipped with UV detection was used for determination of model compounds. Cetirizine (CTZ) and mesalazine (MS) were chosen as model compounds, and each of them was extracted from acidic (as a cation) and basic (as an anion) sample solutions, separately. 1-Octanol and 2-nitrophenyl octylether (NPOE) were used as the common supported liquid membrane (SLM) solvents. EME parameters, such as extraction time, extraction voltage and pH of donor and acceptor solutions were studied in details for cationic and anionic forms of each model compound and obtained results for two ionic forms (cationic and anionic) of each compound were compared together. Results showed that zwitterionic compounds could be extracted in both cationic and anionic forms. Moreover, it was found that the extraction of anionic form of each model compound could be done in low voltages when 1-octanol was used as the SLM solvent. Results showed that charge type was not highly effective on the extraction efficiency of model compounds whereas the position of charge within the molecule was the key parameter. In optimized conditions, enrichment factors (EF) of 27-60 that corresponded to recoveries ranging from 39 to 86% were achieved. Copyright © 2012 Elsevier B.V. All rights reserved.

Real-Time Measurements of Gas/Particle Partitioning of Semivolatile Organic Compounds into Different Probe Particles in a Teflon Chamber

NASA Astrophysics Data System (ADS)

Liu, X.; Day, D. A.; Ziemann, P. J.; Krechmer, J. E.; Jimenez, J. L.

2017-12-01

The partitioning of semivolatile organic compounds (SVOCs) into and out of particles plays an essential role in secondary organic aerosol (SOA) formation and evolution. Most atmospheric models treat the gas/particle partitioning as an equilibrium between bulk gas and particle phases, despite potential kinetic limitations and differences in thermodynamics as a function of SOA and pre-existing OA composition. This study directly measures the partitioning of oxidized compounds in a Teflon chamber in the presence of single component seeds of different phases and polarities, including oleic acid, squalane, dioctyl sebacate, pentaethylene glycol, dry/wet ammonium sulfate, and dry/wet sucrose. The oxidized compounds are generated by a fast OH oxidation of a series of alkanols under high nitric oxide conditions. The observed SOA mass enhancements are highest with oleic acid, and lowest with wet ammonium sulfate and sucrose. A chemical ionization mass spectrometer (CIMS) was used to measure the decay of gas-phase organic nitrates, which reflects uptake by particles and chamber walls. We observed clear changes in equilibrium timescales with varying seed concentrations and in equilibrium gas-phase concentrations across different seeds. In general, the gas evolution can be reproduced by a kinetic box model that considers partitioning and evaporation with particles and chamber walls, except for the wet sucrose system. The accommodation coefficient and saturation mass concentration of each species in the presence of each seed are derived using the model. The changes in particle size distributions and composition monitored by a scanning mobility particle sizer (SMPS) and a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) are investigated to probe the SOA formation mechanism. Based on these results, the applicability of partitioning theory to these systems and the relevant quantitative parameters, including the dependencies on seed particle composition, will be discussed.

From Broad-Spectrum Biocides to Quorum Sensing Disruptors and Mussel Repellents: Antifouling Profile of Alkyl Triphenylphosphonium Salts

PubMed Central

Martín-Rodríguez, Alberto J.; Babarro, Jose M. F.; Lahoz, Fernando; Sansón, Marta; Martín, Víctor S.; Norte, Manuel; Fernández, José J.

2015-01-01

‘Onium’ compounds, including ammonium and phosphonium salts, have been employed as antiseptics and disinfectants. These cationic biocides have been incorporated into multiple materials, principally to avoid bacterial attachment. In this work, we selected 20 alkyl-triphenylphosphonium salts, differing mainly in the length and functionalization of their alkyl chains, in fulfilment of two main objectives: 1) to provide a comprehensive evaluation of the antifouling profile of these molecules with relevant marine fouling organisms; and 2) to shed new light on their potential applications, beyond their classic use as broad-spectrum biocides. In this regard, we demonstrate for the first time that these compounds are also able to act as non-toxic quorum sensing disruptors in two different bacterial models (Chromobacterium violaceum and Vibrio harveyi) as well as repellents in the mussel Mytilus galloprovincialis. In addition, their inhibitory activity on a fouling-relevant enzymatic model (tyrosinase) is characterized. An analysis of the structure-activity relationships of these compounds for antifouling purposes is provided, which may result useful in the design of targeted antifouling solutions with these molecules. Altogether, the findings reported herein provide a different perspective on the biological activities of phosphonium compounds that is particularly focused on, but, as the reader will realize, is not limited to their use as antifouling agents. PMID:25897858

Kinetics of biological methane oxidation in the presence of non-methane organic compounds in landfill bio-covers

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

Albanna, Muna, E-mail: muna.albanna@gju.edu.j; Warith, Mostafa; Fernandes, Leta

2010-02-15

In this experimental program, the effects of non-methane organic compounds (NMOCs) on the biological methane (CH{sub 4}) oxidation process were examined. The investigation was performed on compost experiments incubated with CH{sub 4} and selected NMOCs under different environmental conditions. The selected NMOCs had different concentrations and their effects were tested as single compounds and mixtures of compounds. The results from all experimental sets showed a decrease in CH{sub 4} oxidation capacity of the landfill bio-cover with the increase in NMOCs concentrations. For example, in the experiment using compost with 100% moisture content at 35 deg. C without any NMOCs themore » V{sub max} value was 35.0 mug CH{sub 4}h{sup -1}g{sub wetwt}{sup -1}. This value was reduced to 19.1 mug CH{sub 4}h{sup -1}g{sub wetwt}{sup -1} when mixed NMOCs were present in the batch reactors under the same environmental conditions. The experimental oxidation rates of CH{sub 4} in the presence of single and mixed NMOCs were modeled using the uncompetitive inhibition model and kinetic parameters, including the dissociation constants, were obtained. Additionally, the degradation rates of the NMOCs and co-metabolic abilities of methanotrophic bacteria were estimated.« less

Simulating and explaining passive air sampling rates for semi-volatile compounds on polyurethane foam passive samplers

PubMed Central

Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.

2013-01-01

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599

Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits

PubMed Central

Hermes, Helen E.; Teutonico, Donato; Preuss, Thomas G.; Schneckener, Sebastian

2018-01-01

The environmental fates of pharmaceuticals and the effects of crop protection products on non-target species are subjects that are undergoing intense review. Since measuring the concentrations and effects of xenobiotics on all affected species under all conceivable scenarios is not feasible, standard laboratory animals such as rabbits are tested, and the observed adverse effects are translated to focal species for environmental risk assessments. In that respect, mathematical modelling is becoming increasingly important for evaluating the consequences of pesticides in untested scenarios. In particular, physiologically based pharmacokinetic/toxicokinetic (PBPK/TK) modelling is a well-established methodology used to predict tissue concentrations based on the absorption, distribution, metabolism and excretion of drugs and toxicants. In the present work, a rabbit PBPK/TK model is developed and evaluated with data available from the literature. The model predictions include scenarios of both intravenous (i.v.) and oral (p.o.) administration of small and large compounds. The presented rabbit PBPK/TK model predicts the pharmacokinetics (Cmax, AUC) of the tested compounds with an average 1.7-fold error. This result indicates a good predictive capacity of the model, which enables its use for risk assessment modelling and simulations. PMID:29561908

EMPIRE: Nuclear Reaction Model Code System for Data Evaluation

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

Herman, M.; Capote, R.; Carlson, B.V.

EMPIRE is a modular system of nuclear reaction codes, comprising various nuclear models, and designed for calculations over a broad range of energies and incident particles. A projectile can be a neutron, proton, any ion (including heavy-ions) or a photon. The energy range extends from the beginning of the unresolved resonance region for neutron-induced reactions ({approx} keV) and goes up to several hundred MeV for heavy-ion induced reactions. The code accounts for the major nuclear reaction mechanisms, including direct, pre-equilibrium and compound nucleus ones. Direct reactions are described by a generalized optical model (ECIS03) or by the simplified coupled-channels approachmore » (CCFUS). The pre-equilibrium mechanism can be treated by a deformation dependent multi-step direct (ORION + TRISTAN) model, by a NVWY multi-step compound one or by either a pre-equilibrium exciton model with cluster emission (PCROSS) or by another with full angular momentum coupling (DEGAS). Finally, the compound nucleus decay is described by the full featured Hauser-Feshbach model with {gamma}-cascade and width-fluctuations. Advanced treatment of the fission channel takes into account transmission through a multiple-humped fission barrier with absorption in the wells. The fission probability is derived in the WKB approximation within the optical model of fission. Several options for nuclear level densities include the EMPIRE-specific approach, which accounts for the effects of the dynamic deformation of a fast rotating nucleus, the classical Gilbert-Cameron approach and pre-calculated tables obtained with a microscopic model based on HFB single-particle level schemes with collective enhancement. A comprehensive library of input parameters covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers, moments of inertia and {gamma}-ray strength functions. The results can be converted into ENDF-6 formatted files using the accompanying code EMPEND and completed with neutron resonances extracted from the existing evaluations. The package contains the full EXFOR (CSISRS) library of experimental reaction data that are automatically retrieved during the calculations. Publication quality graphs can be obtained using the powerful and flexible plotting package ZVView. The graphic user interface, written in Tcl/Tk, provides for easy operation of the system. This paper describes the capabilities of the code, outlines physical models and indicates parameter libraries used by EMPIRE to predict reaction cross sections and spectra, mainly for nucleon-induced reactions. Selected applications of EMPIRE are discussed, the most important being an extensive use of the code in evaluations of neutron reactions for the new US library ENDF/B-VII.0. Future extensions of the system are outlined, including neutron resonance module as well as capabilities of generating covariances, using both KALMAN and Monte-Carlo methods, that are still being advanced and refined.« less

Compounded effects of heat waves and droughts over the Western Electricity Grid: spatio-temporal scales of impacts and predictability toward mitigation and adaptation.

NASA Astrophysics Data System (ADS)

Voisin, N.; Kintner-Meyer, M.; Skaggs, R.; Xie, Y.; Wu, D.; Nguyen, T. B.; Fu, T.; Zhou, T.

2016-12-01

Heat waves and droughts are projected to be more frequent and intense. We have seen in the past the effects of each of those extreme climate events on electricity demand and constrained electricity generation, challenging power system operations. Our aim here is to understand the compounding effects under historical conditions. We present a benchmark of Western US grid performance under 55 years of historical climate, and including droughts, using 2010-level of water demand and water management infrastructure, and 2010-level of electricity grid infrastructure and operations. We leverage CMIP5 historical hydrology simulations and force a large scale river routing- reservoir model with 2010-level sectoral water demands. The regulated flow at each water-dependent generating plants is processed to adjust water-dependent electricity generation parameterization in a production cost model, that represents 2010-level power system operations with hourly energy demand of 2010. The resulting benchmark includes a risk distribution of several grid performance metrics (unserved energy, production cost, carbon emission) as a function of inter-annual variability in regional water availability and predictability using large scale climate oscillations. In the second part of the presentation, we describe an approach to map historical heat waves onto this benchmark grid performance using a building energy demand model. The impact of the heat waves, combined with the impact of droughts, is explored at multiple scales to understand the compounding effects. Vulnerabilities of the power generation and transmission systems are highlighted to guide future adaptation.

Modifiers of radiation effects in the eye

NASA Astrophysics Data System (ADS)

Kleiman, Norman J.; Stewart, Fiona A.; Hall, Eric J.

2017-11-01

World events, including the threat of radiological terrorism and the fear of nuclear accidents, have highlighted an urgent need to develop medical countermeasures to prevent or reduce radiation injury. Similarly, plans for manned spaceflight to a near-Earth asteroid or journey to Mars raise serious concerns about long-term effects of space radiation on human health and the availability of suitable therapeutic interventions. At the same time, the need to protect normal tissue from the deleterious effects of radiotherapy has driven considerable research into the design of effective radioprotectors. For more than 70 years, animal models of radiation cataract have been utilized to test the short and long-term efficacy of various radiation countermeasures. While some compounds, most notably the Walter Reed (WR) class of radioprotectors, have reported limited effectiveness when given before exposure to low-LET radiation, the human toxicity of these molecules at effective doses limits their usefulness. Furthermore, while there has been considerable testing of eye responses to X- and gamma irradiation, there is limited information about using such models to limit the injurious effects of heavy ions and neutrons on eye tissue. A new class of radioprotector molecules, including the sulfhydryl compound PrC-210, are reported to be effective at much lower doses and with far less side effects. Their ability to modify ocular radiation damage has not yet been examined. The ability to non-invasively measure sensitive, radiation-induced ocular changes over long periods of time makes eye models an attractive option to test the radioprotective and radiation mitigating abilities of new novel compounds.

Insights into Hydrate Formation and Stability of Morphinanes from a Combination of Experimental and Computational Approaches

PubMed Central

2014-01-01

Morphine, codeine, and ethylmorphine are important drug compounds whose free bases and hydrochloride salts form stable hydrates. These compounds were used to systematically investigate the influence of the type of functional groups, the role of water molecules, and the Cl– counterion on molecular aggregation and solid state properties. Five new crystal structures have been determined. Additionally, structure models for anhydrous ethylmorphine and morphine hydrochloride dihydrate, two phases existing only in a very limited humidity range, are proposed on the basis of computational dehydration modeling. These match the experimental powder X-ray diffraction patterns and the structural information derived from infrared spectroscopy. All 12 structurally characterized morphinane forms (including structures from the Cambridge Structural Database) crystallize in the orthorhombic space group P212121. Hydrate formation results in higher dimensional hydrogen bond networks. The salt structures of the different compounds exhibit only little structural variation. Anhydrous polymorphs were detected for all compounds except ethylmorphine (one anhydrate) and its hydrochloride salt (no anhydrate). Morphine HCl forms a trihydrate and dihydrate. Differential scanning and isothermal calorimetry were employed to estimate the heat of the hydrate ↔ anhydrate phase transformations, indicating an enthalpic stabilization of the respective hydrate of 5.7 to 25.6 kJ mol–1 relative to the most stable anhydrate. These results are in qualitative agreement with static 0 K lattice energy calculations for all systems except morphine hydrochloride, showing the need for further improvements in quantitative thermodynamic prediction of hydrates having water···water interactions. Thus, the combination of a variety of experimental techniques, covering temperature- and moisture-dependent stability, and computational modeling allowed us to generate sufficient kinetic, thermodynamic and structural information to understand the principles of hydrate formation of the model compounds. This approach also led to the detection of several new crystal forms of the investigated morphinanes. PMID:25036525

Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

Cannabinoids as Anticancer Drugs.

PubMed

Ramer, Robert; Hinz, Burkhard

2017-01-01

The endocannabinoid system encompassing cannabinoid receptors, endogenous receptor ligands (endocannabinoids), as well as enzymes conferring the synthesis and degradation of endocannabinoids has emerged as a considerable target for pharmacotherapeutical approaches of numerous diseases. Besides palliative effects of cannabinoids used in cancer treatment, phytocannabinoids, synthetic agonists, as well as substances that increase endogenous endocannabinoid levels have gained interest as potential agents for systemic cancer treatment. Accordingly, cannabinoid compounds have been reported to inhibit tumor growth and spreading in numerous rodent models. The underlying mechanisms include induction of apoptosis, autophagy, and cell cycle arrest in tumor cells as well as inhibition of tumor cell invasion and angiogenic features of endothelial cells. In addition, cannabinoids have been shown to suppress epithelial-to-mesenchymal transition, to enhance tumor immune surveillance, and to support chemotherapeutics' effects on drug-resistant cancer cells. However, unwanted side effects include psychoactivity and possibly pathogenic effects on liver health. Other cannabinoids such as the nonpsychoactive cannabidiol exert a comparatively good safety profile while exhibiting considerable anticancer properties. So far experience with anticarcinogenic effects of cannabinoids is confined to in vitro studies and animal models. Although a bench-to-bedside conversion remains to be established, the current knowledge suggests cannabinoid compounds to serve as a group of drugs that may offer significant advantages for patients suffering from cancer diseases. The present review summarizes the role of the endocannabinoid system and cannabinoid compounds in tumor progression. © 2017 Elsevier Inc. All rights reserved.

Preclinical characterization of signal transducer and activator of transcription 3 small molecule inhibitors for primary and metastatic brain cancer therapy.

PubMed

Assi, Hikmat H; Paran, Chris; VanderVeen, Nathan; Savakus, Jonathan; Doherty, Robert; Petruzzella, Emanuele; Hoeschele, James D; Appelman, Henry; Raptis, Leda; Mikkelsen, Tom; Lowenstein, Pedro R; Castro, Maria G

2014-06-01

Signal transducer and activator of transcription 3 (STAT3) has been implicated as a hub for multiple oncogenic pathways. The constitutive activation of STAT3 is present in several cancers, including gliomas (GBMs), and is associated with poor therapeutic responses. Phosphorylation of STAT3 triggers its dimerization and nuclear transport, where it promotes the transcription of genes that stimulate tumor growth. In light of this role, inhibitors of the STAT3 pathway are attractive therapeutic targets for cancer. To this end, we evaluated the STAT3-inhibitory activities of three compounds (CPA-7 [trichloronitritodiammineplatinum(IV)], WP1066 [(S,E)-3-(6-bromopyridin-2-yl)-2-cyano-N-(1-phenylethyl)acrylamide, C17H14BrN3O], and ML116 [4-benzyl-1-{thieno[2,3-d]pyrimidin-4-yl}piperidine, C18H19N3S]) in cultured rodent and human glioma cells, including GBM cancer stem cells. Our results demonstrate a potent induction of growth arrest in GBM cells after drug treatment with a concomitant induction of cell death. Although these compounds were effective at inhibiting STAT3 phosphorylation, they also displayed variable dose-dependent inhibition of STAT1, STAT5, and nuclear factor κ light-chain enhancer of activated B cells. The therapeutic efficacy of these compounds was further evaluated in peripheral and intracranial mouse tumor models. Whereas CPA-7 elicited regression of peripheral tumors, both melanoma and GBM, its efficacy was not evident when the tumors were implanted within the brain. Our data suggest poor permeability of this compound to tumors located within the central nervous system. WP1066 and ML116 exhibited poor in vivo efficacy. In summary, CPA-7 constitutes a powerful anticancer agent in models of peripheral solid cancers. Our data strongly support further development of CPA-7-derived compounds with increased permeability to enhance their efficacy in primary and metastatic brain tumors.

Meta-analysis of pesticide sorption in subsoils

NASA Astrophysics Data System (ADS)

Jarvis, Nicholas

2017-04-01

It has been known for several decades that sorption koc values tend to be larger in soils that are low in organic carbon (i.e. subsoils). Nevertheless, in a regulatory context, the models used to assess leaching of pesticides to groundwater still rely on a constant koc value, which is usually measured on topsoil samples. This is mainly because the general applicability of any improved model approach that is also simple enough to use for regulatory purposes has not been demonstrated. The objective of this study was therefore first to summarize and generalize available literature data in order to assess the magnitude of any systematic increase of koc values in subsoil and to test an alternative model of subsoil sorption that could be useful in pesticide risk assessment and management. To this end, a database containing the results of batch sorption experiments for pesticides was compiled from published studies in the literature, which placed at least as much emphasis on measurements in subsoil horizons as in topsoil. The database includes 967 data entries from 46 studies and for 34 different active substances (15 non-ionic compounds, 13 weak acids, 6 weak bases). In order to minimize pH effects on sorption, data for weak acids and bases were only included if the soil pH was more than two units larger than the compound pKa. A simple empirical model, whereby the sorption constant is given as a power law function of the soil organic carbon content, gave good fits to most data sets. Overall, the apparent koc value, koc(app), for non-ionic compounds and weak bases roughly doubled as the soil organic carbon content decreased by a factor of ten. The typical increase in koc(app) was even larger for weak acids: on average koc(app) increased by a factor of six as soil organic carbon content decreased by a factor of ten. These results suggest the koc concept currently used in leaching models should be replaced by an alternative approach that gives a more realistic representation of pesticide sorption in subsoil. The model tested in this study appears to be widely applicable and simple enough to parameterize for risk assessment purposes. However, more data on subsoil sorption should first be included in the analysis to enable reliable estimation of worst-case percentile values of the power law exponent in the model.

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.

Heavy Metals in ToxCast: Relevance to Food Safety (SOT) ...

EPA Pesticide Factsheets

Human exposure to heavy metals occurs through food contamination due to industrial processes, vehicle emissions and farming methods. Specific toxicity endpoints have been associated with metal exposures, e.g. lead and neurotoxicity; however, numerous varieties of heavy metals have not been systematically examined for potential toxicities. We describe results from testing a large set of heavy metal-containing compounds in extensive suites of in vitro assays to suggest possible molecular initiating events in toxicity pathways. A broad definition of heavy metals that includes As, Se and organometallics or inorganic salts containing metals in Group III or higher (MW > 40) was used to identify 75 different compounds tested in the EPA’s ToxCast assays encompassing biochemical, cellular and model organism assays. These 75, plus an additional 100 metal-containing compounds, were tested in Tox21 quantitative high-throughput screening (qHTS) assays covering nuclear receptor and stress pathways. Known activities were confirmed such as activation of stress pathways and nuclear receptors (RXR, PPARg) as well as overt cytotoxicity. Specifically, organotin and organomercury were among the most potent of over 8K chemicals tested. The HTS results support known toxicities, including promiscuous GPCR activity for mercury compounds consistent with the neuropsychiatric effects seen in mercury poisoning (Mad Hatter’s Syndrome). As such, HTS approaches provide an efficient method

Interspecies Interactions Stimulate Diversification of the Streptomyces coelicolor Secreted Metabolome

PubMed Central

Traxler, Matthew F.; Watrous, Jeramie D.; Alexandrov, Theodore; Dorrestein, Pieter C.; Kolter, Roberto

2013-01-01

ABSTRACT Soils host diverse microbial communities that include filamentous actinobacteria (actinomycetes). These bacteria have been a rich source of useful metabolites, including antimicrobials, antifungals, anticancer agents, siderophores, and immunosuppressants. While humans have long exploited these compounds for therapeutic purposes, the role these natural products may play in mediating interactions between actinomycetes has been difficult to ascertain. As an initial step toward understanding these chemical interactions at a systems level, we employed the emerging techniques of nanospray desorption electrospray ionization (NanoDESI) and matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) imaging mass spectrometry to gain a global chemical view of the model bacterium Streptomyces coelicolor interacting with five other actinomycetes. In each interaction, the majority of secreted compounds associated with S. coelicolor colonies were unique, suggesting an idiosyncratic response from S. coelicolor. Spectral networking revealed a family of unknown compounds produced by S. coelicolor during several interactions. These compounds constitute an extended suite of at least 12 different desferrioxamines with acyl side chains of various lengths; their production was triggered by siderophores made by neighboring strains. Taken together, these results illustrate that chemical interactions between actinomycete bacteria exhibit high complexity and specificity and can drive differential secondary metabolite production. PMID:23963177

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

Glaser, D.; Connolly, J.; Berghoffen, A.

The resident bald eagles of the lower Columbia River have lower productivity and higher contaminant levels than other bald eagles of the Pacific Northwest. The primary population stressors are believed to be habitat loss, human disturbance, p,p{prime}DDE, PCBs, dioxins and furans. The primary effect of habitat loss is to reduce the carrying capacity of the region for nesting sites, and the primary effects of human disturbance and contamination by organic compounds are to reduce productivity. The purpose of this study was to quantitatively evaluate the effects of all of, these potential stressors on the bald eagle population dynamics. A modelmore » of the population dynamics was developed. The model structure includes a physiologically-based toxicokinetic (PBTK) submodel to estimate the degree of contamination, which is linked via a toxicology submodel to a population dynamics submodel. The PBTK submodel is time-variable, incorporating species-specific bioenergetics, as well as contaminant assimilation and excretion rates for each compound of interest. Calculated body burdens and egg concentrations for each compound account for spatial and temporal variations in feeding habits and prey contaminant levels. The population submodel includes fecundity and survival information, as well as a limit to the number of breeding pairs (carrying capacity) and a population of non-breeding subadults and adults (floaters). Model simulations are performed in a Monte Carlo framework. Results include estimates of the persistence, resistance and resilience of the population: the probability of extinction, the relationship between magnitude of stress and change in population size, and the time course of recovery of a population following a reduction in stress.« less

The possible DNA damage induced by environmental organic compounds: The case of Nonylphenol.

PubMed

Noorimotlagh, Zahra; Mirzaee, Seyyed Abbas; Ahmadi, Mehdi; Jaafarzadeh, Neemat; Rahim, Fakher

2018-08-30

Human impact on the environment leads to the release of many pollutants that produce artificial compounds, which can have harmful effects on the body's endocrine system; these are known as endocrine disruptors (EDs). Nonylphenol (NP) is a chemical compound with a nonyl group that is attached to a phenol ring. NP-induced H 2 AX is a sensitive genotoxic biomarker for detecting possible DNA damage; it also causes male infertility and carcinogenesis. We attempt to comprehensively review all the available evidence about the different ways with descriptive mechanisms for explaining the possible DNA damage that is induced by NP. We systematically searched several databases, including PubMed, Scopus, Web of Science, and gray literature, such as Google Scholar by using medical subheading (MeSH) terms and various combinations of selected keywords from January 1970 to August 2017. The initial search identified 62,737 potentially eligible studies; of these studies, 33 were included according to the established inclusion criteria. Thirty-three selected studies, include the topics of animal model (n = 21), cell line (n = 6), human model (n = 4), microorganisms (n = 1), solid DNA (n = 1), infertility (n = 4), apoptosis (n = 6), and carcinogenesis (n = 3). This review highlighted the possible deleterious effects of NP on DNA damage through the ability to produce ROS/RNS. Finally, it is significant to observe caution at this stage with the continued use of environmental pollutants such as NP, which may induce DNA damage and apoptosis. Copyright © 2018 Elsevier Inc. All rights reserved.

Docking, synthesis and pharmacological activity of novel urea-derivatives designed as p38 MAPK inhibitors.

PubMed

de Oliveira Lopes, Raquel; Romeiro, Nelilma Correia; de Lima, Cleverton Kleiton F; Louback da Silva, Leandro; de Miranda, Ana Luisa Palhares; Nascimento, Paulo Gustavo B D; Cunha, Fernando Q; Barreiro, Eliezer J; Lima, Lídia Moreira

2012-08-01

p38 mitogen-activated protein kinase (p38 MAPK) is an important signal transducing enzyme involved in many cellular regulations, including signaling pathways, pain and inflammation. Several p38 MAPK inhibitors have been developed as drug candidates to treatment of autoimmune disorders, such as rheumatoid arthritis. In this paper we reported the docking, synthesis and pharmacological activity of novel urea-derivatives (4a-e) designed as p38 MAPK inhibitors. These derivatives presented good theoretical affinity to the target p38 MAPK, standing out compound 4e (LASSBio-998), which showed a better score value compared to the prototype GK-00687. This compound was able to reduce in vitro TNF-α production and was orally active in a hypernociceptive murine model sensible to p38 MAPK inhibitors. Otherwise, compound 4e presented a dose-dependent analgesic effect in a model of antigen (mBSA)-induced arthritis and anti-inflammatory profile in carrageenan induced paw edema, indicating its potential as a new antiarthritis prototype. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

[Influence of antitumor system rhenium-platinum on biochemical state of the liver].

PubMed

Ivchuk, V V; Polishko, T M; Golichenko, O A; Shtemenko, O V; Shtemenko, N I

2011-01-01

Influence of the antitumour rhenium-platinum system on biochemical liver characteristics in the model of tumor growth (Guerin carcinoma) was studied and possible hepatoprotective activity of rhenium cluster compounds when introducing them in different forms was shown, that was confirmed by decreasing of diagnostic enzymes activity in blood (aminotransferase--AST 6 times and ALT 5.6 times, lactatedehydrogenase 4.9 times, gamma-glutamyltranspeptidase 3.6 times) and normalization of morphological state of the liver cells. The hepatoprotective activity of the cluster rhenium compound with adamanthyl ligands was confirmed in the model of acute toxic hepatitis. Introduction of this compound led to reduction of the concentration of MDA in homogenates of liver tissue (2 times), and in blood plasma (3.8 times); to reduction of levels of diagnostic liver enzymes in blood--AST and ALT 5.8 and 5.5 times respectively in comparison with control group. Some aspects of the mechanism of hepatoprotection were discussed, that included the presence of conjugated systems around the quadrupol rhenium-rhenium bond and alkyl radicals with significant positive inductive effects.

Rapid Deposition of Oxidized Biogenic Compounds to a Temperate Forest

NASA Technical Reports Server (NTRS)

Nguyen, Tran B.; Crounse, John D.; Teng, Alex P.; St. Clair, Jason M.; Paulot, Fabien; Wolfe, Glenn M.; Wennberg, Paul O.

2015-01-01

We report fluxes and dry deposition velocities for 16 atmospheric compounds above a southeastern United States forest, including: hydrogen peroxide (H2O2), nitric acid (HNO3), hydrogen cyanide (HCN), hydroxymethyl hydroperoxide, peroxyacetic acid, organic hydroxy nitrates, and other multifunctional species derived from the oxidation of isoprene and monoterpenes. The data suggest that dry deposition is the dominant daytime sink for small, saturated oxygenates. Greater than 6 wt %C emitted as isoprene by the forest was returned by dry deposition of its oxidized products. Peroxides account for a large fraction of the oxidant flux, possibly eclipsing ozone in more pristine regions. The measured organic nitrates comprise a sizable portion (15%) of the oxidized nitrogen input into the canopy, with HNO3 making up the balance. We observe that water-soluble compounds (e.g., strong acids and hydroperoxides) deposit with low surface resistance whereas compounds with moderate solubility (e.g., organic nitrates and hydroxycarbonyls) or poor solubility (e.g., HCN) exhibited reduced uptake at the surface of plants. To first order, the relative deposition velocities of water-soluble compounds are constrained by their molecular diffusivity. From resistance modeling, we infer a substantial emission flux of formic acid at the canopy level (approx. 1 nmol m(exp.-2)·s(exp.-1)). GEOS-Chem, awidely used atmospheric chemical transport model, currently underestimates dry deposition for most molecules studied in this work. Reconciling GEOS-Chem deposition velocities with observations resulted in up to a 45% decrease in the simulated surface concentration of trace gases.

A topological substructural molecular design approach for predicting mutagenesis end-points of alpha, beta-unsaturated carbonyl compounds.

PubMed

Pérez-Garrido, Alfonso; Helguera, Aliuska Morales; López, Gabriel Caravaca; Cordeiro, M Natália D S; Escudero, Amalio Garrido

2010-01-31

Chemically reactive, alpha, beta-unsaturated carbonyl compounds are common environmental pollutants able to produce a wide range of adverse effects, including, e.g. mutagenicity. This toxic property can often be related to chemical structure, in particular to specific molecular substructures or fragments (alerts), which can then be used in specialized software or expert systems for predictive purposes. In the past, there have been many attempts to predict the mutagenicity of alpha, beta-unsaturated carbonyl compounds through quantitative structure activity relationships (QSAR) but considering only one exclusive endpoint: the Ames test. Besides, even though those studies give a comprehensive understanding of the phenomenon, they do not provide substructural information that could be useful forward improving expert systems based on structural alerts (SAs). This work reports an evaluation of classification models to probe the mutagenic activity of alpha, beta-unsaturated carbonyl compounds over two endpoints--the Ames and mammalian cell gene mutation tests--based on linear discriminant analysis along with the topological Substructure molecular design (TOPS-MODE) approach. The obtained results showed the better ability of the TOPS-MODE approach in flagging structural alerts for the mutagenicity of these compounds compared to the expert system TOXTREE. Thus, the application of the present QSAR models can aid toxicologists in risk assessment and in prioritizing testing, as well as in the improvement of expert systems, such as the TOXTREE software, where SAs are implemented. 2009 Elsevier Ireland Ltd. All rights reserved.

Rapid deposition of oxidized biogenic compounds to a temperate forest

PubMed Central

Nguyen, Tran B.; Crounse, John D.; Teng, Alex P.; St. Clair, Jason M.; Paulot, Fabien; Wolfe, Glenn M.; Wennberg, Paul O.

2015-01-01

We report fluxes and dry deposition velocities for 16 atmospheric compounds above a southeastern United States forest, including: hydrogen peroxide (H2O2), nitric acid (HNO3), hydrogen cyanide (HCN), hydroxymethyl hydroperoxide, peroxyacetic acid, organic hydroxy nitrates, and other multifunctional species derived from the oxidation of isoprene and monoterpenes. The data suggest that dry deposition is the dominant daytime sink for small, saturated oxygenates. Greater than 6 wt %C emitted as isoprene by the forest was returned by dry deposition of its oxidized products. Peroxides account for a large fraction of the oxidant flux, possibly eclipsing ozone in more pristine regions. The measured organic nitrates comprise a sizable portion (15%) of the oxidized nitrogen input into the canopy, with HNO3 making up the balance. We observe that water-soluble compounds (e.g., strong acids and hydroperoxides) deposit with low surface resistance whereas compounds with moderate solubility (e.g., organic nitrates and hydroxycarbonyls) or poor solubility (e.g., HCN) exhibited reduced uptake at the surface of plants. To first order, the relative deposition velocities of water-soluble compounds are constrained by their molecular diffusivity. From resistance modeling, we infer a substantial emission flux of formic acid at the canopy level (∼1 nmol m−2⋅s−1). GEOS−Chem, a widely used atmospheric chemical transport model, currently underestimates dry deposition for most molecules studied in this work. Reconciling GEOS−Chem deposition velocities with observations resulted in up to a 45% decrease in the simulated surface concentration of trace gases. PMID:25605913

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

PubMed

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

PubMed

Ren, Biye

2003-01-01

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

Chemical Characterization of Beer Aging Products Derived from Hard Resin Components in Hops (Humulus lupulus L.).

PubMed

Taniguchi, Yoshimasa; Yamada, Makiko; Taniguchi, Harumi; Matsukura, Yasuko; Shindo, Kazutoshi

2015-11-25

The bitter taste of beer originates from resins in hops (Humulus lupulus L.), which are classified into two subtypes (soft and hard). Whereas the nature and reactivity of soft-resin-derived compounds, such as α-, β-, and iso-α-acids, are well studied, there is only a little information on the compounds in hard resin. For this work, hard resin was prepared from stored hops and investigated for its compositional changes in an experimental model of beer aging. The hard resin contained a series of α-acid oxides. Among them, 4'-hydroxyallohumulinones were unstable under beer storage conditions, and their transformation induced primary compositional changes of the hard resin during beer aging. The chemical structures of the products, including novel polycyclic compounds scorpiohumulinols A and B and dicyclohumulinols A and B, were determined by HRMS and NMR analyses. These compounds were proposed to be produced via proton-catalyzed cyclization reactions of 4'-hydroxyallohumulinones. Furthermore, they were more stable than their precursor 4'-hydroxyallohumulinones during prolonged storage periods.

Separation-oriented derivatization of native fluorescent compounds through fluorous labeling followed by liquid chromatography with fluorous-phase.

PubMed

Sakaguchi, Yohei; Yoshida, Hideyuki; Todoroki, Kenichiro; Nohta, Hitoshi; Yamaguchi, Masatoshi

2009-06-15

We have developed a new and simple method based on "fluorous derivatization" for LC of native fluorescent compounds. This method involves the use of a column with a fluorous stationary phase. Native fluorescent analytes with target functional groups are precolumn derivatized with a nonfluorescent fluorous tag, and the fluorous-labeled analytes are retained in the column, whereas underivatized substances are not. Only the retained fluorescent analytes are detected fluorometrically at appropriate retention times, and retained substrates without fluorophores are not detected. In this study, biologically important carboxylic acids (homovanillic acid, vanillylmandelic acid, and 5-hydroxyindoleacetic acid) and drugs (naproxen, felbinac, flurbiprofen, and etodolac) were used as model native fluorescent compounds. Experimental results indicate that the fluorous-phase column can selectively retain fluorous compounds including fluorous-labeled analytes on the basis of fluorous separation. We believe that separation-oriented derivatization presented here is the first step toward the introduction of fluorous derivatization in quantitative LC analysis.

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

Eskenazi, B.; Kimmel, G.

This summary report focuses on current studies on reproductive effects reported at the workshop on Perinatal Exposure to Dioxin-like Compounds and supporting data noted in the discussion. Recent laboratory studies have suggested that altered development (e.g., low birth weight, spontaneous abortion, congenital malformation) and reproductive health (e.g., fertility, sex organ development, reproductive behavior) may be among the most sensitive end points when examining the effects of dioxin-like compounds. Thus, future research should target the reproductive health of both males and females exposed postnatally and prenatally. Studies in humans are needed and are on-going. In animal models, postnatal exposure to dioxinmore » or dioxinlike compounds has been associated with abnormal spermatogenesis and abnormal testicular morphology and size in males and with reduced fertility and endometriosis in females. In utero exposure may also produce profound reproductive consequences in both males and females including delays in sexual maturation, abnormalities in development of sexual organs, and abnormal sexual behavior. The mechanism by which dioxin-like compounds cause reproductive effects is not well delineated. 13 refs.« less

Investigation of atmospheric pressure capillary non-thermal plasmas and their applications to the degradation of volatile organic compounds

NASA Astrophysics Data System (ADS)

Yin, Shu-Min

Atmospheric pressure capillary non-thermal plasma (AP-CNTP) has been investigated as a potential technology far the removal of volatile organic compounds (VOCs) in Advanced Life Support Systems (ALS). AP-CNTP is a destructive technology far the removal of VOCs from air streams by active plasma species, such as electrons, ions, and excited molecules. Complete VOC destruction ideally results in the formation of water, carbon dioxide (CO2), and other by-product's may also form, including ozone (O3), nitrous oxide (N2O), nitrogen dioxide (NO2), and decomposed hydrocarbons. Several organic compounds, such as BTEX, ethylene, n-heptane, isooctane, methanol and NH3, were tested in an AP-CNTP system. Parametric experiments were carried out by varying plasma discharge power, flowrates, and initial concentrations. The degradation efficiency varied depending on the chemical nature of the compounds. A plasmochemical kinetic model was derived for toluene, ethylbenzene, and m-xylene and n-heptane.

Environmental estrogenic compounds and the induction of hepatic vitellogenin synthesis using cultured goldfish hepatocytes

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

Yao, Z.; Kraak, G.J. Van Der; Squires, E.J.

1995-12-31

A series of experiments were conducted to evaluate the estrogenic activity of some environmental contaminants including the {beta}-sitosterol, nonylphenol (major components of pulp mill effluent) and 3-trifluoromethyl-4-nitrophenol (TFM, a lampricide widely used in the Great Lakes), using the goldfish (Carassius auratus L.) as a model species. The in vivo exposure studies have demonstrated that all three compounds tested possess various degrees of estrogenic activity as measured by increased plasma vitellogenin (VTG) production in both the male and female fish. To understand how these compounds induce hepatic VTG synthesis and determine their potency of VTG induction, an in vitro hepatocyte culturemore » system of goldfish was established and the induction of VTG synthesis by these compounds in the cultured hepatocytes was studied. The concentration of VTG in the plasma and in the cell culture medium was determined with a enzyme-linked immunosorbent assay. Both in vivo and in vitro studies suggest that {beta}-sitosterol has the highest estrogenic activity of VTG induction.« less

Induction of quinone reductase (QR) by withanolides isolated from Physalis pubescens L. (Solanaceae).

PubMed

Ji, Long; Yuan, Yonglei; Ma, Zhongjun; Chen, Zhe; Gan, Lishe; Ma, Xiaoqiong; Huang, Dongsheng

2013-09-01

In the present study, it was demonstrated that the dichloromethane extract of Physalis pubescens L. (DEPP) had weak potential quinone reductase (QR) inducing activity, but an UPLC-ESI-MS method with glutathione (GSH) as the substrate revealed that the DEPP had electrophiles (with an α,β-unsaturated ketone moiety). These electrophiles could induce quinone reductase (QR) activity, which might be attributed to the modification of the highly reactive cysteine residues in Keap1. Herein, four withanolides, including three new compounds physapubescin B (2), physapubescin C (3), physapubescin D (4), together with one known steroidal compound physapubescin (1) were isolated. Structures of these compounds were determined by spectroscopic analysis and that of physapubescin C (3) was confirmed by a combination of molecular modeling and quantum chemical DFT-GIAO calculations. Evaluation of the QR inducing activities of all withanolides indicated potent activities of compounds 1 and 2, which had a common α,β-unsaturated ketone moiety. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nerve agent analogues that produce authentic soman, sarin, tabun, and cyclohexyl methylphosphonate-modified human butyrylcholinesterase.

PubMed

Gilley, Cynthia; MacDonald, Mary; Nachon, Florian; Schopfer, Lawrence M; Zhang, Jun; Cashman, John R; Lockridge, Oksana

2009-10-01

The goal was to test 14 nerve agent model compounds of soman, sarin, tabun, and cyclohexyl methylphosphonofluoridate (GF) for their suitability as substitutes for true nerve agents. We wanted to know whether the model compounds would form the identical covalent adduct with human butyrylcholinesterase that is produced by reaction with true nerve agents. Nerve agent model compounds containing thiocholine or thiomethyl in place of fluorine or cyanide were synthesized as Sp and Rp stereoisomers. Purified human butyrylcholinesterase was treated with a 45-fold molar excess of nerve agent analogue at pH 7.4 for 17 h at 21 degrees C. The protein was denatured by boiling and was digested with trypsin. Aged and nonaged active site peptide adducts were quantified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry of the tryptic digest mixture. The active site peptides were isolated by HPLC and analyzed by MALDI-TOF-TOF mass spectrometry. Serine 198 of butyrylcholinesterase was covalently modified by all 14 compounds. Thiocholine was the leaving group in all compounds that had thiocholine in place of fluorine or cyanide. Thiomethyl was the leaving group in the GF thiomethyl compounds. However, sarin thiomethyl compounds released either thiomethyl or isopropyl, while soman thiomethyl compounds released either thiomethyl or pinacolyl. Thiocholine compounds reacted more rapidly with butyrylcholinesterase than thiomethyl compounds. Labeling with the model compounds resulted in aged adducts that had lost the O-alkyl group (O-ethyl for tabun, O-cyclohexyl for GF, isopropyl for sarin, and pinacolyl for soman) in addition to the thiocholine or thiomethyl group. The nerve agent model compounds containing thiocholine and the GF thiomethyl analogue were found to be suitable substitutes for true soman, sarin, tabun, and GF in terms of the adduct that they produced with human butyrylcholinesterase. However, the soman and sarin thiomethyl compounds yielded two types of adducts, one of which was thiomethyl phosphonate, a modification not found after treatment with authentic soman and sarin.

Modelling biogas production of solid waste: application of the BGP model to a synthetic landfill

NASA Astrophysics Data System (ADS)

Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco

2013-04-01

Production of biogas as a result of the decomposition of organic matter included on solid waste landfills is still an issue to be understood. Reports on this matter are rarely included on the engineering construction projects of solid waste landfills despite it can be an issue of critical importance while operating the landfill and after its closure. This paper presents an application of BGP (Bio-Gas-Production) model to a synthetic landfill. The evolution in time of the concentrations of the different chemical compounds of biogas is studied. Results obtained show the impact on the air quality of different management alternatives which are usually performed in real landfills.

Modeling the surface tension of complex, reactive organic-inorganic mixtures

NASA Astrophysics Data System (ADS)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. F.

2013-01-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as cloud condensation nuclei (CCN) ability. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well-described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling fits and goodness of fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

Toxicogenomics to Evaluate Endocrine Disrupting Effects of Environmental Chemicals Using the Zebrafish Model

PubMed Central

Caballero-Gallardo, Karina; Olivero-Verbel, Jesus; Freeman, Jennifer L.

2016-01-01

The extent of our knowledge on the number of chemical compounds related to anthropogenic activities that can cause damage to the environment and to organisms is increasing. Endocrine disrupting chemicals (EDCs) are one group of potentially hazardous substances that include natural and synthetic chemicals and have the ability to mimic endogenous hormones, interfering with their biosynthesis, metabolism, and normal functions. Adverse effects associated with EDC exposure have been documented in aquatic biota and there is widespread interest in the characterization and understanding of their modes of action. Fish are considered one of the primary risk organisms for EDCs. Zebrafish (Danio rerio) are increasingly used as an animal model to study the effects of endocrine disruptors, due to their advantages compared to other model organisms. One approach to assess the toxicity of a compound is to identify those patterns of gene expression found in a tissue or organ exposed to particular classes of chemicals, through new technologies in genomics (toxicogenomics), such as microarrays or whole-genome sequencing. Application of these technologies permit the quantitative analysis of thousands of gene expression changes simultaneously in a single experiment and offer the opportunity to use transcript profiling as a tool to predict toxic outcomes of exposure to particular compounds. The application of toxicogenomic tools for identification of chemicals with endocrine disrupting capacity using the zebrafish model system is reviewed. PMID:28217008

Simplified jet-A kinetic mechanism for combustor application

NASA Technical Reports Server (NTRS)

Lee, Chi-Ming; Kundu, Krishna; Ghorashi, Bahman

1993-01-01

Successful modeling of combustion and emissions in gas turbine engine combustors requires an adequate description of the reaction mechanism. For hydrocarbon oxidation, detailed mechanisms are only available for the simplest types of hydrocarbons such as methane, ethane, acetylene, and propane. These detailed mechanisms contain a large number of chemical species participating simultaneously in many elementary kinetic steps. Current computational fluid dynamic (CFD) models must include fuel vaporization, fuel-air mixing, chemical reactions, and complicated boundary geometries. To simulate these conditions a very sophisticated computer model is required, which requires large computer memory capacity and long run times. Therefore, gas turbine combustion modeling has frequently been simplified by using global reaction mechanisms, which can predict only the quantities of interest: heat release rates, flame temperature, and emissions. Jet fuels are wide-boiling-range hydrocarbons with ranges extending through those of gasoline and kerosene. These fuels are chemically complex, often containing more than 300 components. Jet fuel typically can be characterized as containing 70 vol pct paraffin compounds and 25 vol pct aromatic compounds. A five-step Jet-A fuel mechanism which involves pyrolysis and subsequent oxidation of paraffin and aromatic compounds is presented here. This mechanism is verified by comparing with Jet-A fuel ignition delay time experimental data, and species concentrations obtained from flametube experiments. This five-step mechanism appears to be better than the current one- and two-step mechanisms.

Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines.

PubMed

Pozo-Bayón, Maria Angeles; Andujar-Ortiz, Inmaculada; Alcaide-Hidalgo, Juan María; Martín-Alvarez, Pedro J; Moreno-Arribas, M Victoria

2009-11-25

The characterization of commercial enological inactive dry yeast (IDY) with different applications in wine production has been carried out. This study was based on the yeast's ability to release soluble compounds (high molecular weight nitrogen, free amino nitrogen, peptidic nitrogen, free amino acids, and polysaccharides) into model wines and on its behavior toward the volatility of seven wine aroma compounds. Important differences in soluble compounds released into the model wines supplemented with commercial IDY were found, with the free amino acids being among the most released. The volatility of most of the aroma compounds was affected by the addition of IDY preparations at a concentration usually employed during winemaking. The extent of this effect was dependent on the physicochemical characteristics of the aroma compound and on the length of time the IDY preparations remained in contact with the model wines. Whereas shorter contact times (2, 4, and 6 days) mainly promoted a "salting-out" effect, longer exposure (9 and 13 days) provoked a retention effect, with the consequent reduction of aroma compounds in the headspace. The use of different commercial preparations also promoted different effects toward the aroma compounds that may be at least in part due to differences in their ability to release soluble compounds of yeast origin into the wines.

Development of Monopole Interaction Models for Ionic Compounds. Part I: Estimation of Aqueous Henry’s Law Constants for Ions and Gas Phase pKa Values for Acidic Compounds

EPA Science Inventory

The SPARC (SPARC Performs Automated Reasoning in Chemistry) physicochemical mechanistic models for neutral compounds have been extended to estimate Henry’s Law Constant (HLC) for charged species by incorporating ionic electrostatic interaction models. Combinations of absolute aq...

Stereoregularity of poly (lactic acid) and their model compounds as studied by NMR and quantum chemical calculations

USDA-ARS?s Scientific Manuscript database

In order to understand the origin of the tacticity splitting in the NMR spectrum of poly(lactic acid), monomer model compound and dimer model compounds (both isotactic and syndiotactic) were synthesized and their 1H and 13C NMR chemical shifts observed. Two energetically stable conformations were o...

Encapsulation of a model compound in pectin delays its release from a biobased polymeric material

USDA-ARS?s Scientific Manuscript database

A model compound was encapsulated in pectin and then extruded with thermoplastic starch to form a composite. The intended product was a food-contact tray made of biobased polymers infused with an anti-microbial agent; however, caffeine was used as the model compound in the preliminary work. The mode...

Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

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

Choi, Yong S.; Singh, Rahul; Zhang, Jing

2016-01-01

Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation.more » The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.« less

Diphenylurea derivatives for combating methicillin- and vancomycin-resistant Staphylococcus aureus.

PubMed

Eissa, Ibrahim H; Mohammad, Haroon; Qassem, Omar A; Younis, Waleed; Abdelghany, Tamer M; Elshafeey, Ahmed; Abd Rabo Moustafa, Mahmoud M; Seleem, Mohamed N; Mayhoub, Abdelrahman S

2017-04-21

A new class of diphenylurea was identified as a novel antibacterial scaffold with an antibacterial spectrum that includes highly resistant staphylococcal isolates, namely methicillin- and vancomycin-resistant Staphylococcus aureus (MRSA & VRSA). Starting with a lead compound 3 that carries an aminoguanidine functionality from one side and a n-butyl moiety on the other ring, several analogues were prepared. Considering the pharmacokinetic parameters as a key factor in structural optimization, the structure-activity-relationships (SARs) at the lipophilic side chain were rigorously examined leading to the discovery of the cycloheptyloxyl analogue 21n as a potential drug-candidate. This compound has several notable advantages over vancomycin and linezolid including rapid killing kinetics against MRSA and the ability to target and reduce the burden of MRSA harboring inside immune cells (macrophages). Furthermore, the potent anti-MRSA activity of 21n was confirmed in vivo using a Caenorhabditis elegans animal model. The present study provides a foundation for further development of diphenylurea compounds as potential therapeutic agents to address the burgeoning challenge of bacterial resistance to antibiotics. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

The Chemically Inducible Plant Cytochrome P450 CYP76B1 Actively Metabolizes Phenylureas and Other Xenobiotics1

PubMed Central

Robineau, Tiburce; Batard, Yannick; Nedelkina, Svetlana; Cabello-Hurtado, Francisco; LeRet, Monique; Sorokine, Odile; Didierjean, Luc; Werck-Reichhart, Danièle

1998-01-01

Cytochrome P450s (P450s) constitute one of the major classes of enzymes that are responsible for detoxification of exogenous molecules both in animals and plants. On the basis of its inducibility by exogenous chemicals, we recently isolated a new plant P450, CYP76B1, from Jerusalem artichoke (Helianthus tuberosus) and showed that it was capable of dealkylating a model xenobiotic compound, 7-ethoxycoumarin. In the present paper we show that CYP76B1 is more strongly induced by foreign compounds than other P450s isolated from the same plant, and metabolizes with high efficiency a wide range of xenobiotics, including alkoxycoumarins, alkoxyresorufins, and several herbicides of the class of phenylureas. CYP76B1 catalyzes the double N-dealkylation of phenylureas with turnover rates comparable to those reported for physiological substrates and produces nonphytotoxic compounds. Potential uses for CYP76B1 thus include control of herbicide tolerance and selectivity, as well as soil and groundwater bioremediation. PMID:9808750

Cytochrome P450 humanised mice

PubMed Central

2004-01-01

Humans are exposed to countless foreign compounds, typically referred to as xenobiotics. These can include clinically used drugs, environmental pollutants, food additives, pesticides, herbicides and even natural plant compounds. Xenobiotics are metabolised primarily in the liver, but also in the gut and other organs, to derivatives that are more easily eliminated from the body. In some cases, however, a compound is converted to an electrophile that can cause cell toxicity and transformation leading to cancer. Among the most important xenobiotic-metabolising enzymes are the cytochromes P450 (P450s). These enzymes represent a superfamily of multiple forms that exhibit marked species differences in their expression and catalytic activities. To predict how humans will metabolise xenobiotics, including drugs, human liver extracts and recombinant P450s have been used. New humanised mouse models are being developed which will be of great value in the study of drug metabolism, pharmacokinetics and pharmacodynamics in vivo, and in carrying out human risk assessment of xenobiotics. Humanised mice expressing CYP2D6 and CYP3A4, two major drug-metabolising P450s, have revealed the feasibility of this approach. PMID:15588489

Treating SCA1 Mice with Water-Soluble Compounds to Non-Specifically Boost Mitochondrial Function.

PubMed

Ferro, Austin; Carbone, Emily; Marzouk, Evan; Siegel, Asher; Nguyen, Donna; Polley, Kailen; Hartman, Jessilyn; Frederick, Kimberley; Ives, Stephen; Lagalwar, Sarita

2017-01-22

Mitochondrial dysfunction plays a significant role in the aging process and in neurodegenerative diseases including several hereditary spinocerebellar ataxias and other movement disorders marked by progressive degeneration of the cerebellum. The goal of this protocol is to assess mitochondrial dysfunction in Spinocerebellar ataxia type 1 (SCA1) and assess the efficacy of pharmacological targeting of metabolic respiration via the water-soluble compound succinic acid to slow disease progression. This approach is applicable to other cerebellar diseases and can be adapted to a host of water-soluble therapies. Ex vivo analysis of mitochondrial respiration is used to detect and quantify disease-related changes in mitochondrial function. With genetic evidence (unpublished data) and proteomic evidence of mitochondrial dysfunction in the SCA1 mouse model, we evaluate the efficacy of treatment with the water-soluble metabolic booster succinic acid by dissolving this compound directly into the home cage drinking water. The ability of the drug to pass the blood brain barrier can be deduced using high performance liquid chromatography (HPLC). The efficacy of these compounds can then be tested using multiple behavioral paradigms including the accelerating rotarod, balance beam test and footprint analysis. Cytoarchitectural integrity of the cerebellum can be assessed using immunofluorescence assays that detect Purkinje cell nuclei and Purkinje cell dendrites and soma. These methods are robust techniques for determining mitochondrial dysfunction and the efficacy of treatment with water-soluble compounds in cerebellar neurodegenerative disease.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

A post-Galileo view of Io's interior

USGS Publications Warehouse

Keszthelyi, L.; Jaeger, W.L.; Turtle, E.P.; Milazzo, M.; Radebaugh, J.

2004-01-01

We present a self-consistent model for the interior of Io, taking the recent Galileo data into account. In this model, Io has a completely molten core, substantially molten mantle, and a very cold lithosphere. Heat from magmatic activity can mobilize volatile compounds such as SO2 in the lithosphere, and the movement of such cryogenic fluids may be important in the formation of surface features including sapping scarps and paterae. ?? Published by Elsevier Inc.

Development of a semi-quantitative risk assessment model for evaluating environmental threat posed by the three first EU watch-list pharmaceuticals to urban wastewater treatment plants: An Irish case study.

PubMed

Tahar, Alexandre; Tiedeken, Erin Jo; Clifford, Eoghan; Cummins, Enda; Rowan, Neil

2017-12-15

Contamination of receiving waters with pharmaceutical compounds is of pressing concern. This constitutes the first study to report on the development of a semi-quantitative risk assessment (RA) model for evaluating the environmental threat posed by three EU watch list pharmaceutical compounds namely, diclofenac, 17-beta-estradiol and 17-alpha-ethinylestradiol, to aquatic ecosystems using Irish data as a case study. This RA model adopts the Irish Environmental Protection Agency Source-Pathway-Receptor concept to define relevant parameters for calculating low, medium or high risk score for each agglomeration of wastewater treatment plant (WWTP), which include catchment, treatments, operational and management factors. This RA model may potentially be used on a national scale to (i) identify WWTPs that pose a particular risk as regards releasing disproportionally high levels of these pharmaceutical compounds, and (ii) help identify priority locations for introducing or upgrading control measures (e.g. tertiary treatment, source reduction). To assess risks for these substances of emerging concern, the model was applied to 16 urban WWTPs located in different regions in Ireland that were scored for the three different compounds and ranked as low, medium or high risk. As a validation proxy, this case study used limited monitoring data recorded at some these plants receiving waters. It is envisaged that this semi-quantitative RA approach may aid other EU countries investigate and screen for potential risks where limited measured or predicted environmental pollutant concentrations and/or hydrological data are available. This model is semi-quantitative, as other factors such as influence of climate change and drug usage or prescription data will need to be considered in a future point for estimating and predicting risks. Copyright © 2017 Elsevier B.V. All rights reserved.

Inferring the unobserved chemical state of the atmosphere: idealized data assimilation experiments

NASA Astrophysics Data System (ADS)

Knote, C. J.; Barré, J.; Eckl, M.; Hornbrook, R. S.; Wiedinmyer, C.; Emmons, L. K.; Orlando, J. J.; Tyndall, G. S.; Arellano, A. F.

2015-12-01

Chemical data assimilation in numerical models of the atmosphere is a venture into uncharted territory, into a world populated by a vast zoo of chemical compounds with strongly non-linear interactions. Commonly assimilated observations exist for only a selected few of those key gas phase compounds (CO, O3, NO2), and assimilating those in models assuming linearity begs the question of: To what extent we can infer the remainder to create a new state of the atmosphere that is chemically sound and optimal? In our work we present the first systematic investigation of sensitivities that exist between chemical compounds under varying ambient conditions in order to inform scientists on the potential pitfalls when assimilating single/few chemical compounds into complex 3D chemistry transport models. In order to do this, we developed a box-modeling tool (BOXMOX) based on the Kinetic PreProcessor (KPP, http://people.cs.vt.edu/~asandu/Software/Kpp/) in which we can conduct simulations with a suite of 'mechanisms', sets of differential equations describing atmospheric photochemistry. The box modeling approach allows us to sample a large variety of atmospheric conditions (urban, rural, biogenically dominated, biomass burning plumes) to capture the range of chemical conditions that typically exist in the atmosphere. Included in our suite are 'lumped' mechanisms typically used in regional and global chemistry transport models (MOZART, RACM, RADM2, SAPRC99, CB05, CBMZ) as well as the Master Chemical Mechanism (MCM, U. Leeds). We will use an Observing System Simulation Experiment approach with the MCM prediction as 'nature' or 'true' state, assimilating idealized synthetic observations (from MCM) into the different ‚lumped' mechanisms under various environments. Two approaches to estimate the sensitivity of the chemical system will be compared: 1) adjoint: using Jacobians computed by KPP and 2) ensemble: by perturbing emissions, temperature, photolysis rates, entrainment, etc., in order to create gain matrices to infer the unobserved part of the photochemical system.

An efficient descriptor model for designing materials for solar cells

NASA Astrophysics Data System (ADS)

Alharbi, Fahhad H.; Rashkeev, Sergey N.; El-Mellouhi, Fedwa; Lüthi, Hans P.; Tabet, Nouar; Kais, Sabre

2015-11-01

An efficient descriptor model for fast screening of potential materials for solar cell applications is presented. It works for both excitonic and non-excitonic solar cells materials, and in addition to the energy gap it includes the absorption spectrum (α(E)) of the material. The charge transport properties of the explored materials are modelled using the characteristic diffusion length (Ld) determined for the respective family of compounds. The presented model surpasses the widely used Scharber model developed for bulk heterojunction solar cells. Using published experimental data, we show that the presented model is more accurate in predicting the achievable efficiencies. To model both excitonic and non-excitonic systems, two different sets of parameters are used to account for the different modes of operation. The analysis of the presented descriptor model clearly shows the benefit of including α(E) and Ld in view of improved screening results.

Predicting trace organic compound attenuation by ozone oxidation: Development of indicator and surrogate models.

PubMed

Park, Minkyu; Anumol, Tarun; Daniels, Kevin D; Wu, Shimin; Ziska, Austin D; Snyder, Shane A

2017-08-01

Ozone oxidation has been demonstrated to be an effective treatment process for the attenuation of trace organic compounds (TOrCs); however, predicting TOrC attenuation by ozone processes is challenging in wastewaters. Since ozone is rapidly consumed, determining the exposure times of ozone and hydroxyl radical proves to be difficult. As direct potable reuse schemes continue to gain traction, there is an increasing need for the development of real-time monitoring strategies for TOrC abatement in ozone oxidation processes. Hence, this study is primarily aimed at developing indicator and surrogate models for the prediction of TOrC attenuation by ozone oxidation. To this end, the second-order kinetic equations with a second-phase R ct value (ratio of hydroxyl radical exposure to molecular ozone exposure) were used to calculate comparative kinetics of TOrC attenuation and the reduction of indicator and spectroscopic surrogate parameters, including UV absorbance at 254 nm (UVA 254 ) and total fluorescence (TF). The developed indicator model using meprobamate as an indicator compound and the surrogate models with UVA 254 and TF exhibited good predictive power for the attenuation of 13 kinetically distinct TOrCs in five filtered and unfiltered wastewater effluents (R 2 values > 0.8). This study is intended to help provide a guideline for the implementation of indicator/surrogate models for real-time monitoring of TOrC abatement with ozone processes and integrate them into a regulatory framework in water reuse. Copyright © 2017 Elsevier Ltd. All rights reserved.

Long-term transport behavior of psychoactive compounds in sewage-affected groundwater

NASA Astrophysics Data System (ADS)

Nham, Hang Thuy Thi; Greskowiak, Janek; Hamann, Enrico; Meffe, Raffaella; Hass, Ulrike; Massmann, Gudrun

2016-11-01

The present study provides a model-based characterization of the long-term transport behavior of five psychoactive compounds (meprobamate, pyrithyldione, primidone, phenobarbital and phenylethylmalonamide) introduced into groundwater via sewage irrigation in Berlin, Germany. Compounds are still present in the groundwater despite the sewage farm closure in the year 1980. Due to the limited information on (i) compound concentrations in the source water and (ii) substance properties, a total of 180 cross-sectional model realizations for each compound were carried out, covering a large range of possible parameter combinations. Results were compared with the present-day contamination patterns in the aquifer and the most likely scenarios were identified based on a number of model performance criteria. The simulation results show that (i) compounds are highly persistent under the present field conditions, and (ii) sorption is insignificant. Thus, back-diffusion from low permeability zones appears as the main reason for the compound retardation.

A Comparison of Parameterizations of Secondary Organic Aerosol Production: Global Budget and Spatiotemporal Variability

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S.

2014-12-01

Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols.

Roles of small laccases from Streptomyces in lignin degradation.

PubMed

Majumdar, Sudipta; Lukk, Tiit; Solbiati, Jose O; Bauer, Stefan; Nair, Satish K; Cronan, John E; Gerlt, John A

2014-06-24

Laccases (EC 1.10.3.2) are multicopper oxidases that can oxidize a range of substrates, including phenols, aromatic amines, and nonphenolic substrates. To investigate the involvement of the small Streptomyces laccases in lignin degradation, we generated acid-precipitable polymeric lignin obtained in the presence of wild-type Streptomyces coelicolor A3(2) (SCWT) and its laccase-less mutant (SCΔLAC) in the presence of Miscanthus x giganteus lignocellulose. The results showed that strain SCΔLAC was inefficient in degrading lignin compared to strain SCWT, thereby supporting the importance of laccase for lignin degradation by S. coelicolor A3(2). We also studied the lignin degradation activity of laccases from S. coelicolor A3(2), Streptomyces lividans TK24, Streptomyces viridosporus T7A, and Amycolatopsis sp. 75iv2 using both lignin model compounds and ethanosolv lignin. All four laccases degraded a phenolic model compound (LM-OH) but were able to oxidize a nonphenolic model compound only in the presence of redox mediators. Their activities are highest at pH 8.0 with a low krel/Kapp for LM-OH, suggesting that the enzymes’ natural substrates must be different in shape or chemical nature. Crystal structures of the laccases from S. viridosporus T7A (SVLAC) and Amycolatopsis sp. 75iv2 were determined both with and without bound substrate. This is the first report of a crystal structure for any laccase bound to a nonphenolic β-O-4 lignin model compound. An additional zinc metal binding site in SVLAC was also identified. The ability to oxidize and/or rearrange ethanosolv lignin provides further evidence of the utility of laccase activity for lignin degradation and/or modification.

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

77 FR 76419 - Health and Safety Data Reporting; Addition of Certain Chemicals; Withdrawal of Final Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-28

... importers) of cadmium or cadmium compounds, including as part of an article, that have been, or are... (including importer) of cadmium or cadmium compounds, including as part of an article, that have been, or are... reporting rule that would have required manufacturers (including importers) of cadmium or cadmium compounds...

Decomposition of food lipids by ionizing radiation

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

Nawar, W.W.

1973-01-01

A number of animal and vegetable fats as well as model systems of triglycerides were used in a study to examine the effects of irradiation on the lipid fraction of foods. More than one hundred compounds were identified as radiolytic products. These include a series of hydrocarbons, aldehydes, esters, free acids, ethane- and propanediol diesters, propenediol diesters, diglycerides, triglycerides, ketones, glyceryl ether diesters, and 2-alkyl cyclobutanones. Reaction mechanism are proposed to explain the formation of the decomposition products. Bascially, these compounds result via the formation of free radicals according to preferential cleavages in the vicinity of the carbonyl groups. Sincemore » some of these compounds are unique to radiation effects, a method was developed to detect irradiation treatment in foods. Variables affecting the radiolytic pattern are discussed, and a comparison between thermolytic and radiolytic effects is presented. (GE)« less

Utilizing Ion-Mobility Data to Estimate Molecular Masses

NASA Technical Reports Server (NTRS)

Duong, Tuan; Kanik, Isik

2008-01-01

A method is being developed for utilizing readings of an ion-mobility spectrometer (IMS) to estimate molecular masses of ions that have passed through the spectrometer. The method involves the use of (1) some feature-based descriptors of structures of molecules of interest and (2) reduced ion mobilities calculated from IMS readings as inputs to (3) a neural network. This development is part of a larger effort to enable the use of IMSs as relatively inexpensive, robust, lightweight instruments to identify, via molecular masses, individual compounds or groups of compounds (especially organic compounds) that may be present in specific environments or samples. Potential applications include detection of organic molecules as signs of life on remote planets, modeling and detection of biochemicals of interest in the pharmaceutical and agricultural industries, and detection of chemical and biological hazards in industrial, homeland-security, and industrial settings.

Strategies, linkers and coordination polymers for high-performance sorbents

DOEpatents

Matzger, Adam J.; Wong-Foy, Antek G.; Lebel, Oliver

2015-09-15

A linking ligand compound includes three bidentate chemical moieties distributed about a central chemical moiety. Another linking ligand compound includes a bidentate linking ligand and a monodentate chemical moiety. Coordination polymers include a plurality of metal clusters linked together by residues of the linking ligand compounds.

Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

PubMed

Chen, Hongming; Carlsson, Lars; Eriksson, Mats; Varkonyi, Peter; Norinder, Ulf; Nilsson, Ingemar

2013-06-24

A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

PubMed Central

Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

2015-01-01

Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

Design, synthesis, and protein crystallography of biaryltriazoles as potent tautomerase inhibitors of macrophage migration inhibitory factor.

PubMed

Dziedzic, Pawel; Cisneros, José A; Robertson, Michael J; Hare, Alissa A; Danford, Nadia E; Baxter, Richard H G; Jorgensen, William L

2015-03-04

Optimization is reported for biaryltriazoles as inhibitors of the tautomerase activity of human macrophage migration inhibitory factor (MIF), a proinflammatory cytokine associated with numerous inflammatory diseases and cancer. A combined approach was taken featuring organic synthesis, enzymatic assaying, crystallography, and modeling including free-energy perturbation (FEP) calculations. X-ray crystal structures for 3a and 3b bound to MIF are reported and provided a basis for the modeling efforts. The accommodation of the inhibitors in the binding site is striking with multiple hydrogen bonds and aryl-aryl interactions. Additional modeling encouraged pursuit of 5-phenoxyquinolinyl analogues, which led to the very potent compound 3s. Activity was further enhanced by addition of a fluorine atom adjacent to the phenolic hydroxyl group as in 3w, 3z, 3aa, and 3bb to strengthen a key hydrogen bond. It is also shown that physical properties of the compounds can be modulated by variation of solvent-exposed substituents. Several of the compounds are likely the most potent known MIF tautomerase inhibitors; the most active ones are more than 1000-fold more active than the well-studied (R)-ISO-1 and more than 200-fold more active than the chromen-4-one Orita-13.

QSAR and 3D-QSAR studies applied to compounds with anticonvulsant activity.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Estrada, Mario R

2015-01-01

Quantitative structure-activity relationships (QSAR and 3D-QSAR) have been applied in the last decade to obtain a reliable statistical model for the prediction of the anticonvulsant activities of new chemical entities. However, despite the large amount of information on QSAR, no recent review has published and discussed this data in detail. In this review, the authors provide a detailed discussion of QSAR studies that have been applied to compounds with anticonvulsant activity published between the years 2003 and 2013. They also evaluate the mathematical approaches and the main software used to develop the QSAR and 3D-QSAR model. QSAR methodologies continue to attract the attention of researchers and provide valuable information for the development of new potentially active compounds including those with anticonvulsant activity. This has been helped in part by improvements in the size and performance of computers; the development of specific software and the development of novel molecular descriptors, which have given rise to new and more predictive QSAR models. The extensive development of descriptors, and the way by which descriptor values are derived, have allowed the evolution of the QSAR methods. This evolution could strengthen the QSAR methods as an important tool in research and development of new and more potent anticonvulsant agents.

Design, Synthesis, and Protein Crystallography of Biaryltriazoles as Potent Tautomerase Inhibitors of Macrophage Migration Inhibitory Factor

DOE PAGES

Dziedzic, Pawel; Cisneros, José A.; Robertson, Michael J.; ...

2015-02-20

Optimization is reported for biaryltriazoles as inhibitors of the tautomerase activity of human macrophage migration inhibitory factor (MIF), a proinflammatory cytokine associated with numerous inflammatory diseases and cancer. A combined approach was taken featuring organic synthesis, enzymatic assaying, crystallography, and modeling including free-energy perturbation (FEP) calculations. X-ray crystal structures for 3a and 3b bound to MIF are reported and provided a basis for the modeling efforts. The accommodation of the inhibitors in the binding site is striking with multiple hydrogen bonds and aryl–aryl interactions. Additional modeling encouraged pursuit of 5-phenoxyquinolinyl analogues, which led to the very potent compound 3s. Activitymore » was further enhanced by addition of a fluorine atom adjacent to the phenolic hydroxyl group as in 3w, 3z, 3aa, and 3bb to strengthen a key hydrogen bond. We also show that physical properties of the compounds can be modulated by variation of solvent-exposed substituents. Several of the compounds are likely the most potent known MIF tautomerase inhibitors; the most active ones are more than 1000-fold more active than the well-studied (R)-ISO-1 and more than 200-fold more active than the chromen-4-one Orita-13.« less

[The use of complex interval models for predicting activity of non-nucleoside reverse transcriptase activity].

PubMed

Burliaeva, E V; Tarkhov, A E; Burliaev, V V; Iurkevich, A M; Shvets, V I

2002-01-01

Searching of new anti-HIV agents is still crucial now. In general, researches are looking for inhibitors of certain HIV's vital enzymes, especially for reverse transcriptase (RT) inhibitors. Modern generation of anti-HIV agents represents non-nucleoside reverse transcriptase inhibitors (NNRTIs). They are much less toxic than nucleoside analogues and more chemically stable, thus being slower metabolized and emitted from the human body. Thus, search of new NNRTIs is actual today. Synthesis and study of new anti-HIV drugs is very expensive. So employment of the activity prediction techniques for such a search is very beneficial. This technique allows predicting the activities for newly proposed structures. It is based on the property model built by investigation of a series of known compounds with measured activity. This paper presents an approach of activity prediction based on "structure-activity" models designed to form a hypothesis about probably activity interval estimate. This hypothesis formed is based on structure descriptor domains, calculated for all energetically allowed conformers for each compound in the studied sef. Tetrahydroimidazobenzodiazipenone (TIBO) derivatives and phenylethyltiazolyltiourea (PETT) derivatives illustrated the predictive power of this method. The results are consistent with experimental data and allow to predict inhibitory activity of compounds, which were not included into the training set.

Toxic volatile organic compounds in environmental tobacco smoke: Emission factors for modeling exposures of California populations

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

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air contaminants in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including, 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosamines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were alsomore » determined for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors ({mu}g/cigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were Generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

Formation of hydrogen peroxide from illuminated polar snows and frozen solutions of model compounds

NASA Astrophysics Data System (ADS)

Hullar, Ted; Patten, Kelley; Anastasio, Cort

2012-08-01

Hydrogen peroxide (HOOH) is an important trace constituent in snow and ice, including in Arctic and Antarctic ice cores. To better understand the budget of snowpack HOOH, here we examine its production in illuminated snow and ice. To evaluate what types of compounds might be important photochemical sources of HOOH, we first illuminated laboratory ice samples containing 10 different model organic compounds: guaiacol, phenol, syringol, benzoate, formate, octanal, octanoic acid, octanedioic acid, phenylalanine, and mixtures of oxalate with iron (III). Half of these compounds produced little or no HOOH during illumination, but two classes of compounds were very reactive: phenolic compounds (with rates of HOOH of 6-62 nM-HOOH h-1 μM-1-phenolic) and mixtures of Fe(III) with a stoichiometric excess of oxalate (with rates of HOOH production as high as 2,000,000 nM h-1 per μM iron). To quantify rates of HOOH production in the environment we also illuminated snow samples collected from the Arctic and Antarctic. The average (±1σ) HOOH production rate in these samples was low, 5.3 ± 5.0 nM h-1 and replicate measurements showed high variability. In some natural samples there was an initial burst of HOOH production (with a rate approximately 10 times higher than the average production rate), followed by reduced rates at subsequent time points. Although our laboratory ice samples reveal that illuminated organics and metal-organic complexes can form HOOH, the low rates of HOOH formation in the Arctic and Antarctic snow samples suggest this process has only a modest impact on the HOOH budget in the snowpack.

Toxic Volatile Organic Compounds in Environmental Tobacco Smoke:Emission Factors for Modeling Exposures of California Populations

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

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosarnines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were also determinedmore » for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors (pgkigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

IEEE Photovoltaic Specialists Conference, 20th, Las Vegas, NV, Sept. 26-30, 1988, Conference Record. Volumes 1 & 2

NASA Astrophysics Data System (ADS)

Various papers on photovoltaics are presented. The general topics considered include: amorphous materials and cells; amorphous silicon-based solar cells and modules; amorphous silicon-based materials and processes; amorphous materials characterization; amorphous silicon; high-efficiency single crystal solar cells; multijunction and heterojunction cells; high-efficiency III-V cells; modeling and characterization of high-efficiency cells; LIPS flight experience; space mission requirements and technology; advanced space solar cell technology; space environmental effects and modeling; space solar cell and array technology; terrestrial systems and array technology; terrestrial utility and stand-alone applications and testing; terrestrial concentrator and storage technology; terrestrial stand-alone systems applications; terrestrial systems test and evaluation; terrestrial flatplate and concentrator technology; use of polycrystalline materials; polycrystalline II-VI compound solar cells; analysis of and fabrication procedures for compound solar cells.

Hydra, a model system for environmental studies.

PubMed

Quinn, Brian; Gagné, François; Blaise, Christian

2012-01-01

Hydra have been extensively used for studying the teratogenic and toxic potential of numerous toxins throughout the years and are more recently growing in popularity to assess the impacts of environmental pollutants. Hydra are an appropriate bioindicator species for use in environmental assessment owing to their easily measurable physical (morphology), biochemical (xenobiotic biotransformation; oxidative stress), behavioural (feeding) and reproductive (sexual and asexual) endpoints. Hydra also possess an unparalleled ability to regenerate, allowing the assessment of teratogenic compounds and the impact of contaminants on stem cells. Importantly, Hydra are ubiquitous throughout freshwater environments and relatively easy to culture making them appropriate for use in small scale bioassay systems. Hydra have been used to assess the environmental impacts of numerous environmental pollutants including metals, organic toxicants (including pharmaceuticals and endocrine disrupting compounds), nanomaterials and industrial and municipal effluents. They have been found to be among the most sensitive animals tested for metals and certain effluents, comparing favourably with more standardised toxicity tests. Despite their lack of use in formalised monitoring programmes, Hydra have been extensively used and are regarded as a model organism in aquatic toxicology.

MISTRA mechanism development: A new mechanism focused on marine environments

NASA Astrophysics Data System (ADS)

Bräuer, Peter; Sommariva, Roberto; von Glasow, Roland

2015-04-01

The tropospheric multiphase chemistry of halogen compounds plays a key role in marine environments. Moreover, halogen compounds have an impact on the tropospheric oxidation capacity and climate. With more than two thirds of the Earth's surface covered with oceans, effects are of global importance. Various conditions are found in marine environments ranging from pristine regions to polluted regimes in the continental outflow. Furthermore, there are important sources for halogen compounds over land, such as volcanoes, salt lakes, or emissions from industrial processes. To assess the impact of halogen chemistry with numerical models under these distinct conditions, a multiphase mechanism has been developed in the last decades and applied successfully in numerous box and 1D model studies. Contributions from these model studies helped to identify important chemical cycles affecting the composition and chemistry of the troposphere. However, several discrepancies between model results and field measurements remain. Therefore, a major revision of the chemical mechanism has been performed including an update of the kinetic data and the addition of new reaction cycles. The extended mechansims have been evaluated in several model studies with the 1D model MISTRA. Current work focuses at the identification of the most important reaction cycles, which led to significant changes in the concentration-time profiles of several halogen species. Subsequently, the mechanism will be reduced to the most imporatant reactions, which are currently investigated. As regional and global model studies become more important to identify the importance of tropospheric halogen multiphase chemistry, the goal is to derive parameterisations for the most important halogen chemistry cycles, which can than be implemented in regional and global 3D models. In the reduction process, the extented MISTRA version will serve as a benchmark to assess the quality and accuracy of the reduced mechansim versions.

Release kinetics of volatile organic compounds from roasted and ground coffee: online measurements by PTR-MS and mathematical modeling.

PubMed

Mateus, Maria-L; Lindinger, Christian; Gumy, Jean-C; Liardon, Remy

2007-12-12

The present work shows the possibilities and limitations in modeling release kinetics of volatile organic compounds (VOCs) from roasted and ground coffee by applying physical and empirical models such as the diffusion and Weibull models. The release kinetics of VOCs were measured online by proton transfer reaction-mass spectrometry (PTR-MS). Compounds were identified by GC-MS, and the contribution of the individual compounds to different mass fragments was elucidated by GC/PTR-MS. Coffee samples roasted to different roasting degrees and ground to different particle sizes were studied under dry and wet stripping conditions. To investigate the accuracy of modeling the VOC release kinetics recorded using PTR-MS, online kinetics were compared with kinetics reconstituted from purge and trap samplings. Results showed that uncertainties in ion intensities due to the presence of isobaric species may prevent the development of a robust mathematical model. Of the 20 identified compounds, 5 were affected to a lower extent as their contribution to specific m/z intensity varied by <15% over the stripping time. The kinetics of these compounds were fitted using physical and statistical models, respectively, the diffusion and Weibull models, which helped to identify the underlying release mechanisms. For dry stripping, the diffusion model allowed a good representation of the release kinetics, whereas for wet stripping conditions, release patterns were very complex and almost specific for each compound analyzed. In the case of prewetted coffee, varying particle size (approximately 400-1200 microm) had no significant effect on the VOC release rate, whereas for dry coffee, the release was faster for smaller particles. The absence of particle size effect in wet coffee was attributed to the increase of opened porosity and compound diffusivity by solubilization and matrix relaxation. To conclude, the accurate modeling of VOC release kinetics from coffee allowed small variations in compound release to be discriminated. Furthermore, it evidenced the different aroma compositions that may be obtained depending on the time when VOCs are recovered.

The reactivity of phenolic and non-phenolic residual kraft lignin model compounds with Mn(II)-peroxidase from Lentinula edodes.

PubMed

Crestini, C; D'Annibale, A; Sermanni, G G; Saladino, R

2000-02-01

Three phenolic model compounds representing bonding patterns of residual kraft lignin were incubated with manganese peroxidase from Lentinula edodes. Extensive degradation of all the phenolic models, mainly occurring via side-chain benzylic oxidation, was observed. Among the tested model compounds the diphenylmethane alpha-5 phenolic model was found to be the most reactive, yielding several products showing oxidation and fragmentation at the bridging position. The non-phenolic 5-5' biphenyl and 5-5' diphenylmethane models were found unreactive.

40 CFR 442.2 - General definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., organic chemicals including: alcohols, aldehydes, formaldehydes, phenols, peroxides, organic salts, amines, amides, other nitrogen compounds, other aromatic compounds, aliphatic organic chemicals, glycols, glycerines, and organic polymers; refractory organic compounds including: ketones, nitriles, organo-metallic...

EMERGING CONTAMINANTS IN BIOSOLIDS

EPA Science Inventory

Emerging contaminants are receiving increasing media and scientific attention. These chemicals are sometimes referred to as compounds of emerging concern or trace organic compounds, and include several groups of chemicals including endocrine disrupting compounds (EDCs), and phar...

Elastic and inelastic scattering of neutrons on 238U nucleus

NASA Astrophysics Data System (ADS)

Capote, R.; Trkov, A.; Sin, M.; Herman, M. W.; Soukhovitskiĩ, E. Sh.

2014-04-01

Advanced modelling of neutron induced reactions on the 238U nucleus is aimed at improving our knowledge of neutron scattering. Capture and fission channels are well constrained by available experimental data and neutron standard evaluation. A focus of this contribution is on elastic and inelastic scattering cross sections. The employed nuclear reaction model includes - a new rotational-vibrational dispersive optical model potential coupling the low-lying collective bands of vibrational character observed in even-even actinides; - the Engelbrecht-Weidenmüller transformation allowing for inclusion of compound-direct interference effects; - and a multi-humped fission barrier with absorption in the secondary well described within the optical model for fission. Impact of the advanced modelling on elastic and inelastic scattering cross sections including angular distributions and emission spectra is assessed both by comparison with selected microscopic experimental data and integral criticality benchmarks including measured reaction rates (e.g. JEMIMA, FLAPTOP and BIG TEN). Benchmark calculations provided feedback to improve the reaction modelling. Improvement of existing libraries will be discussed.

Long-term characterization of the diet-induced obese and diet-resistant rat model: a polygenetic rat model mimicking the human obesity syndrome.

PubMed

Madsen, Andreas Nygaard; Hansen, Gitte; Paulsen, Sarah Juel; Lykkegaard, Kirsten; Tang-Christensen, Mads; Hansen, Harald S; Levin, Barry E; Larsen, Philip Just; Knudsen, Lotte Bjerre; Fosgerau, Keld; Vrang, Niels

2010-09-01

The availability of useful animal models reflecting the human obesity syndrome is crucial in the search for novel compounds for the pharmacological treatment of obesity. In the current study, we have performed an extensive characterization of the obesity syndrome in a polygenetic animal model, namely the selectively bred diet-induced obese (DIO) and diet-resistant (DR) rat strains. We show that they constitute useful models of the human obesity syndrome. DIO and DR rats were fed either a high-energy (HE) or a standard chow (Chow) diet from weaning to 9 months of age. Metabolic characterization including blood biochemistry and glucose homeostasis was examined at 2, 3, 6, and 9 months of age. Furthermore, in 6-month-old HE-fed DIO rats, the anti-obesity effects of liraglutide and sibutramine were examined in a 28-day study. Only HE-fed DIO rats developed visceral obesity, hyperleptinemia, hyperinsulinemia, and dyslipidemia, and showed a worsening of glucose tolerance over time. In line with the hyperlipidemic profile, a severe hepatic fat infiltration was observed in DIO rats at 6 months of age. The effects of liraglutide and sibutramine were tested in 6-month-old DIO rats. Both compounds effectively reduced food intake and body weight in DIO rats. Liraglutide furthermore improved glucose tolerance when compared with sibutramine. Our data highlights the usefulness of a polygenetic animal model for screening of compounds affecting food intake, body weight, and glucose homeostasis. Furthermore, the results underscore the effectiveness of GLP-1 mimetics both as anti-diabetes and anti-obesity agents.

Experience with compound words influences their processing: An eye movement investigation with English compound words.

PubMed

Juhasz, Barbara J

2016-11-14

Recording eye movements provides information on the time-course of word recognition during reading. Juhasz and Rayner [Juhasz, B. J., & Rayner, K. (2003). Investigating the effects of a set of intercorrelated variables on eye fixation durations in reading. Journal of Experimental Psychology: Learning, Memory and Cognition, 29, 1312-1318] examined the impact of five word recognition variables, including familiarity and age-of-acquisition (AoA), on fixation durations. All variables impacted fixation durations, but the time-course differed. However, the study focused on relatively short, morphologically simple words. Eye movements are also informative for examining the processing of morphologically complex words such as compound words. The present study further examined the time-course of lexical and semantic variables during morphological processing. A total of 120 English compound words that varied in familiarity, AoA, semantic transparency, lexeme meaning dominance, sensory experience rating (SER), and imageability were selected. The impact of these variables on fixation durations was examined when length, word frequency, and lexeme frequencies were controlled in a regression model. The most robust effects were found for familiarity and AoA, indicating that a reader's experience with compound words significantly impacts compound recognition. These results provide insight into semantic processing of morphologically complex words during reading.

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Enabling PBPK model development through the application of ...

EPA Pesticide Factsheets

The creation of Physiologically Based Pharmacokinetic (PBPK) models for a new chemical requires the selection of an appropriate model structure and the collection of a large amount of data for parameterization. Commonly, a large proportion of the needed information is collected from previously published PBPK models for compounds analogous to the chemical of interest. A key difficulty in quickly developing new models is therefore the identification of appropriate chemical analogs within PBPK model literature. To reduce the burden on researchers of finding the appropriate literature to inform new modeling efforts, we sought to collect a comprehensive listing of chemicals contained in the corpus of PBPK articles and embed them into a chemically searchable database for facile analog identification. To cull the list of chemicals from PBPK literature, we investigated the use of three easily accessible methods: collecting chemicals via MeSH controlled vocabulary processing abstracts using OSCAR4 text-mining software, and annotating abstracts using chemicalize.org. In total, just over 300 unique compounds spanning a variety of chemical classes were identified as having completed PBPK models from over 1700 articles. Additional annotations of PBPK model details including species, lifestage, number of compartments, gender, and exposure routes were tabulated. These data were then imbedded into the Toxicokinetic Knowledge Base (TKKB), an internal website for chemicall

Optimal choice of pH for toxicity and bioaccumulation studies of ionizing organic chemicals.

PubMed

Rendal, Cecilie; Kusk, Kresten Ole; Trapp, Stefan

2011-11-01

It is recognized that the pH of exposure solutions can influence the toxicity and bioaccumulation of ionizing compounds. The present study investigates whether it can be considered a general rule that an ionizable compound is more toxic and more bioaccumulative when in the neutral state. Three processes were identified to explain the behavior of ionizing compounds with changing pH: the change in lipophilicity when a neutral compound becomes ionized, electrical attraction, and the ion trap. The literature was screened for bioaccumulation and toxicity tests of ionizing organic compounds performed at multiple pH levels. Toxicity and bioconcentration factors (BCFs) were higher for acids at lower pH values, whereas the opposite was true for bases. The effect of pH was most pronounced when pH - pK(a) was in the range of -1 to 3 for acids, and -3 to 1 for bases. The factor by which toxicity and BCF changed with pH was correlated with the lipophilicity of the compound (log K(OW) of the neutral compound). For both acids and bases, the correlation was positive, but it was significant only for acids. Because experimental data in the literature were limited, results were supplemented with model simulations using a dynamic flux model based on the Fick-Nernst-Planck diffusion equation known as the cell model. The cell model predicts that bases with delocalized charges may in some cases show declining bioaccumulation with increasing pH. Little information is available for amphoteric and zwitterionic compounds; however, based on simulations with the cell model, it is expected that the highest toxicity and bioaccumulation of these compounds will be found where the compounds are most neutral, at the isoelectric point. Copyright © 2011 SETAC.

Investigation of structural and mechanical properties of rare-earth bismuthide (RBi, R=Ce & Pr) with the NaCl structure at high pressure

NASA Astrophysics Data System (ADS)

Yaduvanshi, Namrata; Kapoor, Shilpa; Singh, Sadhna

2018-05-01

We have investigated the structural and mechanical properties of Cerium and Praseodymium Bismuthides under pressure by means of a three body interaction potential model which includes long range columbic interaction, three body interactions and short range overlap repulsive interaction operative up to second nearest neighbor. These compounds shows transition from NaCl structure to body-centered tetragonal (BCT) structure (distorted CsCl-type P4/mmm). The elastic constants and their properties are also reported. Our calculated results of phase transitions and volume collapses of these compounds show a good agreement with available theoretical and experimental results.

Car-Parrinello molecular dynamics study of the charge-discharge cycle in lithium-ion battery materials

NASA Astrophysics Data System (ADS)

Kung, Y. F.; Jia, C. J.; Gent, W. E.; Lee, I.; Moritz, B.; Devereaux, T. P.

Lithium-ion transition metal oxide compounds have shown great potential for use as battery electrodes. However, the underlying structural modifications which accompany delithiation during battery charging remain less well understood. Formation of peroxide-like species and cation migration between layers comprise two promising candidates for describing numerous experimental observations. Taking Li2RuO3 as a model system, we use Car-Parrinello molecular dynamics to examine the structural changes that occur during delithiation and lithiation. We compare our results to existing experimental observations in other compounds and provide guidance for future experiments, including resonant inelastic x-ray scattering (RIXS).

Occurrence of emerging pollutants in urban wastewater and their removal through biological treatment followed by ozonation.

PubMed

Rosal, Roberto; Rodríguez, Antonio; Perdigón-Melón, José Antonio; Petre, Alice; García-Calvo, Eloy; Gómez, María José; Agüera, Ana; Fernández-Alba, Amadeo R

2010-01-01

This work reports a systematic survey of over seventy individual pollutants in a Sewage Treatment Plant (STP) receiving urban wastewater. The compounds include mainly pharmaceuticals and personal care products, as well as some metabolites. The quantification in the ng/L range was performed by Liquid Chromatography-QTRAP-Mass Spectrometry and Gas Chromatography coupled to Mass Spectrometry. The results showed that paraxanthine, caffeine and acetaminophen were the main individual pollutants usually found in concentrations over 20 ppb. N-formyl-4-amino-antipiryne and galaxolide were also detected in the ppb level. A group of compounds including the beta-blockers atenolol, metoprolol and propanolol; the lipid regulators bezafibrate and fenofibric acid; the antibiotics erythromycin, sulfamethoxazole and trimethoprim, the antiinflammatories diclofenac, indomethacin, ketoprofen and mefenamic acid, the antiepileptic carbamazepine and the antiacid omeprazole exhibited removal efficiencies below 20% in the STP treatment. Ozonation with doses lower than 90 microM allowed the removal of many individual pollutants including some of those more refractory to biological treatment. A kinetic model allowed the determination of second order kinetic constants for the ozonation of bezafibrate, cotinine, diuron and metronidazole. The results show that the hydroxyl radical reaction was the major pathway for the oxidative transformation of these compounds. (c) 2009 Elsevier Ltd. All rights reserved.

Small-molecule inhibitors suppress the expression of both type III secretion and amylovoran biosynthesis genes in Erwinia amylovora.

PubMed

Yang, Fan; Korban, Schuyler S; Pusey, P Lawrence; Elofsson, Michael; Sundin, George W; Zhao, Youfu

2014-01-01

The type III secretion system (T3SS) and exopolysaccharide (EPS) amylovoran are two essential pathogenicity factors in Erwinia amylovora, the causal agent of the serious bacterial disease fire blight. In this study, small molecules that inhibit T3SS gene expression in E. amylovora under hrp (hypersensitive response and pathogenicity)-inducing conditions were identified and characterized using green fluorescent protein (GFP) as a reporter. These compounds belong to salicylidene acylhydrazides and also inhibit amylovoran production. Microarray analysis of E. amylovora treated with compounds 3 and 9 identified a total of 588 significantly differentially expressed genes. Among them, 95 and 78 genes were activated and suppressed by both compounds, respectively, when compared with the dimethylsulphoxide (DMSO) control. The expression of the majority of T3SS genes in E. amylovora, including hrpL and the avrRpt2 effector gene, was suppressed by both compounds. Compound 3 also suppressed the expression of amylovoran precursor and biosynthesis genes. However, both compounds induced significantly the expression of glycogen biosynthesis genes and siderophore biosynthesis, regulatory and transport genes. Furthermore, many membrane, lipoprotein and exported protein-encoding genes were also activated by both compounds. Similar expression patterns were observed for compounds 1, 2 and 4. Using crab apple flower as a model, compound 3 was capable of reducing disease development in pistils. These results suggest a common inhibition mechanism shared by salicylidene acylhydrazides and indicate that small-molecule inhibitors that disable T3SS function could be explored to control fire blight disease. © 2013 BSPP AND JOHN WILEY & SONS LTD.

Mastering tricyclic ring systems for desirable functional cannabinoid activity

PubMed Central

Petrov, Ravil R.; Knight, Lindsay; Chen, Shao-Rui; Wager-Miller, Jim; McDaniel, Steven W.; Diaz, Fanny; Barth, Francis; Pan, Hui-Lin; Mackie, Ken; Cavasotto, Claudio N.; Diaz, Philippe

2013-01-01

There is growing interest in using cannabinoid receptor 2 (CB2) agonists for the treatment of neuropathic pain and other indications. In continuation of our ongoing program aiming for the development of new small molecule cannabinoid ligands, we have synthesized a novel series of carbazole and γ-carboline derivatives. The affinities of the newly synthesized compounds were determined by a competitive radioligand displacement assay for human CB2 cannabinoid receptor and rat CB1 cannabinoid receptor. Functional activity and selectivity at human CB1 and CB2 receptors were characterized using receptor internalization and [35S]GTP-γ-S assays. The structure-activity relationship and optimization studies of the carbazole series have led to the discovery of a non-selective CB1 and CB2 agonist, compound 4. Our subsequent research efforts to increase CB2 selectivity of this lead compound have led to the discovery of CB2 selective compound 64, which robustly internalized CB2 receptors. Compound 64 had potent inhibitory effects on pain hypersensitivity in a rat model of neuropathic pain. Other potent and CB2 receptor–selective compounds, including compounds 63 and 68, and a selective CB1 agonist, compound 74 were also discovered. In addition, we identified the CB2 ligand 35 which failed to promote CB2 receptor internalization and inhibited compound CP55,940-induced CB2 internalization despite a high CB2 receptor affinity. The present study provides novel tricyclic series as a starting point for further investigations of CB2 pharmacology and pain treatment. PMID:24125850

Computational Models of the Representation of Bangla Compound Words in the Mental Lexicon.

PubMed

Dasgupta, Tirthankar; Sinha, Manjira; Basu, Anupam

2016-08-01

In this paper we aim to model the organization and processing of Bangla compound words in the mental lexicon. Our objective is to determine whether the mental lexicon access a Bangla compound word as a whole or decomposes the whole word into its constituent morphemes and then recognize them accordingly. To address this issue, we adopted two different strategies. First, we conduct a cross-modal priming experiment over a number of native speakers. Analysis of reaction time (RT) and error rates indicates that in general, Bangla compound words are accessed via partial decomposition process. That is some word follows full-listing mode of representation and some words follow the decomposition route of representation. Next, based on the collected RT data we have developed a computational model that can explain the processing phenomena of the access and representation of Bangla compound words. In order to achieve this, we first explored the individual roles of head word position, morphological complexity, orthographic transparency and semantic compositionality between the constituents and the whole compound word. Accordingly, we have developed a complexity based model by combining these features together. To a large extent we have successfully explained the possible processing phenomena of most of the Bangla compound words. Our proposed model shows an accuracy of around 83 %.

Tailored tools to improve pharmacotherapy in infants.

PubMed

Allegaert, Karel

2014-08-01

Extensive within-population variability is the essence of neonatal pharmacology. Despite this, infants remain one of the last therapeutic orphans. Together with additional legal initiatives, tailoring of already available tools (modeling, covariates, pharmacovigilance) may significantly improve pharmacotherapy in infants. Modeling approaches that hold the promise to improve pharmacotherapy in infants are between-compound extrapolation for compounds that undergo the same route of elimination and integration of time-varying physiology to adapt for the fast maturational changes. Besides these maturational covariates (size, age), newly emerging covariates relate to novel treatment modalities (extracorporeal circulation, hypothermia), environmental issues (microbiome, critical illness) or pharmacogenetics. All these covariates interact with the maturational variation. Finally, pharmacovigilance also needs to be tailored to the characteristics of this population. This relates to preventive strategies, signal detection and assessment of causality. Knowledge on pharmacotherapy in infants is lagging. Tailoring available tools to the specific characteristics (maturation) and clinical needs (newly emerging covariates) of infants is feasible but needs creativity and a multidisciplinary collaboration between modelers, academia, clinical researchers and, obviously, the public, including parents.

The Spectrophotometric Analysis and Modeling of Sunscreens

NASA Astrophysics Data System (ADS)

Walters, Christina; Keeney, Allen; Wigal, Carl T.; Johnston, Cynthia R.; Cornelius, Richard D.

1997-01-01

Sunscreens and their SPF (Sun Protection Factor) values are the focus of this experiment that includes spectrophotometric measurements and molecular modeling. Students suspend weighed amounts of sunscreen lotions graded SPF 4, 6, 8, 15, 30, and 45 in water and dissolve aliquots of the aqueous suspensions in propanol. The expected relationship of absorbance proportional to log10(SPF) applies at 312 nm where a maximum in absorbance occurs for the sunscreen solutions. Results at 330 nm give similar results and are more accessible using spectrometers routinely available in the introductory laboratory. Sunscreens constitute a suitable class of compounds to use for modeling electronic spectra, and using the computer for the active ingredients ethylhexyl para-methoxycinnamate, oxybenzone, 2-ethylhexyl salicylate, and octocrylene found in commercially available formulations typically predicts the absorption maxima within 10 nm. This experiment lets students explore which compounds have the potential to function as sunscreen agents and thereby see the importance of a knowledge of chemistry to the formulation of household items.

Flux measurements of volatile organic compounds from an urban landscape

NASA Astrophysics Data System (ADS)

Velasco, E.; Lamb, B.; Pressley, S.; Allwine, E.; Westberg, H.; Jobson, B. T.; Alexander, M.; Prazeller, P.; Molina, L.; Molina, M.

2005-10-01

Direct measurements of volatile organic compound (VOC) emissions that include all sources in urban areas are a missing requirement to evaluate emission inventories and constrain current photochemical modelling practices. Here we demonstrate the use of micrometeorological techniques coupled with fast-response sensors to measure urban VOC fluxes from a neighbourhood of Mexico City, where the spatial variability of surface cover and roughness is high. Fluxes of olefins, methanol, acetone, toluene and C2-benzenes were measured and compared with the local gridded emissions inventory. VOC fluxes exhibited a clear diurnal pattern with a strong relationship to vehicular traffic. Recent photochemical modelling results suggest that VOC emissions are significantly underestimated in Mexico City, but for the olefin class, toluene, C2-benzenes, and acetone fluxes measured in this work, the results show general agreement with the gridded emissions inventory. While these measurements do not address the full suite of VOC emissions, the comparison with the inventory suggests that other explanations may be needed to explain the photochemical modelling results.

iFly: The eye of the fruit fly as a model to study autophagy and related trafficking pathways.

PubMed

Lőrincz, Péter; Takáts, Szabolcs; Kárpáti, Manuéla; Juhász, Gábor

2016-03-01

Autophagy is a process by which eukaryotic cells degrade and recycle their intracellular components within lysosomes. Autophagy is induced by starvation to ensure survival of individual cells, and it has evolved to fulfill numerous additional roles in animals. Autophagy not only provides nutrient supply through breakdown products during starvation, but it is also required for the elimination of damaged or surplus organelles, toxic proteins, aggregates, and pathogens, and is essential for normal organelle turnover. Because of these roles, defects in autophagy have pathological consequences. Here we summarize the current knowledge of autophagy and related trafficking pathways in a convenient model: the compound eye of the fruit fly Drosophila melanogaster. In our review, we present a general introduction of the development and structure of the compound eye. This is followed by a discussion of various neurodegeneration models including retinopathies, with special emphasis on the protective role of autophagy against these diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of Mutagenicity of Chemicals from Their Calculated Molecular Descriptors: A Case Study with Structurally Homogeneous versus Diverse Datasets.

PubMed

Basak, Subhash C; Majumdar, Subhabrata

2015-01-01

Variation in high-dimensional data is often caused by a few latent factors, and hence dimension reduction or variable selection techniques are often useful in gathering useful information from the data. In this paper we consider two such recent methods: Interrelated two-way clustering and envelope models. We couple these methods with traditional statistical procedures like ridge regression and linear discriminant analysis, and apply them on two data sets which have more predictors than samples (i.e. n < p scenario) and several types of molecular descriptors. One of these datasets consists of a congeneric group of Amines while the other has a much diverse collection compounds. The difference of prediction results between these two datasets for both the methods supports the hypothesis that for a congeneric set of compounds, descriptors of a certain type are enough to provide good QSAR models, but as the data set grows diverse including a variety of descriptors can improve model quality considerably.

Kinetic modeling of benzodiazepine receptor binding with PET and high specific activity [(11)C]Iomazenil in healthy human subjects.

PubMed

Bremner, J D; Horti, A; Staib, L H; Zea-Ponce, Y; Soufer, R; Charney, D S; Baldwin, R

2000-01-01

Quantitation of the PET benzodiazepine receptor antagonist, [(11)C]Iomazenil, using low specific activity radioligand was recently described. The purpose of this study was to quantitate benzodiazepine receptor binding in human subjects using PET and high specific activity [(11)C]Iomazenil. Six healthy human subjects underwent PET imaging following a bolus injection of high specific activity (>100 Ci/mmol) [(11)C]iomazenil. Arterial samples were collected at multiple time points after injection for measurement of unmetabolized total and nonprotein-bound parent compound in plasma. Time activity curves of radioligand concentration in brain and plasma were analyzed using two and three compartment model. Kinetic rate constants of transfer of radioligand between plasma, nonspecifically bound brain tissue, and specifically bound brain tissue compartments were fitted to the model. Values for fitted kinetic rate constants were used in the calculation of measures of benzodiazepine receptor binding, including binding potential (the ratio of receptor density to affinity), and product of BP and the fraction of free nonprotein-bound parent compound (V(3)'). Use of the three compartment model improved the goodness of fit in comparison to the two compartment model. Values for kinetic rate constants and measures of benzodiazepine receptor binding, including BP and V(3)', were similar to results obtained with the SPECT radioligand [(123)I]iomazenil, and a prior report with low specific activity [(11)C]Iomazenil. Kinetic modeling using the three compartment model with PET and high specific activity [(11)C]Iomazenil provides a reliable measure of benzodiazepine receptor binding. Synapse 35:68-77, 2000. Published 2000 Wiley-Liss, Inc.

Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

NASA Astrophysics Data System (ADS)

Murphy, Benjamin N.; Woody, Matthew C.; Jimenez, Jose L.; Carlton, Ann Marie G.; Hayes, Patrick L.; Liu, Shang; Ng, Nga L.; Russell, Lynn M.; Setyan, Ari; Xu, Lu; Young, Jeff; Zaveri, Rahul A.; Zhang, Qi; Pye, Havala O. T.

2017-09-01

Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May-June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from -5.62 to -2.42 µg m-3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73 µg m-3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

Detailed emission profiles for on-road vehicles derived from ambient measurements during a windless traffic episode in Baltimore using a multi-model approach

NASA Astrophysics Data System (ADS)

Ke, Haohao; Ondov, John M.; Rogge, Wolfgang F.

2013-12-01

Composite chemical profiles of motor vehicle emissions were extracted from ambient measurements at a near-road site in Baltimore during a windless traffic episode in November, 2002, using four independent approaches, i.e., simple peak analysis, windless model-based linear regression, PMF, and UNMIX. Although the profiles are in general agreement, the windless-model-based profile treatment more effectively removes interference from non-traffic sources and is deemed to be more accurate for many species. In addition to abundances of routine pollutants (e.g., NOx, CO, PM2.5, EC, OC, sulfate, and nitrate), 11 particle-bound metals and 51 individual traffic-related organic compounds (including n-alkanes, PAHs, oxy-PAHs, hopanes, alkylcyclohexanes, and others) were included in the modeling.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

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

Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.« less

Predicting Dural Tear in Compound Depressed Skull Fractures: A Prospective Multicenter Correlational Study.

PubMed

Salia, Shemsedin Musefa; Mersha, Hagos Biluts; Aklilu, Abenezer Tirsit; Baleh, Abat Sahlu; Lund-Johansen, Morten

2018-06-01

Compound depressed skull fracture (DSF) is a neurosurgical emergency. Preoperative knowledge of dural status is indispensable for treatment decision making. This study aimed to determine predictors of dural tear from clinical and imaging characteristics in patients with compound DSF. This prospective, multicenter correlational study in neurosurgical hospitals in Addis Ababa, Ethiopia, included 128 patients operated on from January 1, 2016, to October 31, 2016. Clinical, imaging, and intraoperative findings were evaluated. Univariate and multivariate analyses were used to establish predictors of dural tear. A logistic regression model was developed to predict probability of dural tear. Model validation was done using the receiver operating characteristic curve. Dural tear was seen in 55.5% of 128 patients. Demographics, injury mechanism, clinical presentation, and site of DSF had no significant correlation with dural tear. In univariate and multivariate analyses, depth of fracture depression (odds ratio 1.3, P < 0.001), pneumocephalus (odds ratio 2.8, P = 0.005), and brain contusions/intracerebral hematoma (odds ratio 5.5, P < 0.001) were significantly correlated with dural tear. We developed a logistic regression model (diagnostic test) to calculate probability of dural tear. Using the receiver operating characteristic curve, we determined the cutoff value for a positive test giving the highest accuracy to be 30% with a corresponding sensitivity of 93.0% and specificity of 43.9%. Dural tear in compound DSF can be predicted with 93.0% sensitivity using preoperative findings and may guide treatment decision making in resource-limited settings where risk of extensive cranial surgery outweighs the benefit. Copyright © 2018 Elsevier Inc. All rights reserved.

Oxidation Chemistry and Kinetics of Model Compounds in Supercritical Water: Glucose, Acetic Acid, and Methylene Chloride

DTIC Science & Technology

1993-06-01

adsorption may be needed. I The underground SCWO process is not discussed in detail here. For a more in- i depth discussion see Gloyna (1989). One noteworthy... furfural were also detected. Xylose hydrolysis produced furfural . Other products identified included formic acid, lactic acid, U levulinic acid...noted, and the liquid products consisted namely of furans and furfurals (Amin et al., I 1975; Modell, 1985b). Woerner (1976) corroborates the results

Specificity of the Antibody Receptor Site to D-Lysergamide: Model of a Physiological Receptor for Lysergic Acid Diethylamide

PubMed Central

Vunakis, Helen Van; Farrow, John T.; Gjika, Hilda B.; Levine, Lawrence

1971-01-01

Antibodies to D-lysergic acid have been produced in rabbits and guinea pigs and a radioimmunoassay for the hapten was developed. The specificity of this lysergamide-antilysergamide reaction was determined by competitive binding with unlabeled lysergic acid diethylamide (LSD), psychotomimetic drugs, neurotransmitters, and other compounds with diverse structures. LSD and several related ergot alkaloids were potent competitors, three to seven times more potent than lysergic acid itself. The N,N-dimethyl derivatives of several compounds, including tryptamine, 5-hydroxytryptamine, 4-hydroxytryptamine, 5-methoxytryptamine, tyramine, and mescaline, were only about ten times less effective than lysergic acid, even though these compounds lack some of the ring systems of lysergic acid. The pattern of inhibition by related compounds with various substituents suggests that the antibody receptor site recognizes structural features resembling the LSD molecule. In particular, the aromatic nucleus and the dimethylated ethylamine side chain in phenylethylamine and tryptamine derivatives may assume in solution a conformation resembling ring A and the methylated nitrogen in ring C of LSD. Among the tryptamine derivatives, a large percentage of the most potent competitors are also psychotomimetic compounds. PMID:5283939

Identification of new anti-inflammatory agents based on nitrosporeusine natural products of marine origin.

PubMed

Philkhana, Satish Chandra; Verma, Abhishek Kumar; Jachak, Gorakhnath R; Hazra, Bibhabasu; Basu, Anirban; Reddy, D Srinivasa

2017-07-28

Nitrosporeusines A and B are two recently isolated marine natural products with novel skeleton and exceptional biological profile. Interesting antiviral activity of nitrosporeusines and promising potential in curing various diseases, evident from positive data from various animal models, led us to investigate their anti-inflammatory potential. Accordingly, we planned and synthesized nitrosporeusines A and B in racemic as well as enantiopure forms. The natural product synthesis was followed by preparation of several analogues, and all the synthesized compounds were evaluated for in vitro and in vivo anti-inflammatory potential. Among them, compounds 25, 29 and 40 significantly reduced levels of nitric oxide (NO), reactive oxygen species (ROS) and pro-inflammatory cytokines. In addition, these compounds suppressed several pro-inflammatory mediators including inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), nuclear factor-κB (NF-κB), and thereby can be emerged as potent anti-inflammatory compounds. Furthermore, all possible isomers of lead compound 25 were synthesized, characterized and profiled in same set of assays and found that one of the enantiomer (-)-25a was superior among them. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Plant extracts and natural compounds used against UVB-induced photoaging.

PubMed

Cavinato, Maria; Waltenberger, Birgit; Baraldo, Giorgia; Grade, Carla V C; Stuppner, Hermann; Jansen-Dürr, Pidder

2017-08-01

Skin is continuously exposed to a variety of environmental stresses, including ultraviolet (UV) radiation. UVB is an inherent component of sunlight that crosses the epidermis and reaches the upper dermis, leading to increased oxidative stress, activation of inflammatory response and accumulation of DNA damage among other effects. The increase in UVB radiation on earth due to the destruction of stratospheric ozone poses a major environmental threat to the skin, increasing the risk of damage with long-term consequences, such as photoaging and photocarcinogenesis. Extracts from plants and natural compounds have been historically used in traditional medicine in the form of teas and ointments but the effect of most of these compounds has yet to be verified. Regarding the increasing concern of the population with issues related to quality of life and appearance, the cosmetic market for anti-aging and photoprotective products based on natural compounds is continuously growing, and there is increasing requirement of expansion on research in this field. In this review we summarized the most current and relevant information concerning plant extracts and natural compounds that are able to protect or mitigate the deleterious effects caused by photoaging in different experimental models.

Heteroaromatic-based electrolytes for lithium and lithium-ion batteries

DOEpatents

Cheng, Gang; Abraham, Daniel P.

2017-04-18

The present invention provides an electrolyte for lithium and/or lithium-ion batteries comprising a lithium salt in a liquid carrier comprising heteroaromatic compound including a five-membered or six-membered heteroaromatic ring moiety selected from the group consisting of a furan, a pyrazine, a triazine, a pyrrole, and a thiophene, the heteroaromatic ring moiety bearing least one carboxylic ester or carboxylic anhydride substituent bound to at least one carbon atom of the heteroaromatic ring. Preferred heteroaromatic ring moieties include pyridine compounds, pyrazine compounds, pyrrole compounds, furan compounds, and thiophene compounds.

Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

PubMed

Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

2017-12-26

Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

Hydrodeoxygenation of coal using organometallic catalyst precursors

NASA Astrophysics Data System (ADS)

Kirby, Stephen R.

2002-04-01

The objective of this dissertation was to determine the desirability of organometallic compounds for the hydrodeoxygenation (HDO) of coal during liquefaction. The primary focus of this study was the removal of phenol-like compounds from coal liquids for the production of a thermally stable jet fuel. Investigation of the HDO ability of an organometallic compound containing both cobalt and molybdenum (CoMo-T2) was achieved using a combination of model compound and coal experiments. Model compounds were chosen representing four oxygen functional groups present in a range of coals. Electron density and bond order calculations were performed for anthrone, dinaphthyl ether, xanthene, di-t-butylmethylphenol, and some of their derivatives to ascertain a potential order of hydrogenolysis and hydrogenation reactivity for these compounds. The four model compounds were then reacted with CoMo-T2, as well as ammonium tetrathiomolybdate (ATTM). Products of reaction were grouped as compounds that had undergone deoxygenation, those that had aromatic rings reduced, those that were products of both reaction pathways, and those produced through other routes. ATTM had an affinity for both reaction types. Its reaction order for the four model compounds with respect to deoxygenated compounds was the same as that estimated from electron density calculations for hydrogenolysis reactivity. CoMo-T2 appeared to show a preference toward hydrogenation, although deoxygenated products were still achieved in similar, or greater, yields, for almost all the model compounds. The reactivity order achieved for the four compounds with CoMo-T2 was similar to that estimated from bond order calculations for hydrogenation reactivity. Three coals were selected representing a range of coal ranks and oxygen contents. DECS-26 (Wyodak), DECS-24 (Illinois #6), and DECS-23 (Pittsburgh #8) were analyzed by CPMAS 13C NMR and pyrolysis-GC-MS to determine the functional groups comprising the oxygen content of these coals. Trends within the data were similar to those reported by other authors. Based on the conclusions from both the model compound studies and the coal analysis, predictions were made of the catalyst precursors' performance in the HDO of the three selected coals. It was concluded that CoMo-T2 is a desirable catalyst precursor for the HDO of coals (particularly low-rank coals), but that an optimum set of conditions must be determined to take full advantage of its HDO ability. (Abstract shortened by UMI.)

Investigation of the emissions and profiles of a wide range of VOCs during the Clean air for London project

NASA Astrophysics Data System (ADS)

Holmes, Rachel; Lidster, Richard; Hamilton, Jacqueline; Lee, James; Hopkins, James; Whalley, Lisa; Lewis, Alistair

2014-05-01

The majority of the World's population live in polluted urbanized areas. Poor air quality is shortening life expectancy of people in the UK by an average 7-8 months and costs society around £20 billion per year.[1] Despite this, our understanding of atmospheric processing in urban environments and its effect on air quality is incomplete. Air quality models are used to predict how air quality changes given different concentrations of pollution precursors, such as volatile organic compounds (VOCs). The urban environment of megacities pose a unique challenge for air quality measurements and modelling, due to high population densities, pollution levels and complex infrastructure. For over 60 years the air quality in London has been monitored, however the existing measurements are limited to a small group of compounds. In order to fully understand the chemical and physical processes that occur in London, more intensive and comprehensive measurements should be made. The Clean air for London (ClearfLo) project was conducted to investigate the air quality, in particular the boundary layer pollution, of London. A relatively new technique, comprehensive two dimensional gas chromatography (GC×GC) [2] was combined with a well-established dual channel GC (DC-GC) [3] system to provide a more comprehensive measurement of VOCs. A total of 78 individual VOCs (36 aliphatics, 19 monoaromatics, 21 oxygenated and 2 halogenated) and 10 groups of VOCs (8 aliphatic, 1 monoaromatic and 1 monoterpene) from C1-C13+ were quantified. Seasonal and diurnal profiles of these VOCs have been found which show the influence of emission source and chemical processing. Including these extra VOCs should enhance the prediction capability of air quality models thus informing policy makers on how to potentially improve air quality in megacities. References 1. House of Commons Environmental Audit Committee, Air Quality: A follow-up report, Ninth Report of session 2012-12. 2. Lidster, R.T., J.F. Hamilton, and A.C. Lewis, The application of two total transfer valve modulators for comprehensive two-dimensional gas chromatography of volatile organic compounds. Journal of Separation Science, 2011. 34(7): p. 812-821. 3. Hopkins, J.R., C.E. Jones, and A.C. Lewis, A dual channel gas chromatograph for atmospheric analysis of volatile organic compounds including oxygenated and monoterpene compounds. Journal of Environmental Monitoring, 2011. 13(8): p. 2268-2276.

Computational Design of Flat-Band Material.

PubMed

Hase, I; Yanagisawa, T; Kawashima, K

2018-02-26

Quantum mechanics states that hopping integral between local orbitals makes the energy band dispersive. However, in some special cases, there are bands with no dispersion due to quantum interference. These bands are called as flat band. Many models having flat band have been proposed, and many interesting physical properties are predicted. However, no real compound having flat band has been found yet despite the 25 years of vigorous researches. We have found that some pyrochlore oxides have quasi-flat band just below the Fermi level by first principles calculation. Moreover, their valence bands are well described by a tight-binding model of pyrochlore lattice with isotropic nearest neighbor hopping integral. This model belongs to a class of Mielke model, whose ground state is known to be ferromagnetic with appropriate carrier doping and on-site repulsive Coulomb interaction. We have also performed a spin-polarized band calculation for the hole-doped system from first principles and found that the ground state is ferromagnetic for some doping region. Interestingly, these compounds do not include magnetic element, such as transition metal and rare-earth elements.

Computational Design of Flat-Band Material

NASA Astrophysics Data System (ADS)

Hase, I.; Yanagisawa, T.; Kawashima, K.

2018-02-01

Quantum mechanics states that hopping integral between local orbitals makes the energy band dispersive. However, in some special cases, there are bands with no dispersion due to quantum interference. These bands are called as flat band. Many models having flat band have been proposed, and many interesting physical properties are predicted. However, no real compound having flat band has been found yet despite the 25 years of vigorous researches. We have found that some pyrochlore oxides have quasi-flat band just below the Fermi level by first principles calculation. Moreover, their valence bands are well described by a tight-binding model of pyrochlore lattice with isotropic nearest neighbor hopping integral. This model belongs to a class of Mielke model, whose ground state is known to be ferromagnetic with appropriate carrier doping and on-site repulsive Coulomb interaction. We have also performed a spin-polarized band calculation for the hole-doped system from first principles and found that the ground state is ferromagnetic for some doping region. Interestingly, these compounds do not include magnetic element, such as transition metal and rare-earth elements.

Oxide-based method of making compound semiconductor films and making related electronic devices

DOEpatents

Kapur, Vijay K.; Basol, Bulent M.; Leidholm, Craig R.; Roe, Robert A.

2000-01-01

A method for forming a compound film includes the steps of preparing a source material, depositing the source material on a base and forming a preparatory film from the source material, heating the preparatory film in a suitable atmosphere to form a precursor film, and providing suitable material to said precursor film to form the compound film. The source material includes oxide-containing particles including Group IB and IIIA elements. The precursor film includes non-oxide Group IB and IIIA elements. The compound film includes a Group IB-IIIA-VIA compound. The oxides may constitute greater than about 95 molar percent of the Group IB elements and greater than about 95 molar percent of the Group IIIA elements in the source material. Similarly, non-oxides may constitute greater than about 95 molar percent of the Group IB elements and greater than about 95 molar percent of the Group IIIA elements in the precursor film. The molar ratio of Group IB to Group IIIA elements in the source material may be greater than about 0.6 and less than about 1.0, or substantially greater that 1.0, in which case this ratio in the compound film may be reduced to greater than about 0.6 and less than about 1.0. The source material may be prepared as an ink from particles in powder form. The oxide-containing particles may include a dopant, as may the compound film. Compound films including a Group IIB-IVA-VA compound may be substituted using appropriate substitutions in the method. The method, also, is applicable to fabrication of solar cells and other electronic devices.

High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome.

PubMed

Kaufmann, Markus; Schuffenhauer, Ansgar; Fruh, Isabelle; Klein, Jessica; Thiemeyer, Anke; Rigo, Pierre; Gomez-Mancilla, Baltazar; Heidinger-Millot, Valerie; Bouwmeester, Tewis; Schopfer, Ulrich; Mueller, Matthias; Fodor, Barna D; Cobos-Correa, Amanda

2015-10-01

Fragile X syndrome (FXS) is the most common form of inherited mental retardation, and it is caused in most of cases by epigenetic silencing of the Fmr1 gene. Today, no specific therapy exists for FXS, and current treatments are only directed to improve behavioral symptoms. Neuronal progenitors derived from FXS patient induced pluripotent stem cells (iPSCs) represent a unique model to study the disease and develop assays for large-scale drug discovery screens since they conserve the Fmr1 gene silenced within the disease context. We have established a high-content imaging assay to run a large-scale phenotypic screen aimed to identify compounds that reactivate the silenced Fmr1 gene. A set of 50,000 compounds was tested, including modulators of several epigenetic targets. We describe an integrated drug discovery model comprising iPSC generation, culture scale-up, and quality control and screening with a very sensitive high-content imaging assay assisted by single-cell image analysis and multiparametric data analysis based on machine learning algorithms. The screening identified several compounds that induced a weak expression of fragile X mental retardation protein (FMRP) and thus sets the basis for further large-scale screens to find candidate drugs or targets tackling the underlying mechanism of FXS with potential for therapeutic intervention. © 2015 Society for Laboratory Automation and Screening.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

Priming of plant resistance by natural compounds. Hexanoic acid as a model

PubMed Central

Aranega-Bou, Paz; de la O Leyva, Maria; Finiti, Ivan; García-Agustín, Pilar; González-Bosch, Carmen

2014-01-01

Some alternative control strategies of currently emerging plant diseases are based on the use of resistance inducers. This review highlights the recent advances made in the characterization of natural compounds that induce resistance by a priming mechanism. These include vitamins, chitosans, oligogalacturonides, volatile organic compounds, azelaic and pipecolic acid, among others. Overall, other than providing novel disease control strategies that meet environmental regulations, natural priming agents are valuable tools to help unravel the complex mechanisms underlying the induced resistance (IR) phenomenon. The data presented in this review reflect the novel contributions made from studying these natural plant inducers, with special emphasis placed on hexanoic acid (Hx), proposed herein as a model tool for this research field. Hx is a potent natural priming agent of proven efficiency in a wide range of host plants and pathogens. It can early activate broad-spectrum defenses by inducing callose deposition and the salicylic acid (SA) and jasmonic acid (JA) pathways. Later it can prime pathogen-specific responses according to the pathogen’s lifestyle. Interestingly, Hx primes redox-related genes to produce an anti-oxidant protective effect, which might be critical for limiting the infection of necrotrophs. Our Hx-IR findings also strongly suggest that it is an attractive tool for the molecular characterization of the plant alarmed state, with the added advantage of it being a natural compound. PMID:25324848

Enolate-Forming Phloretin Pharmacophores: Hepatoprotection in an Experimental Model of Drug-Induced Toxicity.

PubMed

Geohagen, Brian C; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence; LoPachin, Richard M

2016-06-01

Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2',4',6'-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Enolate-Forming Phloretin Pharmacophores: Hepatoprotection in an Experimental Model of Drug-Induced Toxicity

PubMed Central

Geohagen, Brian C.; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence

2016-01-01

Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2′,4′,6′-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. PMID:27029584

Space Suit Survivability Enhancement NASA Research Announcement 96-OLMSA-01B: Advanced Life Support and Environmental Technologies for Human Exploration and Development of Space

NASA Technical Reports Server (NTRS)

1998-01-01

Conducted two meetings to review the project scope and develop concepts for self-sealing material compositions, Focus has been on developing concepts that would seal a penetration enough to allow the astronauts to re-enter the spacecraft within the window provided by the emergency air supply. Concepts discussed include: quilted fabrics containing a viscous flow material in the quilted cells which would seal the bladder breach when forced to flow by the internal suit pressure; a sealant impregnated felt liner which acts similar to above; and a "blousy" fibrous layer which would mechanically plug a rupture under pressure. Illustrations of the above concepts are included in the attached viewgraphs, which were used in a presentation. The most promising of these concepts will be made into prototypes for testing. ILC has developed a test fixture to test the scaling characteristics of various material layups by measuring real-time changes in pressure and make-up flow in a pressurized cylinder. Candidate viscous sealing compounds such as silicones and urethanes have been identified. These compounds will be coated on existing bladder cloth for initial tests. The most promising compounds will be integrated into the above material structures for final testing. Design and analysis of fabric weaves to improve cut and puncture resistance of the suit TMG layers is underway. Philadelphia Textile is developing a mathematical model to correlate yarn type and weave structure to cut and tear resistance. The computer mathematical modeling of the fabric failure mechanisms by Cornell University, as originally proposed, will be replaced with the above model and empirical testing methods, due to the loss of key Cornell personnel.

A photochemical kinetic model for solid dosage forms.

PubMed

Carvalho, Thiago C; La Cruz, Thomas E; Tábora, Jose E

2017-11-01

Photochemical kinetic models to describe the solution phase degradation of pharmaceutical compounds have been extensively reported, but formalisms applicable to the solid phase under polychromatic light have not received as much attention. The objective of this study was to develop a mathematical model to describe the solid state photodegradation of pharmaceutical powder materials under different area/volumetric scales and light exposure conditions. The model considered the previous formalism presented for photodegradation kinetics in solution phase with important elements applied to static powder material being irradiated with a polychromatic light source. The model also included the influence of optical phenomena (i.e. reflectance, scattering factors, etc.) by applying Beer-Lambert law to light attenuation, including effects of powder density. Drug substance and drug product intermediates (blends and tablet cores) were exposed to different light sources and intensities. The model reasonably predicted the photodegradation levels of powder beds of drug substance and drug product intermediates under white and yellow lights with intensities around 5-11kLux. Importantly, the model estimates demonstrated that the reciprocity law for photoreactions was held. Further model evaluation showed that, due to light attenuation, the powder bed is in virtual darkness at cake depths greater than 500μm. At 100μm, the photodegradation of the investigated compound is expected to be close to 100% in 10days under white fluorescent halophosphate light at 9.5kLux. For tablets, defining the volume over exposed surface area ratio is more challenging. Nevertheless, the model can consider a bracket between worst and best cases to provide a reasonable photodegradation estimate. This tool can be significantly leveraged to simulate different light exposure scenarios while assessing photostability risk in order to define appropriate control strategy in manufacturing. Copyright © 2017 Elsevier B.V. All rights reserved.

Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

PubMed

Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

2012-08-01

The discovery of new and more potent anti-cancer agents constitutes one of the most active fields of research in chemotherapy. Colorectal cancer (CRC) is one of the most studied cancers because of its high prevalence and number of deaths. In the current pharmaceutical design of more efficient anti-CRC drugs, the use of methodologies based on Chemoinformatics has played a decisive role, including Quantitative-Structure-Activity Relationship (QSAR) techniques. However, until now, there is no methodology able to predict anti-CRC activity of compounds against more than one CRC cell line, which should constitute the principal goal. In an attempt to overcome this problem we develop here the first multi-target (mt) approach for the virtual screening and rational in silico discovery of anti-CRC agents against ten cell lines. Here, two mt-QSAR classification models were constructed using a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors while the second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted from the molecules and their contributions to anti-CRC activity were calculated using mt-QSAR-LDA model. Several fragments were identified as potential substructural features responsible for the anti-CRC activity and new molecules designed from those fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-CRC agents. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identification of natural products with neuronal and metabolic benefits through autophagy induction.

PubMed

Fan, Yuying; Wang, Nan; Rocchi, Altea; Zhang, Weiran; Vassar, Robert; Zhou, Yifa; He, Congcong

2017-01-02

Autophagy is a housekeeping lysosomal degradation pathway important for cellular survival, homeostasis and function. Various disease models have shown that upregulation of autophagy may be beneficial to combat disease pathogenesis. However, despite several recently reported small-molecule screens for synthetic autophagy inducers, natural chemicals of diverse structures and functions have not been included in the synthetic libraries, and characterization of their roles in autophagy has been lacking. To discover novel autophagy-regulating compounds and study their therapeutic mechanisms, we used analytic chemistry approaches to isolate natural phytochemicals from a reservoir of medicinal plants used in traditional remedies. From this pilot plant metabolite library, we identified several novel autophagy-inducing phytochemicals, including Rg2. Rg2 is a steroid glycoside chemical that activates autophagy in an AMPK-ULK1-dependent and MTOR-independent manner. Induction of autophagy by Rg2 enhances the clearance of protein aggregates in a cell-based model, improves cognitive behaviors in a mouse model of Alzheimer disease, and prevents high-fat diet-induced insulin resistance. Thus, we discovered a series of autophagy-inducing phytochemicals from medicinal plants, and found that one of the compounds Rg2 mediates metabolic and neurotrophic effects dependent on activation of the autophagy pathway. These findings may help explain how medicinal plants exert the therapeutic functions against metabolic diseases.

Charge-dependent non-bonded interaction methods for use in quantum mechanical modeling of condensed phase reactions

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.

Molecular modeling and computer simulation techniques can provide detailed insight into biochemical phenomena. This dissertation describes the development, implementation and parameterization of two methods for the accurate modeling of chemical reactions in aqueous environments, with a concerted scientific effort towards the inclusion of charge-dependent non-bonded non-electrostatic interactions into currently used computational frameworks. The first of these models, QXD, modifies interactions in a hybrid quantum mechanical/molecular (QM/MM) mechanical framework to overcome the current limitations of 'atom typing' QM atoms; an inaccurate and non-intuitive practice for chemically active species as these static atom types are dictated by the local bonding and electrostatic environment of the atoms they represent, which will change over the course of the simulation. The efficacy QXD model is demonstrated using a specific reaction parameterization (SRP) of the Austin Model 1 (AM1) Hamiltonian by simultaneously capturing the reaction barrier for chloride ion attack on methylchloride in solution and the solvation free energies of a series of compounds including the reagents of the reaction. The second, VRSCOSMO, is an implicit solvation model for use with the DFTB3/3OB Hamiltonian for biochemical reactions; allowing for accurate modeling of ionic compound solvation properties while overcoming the discontinuous nature of conventional PCM models when chemical reaction coordinates. The VRSCOSMO model is shown to accurately model the solvation properties of over 200 chemical compounds while also providing smooth, continuous reaction surfaces for a series of biologically motivated phosphoryl transesterification reactions. Both of these methods incorporate charge-dependent behavior into the non-bonded interactions variationally, allowing the 'size' of atoms to change in meaningful ways with respect to changes in local charge state, as to provide an accurate, predictive and transferable models for the interactions between the quantum mechanical system and their solvated surroundings.

Semiconductor millimeter wavelength electronics

NASA Astrophysics Data System (ADS)

Rosenbaum, F. J.

1985-12-01

This final report summarizes the results of research carried out on topics in millimeter wavelength semiconductor electronics under an ONR Selected Research Opportunity program. Study areas included III-V compound semiconductor growth and characterization, microwave and millimeter wave device modeling, fabrication and testing, and the development of new device concepts. A new millimeter wave mixer and detector, the Gap diode was invented. Topics reported on include ballistic transport, Zener oscillations, impurities in GaAs, electron velocity-electric field calculation and measurements, etc., calculations.

Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells

PubMed Central

2011-01-01

Background Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics. PMID:21418624

Docking model of the nicotinic acetylcholine receptor and nitromethylene neonicotinoid derivatives with a longer chiral substituent and their biological activities.

PubMed

Nagaoka, Hikaru; Nishiwaki, Hisashi; Kubo, Takuya; Akamatsu, Miki; Yamauchi, Satoshi; Shuto, Yoshihiro

2015-02-15

In the present study, nitromethylene neonicotinoid derivatives possessing substituents that contain a sulfur atom, oxygen atom or aromatic ring at position 5 on the imidazolidine ring were synthesized to evaluate their affinity for the nicotinic acetylcholine receptor (nAChR) and their insecticidal activity against adult female houseflies. Comparing the receptor affinity of the alkylated derivative with the receptor affinity of compounds possessing either ether or thioether groups revealed that conversion of the carbon atom to a sulfur atom did not influence the receptor affinity, whereas conversion to an oxygen atom was disadvantageous for the receptor affinity. The receptor affinity of compounds possessing a benzyl or phenyl group was lower than that of the unsubstituted compound. Analysis of the three-dimensional quantitative structure-activity relationship using comparative molecular field analysis demonstrated that steric hindrance of the receptor should exist around the C3 of an n-butyl group attached at position 5 on the imidazolidine ring. A docking study of the nAChR-ligand model suggested that the ligand-binding region expands as the length of the substituent increases by brushing against the amino acids that form the binding region. The insecticidal activity of the compounds was positively correlated with the receptor affinity by considering logP and the number of heteroatoms, including sulfur and oxygen atoms, in the substituents, suggesting that the insecticidal activity is influenced by the receptor affinity, hydrophobicity, and metabolic stability of the compounds. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-aided insights into receptor-ligand interaction for novel 5-arylhydantoin derivatives as serotonin 5-HT7 receptor agents with antidepressant activity.

PubMed

Kucwaj-Brysz, Katarzyna; Kurczab, Rafał; Jastrzębska-Więsek, Magdalena; Żesławska, Ewa; Satała, Grzegorz; Nitek, Wojciech; Partyka, Anna; Siwek, Agata; Jankowska, Agnieszka; Wesołowska, Anna; Kieć-Kononowicz, Katarzyna; Handzlik, Jadwiga

2018-03-10

This paper presents a computer-aided insight into the receptor-ligand interaction for novel analogs of the lead structure 5-(4-fluorophenyl)-3-(2-hydroxy-3-(4-(2-methoxyphenyl)piperazin-1-yl)propyl)-5-methylimidazolidine-2,4-dione (1, MF-8), as part of the search for potent and selective serotonin 5-HT 7 receptor (5-HT 7 R) agents. New hydantoin derivatives (4-19) were designed and synthesized. For 5-phenyl-3-(2-hydroxy-3-(4-(2-ethoxyphenyl)piperazin-1-yl)propyl)-5-methylimidazolidine-2,4-dione (4), its crystal structure was determined experimentally. Molecular modeling studies were performed, including both pharmacophore and structure-based approaches. New compounds were investigated in radioligand binding assays (RBA) for their affinity toward 5-HT 7 R and selectivity over 5-HT 1A R, dopamine D 2 R and α 1 -, α 2 -and β-adrenoceptors. Selected compounds (5-8) were assessed for their antidepressant and anxiolytic effects in vivo in mice. Most of the tested compounds displayed potent affinity and selectivity for 5-HT 7 R in RBA, in particular seven compounds (4, 5, 7, 8 and 10-12,K i  ≤ 10 nM). Antidepressant-like activity in vivo for all tested compounds (5-8) was confirmed. SAR analysis based on both crystallography-supported molecular modeling and RBA results indicated that mono-phenyl substituents at both hydantoin and piperazine are more favorable for 5-HT 7 R affinity than the di-phenyl ones. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Photovoltaic Device Including A Boron Doping Profile In An I-Type Layer

DOEpatents

Yang, Liyou

1993-10-26

A photovoltaic cell for use in a single junction or multijunction photovoltaic device, which includes a p-type layer of a semiconductor compound including silicon, an i-type layer of an amorphous semiconductor compound including silicon, and an n-type layer of a semiconductor compound including silicon formed on the i-type layer. The i-type layer including an undoped first sublayer formed on the p-type layer, and a boron-doped second sublayer formed on the first sublayer.

ESTIMATING TRANSPORT AND DEPOSITION OF A SEMI-VOLATILE COMPOUND WITH A REGIONAL PHOTOCHEMICAL MODEL

EPA Science Inventory

To simulate the fate of compounds that are considered semi-volatile and toxic, we have modified a model for regional particulate matter. Our changes introduce a semi-volatile compound into the atmosphere as gaseous emissions from an area source. Once emitted, the gas can transf...

Effects of structure on the interactions between five natural antimicrobial compounds and phospholipids of bacterial cell membrane on model monolayers

USDA-ARS?s Scientific Manuscript database

Monolayers composed of bacterial phospholipids were used as model membranes to study interactions of naturally occurring phenolic compounds 2,5-dihydroxybenzaldehyde, 2-hydroxy-5-methoxybenzaldehyde and the plant essential oil compounds carvacrol, cinnamaldehyde, and geraniol, previously found to be...

Modeling long-term uptake and re-volatilization of semi-volatile organic compounds (SVOCs) across the soil-atmosphere interface.

PubMed

Bao, Zhongwen; Haberer, Christina; Maier, Uli; Beckingham, Barbara; Amos, Richard T; Grathwohl, Peter

2015-12-15

Soil-atmosphere exchange is important for the environmental fate and atmospheric transport of many semi-volatile organic compounds (SVOCs). This study focuses on modeling the vapor phase exchange of semi-volatile hydrophobic organic pollutants between soil and the atmosphere using the multicomponent reactive transport code MIN3P. MIN3P is typically applied to simulate aqueous and vapor phase transport and reaction processes in the subsurface. We extended the code to also include an atmospheric boundary layer where eddy diffusion takes place. The relevant processes and parameters affecting soil-atmosphere exchange were investigated in several 1-D model scenarios and at various time scales (from years to centuries). Phenanthrene was chosen as a model compound, but results apply for other hydrophobic organic compounds as well. Gaseous phenanthrene was assumed to be constantly supplied to the system during a pollution period and a subsequent regulation period (with a 50% decline in the emission rate). Our results indicate that long-term soil-atmosphere exchange of phenanthrene is controlled by the soil compartment - re-volatilization thus depends on soil properties. A sensitivity analysis showed that accumulation and transport in soils in the short term is dominated by diffusion, whereas in the long term groundwater recharge and biodegradation become relevant. As expected, sorption causes retardation and slows down transport and biodegradation. If atmospheric concentration is reduced (e.g. after environmental regulations), re-volatilization from soil to the atmosphere occurs only for a relatively short time period. Therefore, the model results demonstrate that soils generally are sinks for atmospheric pollutants. The atmospheric boundary layer is only relevant for time scales of less than one month. The extended MIN3P code can also be applied to simulate fluctuating concentrations in the atmosphere, for instance due to temperature changes in the topsoil. Copyright © 2015. Published by Elsevier B.V.

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.

Chemistry Experiments

NASA Technical Reports Server (NTRS)

Brasseur, Guy; Remsberg, Ellis; Purcell, Patrick; Bhatt, Praful; Sage, Karen H.; Brown, Donald E.; Scott, Courtney J.; Ko, Malcolm K. W.; Tie, Xue-Xi; Huang, Theresa

1999-01-01

The purpose of the chemistry component of the model comparison is to assess to what extent differences in the formulation of chemical processes explain the variance between model results. Observed concentrations of chemical compounds are used to estimate to what degree the various models represent realistic situations. For readability, the materials for the chemistry experiment are reported in three separate sections. This section discussed the data used to evaluate the models in their simulation of the source gases and the Nitrogen compounds (NO(y)) and Chlorine compounds (Cl(y)) species.

Design new P-glycoprotein modulators based on molecular docking and CoMFA study of α, β-unsaturated carbonyl-based compounds and oxime analogs as anticancer agents

NASA Astrophysics Data System (ADS)

Sepehri, Bakhtyar; Ghavami, Raouf

2017-02-01

In this research, molecular docking and CoMFA were used to determine interactions of α, β-unsaturated carbonyl-based compounds and oxime analogs with P-glycoprotein and prediction of their activity. Molecular docking study shown these molecules establish strong Van der Waals interactions with side chain of PHE-332, PHE-728 and PHE-974. Based on the effect of component numbers on squared correlation coefficient for cross validation tests (including leave-one-out and leave-many-out), CoMFA models with five components were built to predict pIC50 of molecules in seven cancer cell lines (including Panc-1 (pancreas cancer cell line), PaCa-2 (pancreatic carcinoma cell line), MCF-7 (breast cancer cell line), A-549 (epithelial), HT-29 (colon cancer cell line), H-460 (lung cancer cell line), PC-3 (prostate cancer cell line)). R2 values for training and test sets were in the range of 0.94-0.97 and 0.84 to 0.92, respectively, and for LOO and LMO cross validation test, q2 values were in the range of 0.75-0.82 and 0.65 to 0.73, respectively. Based on molecular docking results and extracted steric and electrostatic contour maps for CoMFA models, four new molecules with higher activity with respect to the most active compound in data set were designed.

In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin

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

Thorsteinson, Nels; Ban, Fuqiang; Santos-Filho, Osvaldo

2009-01-01

Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We alsomore » screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [{sup 3}H]5{alpha}-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 {mu}M concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost.« less

Organic compounds in Elm Fork Trinity River water used for public supply near Carrollton, Texas, 2002-05

USGS Publications Warehouse

Ging, Patricia B.; Delzer, Gregory C.; Hamilton, Pixie A.

2009-01-01

Organic compounds studied in this U.S. Geological Survey (USGS) assessment generally are man-made, including pesticides, solvents, gasoline hydrocarbons, personal-care and domestic-use products, refrigerants, and propellants. A total of 103 of 277 compounds were detected at least once among the 30 samples of source water for a community water system on the Elm Fork Trinity River near Carrollton, Texas, collected approximately monthly during 2002-05. The diversity of compounds detected indicates a variety of different sources and uses (including wastewater discharge, industrial, agricultural, domestic, and others) and different pathways (including overland runoff and groundwater discharge) to drinking-water supplies. Nine compounds were detected year-round in source-water samples, including chloroform, methyl tert-butyl ether (MTBE), and selected herbicide compounds commonly used in the Trinity River Basin and in other urban areas across the United States. About 90 percent of the 42 compounds detected most frequently in source water (in at least 20 percent of the samples) also were detected most frequently in finished water (after treatment but before distribution). Concentrations for all detected compounds in source and finished water generally were less than 0.1 microgram per liter and always less than human-health benchmarks, which are available for about one-half of the detected compounds.

Development of a model and computer code to describe solar grade silicon production processes

NASA Technical Reports Server (NTRS)

Srivastava, R.; Gould, R. K.

1979-01-01

Mathematical models, and computer codes based on these models were developed which allow prediction of the product distribution in chemical reactors in which gaseous silicon compounds are converted to condensed phase silicon. The reactors to be modeled are flow reactors in which silane or one of the halogenated silanes is thermally decomposed or reacted with an alkali metal, H2 or H atoms. Because the product of interest is particulate silicon, processes which must be modeled, in addition to mixing and reaction of gas-phase reactants, include the nucleation and growth of condensed Si via coagulation, condensation, and heterogeneous reaction.

Interaction of Isoflavones with the BCRP/ABCG2 Drug Transporter

PubMed Central

Bircsak, Kristin M; Aleksunes, Lauren M

2015-01-01

This review will provide a comprehensive overview of the interactions between dietary isoflavones and the ATP-binding cassette (ABC) G2 efflux transporter, which is also named the breast cancer resistance protein (BCRP). Expressed in a variety of organs including the liver, kidneys, intestine, and placenta, BCRP mediates the disposition and excretion of numerous endogenous chemicals and xenobiotics. Isoflavones are a class of naturally-occurring compounds that are found at high concentrations in commonly consumed foods and dietary supplements. A number of isoflavones, including genistein and daidzein and their metabolites, interact with BCRP as substrates, inhibitors, and/or modulators of gene expression. To date, a variety of model systems have been employed to study the ability of isoflavones to serve as substrates and inhibitors of BCRP; these include whole cells, inverted plasma membrane vesicles, in situ organ perfusion, as well as in vivo rodent and sheep models. Evidence suggests that BCRP plays a role in mediating the disposition of isoflavones and in particular, their conjugated forms. Furthermore, as inhibitors, these compounds may aid in reversing multidrug resistance and sensitizing cancer cells to chemotherapeutic drugs. This review will also highlight the consequences of altered BCRP expression and/or function on the pharmacokinetics and toxicity of chemicals following isoflavone exposure. PMID:26179608

Design, synthesis, molecular modeling and biological evaluation of novel 2,3-dihydrophthalazine-1,4-dione derivatives as potential anticonvulsant agents

NASA Astrophysics Data System (ADS)

El-Helby, Abdel Ghany A.; Ayyad, Rezk R.; Sakr, Helmy M.; Abdelrahim, Adel S.; El-Adl, K.; Sherbiny, Farag S.; Eissa, Ibrahim H.; Khalifa, Mohamed M.

2017-02-01

In view of their expected anticonvulsant activity, some novel derivatives of 2,3-dihydrophthalazine-1,4-dione 4-22 were designed, synthesized and evaluated using pentylenetetrazole (PTZ) and picrotoxin as convulsion-inducing models. Moreover, the most active compounds were tested against electrical induced convulsion using maximal electroshock (MES) models of seizures. Most of the tested compounds showed considerable anticonvulsant activity in at least one of the anticonvulsant tests. Compounds 13 and 14g were proved to be the most potent compounds of this series with relatively low toxicity in the median lethal dose test when compared with the reference drug. Molecular modeling studies were done to verify the biological activity. The obtained results showed that the most potent compounds could be useful as a template for future design, optimization, and investigation to produce more active analogues.

Rebelling against the (Insulin) Resistance: A Review of the Proposed Insulin-Sensitizing Actions of Soybeans, Chickpeas, and Their Bioactive Compounds

PubMed Central

Zahradka, Peter

2018-01-01

Insulin resistance is a major risk factor for diseases such as type 2 diabetes and metabolic syndrome. Current methods for management of insulin resistance include pharmacological therapies and lifestyle modifications. Several clinical studies have shown that leguminous plants such as soybeans and pulses (dried beans, dried peas, chickpeas, lentils) are able to reduce insulin resistance and related type 2 diabetes parameters. However, to date, no one has summarized the evidence supporting a mechanism of action for soybeans and pulses that explains their ability to lower insulin resistance. While it is commonly assumed that the biological activities of soybeans and pulses are due to their antioxidant activities, these bioactive compounds may operate independent of their antioxidant properties and, thus, their ability to potentially improve insulin sensitivity via alternative mechanisms needs to be acknowledged. Based on published studies using in vivo and in vitro models representing insulin resistant states, the proposed mechanisms of action for insulin-sensitizing actions of soybeans, chickpeas, and their bioactive compounds include increasing glucose transporter-4 levels, inhibiting adipogenesis by down-regulating peroxisome proliferator-activated receptor-γ, reducing adiposity, positively affecting adipokines, and increasing short-chain fatty acid-producing bacteria in the gut. Therefore, this review will discuss the current evidence surrounding the proposed mechanisms of action for soybeans and certain pulses, and their bioactive compounds, to effectively reduce insulin resistance. PMID:29601521

Diversity-oriented synthesis yields novel multistage antimalarial inhibitors.

PubMed

Kato, Nobutaka; Comer, Eamon; Sakata-Kato, Tomoyo; Sharma, Arvind; Sharma, Manmohan; Maetani, Micah; Bastien, Jessica; Brancucci, Nicolas M; Bittker, Joshua A; Corey, Victoria; Clarke, David; Derbyshire, Emily R; Dornan, Gillian L; Duffy, Sandra; Eckley, Sean; Itoe, Maurice A; Koolen, Karin M J; Lewis, Timothy A; Lui, Ping S; Lukens, Amanda K; Lund, Emily; March, Sandra; Meibalan, Elamaran; Meier, Bennett C; McPhail, Jacob A; Mitasev, Branko; Moss, Eli L; Sayes, Morgane; Van Gessel, Yvonne; Wawer, Mathias J; Yoshinaga, Takashi; Zeeman, Anne-Marie; Avery, Vicky M; Bhatia, Sangeeta N; Burke, John E; Catteruccia, Flaminia; Clardy, Jon C; Clemons, Paul A; Dechering, Koen J; Duvall, Jeremy R; Foley, Michael A; Gusovsky, Fabian; Kocken, Clemens H M; Marti, Matthias; Morningstar, Marshall L; Munoz, Benito; Neafsey, Daniel E; Sharma, Amit; Winzeler, Elizabeth A; Wirth, Dyann F; Scherer, Christina A; Schreiber, Stuart L

2016-10-20

Antimalarial drugs have thus far been chiefly derived from two sources-natural products and synthetic drug-like compounds. Here we investigate whether antimalarial agents with novel mechanisms of action could be discovered using a diverse collection of synthetic compounds that have three-dimensional features reminiscent of natural products and are underrepresented in typical screening collections. We report the identification of such compounds with both previously reported and undescribed mechanisms of action, including a series of bicyclic azetidines that inhibit a new antimalarial target, phenylalanyl-tRNA synthetase. These molecules are curative in mice at a single, low dose and show activity against all parasite life stages in multiple in vivo efficacy models. Our findings identify bicyclic azetidines with the potential to both cure and prevent transmission of the disease as well as protect at-risk populations with a single oral dose, highlighting the strength of diversity-oriented synthesis in revealing promising therapeutic targets.

Predicting Chemically Induced Duodenal Ulcer and Adrenal Necrosis with Classification Trees

NASA Astrophysics Data System (ADS)

Giampaolo, Casimiro; Gray, Andrew T.; Olshen, Richard A.; Szabo, Sandor

1991-07-01

Binary tree-structured statistical classification algorithms and properties of 56 model alkyl nucleophiles were brought to bear on two problems of experimental pharmacology and toxicology. Each rat of a learning sample of 745 was administered one compound and autopsied to determine the presence of duodenal ulcer or adrenal hemorrhagic necrosis. The cited statistical classification schemes were then applied to these outcomes and 67 features of the compounds to ascertain those characteristics that are associated with biologic activity. For predicting duodenal ulceration, dipole moment, melting point, and solubility in octanol are particularly important, while for predicting adrenal necrosis, important features include the number of sulfhydryl groups and double bonds. These methods may constitute inexpensive but powerful ways to screen untested compounds for possible organ-specific toxicity. Mechanisms for the etiology and pathogenesis of the duodenal and adrenal lesions are suggested, as are additional avenues for drug design.

Phytovolatilization of Organic Contaminants.

PubMed

Limmer, Matt; Burken, Joel

2016-07-05

Plants can interact with a variety of organic compounds, and thereby affect the fate and transport of many environmental contaminants. Volatile organic compounds may be volatilized from stems or leaves (direct phytovolatilization) or from soil due to plant root activities (indirect phytovolatilization). Fluxes of contaminants volatilizing from plants are important across scales ranging from local contaminant spills to global fluxes of methane emanating from ecosystems biochemically reducing organic carbon. In this article past studies are reviewed to clearly differentiate between direct- and indirect-phytovolatilization and we discuss the plant physiology driving phytovolatilization in different ecosystems. Current measurement techniques are also described, including common difficulties in experimental design. We also discuss reports of phytovolatilization in the literature, finding that compounds with low octanol-air partitioning coefficients are more likely to be phytovolatilized (log KOA < 5). Reports of direct phytovolatilization at field sites compare favorably to model predictions. Finally, future research needs are presented that could better quantify phytovolatilization fluxes at field scale.