Analysis and control of the photon beam position at PLS-II

PubMed Central

Ko, J.; Kim, I.-Y.; Kim, C.; Kim, D.-T.; Huang, J.-Y.; Shin, S.

2016-01-01

At third-generation light sources, the photon beam position stability is a critical issue for user experiments. In general, photon beam position monitors are developed to detect the real photon beam position, and the position is controlled by a feedback system in order to maintain the reference photon beam position. At Pohang Light Source II, a photon beam position stability of less than 1 µm r.m.s. was achieved for a user service period in the beamline, where the photon beam position monitor is installed. Nevertheless, a detailed analysis of the photon beam position data was necessary in order to ensure the performance of the photon beam position monitor, since it can suffer from various unknown types of noise, such as background contamination due to upstream or downstream dipole radiation, and undulator gap dependence. This paper reports the results of a start-to-end study of the photon beam position stability and a singular value decomposition analysis to confirm the reliability of the photon beam position data. PMID:26917132

Error propagation of partial least squares for parameters optimization in NIR modeling.

PubMed

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Error propagation of partial least squares for parameters optimization in NIR modeling

NASA Astrophysics Data System (ADS)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Modeling the interaction of a heavily beam loaded SRF cavity with its low-level RF feedback loops

NASA Astrophysics Data System (ADS)

Liu, Zong-Kai; Wang, Chaoen; Chang, Lung-Hai; Yeh, Meng-Shu; Chang, Fu-Yu; Chang, Mei-Hsia; Chang, Shian-Wen; Chen, Ling-Jhen; Chung, Fu-Tsai; Lin, Ming-Chyuan; Lo, Chih-Hung; Yu, Tsung-Chi

2018-06-01

A superconducting radio frequency (SRF) cavity provides superior stability to power high intensity light sources and can suppress coupled-bunch instabilities due to its smaller impedance for higher order modes. Because of these features, SRF cavities are commonly used for modern light sources, such as the TLS, CLS, DLS, SSRF, PLS-II, TPS, and NSLS-II, with an aggressive approach to operate the light sources at high beam currents. However, operating a SRF cavity at high beam currents may result with unacceptable stability problems of the low level RF (LLRF) system, due to drifts of the cavity resonant frequency caused by unexpected perturbations from the environment. As the feedback loop gets out of control, the cavity voltage may start to oscillate with a current-dependent characteristic frequency. Such situations can cause beam abort due to the activation of the interlock protection system, i.e. false alarm of quench detection. This malfunction of the light source reduces the reliability of SRF operation. Understanding this unstable mechanism to prevent its appearance becomes a primary task in the pursuit of highly reliable SRF operation. In this paper, a Pedersen model, including the response of the LLRF system, was used to simulate the beam-cavity interaction of a SRF cavity under heavy beam loading. Causes for the onset of instability at high beam current will be discussed as well as remedies to assure the design of a stable LLRF system.

Transmission versus reflectance spectroscopy for quantitation.

PubMed

Gardner, Craig M

2018-01-01

The objective of this work was to compare the accuracy of analyte concentration estimation when using transmission versus diffuse reflectance spectroscopy of a scattering medium. Monte Carlo ray tracing of light through the medium was used in conjunction with pure component absorption spectra and Beer-Lambert absorption along each ray's pathlength to generate matched sets of pseudoabsorbance spectra, containing water and six analytes present in skin. PLS regression models revealed an improvement in accuracy when using transmission compared to reflectance for a range of medium thicknesses and instrument noise levels. An analytical expression revealed the source of the accuracy degradation with reflectance was due both to the reduced collection efficiency for a fixed instrument etendue and to the broad pathlength distribution that detected light travels in the medium before exiting from the incident side. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Development of new S-band RF window for stable high-power operation in linear accelerator RF system

NASA Astrophysics Data System (ADS)

Joo, Youngdo; Lee, Byung-Joon; Kim, Seung-Hwan; Kong, Hyung-Sup; Hwang, Woonha; Roh, Sungjoo; Ryu, Jiwan

2017-09-01

For stable high-power operation, a new RF window is developed in the S-band linear accelerator (Linac) RF systems of the Pohang Light Source-II (PLS-II) and the Pohang Accelerator Laboratory X-ray Free-Electron Laser (PAL-XFEL). The new RF window is designed to mitigate the strength of the electric field at the ceramic disk and also at the waveguide-cavity coupling structure of the conventional RF window. By replacing the pill-box type cavity in the conventional RF window with an overmoded cavity, the electric field component perpendicular to the ceramic disk that caused most of the multipacting breakdowns in the ceramic disk was reduced by an order of magnitude. The reduced electric field at the ceramic disk eliminated the Ti-N coating process on the ceramic surface in the fabrication procedure of the new RF window, preventing the incomplete coating from spoiling the RF transmission and lowering the fabrication cost. The overmoded cavity was coupled with input and output waveguides through dual side-wall coupling irises to reduce the electric field strength at the waveguide-cavity coupling structure and the possibility of mode competitions in the overmoded cavity. A prototype of the new RF window was fabricated and fully tested with the Klystron peak input power, pulse duration and pulse repetition rate of 75 MW, 4.5 μs and 10 Hz, respectively, at the high-power test stand. The first mass-produced new RF window installed in the PLS-II Linac is running in normal operation mode. No fault is reported to date. Plans are being made to install the new RF window to all S-band accelerator RF modules of the PLS-II and PAL-XFEL Linacs. This new RF window may be applied to the output windows of S-band power sources like Klystron as wells as the waveguide windows of accelerator facilities which operate in S-band.

Fast and simultaneously determination of light and heavy rare earth elements in monazite using combination of ultraviolet-visible spectrophotometry and multivariate analysis

NASA Astrophysics Data System (ADS)

Anggraeni, Anni; Arianto, Fernando; Mutalib, Abdul; Pratomo, Uji; Bahti, Husein H.

2017-05-01

Rare Earth Elements (REE) are elements that a lot of function for life, such as metallurgy, optical devices, and manufacture of electronic devices. Sources of REE is present in the mineral, in which each element has similar properties. Currently, to determining the content of REE is used instruments such as ICP-OES, ICP-MS, XRF, and HPLC. But in each instruments, there are still have some weaknesses. Therefore we need an alternative analytical method for the determination of rare earth metal content, one of them is by a combination of UV-Visible spectrophotometry and multivariate analysis, including Principal Component Analysis (PCA), Principal Component Regression (PCR), and Partial Least Square Regression (PLS). The purpose of this experiment is to determine the content of light and medium rare earth elements in the mineral monazite without chemical separation by using a combination of multivariate analysis and UV-Visible spectrophotometric methods. Training set created 22 variations of concentration and absorbance was measured using a UV-Vis spectrophotometer, then the data is processed by PCA, PCR, and PLSR. The results were compared and validated to obtain the mathematical equation with the smallest percent error. From this experiment, mathematical equation used PLS methods was better than PCR after validated, which has RMSE value for La, Ce, Pr, Nd, Gd, Sm, Eu, and Tb respectively 0.095; 0.573; 0.538; 0.440; 3.387; 1.240; 1.870; and 0.639.

Improving near-infrared prediction model robustness with support vector machine regression: a pharmaceutical tablet assay example.

PubMed

Igne, Benoît; Drennen, James K; Anderson, Carl A

2014-01-01

Changes in raw materials and process wear and tear can have significant effects on the prediction error of near-infrared calibration models. When the variability that is present during routine manufacturing is not included in the calibration, test, and validation sets, the long-term performance and robustness of the model will be limited. Nonlinearity is a major source of interference. In near-infrared spectroscopy, nonlinearity can arise from light path-length differences that can come from differences in particle size or density. The usefulness of support vector machine (SVM) regression to handle nonlinearity and improve the robustness of calibration models in scenarios where the calibration set did not include all the variability present in test was evaluated. Compared to partial least squares (PLS) regression, SVM regression was less affected by physical (particle size) and chemical (moisture) differences. The linearity of the SVM predicted values was also improved. Nevertheless, although visualization and interpretation tools have been developed to enhance the usability of SVM-based methods, work is yet to be done to provide chemometricians in the pharmaceutical industry with a regression method that can supplement PLS-based methods.

Dental Composites with Calcium / Strontium Phosphates and Polylysine.

PubMed

Panpisut, Piyaphong; Liaqat, Saad; Zacharaki, Eleni; Xia, Wendy; Petridis, Haralampos; Young, Anne Margaret

2016-01-01

This study developed light cured dental composites with added monocalcium phosphate monohydrate (MCPM), tristrontium phosphate (TSrP) and antimicrobial polylysine (PLS). The aim was to produce composites that have enhanced water sorption induced expansion, can promote apatite precipitation and release polylysine. Experimental composite formulations consisted of light activated dimethacrylate monomers combined with 80 wt% powder. The powder phase contained a dental glass with and without PLS (2.5 wt%) and/or reactive phosphate fillers (15 wt% TSrP and 10 wt% MCPM). The commercial composite, Z250, was used as a control. Monomer conversion and calculated polymerization shrinkage were assessed using FTIR. Subsequent mass or volume changes in water versus simulated body fluid (SBF) were quantified using gravimetric studies. These were used, along with Raman and SEM, to assess apatite precipitation on the composite surface. PLS release was determined using UV spectroscopy. Furthermore, biaxial flexural strengths after 24 hours of SBF immersion were obtained. Monomer conversion of the composites decreased upon the addition of phosphate fillers (from 76 to 64%) but was always higher than that of Z250 (54%). Phosphate addition increased water sorption induced expansion from 2 to 4% helping to balance the calculated polymerization shrinkage of ~ 3.4%. Phosphate addition promoted apatite precipitation from SBF. Polylysine increased the apatite layer thickness from ~ 10 to 20 μm after 4 weeks. The novel composites showed a burst release of PLS (3.7%) followed by diffusion-controlled release irrespective of phosphate addition. PLS and phosphates decreased strength from 154 MPa on average by 17% and 18%, respectively. All formulations, however, had greater strength than the ISO 4049 requirement of > 80 MPa. The addition of MCPM with TSrP promoted hygroscopic expansion, and apatite formation. These properties are expected to help compensate polymerization shrinkage and help remineralize demineralized dentin. Polylysine can be released from the composites at early time. This may kill residual bacteria.

Improved detection of highly energetic materials traces on surfaces by standoff laser-induced thermal emission incorporating neural networks

NASA Astrophysics Data System (ADS)

Figueroa-Navedo, Amanda; Galán-Freyle, Nataly Y.; Pacheco-Londoño, Leonardo C.; Hernández-Rivera, Samuel P.

2013-05-01

Terrorists conceal highly energetic materials (HEM) as Improvised Explosive Devices (IED) in various types of materials such as PVC, wood, Teflon, aluminum, acrylic, carton and rubber to disguise them from detection equipment used by military and security agency personnel. Infrared emissions (IREs) of substrates, with and without HEM, were measured to generate models for detection and discrimination. Multivariable analysis techniques such as principal component analysis (PCA), soft independent modeling by class analogy (SIMCA), partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM) and neural networks (NN) were employed to generate models, in which the emission of IR light from heated samples was stimulated using a CO2 laser giving rise to laser induced thermal emission (LITE) of HEMs. Traces of a specific target threat chemical explosive: PETN in surface concentrations of 10 to 300 ug/cm2 were studied on the surfaces mentioned. Custom built experimental setup used a CO2 laser as a heating source positioned with a telescope, where a minimal loss in reflective optics was reported, for the Mid-IR at a distance of 4 m and 32 scans at 10 s. SVM-DA resulted in the best statistical technique for a discrimination performance of 97%. PLS-DA accurately predicted over 94% and NN 88%.

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Feasibility for direct rapid energy dispersive X-ray fluorescence (EDXRF) and scattering analysis of complex matrix liquids by partial least squares.

PubMed

Angeyo, K H; Gari, S; Mustapha, A O; Mangala, J M

2012-11-01

The greatest challenge to material characterization by XRF technique is encountered in direct trace analysis of complex matrices. We exploited partial least squares (PLS) in conjunction with energy dispersive X-ray fluorescence and scattering (EDXRFS) spectrometry to rapidly (200 s) analyze lubricating oils. The PLS-EDXRFS method affords non-invasive quality assurance (QA) analysis of complex matrix liquids as it gave optimistic results for both heavy- and low-Z metal additives. Scatter peaks may further be used for QA characterization via the light elements. Copyright © 2012 Elsevier Ltd. All rights reserved.

Micro-spectroscopy on silicon wafers and solar cells

PubMed Central

2011-01-01

Micro-Raman (μRS) and micro-photoluminescence spectroscopy (μPLS) are demonstrated as valuable characterization techniques for fundamental research on silicon as well as for technological issues in the photovoltaic production. We measure the quantitative carrier recombination lifetime and the doping density with submicron resolution by μPLS and μRS. μPLS utilizes the carrier diffusion from a point excitation source and μRS the hole density-dependent Fano resonances of the first order Raman peak. This is demonstrated on micro defects in multicrystalline silicon. In comparison with the stress measurement by μRS, these measurements reveal the influence of stress on the recombination activity of metal precipitates. This can be attributed to the strong stress dependence of the carrier mobility (piezoresistance) of silicon. With the aim of evaluating technological process steps, Fano resonances in μRS measurements are analyzed for the determination of the doping density and the carrier lifetime in selective emitters, laser fired doping structures, and back surface fields, while μPLS can show the micron-sized damage induced by the respective processes. PMID:21711723

Polar lows in the Labrador Sea based on the Moravian historical collection of meteorological data in Labrador and Greenland since the mid-18th century

NASA Astrophysics Data System (ADS)

Matiu, Michael; Lüdecke, Cornelia; Newell, Dianne; Menzel, Annette

2017-04-01

Systematically recorded daily instrumental meteorological data from the Moravian Brethern mission stations located on the east coast of Labrador and southwest coast of Greenland during the 18th, 19th and 20th centuries provide a most valuable source of historical climatological data in the Subarctic region. Although the collections of original data themselves are both scattered in physical location and fragmented in their coverage of time and place, and large amounts still need to be digitized, this data provides large potential for studying climate extreme events in this remote region. In this paper, we study polar lows (PLs). They are high-latitude intense maritime cyclones with only 200 to 1000 km in diameter, a short life-time of only two days, mostly occurring in wintertime, e.g. in the Norwegian, Barents, but also Labrador and Greenland seas. Due to high wind speeds exceeding 30 m s-1, high ocean waves and heavy snow showers, they constitute a major hazard risk difficult to forecast. Published papers indicate that with future climate warming, the frequency of PLs is predicted to decrease; however, climatologies of PLs for the last 7 decades (1948-2009) based on reanalysis data and satellite remote sensing products did not indicate any change in their mean annual frequency. In our digitized long-term dataset (1846-2015) for one Moravian station at Nain, Labrador, we identified PLs as follows: If there was a drop in air pressure of at least 30hPa during 48 hours, we marked it as a preliminary event. Then, each preliminary event was checked manually to see whether additional changes in air pressure, air temperature, wind direction and wind speed matched the known textbook example. If more than two variables showed the required pattern, the preliminary event was identified as PL. Our analysis revealed an average frequency of 5.6 PLs yr-1 for 1846-1853, 5.2 PLs yr-1(1882-1913), and 4.4 PLs yr-1 (1926-1939), largely confirming long-term averages for the more recent periods 1948-2005 (4.9 PLs yr-1) as well as 1977-1994 (4.4 PLs yr-1) reported in the literature. Once more data from the historical Moravian collection is digitized, it may be checked whether there is a stable tendency of more annual PLs in the mid-19th century compared to recent numbers of this extreme event. With respect of the boundary conditions in which PLs are developing, our data from the mid-19th century cannot confirm recent findings that the occurrence of PLs is mainly associated with NAO+ phases. Due to additional concurrently operating Moravian climate stations at the eastern Labrador and southwestern Greenland coasts, the moving of PLs and PL clusters over the Labrador Sea and southern Davis Strait can be confirmed based on this unique historical subarctic climate data.

Phosphatidic Acid Synthesis in Bacteria

PubMed Central

Yao, Jiangwei; Rock, Charles O.

2012-01-01

Membrane phospholipid synthesis is a vital facet of bacterial physiology. Although the spectrum of phospholipid headgroup structures produced by bacteria is large, the key precursor to all of these molecules is phosphatidic acid (PtdOH). Glycerol-3-phosphate derived from the glycolysis via glycerol-phosphate synthase is the universal source for the glycerol backbone of PtdOH. There are two distinct families of enzymes responsible for the acylation of the 1-position of glycerol-3-phosphate. The PlsB acyltransferase was discovered in Escherichia coli, and homologs are present in many eukaryotes. This protein family primarily uses acyl-acyl carrier protein (ACP) endproducts of fatty acid synthesis as acyl donors, but may also use acyl-CoA derived from exogenous fatty acids. The second protein family, PlsY, is more widely distributed in bacteria and utilizes the unique acyl donor, acyl-phosphate, which is produced from acyl-ACP by the enzyme PlsX. The acylation of the 2-position is carried out by members of the PlsC protein family. All PlsCs use acyl-ACP as the acyl donor, although the PlsCs of the γ-proteobacteria also may use acyl-CoA. Phospholipid headgroups are precursors in the biosynthesis of other membrane-associated molecules and the diacylglycerol product of these reactions is converted to PtdOH by one of two distinct families of lipid kinases. The central importance of the de novo and recycling pathways to PtdOH in cell physiology suggest these enzymes are suitable targets for the development of antibacterial therapeutics in Gram-positive pathogens. This article is part of a Special Issue entitled Phospholipids and Phospholipid Metabolism. PMID:22981714

Simulation of two-dimensional adjustable liquid gradient refractive index (L-GRIN) microlens

NASA Astrophysics Data System (ADS)

Le, Zichun; Wu, Xiang; Sun, Yunli; Du, Ying

2017-07-01

In this paper, a two-dimensional liquid gradient refractive index (L-GRIN) microlens is designed which can be used in adjusting focusing direction and focal spot of light beam. Finite element method (FEM) is used to simulate the convection diffusion process happening in core inlet flow and cladding inlet flow. And the ray tracing method shows us the light beam focusing effect including the extrapolation of focal length and output beam spot size. When the flow rates of the core and cladding fluids are held the same between the internal and external, left and right, and upper and lower inlets, the focal length varied from 313 μm to 53.3 μm while the flow rate of liquids ranges from 500 pL/s to 10,000 pL/s. While the core flow rate is bigger than the cladding inlet flow rate, the light beam will focus on a light spot with a tunable size. By adjusting the ratio of cladding inlet flow rate including Qright/Qleft and Qup/Qdown, we get the adjustable two-dimensional focus direction rather than the one-dimensional focusing. In summary, by adjusting the flow rate of core inlet and cladding inlet, the focal length, output beam spot and focusing direction of the input light beam can be manipulated. We suppose this kind of flexible microlens can be used in integrated optics and lab-on-a-chip system.

Structure of Full-length Drosophila Cryptochrome

PubMed Central

Zoltowski, Brian D.; Vaidya, Anand T.; Top, Deniz; Widom, Joanne; Young, Michael W.; Crane, Brian R.

2011-01-01

The Cryptochrome/Photolyase (CRY/PL) family of photoreceptors mediates adaptive responses to UV and blue light exposure in all kingdoms of life 1; 2; 3; 4; 5. Whereas PLs function predominantly in DNA repair of cyclobutane pyrimidine dimers (CPDs)and 6-4 photolesions caused by UV radiation, CRYs transduce signals important for growth, development, magnetosensitivity and circadian clocks1; 2; 3; 4; 5. Despite these diverse functions, PLs/CRYs preserve a common structural fold, a dependence on flavin adenine dinucleotide (FAD) and an internal photoactivation mechanism3; 6. However, members of the CRY/PL family differ in the substrates recognized (protein or DNA), photochemical reactions catalyzed and involvement of an antenna cofactor. It is largely unknown how the animal CRYs that regulate circadian rhythms act on their substrates. CRYs contain a variable C-terminal tail that appends the conserved PL homology domain (PHD) and is important for function 7; 8; 9; 10; 11; 12. Herein, we report a 2.3 Å resolution crystal structure of Drosophila CRY with an intact C-terminus. The C-terminal helix docks in the analogous groove that binds DNA substrates in PLs. Conserved Trp536 juts into the CRY catalytic center to mimic PL recognition of DNA photolesions. The FAD anionic semiquinone found in the crystals assumes a conformation to facilitate restructuring of the tail helix. These results help reconcile the diverse functions of the CRY/PL family by demonstrating how conserved protein architecture, and photochemistry can be elaborated into a range of light-driven functions. PMID:22080955

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Rapid classification of pharmaceutical ingredients with Raman spectroscopy using compressive detection strategy with PLS-DA multivariate filters.

PubMed

Cebeci Maltaş, Derya; Kwok, Kaho; Wang, Ping; Taylor, Lynne S; Ben-Amotz, Dor

2013-06-01

Identifying pharmaceutical ingredients is a routine procedure required during industrial manufacturing. Here we show that a recently developed Raman compressive detection strategy can be employed to classify various widely used pharmaceutical materials using a hybrid supervised/unsupervised strategy in which only two ingredients are used for training and yet six other ingredients can also be distinguished. More specifically, our liquid crystal spatial light modulator (LC-SLM) based compressive detection instrument is trained using only the active ingredient, tadalafil, and the excipient, lactose, but is tested using these and various other excipients; microcrystalline cellulose, magnesium stearate, titanium (IV) oxide, talc, sodium lauryl sulfate and hydroxypropyl cellulose. Partial least squares discriminant analysis (PLS-DA) is used to generate the compressive detection filters necessary for fast chemical classification. Although the filters used in this study are trained on only lactose and tadalafil, we show that all the pharmaceutical ingredients mentioned above can be differentiated and classified using PLS-DA compressive detection filters with an accumulation time of 10ms per filter. Copyright © 2013 Elsevier B.V. All rights reserved.

Involvement of PlsX and the acyl-phosphate dependent sn-glycerol-3-phosphate acyltransferase PlsY in the initial stage of glycerolipid synthesis in Bacillus subtilis.

PubMed

Hara, Yoshinori; Seki, Masahide; Matsuoka, Satoshi; Hara, Hiroshi; Yamashita, Atsushi; Matsumoto, Kouji

2008-12-01

The gene responsible for the first acylation of sn-glycerol-3-phosphate (G3P) in Bacillus subtilis has not yet been determined with certainty. The product of this first acylation, lysophosphatidic acid (LPA), is subsequently acylated again to form phosphatidic acid (PA), the primary precursor to membrane glycerolipids. A novel G3P acyltransferase (GPAT), the gene product of plsY, which uses acyl-phosphate formed by the plsX gene product, has recently been found to synthesize LPA in Streptococcus pneumoniae. We found that in B. subtilis growth arrests after repression of either a plsY homologue or a plsX homologue were overcome by expression of E. coli plsB, which encodes an acyl-acylcarrier protein (acyl-ACP)-dependent GPAT, although in the case of plsX repression a high level of plsB expression was required. B. subtilis has, therefore, a capability to use the acyl-ACP dependent GPAT of PlsB. Simultaneous expression of plsY and plsX suppressed the glycerol requirement of a strict glycerol auxotrophic derivative of the E. coli plsB26 mutant, although either one alone did not. Membrane fractions from B. subtilis cells catalyzed palmitoylphosphate-dependent acylation of [14C]-labeled G3P to synthesize [14C]-labeled LPA, whereas those from DeltaplsY cells did not. The results indicate unequivocally that PlsY is an acyl-phosphate dependent GPAT. Expression of plsX corrected the glycerol auxotrophy of a DeltaygiH (the deleted allele of an E. coli homologue of plsY) derivative of BB26-36 (plsB26 plsX50), suggesting an essential role of plsX other than substrate supply for acyl-phosphate dependent LPA synthesis. Two-hybrid examinations suggested that PlsY is associated with PlsX and that each may exist in multimeric form.

Recombinant plasmids for encoding restriction enzymes DpnI and DpnII of streptococcus pneumontae

DOEpatents

Lacks, Sanford A.

1990-01-01

Chromosomal DNA cassettes containing genes encoding either the DpnI or DpnII restriction endonucleases from Streptococcus pneumoniae are cloned into a streptococcal vector, pLS101. Large amounts of the restriction enzymes are produced by cells containing the multicopy plasmids, pLS202 and pLS207, and their derivatives pLS201, pLS211, pLS217, pLS251 and pLS252.

Recombinant plasmids for encoding restriction enzymes DpnI and DpnII of Streptococcus pneumontae

DOEpatents

Lacks, S.A.

1990-10-02

Chromosomal DNA cassettes containing genes encoding either the DpnI or DpnII restriction endonucleases from Streptococcus pneumoniae are cloned into a streptococcal vector, pLS101. Large amounts of the restriction enzymes are produced by cells containing the multicopy plasmids, pLS202 and pLS207, and their derivatives pLS201, pLS211, pLS217, pLS251 and pLS252. 9 figs.

Performance of one hundred watt HVM LPP-EUV source

NASA Astrophysics Data System (ADS)

Mizoguchi, Hakaru; Nakarai, Hiroaki; Abe, Tamotsu; Nowak, Krzysztof M.; Kawasuji, Yasufumi; Tanaka, Hiroshi; Watanabe, Yukio; Hori, Tsukasa; Kodama, Takeshi; Shiraishi, Yutaka; Yanagida, Tatsuya; Soumagne, Georg; Yamada, Tsuyoshi; Yamazaki, Taku; Okazaki, Shinji; Saitou, Takashi

2015-03-01

We have been developing CO2-Sn-LPP EUV light source which is the most promising solution as the 13.5nm high power light source for HVM EUVL. Unique and original technologies such as: combination of pulsed CO2 laser and Sn droplets, dual wavelength laser pulses shooting, and mitigation with magnetic field, have been developed in Gigaphoton Inc. The theoretical and experimental data have clearly showed the advantage of our proposed strategy. Based on these data we are developing first practical source for HVM - "GL200E". This data means 250W EUV power will be able to realize around 20kW level pulsed CO2 laser. We have reported engineering data from our recent test such around 43W average clean power, CE=2.0%, with 100kHz operation and other data 19). We have already finished preparation of higher average power CO2 laser more than 20kW at output power cooperate with Mitsubishi Electric Corporation 14). Recently we achieved 92W with 50kHz, 50% duty cycle operation 20). We have reported component technology progress of EUV light source system. We report promising experimental data and result of simulation of magnetic mitigation system in Proto #1 system. We demonstrated several data with Proto #2 system: (1) emission data of 140W in burst under 70kHz 50% duty cycle during 10 minutes. (2) emission data of 118W in burst under 60kHz 70% duty cycle during 10 minutes. (3) emission data of 42W in burst under 20kHz 50% duty cycle (10000pls/0.5ms OFF) during 3 hours (110Mpls). Also we report construction of Pilot #1 system. Final target is week level operation with 250W EUV power with CE=4%, more than 27kW CO2 laser power by the end of Q2 of 2015.

Seasonal forecasting of high wind speeds over Western Europe

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Holt, T.

2003-04-01

As financial losses associated with extreme weather events escalate, there is interest from end users in the forestry and insurance industries, for example, in the development of seasonal forecasting models with a long lead time. This study uses exceedences of the 90th, 95th, and 99th percentiles of daily maximum wind speed over the period 1958 to present to derive predictands of winter wind extremes. The source data is the 6-hourly NCEP Reanalysis gridded surface wind field. Predictor variables include principal components of Atlantic sea surface temperature and several indices of climate variability, including the NAO and SOI. Lead times of up to a year are considered, in monthly increments. Three regression techniques are evaluated; multiple linear regression (MLR), principal component regression (PCR), and partial least squares regression (PLS). PCR and PLS proved considerably superior to MLR with much lower standard errors. PLS was chosen to formulate the predictive model since it offers more flexibility in experimental design and gave slightly better results than PCR. The results indicate that winter windiness can be predicted with considerable skill one year ahead for much of coastal Europe, but that this deteriorates rapidly in the hinterland. The experiment succeeded in highlighting PLS as a very useful method for developing more precise forecasting models, and in identifying areas of high predictability.

Remote quantification of phycocyanin in potable water sources through an adaptive model

NASA Astrophysics Data System (ADS)

Song, Kaishan; Li, Lin; Tedesco, Lenore P.; Li, Shuai; Hall, Bob E.; Du, Jia

2014-09-01

Cyanobacterial blooms in water supply sources in both central Indiana USA (CIN) and South Australia (SA) are a cause of great concerns for toxin production and water quality deterioration. Remote sensing provides an effective approach for quick assessment of cyanobacteria through quantification of phycocyanin (PC) concentration. In total, 363 samples spanning a large variation of optically active constituents (OACs) in CIN and SA waters were collected during 24 field surveys. Concurrently, remote sensing reflectance spectra (Rrs) were measured. A partial least squares-artificial neural network (PLS-ANN) model, artificial neural network (ANN) and three-band model (TBM) were developed or tuned by relating the Rrs with PC concentration. Our results indicate that the PLS-ANN model outperformed the ANN and TBM with both the original spectra and simulated ESA/Sentinel-3/Ocean and Land Color Instrument (OLCI) and EO-1/Hyperion spectra. The PLS-ANN model resulted in a high coefficient of determination (R2) for CIN dataset (R2 = 0.92, R: 0.3-220.7 μg/L) and SA (R2 = 0.98, R: 0.2-13.2 μg/L). In comparison, the TBM model yielded an R2 = 0.77 and 0.94 for the CIN and SA datasets, respectively; while the ANN obtained an intermediate modeling accuracy (CIN: R2 = 0.86; SA: R2 = 0.95). Applying the simulated OLCI and Hyperion aggregated datasets, the PLS-ANN model still achieved good performance (OLCI: R2 = 0.84; Hyperion: R2 = 0.90); the TBM also presented acceptable performance for PC estimations (OLCI: R2 = 0.65, Hyperion: R2 = 0.70). Based on the results, the PLS-ANN is an effective modeling approach for the quantification of PC in productive water supplies based on its effectiveness in solving the non-linearity of PC with other OACs. Furthermore, our investigation indicates that the ratio of inorganic suspended matter (ISM) to PC concentration has close relationship to modeling relative errors (CIN: R2 = 0.81; SA: R2 = 0.92), indicating that ISM concentration exert significant impact on PC estimation accuracy.

Glucose determination in human aqueous humor with Raman spectroscopy

NASA Technical Reports Server (NTRS)

Lambert, James L.; Pelletier, Christine C.; Borchert, Mark

2005-01-01

It has been suggested that spectroscopic analysis of the aqueous humor of the eye could be used to indirectly predict blood glucose levels in diabetics noninvasively. We have been investigating this potential using Raman spectroscopy in combination with partial least squares (PLS) analysis. We have determined that glucose at clinically relevant concentrations can be accurately predicted in human aqueous humor in vitro using a PLS model based on artificial aqueous humor. We have further determined that with proper instrument design, the light energy necessary to achieve clinically acceptable prediction of glucose does not damage the retinas of rabbits and can be delivered at powers below internationally acceptable safety limits. Herein we summarize our current results and address our strategies to improve instrument design. 2005 Society of Photo-Optical Instrumentation Engineers.

Value of Developing Plain Language Summaries of Scientific and Clinical Articles: A Survey of Patients and Physicians.

PubMed

Pushparajah, Daphnee S; Manning, Elizabeth; Michels, Erik; Arnaudeau-Bégard, Catherine

2017-01-01

We sought to determine the value and feasibility of developing plain language summaries (PLS) of peer-reviewed articles for patients. Members of the European Patients Academy on Therapeutic Innovation or UCB Pharma (N = 74) with a diagnosis of chronic disease, as well as a group of randomly selected neurologists in the US (N = 90) participated in online surveys. Two physicians, 5 patients, and 1 caregiver participated in interviews. Patient survey and interview participants reported that they routinely sought health-related information online. Articles in scientific journals were ranked the third most important source in the survey (47%), after general Internet searches (61%) and patient-specific websites (57%). Survey physicians were equivocal in their views; 46% rated PLS as valuable, 46% as neutral, and 8% as not valuable; however, 60% reported they would use them. A predominant theme emerging in patient interviews was the importance of knowledge and the sense of empowerment it engenders. Patients viewed PLS as tools to facilitate knowledge sharing and making important information accessible. In interviews, physicians noted the value of PLS in generating dialogue, saving time and streamlining communication with patients, as patients are not completely dependent on them for information. Our results indicate PLS could play an important role in the patient-physician dialogue. Although patients in this study tended to be more informed and engaged than the general patient population, with continued expansion of online platforms and open-access publishing, it is likely that greater numbers of patients will seek more specialized health-related information in the future.

Polar Plasma at Ganymede: Ionospheric outflow and discovery of the plasma sheet

NASA Astrophysics Data System (ADS)

Collinson, G.; Paterson, W.; Dorelli, J.; Glocer, A.; Sarantos, M.; Wilson, R. J.; Bard, C.

2017-12-01

On the 27th of June 1996, the NASA Galileo spacecraft made humanities first flyby of Jupiter's largest moon, Ganymede, discovering that it is unique to science in being the only moon known to possess an internally generated magnetic dynamo field. Although Galileo carried a plasma spectrometer, the Plasma Subsystem (PLS), converting its highly complex raw data stream into meaningful plasma moments (density, temperature, velocity) is extremely challenging, and was only ever performed for the second (out of six) Ganymede flybys. Resurrecting the original Galileo PLS data analysis software, we processed the raw PLS data from G01, and for the first time present the properties of plasmas encountered. Dense, cold ions were observed outflowing from the moon's north pole (presumed to be dominated by H+ from the icy surface), with more diffuse, warmer field-aligned outflows in the lobes. Dropouts in plasma density combined with velocity perturbations either side of this suggest that Galileo briefly crossed the cusps onto closed magnetic field lines. PLS observations show that upon entry into the magnetosphere, Galileo crossed through the plasma sheet, observing plasma flows consistent with reconnection-driven convection, highly energized 105 eV ions, and a reversal in the magnetic field. The densities of plasmas flowing upwards from Ganymede's ionosphere were higher on open "lobe" field lines than on closed field lines, suggesting that the ionospheric source of these plasmas may be denser at the poles, there may be additional acceleration mechanisms at play, or the balance of ions were outside the energy range of PLS.

Variable selection based cotton bollworm odor spectroscopic detection

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Gai, Shasha; Luo, Min; Zhao, Bo

2016-10-01

Aiming at rapid automatic pest detection based efficient and targeting pesticide application and shooting the trouble of reflectance spectral signal covered and attenuated by the solid plant, the possibility of near infrared spectroscopy (NIRS) detection on cotton bollworm odor is studied. Three cotton bollworm odor samples and 3 blank air gas samples were prepared. Different concentrations of cotton bollworm odor were prepared by mixing the above gas samples, resulting a calibration group of 62 samples and a validation group of 31 samples. Spectral collection system includes light source, optical fiber, sample chamber, spectrometer. Spectra were pretreated by baseline correction, modeled with partial least squares (PLS), and optimized by genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS). Minor counts differences are found among spectra of different cotton bollworm odor concentrations. PLS model of all the variables was built presenting RMSEV of 14 and RV2 of 0.89, its theory basis is insect volatilizes specific odor, including pheromone and allelochemics, which are used for intra-specific and inter-specific communication and could be detected by NIR spectroscopy. 28 sensitive variables are selected by GA, presenting the model performance of RMSEV of 14 and RV2 of 0.90. Comparably, 8 sensitive variables are selected by CARS, presenting the model performance of RMSEV of 13 and RV2 of 0.92. CARS model employs only 1.5% variables presenting smaller error than that of all variable. Odor gas based NIR technique shows the potential for cotton bollworm detection.

Non-Destructive Quality Evaluation of Pepper (Capsicum annuum L.) Seeds Using LED-Induced Hyperspectral Reflectance Imaging

PubMed Central

Mo, Changyeun; Kim, Giyoung; Lee, Kangjin; Kim, Moon S.; Cho, Byoung-Kwan; Lim, Jongguk; Kang, Sukwon

2014-01-01

In this study, we developed a viability evaluation method for pepper (Capsicum annuum L.) seeds based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400–700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares–discriminant analysis (PLS-DA) model is developed to classify viable and non-viable seeds. Four spectral ranges generated with four types of LEDs (blue, green, red, and RGB), which were pretreated using various methods, are investigated to develop the classification models. The optimal PLS-DA model based on the standard normal variate for RGB LED illumination (400–700 nm) yields discrimination accuracies of 96.7% and 99.4% for viable seeds and nonviable seeds, respectively. The use of images based on the PLS-DA model with the first-order derivative of a 31.5-nm gap for red LED illumination (600–700 nm) yields 100% discrimination accuracy for both viable and nonviable seeds. The results indicate that a hyperspectral imaging technique based on LED light can be potentially applied to high-quality pepper seed sorting. PMID:24763251

Relationship between Composition and Toxicity of Motor Vehicle Emission Samples

PubMed Central

McDonald, Jacob D.; Eide, Ingvar; Seagrave, JeanClare; Zielinska, Barbara; Whitney, Kevin; Lawson, Douglas R.; Mauderly, Joe L.

2004-01-01

In this study we investigated the statistical relationship between particle and semivolatile organic chemical constituents in gasoline and diesel vehicle exhaust samples, and toxicity as measured by inflammation and tissue damage in rat lungs and mutagenicity in bacteria. Exhaust samples were collected from “normal” and “high-emitting” gasoline and diesel light-duty vehicles. We employed a combination of principal component analysis (PCA) and partial least-squares regression (PLS; also known as projection to latent structures) to evaluate the relationships between chemical composition of vehicle exhaust and toxicity. The PLS analysis revealed the chemical constituents covarying most strongly with toxicity and produced models predicting the relative toxicity of the samples with good accuracy. The specific nitro-polycyclic aromatic hydrocarbons important for mutagenicity were the same chemicals that have been implicated by decades of bioassay-directed fractionation. These chemicals were not related to lung toxicity, which was associated with organic carbon and select organic compounds that are present in lubricating oil. The results demonstrate the utility of the PCA/PLS approach for evaluating composition–response relationships in complex mixture exposures and also provide a starting point for confirming causality and determining the mechanisms of the lung effects. PMID:15531438

Non-destructive quality evaluation of pepper (Capsicum annuum L.) seeds using LED-induced hyperspectral reflectance imaging.

PubMed

Mo, Changyeun; Kim, Giyoung; Lee, Kangjin; Kim, Moon S; Cho, Byoung-Kwan; Lim, Jongguk; Kang, Sukwon

2014-04-24

In this study, we developed a viability evaluation method for pepper (Capsicum annuum L.) seeds based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400-700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) model is developed to classify viable and non-viable seeds. Four spectral ranges generated with four types of LEDs (blue, green, red, and RGB), which were pretreated using various methods, are investigated to develop the classification models. The optimal PLS-DA model based on the standard normal variate for RGB LED illumination (400-700 nm) yields discrimination accuracies of 96.7% and 99.4% for viable seeds and nonviable seeds, respectively. The use of images based on the PLS-DA model with the first-order derivative of a 31.5-nm gap for red LED illumination (600-700 nm) yields 100% discrimination accuracy for both viable and nonviable seeds. The results indicate that a hyperspectral imaging technique based on LED light can be potentially applied to high-quality pepper seed sorting.

Experiences of stigma and discrimination of people with schizophrenia in India

PubMed Central

Koschorke, Mirja; Padmavati, R.; Kumar, Shuba; Cohen, Alex; Weiss, Helen A.; Chatterjee, Sudipto; Pereira, Jesina; Naik, Smita; John, Sujit; Dabholkar, Hamid; Balaji, Madhumitha; Chavan, Animish; Varghese, Mathew; Thara, R.; Thornicroft, Graham; Patel, Vikram

2014-01-01

Stigma contributes greatly to the burden of schizophrenia and is a major obstacle to recovery, yet, little is known about the subjective experiences of those directly affected in low and middle income countries. This paper aims to describe the experiences of stigma and discrimination of people living with schizophrenia (PLS) in three sites in India and to identify factors influencing negative discrimination. The study used mixed methods and was nested in a randomised controlled trial of community care for schizophrenia. Between November 2009 and October 2010, data on four aspects of stigma experienced by PLS and several clinical variables were collected from 282 PLS and 282 caregivers and analysed using multivariate regression. In addition, in-depth-interviews with PLS and caregivers (36 each) were carried out and analysed using thematic analysis. Quantitative findings indicate that experiences of negative discrimination were reported less commonly (42%) than more internalised forms of stigma experience such as a sense of alienation (79%) and significantly less often than in studies carried out elsewhere. Experiences of negative discrimination were independently predicted by higher levels of positive symptoms of schizophrenia, lower levels of negative symptoms of schizophrenia, higher caregiver knowledge about symptomatology, lower PLS age and not having a source of drinking water in the home. Qualitative findings illustrate the major impact of stigma on ‘what matters most’ in the lives of PLS and highlight three key domains influencing the themes of 'negative reactions' and ‘negative views and feelings about the self’, i.e., ‘others finding out’, ‘behaviours and manifestations of the illness’ and ‘reduced ability to meet role expectations’. Findings have implications for conceptualising and measuring stigma and add to the rationale for enhancing psycho-social interventions to support those facing discrimination. Findings also highlight the importance of addressing public stigma and achieving higher level social and political structural change. PMID:25462616

On-line monitoring of extraction process of Flos Lonicerae Japonicae using near infrared spectroscopy combined with synergy interval PLS and genetic algorithm

NASA Astrophysics Data System (ADS)

Yang, Yue; Wang, Lei; Wu, Yongjiang; Liu, Xuesong; Bi, Yuan; Xiao, Wei; Chen, Yong

2017-07-01

There is a growing need for the effective on-line process monitoring during the manufacture of traditional Chinese medicine to ensure quality consistency. In this study, the potential of near infrared (NIR) spectroscopy technique to monitor the extraction process of Flos Lonicerae Japonicae was investigated. A new algorithm of synergy interval PLS with genetic algorithm (Si-GA-PLS) was proposed for modeling. Four different PLS models, namely Full-PLS, Si-PLS, GA-PLS, and Si-GA-PLS, were established, and their performances in predicting two quality parameters (viz. total acid and soluble solid contents) were compared. In conclusion, Si-GA-PLS model got the best results due to the combination of superiority of Si-PLS and GA. For Si-GA-PLS, the determination coefficient (Rp2) and root-mean-square error for the prediction set (RMSEP) were 0.9561 and 147.6544 μg/ml for total acid, 0.9062 and 0.1078% for soluble solid contents, correspondingly. The overall results demonstrated that the NIR spectroscopy technique combined with Si-GA-PLS calibration is a reliable and non-destructive alternative method for on-line monitoring of the extraction process of TCM on the production scale.

Optical scatterometry of quarter-micron patterns using neural regression

NASA Astrophysics Data System (ADS)

Bischoff, Joerg; Bauer, Joachim J.; Haak, Ulrich; Hutschenreuther, Lutz; Truckenbrodt, Horst

1998-06-01

With shrinking dimensions and increasing chip areas, a rapid and non-destructive full wafer characterization after every patterning cycle is an inevitable necessity. In former publications it was shown that Optical Scatterometry (OS) has the potential to push the attainable feature limits of optical techniques from 0.8 . . . 0.5 microns for imaging methods down to 0.1 micron and below. Thus the demands of future metrology can be met. Basically being a nonimaging method, OS combines light scatter (or diffraction) measurements with modern data analysis schemes to solve the inverse scatter issue. For very fine patterns with lambda-to-pitch ratios grater than one, the specular reflected light versus the incidence angle is recorded. Usually, the data analysis comprises two steps -- a training cycle connected the a rigorous forward modeling and the prediction itself. Until now, two data analysis schemes are usually applied -- the multivariate regression based Partial Least Squares method (PLS) and a look-up-table technique which is also referred to as Minimum Mean Square Error approach (MMSE). Both methods are afflicted with serious drawbacks. On the one hand, the prediction accuracy of multivariate regression schemes degrades with larger parameter ranges due to the linearization properties of the method. On the other hand, look-up-table methods are rather time consuming during prediction thus prolonging the processing time and reducing the throughput. An alternate method is an Artificial Neural Network (ANN) based regression which combines the advantages of multivariate regression and MMSE. Due to the versatility of a neural network, not only can its structure be adapted more properly to the scatter problem, but also the nonlinearity of the neuronal transfer functions mimic the nonlinear behavior of optical diffraction processes more adequately. In spite of these pleasant properties, the prediction speed of ANN regression is comparable with that of the PLS-method. In this paper, the viability and performance of ANN-regression will be demonstrated with the example of sub-quarter-micron resist metrology. To this end, 0.25 micrometer line/space patterns have been printed in positive photoresist by means of DUV projection lithography. In order to evaluate the total metrology chain from light scatter measurement through data analysis, a thorough modeling has been performed. Assuming a trapezoidal shape of the developed resist profile, a training data set was generated by means of the Rigorous Coupled Wave Approach (RCWA). After training the model, a second data set was computed and deteriorated by Gaussian noise to imitate real measuring conditions. Then, these data have been fed into the models established before resulting in a Standard Error of Prediction (SEP) which corresponds to the measuring accuracy. Even with putting only little effort in the design of a back-propagation network, the ANN is clearly superior to the PLS-method. Depending on whether a network with one or two hidden layers was used, accuracy gains between 2 and 5 can be achieved compared with PLS regression. Furthermore, the ANN is less noise sensitive, for there is only a doubling of the SEP at 5% noise for ANN whereas for PLS the accuracy degrades rapidly with increasing noise. The accuracy gain also depends on the light polarization and on the measured parameters. Finally, these results have been proven experimentally, where the OS-results are in good accordance with the profiles obtained from cross- sectioning micrographs.

Effect of the environment microbiota on the flavour of light-flavour Baijiu during spontaneous fermentation.

PubMed

Pang, Xiao-Na; Han, Bei-Zhong; Huang, Xiao-Ning; Zhang, Xin; Hou, Lin-Feng; Cao, Ming; Gao, Li-Juan; Hu, Guang-Hui; Chen, Jing-Yu

2018-02-21

Light-flavour Baijiu is a type of Chinese liquor with a pure and mild flavour produced by traditional spontaneous solid-state fermentation. The flavour of this liquor has been found to vary in the different periods of annual production. To explore the factors affecting flavour, the microbiota of the surrounding environment, starter and fermentation process in different periods were investigated. Results showed that the ester content and acidity of light-flavour Baijiu were significantly lower when annual production was resumed after a summer break. HCA plot of volatile flavour profile and bacterial PCoA results indicated that the differences occurred at later stages, mainly due to different structures of Lactobacillus. Correlation analysis by O2PLS indicated that Lactobacillus positively correlated with esters. Species-level analysis showed that the lack of L. acetotolerans on the surface of the jar might cause a lag in fermentation and lower ester content. Thereafter, L. acetotolerans was revived during fermentation and enriched on the surface of the jar, which promoted ester formation. As important sources of L. acetotolerans, the air and fermentation jars played a critical role during fermentation. Therefore, this systematic study on environmental microbial ecology is valuable for quality control and to explore environmental microbiota functions during spontaneous fermentation.

Autofluoresence spectroscopy for in-vivo diagnosis of human oral carcinogenesis

NASA Astrophysics Data System (ADS)

Wang, Chih-Yu; Tsai, Tsuimin; Chen, Hsin-Ming; Kuo, Ying-Shiung; Chen, Chin-Tin; Chiang, Chung-Ping

2002-09-01

An in vivo study of human oral cancer diagnosis by using autofluorescence spectroscopy is presented. A Xenon-lamp with a motor-controlled monochromator was adopted as the excitation light source. We chose the excitation wavelength of 330 nm, and the spectral measurement range was from 340 nm to 601 nm. A Y-type fiber bundle was used to guide the excitation light, and collect the autofluorescence of samples. The emitted light was detected by a motor-controlled monochromator and a PMT. After measurement, the measured sites were sectioned and sent for histological examination. In total 15 normal sites, 30 OSF (oral submucosa fibrosis) sites, 26 EH (epithelial hyperkratosis) sites, 13 ED (epithelial dysplasia) sites, and 13 SCC (squamous cell carcinoma) sites were measured. The discriminant algorithm was established by partial-least squares (PLS) method with cross-validation technique. By extracting the first two t-scores of each sample and make scattering plot, we found that the samples of different cancerous stages were in grouped distinct locations, except that samples of ED and EH were mixed together. It means that this algorithm can be used to classify normal, premalignant, and malignant tissues. We conclude that autofluorescence spectroscopy may be useful for in vivo detection of early stage oral cancer.

Fast and nondestructive determination of protein content in rapeseeds (Brassica napus L.) using Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS).

PubMed

Lu, Yuzhen; Du, Changwen; Yu, Changbing; Zhou, Jianmin

2014-08-01

Fast and non-destructive determination of rapeseed protein content carries significant implications in rapeseed production. This study presented the first attempt of using Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) to quantify protein content of rapeseed. The full-spectrum model was first built using partial least squares (PLS). Interval selection methods including interval partial least squares (iPLS), synergy interval partial least squares (siPLS), backward elimination interval partial least squares (biPLS) and dynamic backward elimination interval partial least squares (dyn-biPLS) were then employed to select the relevant band or band combination for PLS modeling. The full-spectrum PLS model achieved an ratio of prediction to deviation (RPD) of 2.047. In comparison, all interval selection methods produced better results than full-spectrum modeling. siPLS achieved the best predictive accuracy with an RPD of 3.215 when the spectrum was sectioned into 25 intervals, and two intervals (1198-1335 and 1614-1753 cm(-1) ) were selected. iPLS excelled biPLS and dyn-biPLS, and dyn-biPLS performed slightly better than biPLS. FTIR-PAS was verified as a promising analytical tool to quantify rapeseed protein content. Interval selection could extract the relevant individual band or synergy band associated with the sample constituent of interest, and then improve the prediction accuracy of the full-spectrum model. © 2013 Society of Chemical Industry.

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data

PubMed Central

Ferragina, A.; de los Campos, G.; Vazquez, A. I.; Cecchinato, A.; Bittante, G.

2017-01-01

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict “difficult-to-predict” dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and protein recovery, using Fourier-transform infrared (FTIR) spectral data. Our main hypothesis was that Bayesian models that can estimate shrinkage and perform variable selection may improve our ability to predict FA traits and technological traits above and beyond what can be achieved using the current calibration models (e.g., partial least squares, PLS). To this end, we assessed a series of Bayesian methods and compared their prediction performance with that of PLS. The comparison between models was done using the same sets of data (i.e., same samples, same variability, same spectral treatment) for each trait. Data consisted of 1,264 individual milk samples collected from Brown Swiss cows for which gas chromatographic FA composition, milk coagulation properties, and cheese-yield traits were available. For each sample, 2 spectra in the infrared region from 5,011 to 925 cm−1 were available and averaged before data analysis. Three Bayesian models: Bayesian ridge regression (Bayes RR), Bayes A, and Bayes B, and 2 reference models: PLS and modified PLS (MPLS) procedures, were used to calibrate equations for each of the traits. The Bayesian models used were implemented in the R package BGLR (http://cran.r-project.org/web/packages/BGLR/index.html), whereas the PLS and MPLS were those implemented in the WinISI II software (Infrasoft International LLC, State College, PA). Prediction accuracy was estimated for each trait and model using 25 replicates of a training-testing validation procedure. Compared with PLS, which is currently the most widely used calibration method, MPLS and the 3 Bayesian methods showed significantly greater prediction accuracy. Accuracy increased in moving from calibration to external validation methods, and in moving from PLS and MPLS to Bayesian methods, particularly Bayes A and Bayes B. The maximum R2 value of validation was obtained with Bayes B and Bayes A. For the FA, C10:0 (% of each FA on total FA basis) had the highest R2 (0.75, achieved with Bayes A and Bayes B), and among the technological traits, fresh cheese yield R2 of 0.82 (achieved with Bayes B). These 2 methods have proven to be useful instruments in shrinking and selecting very informative wavelengths and inferring the structure and functions of the analyzed traits. We conclude that Bayesian models are powerful tools for deriving calibration equations, and, importantly, these equations can be easily developed using existing open-source software. As part of our study, we provide scripts based on the open source R software BGLR, which can be used to train customized prediction equations for other traits or populations. PMID:26387015

Analysis of multi-mode to single-mode conversion at 635 nm and 1550 nm

NASA Astrophysics Data System (ADS)

Zamora, Vanessa; Bogatzki, Angelina; Arndt-Staufenbiel, Norbert; Hofmann, Jens; Schröder, Henning

2016-03-01

We propose two low-cost and robust optical fiber systems based on the photonic lantern (PL) technology for operating at 635 nm and 1550 nm. The PL is an emerging technology that couples light from a multi-mode (MM) fiber to several single-mode (SM) fibers via a low-loss adiabatic transition. This bundle of SM fibers is observed as a MM fiber system whose spatial modes are the degenerate supermodes of the bundle. The adiabatic transition allows that those supermodes evolve into the modes of the MM fiber. Simulations of the MM fiber end structure and its taper transition have been performed via functional mode solver tools in order to understand the modal evolution in PLs. The modelled design consists of 7 SM fibers inserted into a low-index capillary. The material and geometry of the PLs are chosen such that the supermodes match to the spatial modes of the desired step-index MM fiber in a moderate loss transmission. The dispersion of materials is also considered. These parameters are studied in two PL systems in order to reach a spectral transmission from 450 nm to 1600 nm. Additionally, an analysis of the geometry and losses due to the mismatching of modes is presented. PLs are typically used in the fields of astrophotonics and space photonics. Recently, they are demonstrated as mode converters in telecommunications, especially focusing on spatial division multiplexing. In this study, we show the use of PLs as a promising interconnecting tool for the development of miniaturized spectrometers operating in a broad wavelength range.

Airway diffusing capacity of nitric oxide and steroid therapy in asthma.

PubMed

Shin, Hye-Won; Rose-Gottron, Christine M; Cooper, Dan M; Newcomb, Robert L; George, Steven C

2004-01-01

Exhaled nitric oxide (NO) concentration is a noninvasive index for monitoring lung inflammation in diseases such as asthma. The plateau concentration at constant flow is highly dependent on the exhalation flow rate and the use of corticosteroids and cannot distinguish airway and alveolar sources. In subjects with steroid-naive asthma (n = 8) or steroid-treated asthma (n = 12) and in healthy controls (n = 24), we measured flow-independent NO exchange parameters that partition exhaled NO into airway and alveolar regions and correlated these with symptoms and lung function. The mean (+/-SD) maximum airway flux (pl/s) and airway tissue concentration [parts/billion (ppb)] of NO were lower in steroid-treated asthmatic subjects compared with steroid-naive asthmatic subjects (1,195 +/- 836 pl/s and 143 +/- 66 ppb compared with 2,693 +/- 1,687 pl/s and 438 +/- 312 ppb, respectively). In contrast, the airway diffusing capacity for NO (pl.s-1.ppb-1) was elevated in both asthmatic groups compared with healthy controls, independent of steroid therapy (11.8 +/- 11.7, 8.71 +/- 5.74, and 3.13 +/- 1.57 pl.s-1.ppb-1 for steroid treated, steroid naive, and healthy controls, respectively). In addition, the airway diffusing capacity was inversely correlated with both forced expired volume in 1 s and forced vital capacity (%predicted), whereas the airway tissue concentration was positively correlated with forced vital capacity. Consistent with previously reported results from Silkoff et al. (Silkoff PE, Sylvester JT, Zamel N, and Permutt S, Am J Respir Crit Med 161: 1218-1228, 2000) that used an alternate technique, we conclude that the airway diffusing capacity for NO is elevated in asthma independent of steroid therapy and may reflect clinically relevant changes in airways.

An in vitro approach for lipolysis measurement using high-resolution mass spectrometry and partial least squares based analysis.

PubMed

Chang, Wen-Qi; Zhou, Jian-Liang; Li, Yi; Shi, Zi-Qi; Wang, Li; Yang, Jie; Li, Ping; Liu, Li-Fang; Xin, Gui-Zhong

2017-01-15

The elevation of free fatty acids (FFAs) has been regarded as a universal metabolic signature of excessive adipocyte lipolysis. Nowadays, in vitro lipolysis assay is generally essential for drug screening prior to the animal study. Here, we present a novel in vitro approach for lipolysis measurement combining UHPLC-Orbitrap and partial least squares (PLS) based analysis. Firstly, the calibration matrix was constructed by serial proportions of mixed samples (blended with control and model samples). Then, lipidome profiling was performed by UHPLC-Orbitrap, and 403 variables were extracted and aligned as dataset. Owing to the high resolution of Orbitrap analyzer and open source lipid identification software, 28 FFAs were further screened and identified. Based on the relative intensity of the screened FFAs, PLS regression model was constructed for lipolysis measurement. After leave-one-out cross-validation, ten principal components have been designated to build the final PLS model with excellent performances (RMSECV, 0.0268; RMSEC, 0.0173; R 2 , 0.9977). In addition, the high predictive accuracy (R 2  = 0.9907 and RMSEP = 0.0345) of the trained PLS model was also demonstrated using test samples. Finally, taking curcumin as a model compound, its antilipolytic effect on palmitic acid-induced lipolysis was successfully predicted as 31.78% by the proposed approach. Besides, supplementary evidences of curcumin induced modification in FFAs compositions as well as lipidome were given by PLS extended methods. Different from general biological assays, high resolution MS-based method provide more sophisticated information included in biological events. Thus, the novel biological evaluation model proposed here showed promising perspectives for drug evaluation or disease diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification and topographical characterisation of microbial nanowires in Nostoc punctiforme.

PubMed

Sure, Sandeep; Torriero, Angel A J; Gaur, Aditya; Li, Lu Hua; Chen, Ying; Tripathi, Chandrakant; Adholeya, Alok; Ackland, M Leigh; Kochar, Mandira

2016-03-01

Extracellular pili-like structures (PLS) produced by cyanobacteria have been poorly explored. We have done detailed topographical and electrical characterisation of PLS in Nostoc punctiforme PCC 73120 using transmission electron microscopy (TEM) and conductive atomic force microscopy (CAFM). TEM analysis showed that N. punctiforme produces two separate types of PLS differing in their length and diameter. The first type of PLS are 6-7.5 nm in diameter and 0.5-2 µm in length (short/thin PLS) while the second type of PLS are ~20-40 nm in diameter and more than 10 µm long (long/thick PLS). This is the first study to report long/thick PLS in N. punctiforme. Electrical characterisation of these two different PLS by CAFM showed that both are electrically conductive and can act as microbial nanowires. This is the first report to show two distinct PLS and also identifies microbial nanowires in N. punctiforme. This study paves the way for more detailed investigation of N. punctiforme nanowires and their potential role in cell physiology and symbiosis with plants.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Electromagnetic disturbance of electric drive system signal is extracted based on PLS

NASA Astrophysics Data System (ADS)

Wang, Yun; Wang, Chuanqi; Yang, Weidong; Zhang, Xu; Jiang, Li; Hou, Shuai; Chen, Xichen

2018-05-01

At present ISO11452 and GB/T33014 specified by electromagnetic immunity are narrowband electromagnetic radiation, but our exposure to electromagnetic radiation at ordinary times is not only a narrowband electromagnetic radiation, and some broadband electromagnetic radiation, and even some of the more complex electromagnetic environment. In terms of Electric vehicles, electric drive system is a kind of complex electromagnetic disturbance source, is not only a narrow-band signal, there are a lot of broadband signal, this paper puts forward PLS data processing method is adopted to analyze the electric drive system of electromagnetic disturbance, this kind of method to extract the data can be provide reliable data support for future standards.

Coulomb and CH-π interactions in (6-4) photolyase-DNA complex dominate DNA binding and repair abilities.

PubMed

Terai, Yuma; Sato, Ryuma; Yumiba, Takahiro; Harada, Ryuhei; Shimizu, Kohei; Toga, Tatsuya; Ishikawa-Fujiwara, Tomoko; Todo, Takeshi; Iwai, Shigenori; Shigeta, Yasuteru; Yamamoto, Junpei

2018-05-14

(6-4) Photolyases ((6-4)PLs) are flavoenzymes that repair the carcinogenic UV-induced DNA damage, pyrimidine(6-4)pyrimidone photoproducts ((6-4)PPs), in a light-dependent manner. Although the reaction mechanism of DNA photorepair by (6-4)PLs has been intensively investigated, the molecular mechanism of the lesion recognition remains obscure. We show that a well-conserved arginine residue in Xenopus laevis (6-4)PL (Xl64) participates in DNA binding, through Coulomb and CH-π interactions. Fragment molecular orbital calculations estimated attractive interaction energies of -80-100 kcal mol-1 for the Coulomb interaction and -6 kcal mol-1 for the CH-π interaction, and the loss of either of them significantly reduced the affinity for (6-4)PP-containing oligonucleotides, as well as the quantum yield of DNA photorepair. From experimental and theoretical observations, we formulated a DNA binding model of (6-4)PLs. Based on the binding model, we mutated this Arg in Xl64 to His, which is well conserved among the animal cryptochromes (CRYs), and found that the CRY-type mutant exhibited reduced affinity for the (6-4)PP-containing oligonucleotides, implying the possible molecular origin of the functional diversity of the photolyase/cryptochrome superfamily.

Determination of benzo[a]pyrene in cigarette mainstream smoke by using mid-infrared spectroscopy associated with a novel chemometric algorithm.

PubMed

Zhang, Yan; Zou, Hong-Yan; Shi, Pei; Yang, Qin; Tang, Li-Juan; Jiang, Jian-Hui; Wu, Hai-Long; Yu, Ru-Qin

2016-01-01

Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of new S-band SLED for PAL-XFEL Linac

NASA Astrophysics Data System (ADS)

Joo, Youngdo; Park, Yongjung; Heo, Hoon; Heo, Jinyul; Park, Sung-Soo; Kim, Sang-Hee; Kim, Kwang-Hoon; Kang, Heung-Sik; Lee, Heung-Soo; Noh, Sungju; Oh, Kyoungmin

2017-01-01

In order to achieve beam acceleration to the beam energy of 10 GeV at the end of its 716 m-long linear accelerator (Linac), the Pohang Accelerator Laboratory X-ray Free Electron Laser (PAL-XFEL) is going to operate the Stanford Linear Accelerator Energy Doubler (SLED) at the maximum klystron output peak power of 80 MW, with a pulse length of 4 μs, and at a repetition rate of 60 Hz. The original SLED that had been used in Pohang Light Source-II (PLS-II) can no longer sustain such a high-power operation because excessive radiation caused by RF breakdown has been frequently detected even at the lower klystron peak power during the PLS-II operation. Therefore, a new SLED is designed by modifying both the 3-dB power hybrid and the waveguide-cavity coupling structure of the original SLED where the excessive radiation has been mainly detected. The finite-difference time-domain (FDTD) simulation in the CST Microwave Studio shows that the new SLED has a peak electric field and a surface current lower than those of the original SLED at the same level of the RF input peak power, which would secure stable high-power operation. All of the 42 SLEDs in the PAL-XFEL Linac are newly fabricated and installed. During the RF conditioning of the PAL-XFEL Linac, no significant vacuum and radiation issue was found in the new SLEDs. Finally, the accelerated electron beam energy of 10 GeV obtained at the end of the PAL-XFEL Linac verified that the RF performance of the new SLED is stable.

Modelling mercury accumulation in minerogenic peat combining FTIR-ATR spectroscopy and partial least squares (PLS)

NASA Astrophysics Data System (ADS)

Pérez-Rodríguez, Marta; Horák-Terra, Ingrid; Rodríguez-Lado, Luis; Martínez Cortizas, Antonio

2016-11-01

Despite its potential, infrared spectroscopy combined with multivariate statistics has been seldom used to model peat properties with environmental value, such us the concentration of potentially toxic metals. In this research, we applied attenuated total reflectance (ATR) Fourier-Transform Infrared (FTIR) spectroscopy to evaluate the ability of the technique to predict mercury concentrations in late-Pleistocene/Holocene peat from a minerogenic peatland from Minas Gerais (Brazil). Mercury concentrations were analysed using a Milestone DMA-80 analyzer and attenuated total reflectance FTIR-ATR was performed using a Gladi-ATR (Pike Technologies) in the mid IR spectrum (4000-400 cm- 1). Concentrations were modelled using principal components (PCR) and partial least squares regression (PLS). The performance of the models varied between moderate and very good (R2 0.67-0.90), with low RMSD values (0.35-1.06). A PLS model based on three latent vectors (LV1 to LV3) provided the best (R2 0.90, RMSD 0.35) results. LV1 reflected total organic matter content versus mineral matter (mainly quartz from local fluxes), LV2 was related to dust deposition from regional sources, and LV3 reflected peat organic matter decomposition. Compared to a previous investigation based on geochemical data, the spectroscopy-based PLS model performed better, but it has to be complemented with additional data (as δ13 C ratios) to reliably reproduce the changes of the factors controlling mercury accumulation over time. This, time- and cost-effective, methodology may help to develop multi-core approaches to study the within and between mire (of a similar type and area) variability in mercury accumulation, and probably also other peat properties. Fig. S2 Loadings weights of the three and two significant components from the direct (dPCR) and transposed (trPCR) PCR models. Fig. S3 Depth records of the cumulative effects of the factors involved in the variation of mercury concentrations. Left, MIR-PLS model; centre, MIR-PLS + δ13 C data model; right, geochemical model from Pérez-Rodríguez et al. [44].

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

NASA Astrophysics Data System (ADS)

Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

2010-09-01

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

Association Between Dietary-related Risk Factors and Ischemic Stroke Using Reduced Rank Regression: The Multi-Ethnic Study of Atherosclerosis (MESA), USA.

PubMed

Nazari, Seyed Saeed Hashemi; Mokhayeri, Yaser; Mansournia, Mohammad Ali; Khodakarim, Soheila; Soori, Hamid

2018-05-21

Some studies shed light on the association between dietary patterns and stroke, though, none of them applied reduced rank regression (RRR). Therefore, we sought to extract dietary patterns using RRR, and showed how well the extracted scores by RRR predict stroke in comparison to those scores produced by partial least squares (PLS) and principal components regression (PCR). Diet data at baseline with four response variables including body mass index (BMI), fibrinogen, IL-6, low-density lipoprotein (LDL) cholesterol were used to extract dietary patterns. Analyses were based on 5468 men and women aged 45-84 y who had no clinical cardiovascular diseases (CVD) from Multi-Ethnic Study of Atherosclerosis (MESA). Dietary patterns were created by three methods RRR, PLS, and PCR. The RRR1 was positively associated with stroke incidence in both models (for model 1 hazard ratio (HR): 7.49; 95% CI: 1.66, 33.69 P for trend = 0.01 and for model 2 HR: 6.83; 95% CI: 1.51, 30.87 for quintile 5 compared with the reference category P for trend = 0.02). The RRR1, PLS1, and PCR1 were high in fats and oils, poultry, tomatoes, fried potato and processed meat. Additionally, RRR1 and PLS1 were high in dark-yellow and cruciferous vegetables which negatively were correlated with the first dietary pattern. Mainly according to the RRR, we identified that a dietary pattern high in fats and oil, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, fried potato and low in dark-yellow and cruciferous vegetables may increase the incidence of stroke.

Lipidomics and H218O labeling techniques reveal increased remodeling of DHA-containing membrane phospholipids associated with abnormal locomotor responses in α-tocopherol deficient zebrafish (danio rerio) embryos

PubMed Central

McDougall, Melissa Q.; Choi, Jaewoo; Stevens, Jan F.; Truong, Lisa; Tanguay, Robert L.; Traber, Maret G.

2016-01-01

We hypothesized that vitamin E (α-tocopherol) is required by the developing embryonic brain to prevent depletion of highly polyunsaturated fatty acids, especially docosahexaenoic acid (DHA, 22:6), the loss of which we predicted would underlie abnormal morphological and behavioral outcomes. Therefore, we fed adult 5D zebrafish (Danio rerio) defined diets without (E−) or with added α-tocopherol (E+, 500 mg RRR-α-tocopheryl acetate/kg diet) for a minimum of 80 days, and then spawned them to obtain E− and E+ embryos. The E− compared with E+ embryos were 82% less responsive (p<0.01) to a light/dark stimulus at 96 h post-fertilization (hpf), demonstrating impaired locomotor behavior, even in the absence of gross morphological defects. Evaluation of phospholipid (PL) and lysophospholipid (lyso-PL) composition using untargeted lipidomics in E− compared with E+ embryos at 24, 48, 72, and 120 hpf showed that four PLs and three lyso-PLs containing docosahexaenoic acid (DHA), including lysophosphatidylcholine (LPC 22:6, required for transport of DHA into the brain, p<0.001), were at lower concentrations in E− at all time-points. Additionally, H218O labeling experiments revealed enhanced turnover of LPC 22:6 (p<0.001) and three other DHA-containing PLs in the E− compared with the E+ embryos, suggesting that increased membrane remodeling is a result of PL depletion. Together, these data indicate that α-tocopherol deficiency in the zebrafish embryo causes the specific depletion and increased turnover of DHA-containing PL and lyso-PLs, which may compromise DHA delivery to the brain and thereby contribute to the functional impairments observed in E− embryos. PMID:26774753

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data.

PubMed

Ferragina, A; de los Campos, G; Vazquez, A I; Cecchinato, A; Bittante, G

2015-11-01

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict "difficult-to-predict" dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and protein recovery, using Fourier-transform infrared (FTIR) spectral data. Our main hypothesis was that Bayesian models that can estimate shrinkage and perform variable selection may improve our ability to predict FA traits and technological traits above and beyond what can be achieved using the current calibration models (e.g., partial least squares, PLS). To this end, we assessed a series of Bayesian methods and compared their prediction performance with that of PLS. The comparison between models was done using the same sets of data (i.e., same samples, same variability, same spectral treatment) for each trait. Data consisted of 1,264 individual milk samples collected from Brown Swiss cows for which gas chromatographic FA composition, milk coagulation properties, and cheese-yield traits were available. For each sample, 2 spectra in the infrared region from 5,011 to 925 cm(-1) were available and averaged before data analysis. Three Bayesian models: Bayesian ridge regression (Bayes RR), Bayes A, and Bayes B, and 2 reference models: PLS and modified PLS (MPLS) procedures, were used to calibrate equations for each of the traits. The Bayesian models used were implemented in the R package BGLR (http://cran.r-project.org/web/packages/BGLR/index.html), whereas the PLS and MPLS were those implemented in the WinISI II software (Infrasoft International LLC, State College, PA). Prediction accuracy was estimated for each trait and model using 25 replicates of a training-testing validation procedure. Compared with PLS, which is currently the most widely used calibration method, MPLS and the 3 Bayesian methods showed significantly greater prediction accuracy. Accuracy increased in moving from calibration to external validation methods, and in moving from PLS and MPLS to Bayesian methods, particularly Bayes A and Bayes B. The maximum R(2) value of validation was obtained with Bayes B and Bayes A. For the FA, C10:0 (% of each FA on total FA basis) had the highest R(2) (0.75, achieved with Bayes A and Bayes B), and among the technological traits, fresh cheese yield R(2) of 0.82 (achieved with Bayes B). These 2 methods have proven to be useful instruments in shrinking and selecting very informative wavelengths and inferring the structure and functions of the analyzed traits. We conclude that Bayesian models are powerful tools for deriving calibration equations, and, importantly, these equations can be easily developed using existing open-source software. As part of our study, we provide scripts based on the open source R software BGLR, which can be used to train customized prediction equations for other traits or populations. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

PubMed

Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

2015-09-01

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. Copyright © 2015 Elsevier B.V. All rights reserved.

Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data

NASA Astrophysics Data System (ADS)

Ogulei, David; Hopke, Philip K.; Zhou, Liming; Patrick Pancras, J.; Nair, Narayanan; Ondov, John M.

Several multivariate data analysis methods have been applied to a combination of particle size and composition measurements made at the Baltimore Supersite. Partial least squares (PLS) was used to investigate the relationship (linearity) between number concentrations and the measured PM2.5 mass concentrations of chemical species. The data were obtained at the Ponca Street site and consisted of six days' measurements: 6, 7, 8, 18, 19 July, and 21 August 2002. The PLS analysis showed that the covariance between the data could be explained by 10 latent variables (LVs), but only the first four of these were sufficient to establish the linear relationship between the two data sets. More LVs could not make the model better. The four LVs were found to better explain the covariance between the large sized particles and the chemical species. A bilinear receptor model, PMF2, was then used to simultaneously analyze the size distribution and chemical composition data sets. The resolved sources were identified using information from number and mass contributions from each source (source profiles) as well as meteorological data. Twelve sources were identified: oil-fired power plant emissions, secondary nitrate I, local gasoline traffic, coal-fired power plant, secondary nitrate II, secondary sulfate, diesel emissions/bus maintenance, Quebec wildfire episode, nucleation, incinerator, airborne soil/road-way dust, and steel plant emissions. Local sources were mostly characterized by bi-modal number distributions. Regional sources were characterized by transport mode particles (0.2- 0.5μm).

MALDI-TOF-MS with PLS Modeling Enables Strain Typing of the Bacterial Plant Pathogen Xanthomonas axonopodis

NASA Astrophysics Data System (ADS)

Sindt, Nathan M.; Robison, Faith; Brick, Mark A.; Schwartz, Howard F.; Heuberger, Adam L.; Prenni, Jessica E.

2018-02-01

Matrix-assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) is a fast and effective tool for microbial species identification. However, current approaches are limited to species-level identification even when genetic differences are known. Here, we present a novel workflow that applies the statistical method of partial least squares discriminant analysis (PLS-DA) to MALDI-TOF-MS protein fingerprint data of Xanthomonas axonopodis, an important bacterial plant pathogen of fruit and vegetable crops. Mass spectra of 32 X. axonopodis strains were used to create a mass spectral library and PLS-DA was employed to model the closely related strains. A robust workflow was designed to optimize the PLS-DA model by assessing the model performance over a range of signal-to-noise ratios (s/n) and mass filter (MF) thresholds. The optimized parameters were observed to be s/n = 3 and MF = 0.7. The model correctly classified 83% of spectra withheld from the model as a test set. A new decision rule was developed, termed the rolled-up Maximum Decision Rule (ruMDR), and this method improved identification rates to 92%. These results demonstrate that MALDI-TOF-MS protein fingerprints of bacterial isolates can be utilized to enable identification at the strain level. Furthermore, the open-source framework of this workflow allows for broad implementation across various instrument platforms as well as integration with alternative modeling and classification algorithms.

Simultaneous quantitative determination of paracetamol and tramadol in tablet formulation using UV spectrophotometry and chemometric methods

NASA Astrophysics Data System (ADS)

Glavanović, Siniša; Glavanović, Marija; Tomišić, Vladislav

2016-03-01

The UV spectrophotometric methods for simultaneous quantitative determination of paracetamol and tramadol in paracetamol-tramadol tablets were developed. The spectrophotometric data obtained were processed by means of partial least squares (PLS) and genetic algorithm coupled with PLS (GA-PLS) methods in order to determine the content of active substances in the tablets. The results gained by chemometric processing of the spectroscopic data were statistically compared with those obtained by means of validated ultra-high performance liquid chromatographic (UHPLC) method. The accuracy and precision of data obtained by the developed chemometric models were verified by analysing the synthetic mixture of drugs, and by calculating recovery as well as relative standard error (RSE). A statistically good agreement was found between the amounts of paracetamol determined using PLS and GA-PLS algorithms, and that obtained by UHPLC analysis, whereas for tramadol GA-PLS results were proven to be more reliable compared to those of PLS. The simplest and the most accurate and precise models were constructed by using the PLS method for paracetamol (mean recovery 99.5%, RSE 0.89%) and the GA-PLS method for tramadol (mean recovery 99.4%, RSE 1.69%).

Modified multiblock partial least squares path modeling algorithm with backpropagation neural networks approach

NASA Astrophysics Data System (ADS)

Yuniarto, Budi; Kurniawan, Robert

2017-03-01

PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.

Lactoferrin-modified PEGylated liposomes loaded with doxorubicin for targeting delivery to hepatocellular carcinoma

PubMed Central

Wei, Minyan; Guo, Xiucai; Tu, Liuxiao; Zou, Qi; Li, Qi; Tang, Chenyi; Chen, Bao; Xu, Yuehong; Wu, Chuanbin

2015-01-01

Lactoferrin (Lf) is a potential-targeting ligand for hepatocellular carcinoma (HCC) cells because of its specific binding with asialoglycoprotein receptor (ASGPR). In this present work, a doxorubicin (DOX)-loaded, Lf-modified, polyethylene glycol (PEG)ylated liposome (Lf-PLS) system was developed, and its targeting effect and antitumor efficacy to HCC was also explored. The DOX-loaded Lf-PLS system had spherical or oval vesicles, with mean particle size approximately 100 nm, and had an encapsulation efficiency of 97%. The confocal microscopy and flow cytometry indicated that the cellular uptake of Lf-PLS was significantly higher than that of PEGylated liposome (PLS) in ASGPR-positive cells (P<0.05) but not in ASGPR-negative cells (P>0.05). Cytotoxicity assay by MTT demonstrated that DOX-loaded Lf-PLS showed significantly stronger antiproliferative effects on ASGPR-positive HCC cells than did PLS without the Lf modification (P<0.05). The in vivo antitumor studies on male BALB/c nude mice bearing HepG2 xenografts demonstrated that DOX-loaded Lf-PLS had significantly stronger antitumor efficacy compared with PLS (P<0.05) and free DOX (P<0.05). All these results demonstrated that a DOX-loaded Lf-PLS might have great potential application for HCC-targeting therapy. PMID:26316745

A Thioesterase Bypasses the Requirement for Exogenous Fatty Acids in the plsX Deletion of Streptococcus pneumoniae

PubMed Central

Parsons, Joshua B.; Frank, Matthew W.; Eleveld, Marc J.; Schalkwijk, Joost; Broussard, Tyler C.; de Jonge, Marien I.; Rock, Charles O.

2015-01-01

Summary PlsX is an acyl-acyl carrier protein (ACP):phosphate transacylase that interconverts the two acyl donors in Gram-positive bacterial phospholipid synthesis. The deletion of plsX in Staphylococcus aureus results in a requirement for both exogenous fatty acids and de novo type II fatty acid biosynthesis. Deletion of plsX (SP0037) in Streptococcus pneumoniae did not result in an auxotrophic phenotype. The ΔplsX S. pneumoniae strain was refractory to myristic acid-dependent growth arrest, and unlike the wild-type strain, was susceptible to fatty acid synthesis inhibitors in the presence of exogenous oleate. The ΔplsX strain contained longer-chain saturated fatty acids imparting a distinctly altered phospholipid molecular species profile. An elevated pool of 18- and 20-carbon saturated fatty acids was detected in the ΔplsX strain. A S. pneumoniae thioesterase (TesS, SP1408) hydrolyzed acyl-ACP in vitro, and the ΔtesS ΔplsX double knockout strain was a fatty acid auxotroph. Thus, the TesS thioesterase hydrolyzed the accumulating acyl-ACP in the ΔplsX strain to liberate fatty acids that were activated by fatty acid kinase to bypass a requirement for extracellular fatty acid. This work identifies tesS as the gene responsible for the difference in exogenous fatty acid growth requirement of the ΔplsX strains of S. aureus and S. pneumoniae. PMID:25534847

New strategy for determination of anthocyanins, polyphenols and antioxidant capacity of Brassica oleracea liquid extract using infrared spectroscopies and multivariate regression

NASA Astrophysics Data System (ADS)

de Oliveira, Isadora R. N.; Roque, Jussara V.; Maia, Mariza P.; Stringheta, Paulo C.; Teófilo, Reinaldo F.

2018-04-01

A new method was developed to determine the antioxidant properties of red cabbage extract (Brassica oleracea) by mid (MID) and near (NIR) infrared spectroscopies and partial least squares (PLS) regression. A 70% (v/v) ethanolic extract of red cabbage was concentrated to 9° Brix and further diluted (12 to 100%) in water. The dilutions were used as external standards for the building of PLS models. For the first time, this strategy was applied for building multivariate regression models. Reference analyses and spectral data were obtained from diluted extracts. The determinate properties were total and monomeric anthocyanins, total polyphenols and antioxidant capacity by ABTS (2,2-azino-bis(3-ethyl-benzothiazoline-6-sulfonate)) and DPPH (2,2-diphenyl-1-picrylhydrazyl) methods. Ordered predictors selection (OPS) and genetic algorithm (GA) were used for feature selection before PLS regression (PLS-1). In addition, a PLS-2 regression was applied to all properties simultaneously. PLS-1 models provided more predictive models than did PLS-2 regression. PLS-OPS and PLS-GA models presented excellent prediction results with a correlation coefficient higher than 0.98. However, the best models were obtained using PLS and variable selection with the OPS algorithm and the models based on NIR spectra were considered more predictive for all properties. Then, these models provided a simple, rapid and accurate method for determination of red cabbage extract antioxidant properties and its suitability for use in the food industry.

Overcoming the bottleneck of platelet lysate supply in large-scale clinical expansion of adipose-derived stem cells: A comparison of fresh versus three types of platelet lysates from outdated buffy coat-derived platelet concentrates.

PubMed

Glovinski, Peter V; Herly, Mikkel; Mathiasen, Anders B; Svalgaard, Jesper D; Borup, Rehannah; Talman, Maj-Lis M; Elberg, Jens J; Kølle, Stig-Frederik T; Drzewiecki, Krzysztof T; Fischer-Nielsen, Anne

2017-02-01

Platelet lysates (PL) represent a promising replacement for xenogenic growth supplement for adipose-derived stem cell (ASC) expansions. However, fresh platelets from human blood donors are not clinically feasible for large-scale cell expansion based on their limited supply. Therefore, we tested PLs prepared via three methods from outdated buffy coat-derived platelet concentrates (PCs) to establish an efficient and feasible expansion of ASCs for clinical use. PLs were prepared by the freeze-thaw method from freshly drawn platelets or from outdated buffy coat-derived PCs stored in the platelet additive solution, InterSol. Three types of PLs were prepared from outdated PCs with platelets suspended in either (1) InterSol (not manipulated), (2) InterSol + supplemented with plasma or (3) plasma alone (InterSol removed). Using these PLs, we compared ASC population doubling time, cell yield, differentiation potential and cell surface markers. Gene expression profiles were analyzed using microarray assays, and growth factor concentrations in the cell culture medium were measured using enzyme-linked immunosorbent assay (ELISA). Of the three PL compositions produced from outdated PCs, removal of Intersol and resuspension in plasma prior to the first freezing process was overall the best. This specific outdated PL induced ASC growth kinetics, surface markers, plastic adherence and differentiation potentials comparable with PL from fresh platelets. ASCs expanded in PL from fresh versus outdated PCs exhibited different expressions of 17 overlapping genes, of which 10 were involved in cellular proliferation, although not significantly reflected by cell growth. Only minor differences in growth factor turnover were observed. PLs from outdated platelets may be an efficient and reliable source of human growth supplement allowing for large-scale ASC expansion for clinical use. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Polish Experimental Light-Conducting Teletransmission System,

DTIC Science & Technology

1982-07-26

7 AD-AuGB 959 FOREIGN TECHNOLOGY DIV WRIGHT-PATTERSON AFB OH F/G 17/2 PLS EPERIMENTAL LIHT-CONDUCTIN , TELETRANSMTSSION SYSTEM,(U) JUL 82 Z SZPIGLER...amplifier; 1) transmitter; 2) transit amplifier; 3) receiver Transmitting facilities E7] When designing the tract, it was decided that the terminal _- ups...connections between exchanges. The described line has an experimental character. It enables one to collect many valuable data concerning both the design

Seminal, clinical and colour-Doppler ultrasound correlations of prostatitis-like symptoms in males of infertile couples.

PubMed

Lotti, F; Corona, G; Mondaini, N; Maseroli, E; Rossi, M; Filimberti, E; Noci, I; Forti, G; Maggi, M

2014-01-01

'Prostatitis-like symptoms' (PLS) are a cluster of bothersome conditions defined as 'perineal and/or ejaculatory pain or discomfort and National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) pain subdomain score ≥4' (Nickel's criteria). PLS may originate from the prostate or from other portions of the male genital tract. Although PLS could be associated with 'prostatitis', they should not be confused. The NIH-CPSI is considered the gold-standard for assessing PLS severity. Although previous studies investigated the impact of prostatitis, vesiculitis or epididymitis on semen parameters, correlations between their related symptoms and seminal or scrotal/transrectal colour-Doppler ultrasound (CDU) characteristics have not been carefully determined. And no previous study evaluated the CDU features of PLS in infertile men. This study was aimed at investigating possible associations among NIH-CPSI (total and subdomain) scores and PLS, with seminal, clinical and scrotal/transrectal CDU parameters in a cohort of males of infertile couples. PLS of 400 men (35.8 ± 7.2 years) with a suspected male factor were assessed by the NIH-CPSI. All patients underwent, during the same day, semen analysis, seminal plasma interleukin 8 (sIL-8, a marker of male genital tract inflammation), biochemical evaluation, urine/seminal cultures, scrotal/transrectal CDU. PLS was detected in 39 (9.8%) subjects. After adjusting for age, waist and total testosterone (TT), no association among NIH-CPSI (total or subdomain) scores or PLS and sperm parameters was observed. However, we found a positive association with current positive urine and/or seminal cultures, sIL-8 levels and CDU features suggestive of inflammation of the epididymis, seminal vesicles, prostate, but not of the testis. The aforementioned significant associations of PLS were further confirmed by comparing PLS patients with age-, waist- and TT-matched PLS-free patients (1 : 3 ratio). In conclusion, NIH-CPSI scores and PLS evaluated in males of infertile couples, are not related to sperm parameters, but mainly to clinical and CDU signs of infection/inflammation. © 2013 American Society of Andrology and European Academy of Andrology.

The effect of thermal treatment on the enhancement of detection of adulteration in extra virgin olive oils by synchronous fluorescence spectroscopy and chemometric analysis.

PubMed

Mabood, F; Boqué, R; Folcarelli, R; Busto, O; Jabeen, F; Al-Harrasi, Ahmed; Hussain, J

2016-05-15

In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration. Copyright © 2016 Elsevier B.V. All rights reserved.

The effect of thermal treatment on the enhancement of detection of adulteration in extra virgin olive oils by synchronous fluorescence spectroscopy and chemometric analysis

NASA Astrophysics Data System (ADS)

Mabood, F.; Boqué, R.; Folcarelli, R.; Busto, O.; Jabeen, F.; Al-Harrasi, Ahmed; Hussain, J.

2016-05-01

In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8 h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration.

Identification of meat species by using laser-induced breakdown spectroscopy.

PubMed

Bilge, Gonca; Velioglu, Hasan Murat; Sezer, Banu; Eseller, Kemal Efe; Boyaci, Ismail Hakki

2016-09-01

The aim of the present study is to identify meat species by using laser-induced breakdown spectroscopy (LIBS). Elemental composition differences between meat species were used for meat identification. For this purpose, certain amounts of pork, beef and chicken were collected from different sources and prepared as pellet form for LIBS measurements. The obtained LIBS spectra were evaluated with some chemometric methods, and meat species were qualitatively discriminated with principal component analysis (PCA) method with 83.37% ratio. Pork-beef and chicken-beef meat mixtures were also analyzed with partial least square (PLS) method quantitatively. Determination coefficient (R(2)) and limit of detection (LOD) values were found as 0.994 and 4.4% for pork adulterated beef, and 0.999 and 2.0% for chicken adulterated beef, respectively. In the light of the findings, it was seen that LIBS can be a valuable tool for quality control measurements of meat as a routine method. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multimodal Classification of Mild Cognitive Impairment Based on Partial Least Squares.

PubMed

Wang, Pingyue; Chen, Kewei; Yao, Li; Hu, Bin; Wu, Xia; Zhang, Jiacai; Ye, Qing; Guo, Xiaojuan

2016-08-10

In recent years, increasing attention has been given to the identification of the conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD). Brain neuroimaging techniques have been widely used to support the classification or prediction of MCI. The present study combined magnetic resonance imaging (MRI), 18F-fluorodeoxyglucose PET (FDG-PET), and 18F-florbetapir PET (florbetapir-PET) to discriminate MCI converters (MCI-c, individuals with MCI who convert to AD) from MCI non-converters (MCI-nc, individuals with MCI who have not converted to AD in the follow-up period) based on the partial least squares (PLS) method. Two types of PLS models (informed PLS and agnostic PLS) were built based on 64 MCI-c and 65 MCI-nc from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results showed that the three-modality informed PLS model achieved better classification accuracy of 81.40%, sensitivity of 79.69%, and specificity of 83.08% compared with the single-modality model, and the three-modality agnostic PLS model also achieved better classification compared with the two-modality model. Moreover, combining the three modalities with clinical test score (ADAS-cog), the agnostic PLS model (independent data: florbetapir-PET; dependent data: FDG-PET and MRI) achieved optimal accuracy of 86.05%, sensitivity of 81.25%, and specificity of 90.77%. In addition, the comparison of PLS, support vector machine (SVM), and random forest (RF) showed greater diagnostic power of PLS. These results suggested that our multimodal PLS model has the potential to discriminate MCI-c from the MCI-nc and may therefore be helpful in the early diagnosis of AD.

Structure-activity relationships of an antimicrobial peptide plantaricin s from two-peptide class IIb bacteriocins.

PubMed

Soliman, Wael; Wang, Liru; Bhattacharjee, Subir; Kaur, Kamaljit

2011-04-14

Class IIb bacteriocins are ribosomally synthesized antimicrobial peptides comprising two different peptides synergistically acting in equal amounts for optimal potency. In this study, we demonstrate for the first time potent (nanomolar) antimicrobial activity of a representative class IIb bacteriocin, plantaricin S (Pls), against four pathogenic gram-positive bacteria, including Listeria monocytogenes. The structure-activity relationships for Pls were studied using activity assays, circular dichroism (CD), and molecular dynamics (MD) simulations. The two Pls peptides and five Pls derived fragments were synthesized. The CD spectra of the Pls and selected fragments revealed helical conformations in aqueous 2,2,2-trifluoroethanol. The MD simulations showed that when the two Pls peptides are in antiparallel orientation, the helical regions interact and align, mediated by strong attraction between conserved GxxxG/AxxxA motifs. The results strongly correlate with the antimicrobial activity suggesting that helix-helix alignment of the two Pls peptides and interaction between the conserved motifs are crucial for interaction with the target cell membrane.

A Cultural Diffusion Model for the Rise and Fall of Programming Languages.

PubMed

Valverde, Sergi; Solé, Ricard V

2015-07-01

Our interaction with complex computing machines is mediated by programming languages (PLs), which constitute one of the major innovations in the evolution of technology. PLs allow flexible, scalable, and fast use of hardware and are largely responsible for shaping the history of information technology since the rise of computers in the 1950s. The rapid growth and impact of computers were followed closely by the development of PLs. As occurs with natural, human languages, PLs have emerged and gone extinct. There has been always a diversity of coexisting PLs that compete somewhat while occupying special niches. Here we show that the statistical patterns of language adoption, rise, and fall can be accounted for by a simple model in which a set of programmers can use several PLs, decide to use existing PLs used by other programmers, or decide not to use them. Our results highlight the influence of strong communities of practice in the diffusion of PL innovations.

Prediction of properties and elemental composition of biomass pyrolysis oils by NMR and partial least squares analysis

USDA-ARS?s Scientific Manuscript database

Several partial least squares (PLS) models were created correlating various properties and chemical composition measurements with the 1H and 13C NMR spectra of 73 different of pyrolysis bio-oil samples from various biomass sources (crude and intermediate products), finished oils and small molecule s...

Effect of Thermal Processing towards Lipid Oxidation and Non-enzymatic Browning Reactions of Antartic Krill (Euphausia superba) Meal.

PubMed

Liu, Yanzi; Cong, Peixu; Li, Beijia; Song, Yu; Liu, Yanjun; Xu, Jie; Xue, Changhu

2018-04-13

Antarctic krill is a huge source of biomass and prospective high-quality lipid source. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), nutritionally important lipid components with poor oxidative stability, were used as markers of oxidation during thermal processing of Antarctic krill (Euphausia superba) meal by evaluating the lipolysis, lipid oxidation, and non-enzymatic browning reactions. Liquid chromatography-mass spectrometry of the phospholipids (PLs) and the main oxidation products of free fatty acids (FFAs) and phosphatidylcholine (PC) was effective for evaluating the oxidation of EPA and DHA. During boiling, oxidation of EPA and DHA in the FFA and PC fractions and hydrolysis of the fatty acids at the sn-2 position of the PLs were predominant. The changes in PC during drying were mainly attributed to the oxidation of EPA and DHA. Heat treatment increased the oxidation products and concentration of hydrophobic pyrrole owing to pyrrolization between phosphatidylethanolamine (PE) and the lipid oxidation products. The lipid oxidation level of Antarctic krill increased after drying, owing to prolonged heating under the severe conditions. This article is protected by copyright. All rights reserved.

The Plasmin-Sensitive Protein Pls in Methicillin-Resistant Staphylococcus aureus (MRSA) Is a Glycoprotein.

PubMed

Bleiziffer, Isabelle; Eikmeier, Julian; Pohlentz, Gottfried; McAulay, Kathryn; Xia, Guoqing; Hussain, Muzaffar; Peschel, Andreas; Foster, Simon; Peters, Georg; Heilmann, Christine

2017-01-01

Most bacterial glycoproteins identified to date are virulence factors of pathogenic bacteria, i.e. adhesins and invasins. However, the impact of protein glycosylation on the major human pathogen Staphylococcus aureus remains incompletely understood. To study protein glycosylation in staphylococci, we analyzed lysostaphin lysates of methicillin-resistant Staphylococcus aureus (MRSA) strains by SDS-PAGE and subsequent periodic acid-Schiff's staining. We detected four (>300, ∼250, ∼165, and ∼120 kDa) and two (>300 and ∼175 kDa) glycosylated surface proteins with strain COL and strain 1061, respectively. The ∼250, ∼165, and ∼175 kDa proteins were identified as plasmin-sensitive protein (Pls) by mass spectrometry. Previously, Pls has been demonstrated to be a virulence factor in a mouse septic arthritis model. The pls gene is encoded by the staphylococcal cassette chromosome (SCC)mec type I in MRSA that also encodes the methicillin resistance-conferring mecA and further genes. In a search for glycosyltransferases, we identified two open reading frames encoded downstream of pls on the SCCmec element, which we termed gtfC and gtfD. Expression and deletion analysis revealed that both gtfC and gtfD mediate glycosylation of Pls. Additionally, the recently reported glycosyltransferases SdgA and SdgB are involved in Pls glycosylation. Glycosylation occurs at serine residues in the Pls SD-repeat region and modifying carbohydrates are N-acetylhexosaminyl residues. Functional characterization revealed that Pls can confer increased biofilm formation, which seems to involve two distinct mechanisms. The first mechanism depends on glycosylation of the SD-repeat region by GtfC/GtfD and probably also involves eDNA, while the second seems to be independent of glycosylation as well as eDNA and may involve the centrally located G5 domains. Other previously known Pls properties are not related to the sugar modifications. In conclusion, Pls is a glycoprotein and Pls glycosyl residues can stimulate biofilm formation. Thus, sugar modifications may represent promising new targets for novel therapeutic or prophylactic measures against life-threatening S. aureus infections.

Partial least squares methods for spectrally estimating lunar soil FeO abundance: A stratified approach to revealing nonlinear effect and qualitative interpretation

NASA Astrophysics Data System (ADS)

Li, Lin

2008-12-01

Partial least squares (PLS) regressions were applied to lunar highland and mare soil data characterized by the Lunar Soil Characterization Consortium (LSCC) for spectral estimation of the abundance of lunar soil chemical constituents FeO and Al2O3. The LSCC data set was split into a number of subsets including the total highland, Apollo 16, Apollo 14, and total mare soils, and then PLS was applied to each to investigate the effect of nonlinearity on the performance of the PLS method. The weight-loading vectors resulting from PLS were analyzed to identify mineral species responsible for spectral estimation of the soil chemicals. The results from PLS modeling indicate that the PLS performance depends on the correlation of constituents of interest to their major mineral carriers, and the Apollo 16 soils are responsible for the large errors of FeO and Al2O3 estimates when the soils were modeled along with other types of soils. These large errors are primarily attributed to the degraded correlation FeO to pyroxene for the relatively mature Apollo 16 soils as a result of space weathering and secondary to the interference of olivine. PLS consistently yields very accurate fits to the two soil chemicals when applied to mare soils. Although Al2O3 has no spectrally diagnostic characteristics, this chemical can be predicted for all subset data by PLS modeling at high accuracies because of its correlation to FeO. This correlation is reflected in the symmetry of the PLS weight-loading vectors for FeO and Al2O3, which prove to be very useful for qualitative interpretation of the PLS results. However, this qualitative interpretation of PLS modeling cannot be achieved using principal component regression loading vectors.

Analyses of direct and indirect impacts of a positive list system on pharmaceutical R&D investments.

PubMed

Han, Euna; Kim, Tae Hyun; Jeung, Myung Jin; Lee, Eui-Kyung

2013-07-01

The South Korean government recently enacted a Positive List System (PLS) as a major change of the national formulary listing system and reimbursed prices for pharmaceutical products. Regardless of the primary goal of the PLS, its implementation might have spillover effects by influencing the pharmaceutical industry's research and development (R&D), potentially leading to a variety of responses by firms in relation to their R&D activities. We investigated the spillover effect of the PLS on R&D investments of the pharmaceutical industry in Korea through both direct and indirect channels, examining the influence of the PLS on sales profit and cash flow. Data from 9 years (5 before and 4 after PLS implementation) were drawn from the financial statements of firms whose stocks were exchanged in 2 official stock markets in Korea (526 firms) and additional pharmaceutical firms whose financial performance was officially audited by external reviewers (263 firms). Longitudinal analyses were conducted, using the panel nature of the data to control for permanent unobserved firm heterogeneity. Our results showed that the PLS was directly associated with R&D investments. In contrast, its indirect impacts stemming from the influence on sales profit and cash flow were minimal and statistically nonsignificant. The gross impact of the PLS on R&D investments increased moving further from the enactment year; R&D investments were reduced by 18.3% to 25.8% in 2009-2010 (compared with before PLS implementation) in the firm fixed-effects model. We also found that such negative direct and gross impacts of the PLS on R&D investments were significant only in firms without newly developed chemical entities. Considering the gross negative impact of the PLS on R&D investments of pharmaceutical firms and the heterogeneous response of these firms by the R&D activities, governmental efforts of cost-containment may need to consider the spillover impact of the PLS on pharmaceutical innovation. Copyright © 2013 Elsevier HS Journals, Inc. All rights reserved.

The crucial role of the Pls1 tetraspanin during ascospore germination in Podospora anserina provides an example of the convergent evolution of morphogenetic processes in fungal plant pathogens and saprobes.

PubMed

Lambou, Karine; Malagnac, Fabienne; Barbisan, Crystel; Tharreau, Didier; Lebrun, Marc-Henri; Silar, Philippe

2008-10-01

Pls1 tetraspanins were shown for some pathogenic fungi to be essential for appressorium-mediated penetration into their host plants. We show here that Podospora anserina, a saprobic fungus lacking appressorium, contains PaPls1, a gene orthologous to known PLS1 genes. Inactivation of PaPls1 demonstrates that this gene is specifically required for the germination of ascospores in P. anserina. These ascospores are heavily melanized cells that germinate under inducing conditions through a specific pore. On the contrary, MgPLS1, which fully complements a DeltaPaPls1 ascospore germination defect, has no role in the germination of Magnaporthe grisea nonmelanized ascospores but is required for the formation of the penetration peg at the pore of its melanized appressorium. P. anserina mutants with mutation of PaNox2, which encodes the NADPH oxidase of the NOX2 family, display the same ascospore-specific germination defect as the DeltaPaPls1 mutant. Both mutant phenotypes are suppressed by the inhibition of melanin biosynthesis, suggesting that they are involved in the same cellular process required for the germination of P. anserina melanized ascospores. The analysis of the distribution of PLS1 and NOX2 genes in fungal genomes shows that they are either both present or both absent. These results indicate that the germination of P. anserina ascospores and the formation of the M. grisea appressorium penetration peg use the same molecular machinery that includes Pls1 and Nox2. This machinery is specifically required for the emergence of polarized hyphae from reinforced structures such as appressoria and ascospores. Its recurrent recruitment during fungal evolution may account for some of the morphogenetic convergence observed in fungi.

Xylella taiwanensis sp. nov., causing pear leaf scorch disease.

PubMed

Su, C-C; Deng, W-L; Jan, F-J; Chang, C-J; Huang, H; Shih, H-T; Chen, J

2016-11-01

A Gram-stain-negative, nutritionally fastidious bacterium (PLS229T) causing pear leaf scorch was identified in Taiwan and previously grouped into Xylella fastidiosa. Yet, significant variations between PLS229T and Xylellafastidiosa were noted. In this study, PLS229T was evaluated phenotypically and genotypically against representative strains of Xylellafastidiosa, including strains of the currently known subspecies of Xylellafastidiosa, Xylella fastidiosa subsp. multiplex and 'Xylella fastidiosasubsp.pauca'. Because of the difficulty of in vitro culture characterization, emphases were made to utilize the available whole-genome sequence information. The average nucleotide identity (ANI) values, an alternative for DNA-DNA hybridization relatedness, between PLS229T and Xylellafastidiosa were 83.4-83.9 %, significantly lower than the bacterial species threshold of 95 %. In contrast, sequence similarity of 16S rRNA genes was greater than 98 %, higher than the 97 % threshold to justify if two bacterial strains belong to different species. The uniqueness of PLS229T was also evident by observing only about 87 % similarity in the sequence of the 16S-23S internal transcribed spacer (ITS) between PLS229T and strains of Xylellafastidiosa, discovering significant single nucleotide polymorphisms at 18 randomly selected housekeeping gene loci, observing a distinct fatty acid profile for PLS229T compared with Xylellafastidiosa, and PLS229T having different observable phenotypes, such as different susceptibility to antibiotics. A phylogenetic tree derived from 16S rRNA gene sequences showed a distinct PLS229T phyletic lineage positioning it between Xylellafastidiosa and members of the genus Xanthomonas. On the basis of these data, a novel species, Xylella taiwanensis sp. nov. is proposed. The type strain is PLS229T (=BCRC 80915T=JCM 31187T).

[Exploration of rapidly determining quality of traditional Chinese medicines by (NIR) spectroscopy based on internet sharing mode].

PubMed

Ni, Li-Jun; Luan, Shao-Rong; Zhang, Li-Guo

2016-10-01

Because of the numerous varieties of herbal species and active ingredients in the traditional Chinese medicine(TCM),the traditional methods employed could hardly satisfy the current determination requirements of TCM.The present work proposed an idea to realize rapid determination of the quality of TCM based on near infrared(NIR)spectroscopy and internet sharing mode. Low cost and portable multi-source composite spectrometer was invented by our group for in-site fast measurement of spectra of TCM samples. The database could be set up by sharing spectra and quality detection data of TCM samples among TCM enterprises based on the internet platform.A novel method called as keeping same relationship between X and Y space based on K nearest neighbors(KNN-KSR for short)was applied to predict the contents of effective compounds of the samples. In addition,a comparative study between KNN-KSR and partial least squares(PLS)was conducted. Two datasets were applied to validate above idea:one was about 58 Ginkgo Folium samples samples measured with four near-infrared spectroscopy instruments and two multi-source composite spectrometers,another one was about 80 corn samples available online measured with three NIR instruments. The results show that the KNN-KSR method could obtain more reliable outcomes without correcting spectrum.However transforming the PLS models to other instruments could hardly acquire better predictive results until spectral calibration is performed. Meanwhile,the similar analysis results of total flavonoids and total lactones of Ginkgo Folium samples are achieved on the multi-source composite spectrometers and near-infrared spectroscopy instruments,and the prediction results of KNN-KSR are better than PLS. The idea proposed in present study is in urgent need of more samples spectra, and then to be verified by more case studies. Copyright© by the Chinese Pharmaceutical Association.

Long-term change of disease behavior in Papillon-Lefèvre syndrome: seven years follow-up.

PubMed

Wang, Xinwen; Liu, Yang; Liu, Yuan; Dong, Guangying; Kenney, E Barrie; Liu, Qing; Ma, Zhiwei; Wang, Qingtao

2015-03-01

Papillon-Lefèvre syndrome (PLS) is an autosomal recessive disease, characterized by severe periodontitis and palmoplantar hyperkeratosis. Mutations in the cathepsin C (CTSC) gene are the causative genetic factor. PLS starts at very early age, however, the age associated change of PLS has never been characterized. In this report, four PLS patients with CTSC mutations were followed up for seven years, periodontal condition and serum immunoglobulins (Igs) were recorded. Results showed that periodontal inflammation of PLS peaked at teenage years, but declined with time. At the same time the serum IgE change was consistent with the change, suggesting the possibility of using IgE as a monitoring index for PLS inflammation level, or to develop new target for therapy. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

On-line monitoring the extract process of Fu-fang Shuanghua oral solution using near infrared spectroscopy and different PLS algorithms

NASA Astrophysics Data System (ADS)

Kang, Qian; Ru, Qingguo; Liu, Yan; Xu, Lingyan; Liu, Jia; Wang, Yifei; Zhang, Yewen; Li, Hui; Zhang, Qing; Wu, Qing

2016-01-01

An on-line near infrared (NIR) spectroscopy monitoring method with an appropriate multivariate calibration method was developed for the extraction process of Fu-fang Shuanghua oral solution (FSOS). On-line NIR spectra were collected through two fiber optic probes, which were designed to transmit NIR radiation by a 2 mm flange. Partial least squares (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) algorithms were used comparatively for building the calibration regression models. During the extraction process, the feasibility of NIR spectroscopy was employed to determine the concentrations of chlorogenic acid (CA) content, total phenolic acids contents (TPC), total flavonoids contents (TFC) and soluble solid contents (SSC). High performance liquid chromatography (HPLC), ultraviolet spectrophotometric method (UV) and loss on drying methods were employed as reference methods. Experiment results showed that the performance of siPLS model is the best compared with PLS and iPLS. The calibration models for AC, TPC, TFC and SSC had high values of determination coefficients of (R2) (0.9948, 0.9992, 0.9950 and 0.9832) and low root mean square error of cross validation (RMSECV) (0.0113, 0.0341, 0.1787 and 1.2158), which indicate a good correlation between reference values and NIR predicted values. The overall results show that the on line detection method could be feasible in real application and would be of great value for monitoring the mixed decoction process of FSOS and other Chinese patent medicines.

Exclusion of phospholipases (PLs)-producing bacteria in raw milk flushed with nitrogen gas (N(2)).

PubMed

Munsch-Alatossava, Patricia; Gursoy, Oguz; Alatossava, Tapani

2010-01-01

Prolonged cold storage of raw milks favors the growth of psychrotrophs, which produce heat-resistant exoenzymes of considerable spoilage potential; the bacterial proteases and lipases affect raw milk quality; among them phospholipases (PLs) may target the milk fat globule. More importantly, bacterial PLs are key virulence factors for numerous species. Two studies examined the use of nitrogen (N(2)) gas and examined its effect on psychrotrophs, proteases and lipase producers when the milk was stored in closed vessels; however, the effect on PLs producers is unknown. Here we show that by considering an open system the PLs producers were sooner or later excluded in raw milk (whereas the PLs producers in the non-treated controls culminated at 10(8)CFU/ml), by effective gas treatments that bring oxygen (O(2)) levels in milk lower than 0.1ppm. No increase of the PLs producers among the anaerobes was noticed during the course of the experiments. In the experiments performed at 6.0 degrees C, the delay after which the PLs producers were no longer detectable seemed independent of the initial level of PLs producers in raw milk (lower than 10(3)CFU/ml). We anticipate that flushing pure N(2) gas in raw milk tanks, considered as open systems, along the cold chain of raw milk storage and transportation, may be an additional technique to control psychrotrophs, and may also constitute an interesting perspective for limiting their spoilage and pathogenic potential in food materials in general.

Nurses' Own Birth Experiences Influence Labor Support Attitudes and Behaviors.

PubMed

Aschenbrenner, Ann P; Hanson, Lisa; Johnson, Teresa S; Kelber, Sheryl T

2016-01-01

To describe the attitudes of intrapartum nurses about the importance of and intent to provide professional labor support (PLS); barriers to PLS, such as perceived subjective norms and perceived behavioral control; and relationships among attitudes, behaviors, and nurse and site characteristics. A cross-sectional, mixed-methods, descriptive design was guided by the Theory of Planned Behavior. Three hospital sites in one region of a single Midwestern state. Sixty intrapartum nurses participated. The Labor Support Questionnaire and demographic questionnaire were administered online. The Labor Support Questionnaire is used to measure attitudes about the importance of and intended behaviors associated with labor support. Nurse Caring Behaviors was the highest rated PLS dimension. Participants' own personal birth experiences and length of current intrapartum experience were positively correlated with attitudes about and intent to provide PLS. Barriers to PLS included staffing, documentation, physicians, use of epidural analgesia, doulas, and birth plans. Personal birth and work experience influenced attitudes about and intent to provide PLS and demonstrated the relationships described in the Theory of Planned Behavior. Intrapartum nurses may benefit from an examination of their personal experiences to see how they might influence attitudes about PLS. Enhanced training and expanded labor and birth experience for novice nurses or students may improve attitudes and intended behavior with regard to PLS. Further investigations of the factors that affect integration of PLS into care are important to promote healthy birth outcomes. Copyright © 2016 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

Predicting tropical plant physiology from leaf and canopy spectroscopy

NASA Astrophysics Data System (ADS)

Doughty, C.; Asner, G. P.; Martin, R.

2009-12-01

A broad understanding of tropical forest leaf photosynthesis has long been a goal for tropical forest ecologists, but elusive, due to difficult canopy access and great species diversity. In this paper, we develop an empirical model to predict light saturated sunlit tropical leaf photosynthesis based on leaf and canopy spectra with the goal of developing a high resolution remote sensing technique to measure canopy photosynthesis. To develop this model, we used the partial least squares (PLS) regression technique on three tropical forest datasets (~168 species), two in Hawaii and one in the tropical rainforest module of Biosphere 2 (B2L). For each species, we measured light saturated photosynthesis (A), light and CO2 saturated photosynthesis (Amax), day respiration (R), leaf spectra (400-2500 nm with 1 nm sampling), leaf nitrogen (N), chlorophyll A and B, carotenoids, and specific leaf area (SLA). On a subset of species we measured Jmax and Vcmax based on light and Aci curves. The model best predicted A (r2 = 0.74, root mean square error (RMSE) = 2.85 µmol m-2 s-1), R (r2 of 0.48, RMSE of -0.52 µmol m-2 s-1) followed by Amax (r2 of 0.47, RMSE of 5.1 µmol m-2 s-1), Jmax, (R2 = 0.52, RMSE = 39) and VCmax (R2 = 0.39, RMSE = 36). The PLS weightings, which indicate which wavelengths most contribute to the model, indicated that physiology weightings were most similar to nitrogen weightings, followed by chlorophyll and SLA. We combined leaf-level reflectance and transmittance with a canopy radiative transfer model to simulate top-of-canopy reflectance, and found that canopy spectra are a better predictor of light saturated photosynthesis more strongly (RMSE = 2.4 µmol m-2 s-1) than are leaf spectra (RMSE = 2.85 µmol m-2 s-1). The results suggest that there is potential for this technique to be used with high fidelity imaging spectrometers to remotely sense tropical forest canopy photosynthesis.

Coexistence of antiphospholipid antibodies and cephalalgia.

PubMed

Islam, Md Asiful; Alam, Fahmida; Gan, Siew Hua; Cavestro, Cinzia; Wong, Kah Keng

2018-03-01

Background The occurrence of antiphospholipid antibodies (aPLs) and headache comorbidity in the presence or absence of underlying autoimmune diseases remains unclear. Aim The aim of this review was to summarize the relationship between headache and aPLs based on evidences from cohort studies and case reports, in addition to examining the treatment strategies that resolved headache in aPLs-positive individuals. Methods A comprehensive literature search was conducted through PubMed, ISI Web of Science and Google Scholar. A total of 559 articles were screened and the appropriate articles were selected based on quality and level of evidence. Results Cohort studies (n = 27) from Europe, North America and Asia demonstrated comorbidity of aPLs and headache in antiphospholipid syndrome, systemic lupus erythematosus (SLE) and neuropsychiatric SLE patients. Significantly higher association between migraine and aPLs was observed (n = 170/779; p < 0.0001) in individuals without any underlying diseases. Our analysis of shortlisted case reports (n = 17) showed that a higher frequency of anticardiolipin antibodies were present in subjects with different autoimmune disorders (70.6%). Corticosteroids were highly effective in resolving headache in aPLs-positive individuals. Conclusion Higher frequency of comorbidity between aPLs and headache was observed in healthy individuals and patient cases. Therefore, experimental studies are warranted to evaluate the aPLs-induced pathogenic mechanism of headache.

Nearest clusters based partial least squares discriminant analysis for the classification of spectral data.

PubMed

Song, Weiran; Wang, Hui; Maguire, Paul; Nibouche, Omar

2018-06-07

Partial Least Squares Discriminant Analysis (PLS-DA) is one of the most effective multivariate analysis methods for spectral data analysis, which extracts latent variables and uses them to predict responses. In particular, it is an effective method for handling high-dimensional and collinear spectral data. However, PLS-DA does not explicitly address data multimodality, i.e., within-class multimodal distribution of data. In this paper, we present a novel method termed nearest clusters based PLS-DA (NCPLS-DA) for addressing the multimodality and nonlinearity issues explicitly and improving the performance of PLS-DA on spectral data classification. The new method applies hierarchical clustering to divide samples into clusters and calculates the corresponding centre of every cluster. For a given query point, only clusters whose centres are nearest to such a query point are used for PLS-DA. Such a method can provide a simple and effective tool for separating multimodal and nonlinear classes into clusters which are locally linear and unimodal. Experimental results on 17 datasets, including 12 UCI and 5 spectral datasets, show that NCPLS-DA can outperform 4 baseline methods, namely, PLS-DA, kernel PLS-DA, local PLS-DA and k-NN, achieving the highest classification accuracy most of the time. Copyright © 2018 Elsevier B.V. All rights reserved.

Pyogenic liver abscess and peritonitis due to Rhizopus oryzae in a child with Papillon-Lefevre syndrome.

PubMed

Dalgic, Buket; Bukulmez, Aysegul; Sari, Sinan

2011-06-01

Papillon-Lefevre syndrome (PLS) is an autosomal recessive disease that is characterized by symmetric palmoplantar keratodermatitis and severe periodontal destruction. Mutations in the cathepsin C gene (CTSC) have recently been detected in PLS. Immune dysregulation, due to a mutation in CTSC, increases the risk of pyogenic infections in PLS patients. A child with PLS is presented here with liver abscesses and peritonitis caused by Rhizopus oryzae. His liver abscess and peritonitis were cured with amphotericin B without surgical care. This is the first case in the literature liver abscess due to Rhizopus oryzae in a child with PLS.

Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data

NASA Astrophysics Data System (ADS)

Yin, Shen; Wang, Guang; Yang, Xu

2014-07-01

In practical industrial applications, the key performance indicator (KPI)-related prediction and diagnosis are quite important for the product quality and economic benefits. To meet these requirements, many advanced prediction and monitoring approaches have been developed which can be classified into model-based or data-driven techniques. Among these approaches, partial least squares (PLS) is one of the most popular data-driven methods due to its simplicity and easy implementation in large-scale industrial process. As PLS is totally based on the measured process data, the characteristics of the process data are critical for the success of PLS. Outliers and missing values are two common characteristics of the measured data which can severely affect the effectiveness of PLS. To ensure the applicability of PLS in practical industrial applications, this paper introduces a robust version of PLS to deal with outliers and missing values, simultaneously. The effectiveness of the proposed method is finally demonstrated by the application results of the KPI-related prediction and diagnosis on an industrial benchmark of Tennessee Eastman process.

[Research on partial least squares for determination of impurities in the presence of high concentration of matrix by ICP-AES].

PubMed

Wang, Yan-peng; Gong, Qi; Yu, Sheng-rong; Liu, You-yan

2012-04-01

A method for detecting trace impurities in high concentration matrix by ICP-AES based on partial least squares (PLS) was established. The research showed that PLS could effectively correct the interference caused by high level of matrix concentration error and could withstand higher concentrations of matrix than multicomponent spectral fitting (MSF). When the mass ratios of matrix to impurities were from 1 000 : 1 to 20 000 : 1, the recoveries of standard addition were between 95% and 105% by PLS. For the system in which interference effect has nonlinear correlation with the matrix concentrations, the prediction accuracy of normal PLS method was poor, but it can be improved greatly by using LIN-PPLS, which was based on matrix transformation of sample concentration. The contents of Co, Pb and Ga in stream sediment (GBW07312) were detected by MSF, PLS and LIN-PPLS respectively. The results showed that the prediction accuracy of LIN-PPLS was better than PLS, and the prediction accuracy of PLS was better than MSF.

External characteristic determination of eggs and cracked eggs identification using spectral signature

PubMed Central

Xie, Chuanqi; He, Yong

2016-01-01

This study was carried out to use hyperspectral imaging technique for determining color (L*, a* and b*) and eggshell strength and identifying cracked chicken eggs. Partial least squares (PLS) models based on full and selected wavelengths suggested by regression coefficient (RC) method were established to predict the four parameters, respectively. Partial least squares-discriminant analysis (PLS-DA) and RC-partial least squares-discriminant analysis (RC-PLS-DA) models were applied to identify cracked eggs. PLS models performed well with the correlation coefficient (rp) of 0.788 for L*, 0.810 for a*, 0.766 for b* and 0.835 for eggshell strength. RC-PLS models also obtained the rp of 0.771 for L*, 0.806 for a*, 0.767 for b* and 0.841 for eggshell strength. The classification results were 97.06% in PLS-DA model and 88.24% in RC-PLS-DA model. It demonstrated that hyperspectral imaging technique has the potential to be used to detect color and eggshell strength values and identify cracked chicken eggs. PMID:26882990

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

Firefly as a novel swarm intelligence variable selection method in spectroscopy.

PubMed

Goodarzi, Mohammad; dos Santos Coelho, Leandro

2014-12-10

A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy.

PubMed

Kuligowski, Julia; Carrión, David; Quintás, Guillermo; Garrigues, Salvador; de la Guardia, Miguel

2011-01-01

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).

Cloning of ε-poly-L-lysine (ε-PL) synthetase gene from a newly isolated ε-PL-producing Streptomyces albulus NK660 and its heterologous expression in Streptomyces lividans

PubMed Central

Geng, Weitao; Yang, Chao; Gu, Yanyan; Liu, Ruihua; Guo, Wenbin; Wang, Xiaomeng; Song, Cunjiang; Wang, Shufang

2014-01-01

ε-Poly-L-lysine (ε-PL), showing a wide range of antimicrobial activity, is now industrially produced as a food additive by a fermentation process. A new strain capable of producing ε-PL was isolated from a soil sample collected from Gutian, Fujian Province, China. Based on its morphological and biochemical features and phylogenetic similarity with 16S rRNA gene, the strain was identified as Streptomyces albulus and named NK660. The yield of ε-PL in 30 l fed-batch fermentation with pH control was 4.2 g l−1 when using glycerol as the carbon source. The structure of ε-PL was determined by nuclear magnetic resonance (NMR) and matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS). Previous studies have shown that the antimicrobial activity of ε-PL is dependent on its molecular size. In this study, the polymerization degree of the ε-PL produced by strain NK660 ranged from 19 to 33 L-lysine monomers, with the main component consisting of 24–30 L-lysine monomers, which implied that the ε-PL might have higher antimicrobial activity. Furthermore, the ε-PL synthetase gene (pls) was cloned from strain NK660 by genome walking. The pls gene with its native promoter was heterologously expressed in Streptomyces lividans ZX7, and the recombinant strain was capable of synthesizing ε-PL. Here, we demonstrated for the first time heterologous expression of the pls gene in S. lividans. The heterologous expression of pls gene in S. lividans will open new avenues for elucidating the molecular mechanisms of ε-PL synthesis. PMID:24423427

Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis

NASA Astrophysics Data System (ADS)

Mabood, Fazal; Boqué, Ricard; Folcarelli, Rita; Busto, Olga; Al-Harrasi, Ahmed; Hussain, Javid

2015-05-01

We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8 h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720 nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20 nm, 40 nm, 60 nm and 80 nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20 nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.

Hyphopodium-Specific VdNoxB/VdPls1-Dependent ROS-Ca2+ Signaling Is Required for Plant Infection by Verticillium dahliae.

PubMed

Zhao, Yun-Long; Zhou, Ting-Ting; Guo, Hui-Shan

2016-07-01

Verticillium dahliae is a phytopathogenic fungus obligate in root infection. A few hyphopodia differentiate from large numbers of hyphae after conidia germination on the root surface for further infection. However, the molecular features and role of hyphopodia in the pathogenicity of V. dahliae remain elusive. In this study, we found that the VdPls1, a tetraspanin, and the VdNoxB, a catalytic subunit of membrane-bound NADPH oxidases for reactive oxygen species (ROS) production, were specifically expressed in hyphopodia. VdPls1 and VdNoxB highly co-localize with the plasma membrane at the base of hyphopodia, where ROS and penetration pegs are generated. Mutant strains, VdΔnoxb and VdΔpls1, in which VdPls1 and VdNoxB were deleted, respectively, developed defective hyphpodia incapable of producing ROS and penetration pegs. Defective plasma membrane localization of VdNoxB in VdΔpls1 demonstrates that VdPls1 functions as an adaptor protein for the recruitment and activation of the VdNoxB. Furthermore, in VdΔnoxb and VdΔpls1, tip-high Ca2+ accumulation was impaired in hyphopodia, but not in vegetative hyphal tips. Moreover, nuclear targeting of VdCrz1 and activation of calcineurin-Crz1 signaling upon hyphopodium induction in wild-type V. dahliae was impaired in both knockout mutants, indicating that VdPls1/VdNoxB-dependent ROS was specifically required for tip-high Ca2+ elevation in hyphopodia to activate the transcription factor VdCrz1 in the regulation of penetration peg formation. Together with the loss of virulence of VdΔnoxb and VdΔpls1, which are unable to initiate colonization in cotton plants, our data demonstrate that VdNoxB/VdPls1-mediated ROS production activates VdCrz1 signaling through Ca2+ elevation in hyphopodia, infectious structures of V. dahliae, to regulate penetration peg formation during the initial colonization of cotton roots.

Structure, Antimicrobial Activities and Mode of Interaction with Membranes of Bovel Phylloseptins from the Painted-Belly Leaf Frog, Phyllomedusa sauvagii

PubMed Central

Raja, Zahid; André, Sonia; Piesse, Christophe; Sereno, Denis; Nicolas, Pierre; Foulon, Thierry

2013-01-01

Transcriptomic and peptidomic analysis of skin secretions from the Painted-belly leaf frog Phyllomedusa sauvagii led to the identification of 5 novel phylloseptins (PLS-S2 to -S6) and also of phylloseptin-1 (PSN-1, here renamed PLS-S1), the only member of this family previously isolated in this frog. Synthesis and characterization of these phylloseptins revealed differences in their antimicrobial activities. PLS-S1, -S2, and -S4 (79–95% amino acid sequence identity; net charge  = +2) were highly potent and cidal against Gram-positive bacteria, including multidrug resistant S. aureus strains, and killed the promastigote stage of Leishmania infantum, L. braziliensis and L. major. By contrast, PLS-S3 (95% amino acid identity with PLS-S2; net charge  = +1) and -S5 (net charge  = +2) were found to be almost inactive against bacteria and protozoa. PLS-S6 was not studied as this peptide was closely related to PLS-S1. Differential scanning calorimetry on anionic and zwitterionic multilamellar vesicles combined with circular dichroism spectroscopy and membrane permeabilization assays on bacterial cells indicated that PLS-S1, -S2, and -S4 are structured in an amphipathic α-helix that disrupts the acyl chain packing of anionic lipid bilayers. As a result, regions of two coexisting phases could be formed, one phase rich in peptide and the other lipid-rich. After reaching a threshold peptide concentration, the disruption of lipid packing within the bilayer may lead to local cracks and disintegration of the microbial membrane. Differences in the net charge, α-helical folding propensity, and/or degree of amphipathicity between PLS-S1, -S2 and -S4, and between PLS-S3 and -S5 appear to be responsible for their marked differences in their antimicrobial activities. In addition to the detailed characterization of novel phylloseptins from P. sauvagii, our study provides additional data on the previously isolated PLS-S1 and on the mechanism of action of phylloseptins. PMID:23967105

[Spectral quantitative analysis by nonlinear partial least squares based on neural network internal model for flue gas of thermal power plant].

PubMed

Cao, Hui; Li, Yao-Jiang; Zhou, Yan; Wang, Yan-Xia

2014-11-01

To deal with nonlinear characteristics of spectra data for the thermal power plant flue, a nonlinear partial least square (PLS) analysis method with internal model based on neural network is adopted in the paper. The latent variables of the independent variables and the dependent variables are extracted by PLS regression firstly, and then they are used as the inputs and outputs of neural network respectively to build the nonlinear internal model by train process. For spectra data of flue gases of the thermal power plant, PLS, the nonlinear PLS with the internal model of back propagation neural network (BP-NPLS), the non-linear PLS with the internal model of radial basis function neural network (RBF-NPLS) and the nonlinear PLS with the internal model of adaptive fuzzy inference system (ANFIS-NPLS) are compared. The root mean square error of prediction (RMSEP) of sulfur dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 16.96%, 16.60% and 19.55% than that of PLS, respectively. The RMSEP of nitric oxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 8.60%, 8.47% and 10.09% than that of PLS, respectively. The RMSEP of nitrogen dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 2.11%, 3.91% and 3.97% than that of PLS, respectively. Experimental results show that the nonlinear PLS is more suitable for the quantitative analysis of glue gas than PLS. Moreover, by using neural network function which can realize high approximation of nonlinear characteristics, the nonlinear partial least squares method with internal model mentioned in this paper have well predictive capabilities and robustness, and could deal with the limitations of nonlinear partial least squares method with other internal model such as polynomial and spline functions themselves under a certain extent. ANFIS-NPLS has the best performance with the internal model of adaptive fuzzy inference system having ability to learn more and reduce the residuals effectively. Hence, ANFIS-NPLS is an accurate and useful quantitative thermal power plant flue gas analysis method.

The Crucial Role of the Pls1 Tetraspanin during Ascospore Germination in Podospora anserina Provides an Example of the Convergent Evolution of Morphogenetic Processes in Fungal Plant Pathogens and Saprobes▿ †

PubMed Central

Lambou, Karine; Malagnac, Fabienne; Barbisan, Crystel; Tharreau, Didier; Lebrun, Marc-Henri; Silar, Philippe

2008-01-01

Pls1 tetraspanins were shown for some pathogenic fungi to be essential for appressorium-mediated penetration into their host plants. We show here that Podospora anserina, a saprobic fungus lacking appressorium, contains PaPls1, a gene orthologous to known PLS1 genes. Inactivation of PaPls1 demonstrates that this gene is specifically required for the germination of ascospores in P. anserina. These ascospores are heavily melanized cells that germinate under inducing conditions through a specific pore. On the contrary, MgPLS1, which fully complements a ΔPaPls1 ascospore germination defect, has no role in the germination of Magnaporthe grisea nonmelanized ascospores but is required for the formation of the penetration peg at the pore of its melanized appressorium. P. anserina mutants with mutation of PaNox2, which encodes the NADPH oxidase of the NOX2 family, display the same ascospore-specific germination defect as the ΔPaPls1 mutant. Both mutant phenotypes are suppressed by the inhibition of melanin biosynthesis, suggesting that they are involved in the same cellular process required for the germination of P. anserina melanized ascospores. The analysis of the distribution of PLS1 and NOX2 genes in fungal genomes shows that they are either both present or both absent. These results indicate that the germination of P. anserina ascospores and the formation of the M. grisea appressorium penetration peg use the same molecular machinery that includes Pls1 and Nox2. This machinery is specifically required for the emergence of polarized hyphae from reinforced structures such as appressoria and ascospores. Its recurrent recruitment during fungal evolution may account for some of the morphogenetic convergence observed in fungi. PMID:18757568

Improved Quantitative Analysis of Ion Mobility Spectrometry by Chemometric Multivariate Calibration

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

Fraga, Carlos G.; Kerr, Dayle; Atkinson, David A.

2009-09-01

Traditional peak-area calibration and the multivariate calibration methods of principle component regression (PCR) and partial least squares (PLS), including unfolded PLS (U-PLS) and multi-way PLS (N-PLS), were evaluated for the quantification of 2,4,6-trinitrotoluene (TNT) and cyclo-1,3,5-trimethylene-2,4,6-trinitramine (RDX) in Composition B samples analyzed by temperature step desorption ion mobility spectrometry (TSD-IMS). The true TNT and RDX concentrations of eight Composition B samples were determined by high performance liquid chromatography with UV absorbance detection. Most of the Composition B samples were found to have distinct TNT and RDX concentrations. Applying PCR and PLS on the exact same IMS spectra used for themore » peak-area study improved quantitative accuracy and precision approximately 3 to 5 fold and 2 to 4 fold, respectively. This in turn improved the probability of correctly identifying Composition B samples based upon the estimated RDX and TNT concentrations from 11% with peak area to 44% and 89% with PLS. This improvement increases the potential of obtaining forensic information from IMS analyzers by providing some ability to differentiate or match Composition B samples based on their TNT and RDX concentrations.« less

Multivariate analysis applied to the study of spatial distributions found in drug-eluting stent coatings by confocal Raman microscopy.

PubMed

Balss, Karin M; Long, Frederick H; Veselov, Vladimir; Orana, Argjenta; Akerman-Revis, Eugena; Papandreou, George; Maryanoff, Cynthia A

2008-07-01

Multivariate data analysis was applied to confocal Raman measurements on stents coated with the polymers and drug used in the CYPHER Sirolimus-eluting Coronary Stents. Partial least-squares (PLS) regression was used to establish three independent calibration curves for the coating constituents: sirolimus, poly(n-butyl methacrylate) [PBMA], and poly(ethylene-co-vinyl acetate) [PEVA]. The PLS calibrations were based on average spectra generated from each spatial location profiled. The PLS models were tested on six unknown stent samples to assess accuracy and precision. The wt % difference between PLS predictions and laboratory assay values for sirolimus was less than 1 wt % for the composite of the six unknowns, while the polymer models were estimated to be less than 0.5 wt % difference for the combined samples. The linearity and specificity of the three PLS models were also demonstrated with the three PLS models. In contrast to earlier univariate models, the PLS models achieved mass balance with better accuracy. This analysis was extended to evaluate the spatial distribution of the three constituents. Quantitative bitmap images of drug-eluting stent coatings are presented for the first time to assess the local distribution of components.

Quantification of amine functional groups and their influence on OM/OC in the IMPROVE network

NASA Astrophysics Data System (ADS)

Kamruzzaman, Mohammed; Takahama, Satoshi; Dillner, Ann M.

2018-01-01

Recently, we developed a method using FT-IR spectroscopy coupled with partial least squares (PLS) regression to measure the four most abundant organic functional groups, aliphatic C-H, alcohol OH, carboxylic acid OH and carbonyl C=O, in atmospheric particulate matter. These functional groups are summed to estimate organic matter (OM) while the carbon from the functional groups is summed to estimate organic carbon (OC). With this method, OM and OM/OC can be estimated for each sample rather than relying on one assumed value to convert OC measurements to OM. This study continues the development of the FT-IR and PLS method for estimating OM and OM/OC by including the amine functional group. Amines are ubiquitous in the atmosphere and come from motor vehicle exhaust, animal husbandry, biomass burning, and vegetation among other sources. In this study, calibration standards for amines are produced by aerosolizing individual amine compounds and collecting them on PTFE filters using an IMPROVE sampler, thereby mimicking the filter media and collection geometry of ambient standards. The moles of amine functional group on each standard and a narrow range of amine-specific wavenumbers in the FT-IR spectra (wavenumber range 1 550-1 500 cm-1) are used to develop a PLS calibration model. The PLS model is validated using three methods: prediction of a set of laboratory standards not included in the model, a peak height analysis and a PLS model with a broader wavenumber range. The model is then applied to the ambient samples collected throughout 2013 from 16 IMPROVE sites in the USA. Urban sites have higher amine concentrations than most rural sites, but amine functional groups account for a lower fraction of OM at urban sites. Amine concentrations, contributions to OM and seasonality vary by site and sample. Amine has a small impact on the annual average OM/OC for urban sites, but for some rural sites including amine in the OM/OC calculations increased OM/OC by 0.1 or more.

Genetic and Physiological Studies of Bacillus anthracis Related to Development of an Improved Vaccine

DTIC Science & Technology

1987-07-01

nontransformable Bacillus species such as B. anthracis. Our results suggest that plasmid pLS20 of Bacillus subtilis ( natto ), which promotes transfer of the...mobilizing pBC16, pLS20 mediates transfer of the B. subtills ( natto ) plasmid pLS19 and the Staphylococcus aureus plasmid pUB110. To facilitate direct...and (v) transformation of B. cereus and B. anthracis with plasmid DNA. The 55-kb plasmid, pLS20, of Bacillus subtilis ( natto ) 3335 promotes tr msfer

Effective apatinib treatment of pleomorphic liposarcoma: A case report.

PubMed

Yan, Peng; Sun, Mei-Li; Sun, Yu-Ping; Liu, Chuan-Yong

2017-08-01

Pleomorphic liposarcoma (PLS) is a rare and aggressive malignant tumor, and both radiation and conventional cytotoxic chemotherapy remain controversial for metastatic or unresectable disease. We presented an 81-year-old Chinese woman with advanced PLS who received apatinib after failure chemotherapy. The patient was diagnosed as having PLS by biopsy. After a failed chemotherapy, apatinib started to be taken orally 425 mg per day. This patient achieved 3-month progression-free survival (PFS) and a higher quality of life. Meanwhile, this patient suffered grade 2 hypertension and grade 3 hand-foot syndrome (HFS). In this case, apatinib presented good efficacy and safety to treat PLS. Randomized clinical studies are required to confirm the efficacy and safety of apatinib in the treatment of PLS.

An In Silico Method for Screening Nicotine Derivatives as Cytochrome P450 2A6 Selective Inhibitors Based on Kernel Partial Least Squares

PubMed Central

Wang, Yonghua; Li, Yan; Wang, Bin

2007-01-01

Nicotine and a variety of other drugs and toxins are metabolized by cytochrome P450 (CYP) 2A6. The aim of the present study was to build a quantitative structure-activity relationship (QSAR) model to predict the activities of nicotine analogues on CYP2A6. Kernel partial least squares (K-PLS) regression was employed with the electro-topological descriptors to build the computational models. Both the internal and external predictabilities of the models were evaluated with test sets to ensure their validity and reliability. As a comparison to K-PLS, a standard PLS algorithm was also applied on the same training and test sets. Our results show that the K-PLS produced reasonable results that outperformed the PLS model on the datasets. The obtained K-PLS model will be helpful for the design of novel nicotine-like selective CYP2A6 inhibitors.

Pigmented striae of the anterior lens capsule and age-associated pigment dispersion of variable degree in a group of older African-Americans: an age, race, and gender matched study.

PubMed

Roberts, D K; Winters, J E; Castells, D D; Clark, C A; Teitelbaum, B A

2001-01-01

To investigate pigmented striae of the anterior lens capsule in African-Americans, a potential indicator of significant anterior segment pigment dispersion. A group of 40 African-American subjects who exhibited pigmented lens striae (PLS) were identified from a non-referred, primary eye care population in Chicago, IL, USA. These subjects were then compared to an age, race, and gender matched control group relative to refractive error and the presence or absence of diabetes and hypertension. The PLS subjects (mean age = 65.4 +/- 8.8 years, range = 50-87 years) consisted of 36 females and 4 males. PLS were bilateral in 36 (85%) of the 40 subjects. Among the eyes with PLS, 21 (55%) of 38 right eyes and 22 (61%) of 36 left eyes also had significant corneal endothelial pigment dusting, commonly in the shape of a Krukenberg's spindle. Ten (25%) of the PLS subjects had either glaucoma or ocular hypertension (7 bilateral, 3 unilateral). The presence of trabecular meshwork pigment varied from minimal to heavy. The mean +/- SD (range) refractive error of the PLS right eyes was +1.61 +/- 1.43D (-1.50 to +5.00D) and +1.77 +/- 1.37D (-1.00 to +5.00D) for the left eyes. Based on these data, the PLS right eyes were +1.63D (Student's t, p = 0.0001; 95% CI = +0.82 to +2.44D) more hyperopic on average than the control right eyes, and the PLS left eyes were +1.77D (p = 0.0001; 95% CI = +0.92 to +2.63D) more hyperopic on average than the control left eyes. Trend analysis showed a gradually increasing likelihood of PLS with increasing magnitude of hyperopia in both eyes (Mantel-Haenszel chi-square, p = 0.001). Among PLS subjects, 24 (60%) of 40 were hypertensive and 9 (23%) of 40 were diabetic. However, these proportions were not significantly different (two-tailed Fisher's exact test; hypertension: p = 0.30; diabetes: p = 0.70) from the randomly selected controls. Among our African-American group, which consisted predominately of females >50 years of age, the likelihood of PLS increased with increasing hyperopic refractive error. This finding is consistent with the possibility that PLS may, in some circumstances, indicate a significant pigment dispersal process due to iris-lens rubbing that may be associated with crowding of anterior segment structures. Additional study is warranted to further assess the nature of PLS, their precise relationship with an age-related pigment dispersal process, and their true significance as a risk factor for development of glaucoma.

Quantitative methods for structural characterization of proteins based on deep UV resonance Raman spectroscopy.

PubMed

Shashilov, Victor A; Sikirzhytski, Vitali; Popova, Ludmila A; Lednev, Igor K

2010-09-01

Here we report on novel quantitative approaches for protein structural characterization using deep UV resonance Raman (DUVRR) spectroscopy. Specifically, we propose a new method combining hydrogen-deuterium (HD) exchange and Bayesian source separation for extracting the DUVRR signatures of various structural elements of aggregated proteins including the cross-beta core and unordered parts of amyloid fibrils. The proposed method is demonstrated using the set of DUVRR spectra of hen egg white lysozyme acquired at various stages of HD exchange. Prior information about the concentration matrix and the spectral features of the individual components was incorporated into the Bayesian equation to eliminate the ill-conditioning of the problem caused by 100% correlation of the concentration profiles of protonated and deuterated species. Secondary structure fractions obtained by partial least squares (PLS) and least squares support vector machines (LS-SVMs) were used as the initial guess for the Bayessian source separation. Advantages of the PLS and LS-SVMs methods over the classical least squares calibration (CLSC) are discussed and illustrated using the DUVRR data of the prion protein in its native and aggregated forms. Copyright (c) 2010 Elsevier Inc. All rights reserved.

In Situ Analysis of Metabolic Characteristics Reveals the Key Yeast in the Spontaneous and Solid-State Fermentation Process of Chinese Light-Style Liquor

PubMed Central

Kong, Yu; Wu, Qun; Zhang, Yan

2014-01-01

The in situ metabolic characteristics of the yeasts involved in spontaneous fermentation process of Chinese light-style liquor are poorly understood. The covariation between metabolic profiles and yeast communities in Chinese light-style liquor was modeled using the partial least square (PLS) regression method. The diversity of yeast species was evaluated by sequence analysis of the 26S ribosomal DNA (rDNA) D1/D2 domains of cultivable yeasts, and the volatile compounds in fermented grains were analyzed by gas chromatography (GC)-mass spectrometry (MS). Eight yeast species and 58 volatile compounds were identified, respectively. The modulation of 16 of these volatile compounds was associated with variations in the yeast population (goodness of prediction [Q2] > 20%). The results showed that Pichia anomala was responsible for the characteristic aroma of Chinese liquor, through the regulation of several important volatile compounds, such as ethyl lactate, octanoic acid, and ethyl tetradecanoate. Correspondingly, almost all of the compounds associated with P. anomala were detected in a pure culture of this yeast. In contrast to the PLS regression results, however, ethyl lactate and ethyl isobutyrate were not detected in the same pure culture, which indicated that some metabolites could be generated by P. anomala only when it existed in a community with other yeast species. Furthermore, different yeast communities provided different volatile patterns in the fermented grains, which resulted in distinct flavor profiles in the resulting liquors. This study could help identify the key yeast species involved in spontaneous fermentation and provide a deeper understanding of the role of individual yeast species in the community. PMID:24727269

Kernel PLS-SVC for Linear and Nonlinear Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Matthews, Bryan

2003-01-01

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

Effective apatinib treatment of pleomorphic liposarcoma

PubMed Central

Yan, Peng; Sun, Mei-Li; Sun, Yu-Ping; Liu, Chuan-Yong

2017-01-01

Abstract Rationale: Pleomorphic liposarcoma (PLS) is a rare and aggressive malignant tumor, and both radiation and conventional cytotoxic chemotherapy remain controversial for metastatic or unresectable disease. Patient Concerns: We presented an 81-year-old Chinese woman with advanced PLS who received apatinib after failure chemotherapy. Diagnoses: The patient was diagnosed as having PLS by biopsy. Interventions: After a failed chemotherapy, apatinib started to be taken orally 425 mg per day. Outcomes: This patient achieved 3-month progression-free survival (PFS) and a higher quality of life. Meanwhile, this patient suffered grade 2 hypertension and grade 3 hand–foot syndrome (HFS). Lessons: In this case, apatinib presented good efficacy and safety to treat PLS. Randomized clinical studies are required to confirm the efficacy and safety of apatinib in the treatment of PLS. PMID:28816958

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel-kerosene mixtures: a comparative study.

PubMed

Divya, O; Mishra, Ashok K

2007-05-29

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis.

PubMed

Nespeca, Maurilio Gustavo; Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000-650 cm -1 . The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis

PubMed Central

Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000–650 cm−1. The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time. PMID:29629209

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

NASA Astrophysics Data System (ADS)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

The Picmonic(®) Learning System: enhancing memory retention of medical sciences, using an audiovisual mnemonic Web-based learning platform.

PubMed

Yang, Adeel; Goel, Hersh; Bryan, Matthew; Robertson, Ron; Lim, Jane; Islam, Shehran; Speicher, Mark R

2014-01-01

Medical students are required to retain vast amounts of medical knowledge on the path to becoming physicians. To address this challenge, multimedia Web-based learning resources have been developed to supplement traditional text-based materials. The Picmonic(®) Learning System (PLS; Picmonic, Phoenix, AZ, USA) is a novel multimedia Web-based learning platform that delivers audiovisual mnemonics designed to improve memory retention of medical sciences. A single-center, randomized, subject-blinded, controlled study was conducted to compare the PLS with traditional text-based material for retention of medical science topics. Subjects were randomly assigned to use two different types of study materials covering several diseases. Subjects randomly assigned to the PLS group were given audiovisual mnemonics along with text-based materials, whereas subjects in the control group were given the same text-based materials with key terms highlighted. The primary endpoints were the differences in performance on immediate, 1 week, and 1 month delayed free-recall and paired-matching tests. The secondary endpoints were the difference in performance on a 1 week delayed multiple-choice test and self-reported satisfaction with the study materials. Differences were calculated using unpaired two-tailed t-tests. PLS group subjects demonstrated improvements of 65%, 161%, and 208% compared with control group subjects on free-recall tests conducted immediately, 1 week, and 1 month after study of materials, respectively. The results of performance on paired-matching tests showed an improvement of up to 331% for PLS group subjects. PLS group subjects also performed 55% greater than control group subjects on a 1 week delayed multiple choice test requiring higher-order thinking. The differences in test performance between the PLS group subjects and the control group subjects were statistically significant (P<0.001), and the PLS group subjects reported higher overall satisfaction with the material. The data of this pilot site demonstrate marked improvements in the retention of disease topics when using the PLS compared with traditional text-based materials. The use of the PLS in medical education is supported.

The assessment of the performance of covariance-based structural equation modeling and partial least square path modeling

NASA Astrophysics Data System (ADS)

Aimran, Ahmad Nazim; Ahmad, Sabri; Afthanorhan, Asyraf; Awang, Zainudin

2017-05-01

Structural equation modeling (SEM) is the second generation statistical analysis technique developed for analyzing the inter-relationships among multiple variables in a model. Previous studies have shown that there seemed to be at least an implicit agreement about the factors that should drive the choice between covariance-based structural equation modeling (CB-SEM) and partial least square path modeling (PLS-PM). PLS-PM appears to be the preferred method by previous scholars because of its less stringent assumption and the need to avoid the perceived difficulties in CB-SEM. Along with this issue has been the increasing debate among researchers on the use of CB-SEM and PLS-PM in studies. The present study intends to assess the performance of CB-SEM and PLS-PM as a confirmatory study in which the findings will contribute to the body of knowledge of SEM. Maximum likelihood (ML) was chosen as the estimator for CB-SEM and was expected to be more powerful than PLS-PM. Based on the balanced experimental design, the multivariate normal data with specified population parameter and sample sizes were generated using Pro-Active Monte Carlo simulation, and the data were analyzed using AMOS for CB-SEM and SmartPLS for PLS-PM. Comparative Bias Index (CBI), construct relationship, average variance extracted (AVE), composite reliability (CR), and Fornell-Larcker criterion were used to study the consequence of each estimator. The findings conclude that CB-SEM performed notably better than PLS-PM in estimation for large sample size (100 and above), particularly in terms of estimations accuracy and consistency.

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

PubMed

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Is Efficacy of the Anti-Cd20 Antibody Rituximab Preventing Hemolysis Due to Passenger Lymphocyte Syndrome?

PubMed

Tsujimura, Kazuma; Ishida, Hideki; Tanabe, Kazunari

2017-02-01

Passenger lymphocyte syndrome (PLS) often occurs after ABO-mismatched solid organ and/or bone marrow transplantation between a donor and recipient. Viable donor B-lymphocytes transferred during organ transplantation produce antibodies against recipient red cell antigens, leading to hemolysis. The incidence of PLS has been reported to be around 9% after renal transplantation. A previous report showed that rituximab (Rit) was useful for treatment of PLS in allogeneic stem cell transplantation, bowel transplant and severe cases of hemolysis. However, the effectiveness of Rit in preventing PLS after renal transplantation has not yet been evaluated. The participants in this study were 85 patients who had undergone ABO-mismatched renal transplantation from January 2005 to April 2013. Rit was administered to these patients before transplantation. None of the patients that received Rit treatment developed PLS. Thus administration of Rit before transplantation effectively controlled the production of antibodies by B-lymphocytes, which probably prevented the development of PLS. © 2016 International Society for Apheresis, Japanese Society for Apheresis, and Japanese Society for Dialysis Therapy.

Generation and Biological Activities of Oxidized Phospholipids

PubMed Central

Oskolkova, Olga V.; Birukov, Konstantin G.; Levonen, Anna-Liisa; Binder, Christoph J.; Stöckl, Johannes

2010-01-01

Abstract Glycerophospholipids represent a common class of lipids critically important for integrity of cellular membranes. Oxidation of esterified unsaturated fatty acids dramatically changes biological activities of phospholipids. Apart from impairment of their structural function, oxidation makes oxidized phospholipids (OxPLs) markers of “modified-self” type that are recognized by soluble and cell-associated receptors of innate immunity, including scavenger receptors, natural (germ line-encoded) antibodies, and C-reactive protein, thus directing removal of senescent and apoptotic cells or oxidized lipoproteins. In addition, OxPLs acquire novel biological activities not characteristic of their unoxidized precursors, including the ability to regulate innate and adaptive immune responses. Effects of OxPLs described in vitro and in vivo suggest their potential relevance in different pathologies, including atherosclerosis, acute inflammation, lung injury, and many other conditions. This review summarizes current knowledge on the mechanisms of formation, structures, and biological activities of OxPLs. Furthermore, potential applications of OxPLs as disease biomarkers, as well as experimental therapies targeting OxPLs, are described, providing a broad overview of an emerging class of lipid mediators. Antioxid. Redox Signal. 12, 1009–1059. PMID:19686040

A PLS-based extractive spectrophotometric method for simultaneous determination of carbamazepine and carbamazepine-10,11-epoxide in plasma and comparison with HPLC

NASA Astrophysics Data System (ADS)

Hemmateenejad, Bahram; Rezaei, Zahra; Khabnadideh, Soghra; Saffari, Maryam

2007-11-01

Carbamazepine (CBZ) undergoes enzyme biotransformation through epoxidation with the formation of its metabolite, carbamazepine-10,11-epoxide (CBZE). A simple chemometrics-assisted spectrophotometric method has been proposed for simultaneous determination of CBZ and CBZE in plasma. A liquid extraction procedure was operated to separate the analytes from plasma, and the UV absorbance spectra of the resultant solutions were subjected to partial least squares (PLS) regression. The optimum number of PLS latent variables was selected according to the PRESS values of leave-one-out cross-validation. A HPLC method was also employed for comparison. The respective mean recoveries for analysis of CBZ and CBZE in synthetic mixtures were 102.57 (±0.25)% and 103.00 (±0.09)% for PLS and 99.40 (±0.15)% and 102.20 (±0.02)%. The concentrations of CBZ and CBZE were also determined in five patients using the PLS and HPLC methods. The results showed that the data obtained by PLS were comparable with those obtained by HPLC method.

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

Use of partial least squares regression for the multivariate calibration of hazardous air pollutants in open-path FT-IR spectrometry

NASA Astrophysics Data System (ADS)

Hart, Brian K.; Griffiths, Peter R.

1998-06-01

Partial least squares (PLS) regression has been evaluated as a robust calibration technique for over 100 hazardous air pollutants (HAPs) measured by open path Fourier transform infrared (OP/FT-IR) spectrometry. PLS has the advantage over the current recommended calibration method of classical least squares (CLS), in that it can look at the whole useable spectrum (700-1300 cm-1, 2000-2150 cm-1, and 2400-3000 cm-1), and detect several analytes simultaneously. Up to one hundred HAPs synthetically added to OP/FT-IR backgrounds have been simultaneously calibrated and detected using PLS. PLS also has the advantage in requiring less preprocessing of spectra than that which is required in CLS calibration schemes, allowing PLS to provide user independent real-time analysis of OP/FT-IR spectra.

Assessment of Various Organic Matter Properties by Infrared Reflectance Spectroscopy of Sediments and Filters

NASA Astrophysics Data System (ADS)

Alaoui, G.; Leger, M.; Gagne, J.; Tremblay, L.

2009-05-01

The goal of this work was to evaluate the capability of infrared reflectance spectroscopy for a fast quantification of the elemental and molecular compositions of sedimentary and particulate organic matter (OM). A partial least-squares (PLS) regression model was used for analysis and values were compared to those obtained by traditional methods (i.e., elemental, humic and HPLC analyses). PLS tools are readily accessible from software such as GRAMS (Thermo-Fisher) used in spectroscopy. This spectroscopic-chemometric approach has several advantages including its rapidity and use of whole unaltered samples. To predict properties, a set of infrared spectra from representative samples must first be fitted to form a PLS calibration model. In this study, a large set (180) of sediments and particles on GFF filters from the St. Lawrence estuarine system were used. These samples are very heterogenous (e.g., various tributaries, terrigenous vs. marine, events such as landslides and floods) and thus represent a challenging test for PLS prediction. For sediments, the infrared spectra were obtained with a diffuse reflectance, or DRIFT, accessory. Sedimentary carbon, nitrogen, humic substance contents as well as humic substance proportions in OM and N:C ratios were predicted by PLS. The relative root mean square error of prediction (%RMSEP) for these properties were between 5.7% (humin content) and 14.1% (total humic substance yield) using the cross-validation, or leave-one out, approach. The %RMSEP calculated by PLS for carbon content was lower with the PLS model (7.6%) than with an external calibration method (11.7%) (Tremblay and Gagné, 2002, Anal. Chem., 74, 2985). Moreover, the PLS approach does not require the extraction of POM needed in external calibration. Results highlighted the importance of using a PLS calibration set representative of the unknown samples (e.g., same area). For filtered particles, the infrared spectra were obtained using a novel approach based on attenuated total reflectance, or ATR, allowing the direct analysis of the filters. In addition to carbon and nitrogen contents, amino acid and muramic acid (a bacterial biomarker) yields were predicted using PLS. Calculated %RMSEP varied from 6.4% (total amino acid content) to 18.6% (muramic acid content) with cross-validation. PLS regression modeling does not require a priori knowledge of the spectral bands associated with the properties to be predicted. In turn, the spectral regions that give good PLS predictions provided valuable information on band assignment and geochemical processes. For instance, nitrogen and humin contents were greatly determined by an absorption band caused by aluminosilicate OH group. This supports the idea that OM-clay interactions, important in humin formation and OM preservation, are mediated by nitrogen-containing groups.

Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shi, Ji-yong; Zou, Xiao-bo; Zhao, Jie-wen; Mel, Holmes; Wang, Kai-liang; Wang, Xue; Chen, Hong

Total flavonoids content is often considered an important quality index of Ginkgo biloba leaf. The feasibility of using near infrared (NIR) spectra at the wavelength range of 10,000-4000 cm-1 for rapid and nondestructive determination of total flavonoids content in G. biloba leaf was investigated. 120 fresh G. biloba leaves in different colors (green, green-yellowish and yellow) were used to spectra acquisition and total flavonoids determination. Partial least squares (PLS), interval partial least squares (iPLS) and synergy interval partial least squares (SiPLS) were used to develop calibration models for total flavonoids content in two colors leaves (green-yellowish and yellow) and three colors leaves (green, green-yellowish and yellow), respectively. The level of total flavonoids content for green, green-yellowish and yellow leaves was in an increasing order. Two characteristic wavelength regions (5840-6090 cm-1 and 6620-6880 cm-1), which corresponded to the absorptions of two aromatic rings in basic flavonoid structure, were selected by SiPLS. The optimal SiPLS model for total flavonoids content in the two colors leaves (r2 = 0.82, RMSEP = 2.62 mg g-1) had better performance than PLS and iPLS models. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total flavonoids content in fresh G. biloba leaf.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm.

PubMed

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV=0.0776, R(c)=0.9777, RMSEP=0.0963, and R(p)=0.9686 for pH model; RMSECV=1.3544% w/w, R(c)=0.8871, RMSEP=1.4946% w/w, and R(p)=0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry. Copyright © 2012 Elsevier B.V. All rights reserved.

Baseline correction combined partial least squares algorithm and its application in on-line Fourier transform infrared quantitative analysis.

PubMed

Peng, Jiangtao; Peng, Silong; Xie, Qiong; Wei, Jiping

2011-04-01

In order to eliminate the lower order polynomial interferences, a new quantitative calibration algorithm "Baseline Correction Combined Partial Least Squares (BCC-PLS)", which combines baseline correction and conventional PLS, is proposed. By embedding baseline correction constraints into PLS weights selection, the proposed calibration algorithm overcomes the uncertainty in baseline correction and can meet the requirement of on-line attenuated total reflectance Fourier transform infrared (ATR-FTIR) quantitative analysis. The effectiveness of the algorithm is evaluated by the analysis of glucose and marzipan ATR-FTIR spectra. BCC-PLS algorithm shows improved prediction performance over PLS. The root mean square error of cross-validation (RMSECV) on marzipan spectra for the prediction of the moisture is found to be 0.53%, w/w (range 7-19%). The sugar content is predicted with a RMSECV of 2.04%, w/w (range 33-68%). Copyright © 2011 Elsevier B.V. All rights reserved.

The development of comparative bias index

NASA Astrophysics Data System (ADS)

Aimran, Ahmad Nazim; Ahmad, Sabri; Afthanorhan, Asyraf; Awang, Zainudin

2017-08-01

Structural Equation Modeling (SEM) is a second generation statistical analysis techniques developed for analyzing the inter-relationships among multiple variables in a model simultaneously. There are two most common used methods in SEM namely Covariance-Based Structural Equation Modeling (CB-SEM) and Partial Least Square Path Modeling (PLS-PM). There have been continuous debates among researchers in the use of PLS-PM over CB-SEM. While there is few studies were conducted to test the performance of CB-SEM and PLS-PM bias in estimating simulation data. This study intends to patch this problem by a) developing the Comparative Bias Index and b) testing the performance of CB-SEM and PLS-PM using developed index. Based on balanced experimental design, two multivariate normal simulation data with of distinct specifications of size 50, 100, 200 and 500 are generated and analyzed using CB-SEM and PLS-PM.

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

NASA Technical Reports Server (NTRS)

Morris, Richard; Anderson, R.; Clegg, S. M.; Bell, J. F., III

2010-01-01

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

45 CFR 303.70 - Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent...

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 2 2013-10-01 2012-10-01 true Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent Locator Service (Federal PLS). 303.70 Section 303.70 Public Welfare Regulations Relating to Public Welfare OFFICE OF CHILD SUPPORT ENFORCEMENT (CHILD SUPPORT...

45 CFR 303.70 - Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent...

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 2 2011-10-01 2011-10-01 false Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent Locator Service (Federal PLS). 303.70 Section 303.70 Public Welfare Regulations Relating to Public Welfare OFFICE OF CHILD SUPPORT ENFORCEMENT (CHILD SUPPORT...

45 CFR 303.70 - Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent...

Code of Federal Regulations, 2012 CFR

2012-10-01

... 45 Public Welfare 2 2012-10-01 2012-10-01 false Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent Locator Service (Federal PLS). 303.70 Section 303.70 Public Welfare Regulations Relating to Public Welfare OFFICE OF CHILD SUPPORT ENFORCEMENT (CHILD SUPPORT...

45 CFR 303.70 - Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent...

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 2 2014-10-01 2012-10-01 true Procedures for submissions to the State Parent Locator Service (State PLS) or the Federal Parent Locator Service (Federal PLS). 303.70 Section 303.70 Public Welfare Regulations Relating to Public Welfare OFFICE OF CHILD SUPPORT ENFORCEMENT (CHILD SUPPORT...

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Late-onset Papillon-Lefèvre syndrome without alteration of the cathepsin C gene.

PubMed

Pilger, Ulrike; Hennies, Hans Christian; Truschnegg, Astrid; Aberer, Elisabeth

2003-11-01

Mutations in the cathepsin C gene have recently been detected in Papillon-Lefèvre syndrome (PLS). Until now, 5 cases with the late-onset variation of this disease have been reported in the literature. The genetic background of this type of PLS is still unknown. We describe a 46-year-old woman with late-onset transgredient palmar hyperkeratosis and a 10-year history of severe periodontal disease. Histology of skin biopsy specimens revealed a psoriasiform pattern. Dental examination showed severe gingival inflammation with loss of alveolar bone. Dental plaque investigated by a polymerase chain reaction method revealed DNA signals of 5 different dental bacteria. DNA from EDTA blood was investigated for mutations in the cathepsin C gene by polymerase chain reaction analysis and direct sequencing. A silent variation in the codon for proline-459 was detected but interpreted as a polymorphism of this gene. All genetic linkage and mutation studies for PLS performed so far have shown that PLS is genetically homogeneous. Our patient with late-onset variation of PLS, however, did not show a mutation in the cathepsin C gene. Thus, we suspect that there is another genetic cause for the late-onset forms of PLS.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Comparison of multivariate analysis methods for extracting the paraffin component from the paraffin-embedded cancer tissue spectra for Raman imaging

NASA Astrophysics Data System (ADS)

Meksiarun, Phiranuphon; Ishigaki, Mika; Huck-Pezzei, Verena A. C.; Huck, Christian W.; Wongravee, Kanet; Sato, Hidetoshi; Ozaki, Yukihiro

2017-03-01

This study aimed to extract the paraffin component from paraffin-embedded oral cancer tissue spectra using three multivariate analysis (MVA) methods; Independent Component Analysis (ICA), Partial Least Squares (PLS) and Independent Component - Partial Least Square (IC-PLS). The estimated paraffin components were used for removing the contribution of paraffin from the tissue spectra. These three methods were compared in terms of the efficiency of paraffin removal and the ability to retain the tissue information. It was found that ICA, PLS and IC-PLS could remove the paraffin component from the spectra at almost the same level while Principal Component Analysis (PCA) was incapable. In terms of retaining cancer tissue spectral integrity, effects of PLS and IC-PLS on the non-paraffin region were significantly less than that of ICA where cancer tissue spectral areas were deteriorated. The paraffin-removed spectra were used for constructing Raman images of oral cancer tissue and compared with Hematoxylin and Eosin (H&E) stained tissues for verification. This study has demonstrated the capability of Raman spectroscopy together with multivariate analysis methods as a diagnostic tool for the paraffin-embedded tissue section.

PlsX deletion impacts fatty acid synthesis and acid adaptation in Streptococcus mutans.

PubMed

Cross, Benjamin; Garcia, Ariana; Faustoferri, Roberta; Quivey, Robert G

2016-04-01

Streptococcus mutans, one of the primary causative agents of dental caries in humans, ferments dietary sugars in the mouth to produce organic acids. These acids lower local pH values, resulting in demineralization of the tooth enamel, leading to caries. To survive acidic environments, Strep. mutans employs several adaptive mechanisms, including a shift from saturated to unsaturated fatty acids in membrane phospholipids. PlsX is an acyl-ACP : phosphate transacylase that links the fatty acid synthase II (FASII) pathway to the phospholipid synthesis pathway, and is therefore central to the movement of unsaturated fatty acids into the membrane. Recently, we discovered that plsX is not essential in Strep. mutans. A plsX deletion mutant was not a fatty acid or phospholipid auxotroph. Gas chromatography of fatty acid methyl esters indicated that membrane fatty acid chain length in the plsX deletion strain differed from those detected in the parent strain, UA159. The deletion strain displayed a fatty acid shift similar to WT, but had a higher percentage of unsaturated fatty acids at low pH. The deletion strain survived significantly longer than the parent strain when cultures were subjected to an acid challenge of pH 2.5.The ΔplsX strain also exhibited elevated F-ATPase activity at pH 5.2, compared with the parent. These results indicate that the loss of plsX affects both the fatty acid synthesis pathway and the acid-adaptive response of Strep. mutans.

An Advanced Analytical Chemistry Experiment Using Gas Chromatography-Mass Spectrometry, MATLAB, and Chemometrics to Predict Biodiesel Blend Percent Composition

ERIC Educational Resources Information Center

Pierce, Karisa M.; Schale, Stephen P.; Le, Trang M.; Larson, Joel C.

2011-01-01

We present a laboratory experiment for an advanced analytical chemistry course where we first focus on the chemometric technique partial least-squares (PLS) analysis applied to one-dimensional (1D) total-ion-current gas chromatography-mass spectrometry (GC-TIC) separations of biodiesel blends. Then, we focus on n-way PLS (n-PLS) applied to…

Quantitative Differentiation of LV Myocardium with and without Layer-Specific Fibrosis Using MRI in Hypertrophic Cardiomyopathy and Layer-Specific Strain TTE Analysis.

PubMed

Funabashi, Nobusada; Takaoka, Hiroyuki; Ozawa, Koya; Kamata, Tomoko; Uehara, Masae; Komuro, Issei; Kobayashi, Yoshio

2018-05-30

To achieve further risk stratification in hypertrophic cardiomyopathy (HCM) patients, we localized and quantified layer-specific LVM fibrosis on MRI in HCM patients using regional layer-specific peak longitudinal strain (PLS) and peak circumferential strain (PCS) in LV myocardium (LVM) on speckle tracking transthoracic echocardiography (TTE). A total of 18 HCM patients (14 males; 58 ± 17 years) underwent 1.5T-MRI and TTE. PLS and PCS in each layer of the LVM (endocardium, epicardium, and whole-layer myocardium) were calculated for 17 AHA-defined lesions. MRI assessment showed that fibrosis was classified as endocardial, epicardial, or whole-layer (= either or both of these). Regional PLS was smaller in fibrotic endocardial lesions than in non-fibrotic endocardial lesions (P = 0.004). To detect LV endocardial lesions with fibrosis, ROC curves of regional PLS revealed an area under the curve (AUC) of 0.609 and a best cut-off point of 13.5%, with sensitivity of 65.3% and specificity of 54.3%. Regional PLS was also smaller in fibrotic epicardial lesions than in non-fibrotic epicardial lesions (P < 0.001). To detect LV epicardial lesions with fibrosis, ROC curves of PLS revealed an AUC of 0.684 and a best cut-off point of 9.5%, with sensitivity of 73.5% and specificity of 55.5%. Using whole-layer myocardium analysis, PLS was smaller in fibrotic lesions than in non-fibrotic lesions (P < 0.001). To detect whole-layer LV lesions with fibrosis, ROC curves of regional PLS revealed an AUC of 0.674 and a best cut-off point of 12.5%, with sensitivity of 79.0% and specificity of 50.7%. There were no significant differences in PCS of LV myocardium (endocardium, epicardium, and whole-layer) between fibrotic and non-fibrotic lesions. Quantitative regional PLS but not PCS in LV endocardium, epicardium, and whole-layer myocardium provides useful non-invasive information for layer-specific localization of fibrosis in HCM patients.

The Extent and Prediction of Heavy Metal Pollution in Soils of Shahrood and Damghan, Iran.

PubMed

Sakizadeh, Mohamad; Mirzaei, Rouhollah; Ghorbani, Hadi

2015-12-01

The levels of 12 heavy metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Ni, Pb, Tl, V, Zn) were considered in 229 soil samples in Semnan Province, Iran. To discriminate between natural and anthropogenic inputs of heavy metals, factor analysis was used. Seven factors accounting for 90.5 % of the total variance were extracted. The mining and agricultural activities along with geogenic sources have been attributed as the main causes of the levels of heavy metals in the study area. The partial least squares regression was utilized to predict the level of soil pollution index (SPI) considering the concentrations of 12 heavy metals. The eigenvectors from the first three PLS represented more than 98 % of the overall variance. The correlation coefficient between the observed and predicted SPI was 0.99 indicating the high efficiency of this method. The resultant coefficient of determination for three PLS components was 0.984 confirming the predictive ability of this method.

Partial least squares based identification of Duchenne muscular dystrophy specific genes.

PubMed

An, Hui-bo; Zheng, Hua-cheng; Zhang, Li; Ma, Lin; Liu, Zheng-yan

2013-11-01

Large-scale parallel gene expression analysis has provided a greater ease for investigating the underlying mechanisms of Duchenne muscular dystrophy (DMD). Previous studies typically implemented variance/regression analysis, which would be fundamentally flawed when unaccounted sources of variability in the arrays existed. Here we aim to identify genes that contribute to the pathology of DMD using partial least squares (PLS) based analysis. We carried out PLS-based analysis with two datasets downloaded from the Gene Expression Omnibus (GEO) database to identify genes contributing to the pathology of DMD. Except for the genes related to inflammation, muscle regeneration and extracellular matrix (ECM) modeling, we found some genes with high fold change, which have not been identified by previous studies, such as SRPX, GPNMB, SAT1, and LYZ. In addition, downregulation of the fatty acid metabolism pathway was found, which may be related to the progressive muscle wasting process. Our results provide a better understanding for the downstream mechanisms of DMD.

Locally-Based Kernal PLS Smoothing to Non-Parametric Regression Curve Fitting

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Wheeler, Kevin; Korsmeyer, David (Technical Monitor)

2002-01-01

We present a novel smoothing approach to non-parametric regression curve fitting. This is based on kernel partial least squares (PLS) regression in reproducing kernel Hilbert space. It is our concern to apply the methodology for smoothing experimental data where some level of knowledge about the approximate shape, local inhomogeneities or points where the desired function changes its curvature is known a priori or can be derived based on the observed noisy data. We propose locally-based kernel PLS regression that extends the previous kernel PLS methodology by incorporating this knowledge. We compare our approach with existing smoothing splines, hybrid adaptive splines and wavelet shrinkage techniques on two generated data sets.

Perfusion lung imaging in the adult respiratory distress syndrome

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

Pistolesi, M.; Miniati, M.; Di Ricco, G.

1986-07-01

In 29 perfusion lung scans (PLS) of 19 patients with ARDS, 20 of which were obtained within six days from the onset of respiratory symptoms, perfusion abnormalities were the rule. These included focal, nonsegmental defects, mostly peripheral and dorsal, and perfusion redistribution away from the dependent lung zones. PLS were scored for the presence and intensity of perfusion abnormalities and the scores of perfusion redistribution were validated against numerical indices of blood flow distribution per unit lung volume. PLS scores were correlated with arterial blood gas values, hemodynamic parameters, and chest radiographic scores of ARDS. Arterial oxygen tension correlated withmore » the scores of both perfusion defects and redistribution. Perfusion defects correlated better with the radiographic score of ARDS, and perfusion redistribution with PAP and vascular resistance. ARDS patients exhibit peculiar patterns of PLS abnormalities not observed in other disorders. Thus, PLS may help considerably in the detection and evaluation of pulmonary vascular injury in ARDS.« less

Recognition of beer brand based on multivariate analysis of volatile fingerprint.

PubMed

Cajka, Tomas; Riddellova, Katerina; Tomaniova, Monika; Hajslova, Jana

2010-06-18

Automated head-space solid-phase microextraction (HS-SPME)-based sampling procedure, coupled to gas chromatography-time-of-flight mass spectrometry (GC-TOFMS), was developed and employed for obtaining of fingerprints (GC profiles) of beer volatiles. In total, 265 speciality beer samples were collected over a 1-year period with the aim to distinguish, based on analytical (profiling) data, (i) the beers labelled as Rochefort 8; (ii) a group consisting of Rochefort 6, 8, 10 beers; and (iii) Trappist beers. For the chemometric evaluation of the data, partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and artificial neural networks with multilayer perceptrons (ANN-MLP) were tested. The best prediction ability was obtained for the model that distinguished a group of Rochefort 6, 8, 10 beers from the rest of beers. In this case, all chemometric tools employed provided 100% correct classification. Slightly worse prediction abilities were achieved for the models "Trappist vs. non-Trappist beers" with the values of 93.9% (PLS-DA), 91.9% (LDA) and 97.0% (ANN-MLP) and "Rochefort 8 vs. the rest" with the values of 87.9% (PLS-DA) and 84.8% (LDA) and 93.9% (ANN-MLP). In addition to chromatographic profiling, also the potential of direct coupling of SPME (extraction/pre-concentration device) with high-resolution TOFMS employing a direct analysis in real time (DART) ion source has been demonstrated as a challenging profiling approach. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A Piecewise Local Partial Least Squares (PLS) Method for the Quantitative Analysis of Plutonium Nitrate Solutions

DOE PAGES

Lascola, Robert; O'Rourke, Patrick E.; Kyser, Edward A.

2017-10-05

Here, we have developed a piecewise local (PL) partial least squares (PLS) analysis method for total plutonium measurements by absorption spectroscopy in nitric acid-based nuclear material processing streams. Instead of using a single PLS model that covers all expected solution conditions, the method selects one of several local models based on an assessment of solution absorbance, acidity, and Pu oxidation state distribution. The local models match the global model for accuracy against the calibration set, but were observed in several instances to be more robust to variations associated with measurements in the process. The improvements are attributed to the relativemore » parsimony of the local models. Not all of the sources of spectral variation are uniformly present at each part of the calibration range. Thus, the global model is locally overfitting and susceptible to increased variance when presented with new samples. A second set of models quantifies the relative concentrations of Pu(III), (IV), and (VI). Standards containing a mixture of these species were not at equilibrium due to a disproportionation reaction. Therefore, a separate principal component analysis is used to estimate of the concentrations of the individual oxidation states in these standards in the absence of independent confirmatory analysis. The PL analysis approach is generalizable to other systems where the analysis of chemically complicated systems can be aided by rational division of the overall range of solution conditions into simpler sub-regions.« less

A Piecewise Local Partial Least Squares (PLS) Method for the Quantitative Analysis of Plutonium Nitrate Solutions

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

Lascola, Robert; O'Rourke, Patrick E.; Kyser, Edward A.

Here, we have developed a piecewise local (PL) partial least squares (PLS) analysis method for total plutonium measurements by absorption spectroscopy in nitric acid-based nuclear material processing streams. Instead of using a single PLS model that covers all expected solution conditions, the method selects one of several local models based on an assessment of solution absorbance, acidity, and Pu oxidation state distribution. The local models match the global model for accuracy against the calibration set, but were observed in several instances to be more robust to variations associated with measurements in the process. The improvements are attributed to the relativemore » parsimony of the local models. Not all of the sources of spectral variation are uniformly present at each part of the calibration range. Thus, the global model is locally overfitting and susceptible to increased variance when presented with new samples. A second set of models quantifies the relative concentrations of Pu(III), (IV), and (VI). Standards containing a mixture of these species were not at equilibrium due to a disproportionation reaction. Therefore, a separate principal component analysis is used to estimate of the concentrations of the individual oxidation states in these standards in the absence of independent confirmatory analysis. The PL analysis approach is generalizable to other systems where the analysis of chemically complicated systems can be aided by rational division of the overall range of solution conditions into simpler sub-regions.« less

Differentiation of Crataegus spp. guided by nuclear magnetic resonance spectrometry with chemometric analyses.

PubMed

Lund, Jensen A; Brown, Paula N; Shipley, Paul R

2017-09-01

For compliance with US Current Good Manufacturing Practice regulations for dietary supplements, manufacturers must provide identity of source plant material. Despite the popularity of hawthorn as a dietary supplement, relatively little is known about the comparative phytochemistry of different hawthorn species, and in particular North American hawthorns. The combination of NMR spectrometry with chemometric analyses offers an innovative approach to differentiating hawthorn species and exploring the phytochemistry. Two European and two North American species, harvested from a farm trial in late summer 2008, were analyzed by standard 1D 1 H and J-resolved (JRES) experiments. The data were preprocessed and modelled by principal component analysis (PCA). A supervised model was then generated by partial least squares-discriminant analysis (PLS-DA) for classification and evaluated by cross validation. Supervised random forests models were constructed from the dataset to explore the potential of machine learning for identification of unique patterns across species. 1D 1 H NMR data yielded increased differentiation over the JRES data. The random forests results correlated with PLS-DA results and outperformed PLS-DA in classification accuracy. In all of these analyses differentiation of the Crataegus spp. was best achieved by focusing on the NMR spectral region that contains signals unique to plant phenolic compounds. Identification of potentially significant metabolites for differentiation between species was approached using univariate techniques including significance analysis of microarrays and Kruskall-Wallis tests. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of a peer-led hypertension intervention for veterans: impact on peer leaders.

PubMed

Mosack, Katie E; Patterson, Leslie; Brouwer, Amanda M; Wendorf, Angela R; Ertl, Kristyn; Eastwood, Dan; Morzinski, Jeffrey; Fletcher, Kathlyn; Whittle, Jeff

2013-06-01

Volunteer peer leaders (PLs) benefit from their involvement in health interventions but we know little about how they compare with other non-PL volunteers or with the intervention recipients themselves. We randomized 58 veterans' service organizations' posts (e.g. VFW) to peer- versus professionally led self-management support interventions. Our primary research questions were whether hypertensive PLs changed over the course of the project, whether they changed more than hypertensive volunteers who were not randomized to such a role [i.e. post representatives (PRs)] and whether they changed more than the intervention recipients with respect to health knowledge, health beliefs and health outcomes from baseline to 12 months. After the intervention, PLs provided open-ended feedback and participated in focus groups designed to explore intervention impact. Hypertensive PLs improved their systolic blood pressure and hypertension knowledge and increased their fruit/vegetable intake and pedometer use. We found no differences between PLs and PRs. PLs improved knowledge and increased fruit/vegetable intake more than intervention recipients did; they provided specific examples of personal health behavior change and knowledge acquisition. Individuals who volunteer to be peer health leaders are likely to receive important benefits even if they do not actually take on such a role.

Imaging of glia activation in people with primary lateral sclerosis.

PubMed

Paganoni, Sabrina; Alshikho, Mohamad J; Zürcher, Nicole R; Cernasov, Paul; Babu, Suma; Loggia, Marco L; Chan, James; Chonde, Daniel B; Garcia, David Izquierdo; Catana, Ciprian; Mainero, Caterina; Rosen, Bruce R; Cudkowicz, Merit E; Hooker, Jacob M; Atassi, Nazem

2018-01-01

Glia activation is thought to contribute to neuronal damage in several neurodegenerative diseases based on preclinical and human post - mortem studies, but its role in primary lateral sclerosis (PLS) is unknown. To localize and measure glia activation in people with PLS compared to healthy controls (HC). Ten participants with PLS and ten age-matched HCs underwent simultaneous magnetic resonance (MR) and proton emission tomography (PET). The radiotracer [ 11 C]-PBR28 was used to obtain PET-based measures of 18 kDa translocator protein (TSPO) expression, a marker of activated glial cells. MR techniques included a structural sequence to measure cortical thickness and diffusion tensor imaging (DTI) to assess white matter integrity. PET data showed increased [ 11 C]-PBR28 uptake in anatomically-relevant motor regions which co-localized with areas of regional gray matter atrophy and decreased subcortical fractional anisotropy. This study supports a link between glia activation and neuronal degeneration in PLS, and suggests that these disease mechanisms can be measured in vivo in PLS. Future studies are needed to determine the longitudinal changes of these imaging measures and to clarify if MR-PET with [ 11 C]-PBR28 can be used as a biomarker for drug development in the context of clinical trials for PLS.

Irreversible dual inhibitory mode: the novel Btk inhibitor PLS-123 demonstrates promising anti-tumor activity in human B-cell lymphoma.

PubMed

Ding, Ning; Li, Xitao; Shi, Yunfei; Ping, Lingyan; Wu, Lina; Fu, Kai; Feng, Lixia; Zheng, Xiaohui; Song, Yuqin; Pan, Zhengying; Zhu, Jun

2015-06-20

The B-cell receptor (BCR) signaling pathway has gained significant attention as a therapeutic target in B-cell malignancies. Recently, several drugs that target the BCR signaling pathway, especially the Btk inhibitor ibrutinib, have demonstrated notable therapeutic effects in relapsed/refractory patients, which indicates that pharmacological inhibition of BCR pathway holds promise in B-cell lymphoma treatment. Here we present a novel covalent irreversible Btk inhibitor PLS-123 with more potent anti-proliferative activity compared with ibrutinib in multiple cellular and in vivo models through effective apoptosis induction and dual-action inhibitory mode of Btk activation. The phosphorylation of BCR downstream activating AKT/mTOR and MAPK signal pathways was also more significantly reduced after treatment with PLS-123 than ibrutinib. Gene expression profile analysis further suggested that the different selectivity profile of PLS-123 led to significant downregulation of oncogenic gene PTPN11 expression, which might also offer new opportunities beyond what ibrutinib has achieved. In addition, PLS-123 dose-dependently attenuated BCR- and chemokine-mediated lymphoma cell adhesion and migration. Taken together, Btk inhibitor PLS-123 suggested a new direction to pharmacologically modulate Btk function and develop novel therapeutic drug for B-cell lymphoma treatment.

Irreversible dual inhibitory mode: the novel Btk inhibitor PLS-123 demonstrates promising anti-tumor activity in human B-cell lymphoma

PubMed Central

Ding, Ning; Li, Xitao; Shi, Yunfei; Ping, Lingyan; Wu, Lina; Fu, Kai; Feng, Lixia; Zheng, Xiaohui; Song, Yuqin; Pan, Zhengying; Zhu, Jun

2015-01-01

The B-cell receptor (BCR) signaling pathway has gained significant attention as a therapeutic target in B-cell malignancies. Recently, several drugs that target the BCR signaling pathway, especially the Btk inhibitor ibrutinib, have demonstrated notable therapeutic effects in relapsed/refractory patients, which indicates that pharmacological inhibition of BCR pathway holds promise in B-cell lymphoma treatment. Here we present a novel covalent irreversible Btk inhibitor PLS-123 with more potent anti-proliferative activity compared with ibrutinib in multiple cellular and in vivo models through effective apoptosis induction and dual-action inhibitory mode of Btk activation. The phosphorylation of BCR downstream activating AKT/mTOR and MAPK signal pathways was also more significantly reduced after treatment with PLS-123 than ibrutinib. Gene expression profile analysis further suggested that the different selectivity profile of PLS-123 led to significant downregulation of oncogenic gene PTPN11 expression, which might also offer new opportunities beyond what ibrutinib has achieved. In addition, PLS-123 dose-dependently attenuated BCR- and chemokine-mediated lymphoma cell adhesion and migration. Taken together, Btk inhibitor PLS-123 suggested a new direction to pharmacologically modulate Btk function and develop novel therapeutic drug for B-cell lymphoma treatment. PMID:25944695

Evaluation of a peer-led hypertension intervention for veterans: impact on peer leaders

PubMed Central

Mosack, Katie E.; Patterson, Leslie; Brouwer, Amanda M.; Wendorf, Angela R.; Ertl, Kristyn; Eastwood, Dan; Morzinski, Jeffrey; Fletcher, Kathlyn; Whittle, Jeff

2013-01-01

Volunteer peer leaders (PLs) benefit from their involvement in health interventions but we know little about how they compare with other non-PL volunteers or with the intervention recipients themselves. We randomized 58 veterans’ service organizations’ posts (e.g. VFW) to peer- versus professionally led self-management support interventions. Our primary research questions were whether hypertensive PLs changed over the course of the project, whether they changed more than hypertensive volunteers who were not randomized to such a role [i.e. post representatives (PRs)] and whether they changed more than the intervention recipients with respect to health knowledge, health beliefs and health outcomes from baseline to 12 months. After the intervention, PLs provided open-ended feedback and participated in focus groups designed to explore intervention impact. Hypertensive PLs improved their systolic blood pressure and hypertension knowledge and increased their fruit/vegetable intake and pedometer use. We found no differences between PLs and PRs. PLs improved knowledge and increased fruit/vegetable intake more than intervention recipients did; they provided specific examples of personal health behavior change and knowledge acquisition. Individuals who volunteer to be peer health leaders are likely to receive important benefits even if they do not actually take on such a role. PMID:23406721

The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization.

PubMed

Gomes, Adriano de Araújo; Alcaraz, Mirta Raquel; Goicoechea, Hector C; Araújo, Mario Cesar U

2014-02-06

In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV-vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL. Copyright © 2013 Elsevier B.V. All rights reserved.

Local classification: Locally weighted-partial least squares-discriminant analysis (LW-PLS-DA).

PubMed

Bevilacqua, Marta; Marini, Federico

2014-08-01

The possibility of devising a simple, flexible and accurate non-linear classification method, by extending the locally weighted partial least squares (LW-PLS) approach to the cases where the algorithm is used in a discriminant way (partial least squares discriminant analysis, PLS-DA), is presented. In particular, to assess which category an unknown sample belongs to, the proposed algorithm operates by identifying which training objects are most similar to the one to be predicted and building a PLS-DA model using these calibration samples only. Moreover, the influence of the selected training samples on the local model can be further modulated by adopting a not uniform distance-based weighting scheme which allows the farthest calibration objects to have less impact than the closest ones. The performances of the proposed locally weighted-partial least squares-discriminant analysis (LW-PLS-DA) algorithm have been tested on three simulated data sets characterized by a varying degree of non-linearity: in all cases, a classification accuracy higher than 99% on external validation samples was achieved. Moreover, when also applied to a real data set (classification of rice varieties), characterized by a high extent of non-linearity, the proposed method provided an average correct classification rate of about 93% on the test set. By the preliminary results, showed in this paper, the performances of the proposed LW-PLS-DA approach have proved to be comparable and in some cases better than those obtained by other non-linear methods (k nearest neighbors, kernel-PLS-DA and, in the case of rice, counterpropagation neural networks). Copyright © 2014 Elsevier B.V. All rights reserved.

"If There Is a Job Description I Don't Think I've Read One": A Case Study of Programme Leadership in a UK Pre-1992 University

ERIC Educational Resources Information Center

Mitchell, Rafael

2015-01-01

This paper reports on an exploratory study of the role of programme leaders (PLs) in a pre-1992 university, based on interviews with PLs (7) and a survey of taught Masters students (54) in a single school. The study elicits PLs' activities, most of which might be categorised as managerial and administrative, with leadership required…

QSAR Study of p56lck Protein Tyrosine Kinase Inhibitory Activity of Flavonoid Derivatives Using MLR and GA-PLS

PubMed Central

Fassihi, Afshin; Sabet, Razieh

2008-01-01

Quantitative relationships between molecular structure and p56lck protein tyrosine kinase inhibitory activity of 50 flavonoid derivatives are discovered by MLR and GA-PLS methods. Different QSAR models revealed that substituent electronic descriptors (SED) parameters have significant impact on protein tyrosine kinase inhibitory activity of the compounds. Between the two statistical methods employed, GA-PLS gave superior results. The resultant GA-PLS model had a high statistical quality (R2 = 0.74 and Q2 = 0.61) for predicting the activity of the inhibitors. The models proposed in the present work are more useful in describing QSAR of flavonoid derivatives as p56lck protein tyrosine kinase inhibitors than those provided previously. PMID:19325836

Raman microspectroscopy of nucleus and cytoplasm for human colon cancer diagnosis.

PubMed

Liu, Wenjing; Wang, Hongbo; Du, Jingjing; Jing, Chuanyong

2017-11-15

Subcellular Raman analysis is a promising clinic tool for cancer diagnosis, but constrained by the difficulty of deciphering subcellular spectra in actual human tissues. We report a label-free subcellular Raman analysis for use in cancer diagnosis that integrates subcellular signature spectra by subtracting cytoplasm from nucleus spectra (Nuc.-Cyt.) with a partial least squares-discriminant analysis (PLS-DA) model. Raman mapping with the classical least-squares (CLS) model allowed direct visualization of the distribution of the cytoplasm and nucleus. The PLS-DA model was employed to evaluate the diagnostic performance of five types of spectral datasets, including non-selective, nucleus, cytoplasm, ratio of nucleus to cytoplasm (Nuc./Cyt.), and nucleus minus cytoplasm (Nuc.-Cyt.), resulting in diagnostic sensitivity of 88.3%, 84.0%, 98.4%, 84.5%, and 98.9%, respectively. Discriminating between normal and cancerous cells of actual human tissues through subcellular Raman markers is feasible, especially when using the nucleus-cytoplasm difference spectra. The subcellular Raman approach had good stability, and had excellent diagnostic performance for rectal as well as colon tissues. The insights gained from this study shed new light on the general applicability of subcellular Raman analysis in clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.

Do Health Claims and Front-of-Pack Labels Lead to a Positivity Bias in Unhealthy Foods?

PubMed Central

Talati, Zenobia; Pettigrew, Simone; Dixon, Helen; Neal, Bruce; Ball, Kylie; Hughes, Clare

2016-01-01

Health claims and front-of-pack labels (FoPLs) may lead consumers to hold more positive attitudes and show a greater willingness to buy food products, regardless of their actual healthiness. A potential negative consequence of this positivity bias is the increased consumption of unhealthy foods. This study investigated whether a positivity bias would occur in unhealthy variations of four products (cookies, corn flakes, pizzas and yoghurts) that featured different health claim conditions (no claim, nutrient claim, general level health claim, and higher level health claim) and FoPL conditions (no FoPL, the Daily Intake Guide (DIG), Multiple Traffic Lights (MTL), and the Health Star Rating (HSR)). Positivity bias was assessed via measures of perceived healthiness, global evaluations (incorporating taste, quality, convenience, etc.) and willingness to buy. On the whole, health claims did not produce a positivity bias, while FoPLs did, with the DIG being the most likely to elicit this bias. The HSR most frequently led to lower ratings of unhealthy foods than the DIG and MTL, suggesting that this FoPL has the lowest risk of creating an inaccurate positivity bias in unhealthy foods. PMID:27918426

Oxygen vacancy effect on photoluminescence of KNb3O8 nanosheets

NASA Astrophysics Data System (ADS)

Li, Rui; Liu, Liying; Ming, Bangming; Ji, Yuhang; Wang, Ruzhi

2018-05-01

Fungus-like potassium niobate (KNb3O8) nanosheets have been synthesized on indium-doped tin oxide (ITO) glass substrates by a simple and environmental friendly two-step hydrothermal process. The prepared samples have been characterized by using X-ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM), High Resolution Transmission Electron Microscope (HRTEM), Fourier Transform Infra-Red Spectroscopy (FTIR), Raman Spectroscopy and X-ray Photoelectron Spectroscopy (XPS). Furthermore, the photoluminescence (PL) of KNb3O8 nanosheets have been systematically studied. The results showed that the PL spectrum is between 300 and 645 nm with a 325 nm light excitation, which is divided into some sub-peaks. It is different from the perfect KNb3O8 nanosheets whose PL emission peaks located at near 433 nm. It should be originated from the effect of the oxygen (O) vacancies in the KNb3O8 nanosheets, which the PLs peaks can be found at about 490 nm and 530 nm by different position of O vacancy. The experimental results are in accordance with the first-principles calculations. Our results may present a feasible clue to estimate the defect position in KNb3O8 by the shape analysis of its spectrum of PLs.

PLS modelling of structure—activity relationships of catechol O-methyltransferase inhibitors

NASA Astrophysics Data System (ADS)

Lotta, Timo; Taskinen, Jyrki; Bäckström, Reijo; Nissinen, Erkki

1992-06-01

Quantitative structure-activity analysis was carried out for in vitro inhibition of rat brain soluble catechol O-methyltransferase by a series (N=99) of 1,5-substituted-3,4-dihydroxybenzenes using computational chemistry and multivariate PLS modelling of data sets. The molecular structural descriptors (N=19) associated with the electronics of the catecholic ring and sizes of substituents were derived theoretically. For the whole set of molecules two separate PLS models have to be used. A PLS model with two significant (crossvalidated) model dimensions describing 82.2% of the variance in inhibition activity data was capable of predicting all molecules except those having the largest R1 substituent or having a large R5 substituent compared to the NO2 group. The other PLS model with three significant (crossvalidated) model dimensions described 83.3% of the variance in inhibition activity data. This model could not handle compounds having a small R5 substituent, compared to the NO2 group, or the largest R1 substituent. The predictive capability of these PLS models was good. The models reveal that inhibition activity is nonlinearly related to the size of the R5 substituent. The analysis of the PLS models also shows that the binding affinity is greatly dependent on the electronic nature of both R1 and R5 substituents. The electron-withdrawing nature of the substituents enhances inhibition activity. In addition, the size of the R1 substituent and its lipophilicity are important in the binding of inhibitors. The size of the R1 substituent has an upper limit. On the other hand, ionized R1 substituents decrease inhibition activity.

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Random sample consensus combined with partial least squares regression (RANSAC-PLS) for microbial metabolomics data mining and phenotype improvement.

PubMed

Teoh, Shao Thing; Kitamura, Miki; Nakayama, Yasumune; Putri, Sastia; Mukai, Yukio; Fukusaki, Eiichiro

2016-08-01

In recent years, the advent of high-throughput omics technology has made possible a new class of strain engineering approaches, based on identification of possible gene targets for phenotype improvement from omic-level comparison of different strains or growth conditions. Metabolomics, with its focus on the omic level closest to the phenotype, lends itself naturally to this semi-rational methodology. When a quantitative phenotype such as growth rate under stress is considered, regression modeling using multivariate techniques such as partial least squares (PLS) is often used to identify metabolites correlated with the target phenotype. However, linear modeling techniques such as PLS require a consistent metabolite-phenotype trend across the samples, which may not be the case when outliers or multiple conflicting trends are present in the data. To address this, we proposed a data-mining strategy that utilizes random sample consensus (RANSAC) to select subsets of samples with consistent trends for construction of better regression models. By applying a combination of RANSAC and PLS (RANSAC-PLS) to a dataset from a previous study (gas chromatography/mass spectrometry metabolomics data and 1-butanol tolerance of 19 yeast mutant strains), new metabolites were indicated to be correlated with tolerance within certain subsets of the samples. The relevance of these metabolites to 1-butanol tolerance were then validated from single-deletion strains of corresponding metabolic genes. The results showed that RANSAC-PLS is a promising strategy to identify unique metabolites that provide additional hints for phenotype improvement, which could not be detected by traditional PLS modeling using the entire dataset. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

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.

Incorporation of Extracellular Fatty Acids by a Fatty Acid Kinase-Dependent Pathway in Staphylococcus aureus

PubMed Central

Parsons, Joshua B.; Frank, Matthew W.; Jackson, Pamela; Subramanian, Chitra; Rock, Charles O.

2014-01-01

Summary Acyl-CoA and acyl-acyl carrier protein (ACP) synthetases activate exogenous fatty acids for incorporation into phospholipids in Gram-negative bacteria. However, Gram-positive bacteria utilize an acyltransferase pathway for the biogenesis of phosphatidic acid that begins with the acylation of sn-glycerol-3-phosphate by PlsY using an acyl-phosphate (acyl-PO4) intermediate. PlsX generates acyl-PO4 from the acyl-ACP end-products of fatty acid synthesis. The plsX gene of Staphylococcus aureus was inactivated and the resulting strain was both a fatty acid auxotroph and required de novo fatty acid synthesis for growth. Exogenous fatty acids were only incorporated into the 1-position and endogenous acyl groups were channeled into the 2-position of the phospholipids in strain PDJ39 (ΔplsX). Extracellular fatty acids were not elongated. Removal of the exogenous fatty acid supplement led to the rapid accumulation of intracellular acyl-ACP and the abrupt cessation of fatty acid synthesis. Extracts from the ΔplsX strain exhibited an ATP-dependent fatty acid kinase activity, and the acyl-PO4 was converted to acyl-ACP when purified PlsX is added. These data reveal the existence of a novel fatty acid kinase pathway for the incorporation of exogenous fatty acids into S. aureus phospholipids. PMID:24673884

Prevalence of Prostatitis-Like Symptoms and Outcomes of NIH-CPSI in Outpatients with Lifelong and Acquired PE: Based on a Large Cross-Sectional Study in China.

PubMed

Zhu, Daofang; Dou, Xianming; Tang, Liang; Tang, Dongdong; Liao, Guiyi; Fang, Weihua; Zhang, Xiansheng

2017-01-01

Premature ejaculation (PE) is one of the most common sexual dysfunctions, which were associated with prostatitis-like symptoms (PLS). We intended to explore the prevalence of prostatitis-like symptoms and outcomes of National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) scores in outpatients with lifelong (LPE) and acquired premature ejaculation (APE). From December 2013 to December 2015, a total of 498 consecutive heterosexual men with PE and 322 male healthy subjects without PE were enrolled. Each of them completed a detailed questionnaire on demographics information, sexual and medical histories, and the NIH-CPSI. Assessment of NIH-CPSI and definition of PLS and PE were used to measure the PLS and NIH-CPSI scores and ejaculatory function for all subjects. Finally, a total of 820 subjects (including 498 men in PE group and 322 men in control group) were enrolled in our study. The mean ages were significantly different between PE and no PE groups. Men with PE reported worse PLS and higher NIH-CPSI scores ( P < 0.001 for all). Similar findings were also observed between men with LPE and APE. Men with APE also reported higher rates of PLS and scores of NIH-CPSI ( P < 0.001 for all). Multivariate analysis showed that PLS and NIH-CPSI scores were significantly associated with PE.

Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations.

PubMed

da Silva, Fabiana E B; Flores, Érico M M; Parisotto, Graciele; Müller, Edson I; Ferrão, Marco F

2016-03-01

An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.

Platelets and Plasma Proteins Are Both Required to Stimulate Collagen Gene Expression by Anterior Cruciate Ligament Cells in Three-Dimensional Culture

PubMed Central

Cheng, Mingyu; Wang, Hao; Yoshida, Ryu

2010-01-01

Collagen–platelet (PL)-rich plasma composites have shown in vivo potential to stimulate anterior cruciate ligament (ACL) healing at early time points in large animal models. However, little is known about the cellular mechanisms by which the plasma component of these composites may stimulate healing. We hypothesized that the components of PL-rich plasma (PRP), namely the PLs and PL-poor plasma (PPP), would independently significantly influence ACL cell viability and metabolic activity, including collagen gene expression. To test this hypothesis, ACL cells were cultured in a collagen type I hydrogel with PLs, PPP, or the combination of the two (PRP) for 14 days. The inclusion of PLs, PPP, and PRP all significantly reduced the rate of cell apoptosis and enhanced the metabolic activity of fibroblasts in the collagen hydrogel. PLs promoted fibroblast-mediated collagen scaffold contraction, whereas PPP inhibited this contraction. PPP and PRP both promoted cell elongation and the formation of wavy fibrous structure in the scaffolds. The addition of only PLs or only plasma proteins did not significantly enhance gene expression of collagen types I and III but the combination, as PRP, did. Our findings suggest that the addition of both PLs and plasma proteins to collagen hydrogel may be useful in stimulating ACL healing by enhancing ACL cell viability, metabolic activity, and collagen synthesis. PMID:19958169

[Effect of near infrared spectrum on the precision of PLS model for oil yield from oil shale].

PubMed

Wang, Zhi-Hong; Liu, Jie; Chen, Xiao-Chao; Sun, Yu-Yang; Yu, Yang; Lin, Jun

2012-10-01

It is impossible to use present measurement methods for the oil yield of oil shale to realize in-situ detection and these methods unable to meet the requirements of the oil shale resources exploration and exploitation. But in-situ oil yield analysis of oil shale can be achieved by the portable near infrared spectroscopy technique. There are different correlativities of NIR spectrum data formats and contents of sample components, and the different absorption specialities of sample components shows in different NIR spectral regions. So with the proportioning samples, the PLS modeling experiments were done by 3 formats (reflectance, absorbance and K-M function) and 4 regions of modeling spectrum, and the effect of NIR spectral format and region to the precision of PLS model for oil yield from oil shale was studied. The results show that the best data format is reflectance and the best modeling region is combination spectral range by PLS model method and proportioning samples. Therefore, the appropriate data format and the proper characteristic spectral region can increase the precision of PLS model for oil yield form oil shale.

A heuristic approach using multiple criteria for environmentally benign 3PLs selection

NASA Astrophysics Data System (ADS)

Kongar, Elif

2005-11-01

Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.

Is environmental sustainability a strategic priority for logistics service providers?

PubMed

Evangelista, Pietro; Colicchia, Claudia; Creazza, Alessandro

2017-08-01

Despite an increasing number of third-party logistics service providers (3PLs) regard environmental sustainability as a key area of management, there is still great uncertainty on how 3PLs implement environmental strategies and on how they translate green efforts into practice. Through a multiple case study analysis, this paper explores the environmental strategies of a sample of medium-sized 3PLs operating in Italy and the UK, in terms of environmental organizational culture, initiatives, and influencing factors. Our analysis shows that, notwithstanding environmental sustainability is generally recognised as a strategic priority, a certain degree of diversity in the deployment of environmental strategies still exists. This paper is original since the extant literature on green strategies of 3PLs provides findings predominantly from a single country perspective and mainly investigates large/multinational organizations. It also provides indications to help managers of medium-sized 3PLs in positioning their business. This is particularly meaningful in the 3PL industry, where medium-sized organizations significantly contribute to the generated turnover and market value. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparison of Multivariate and Pre-Processing Methods for Quantitative Laser-Induced Breakdown Spectroscopy of Geologic Samples

NASA Technical Reports Server (NTRS)

Anderson, R. B.; Morris, R. V.; Clegg, S. M.; Bell, J. F., III; Humphries, S. D.; Wiens, R. C.

2011-01-01

The ChemCam instrument selected for the Curiosity rover is capable of remote laser-induced breakdown spectroscopy (LIBS).[1] We used a remote LIBS instrument similar to ChemCam to analyze 197 geologic slab samples and 32 pressed-powder geostandards. The slab samples are well-characterized and have been used to validate the calibration of previous instruments on Mars missions, including CRISM [2], OMEGA [3], the MER Pancam [4], Mini-TES [5], and Moessbauer [6] instruments and the Phoenix SSI [7]. The resulting dataset was used to compare multivariate methods for quantitative LIBS and to determine the effect of grain size on calculations. Three multivariate methods - partial least squares (PLS), multilayer perceptron artificial neural networks (MLP ANNs) and cascade correlation (CC) ANNs - were used to generate models and extract the quantitative composition of unknown samples. PLS can be used to predict one element (PLS1) or multiple elements (PLS2) at a time, as can the neural network methods. Although MLP and CC ANNs were successful in some cases, PLS generally produced the most accurate and precise results.

Concentration determination of collagen and proteoglycan in bovine nasal cartilage by Fourier transform infrared imaging and PLS

NASA Astrophysics Data System (ADS)

Zhang, Xuexi; Xiao, Zhi-Yan; Yin, Jianhua; Xia, Yang

2014-09-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics can be used to detect the structure of bio-macromolecule, measure the concentrations of some components, and so on. In this study, FTIRI with Partial Least-Squares (PLS) regression was applied to study the concentration of two main components in bovine nasal cartilage (BNC), collagen and proteoglycan. An infrared spectrum library was built by mixing the collagen and chondroitin 6-sulfate (main of proteoglycan) at different ratios. Some pretreatments are needed for building PLS model. FTIR images were collected from BNC sections at 6.25μm and 25μm pixel size. The spectra extracted from BNC-FTIR images were imported into the PLS regression program to predict the concentrations of collagen and proteoglycan. These PLS-determined concentrations are agreed with the result in our previous work and biochemical analytical results. The prediction shows that the concentrations of collagen and proteoglycan in BNC are comparative on the whole. However, the concentration of proteoglycan is a litter higher than that of collagen, to some extent.

Kernel analysis of partial least squares (PLS) regression models.

PubMed

Shinzawa, Hideyuki; Ritthiruangdej, Pitiporn; Ozaki, Yukihiro

2011-05-01

An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA). Thus, it becomes possible to establish the proper interpretation of the scores. A PLS model for the total nitrogen (TN) content in multiple Thai fish sauces is built with a set of near-infrared (NIR) transmittance spectra of the fish sauce samples. The kernel analysis of the scores effectively reveals that the variation of the spectral feature induced by the change in protein content is substantially associated with the total water content and the protein hydration. Kernel analysis is also carried out on a set of time-dependent infrared (IR) spectra representing transient evaporation of ethanol from a binary mixture solution of ethanol and oleic acid. A PLS model to predict the elapsed time is built with the IR spectra and the kernel matrix is derived from the scores. The detailed analysis of the kernel matrix provides penetrating insight into the interaction between the ethanol and the oleic acid.

Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm.

PubMed

de Almeida, Valber Elias; de Araújo Gomes, Adriano; de Sousa Fernandes, David Douglas; Goicoechea, Héctor Casimiro; Galvão, Roberto Kawakami Harrop; Araújo, Mario Cesar Ugulino

2018-05-01

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions. Published by Elsevier B.V.

Personnel Launch System (PLS) study

NASA Technical Reports Server (NTRS)

Ehrlich, Carl F., Jr.

1991-01-01

NASA is currently studying a personnel launch system (PLS) approach to help satisfy the crew rotation requirements for the Space Station Freedom. Several concepts from low L/D capsules to lifting body vehicles are being examined in a series of studies as a potential augmentation to the Space Shuttle launch system. Rockwell International Corporation, under contract to NASA, analyzed a lifting body concept to determine whether the lifting body class of vehicles is appropriate for the PLS function. The results of the study are given.

Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-08-17

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as partial least squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as orthogonal projection to latent structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples collected two weeks after calibration, which represents a 43% and 46% degradation, respectively. The orthogonal score-plot was a very convenient tool to visualize MOX sensor data and to validate the LOD estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Saturation recovery EPR spin-labeling method for quantification of lipids in biological membrane domains.

PubMed

Mainali, Laxman; Camenisch, Theodore G; Hyde, James S; Subczynski, Witold K

2017-12-01

The presence of integral membrane proteins induces the formation of distinct domains in the lipid bilayer portion of biological membranes. Qualitative application of both continuous wave (CW) and saturation recovery (SR) electron paramagnetic resonance (EPR) spin-labeling methods allowed discrimination of the bulk, boundary, and trapped lipid domains. A recently developed method, which is based on the CW EPR spectra of phospholipid (PL) and cholesterol (Chol) analog spin labels, allows evaluation of the relative amount of PLs (% of total PLs) in the boundary plus trapped lipid domain and the relative amount of Chol (% of total Chol) in the trapped lipid domain [ M. Raguz, L. Mainali, W. J. O'Brien, and W. K. Subczynski (2015), Exp. Eye Res., 140:179-186 ]. Here, a new method is presented that, based on SR EPR spin-labeling, allows quantitative evaluation of the relative amounts of PLs and Chol in the trapped lipid domain of intact membranes. This new method complements the existing one, allowing acquisition of more detailed information about the distribution of lipids between domains in intact membranes. The methodological transition of the SR EPR spin-labeling approach from qualitative to quantitative is demonstrated. The abilities of this method are illustrated for intact cortical and nuclear fiber cell plasma membranes from porcine eye lenses. Statistical analysis (Student's t -test) of the data allowed determination of the separations of mean values above which differences can be treated as statistically significant ( P ≤ 0.05) and can be attributed to sources other than preparation/technique.

Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation.

PubMed

Nikzad-Langerodi, Ramin; Lughofer, Edwin; Cernuda, Carlos; Reischer, Thomas; Kantner, Wolfgang; Pawliczek, Marcin; Brandstetter, Markus

2018-07-12

The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample-associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect changes in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling's T 2 and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling's T 2 and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active selection of samples by active learning (AL) used for subsequent model adaptation is advantageous compared to passive (random) selection in case that a drift leads to persistent prediction bias allowing more rapid adaptation at lower reference measurement rates. Fully unsupervised adaptation using FLEXFIS-PLS could improve predictive accuracy significantly for light drifts but was not able to fully compensate for prediction bias in case of significant lack of fit w.r.t. the latent variable space. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantification of adulterations in extra virgin flaxseed oil using MIR and PLS.

PubMed

de Souza, Letícia Maria; de Santana, Felipe Bachion; Gontijo, Lucas Caixeta; Mazivila, Sarmento Júnior; Borges Neto, Waldomiro

2015-09-01

This paper proposes a new method for the quantitative analysis of soybean oil (SO) and sunflower oil (SFO) as adulterants in extra virgin flaxseed oil (EFO) by applying Mid Infrared Spectroscopy (MIR) associated with chemometric technique of Partial Least Squares (PLS). The PLS models were built in accordance with standard method ASTM E1655-05 and these showed good correlation between the reference values and those calculated using the PLS models with low error values, with R = 0.998 for SFO and R = 0.999 for SO in EFO. These models were validated analytically in accordance with Brazilian and international guidelines through the estimate of figures of merit parameters, thus showing an effective and feasible method to control the quality of extra virgin flaxseed oil. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ultrastructural markers of lymph nodes in patients with acquired immune deficiency syndrome and in homosexual males with unexplained persistent lymphadenopathy. A quantitative study.

PubMed

Onerheim, R M; Wang, N S; Gilmore, N; Jothy, S

1984-09-01

To determine if vesicular rosettes (VR), tubuloreticular structures (TRS), and "test-tube and ring-shaped forms" (TRF) are characteristic ultrastructural features of the syndromes of acquired immune deficiency (AIDS) or of unexplained persistent lymphadenopathy (PLS), the authors studied lymph nodes from nine patients with PLS, two patients with AIDS, and seven controls by electron microscopy. An average of 122 lymphocytes per case were photographed. VR were present in only 0.37% of lymphocytes in 4 of 11 index cases and were mimicked by grouped vesicles and degenerating multivesicular bodies (MVB). TRS were found in 10 of 11 index cases, compared with only one of seven controls (P less than 0.01). In the index cases, they were more frequent in AIDS (mean 21%) than in PLS lymphocytes (mean 4%) (P less than 0.05). MVB were found in all index cases and five of seven controls and were more frequent in index lymphocytes (mean 19%) than in controls (mean 5%) (P less than 0.01). TRF were found in one Haitian male with AIDS, where they were present in 4% of lymphocytes. VR are infrequent and indistinct. MVB probably reflect the reactivity of the lymphocytes. TRF is not a feature of PLS. The authors conclude that there are no pathognomonic ultrastructural markers of AIDS or PLS but that TRS are characteristic of both syndromes and occur frequently enough to be supportive to the diagnosis of AIDS and PLS.

A summary to communicate evidence from systematic reviews to the public improved understanding and accessibility of information: a randomized controlled trial.

PubMed

Santesso, Nancy; Rader, Tamara; Nilsen, Elin Strømme; Glenton, Claire; Rosenbaum, Sarah; Ciapponi, Agustín; Moja, Lorenzo; Pardo, Jordi Pardo; Zhou, Qi; Schünemann, Holger J

2015-02-01

To evaluate a new format of a summary, which presents research from synthesized evidence to patients and the public. We conducted a randomized controlled trial in 143 members of the public from five countries (Canada, Norway, Spain, Argentina, and Italy). Participants received either a new summary format (a plain language summary [PLS]) or the current format used in Cochrane systematic reviews. The new PLS presents information about the condition and intervention, a narrative summary of results, and a table of results with absolute numbers for effects of the intervention and quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation. With the new PLS, more participants understood the benefits and harms and quality of evidence (53% vs. 18%, P < 0.001); more answered each of the five questions correctly (P ≤ 0.001 for four questions); and they answered more questions correctly, median 3 (interquartile range [IQR]: 1-4) vs. 1 (IQR: 0-1), P < 0.001). Better understanding was independent of education level. More participants found information in the new PLS reliable, easy to find, easy to understand, and presented in a way that helped make decisions. Overall, participants preferred the new PLS. This new PLS format for patients and the public is a promising tool to translate evidence from synthesized research. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Monitoring of substrate and product concentrations in acetic fermentation processes for onion vinegar production by NIR spectroscopy: value addition to worthless onions.

PubMed

González-Sáiz, J M; Esteban-Díez, I; Sánchez-Gallardo, C; Pizarro, C

2008-08-01

Wastes and by-products of the onion-processing industry pose an increasing disposal and environmental problem and represent a loss of valuable sources of nutrients. The present study focused on the production of vinegar from worthless onions as a potential valorisation route which could provide a viable solution to multiple disposal and environmental problems, simultaneously offering the possibility of converting waste materials into a useful food-grade product and of exploiting the unique properties and health benefits of onions. This study deals specifically with the second and definitive step of the onion vinegar production process: the efficient production of vinegar from onion waste by transforming onion ethanol, previously produced by alcoholic fermentation, into acetic acid via acetic fermentation. Near-infrared spectroscopy (NIRS), coupled with multivariate calibration methods, has been used to monitor the concentrations of both substrates and products in acetic fermentation. Separate partial least squares (PLS) regression models, correlating NIR spectral data of fermentation samples with each kinetic parameter studied, were developed. Wavelength selection was also performed applying the iterative predictor weighting-PLS (IPW-PLS) method in order to only consider significant spectral features in each model development to improve the quality of the final models constructed. Biomass, substrate (ethanol) and product (acetic acid) concentration were predicted in the acetic fermentation of onion alcohol with high accuracy using IPW-PLS models with a root-mean-square error of the residuals in external prediction (RMSEP) lower than 2.5% for both ethanol and acetic acid, and an RMSEP of 6.1% for total biomass concentration (a very satisfactory result considering the relatively low precision and accuracy associated with the reference method used for determining the latter). Thus, the simple and reliable calibration models proposed in this study suggest that they could be implemented in routine applications to monitor and predict the key species involved in the acetic fermentation of onion alcohol, allowing the onion vinegar production process to be controlled in real time.

Effect on the partial least-squares prediction of yarn properties combining raman and infrared measurements and applying wavelength selection.

PubMed

de Groot, P J; Swierenga, H; Postma, G J; Melssen, W J; Buydens, L M C

2003-06-01

The combination of Raman and infrared spectroscopy on the one hand and wavelength selection on the other hand is used to improve the partial least-squares (PLS) prediction of seven selected yarn properties. These properties are important for on-line quality control during production. From 71 yarn samples, the Raman and infrared spectra are measured and reference methods are used to determine the selected properties. Making separate PLS models for all yarn properties using the Raman and infrared spectra, prior to wavelength selection, reveals that Raman spectroscopy outperforms infrared spectroscopy. If wavelength selection is applied, the PLS prediction error decreases and the correlation coefficient increases for all properties. However, a substantial wavelength selection effect is present for the infrared spectra compared to the Raman spectra. For the infrared spectra, wavelength selection results in PLS prediction errors comparable with the prediction performance of the Raman spectra prior to wavelength selection. Concatenating the Raman and infrared spectra does not enhance the PLS prediction performance, not even after wavelength selection. It is concluded that an infrared spectrometer, combined with a wavelength selection procedure, can be used if no (suitable) Raman instrument is available.

Dealing with gene expression missing data.

PubMed

Brás, L P; Menezes, J C

2006-05-01

Compared evaluation of different methods is presented for estimating missing values in microarray data: weighted K-nearest neighbours imputation (KNNimpute), regression-based methods such as local least squares imputation (LLSimpute) and partial least squares imputation (PLSimpute) and Bayesian principal component analysis (BPCA). The influence in prediction accuracy of some factors, such as methods' parameters, type of data relationships used in the estimation process (i.e. row-wise, column-wise or both), missing rate and pattern and type of experiment [time series (TS), non-time series (NTS) or mixed (MIX) experiments] is elucidated. Improvements based on the iterative use of data (iterative LLS and PLS imputation--ILLSimpute and IPLSimpute), the need to perform initial imputations (modified PLS and Helland PLS imputation--MPLSimpute and HPLSimpute) and the type of relationships employed (KNNarray, LLSarray, HPLSarray and alternating PLS--APLSimpute) are proposed. Overall, it is shown that data set properties (type of experiment, missing rate and pattern) affect the data similarity structure, therefore influencing the methods' performance. LLSimpute and ILLSimpute are preferable in the presence of data with a stronger similarity structure (TS and MIX experiments), whereas PLS-based methods (MPLSimpute, IPLSimpute and APLSimpute) are preferable when estimating NTS missing data.

Using the preschool language scale, fourth edition to characterize language in preschoolers with autism spectrum disorders.

PubMed

Volden, Joanne; Smith, Isabel M; Szatmari, Peter; Bryson, Susan; Fombonne, Eric; Mirenda, Pat; Roberts, Wendy; Vaillancourt, Tracy; Waddell, Charlotte; Zwaigenbaum, Lonnie; Georgiades, Stelios; Duku, Eric; Thompson, Ann

2011-08-01

The Preschool Language Scale, Fourth Edition (PLS-4; Zimmerman, Steiner, & Pond, 2002) was used to examine syntactic and semantic language skills in preschool children with autism spectrum disorders (ASD) to determine its suitability for use with this population. We expected that PLS-4 performance would be better in more intellectually able children and that receptive skills would be relatively more impaired than expressive abilities, consistent with previous findings in the area of vocabulary. Our sample consisted of 294 newly diagnosed preschool children with ASD. Children were assessed via a battery of developmental measures, including the PLS-4. As expected, PLS-4 scores were higher in more intellectually able children with ASD, and overall, expressive communication was higher than auditory comprehension. However, this overall advantage was not stable across nonverbal developmental levels. Expressive skills were significantly better than receptive skills at the youngest developmental levels, whereas the converse applied in children with more advanced development. The PLS-4 can be used to obtain a general index of early syntax and semantic skill in young children with ASD. Longitudinal data will be necessary to determine how the developmental relationship between receptive and expressive language skills unfolds in children with ASD.

Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods

NASA Astrophysics Data System (ADS)

Müller, Aline Lima Hermes; Picoloto, Rochele Sogari; Mello, Paola de Azevedo; Ferrão, Marco Flores; dos Santos, Maria de Fátima Pereira; Guimarães, Regina Célia Lourenço; Müller, Edson Irineu; Flores, Erico Marlon Moraes

2012-04-01

Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm-1). This model produced a RMSECV of 400 mg kg-1 S and RMSEP of 420 mg kg-1 S, showing a correlation coefficient of 0.990.

Mixture quantification using PLS in plastic scintillation measurements.

PubMed

Bagán, H; Tarancón, A; Rauret, G; García, J F

2011-06-01

This article reports the capability of plastic scintillation (PS) combined with multivariate calibration (Partial least squares; PLS) to detect and quantify alpha and beta emitters in mixtures. While several attempts have been made with this purpose in mind using liquid scintillation (LS), no attempt was done using PS that has the great advantage of not producing mixed waste after the measurements are performed. Following this objective, ternary mixtures of alpha and beta emitters ((241)Am, (137)Cs and (90)Sr/(90)Y) have been quantified. Procedure optimisation has evaluated the use of the net spectra or the sample spectra, the inclusion of different spectra obtained at different values of the Pulse Shape Analysis parameter and the application of the PLS1 or PLS2 algorithms. The conclusions show that the use of PS+PLS2 applied to the sample spectra, without the use of any pulse shape discrimination, allows quantification of the activities with relative errors less than 10% in most of the cases. This procedure not only allows quantification of mixtures but also reduces measurement time (no blanks are required) and the application of this procedure does not require detectors that include the pulse shape analysis parameter. Copyright © 2011 Elsevier Ltd. All rights reserved.

Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems.

PubMed

Lê Cao, Kim-Anh; Boitard, Simon; Besse, Philippe

2011-06-22

Variable selection on high throughput biological data, such as gene expression or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant information and, therefore, to better characterize diseases or assess genetic structure. There are different ways to perform variable selection in large data sets. Statistical tests are commonly used to identify differentially expressed features for explanatory purposes, whereas Machine Learning wrapper approaches can be used for predictive purposes. In the case of multiple highly correlated variables, another option is to use multivariate exploratory approaches to give more insight into cell biology, biological pathways or complex traits. A simple extension of a sparse PLS exploratory approach is proposed to perform variable selection in a multiclass classification framework. sPLS-DA has a classification performance similar to other wrapper or sparse discriminant analysis approaches on public microarray and SNP data sets. More importantly, sPLS-DA is clearly competitive in terms of computational efficiency and superior in terms of interpretability of the results via valuable graphical outputs. sPLS-DA is available in the R package mixOmics, which is dedicated to the analysis of large biological data sets.

Detection of related substances in polyene phosphatidyl choline extracted from soybean and in its commercial capsule by comprehensive supercritical fluid chromatography with mass spectrometry compared with HPLC with evaporative light scattering detection.

PubMed

Jiang, Qikun; Liu, Wanjun; Li, Xiaoting; Zhang, Tianhong; Wang, Yongjun; Liu, Xiaohong

2016-01-01

Supercritical fluid chromatography with tandem mass spectrometry was used to comprehensively profile polyene phosphatidyl choline (PPC) extracted from soybean. We achieved an efficient chromatographic analysis using a BEH-2EP column (3 × 100 mm(2) , 1.7 μm) with a mobile phase consisting of CO2 and a cosolvent in gradient combination at a flow rate of 1.0 mL/min. The cosolvent consisted of methanol, acetonitrile, and water (containing 10 mM ammonium acetate and 0.2% formic acid). The total single-run time was 7 min. We used this method to accurately detect ten different phospholipids (PLs) during extraction. The limits of quantification for phosphatidyl choline, lyso-phosphatidylcholine (LPC), phosphatidic acid (PA), sphingomyelin, phosphatidyl glycerol, phosphatidyl inositol (PI), cholesterol, cardiolipin, phosphatidyl serine, and phosphatidyl ethanolamine (PE) were 20.6, 19.52, 1.21, 2.38, 0.50, 2.28, 54.3, 0.60, 0.65, and 4.85 ng/mL, respectively. However, adopting the high-performance liquid chromatography with evaporative light scattering detection method issued by the China Food and Drug Administration, only PA, LPC, PE, PI, and PPC could be analyzed accurately, and the limits of quantification were 33.89, 60.5, 30.3, 10.9, and 61.79 μg/mL, respectively. The total single-run time was at the least 20 min. Consequently, the supercritical fluid chromatography with tandem mass spectrometry method was more suitable for the analysis of related PLs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Design and Optimization of a Chemometric-Assisted Spectrophotometric Determination of Telmisartan and Hydrochlorothiazide in Pharmaceutical Dosage Form

PubMed Central

Lakshmi, KS; Lakshmi, S

2010-01-01

Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found. PMID:21331198

Design and optimization of a chemometric-assisted spectrophotometric determination of telmisartan and hydrochlorothiazide in pharmaceutical dosage form.

PubMed

Lakshmi, Ks; Lakshmi, S

2010-01-01

Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

PubMed Central

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-01-01

Abstract. Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens. PMID:26057029

Fast Measurement of Soluble Solid Content in Mango Based on Visible and Infrared Spectroscopy Technique

NASA Astrophysics Data System (ADS)

Yu, Jiajia; He, Yong

Mango is a kind of popular tropical fruit, and the soluble solid content is an important in this study visible and short-wave near-infrared spectroscopy (VIS/SWNIR) technique was applied. For sake of investigating the feasibility of using VIS/SWNIR spectroscopy to measure the soluble solid content in mango, and validating the performance of selected sensitive bands, for the calibration set was formed by 135 mango samples, while the remaining 45 mango samples for the prediction set. The combination of partial least squares and backpropagation artificial neural networks (PLS-BP) was used to calculate the prediction model based on raw spectrum data. Based on PLS-BP, the determination coefficient for prediction (Rp) was 0.757 and root mean square and the process is simple and easy to operate. Compared with the Partial least squares (PLS) result, the performance of PLS-BP is better.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis.

PubMed

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-06-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

A comparison of different strategies in multivariate regression models for the direct determination of Mn, Cr, and Ni in steel samples using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; Gonzaga, Fabiano B.; da Rocha, Werickson F. C.; Lima, Igor C. A.

2018-01-01

Laser-induced breakdown spectroscopy (LIBS) analysis was carried out on eleven steel samples to quantify the concentrations of chromium, nickel, and manganese. LIBS spectral data were correlated to known concentrations of the samples using different strategies in partial least squares (PLS) regression models. For the PLS analysis, one predictive model was separately generated for each element, while different approaches were used for the selection of variables (VIP: variable importance in projection and iPLS: interval partial least squares) in the PLS model to quantify the contents of the elements. The comparison of the performance of the models showed that there was no significant statistical difference using the Wilcoxon signed rank test. The elliptical joint confidence region (EJCR) did not detect systematic errors in these proposed methodologies for each metal.

Chemiluminescence-based multivariate sensing of local equivalence ratios in premixed atmospheric methane-air flames

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

Tripathi, Markandey M.; Krishnan, Sundar R.; Srinivasan, Kalyan K.

Chemiluminescence emissions from OH*, CH*, C2, and CO2 formed within the reaction zone of premixed flames depend upon the fuel-air equivalence ratio in the burning mixture. In the present paper, a new partial least square regression (PLS-R) based multivariate sensing methodology is investigated and compared with an OH*/CH* intensity ratio-based calibration model for sensing equivalence ratio in atmospheric methane-air premixed flames. Five replications of spectral data at nine different equivalence ratios ranging from 0.73 to 1.48 were used in the calibration of both models. During model development, the PLS-R model was initially validated with the calibration data set using themore » leave-one-out cross validation technique. Since the PLS-R model used the entire raw spectral intensities, it did not need the nonlinear background subtraction of CO2 emission that is required for typical OH*/CH* intensity ratio calibrations. An unbiased spectral data set (not used in the PLS-R model development), for 28 different equivalence ratio conditions ranging from 0.71 to 1.67, was used to predict equivalence ratios using the PLS-R and the intensity ratio calibration models. It was found that the equivalence ratios predicted with the PLS-R based multivariate calibration model matched the experimentally measured equivalence ratios within 7%; whereas, the OH*/CH* intensity ratio calibration grossly underpredicted equivalence ratios in comparison to measured equivalence ratios, especially under rich conditions ( > 1.2). The practical implications of the chemiluminescence-based multivariate equivalence ratio sensing methodology are also discussed.« less

The subgingival microbiota of Papillon-Lefèvre syndrome.

PubMed

Albandar, Jasim M; Khattab, Razan; Monem, Fawza; Barbuto, Sara M; Paster, Bruce J

2012-07-01

There is little information about the microbiologic profiles of periodontal lesions in Papillon-Lefèvre syndrome (PLS) and the significance of bacteria in the pathogenesis of periodontitis in these patients. This comprehensive analysis of the subgingival microbiota in patients with PLS used 16S ribosomal RNA (rRNA) clonal analysis and the 16S rRNA-based Human Oral Microbe Identification Microarray (HOMIM). Thirteen patients with PLS from seven unrelated families volunteered for this microbiologic study. Subgingival plaque was collected with sterile paper points from multiple sites with ≥5 mm probing depth, and whole genomic DNA was extracted. The 16S rRNA genes were amplified, cloned, and sequenced. The samples were then probed for ≈300 predominant oral bacterial species using the HOMIM. The most commonly detected phylotypes in the clonal analysis were Gemella morbillorum, Gemella haemolysans, Granulicatella adiacens, Lachnospiraceae OT 100 (EI074), Parvimonas micra, Selenomonas noxia, and Veillonella parvula. As a group, streptococci were commonly detected in these individuals. In the HOMIM analysis, a total of 170 bacterial species/phylotypes were detected, with a range of 40 to 80 species per patient with PLS. Of these, 12 bacterial species were detected in medium to high levels in ≥50% of the individuals. The high-frequency strains were clustered into eight groups: Aggregatibacter actinomycetemcomitans, Campylobacter spp., Capnocytophaga granulosa, G. morbillorum, P. micra, Porphyromonas endodontalis, Streptococcus spp., and Tannerella forsythia. The subgingival microbiota in PLS is diverse. Periodontal pathogens commonly associated with chronic and aggressive periodontitis and opportunistic pathogens may be associated with the development of severe periodontitis in patients with PLS.

Ultrasound-triggered effects of the microbubbles coupled to GDNF- and Nurr1-loaded PEGylated liposomes in a rat model of Parkinson's disease.

PubMed

Yue, Peijian; Gao, Lin; Wang, Xuejing; Ding, Xuebing; Teng, Junfang

2018-06-01

The purpose of this study was to investigate ultrasound-triggered effects of the glial cell line-derived neurotrophic factor (GDNF) + nuclear receptor-related factor 1 (Nurr1)-polyethylene glycol (PEG)ylated liposomes-coupled microbubbles (PLs-GDNF + Nurr1-MBs) on behavioral impairment and neuron loss in a rat model of Parkinson's disease (PD). The unloaded PEGylated liposomes-coupled microbubbles (PLs-MBs) were characterized for zeta potential, particle size, and concentration. 6-hydroxydopamine (6-OHDA) was used to establish the PD rat model. Rotational, climbing pole, and suspension tests were used to detect behavioral impairment. The immunohistochemical staining of tyrosine hydroxylase (TH) and dopamine transporter (DAT) was used to assess the neuron loss. Western blot and quantitative real-time PCR (qRT-PCR) analysis were used to measure the expression levels of GDNF and Nurr1. The particle size of PLs-MBs was gradually increased, while the concentration and absolute zeta potential were gradually decreased as the time prolongs. 6-OHDA increased amphetamine-induced rotations and loss of dopaminergic neurons as compared to sham group. Interestingly, PLs-GDNF-MBs or PLs-Nurr1-MBs decreased rotations and increased the TH and DAT immunoreactivity. Combined of both genes resulted in a robust reduction in the rotations and a greater increase of the dopaminergic neurons. The delivery of PLs-GDNF + Nurr1-MBs into the brains using magnetic resonance imaging (MRI)-guided focused ultrasound may be more efficacious for the treatment of PD than the single treatment. © 2017 Wiley Periodicals, Inc.

Tissue-selective alteration of ethanolamine plasmalogen metabolism in dedifferentiated colon mucosa.

PubMed

Lopez, Daniel H; Bestard-Escalas, Joan; Garate, Jone; Maimó-Barceló, Albert; Fernández, Roberto; Reigada, Rebeca; Khorrami, Sam; Ginard, Daniel; Okazaki, Toshiro; Fernández, José A; Barceló-Coblijn, Gwendolyn

2018-08-01

Human colon lipid analysis by imaging mass spectrometry (IMS) demonstrates that the lipid fingerprint is highly sensitive to a cell's pathophysiological state. Along the colon crypt axis, and concomitant to the differentiation process, certain lipid species tightly linked to signaling (phosphatidylinositols and arachidonic acid (AA)-containing diacylglycerophospholipids), change following a rather simple mathematical expression. We extend here our observations to ethanolamine plasmalogens (PlsEtn), a unique type of glycerophospholipid presenting a vinyl ether linkage at sn-1 position. PlsEtn distribution was studied in healthy, adenomatous, and carcinomatous colon mucosa sections by IMS. In epithelium, 75% of PlsEtn changed in a highly regular manner along the crypt axis, in clear contrast with diacyl species (67% of which remained constant). Consistently, AA-containing PlsEtn species were more abundant at the base, where stem cells reside, and decreased while ascending the crypt. In turn, mono-/diunsaturated species experienced the opposite change. These gradients were accompanied by a gradual expression of ether lipid synthesis enzymes. In lamina propria, 90% of stromal PlsEtn remained unchanged despite the high content of AA and the gradient in AA-containing diacylglycerophospholipids. Finally, both lipid and protein gradients were severely affected in polyps and carcinoma. These results link PlsEtn species regulation to cell differentiation for the first time and confirm that diacyl and ether species are differently regulated. Furthermore, they reaffirm the observations on cell lipid fingerprint image sensitivity to predict cell pathophysiological status, reinforcing the translational impact both lipidome and IMS might have in clinical research. Copyright © 2018 Elsevier B.V. All rights reserved.

Novel PLS3 variants in X-linked osteoporosis: Exploring bone material properties.

PubMed

Balasubramanian, Meena; Fratzl-Zelman, Nadja; O'Sullivan, Rory; Bull, Mary; Fa Peel, Nicola; Pollitt, Rebecca C; Jones, Rebecca; Milne, Elizabeth; Smith, Kath; Roschger, Paul; Klaushofer, Klaus; Bishop, Nicholas J

2018-05-07

Idiopathic Juvenile Osteoporosis (IJO) refers to significantly lower than expected bone mass manifesting in childhood with no identifiable aetiology. IJO classically presents in early pubertal period with multiple fractures including metaphyseal and vertebral crush fractures, and low bone-mass. Here we describe two patients and provide information on their clinical phenotype, genotype and bone material analysis in one of the patients. Patient 1: 40-year old adult male diagnosed with IJO in childhood who re-presented with a hip fracture as an adult. Genetic analysis identified a pathogenic PLS3 hemizygous variant, c.1765del in exon 16. Patient 2: 15-year old boy with multiple vertebral fractures and bone biopsy findings suggestive of IJO who also has a diagnosis of autism spectrum disorder. Genetic analysis identified a maternally inherited PLS3 pathogenic c.1295T>A variant in exon 12. Analyses of the transiliac bone sample revealed severe reduction of trabecular volume and bone turnover indices and elevated bone matrix mineralisation. We propose that genetic testing for PLS3 should be undertaken in patients presenting with a current or previous history of IJO as this has implications for genetic counselling and cascade screening. The extensive evaluation of the transiliac biopsy sample of Patient 2 revealed a novel bone phenotype. This report includes a review of IJO and genetic causes of osteoporosis, and suggests that existing cases of IJO should be screened for PLS3. Through analysis of bone material properties in Patient 2, we can conclude that PLS3 does have a role in bone mineralisation. © 2018 Wiley Periodicals, Inc.

Gas density field imaging in shock dominated flows using planar laser scattering

NASA Astrophysics Data System (ADS)

Pickles, Joshua D.; Mettu, Balachandra R.; Subbareddy, Pramod K.; Narayanaswamy, Venkateswaran

2018-07-01

Planar laser scattering (PLS) imaging of ice particulates present in a supersonic stream is demonstrated to measure 2D gas density fields of shock dominated flows in low enthalpy test facilities. The technique involves mapping the PLS signal to gas density using a calibration curve that accounts for the seed particulate size distribution change across the shock wave. The PLS technique is demonstrated in a shock boundary layer interaction generated by a sharp fin placed on a cylindrical surface in Mach 2.5 flow. The shock structure generated in this configuration has complicating effects from the finite height of the fin as well as the 3D relief offered by the cylindrical surface, which result in steep spatial gradients as well as a wide range of density jumps across different locations of the shock structure. Instantaneous and mean PLS fields delineated the inviscid, separation, and reattachment shock structures at various downstream locations. The inviscid shock assumed increasingly larger curvature with downstream distance; concomitantly, the separation shock wrapped around the cylinder and the separation shock foot missed the cylinder surface entirely. The density fields obtained from the PLS technique were evaluated using RANS simulations of the same flowfield. Comparisons between the computed and measured density fields showed excellent agreement over the entire measurable region that encompassed the flow processed by inviscid, separation, and reattachment shocks away from viscous regions. The PLS approach demonstrated in this work is also shown to be largely independent of the seed particulates, which lends the extension of this approach to a wide range of test facilities.

Paper Spray Mass Spectrometry for the Forensic Analysis of Black Ballpoint Pen Inks

NASA Astrophysics Data System (ADS)

Amador, Victoria Silva; Pereira, Hebert Vinicius; Sena, Marcelo Martins; Augusti, Rodinei; Piccin, Evandro

2017-09-01

This article describes the use of paper spray mass spectrometry (PS-MS) for the direct analysis of black ink writings made with ballpoint pens. The novel approach was developed in a forensic context by first performing the classification of commercially available ballpoint pens according to their brands. Six of the most commonly worldwide utilized brands (Bic, Paper Mate, Faber Castell, Pentel, Compactor, and Pilot) were differentiated according to their characteristic chemical patterns obtained by PS-MS. MS on the negative ion mode at a mass range of m/ z 100-1000 allowed prompt discrimination just by visual inspection. On the other hand, the concept of relative ion intensity (RII) and the analysis at other mass ranges were necessary for the differentiation using the positive ion mode. PS-MS combined with partial least squares (PLS) was utilized to monitor changes on the ink chemical composition after light exposure (artificial aging studies). The PLS model was optimized by variable selection, which allowed the identification of the most influencing ions on the degradation process. The feasibility of the method on forensic investigations was also demonstrated in three different applications: (1) analysis of overlapped fresh ink lines, (2) analysis of old inks from archived documents, and (3) detection of alterations (simulated forgeries) performed on archived documents. [Figure not available: see fulltext.

Shade changing effectiveness of plasdone and blue covarine-based whitening toothpaste on teeth stained with chlorhexidine and black tea.

PubMed

Bergesch, Vania; Baggio Aguiar, Flávio Henrique; Turssi, Cecilia Pedroso; Gomes França, Fabiana Mantovani; Basting, Roberta Tarkany; Botelho Amaral, Flávia Lucisano

2017-01-01

This study evaluated the effectiveness of toothbrushing with whitening toothpaste in altering the shade of stained human enamel. Thirty fragments of human enamel, stained with chlorhexidine/black tea underwent 1000 and 5000 brushing cycles (BC) with ( n = 10): PLS (Gel Dental Day, Bitufo), Close Up White Now, Unilever (COVB) and regular (Gel Dental Night, Bitufo) toothpaste. Images were taken before staining (baseline), after staining (STN) and following 1000 and 5000 BC and were analyzed using the CIELAB parameters (ΔE, Δb and ΔL). Data were submitted to two-way ANOVA (α = 0.05). ΔE was higher from STN to baseline; 1000 BC to STN and 5000 BC to STN ( P < 0.001). Significant differences in Δb values were found from 1000 BC to STN and 5000 BC to STN. For COVB, greater ΔL was observed from 1000 BC to STN, what differed statistically from the regular toothpaste ( P < 0.05). There was no difference between toothpaste when ΔL was calculated from 5000 CB to STN. Toothpaste containing COVB or PLS in association with 5000 BCs showed similar effectiveness in changing enamel shade; but after the first 1000 toothbrushing cycles, the use of COVB toothpaste promoted higher lightness in stained enamel.

Mobility of the native Bacillus subtilis conjugative plasmid pLS20 is regulated by intercellular signaling.

PubMed

Singh, Praveen K; Ramachandran, Gayetri; Ramos-Ruiz, Ricardo; Peiró-Pastor, Ramón; Abia, David; Wu, Ling J; Meijer, Wilfried J J

2013-10-01

Horizontal gene transfer mediated by plasmid conjugation plays a significant role in the evolution of bacterial species, as well as in the dissemination of antibiotic resistance and pathogenicity determinants. Characterization of their regulation is important for gaining insights into these features. Relatively little is known about how conjugation of Gram-positive plasmids is regulated. We have characterized conjugation of the native Bacillus subtilis plasmid pLS20. Contrary to the enterococcal plasmids, conjugation of pLS20 is not activated by recipient-produced pheromones but by pLS20-encoded proteins that regulate expression of the conjugation genes. We show that conjugation is kept in the default "OFF" state and identified the master repressor responsible for this. Activation of the conjugation genes requires relief of repression, which is mediated by an anti-repressor that belongs to the Rap family of proteins. Using both RNA sequencing methodology and genetic approaches, we have determined the regulatory effects of the repressor and anti-repressor on expression of the pLS20 genes. We also show that the activity of the anti-repressor is in turn regulated by an intercellular signaling peptide. Ultimately, this peptide dictates the timing of conjugation. The implications of this regulatory mechanism and comparison with other mobile systems are discussed.

Fingerprinting of egg and oil binders in painted artworks by matrix-assisted laser desorption ionization time-of-flight mass spectrometry analysis of lipid oxidation by-products.

PubMed

Calvano, C D; van der Werf, I D; Palmisano, F; Sabbatini, L

2011-06-01

A matrix-assisted laser desorption ionization time-of-flight mass spectrometry-based approach was applied for the detection of various lipid classes, such as triacylglycerols (TAGs) and phospholipids (PLs), and their oxidation by-products in extracts of small (50-100 μg) samples obtained from painted artworks. Ageing of test specimens under various conditions, including the presence of different pigments, was preliminarily investigated. During ageing, the TAGs and PLs content decreased, whereas the amount of diglycerides, short-chain oxidative products arising from TAGs and PLs, and oxidized TAGs and PLs components increased. The examination of a series of model paint samples gave a clear indication that specific ions produced by oxidative cleavage of PLs and/or TAGs may be used as markers for egg and drying oil-based binders. Their elemental composition and hypothetical structure are also tentatively proposed. Moreover, the simultaneous presence of egg and oil binders can be easily and unambiguously ascertained through the simultaneous occurrence of the relevant specific markers. The potential of the proposed approach was demonstrated for the first time by the analysis of real samples from a polyptych of Bartolomeo Vivarini (fifteenth century) and a "French school" canvas painting (seventeenth century).

dRVVT is more sensitive than KCT or TTI for detecting lupus anticoagulant activity of anti-beta2-glycoprotein I autoantibodies.

PubMed

Pengo, V; Biasiolo, A; Rampazzo, P; Brocco, T

1999-02-01

Anti-beta2-glycoprotein I (beta2-GPI) antibodies behave as classical Lupus Anticoagulants (LA), as they inhibit phospholipid-dependent coagulation reactions and their activity disappears in the presence of excess exogenous phospholipids (PLs). We have recently shown that a certain amount of PLs in the dilute Russell Viper Venom Time (dRVVT) test system is required to express LA activity of anti beta2-GPI antibodies. We have now extended this observation to two other tests, i.e., Kaolin Clotting Time (KCT) in which PLs are not added, and Tissue Thromboplastin Inhibition test (TTI) in which PLs are extremely diluted. In fact, affinity-purified antibody preparations from 5 patients with antiphospholipid syndrome did not express or only weakly expressed anticoagulant activity in both tests; the mean ratios of coagulation times obtained with purified antibodies and that of control buffer were 1.11 and 1.0 for KCT and TTI, respectively. On the contrary, the mean ratios in dRVVT were 1.31 and 1.49 at a PLs dilution of 1:8 and 1:64, respectively. Therefore, the presence of LA activity due to autoantibodies to beta2-GPI is characterized by a positive dRVVT and negative or only weakly positive KCT and TTI.

UV–Vis and ATR–FTIR spectroscopic investigations of postmortem interval based on the changes in rabbit plasma

PubMed Central

Wang, Qi; He, Haijun; Li, Bing; Lin, Hancheng; Zhang, Yinming; Zhang, Ji

2017-01-01

Estimating PMI is of great importance in forensic investigations. Although many methods are used to estimate the PMI, a few investigations focus on the postmortem redistribution. In this study, ultraviolet–visible (UV–Vis) measurement combined with visual inspection indicated a regular diffusion of hemoglobin into plasma after death showing the redistribution of postmortem components in blood. Thereafter, attenuated total reflection–Fourier transform infrared (ATR–FTIR) spectroscopy was used to confirm the variations caused by this phenomenon. First, full-spectrum partial least-squares (PLS) and genetic algorithm combined with PLS (GA-PLS) models were constructed to predict the PMI. The performance of GA-PLS model was better than that of full-spectrum PLS model based on its root mean square error (RMSE) of cross-validation of 3.46 h (R2 = 0.95) and the RMSE of prediction of 3.46 h (R2 = 0.94). The investigation on the similarity of spectra between blood plasma and formed elements also supported the role of redistribution of components in spectral changes in postmortem plasma. These results demonstrated that ATR-FTIR spectroscopy coupled with the advanced mathematical methods could serve as a convenient and reliable tool to study the redistribution of postmortem components and estimate the PMI. PMID:28753641

Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods.

PubMed

Müller, Aline Lima Hermes; Picoloto, Rochele Sogari; de Azevedo Mello, Paola; Ferrão, Marco Flores; de Fátima Pereira dos Santos, Maria; Guimarães, Regina Célia Lourenço; Müller, Edson Irineu; Flores, Erico Marlon Moraes

2012-04-01

Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm(-1)). This model produced a RMSECV of 400 mg kg(-1) S and RMSEP of 420 mg kg(-1) S, showing a correlation coefficient of 0.990. Copyright © 2011 Elsevier B.V. All rights reserved.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

PubMed

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

Characterization of the replication region of the Bacillus subtilis plasmid pLS20: a novel type of replicon.

PubMed Central

Meijer, W J; de Boer, A J; van Tongeren, S; Venema, G; Bron, S

1995-01-01

A 3.1 kb fragment of the large (approximately 55 kb) Bacillus subtilis plasmid pLS20 containing all the information for autonomous replication was cloned and sequenced. In contrast to the parental plasmid, derived minireplicons were unstably maintained. Using deletion analysis the fragment essential and sufficient for replication was delineated to 1.1 kb. This 1.1 kb fragment is located between two divergently transcribed genes, denoted orfA and orfB, neither of which is required for replication. orfA shows homology to the B.subtilis chromosomal genes rapA (spoOL, gsiA) and rapB (spoOP). The 1.1 kb fragment, which is characterized by the presence of several regions of dyad symmetry, contains no open reading frames of more than 85 codons and shows no similarity with other known plasmid replicons. The structural organization of the pLS20 minimal replicon is entirely different from that of typical rolling circle plasmids from Gram-positive bacteria. The pLS20 minireplicons replicate in polA5 and recA4 B.subtilis strains. Taken together, these results strongly suggest that pLS20 belongs to a new class of theta replicons. PMID:7667098

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

PubMed

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Effect of the nature of phospholipids on the degree of their interaction with isobornylphenol antioxidants

NASA Astrophysics Data System (ADS)

Marakulina, K. M.; Kramor, R. V.; Lukanina, Yu. K.; Plashchina, I. G.; Polyakov, A. V.; Fedorova, I. V.; Chukicheva, I. Yu.; Kutchin, A. V.; Shishkina, L. N.

2016-02-01

The parameters of complexation between natural phospholipids (lecithin, sphingomyelin, and cephalin) with antioxidants of a new class, isobornylphenols (IBPs), were determined by UV and IR spectroscopy. The self-organization of phospholipids (PLs) was studied depending on the structure of IBPs by dynamic light scattering. The nature of phospholipids and the structure of IBPs was found to produce a substantial effect both on the degree of complexation and on the size of PL aggregates in a nonpolar solvent. Based on the obtained data it was concluded that the structure of biological membranes mainly depends on the complexation of IBP with sphingomyelin.

Energy dispersive X-ray fluorescence and scattering assessment of soil quality via partial least squares and artificial neural networks analytical modeling approaches.

PubMed

Kaniu, M I; Angeyo, K H; Mwala, A K; Mwangi, F K

2012-08-30

Soil quality assessment (SQA) calls for rapid, simple and affordable but accurate analysis of soil quality indicators (SQIs). Routine methods of soil analysis are tedious and expensive. Energy dispersive X-ray fluorescence and scattering (EDXRFS) spectrometry in conjunction with chemometrics is a potentially powerful method for rapid SQA. In this study, a 25 m Ci (109)Cd isotope source XRF spectrometer was used to realize EDXRFS spectrometry of soils. Glycerol (a simulate of "organic" soil solution) and kaolin (a model clay soil) doped with soil micro (Fe, Cu, Zn) and macro (NO(3)(-), SO(4)(2-), H(2)PO(4)(-)) nutrients were used to train multivariate chemometric calibration models for direct (non-invasive) analysis of SQIs based on partial least squares (PLS) and artificial neural networks (ANN). The techniques were compared for each SQI with respect to speed, robustness, correction ability for matrix effects, and resolution of spectral overlap. The method was then applied to perform direct rapid analysis of SQIs in field soils. A one-way ANOVA test showed no statistical difference at 95% confidence interval between PLS and ANN results compared to reference soil nutrients. PLS was more accurate analyzing C, N, Na, P and Zn (R(2)>0.9) and low SEP of (0.05%, 0.01%, 0.01%, and 1.98 μg g(-1)respectively), while ANN was better suited for analysis of Mg, Cu and Fe (R(2)>0.9 and SEP of 0.08%, 4.02 μg g(-1), and 0.88 μg g(-1) respectively). Copyright © 2012 Elsevier B.V. All rights reserved.

Application of FTIR-ATR spectroscopy coupled with multivariate analysis for rapid estimation of butter adulteration.

PubMed

Fadzlillah, Nurrulhidayah Ahmad; Rohman, Abdul; Ismail, Amin; Mustafa, Shuhaimi; Khatib, Alfi

2013-01-01

In dairy product sector, butter is one of the potential sources of fat soluble vitamins, namely vitamin A, D, E, K; consequently, butter is taken into account as high valuable price from other dairy products. This fact has attracted unscrupulous market players to blind butter with other animal fats to gain economic profit. Animal fats like mutton fat (MF) are potential to be mixed with butter due to the similarity in terms of fatty acid composition. This study focused on the application of FTIR-ATR spectroscopy in conjunction with chemometrics for classification and quantification of MF as adulterant in butter. The FTIR spectral region of 3910-710 cm⁻¹ was used for classification between butter and butter blended with MF at various concentrations with the aid of discriminant analysis (DA). DA is able to classify butter and adulterated butter without any mistakenly grouped. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the frequency regions of 3910-710 cm⁻¹. The equation obtained for the relationship between actual value of MF and FTIR predicted values of MF in PLS calibration model was y = 0.998x + 1.033, with the values of coefficient of determination (R²) and root mean square error of calibration are 0.998 and 0.046% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with MF. Using 9 principal components, root mean square error of prediction (RMSEP) is 1.68% (v/v). The results showed that FTIR spectroscopy can be used for the classification and quantification of MF in butter formulation for verification purposes.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

PubMed

Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

2017-03-05

The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized light. Published by Elsevier B.V.

Mass Spectrometry and Fourier Transform Infrared Spectroscopy for Analysis of Biological Materials

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

Anderson, Timothy J.

Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55% (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the eight weekmore » study, cecal and distal-colon contents samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic treated subgroups were well classified for cecal samples and modestly separated for distal-colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.« less

High-resolution time-of-flight mass spectrometry fingerprinting of metabolites from cecum and distal colon contents of rats fed resistant starch

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

Anderson, Timothy J.; Jones, Roger W.; Ai, Yongfeng

Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55 % (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the 8-weekmore » study, cecal and distal colon content samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic-treated subgroups were well classified for cecal samples and modestly separated for distal colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.« less

A nonpolar, nonamphiphilic molecule can accelerate adsorption of phospholipids and lower their surface tension at the air/water interface.

PubMed

Nguyen, Phuc Nghia; Trinh Dang, Thuan Thao; Waton, Gilles; Vandamme, Thierry; Krafft, Marie Pierre

2011-10-04

The adsorption dynamics of a series of phospholipids (PLs) at the interface between an aqueous solution or dispersion of the PL and a gas phase containing the nonpolar, nonamphiphilic linear perfluorocarbon perfluorohexane (PFH) was studied by bubble profile analysis tensiometry. The PLs investigated were dioctanoylphosphatidylcholine (DiC(8)-PC), dilaurylphosphatidylcholine, dimyristoylphosphatidylcholine, and dipalmitoylphosphatidylcholine. The gas phase consisted of air or air saturated with PFH. The perfluorocarbon gas was found to have an unexpected, strong effect on both the adsorption rate and the equilibrium interfacial tension (γ(eq)) of the PLs. First, for all of the PLs, and at all concentrations investigated, the γ(eq) values were significantly lower (by up to 10 mN m(-1)) when PFH was present in the gas phase. The efficacy of PFH in decreasing γ(eq) depends on the ability of PLs to form micelles or vesicles in water. For vesicles, it also depends on the gel or fluid state of the membranes. Second, the adsorption rates of all the PLs at the interface (as assessed by the time required for the initial interfacial tension to be reduced by 30%) are significantly accelerated (by up to fivefold) by the presence of PFH for the lower PL concentrations. Both the surface-tension reducing effect and the adsorption rate increasing effect establish that PFH has a strong interaction with the PL monolayer and acts as a cosurfactant at the interface, despite the absence of any amphiphilic character. Fitting the adsorption profiles of DiC(8)-PC at the PFH-saturated air/aqueous solution interface with the modified Frumkin model indicated that the PFH molecule lay horizontally at the interface. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and validation of a Partial Least Squares-Discriminant Analysis (PLS-DA) model based on the determination of ethyl glucuronide (EtG) and fatty acid ethyl esters (FAEEs) in hair for the diagnosis of chronic alcohol abuse.

PubMed

Alladio, E; Giacomelli, L; Biosa, G; Corcia, D Di; Gerace, E; Salomone, A; Vincenti, M

2018-01-01

The chronic intake of an excessive amount of alcohol is currently ascertained by determining the concentration of direct alcohol metabolites in the hair samples of the alleged abusers, including ethyl glucuronide (EtG) and, less frequently, fatty acid ethyl esters (FAEEs). Indirect blood biomarkers of alcohol abuse are still determined to support hair EtG results and diagnose a consequent liver impairment. In the present study, the supporting role of hair FAEEs is compared with indirect blood biomarkers with respect to the contexts in which hair EtG interpretation is uncertain. Receiver Operating Characteristics (ROC) curves and multivariate Principal Component Analysis (PCA) demonstrated much stronger correlation of EtG results with FAEEs than with any single indirect biomarker or their combinations. Partial Least Squares Discriminant Analysis (PLS-DA) models based on hair EtG and FAEEs were developed to maximize the biomarkers information content on a multivariate background. The final PLS-DA model yielded 100% correct classification on a training/evaluation dataset of 155 subjects, including both chronic alcohol abusers and social drinkers. Then, the PLS-DA model was validated on an external dataset of 81 individual providing optimal discrimination ability between chronic alcohol abusers and social drinkers, in terms of specificity and sensitivity. The PLS-DA scores obtained for each subject, with respect to the PLS-DA model threshold that separates the probabilistic distributions for the two classes, furnished a likelihood ratio value, which in turn conveys the strength of the experimental data support to the classification decision, within a Bayesian logic. Typical boundary real cases from daily work are discussed, too. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of a Functional Plasmodesmal Localization Signal in a Plant Viral Cell-To-Cell-Movement Protein.

PubMed

Yuan, Cheng; Lazarowitz, Sondra G; Citovsky, Vitaly

2016-01-19

Our fundamental knowledge of the protein-sorting pathways required for plant cell-to-cell trafficking and communication via the intercellular connections termed plasmodesmata has been severely limited by the paucity of plasmodesmal targeting sequences that have been identified to date. To address this limitation, we have identified the plasmodesmal localization signal (PLS) in the Tobacco mosaic virus (TMV) cell-to-cell-movement protein (MP), which has emerged as the paradigm for dissecting the molecular details of cell-to-cell transport through plasmodesmata. We report here the identification of a bona fide functional TMV MP PLS, which encompasses amino acid residues between positions 1 and 50, with residues Val-4 and Phe-14 potentially representing critical sites for PLS function that most likely affect protein conformation or protein interactions. We then demonstrated that this PLS is both necessary and sufficient for protein targeting to plasmodesmata. Importantly, as TMV MP traffics to plasmodesmata by a mechanism that is distinct from those of the three plant cell proteins in which PLSs have been reported, our findings provide important new insights to expand our understanding of protein-sorting pathways to plasmodesmata. The science of virology began with the discovery of Tobacco mosaic virus (TMV). Since then, TMV has served as an experimental and conceptual model for studies of viruses and dissection of virus-host interactions. Indeed, the TMV cell-to-cell-movement protein (MP) has emerged as the paradigm for dissecting the molecular details of cell-to-cell transport through the plant intercellular connections termed plasmodesmata. However, one of the most fundamental and key functional features of TMV MP, its putative plasmodesmal localization signal (PLS), has not been identified. Here, we fill this gap in our knowledge and identify the TMV MP PLS. Copyright © 2016 Yuan et al.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

NASA Astrophysics Data System (ADS)

Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

A preliminary MTD-PLS study for androgen receptor binding of steroid compounds

NASA Astrophysics Data System (ADS)

Bora, Alina; Seclaman, E.; Kurunczi, L.; Funar-Timofei, Simona

The relative binding affinities (RBA) of a series of 30 steroids for Human Androgen Receptor (AR) were used to initiate a MTD-PLS study. The 3D structures of all the compounds were obtained through geometry optimization in the framework of AM1 semiempirical quantum chemical method. The MTD hypermolecule (HM) was constructed, superposing these structures on the AR-bonded dihydrotestosterone (DHT) skeleton obtained from PDB (AR complex, ID 1I37). The parameters characterizing the HM vertices were collected using: AM1 charges, XlogP fragmental values, calculated fragmental polarizabilities (from refractivities), volumes, and H-bond parameters (Raevsky's thermodynamic originated scale). The resulted QSAR data matrix was submitted to PCA (Principal Component Analysis) and PLS (Projections in Latent Structures) procedure (SIMCA P 9.0); five compounds were selected as test set, and the remaining 25 molecules were used as training set. In the PLS procedure supplementary chemical information was introduced, i.e. the steric effect was always considered detrimental, and the hydrophobic and van der Waals interactions were imposed to be beneficial. The initial PLS model using the entire training set has the following characteristics: R2Y = 0.584, Q2 = 0.344. Based on distances to the model criterions (DMODX and DMODY), five compounds were eliminated and the obtained final model had the following characteristics: R2Y D 0.891, Q2 D 0.591. For this the external predictivity on the test set was unsatisfactory. A tentative explanation for these behaviors is the weak information content of the input QSAR matrix for the present series comparatively with other successful MTD-PLS modeling published elsewhere.

Purified human MDR 1 modulates membrane potential in reconstituted proteoliposomes.

PubMed

Howard, Ellen M; Roepe, Paul D

2003-04-01

Human multidrug resistance (hu MDR 1) cDNA was fused to a P. shermanii transcarboxylase biotin acceptor domain (TCBD), and the fusion protein was heterologously overexpressed at high yield in K(+)-uptake deficient Saccharomyces cerevisiae yeast strain 9.3, purified by avidin-biotin chromatography, and reconstituted into proteoliposomes (PLs) formed with Escherichia coli lipid. As measured by pH- dependent ATPase activity, purified, reconstituted, biotinylated MDR-TCBD protein is fully functional. Dodecyl maltoside proved to be the most effective detergent for the membrane solubilization of MDR-TCBD, and various salts were found to significantly affect reconstitution into PLs. After extensive analysis, we find that purified reconstituted MDR-TCBD protein does not catalyze measurable H(+) pumping in the presence of ATP. In the presence of physiologic [ATP], K(+)/Na(+) diffusion potentials monitored by either anionic oxonol or cationic carbocyanine are easily established upon addition of valinomycin to either control or MDR-TCBD PLs. However, in the absence of ATP, although control PLs still maintain easily measurable K(+)/Na(+) diffusion potentials upon addition of valinomycin, MDR-TCBD PLs do not. Dissipation of potential by MDR-TCBD is clearly [ATP] dependent and also appears to be Cl(-) dependent, since replacing Cl(-) with equimolar glutamate restores the ability of MDR-TCBD PLs to form a membrane potential in the absence of physiologic [ATP]. The data are difficult to reconcile with models that might propose ATP-catalyzed "pumping" of the fluorescent probes we use and are more consistent with electrically passive anion transport via MDR-TCBD protein, but only at low [ATP]. These observations may help to resolve the confusing array of data related to putative ion transport by hu MDR 1 protein.

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

PubMed

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Clinicopathologic implications of DNA mismatch repair status in endometrial carcinomas.

PubMed

Shikama, Ayumi; Minaguchi, Takeo; Matsumoto, Koji; Akiyama-Abe, Azusa; Nakamura, Yuko; Michikami, Hiroo; Nakao, Sari; Sakurai, Manabu; Ochi, Hiroyuki; Onuki, Mamiko; Satoh, Toyomi; Oki, Akinori; Yoshikawa, Hiroyuki

2016-02-01

Endometrial carcinoma is the most common malignancy in women with Lynch syndrome caused by mismatch repair (MMR) deficiency. We investigated the clinicopathologic significance of deficient MMR and Lynch syndrome presumed by MMR analyses in unselected endometrial carcinomas. We analyzed immunohistochemistry of MMR proteins (MLH1/MSH2/MSH6/PMS2) and MLH1 promoter methylation in primary endometrial carcinomas from 221 consecutive patients. Based on these results, tumors were categorized as sporadic or probable Lynch syndrome (PLS). Clinicopathologic variables and prognosis were compared according to MMR status and sporadic/PLS classification. Deficient MMR showed only trends towards favorable overall survival (OS) compared with intact MMR (p=0.13), whereas PLS showed significantly better OS than sporadic (p=0.038). Sporadic was significantly associated with older age, obesity, deep myometrial invasion, and advanced stage (p=0.008, 0.01, 0.02 and 0.03), while PLS was significantly associated with early stage and Lynch syndrome-associated multiple cancer (p=0.04 and 0.001). The trend towards favorable OS of PLS was stronger in advanced stage than in early stage (hazard ratio, 0.044 [95% CI 0-25.6] vs. 0.49 [0.063-3.8]). In the subset receiving adjuvant therapies, PLS showed trends towards favorable disease-free survival compared to sporadic by contrast with patients receiving no adjuvant therapies showing no such trend (hazard ratio, 0.045 [95% CI 0-20.3] vs. 0.81 [0.095-7.0]). The current findings suggest that analyzing MMR status and searching for Lynch syndrome may identify a subset of patients with favorable survival and high sensitivity to adjuvant therapies, providing novel and useful implications for formulating the precision medicine in endometrial carcinoma. Copyright © 2015 Elsevier Inc. All rights reserved.

Wind profiling for a coherent wind Doppler lidar by an auto-adaptive background subtraction approach.

PubMed

Wu, Yanwei; Guo, Pan; Chen, Siying; Chen, He; Zhang, Yinchao

2017-04-01

Auto-adaptive background subtraction (AABS) is proposed as a denoising method for data processing of the coherent Doppler lidar (CDL). The method is proposed specifically for a low-signal-to-noise-ratio regime, in which the drifting power spectral density of CDL data occurs. Unlike the periodogram maximum (PM) and adaptive iteratively reweighted penalized least squares (airPLS), the proposed method presents reliable peaks and is thus advantageous in identifying peak locations. According to the analysis results of simulated and actually measured data, the proposed method outperforms the airPLS method and the PM algorithm in the furthest detectable range. The proposed method improves the detection range approximately up to 16.7% and 40% when compared to the airPLS method and the PM method, respectively. It also has smaller mean wind velocity and standard error values than the airPLS and PM methods. The AABS approach improves the quality of Doppler shift estimates and can be applied to obtain the whole wind profiling by the CDL.

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Preliminary antifungal and cytotoxic evaluation of synthetic cycloalkyl[b]thiophene derivatives with PLS-DA analysis.

PubMed

Souza, Beatriz C C; De Oliveira, Tiago B; Aquino, Thiago M; de Lima, Maria C A; Pitta, Ivan R; Galdino, Suely L; Lima, Edeltrudes O; Gonçalves-Silva, Teresinha; Militão, Gardênia C G; Scotti, Luciana; Scotti, Marcus T; Mendonça, Francisco J B

2012-06-01

A series of 2-[(arylidene)amino]-cycloalkyl[b]thiophene-3-carbonitriles (2a-x) was synthesized by incorporation of substituted aromatic aldehydes in Gewald adducts (1a-c). The title compounds were screened for their antifungal activity against Candida krusei and Criptococcus neoformans and for their antiproliferative activity against a panel of 3 human cancer cell lines (HT29, NCI H-292 and HEP). For antiproliferative activity, the partial least squares (PLS) methodology was applied. Some of the prepared compounds exhibited promising antifungal and proliferative properties. The most active compounds for antifungal activity were cyclohexyl[b]thiophene derivatives, and for antiproliferative activity cycloheptyl[b]thiophene derivatives, especially 2-[(1H-indol-2-yl-methylidene)amino]- 5,6,7,8-tetrahydro-4H-cyclohepta[b]thiophene-3-carbonitrile (2r), which inhibited more than 97 % growth of the three cell lines. The PLS discriminant analysis (PLS-DA) applied generated good exploratory and predictive results and showed that the descriptors having shape characteristics were strongly correlated with the biological data.

Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

PubMed

Miaw, Carolina Sheng Whei; Assis, Camila; Silva, Alessandro Rangel Carolino Sales; Cunha, Maria Luísa; Sena, Marcelo Martins; de Souza, Scheilla Vitorino Carvalho

2018-07-15

Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Personnel Launch System for safe and efficient manned operations

NASA Astrophysics Data System (ADS)

Petro, Andrew J.; Andrews, Dana G.; Wetzel, Eric D.

1990-10-01

Several Conceptual designs for a simple, rugged Personnel Launch System (PLS) are presented. This system could transport people to and from Low Earth Orbit (LEO) starting in the late 1990's using a new modular Advanced Launch System (ALS) developed for the Space Exploration Initiative (SEI). The PLS is designed to be one element of a new space transportation architecture including heavy-lift cargo vehicles, lunar transfer vehicles, and multiple-role spcecraft such as the current Space Shuttle. The primary role of the PLS would be to deliver crews embarking on lunar or planetary missions to the Space Station, but it would also be used for earth-orbit sortie missions, space rescue missions, and some satellite servicing missions. The PLS design takes advantage of emerging electronic and structures technologies to offer a robust vehicle with autonomous operating and quick turnaround capabilities. Key features include an intact abort capability anywhere in the operating envelope, and elimination of all toxic propellants to streamline ground operations.

Papaya latex supernatant has a potent effect on the free-living stages of equid cyathostomins in vitro.

PubMed

Peachey, L E; Pinchbeck, G L; Matthews, J B; Burden, F A; Behnke, J M; Hodgkinson, J E

2016-09-15

The control of equid gastrointestinal nematodes in developed countries, in particular the cyathostomins, is threatened by high levels of anthelmintic resistance. In recent years, there has been increasing interest in the evaluation of traditional 'ethnoveterinary' medicines as alternatives to chemical anthelmintics. The cysteine proteinases (CPs), a group of enzymes derived from fruits such as papaya (Carica papaya), pineapple (Ananas comosus) and figs (Ficus spp.), have shown good efficacy against adult stages of a range of parasitic nematodes, in vitro and in vivo. The efficacy of CPs against cyathostomins remains to be explored. In this study, the efficacy of a crude preparation of CPs, papaya latex supernatant (PLS), against the free-living stages of cyathostomins was evaluated using two in vitro tests, the egg hatch test (EHT) and the larval migration inhibition test (LMIT). It was demonstrated that PLS had a potent effect in the EHT, with EC-50 values in the range of 0.12-0.22μM. At concentrations above 6.25μM the eggs did not develop, below this concentration the L1 developed but they lost integrity of the cuticle upon hatching. These effects were inhibited by pre-incubation of PLS with the CP inhibitor L-trans-epoxysuccinyl-l-leucylamido-(4-guanidino butane) (E64), indicating that CPs were responsible for the anti-parasitic activity. A dose-dependent inhibition of migration of third stage larvae (L3) in the LMIT was demonstrated at higher concentrations of PLS, with EC-50 values in the range of 67.35-106.31μM. Incubation of PLS with E64 prior to use in the LMIT did not reverse the anti-migratory effect, suggesting that CPs were not responsible for the reduced migration of cyathostomin L3 and that PLS also contains an additional active compound. This is the first report of PLS and/or CPs showing activity against the free-living stages of a parasitic helminth. In addition, it suggests that cyathostomins are highly sensitive to the effects of CPs and further evaluation of their efficacy against parasitic stages and in vivo are strongly indicated. Copyright © 2016 Elsevier B.V. All rights reserved.

ETV Program Report: Coatings for Wastewater Collection Systems - Protective Liner Systems, Inc., Epoxy Mastic, PLS-614

EPA Science Inventory

The Protective Liner Systems International, Inc. Epoxy Mastic PLS-614 coating used for wastewater collection system rehabilitation was evaluated by EPA’s Environmental Technology Verification Program under laboratory conditions at the Center for Innovative Grouting Material and T...

Application of Partial Least Square (PLS) Regression to Determine Landscape-Scale Aquatic Resources Vulnerability in the Ozark Mountains

EPA Science Inventory

Partial least squares (PLS) analysis offers a number of advantages over the more traditionally used regression analyses applied in landscape ecology, particularly for determining the associations among multiple constituents of surface water and landscape configuration. Common dat...

Real-time near-infrared spectroscopic inspection system for adulterated sesame oil

NASA Astrophysics Data System (ADS)

Kang, Sukwon; Lee, Kang-jin; Son, Jaeryong; Kim, Moon S.

2010-04-01

Sesame seed oil is popular and expensive in Korea and has been often mixed with other less expensive vegetable oils. The objective of this research is to develop an economical and rapid adulteration determination system for sesame seed oil mixed with other vegetable oils. A recently developed inspection system consists of a light source, a measuring unit, a spectrophotometer, fiber optics, and a data acquisition module. A near-infrared transmittance spectroscopic method was used to develop the prediction model using Partial Least Square (PLS). Sesame seed oil mixed with a range of concentrations of corn, or perilla, or soybean oil was measured in 8 mm diameter glass tubes. For the model development, a correlation coefficient value of 0.98 was observed for corn, perilla, and soybean oil mixtures with standard errors of correlation of 6.32%, 6.16%, and 5.67%, respectively. From the prediction model, the correlation coefficients of corn oil, perilla oil, and soybean oil were 0.98, 0.97 and 0.98, respectively. The Standard Error of Prediction (SEP) for corn oil, perilla oil, and soybean oil were 6.52%, 6.89% and 5.88%, respectively. The results indicated that this system can potentially be used as a rapid non-destructive adulteration analysis tool for sesame seed oil mixed with other vegetable oils.

ε-Poly-l-Lysine Peptide Chain Length Regulated by the Linkers Connecting the Transmembrane Domains of ε-Poly-l-Lysine Synthetase

PubMed Central

Kito, Naoko; Kita, Akihiro; Imokawa, Yuuki; Yamanaka, Kazuya; Maruyama, Chitose; Katano, Hajime

2014-01-01

ε-Poly-l-lysine (ε-PL), consisting of 25 to 35 l-lysine residues with linkages between the α-carboxyl groups and ε-amino groups, is produced by Streptomyces albulus NBRC14147. ε-PL synthetase (Pls) is a membrane protein with six transmembrane domains (TM1 to TM6) as well as both an adenylation domain and a thiolation domain, characteristic of the nonribosomal peptide synthetases. Pls directly generates ε-PL chain length diversity (25- to 35-mer), but the processes that control the chain length of ε-PL during the polymerization reaction are still not fully understood. Here, we report on the identification of Pls amino acid residues involved in the regulation of the ε-PL chain length. From approximately 12,000 variants generated by random mutagenesis, we found 8 Pls variants that produced shorter chains of ε-PL. These variants have one or more mutations in two linker regions connecting the TM1 and TM2 domains and the TM3 and TM4 domains. In the Pls catalytic mechanism, the growing chain of ε-PL is not tethered to the enzyme, implying that the enzyme must hold the growing chain until the polymerization reaction is complete. Our findings reveal that the linker regions are important contributors to grasp the growing chain of ε-PL. PMID:24907331

Impaired corticopontocerebellar tracts underlie pseudobulbar affect in motor neuron disorders

PubMed Central

Katipally, Rohan; Kim, Meredith P.; Schanz, Olivia; Stephen, Matthew; Danielian, Laura; Wu, Tianxia; Huey, Edward D.; Meoded, Avner

2014-01-01

Objective: The objectives of the study were (1) to determine the prevalence and characteristics of pseudobulbar affect (PBA) in patients with primary lateral sclerosis (PLS) and amyotrophic lateral sclerosis (ALS) in an outpatient clinic population, and (2) to test the hypothesis that damage of inputs to the cerebellum, leading to cerebellar dysmodulation, is associated with PBA. Methods: Chart review of all patients with PLS and ALS seen between 2000 and 2013. The examining neurologist documented the presence or absence of PBA in 87 patients. Forty-seven patients also had diffusion tensor imaging (DTI) studies. Tract-based spatial statistics were used to compare DTI of patients with and without PBA to identify altered white matter tracts associated with PBA. Results: Thirty-one of 50 patients with PLS and 12 of 37 patients with ALS had PBA. Psychiatric/emotional assessment found congruence between mood and affect during episodes, but excessive magnitude of the response. DTI studies of 25 PLS and 22 ALS patient brains showed reduced fractional anisotropy of the corticospinal and callosal white matter tracts in all patients. Patients with PBA additionally had increased mean diffusivity of white matter tracts underlying the frontotemporal cortex, the transverse pontine fibers, and the middle cerebellar peduncle. Conclusions: PBA is common in PLS. Imaging findings showing disruption of corticopontocerebellar pathways support the hypothesis that PBA can be viewed as a “dysmetria” of emotional expression resulting from cerebellar dysmodulation. PMID:25008395

Impaired corticopontocerebellar tracts underlie pseudobulbar affect in motor neuron disorders.

PubMed

Floeter, Mary Kay; Katipally, Rohan; Kim, Meredith P; Schanz, Olivia; Stephen, Matthew; Danielian, Laura; Wu, Tianxia; Huey, Edward D; Meoded, Avner

2014-08-12

The objectives of the study were (1) to determine the prevalence and characteristics of pseudobulbar affect (PBA) in patients with primary lateral sclerosis (PLS) and amyotrophic lateral sclerosis (ALS) in an outpatient clinic population, and (2) to test the hypothesis that damage of inputs to the cerebellum, leading to cerebellar dysmodulation, is associated with PBA. Chart review of all patients with PLS and ALS seen between 2000 and 2013. The examining neurologist documented the presence or absence of PBA in 87 patients. Forty-seven patients also had diffusion tensor imaging (DTI) studies. Tract-based spatial statistics were used to compare DTI of patients with and without PBA to identify altered white matter tracts associated with PBA. Thirty-one of 50 patients with PLS and 12 of 37 patients with ALS had PBA. Psychiatric/emotional assessment found congruence between mood and affect during episodes, but excessive magnitude of the response. DTI studies of 25 PLS and 22 ALS patient brains showed reduced fractional anisotropy of the corticospinal and callosal white matter tracts in all patients. Patients with PBA additionally had increased mean diffusivity of white matter tracts underlying the frontotemporal cortex, the transverse pontine fibers, and the middle cerebellar peduncle. PBA is common in PLS. Imaging findings showing disruption of corticopontocerebellar pathways support the hypothesis that PBA can be viewed as a "dysmetria" of emotional expression resulting from cerebellar dysmodulation. © 2014 American Academy of Neurology.

Enzymatically oxidized phospholipids restore thrombin generation in coagulation factor deficiencies.

PubMed

Slatter, David A; Percy, Charles L; Allen-Redpath, Keith; Gajsiewicz, Joshua M; Brooks, Nick J; Clayton, Aled; Tyrrell, Victoria J; Rosas, Marcela; Lauder, Sarah N; Watson, Andrew; Dul, Maria; Garcia-Diaz, Yoel; Aldrovandi, Maceler; Heurich, Meike; Hall, Judith; Morrissey, James H; Lacroix-Desmazes, Sebastien; Delignat, Sandrine; Jenkins, P Vincent; Collins, Peter W; O'Donnell, Valerie B

2018-03-22

Hemostatic defects are treated using coagulation factors; however, clot formation also requires a procoagulant phospholipid (PL) surface. Here, we show that innate immune cell-derived enzymatically oxidized phospholipids (eoxPL) termed hydroxyeicosatetraenoic acid-phospholipids (HETE-PLs) restore hemostasis in human and murine conditions of pathological bleeding. HETE-PLs abolished blood loss in murine hemophilia A and enhanced coagulation in factor VIII- (FVIII-), FIX-, and FX-deficient human plasma . HETE-PLs were decreased in platelets from patients after cardiopulmonary bypass (CPB). To explore molecular mechanisms, the ability of eoxPL to stimulate individual isolated coagulation factor/cofactor complexes was tested in vitro. Extrinsic tenase (FVIIa/tissue factor [TF]), intrinsic tenase (FVIIIa/FIXa), and prothrombinase (FVa/FXa) all were enhanced by both HETE-PEs and HETE-PCs, suggesting a common mechanism involving the fatty acid moiety. In plasma, 9-, 15-, and 12-HETE-PLs were more effective than 5-, 11-, or 8-HETE-PLs, indicating positional isomer specificity. Coagulation was enhanced at lower lipid/factor ratios, consistent with a more concentrated area for protein binding. Surface plasmon resonance confirmed binding of FII and FX to HETE-PEs. HETE-PEs increased membrane curvature and thickness, but not surface charge or homogeneity, possibly suggesting increased accessibility to cations/factors. In summary, innate immune-derived eoxPL enhance calcium-dependent coagulation factor function, and their potential utility in bleeding disorders is proposed.

Enzymatically oxidized phospholipids restore thrombin generation in coagulation factor deficiencies

PubMed Central

Slatter, David A.; Percy, Charles L.; Allen-Redpath, Keith; Gajsiewicz, Joshua M.; Brooks, Nick J.; Tyrrell, Victoria J.; Lauder, Sarah N.; Watson, Andrew; Dul, Maria; Garcia-Diaz, Yoel; Aldrovandi, Maceler; Heurich, Meike; Hall, Judith; Lacroix-Desmazes, Sebastien; Delignat, Sandrine; Jenkins, P. Vincent; Collins, Peter W.; O’Donnell, Valerie B.

2018-01-01

Hemostatic defects are treated using coagulation factors; however, clot formation also requires a procoagulant phospholipid (PL) surface. Here, we show that innate immune cell–derived enzymatically oxidized phospholipids (eoxPL) termed hydroxyeicosatetraenoic acid–phospholipids (HETE-PLs) restore hemostasis in human and murine conditions of pathological bleeding. HETE-PLs abolished blood loss in murine hemophilia A and enhanced coagulation in factor VIII- (FVIII-), FIX-, and FX-deficient human plasma . HETE-PLs were decreased in platelets from patients after cardiopulmonary bypass (CPB). To explore molecular mechanisms, the ability of eoxPL to stimulate individual isolated coagulation factor/cofactor complexes was tested in vitro. Extrinsic tenase (FVIIa/tissue factor [TF]), intrinsic tenase (FVIIIa/FIXa), and prothrombinase (FVa/FXa) all were enhanced by both HETE-PEs and HETE-PCs, suggesting a common mechanism involving the fatty acid moiety. In plasma, 9-, 15-, and 12-HETE-PLs were more effective than 5-, 11-, or 8-HETE-PLs, indicating positional isomer specificity. Coagulation was enhanced at lower lipid/factor ratios, consistent with a more concentrated area for protein binding. Surface plasmon resonance confirmed binding of FII and FX to HETE-PEs. HETE-PEs increased membrane curvature and thickness, but not surface charge or homogeneity, possibly suggesting increased accessibility to cations/factors. In summary, innate immune-derived eoxPL enhance calcium-dependent coagulation factor function, and their potential utility in bleeding disorders is proposed. PMID:29563336

Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea.

PubMed

Lee, Soo Yee; Mediani, Ahmed; Maulidiani, Maulidiani; Khatib, Alfi; Ismail, Intan Safinar; Zawawi, Norhasnida; Abas, Faridah

2018-01-01

Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis. Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities. Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Correlation of sensory bitterness in dairy protein hydrolysates: Comparison of prediction models built using sensory, chromatographic and electronic tongue data.

PubMed

Newman, J; Egan, T; Harbourne, N; O'Riordan, D; Jacquier, J C; O'Sullivan, M

2014-08-01

Sensory evaluation can be problematic for ingredients with a bitter taste during research and development phase of new food products. In this study, 19 dairy protein hydrolysates (DPH) were analysed by an electronic tongue and their physicochemical characteristics, the data obtained from these methods were correlated with their bitterness intensity as scored by a trained sensory panel and each model was also assessed by its predictive capabilities. The physiochemical characteristics of the DPHs investigated were degree of hydrolysis (DH%), and data relating to peptide size and relative hydrophobicity from size exclusion chromatography (SEC) and reverse phase (RP) HPLC. Partial least square regression (PLS) was used to construct the prediction models. All PLS regressions had good correlations (0.78 to 0.93) with the strongest being the combination of data obtained from SEC and RP HPLC. However, the PLS with the strongest predictive power was based on the e-tongue which had the PLS regression with the lowest root mean predicted residual error sum of squares (PRESS) in the study. The results show that the PLS models constructed with the e-tongue and the combination of SEC and RP-HPLC has potential to be used for prediction of bitterness and thus reducing the reliance on sensory analysis in DPHs for future food research. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification.

PubMed

Ramírez, J; Górriz, J M; Segovia, F; Chaves, R; Salas-Gonzalez, D; López, M; Alvarez, I; Padilla, P

2010-03-19

This letter shows a computer aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The proposed method is based on partial least squares (PLS) regression model and a random forest (RF) predictor. The challenge of the curse of dimensionality is addressed by reducing the large dimensionality of the input data by downscaling the SPECT images and extracting score features using PLS. A RF predictor then forms an ensemble of classification and regression tree (CART)-like classifiers being its output determined by a majority vote of the trees in the forest. A baseline principal component analysis (PCA) system is also developed for reference. The experimental results show that the combined PLS-RF system yields a generalization error that converges to a limit when increasing the number of trees in the forest. Thus, the generalization error is reduced when using PLS and depends on the strength of the individual trees in the forest and the correlation between them. Moreover, PLS feature extraction is found to be more effective for extracting discriminative information from the data than PCA yielding peak sensitivity, specificity and accuracy values of 100%, 92.7%, and 96.9%, respectively. Moreover, the proposed CAD system outperformed several other recently developed AD CAD systems. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Optical and laser spectroscopic diagnostics for energy applications

NASA Astrophysics Data System (ADS)

Tripathi, Markandey Mani

The continuing need for greater energy security and energy independence has motivated researchers to develop new energy technologies for better energy resource management and efficient energy usage. The focus of this dissertation is the development of optical (spectroscopic) sensing methodologies for various fuels, and energy applications. A fiber-optic NIR sensing methodology was developed for predicting water content in bio-oil. The feasibility of using the designed near infrared (NIR) system for estimating water content in bio-oil was tested by applying multivariate analysis to NIR spectral data. The calibration results demonstrated that the spectral information can successfully predict the bio-oil water content (from 16% to 36%). The effect of ultraviolet (UV) light on the chemical stability of bio-oil was studied by employing laser-induced fluorescence (LIF) spectroscopy. To simulate the UV light exposure, a laser in the UV region (325 nm) was employed for bio-oil excitation. The LIF, as a signature of chemical change, was recorded from bio-oil. From this study, it was concluded that phenols present in the bio-oil show chemical instability, when exposed to UV light. A laser-induced breakdown spectroscopy (LIBS)-based optical sensor was designed, developed, and tested for detection of four important trace impurities in rocket fuel (hydrogen). The sensor can simultaneously measure the concentrations of nitrogen, argon, oxygen, and helium in hydrogen from storage tanks and supply lines. The sensor had estimated lower detection limits of 80 ppm for nitrogen, 97 ppm for argon, 10 ppm for oxygen, and 25 ppm for helium. A chemiluminescence-based spectroscopic diagnostics were performed to measure equivalence ratios in methane-air premixed flames. A partial least-squares regression (PLS-R)-based multivariate sensing methodology was investigated. It was found that the equivalence ratios predicted with the PLS-R-based multivariate calibration model matched with the experimentally measured equivalence ratios within 7 %. A comparative study was performed for equivalence ratios measurement in atmospheric premixed methane-air flames with ungated LIBS and chemiluminescence spectroscopy. It was reported that LIBS-based calibration, which carries spectroscopic information from a "point-like-volume," provides better predictions of equivalence ratios compared to chemiluminescence-based calibration, which is essentially a "line-of-sight" measurement.

Application of Partial Least Squares (PLS) Regression to Determine Landscape-Scale Aquatic Resource Vulnerability in the Ozark Mountains

EPA Science Inventory

Partial least squares (PLS) analysis offers a number of advantages over the more traditionally used regression analyses applied in landscape ecology to study the associations among constituents of surface water and landscapes. Common data problems in ecological studies include: s...

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

Real time flaw detection and characterization in tube through partial least squares and SVR: Application to eddy current testing

NASA Astrophysics Data System (ADS)

Ahmed, Shamim; Miorelli, Roberto; Calmon, Pierre; Anselmi, Nicola; Salucci, Marco

2018-04-01

This paper describes Learning-By-Examples (LBE) technique for performing quasi real time flaw localization and characterization within a conductive tube based on Eddy Current Testing (ECT) signals. Within the framework of LBE, the combination of full-factorial (i.e., GRID) sampling and Partial Least Squares (PLS) feature extraction (i.e., GRID-PLS) techniques are applied for generating a suitable training set in offine phase. Support Vector Regression (SVR) is utilized for model development and inversion during offine and online phases, respectively. The performance and robustness of the proposed GIRD-PLS/SVR strategy on noisy test set is evaluated and compared with standard GRID/SVR approach.

Partial least squares analysis and mixture design for the study of the influence of composition variables on lipidic nanoparticle characteristics.

PubMed

Malzert-Fréon, A; Hennequin, D; Rault, S

2010-11-01

Lipidic nanoparticles (NP), formulated from a phase inversion temperature process, have been studied with chemometric techniques to emphasize the influence of the four major components (Solutol®, Labrasol®, Labrafac®, water) on their average diameter and their distribution in size. Typically, these NP present a monodisperse size lower than 200 nm, as determined by dynamic light scattering measurements. From the application of the partial least squares (PLS) regression technique to the experimental data collected during definition of the feasibility zone, it was established that NP present a core-shell structure where Labrasol® is well encapsulated and contributes to the structuring of the NP. Even if this solubility enhancer is regarded as a pure surfactant in the literature, it appears that the oil moieties of this macrogolglyceride mixture significantly influence its properties. Furthermore, results have shown that PLS technique can be also used for predictions of sizes for given relative proportions of components and it was established that from a mixture design, the quantitative mixture composition to use in order to reach a targeted size and a targeted polydispersity index (PDI) can be easily predicted. Hence, statistical models can be a useful tool to control and optimize the characteristics in size of NP. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Portable Linear Sled (PLS) for biomedical research

NASA Technical Reports Server (NTRS)

Vallotton, Will; Matsuhiro, Dennis; Wynn, Tom; Temple, John

1993-01-01

The PLS is a portable linear motion generating device conceived by researchers at Ames Research Center's Vestibular Research Facility and designed by engineers at Ames for the study of motion sickness in space. It is an extremely smooth apparatus, powered by linear motors and suspended on air bearings which ride on precision ground ceramic ways.

Determination of propranolol hydrochloride in pharmaceutical preparations using near infrared spectrometry with fiber optic probe and multivariate calibration methods.

PubMed

Marques Junior, Jucelino Medeiros; Muller, Aline Lima Hermes; Foletto, Edson Luiz; da Costa, Adilson Ben; Bizzi, Cezar Augusto; Irineu Muller, Edson

2015-01-01

A method for determination of propranolol hydrochloride in pharmaceutical preparation using near infrared spectrometry with fiber optic probe (FTNIR/PROBE) and combined with chemometric methods was developed. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). The treatments based on the mean centered data and multiplicative scatter correction (MSC) were selected for models construction. A root mean square error of prediction (RMSEP) of 8.2 mg g(-1) was achieved using siPLS (s2i20PLS) algorithm with spectra divided into 20 intervals and combination of 2 intervals (8501 to 8801 and 5201 to 5501 cm(-1)). Results obtained by the proposed method were compared with those using the pharmacopoeia reference method and significant difference was not observed. Therefore, proposed method allowed a fast, precise, and accurate determination of propranolol hydrochloride in pharmaceutical preparations. Furthermore, it is possible to carry out on-line analysis of this active principle in pharmaceutical formulations with use of fiber optic probe.

Graphite Based Electrode for ECG Monitoring: Evaluation under Freshwater and Saltwater Conditions.

PubMed

Thap, Tharoeun; Yoon, Kwon-Ha; Lee, Jinseok

2016-04-15

We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP) electrode. In order to assess the qualities of the PLS and PLP electrodes, we compared their performance with that of a commercial Ag/AgCl electrode, under a total of seven different conditions: dry, freshwater immersion with/without movement, post-freshwater wet condition, saltwater immersion with/without movement, and post-saltwater wet condition. In both dry and post-freshwater wet conditions, all ECG-recorded PQRST waves were clearly discernible, with all types of electrodes, Ag/AgCl, PLS, and PLP. On the other hand, under the freshwater- and saltwater-immersion conditions with/without movement, as well as post-saltwater wet conditions, we found that the proposed PLS and PLP electrodes provided better ECG waveform quality, with significant statistical differences compared with the quality provided by Ag/AgCl electrodes.

Near-infrared reflectance spectroscopy predicts protein, starch, and seed weight in intact seeds of common bean ( Phaseolus vulgaris L.).

PubMed

Hacisalihoglu, Gokhan; Larbi, Bismark; Settles, A Mark

2010-01-27

The objective of this study was to explore the potential of near-infrared reflectance (NIR) spectroscopy to determine individual seed composition in common bean ( Phaseolus vulgaris L.). NIR spectra and analytical measurements of seed weight, protein, and starch were collected from 267 individual bean seeds representing 91 diverse genotypes. Partial least-squares (PLS) regression models were developed with 61 bean accessions randomly assigned to a calibration data set and 30 accessions assigned to an external validation set. Protein gave the most accurate PLS regression, with the external validation set having a standard error of prediction (SEP) = 1.6%. PLS regressions for seed weight and starch had sufficient accuracy for seed sorting applications, with SEP = 41.2 mg and 4.9%, respectively. Seed color had a clear effect on the NIR spectra, with black beans having a distinct spectral type. Seed coat color did not impact the accuracy of PLS predictions. This research demonstrates that NIR is a promising technique for simultaneous sorting of multiple seed traits in single bean seeds with no sample preparation.

Partial least squares density modeling (PLS-DM) - a new class-modeling strategy applied to the authentication of olives in brine by near-infrared spectroscopy.

PubMed

Oliveri, Paolo; López, M Isabel; Casolino, M Chiara; Ruisánchez, Itziar; Callao, M Pilar; Medini, Luca; Lanteri, Silvia

2014-12-03

A new class-modeling method, referred to as partial least squares density modeling (PLS-DM), is presented. The method is based on partial least squares (PLS), using a distance-based sample density measurement as the response variable. Potential function probability density is subsequently calculated on PLS scores and used, jointly with residual Q statistics, to develop efficient class models. The influence of adjustable model parameters on the resulting performances has been critically studied by means of cross-validation and application of the Pareto optimality criterion. The method has been applied to verify the authenticity of olives in brine from cultivar Taggiasca, based on near-infrared (NIR) spectra recorded on homogenized solid samples. Two independent test sets were used for model validation. The final optimal model was characterized by high efficiency and equilibrate balance between sensitivity and specificity values, if compared with those obtained by application of well-established class-modeling methods, such as soft independent modeling of class analogy (SIMCA) and unequal dispersed classes (UNEQ). Copyright © 2014 Elsevier B.V. All rights reserved.

Prediction of olive oil sensory descriptors using instrumental data fusion and partial least squares (PLS) regression.

PubMed

Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

2016-08-01

Headspace-Mass Spectrometry (HS-MS), Fourier Transform Mid-Infrared spectroscopy (FT-MIR) and UV-Visible spectrophotometry (UV-vis) instrumental responses have been combined to predict virgin olive oil sensory descriptors. 343 olive oil samples analyzed during four consecutive harvests (2010-2014) were used to build multivariate calibration models using partial least squares (PLS) regression. The reference values of the sensory attributes were provided by expert assessors from an official taste panel. The instrumental data were modeled individually and also using data fusion approaches. The use of fused data with both low- and mid-level of abstraction improved PLS predictions for all the olive oil descriptors. The best PLS models were obtained for two positive attributes (fruity and bitter) and two defective descriptors (fusty and musty), all of them using data fusion of MS and MIR spectral fingerprints. Although good predictions were not obtained for some sensory descriptors, the results are encouraging, specially considering that the legal categorization of virgin olive oils only requires the determination of fruity and defective descriptors. Copyright © 2016 Elsevier B.V. All rights reserved.

A two-helix motif positions the active site of lysophosphatidic acid acyltransferase for catalysis within the membrane bilayer

PubMed Central

Robertson, Rosanna M.; Yao, Jiangwei; Gajewski, Stefan; Kumar, Gyanendra; Martin, Erik W.; Rock, Charles O.; White, Stephen W.

2017-01-01

Phosphatidic acid is the central intermediate in membrane phospholipid synthesis and is generated by two acyltransferases in a pathway conserved in all life forms. The second step in this pathway is catalyzed by 1-acyl-sn-glycero-3-phosphate acyltransferase, called PlsC in bacteria. The crystal structure of PlsC from Thermotoga maritima reveals an unusual hydrophobic/aromatic N-terminal two-helix motif linked to an acyltransferase αβ domain that contains the catalytic HX4D motif. PlsC dictates the acyl chain composition of the 2-position of phospholipids, and the acyl chain selectivity ‘ruler’ is an appropriately placed and closed hydrophobic tunnel. This was confirmed by site-directed mutagenesis and membrane composition analysis of Escherichia coli cells expressing the mutated proteins. MD simulations reveal that the two-helix motif represents a novel substructure that firmly anchors the protein to one leaflet of the membrane. This binding mode allows the PlsC active site to acylate lysophospholipids within the membrane bilayer using soluble acyl donors. PMID:28714993

Nondestructive evaluation of soluble solid content in strawberry by near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Wang, Xiu; Peng, Yankun

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R2 c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R2 p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R2 c = 0.9590 in the calibration set; and RMSEP = 0.2892, R2 p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Kinetic microplate bioassays for relative potency of antibiotics improved by partial Least Square (PLS) regression.

PubMed

Francisco, Fabiane Lacerda; Saviano, Alessandro Morais; Almeida, Túlia de Souza Botelho; Lourenço, Felipe Rebello

2016-05-01

Microbiological assays are widely used to estimate the relative potencies of antibiotics in order to guarantee the efficacy, safety, and quality of drug products. Despite of the advantages of turbidimetric bioassays when compared to other methods, it has limitations concerning the linearity and range of the dose-response curve determination. Here, we proposed to use partial least squares (PLS) regression to solve these limitations and to improve the prediction of relative potencies of antibiotics. Kinetic-reading microplate turbidimetric bioassays for apramacyin and vancomycin were performed using Escherichia coli (ATCC 8739) and Bacillus subtilis (ATCC 6633), respectively. Microbial growths were measured as absorbance up to 180 and 300min for apramycin and vancomycin turbidimetric bioassays, respectively. Conventional dose-response curves (absorbances or area under the microbial growth curve vs. log of antibiotic concentration) showed significant regression, however there were significant deviation of linearity. Thus, they could not be used for relative potency estimations. PLS regression allowed us to construct a predictive model for estimating the relative potencies of apramycin and vancomycin without over-fitting and it improved the linear range of turbidimetric bioassay. In addition, PLS regression provided predictions of relative potencies equivalent to those obtained from agar diffusion official methods. Therefore, we conclude that PLS regression may be used to estimate the relative potencies of antibiotics with significant advantages when compared to conventional dose-response curve determination. Copyright © 2016 Elsevier B.V. All rights reserved.

ε-Poly-L-lysine peptide chain length regulated by the linkers connecting the transmembrane domains of ε-Poly-L-lysine synthetase.

PubMed

Hamano, Yoshimitsu; Kito, Naoko; Kita, Akihiro; Imokawa, Yuuki; Yamanaka, Kazuya; Maruyama, Chitose; Katano, Hajime

2014-08-01

ε-Poly-l-lysine (ε-PL), consisting of 25 to 35 l-lysine residues with linkages between the α-carboxyl groups and ε-amino groups, is produced by Streptomyces albulus NBRC14147. ε-PL synthetase (Pls) is a membrane protein with six transmembrane domains (TM1 to TM6) as well as both an adenylation domain and a thiolation domain, characteristic of the nonribosomal peptide synthetases. Pls directly generates ε-PL chain length diversity (25- to 35-mer), but the processes that control the chain length of ε-PL during the polymerization reaction are still not fully understood. Here, we report on the identification of Pls amino acid residues involved in the regulation of the ε-PL chain length. From approximately 12,000 variants generated by random mutagenesis, we found 8 Pls variants that produced shorter chains of ε-PL. These variants have one or more mutations in two linker regions connecting the TM1 and TM2 domains and the TM3 and TM4 domains. In the Pls catalytic mechanism, the growing chain of ε-PL is not tethered to the enzyme, implying that the enzyme must hold the growing chain until the polymerization reaction is complete. Our findings reveal that the linker regions are important contributors to grasp the growing chain of ε-PL. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Development of a direct in-matrix extraction (DIME) protocol for MALDI-TOF-MS detection of glycated phospholipids in heat-treated food samples.

PubMed

Calvano, Cosima D; De Ceglie, Cristina; Zambonin, Carlo G

2014-09-01

In foodstuffs, one of the main factors inducing modifications in phospholipids (PLs) structure is the heat treatment. Among PLs, only phosphatidylethanolamines and phosphatidylserines, due to their free amino group, can be involved in Maillard reaction and can form adducts with reducing sugars, besides other by-products called advanced glycation end-products. To date, glycated lipid products are less characterized in comparison to proteins. The aim of this work was to develop a novel, rapid and sensitive extraction protocol for the detection and characterization of modified PLs (glycated and oxidized) by means of matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). At first, to investigate the formation of glycated and/or short chain by-products in different classes of PLs, representative standards were heated with or without sugar (lactose or glucose) and subjected to traditional lipid extraction methods as Bligh and Dyer and to the novel direct in matrix extraction (DIME) using 1,8-bis(dimethylamino)naphthalene as preconcentrating matrix. MALDI-MS analysis in negative ion mode allowed detecting glycation and oxidation products both on fatty acid and glucose moieties. Then, the procedure was successfully applied to different heat-treated and powdered samples (milk powders, pasteurized milk, ultra-high-temperature milk and soy flour) for the detection of modified PLs in complex foods. The currently developed DIME protocol could be a powerful tool for understanding lipid glycation also in biological samples. Copyright © 2014 John Wiley & Sons, Ltd.

Diagnosis of small pulmonary lesions by transbronchial lung biopsy with radial endobronchial ultrasound and virtual bronchoscopic navigation versus CT-guided transthoracic needle biopsy: A systematic review and meta-analysis

PubMed Central

Han, Yeji; Kim, Hyun Jung; Kong, Kyoung Ae; Kim, Soo Jung; Lee, Su Hwan; Ryu, Yon Ju; Lee, Jin Hwa; Kim, Yookyoung; Shim, Sung Shine

2018-01-01

Background Advances in bronchoscopy and CT-guided lung biopsy have improved the evaluation of small pulmonary lesions (PLs), leading to an increase in preoperative histological diagnosis. We aimed to evaluate the efficacy and safety of transbronchial lung biopsy using radial endobronchial ultrasound and virtual bronchoscopic navigation (TBLB-rEBUS&VBN) and CT-guided transthoracic needle biopsy (CT-TNB) for tissue diagnosis of small PLs. Methods A systematic search was performed in five electronic databases, including MEDLINE, EMBASE, Cochrane Library Central Register of Controlled Trials, Web of Science, and Scopus, for relevant studies in May 2016; the selected articles were assessed using meta-analysis. The articles were limited to those published after 2000 that studied small PLs ≤ 3 cm in diameter. Results From 7345 records, 9 articles on the bronchoscopic (BR) approach and 15 articles on the percutaneous (PC) approach were selected. The pooled diagnostic yield was 75% (95% confidence interval [CI], 69–80) using the BR approach and 93% (95% CI, 90–96) using the PC approach. For PLs ≤ 2 cm, the PC approach (pooled diagnostic yield: 92%, 95% CI: 88–95) was superior to the BR approach (66%, 95% CI: 55–76). However, for PLs > 2 cm but ≤ 3 cm, the diagnostic yield using the BR approach was improved to 81% (95% CI, 75–85). Complications of pneumothorax and hemorrhage were rare with the BR approach but common with the PC approach. Conclusions CT-TNB was superior to TBLB-rEBUS&VBN for the evaluation of small PLs. However, for lesions greater than 2 cm, the BR approach may be considered considering its diagnostic yield of over 80% and the low risk of procedure-related complications. PMID:29357388

At-line determination of pharmaceuticals small molecule's blending end point using chemometric modeling combined with Fourier transform near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tewari, Jagdish; Strong, Richard; Boulas, Pierre

2017-02-01

This article summarizes the development and validation of a Fourier transform near infrared spectroscopy (FT-NIR) method for the rapid at-line prediction of active pharmaceutical ingredient (API) in a powder blend to optimize small molecule formulations. The method was used to determine the blend uniformity end-point for a pharmaceutical solid dosage formulation containing a range of API concentrations. A set of calibration spectra from samples with concentrations ranging from 1% to 15% of API (w/w) were collected at-line from 4000 to 12,500 cm- 1. The ability of the FT-NIR method to predict API concentration in the blend samples was validated against a reference high performance liquid chromatography (HPLC) method. The prediction efficiency of four different types of multivariate data modeling methods such as partial least-squares 1 (PLS1), partial least-squares 2 (PLS2), principal component regression (PCR) and artificial neural network (ANN), were compared using relevant multivariate figures of merit. The prediction ability of the regression models were cross validated against results generated with the reference HPLC method. PLS1 and ANN showed excellent and superior prediction abilities when compared to PLS2 and PCR. Based upon these results and because of its decreased complexity compared to ANN, PLS1 was selected as the best chemometric method to predict blend uniformity at-line. The FT-NIR measurement and the associated chemometric analysis were implemented in the production environment for rapid at-line determination of the end-point of the small molecule blending operation. FIGURE 1: Correlation coefficient vs Rank plot FIGURE 2: FT-NIR spectra of different steps of Blend and final blend FIGURE 3: Predictions ability of PCR FIGURE 4: Blend uniformity predication ability of PLS2 FIGURE 5: Prediction efficiency of blend uniformity using ANN FIGURE 6: Comparison of prediction efficiency of chemometric models TABLE 1: Order of Addition for Blending Steps

Resting multilayer 2D speckle-tracking TTE for detection of ischemic segments confirmed by invasive FFR part-2, using post-systolic-strain-index and time from aortic-valve-closure to regional peak longitudinal-strain.

PubMed

Ozawa, Koya; Funabashi, Nobusada; Nishi, Takeshi; Takahara, Masayuki; Fujimoto, Yoshihide; Kamata, Tomoko; Kobayashi, Yoshio

2016-08-15

This study evaluated the post-systolic strain index (PSI), and the time interval between aortic valve closure (AVC) and regional peak longitudinal strain (PLS), measured by transthoracic echocardiography (TTE), for detection of left ventricular (LV) myocardial ischemic segments confirmed by invasive fractional flow reserve (FFR). 39 stable patients (32 males; 65.8±11.9years) with 46 coronary arteries at ≥50% stenosis on invasive coronary angiography underwent 2D speckle tracking TTE (Vivid E9, GE Healthcare) and invasive FFR measurements. PSI, AVC and regional PLS in each LV segment were calculated. FFR ≤0.80 was detected in 27 LV segments. There were no significant differences between segments supplied by FFR ≤0.80 and FFR >0.80 vessels in either PSI or the time interval between AVC and regional PLS. To identify LV segments±FFR ≤0.80, the receiver operator characteristic (ROC) curves for PSI, and the time interval between AVC and regional PLS had areas under the curve (AUC) values of 0.58 and 0.57, respectively, with best cut-off points of 12% (sensitivity 70.4%, specificity 57.9%) and 88ms (sensitivity 70.4%, specificity 52.6%), respectively, but the AUCs were not statistically significant. In stable coronary artery disease patients with ≥50% coronary artery stenosis, measurement of PSI, and the time interval between AVC and regional PLS, on resting TTE, enabled the identification of LV segments with FFR ≤0.80 using each appropriate threshold for PSI, and the time interval between AVC and regional PLS, with reasonable diagnostic accuracy. However, the AUC values were not statistically significant. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Mentalizing in schizophrenia: A multivariate functional MRI study.

PubMed

Martin, Andrew K; Dzafic, Ilvana; Robinson, Gail A; Reutens, David; Mowry, Bryan

2016-12-01

Schizophrenia is associated with mentalizing deficits that impact on social functioning and quality of life. Recently, schizophrenia has been conceptualized as a disorder of neural dysconnectivity and network level analyses offers a means of understanding the underlying deficits leading to mentalizing difficulty. Using an established mentalizing task (The Triangles Task), functional magnetic resonance images (fMRI) were acquired from 19 patients with schizophrenia and 17 age- and sex-matched healthy controls (HCs). Participants were required to watch short animations of two triangles interacting with each other with the interactions either random (no interaction), physical (patterned movement), or mental (intentional movement). Task-based Partial Least Squares (PLS) was used to analyze activation differences and commonalities between the three conditions and the two groups. Seed-based PLS was used to assess functional connectivity with peaks identified in the task-based PLS. Behavioural PLS was then performed using the accuracy from the mental conditions. Patients with schizophrenia performed worse on the mentalizing condition compared to HCs. Task-based PLS revealed one significant latent variable (LV) that explained 42.9% of the variance in the task, with theLV separating the mental condition from the physical and random conditions in patients with schizophrenia, but only the mental from physical in healthy controls. The mental animations were associated with increased modulation of the inferior frontal gyri bilaterally, left superior temporal gyrus, right postcentral gyrus, and left caudate nucleus. The physical/random animations were associated with increased modulation of the right medial frontal gyrus and left superior frontal gyrus. Seed-based PLS identified increased functional connectivity with the left inferior frontal gyrus (liFG) and caudate nucleus in patients with schizophrenia, during the mental and physical interactions, with functional connectivity with the liFG associated with increased performance on the mental animations. The results suggest that mentalizing deficits in schizophrenia may arise due to inefficient social brain networks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of Genetic Algorithm (GA) Assisted Partial Least Square (PLS) Analysis on Trilinear and Non-trilinear Fluorescence Data Sets to Quantify the Fluorophores in Multifluorophoric Mixtures: Improving Quantification Accuracy of Fluorimetric Estimations of Dilute Aqueous Mixtures.

PubMed

Kumar, Keshav

2018-03-01

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.

Sub-Model Partial Least Squares for Improved Accuracy in Quantitative Laser Induced Breakdown Spectroscopy

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Clegg, S. M.; Frydenvang, J.

2015-12-01

One of the primary challenges faced by the ChemCam instrument on the Curiosity Mars rover is developing a regression model that can accurately predict the composition of the wide range of target types encountered (basalts, calcium sulfate, feldspar, oxides, etc.). The original calibration used 69 rock standards to train a partial least squares (PLS) model for each major element. By expanding the suite of calibration samples to >400 targets spanning a wider range of compositions, the accuracy of the model was improved, but some targets with "extreme" compositions (e.g. pure minerals) were still poorly predicted. We have therefore developed a simple method, referred to as "submodel PLS", to improve the performance of PLS across a wide range of target compositions. In addition to generating a "full" (0-100 wt.%) PLS model for the element of interest, we also generate several overlapping submodels (e.g. for SiO2, we generate "low" (0-50 wt.%), "mid" (30-70 wt.%), and "high" (60-100 wt.%) models). The submodels are generally more accurate than the "full" model for samples within their range because they are able to adjust for matrix effects that are specific to that range. To predict the composition of an unknown target, we first predict the composition with the submodels and the "full" model. Then, based on the predicted composition from the "full" model, the appropriate submodel prediction can be used (e.g. if the full model predicts a low composition, use the "low" model result, which is likely to be more accurate). For samples with "full" predictions that occur in a region of overlap between submodels, the submodel predictions are "blended" using a simple linear weighted sum. The submodel PLS method shows improvements in most of the major elements predicted by ChemCam and reduces the occurrence of negative predictions for low wt.% targets. Submodel PLS is currently being used in conjunction with ICA regression for the major element compositions of ChemCam data.

Quantitative analysis of glycated albumin in serum based on ATR-FTIR spectrum combined with SiPLS and SVM.

PubMed

Li, Yuanpeng; Li, Fucui; Yang, Xinhao; Guo, Liu; Huang, Furong; Chen, Zhenqiang; Chen, Xingdan; Zheng, Shifu

2018-08-05

A rapid quantitative analysis model for determining the glycated albumin (GA) content based on Attenuated total reflectance (ATR)-Fourier transform infrared spectroscopy (FTIR) combining with linear SiPLS and nonlinear SVM has been developed. Firstly, the real GA content in human serum was determined by GA enzymatic method, meanwhile, the ATR-FTIR spectra of serum samples from the population of health examination were obtained. The spectral data of the whole spectra mid-infrared region (4000-600 cm -1 ) and GA's characteristic region (1800-800 cm -1 ) were used as the research object of quantitative analysis. Secondly, several preprocessing steps including first derivative, second derivative, variable standardization and spectral normalization, were performed. Lastly, quantitative analysis regression models were established by using SiPLS and SVM respectively. The SiPLS modeling results are as follows: root mean square error of cross validation (RMSECV T ) = 0.523 g/L, calibration coefficient (R C ) = 0.937, Root Mean Square Error of Prediction (RMSEP T ) = 0.787 g/L, and prediction coefficient (R P ) = 0.938. The SVM modeling results are as follows: RMSECV T  = 0.0048 g/L, R C  = 0.998, RMSEP T  = 0.442 g/L, and R p  = 0.916. The results indicated that the model performance was improved significantly after preprocessing and optimization of characteristic regions. While modeling performance of nonlinear SVM was considerably better than that of linear SiPLS. Hence, the quantitative analysis model for GA in human serum based on ATR-FTIR combined with SiPLS and SVM is effective. And it does not need sample preprocessing while being characterized by simple operations and high time efficiency, providing a rapid and accurate method for GA content determination. Copyright © 2018 Elsevier B.V. All rights reserved.

Exploitable Lipids and Fatty Acids in the Invasive Oyster Crassostrea gigas on the French Atlantic Coast

PubMed Central

Dagorn, Flore; Couzinet-Mossion, Aurélie; Kendel, Melha; Beninger, Peter G.; Rabesaotra, Vony; Barnathan, Gilles; Wielgosz-Collin, Gaëtane

2016-01-01

Economic exploitation is one means to offset the cost of controlling invasive species, such as the introduced Pacific oyster (Crassostrea gigas Thunberg) on the French Atlantic coast. Total lipid and phospholipid (PL) fatty acids (FAs) and sterols were examined in an invasive population of C. gigas in Bourgneuf Bay, France, over four successive seasons, with a view to identify possible sources of exploitable substances. The total lipid level (% dry weight) varied from 7.1% (winter) to 8.6% (spring). Of this, PLs accounted for 28.1% (spring) to 50.4% (winter). Phosphatidylcholine was the dominant PL throughout the year (up to 74% of total PLs in winter). Plasmalogens were identified throughout the year as a series of eleven dimethylacetals (DMAs) with chain lengths between C16 and C20 (up to 14.5% of PL FAs + DMAs in winter). Thirty-seven FAs were identified in the PL FAs. Eicosapentaenoic acid (20:5n-3 EPA/7.53% to 14.5%) and docosahexaenoic acid (22:6n-3 DHA/5.51% to 9.5%) were the dominant polyunsaturated FAs in all seasons. Two non-methylene-interrupted dienoic (NMID) FAs were identified in all seasons: 7,13-docosadienoic and 7,15-docosadienoic acids, the latter being present at relatively high levels (up to 9.6% in winter). Twenty free sterols were identified, including cholesterol at 29.9% of the sterol mixture and about 33% of phytosterols. C. gigas tissues thus contained exploitable lipids for health benefits or as a potential source of high-quality commercial lecithin. PMID:27231919

Measurement of Vibrated Bulk Density of Coke Particle Blends Using Image Texture Analysis

NASA Astrophysics Data System (ADS)

Azari, Kamran; Bogoya-Forero, Wilinthon; Duchesne, Carl; Tessier, Jayson

2017-09-01

A rapid and nondestructive machine vision sensor was developed for predicting the vibrated bulk density (VBD) of petroleum coke particles based on image texture analysis. It could be used for making corrective adjustments to a paste plant operation to reduce green anode variability (e.g., changes in binder demand). Wavelet texture analysis (WTA) and gray level co-occurrence matrix (GLCM) algorithms were used jointly for extracting the surface textural features of coke aggregates from images. These were correlated with the VBD using partial least-squares (PLS) regression. Coke samples of several sizes and from different sources were used to test the sensor. Variations in the coke surface texture introduced by coke size and source allowed for making good predictions of the VBD of individual coke samples and mixtures of them (blends involving two sources and different sizes). Promising results were also obtained for coke blends collected from an industrial-baked carbon anode manufacturer.

[Evaluation of Sugar Content of Huanghua Pear on Trees by Visible/Near Infrared Spectroscopy].

PubMed

Liu, Hui-jun; Ying, Yi-bin

2015-11-01

A method of ambient light correction was proposed to evaluate the sugar content of Huanghua pears on tree by visible/near infrared diffuse reflectance spectroscopy (Vis/NIRS). Due to strong interference of ambient light, it was difficult to collect the efficient spectral of pears on tree. In the field, covering the fruits with a bag blocking ambient light can get better results, but the efficiency is fairly low, the instrument corrections of dark and reference spectra may help to reduce the error of the model, however, the interference of the ambient light cannot be eliminated effectively. In order to reduce the effect of ambient light, a shutter was attached to the front of probe. When opening shutter, the spot spectrum were obtained, on which instrument light and ambient light acted at the same time. While closing shutter, background spectra were obtained, on which only ambient light acted, then the ambient light spectra was subtracted from spot spectra. Prediction models were built using data on tree (before and after ambient light correction) and after harvesting by partial least square (PLS). The results of the correlation coefficient (R) are 0.1, 0.69, 0.924; the root mean square error of prediction (SEP) are 0. 89°Brix, 0.42°Brix, 0.27°Brix; ratio of standard deviation (SD) to SEP (RPD) are 0.79, 1.69, 2.58, respectively. The results indicate that, method of background correction used in the experiment can reduce the effect of ambient lighting on spectral acquisition of Huanghua pears in field, efficiently. This method can be used to collect the visible/near infrared spectrum of fruits in field, and may give full play to visible/near-infrared spectroscopy in preharvest management and maturity testing of fruits in the field.

Performance Analysis of Physical Layer Security of Opportunistic Scheduling in Multiuser Multirelay Cooperative Networks

PubMed Central

Shim, Kyusung; Do, Nhu Tri; An, Beongku

2017-01-01

In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks. PMID:28212286

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Code of Federal Regulations, 2010 CFR

2010-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Code of Federal Regulations, 2014 CFR

2014-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Code of Federal Regulations, 2011 CFR

2011-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Code of Federal Regulations, 2013 CFR

2013-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

45 CFR 303.15 - Agreements to use the Federal Parent Locator Service (PLS) in parental kidnapping and child...

Code of Federal Regulations, 2012 CFR

2012-10-01

... Service (PLS) in parental kidnapping and child custody or visitation cases. 303.15 Section 303.15 Public... parental kidnapping and child custody or visitation cases. (a) Definitions. The following definitions apply... responsibilities require access in connection with child custody and parental kidnapping cases; (ii) Store the...

Using the Preschool Language Scale, Fourth Edition to Characterize Language in Preschoolers with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Volden, Joanne; Smith, Isabel M.; Szatmari, Peter; Bryson, Susan; Fombonne, Eric; Mirenda, Pat; Roberts, Wendy; Vaillancourt, Tracy; Waddell, Charlotte; Zwaigenbaum, Lonnie; Georgiades, Stelios; Duku, Eric; Thompson, Ann

2011-01-01

Purpose: The Preschool Language Scale, Fourth Edition (PLS-4; Zimmerman, Steiner, & Pond, 2002) was used to examine syntactic and semantic language skills in preschool children with autism spectrum disorders (ASD) to determine its suitability for use with this population. We expected that PLS-4 performance would be better in more…

Reconstructing vegetation past: Pre-Euro-American vegetation for the midwest driftless area, USA

Treesearch

Monika E. Shea; Lisa A. Schulte; Brian J. Palik

2014-01-01

Historical reference conditions provide important context for creating ecological restoration and management plans. The U.S. 19th Century Public Land Survey (PLS) records provide extensive ecological information for constructing such reference conditions. We used PLS records to reconstruct pre-Euro-American tree species cover class and vegetation structure types for...

Terahertz time-domain attenuated total reflection spectroscopy applied to the rapid discrimination of the botanical origin of honeys

NASA Astrophysics Data System (ADS)

Liu, Wen; Zhang, Yuying; Yang, Si; Han, Donghai

2018-05-01

A new technique to identify the floral resources of honeys is demanded. Terahertz time-domain attenuated total reflection spectroscopy combined with chemometrics methods was applied to discriminate different categorizes (Medlar honey, Vitex honey, and Acacia honey). Principal component analysis (PCA), cluster analysis (CA) and partial least squares-discriminant analysis (PLS-DA) have been used to find information of the botanical origins of honeys. Spectral range also was discussed to increase the precision of PLS-DA model. The accuracy of 88.46% for validation set was obtained, using PLS-DA model in 0.5-1.5 THz. This work indicated terahertz time-domain attenuated total reflection spectroscopy was an available approach to evaluate the quality of honey rapidly.

A photosensitive liposome with NIR light triggered doxorubicin release as a combined photodynamic-chemo therapy system.

PubMed

Li, Qingpo; Li, Wei; Di, Haixiao; Luo, Lihua; Zhu, Chunqi; Yang, Jie; Yin, Xiaoyi; Yin, Hang; Gao, Jianqing; Du, Yongzhong; You, Jian

2018-05-10

The targeted drug delivery with the help of nanocarriers and the controlled drug release at the lesion sites are the most effective ways to enhance therapeutic efficacy and reduce side effects. Here, we built a light sensitive liposome (Her2-I&D-LSL) which was formed by a special phospholipid (PLsPC) and a hydrophobically modified photosensitizer (ICG-ODA). DOX was employed as the therapeutic drug, encapsulating in the internal phase of the liposome whose surface was modified by Her2 antibodies for recognizing tumor cells with high Her2 receptor expression. Mediated by NIR light, Her2-I&D-LSL was proved to generate sufficient ROS to realize PDT, which then triggered the release of DOX for combined chemotherapy. The ROS generation and DOX release were verified to be strictly controlled by NIR light and the proportion of ICG-ODA. Thanks to the mediation of Her2 receptor, the specific DOX release and the combination of PDT-chemotherapy triggered by NIR light, Her2-I&D-LSL showed a significant accumulation in MCF7 and SKOV3 tumors, thus leading to the strongest tumor growth inhibition effect compared to PDT alone (I-LSL) or chemotherapy alone (D-LSL). Her2-I&D-LSL also possessed a great biocompatibility due to the targeted treatment, holding promise for future cancer therapy in clinic. Copyright © 2018 Elsevier B.V. All rights reserved.

Testing methods to produce landscape-scale presettlement vegetation maps from the U.S. public land survey records

USGS Publications Warehouse

Manies, K.L.; Mladenoff, D.J.

2000-01-01

The U.S. Public Land Survey (PLS) notebooks are one of the best records of the pre-European settlement landscape and are widely used to recreate presettlement vegetation maps. The purpose of this study was to evaluate the relative ability of several interpolation techniques to map this vegetation, as sampled by the PLS surveyors, at the landscape level. Field data from Sylvania Wilderness Area, MI (U.S.A.), sampled at the same scale as the PLS data, were used for this test. Sylvania is comprised of a forested landscape similar to that present during presettlement times. Data were analyzed using two Arc/Info interpolation processes and indicator kriging. The resulting maps were compared to a 'correct' map of Sylvania, which was classified from aerial photographs. We found that while the interpolation methods used accurately estimated the relative forest composition of the landscape and the order of dominance of different vegetation types, they were unable to accurately estimate the actual area occupied by each vegetation type. Nor were any of the methods we tested able to recreate the landscape patterns found in the natural landscape. The most likely cause for these inabilities is the scale at which the field data (and hence the PLS data) were recorded. Therefore, these interpolation methods should not be used with the PLS data to recreate pre-European settlement vegetation at small scales (e.g., less than several townships or areas < 104 ha). Recommendations are given for ways to increase the accuracy of these vegetation maps.

Simultaneous determination of the impurity and radial tensile strength of reduced glutathione tablets by a high selective NIR-PLS method.

PubMed

Li, Juan; Jiang, Yue; Fan, Qi; Chen, Yang; Wu, Ruanqi

2014-05-05

This paper establishes a high-throughput and high selective method to determine the impurity named oxidized glutathione (GSSG) and radial tensile strength (RTS) of reduced glutathione (GSH) tablets based on near infrared (NIR) spectroscopy and partial least squares (PLS). In order to build and evaluate the calibration models, the NIR diffuse reflectance spectra (DRS) and transmittance spectra (TS) for 330 GSH tablets were accurately measured by using the optimized parameter values. For analyzing GSSG or RTS of GSH tablets, the NIR-DRS or NIR-TS were selected, subdivided reasonably into calibration and prediction sets, and processed appropriately with chemometric techniques. After selecting spectral sub-ranges and neglecting spectrum outliers, the PLS calibration models were built and the factor numbers were optimized. Then, the PLS models were evaluated by the root mean square errors of calibration (RMSEC), cross-validation (RMSECV) and prediction (RMSEP), and by the correlation coefficients of calibration (R(c)) and prediction (R(p)). The results indicate that the proposed models have good performances. It is thus clear that the NIR-PLS can simultaneously, selectively, nondestructively and rapidly analyze the GSSG and RTS of GSH tablets, although the contents of GSSG impurity were quite low while those of GSH active pharmaceutical ingredient (API) quite high. This strategy can be an important complement to the common NIR methods used in the on-line analysis of API in pharmaceutical preparations. And this work expands the NIR applications in the high-throughput and extraordinarily selective analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Articular Joint Lubricants during Osteoarthritis and Rheumatoid Arthritis Display Altered Levels and Molecular Species

PubMed Central

Liebisch, Gerhard; Zhang, Ruiyan; Siebert, Hans-Christian; Wilhelm, Jochen; Kaesser, Ulrich; Dettmeyer, Reinhard B.; Klein, Heiko; Ishaque, Bernd; Rickert, Markus; Schmitz, Gerd; Schmidt, Tannin A.; Steinmeyer, Juergen

2015-01-01

Background Hyaluronic acid (HA), lubricin, and phospholipid species (PLs) contribute independently or together to the boundary lubrication of articular joints that is provided by synovial fluid (SF). Our study is the first reporting quantitative data about the molecular weight (MW) forms of HA, lubricin, and PLs in SF from cohorts of healthy donors, patients with early (eOA)- or late (lOA)-stage osteoarthritis (OA), and patients with active rheumatoid arthritis (RA). Methods We used human SF from unaffected controls, eOA, lOA, and RA. HA and lubricin levels were measured by enzyme-linked immunosorbent assay. PLs was quantified by electrospray ionization tandem mass spectrometry. Fatty acids (FAs) were analyzed by gas chromatography, coupled with mass spectrometry. The MW distribution of HA was determined by agarose gel electrophoresis. Results Compared with control SF, the concentrations of HA and lubricin were lower in OA and RA SF, whereas those of PLs were higher in OA and RA SF. Moreover, the MW distribution of HA shifted toward the lower ranges in OA and RA SF. We noted distinct alterations between cohorts in the relative distribution of PLs and the degree of FA saturation and chain lengths of FAs. Conclusions The levels, composition, and MW distribution of all currently known lubricants in SF—HA, lubricin, PLs—vary with joint disease and stage of OA. Our study is the first delivering a comprehensive view about all joint lubricants during health and widespread joint diseases. Thus, we provide the framework to develop new optimal compounded lubricants to reduce joint destruction. PMID:25933137

Linked functional network abnormalities during intrinsic and extrinsic activity in schizophrenia as revealed by a data-fusion approach.

PubMed

Hashimoto, Ryu-Ichiro; Itahashi, Takashi; Okada, Rieko; Hasegawa, Sayaka; Tani, Masayuki; Kato, Nobumasa; Mimura, Masaru

2018-01-01

Abnormalities in functional brain networks in schizophrenia have been studied by examining intrinsic and extrinsic brain activity under various experimental paradigms. However, the identified patterns of abnormal functional connectivity (FC) vary depending on the adopted paradigms. Thus, it is unclear whether and how these patterns are inter-related. In order to assess relationships between abnormal patterns of FC during intrinsic activity and those during extrinsic activity, we adopted a data-fusion approach and applied partial least square (PLS) analyses to FC datasets from 25 patients with chronic schizophrenia and 25 age- and sex-matched normal controls. For the input to the PLS analyses, we generated a pair of FC maps during the resting state (REST) and the auditory deviance response (ADR) from each participant using the common seed region in the left middle temporal gyrus, which is a focus of activity associated with auditory verbal hallucinations (AVHs). PLS correlation (PLS-C) analysis revealed that patients with schizophrenia have significantly lower loadings of a component containing positive FCs in default-mode network regions during REST and a component containing positive FCs in the auditory and attention-related networks during ADR. Specifically, loadings of the REST component were significantly correlated with the severities of positive symptoms and AVH in patients with schizophrenia. The co-occurrence of such altered FC patterns during REST and ADR was replicated using PLS regression, wherein FC patterns during REST are modeled to predict patterns during ADR. These findings provide an integrative understanding of altered FCs during intrinsic and extrinsic activity underlying core schizophrenia symptoms.

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy.

PubMed

Payne, Courtney E; Wolfrum, Edward J

2015-01-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. We present individual model statistics to demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. It is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.

Mid-infrared and near-infrared spectroscopy for rapid detection of Gardeniae Fructus by a liquid-liquid extraction process.

PubMed

Tao, Lingyan; Lin, Zhonglin; Chen, Jiashan; Wu, Yongjiang; Liu, Xuesong

2017-10-25

Gardeniae Fructus is widely used in the pharmaceutical industry, and many studies have confirmed its medical and economic value. In this study, samples collected from different liquid-liquid extraction batches of Gardeniae Fructus were detected by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. Seven analytes, neochlorogenic acid (5-CQA), cryptochlorogenic acid (4-CQA), chlorogenic acid (3-CQA), geniposidic acid (GEA), deacetyl-asperulosidic acid methyl ester (DAAME), genipin-gentiobioside (GGB), and gardenoside (GA), were chosen as quality property indexes of Gardeniae Fructus. The two kinds of spectra were each used to build models by single partial least squares (PLS). Additionally, both spectral data were combined and modeled by multiblock PLS. For single spectroscopy modeling results, NIR had a better prediction for high-concentration analytes (3-CQA, DAAME, GGB, and GA) whereas MIR performed better for low-concentration analytes (5-CQA, 4-CQA, and GEA). The multiblock methodology was found to be better compared to single spectroscopy models for all seven analytes. Specifically, the coefficients of determination (R 2 ) of the NIR, MIR, and multiblock PLS calibration models of all seven components were higher than 0.95. Relative standard errors of prediction (RSEP) were all less than 7%, except for models of GGB, which were 10.36%, 13.24%, and 8.15% for the NIR-PLS, MIR-PLS, and multiblock models, respectively. These results indicate that MIR and NIR spectrographic techniques could provide a new choice for quality control in industrial production of Gardeniae Fructus. Copyright © 2017 Elsevier B.V. All rights reserved.

PERIAPICAL LESIONS OF THE JAWS: A REVIEW OF 104 CASES IN IBADAN

PubMed Central

Akinyamoju, AO; Gbadebo, SO; Adeyemi, BF

2014-01-01

Background: Periapical lesions (PLs) occur as a result of pulpal inflammation and may rarely be seen in the absence of pulpal diseases. They are the most common pathological lesions affecting the alveolar bone. Objective: This study aims to describe the clinicopathological features of PLs of the jaws with emphasis on the two most common types. Methods: Histopathology records of PLs diagnosed from January 1990 to December 2012 at the Department of Oral Pathology, University College Hospital Ibadan, were examined and categorized into periapical cysts (PCs); periapical granuloma (PGs) and others. Clinical data and histopathological features of these PLs were reviewed and analyzed. Results: One hundred and four lesions met the criteria for this study and consisted of PGs with 71 (68.3%) cases and PCs with 31 (29.8%) cases and one case each of apical scar and pleomorphic adenoma. Age range of cases was 9 to 80 years (mean=35.6 ± 15.8years) with a peak at age group of 20-29 years. Females were more frequently affected with 51.9% of cases. PLs were most frequently diagnosed in the anterior maxillary region with 58 (56.9%) cases, while the most frequently involved tooth was the left maxillary central incisor with 23 (22.1%) cases. Conclusion: Findings in this study are consistent with those of previous studies. It is important for all periapical pathological specimens to be submitted for histological examination to establish an accurate diagnosis and aid in the identification of sinister lesions that may present in the Periradicular region of teeth. PMID:25960702

Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad

2013-05-01

Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicollinearity limit the successful application of the technology. The aim of this study was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n = 230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user's and producer's accuracies ranging from 50% to 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n = 78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user's and producer's accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.

Draft genome sequence of Xylella fastidiosa pear leaf scorch strain in Taiwan

USDA-ARS?s Scientific Manuscript database

The draft genome sequence of Xylella fastidiosa pear leaf scorch strain (PLS229) isolated from pear cultivar Hengshan (Pyrus pyrifolia) in Taiwan is reported. The bacterium has a genome size of 2,733,013 bp with a G+C content of 53.1%. The PLS229 strain genome was annotated to have 3,259 open readin...

Intra-isolate genome variation in arbuscular mycorrhizal fungi persists in the transcriptome.

PubMed

Boon, E; Zimmerman, E; Lang, B F; Hijri, M

2010-07-01

Arbuscular mycorrhizal fungi (AMF) are heterokaryotes with an unusual genetic makeup. Substantial genetic variation occurs among nuclei within a single mycelium or isolate. AMF reproduce through spores that contain varying fractions of this heterogeneous population of nuclei. It is not clear whether this genetic variation on the genome level actually contributes to the AMF phenotype. To investigate the extent to which polymorphisms in nuclear genes are transcribed, we analysed the intra-isolate genomic and cDNA sequence variation of two genes, the large subunit ribosomal RNA (LSU rDNA) of Glomus sp. DAOM-197198 (previously known as G. intraradices) and the POL1-like sequence (PLS) of Glomus etunicatum. For both genes, we find high sequence variation at the genome and transcriptome level. Reconstruction of LSU rDNA secondary structure shows that all variants are functional. Patterns of PLS sequence polymorphism indicate that there is one functional gene copy, PLS2, which is preferentially transcribed, and one gene copy, PLS1, which is a pseudogene. This is the first study that investigates AMF intra-isolate variation at the transcriptome level. In conclusion, it is possible that, in AMF, multiple nuclear genomes contribute to a single phenotype.

Free variable selection QSPR study to predict 19F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods

NASA Astrophysics Data System (ADS)

Goudarzi, Nasser

2016-04-01

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the 19F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the 19F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

Feasibility of using a miniature NIR spectrometer to measure volumic mass during alcoholic fermentation.

PubMed

Fernández-Novales, Juan; López, María-Isabel; González-Caballero, Virginia; Ramírez, Pilar; Sánchez, María-Teresa

2011-06-01

Volumic mass-a key component of must quality control tests during alcoholic fermentation-is of great interest to the winemaking industry. Transmitance near-infrared (NIR) spectra of 124 must samples over the range of 200-1,100-nm were obtained using a miniature spectrometer. The performance of this instrument to predict volumic mass was evaluated using partial least squares (PLS) regression and multiple linear regression (MLR). The validation statistics coefficient of determination (r(2)) and the standard error of prediction (SEP) were r(2) = 0.98, n = 31 and r(2) = 0.96, n = 31, and SEP = 5.85 and 7.49 g/dm(3) for PLS and MLR equations developed to fit reference data for volumic mass and spectral data. Comparison of results from MLR and PLS demonstrates that a MLR model with six significant wavelengths (P < 0.05) fit volumic mass data to transmittance (1/T) data slightly worse than a more sophisticated PLS model using the full scanning range. The results suggest that NIR spectroscopy is a suitable technique for predicting volumic mass during alcoholic fermentation, and that a low-cost NIR instrument can be used for this purpose.

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis.

PubMed

Ouyang, Qin; Zhao, Jiewen; Pan, Wenxiu; Chen, Quansheng

2016-01-01

A portable and low-cost spectral analytical system was developed and used to monitor real-time process parameters, i.e. total sugar content (TSC), alcohol content (AC) and pH during rice wine fermentation. Various partial least square (PLS) algorithms were implemented to construct models. The performance of a model was evaluated by the correlation coefficient (Rp) and the root mean square error (RMSEP) in the prediction set. Among the models used, the synergy interval PLS (Si-PLS) was found to be superior. The optimal performance by the Si-PLS model for the TSC was Rp = 0.8694, RMSEP = 0.438; the AC was Rp = 0.8097, RMSEP = 0.617; and the pH was Rp = 0.9039, RMSEP = 0.0805. The stability and reliability of the system, as well as the optimal models, were verified using coefficients of variation, most of which were found to be less than 5%. The results suggest this portable system is a promising tool that could be used as an alternative method for rapid monitoring of process parameters during rice wine fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of principal component regression and artificial neural network in FT-NIR soluble solids content determination of intact pear fruit

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Fu, Xiaping; Lu, Huishan

2005-11-01

The artificial neural networks (ANNs) have been used successfully in applications such as pattern recognition, image processing, automation and control. However, majority of today's applications of ANNs is back-propagate feed-forward ANN (BP-ANN). In this paper, back-propagation artificial neural networks (BP-ANN) were applied for modeling soluble solid content (SSC) of intact pear from their Fourier transform near infrared (FT-NIR) spectra. One hundred and sixty-four pear samples were used to build the calibration models and evaluate the models predictive ability. The results are compared to the classical calibration approaches, i.e. principal component regression (PCR), partial least squares (PLS) and non-linear PLS (NPLS). The effects of the optimal methods of training parameters on the prediction model were also investigated. BP-ANN combine with principle component regression (PCR) resulted always better than the classical PCR, PLS and Weight-PLS methods, from the point of view of the predictive ability. Based on the results, it can be concluded that FT-NIR spectroscopy and BP-ANN models can be properly employed for rapid and nondestructive determination of fruit internal quality.

Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

PubMed

de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna

2014-07-01

This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

Sensory Profile and Consumer Acceptability of Prebiotic White Chocolate with Sucrose Substitutes and the Addition of Goji Berry (Lycium barbarum).

PubMed

Morais Ferreira, Janaína Madruga; Azevedo, Bruna Marcacini; Luccas, Valdecir; Bolini, Helena Maria André

2017-03-01

Functional food is a product containing nutrients that provide health benefits beyond basic nutrition. The objective of the present study was to evaluate the descriptive sensory profile and consumers' acceptance of functional (prebiotic) white chocolates with and without the addition of an antioxidant source (goji berry [GB]) and sucrose replacement. The descriptive sensory profile was determined by quantitative descriptive analysis (QDA) with trained assessors (n = 12), and the acceptance test was performed with 120 consumers. The correlation of descriptive and hedonic data was determined by partial least squares (PLS). The results of QDA indicated that GB reduces the perception of most aroma and flavor attributes, and enhances the bitter taste, bitter aftertaste, astringency, and most of the texture attributes. The consumers' acceptance of the chocolates was positive for all sensory characteristics, with acceptance scores above 6 on a 9-point scale. According to the PLS regression analysis, the descriptors cream color and cocoa butter flavor contributed positively to the acceptance of functional white chocolates. Therefore, prebiotic white chocolate with or without the addition of GB is innovative and can attract consumers, due to its functional properties, being a promising alternative for the food industry. © 2017 Institute of Food Technologists®.

Determination of total phenolic compounds in compost by infrared spectroscopy.

PubMed

Cascant, M M; Sisouane, M; Tahiri, S; Krati, M El; Cervera, M L; Garrigues, S; de la Guardia, M

2016-06-01

Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction (Rpred(2)) and residual predictive deviation (RPD) being obtained for this latter values of 5.83 and 8.26 for MIR and NIR, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Final design report of a personnel launch system and a family of heavy lift launch vehicles

NASA Technical Reports Server (NTRS)

Tupa, James; Merritt, Debbie; Riha, David; Burton, Lee; Kubinski, Russell; Drake, Kerry; Mann, Darrin; Turner, Ken

1991-01-01

The objective was to design both a Personnel Launch System (PLS) and a family of Heavy Lift Launch Vehicles (FHLLVs) that provide low cost and efficient operation in missions not suited for the Shuttle. The PLS vehicle is designed primarily for space station crew rotation and emergency crew return. The final design of the PLS vehicle and its interior is given. The mission of the FHLLVs is to place large, massive payloads into Earth orbit with payload flexibility being considered foremost in the design. The final design of three launch vehicles was found to yield a payload capacity range from 20 to 200 mt. These designs include the use of multistaged, high thrust liquid engines mounted on the core stages of the rocket.

In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors.

PubMed

Whelan, Jessica; Craven, Stephen; Glennon, Brian

2012-01-01

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed-batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off-line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Rapid Elemental Analysis and Provenance Study of Blumea balsamifera DC Using Laser-Induced Breakdown Spectroscopy

PubMed Central

Liu, Xiaona; Zhang, Qiao; Wu, Zhisheng; Shi, Xinyuan; Zhao, Na; Qiao, Yanjiang

2015-01-01

Laser-induced breakdown spectroscopy (LIBS) was applied to perform a rapid elemental analysis and provenance study of Blumea balsamifera DC. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were implemented to exploit the multivariate nature of the LIBS data. Scores and loadings of computed principal components visually illustrated the differing spectral data. The PLS-DA algorithm showed good classification performance. The PLS-DA model using complete spectra as input variables had similar discrimination performance to using selected spectral lines as input variables. The down-selection of spectral lines was specifically focused on the major elements of B. balsamifera samples. Results indicated that LIBS could be used to rapidly analyze elements and to perform provenance study of B. balsamifera. PMID:25558999

Preparation and characterization of Bi-doped TiO{sub 2} and its solar photocatalytic activity for the degradation of isoproturon herbicide

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

Reddy, Police Anil Kumar; Srinivas, Basavaraju; Kala, Pruthu

Highlights: {yields} Visible active Bi-TiO{sub 2} photocatalyst preparation and thorough charaterization. {yields} Bi-TiO{sub 2} shows high activity for isoproturon degradation under solar light irradiation. {yields} The spectral response of TiO{sub 2} shifts from UV to visible light region by Bi doping. {yields} Bi{sup 3+{delta}+} species are playing a vital role in minimizing e{sup -}/h{sup +} recombination. -- Abstract: Bi-doped TiO{sub 2} catalyst was prepared by sol-gel method and was characterized by thermo gravimetric analysis (TGA), X-ray diffraction spectra (XRD), X-ray photo electronic spectroscopy (XPS), UV-Vis diffused reflectance spectra (DRS), photoluminescence spectra (PLS), transmission electron microscopy (TEM), energy dispersive analysis ofmore » X-rays (EDAX) and BET surface area. The photocatalytic activity of the catalysts were evaluated for the degradation of isoproturon herbicide under solar light irradiation. The UV-Visible DRS of Bi-doped TiO{sub 2} showed red shift in optical absorption. The presence of Bi{sup 3+{delta}+} species are playing a vital role in minimizing the electron hole recombination resulting higher activity compared to bare TiO{sub 2}.« less

Demographics and clinical characteristics of primary lateral sclerosis: case series and a review of literature.

PubMed

Ramanathan, Ramnath Santosh; Rana, Sandeep

2018-02-01

Primary lateral sclerosis (PLS) is a form of motor neuron disease involving only upper motor neurons. In some patients presenting as PLS, the disease progresses to involve lower motor neurons and thereby converting to amyotrophic lateral sclerosis (ALS). However, pure forms of PLS do exist. Our aim was to study epidemiological and clinical characteristics of pure PLS patients treated at our neuromuscular clinic. We retrospectively reviewed 15 patients from July 2011 to October 2014 with PLS treated at the neuromuscular disorder clinic at our hospital. Data collection included patient demographics, age and site of onset, duration of symptoms and duration of follow-up. We also studied clinical features such as bulbar involvement; pseudobulbar affect; depression; spasms/pain; bladder involvement; diagnostic work up, in other words, MRI; brain/electromyography findings; clinical course, namely years to wheelchair; and need for gastrostomy tube requirement baclofen pump placement. We also tried to find a correlation between PLS and environmental factors such as urban/suburban/rural living, consumption of well water, socioeconomic status/occupation and history of trauma. Male-to-female ratio was 1:2, mean age at onset of symptoms was 58.6 years, with the oldest patient being an 84-year-old female at the time of onset of symptoms. Mean duration of follow-up was 51 months. Mean duration of symptoms was 77.4 months. About eight (53%) patients presented with bulbar symptoms in the form of spastic speech and dysphagia, pseudobulbar affect, developed depression and had bladder involvement. Seven (47%) patients presented with symmetric spasticity in the extremities. A third of the patients required baclofen for spasticity and a third required gastrostomy tube placement for dysphagia. None of them had abnormal neuroimaging or electrodiagnostic testing. Only one patient had history of trauma. About half of the patients were from lower socioeconomic status as well as middle class. One of the patients had consumed well water during younger years and three (20%) patients lived in the rural area. Though on review of literature there is no clear consensus about the existence of PLS as a distinct disease entity, we believe that there are rare cases of motor neuron disease with progressive upper motor neuron symptoms that throughout their course never convert to ALS. Our series highlights the demographic and clinical features of these patients and underscores the longer survival of these patients when compared with ALS.

Quantitative transmission Raman spectroscopy of pharmaceutical tablets and capsules.

PubMed

Johansson, Jonas; Sparén, Anders; Svensson, Olof; Folestad, Staffan; Claybourn, Mike

2007-11-01

Quantitative analysis of pharmaceutical formulations using the new approach of transmission Raman spectroscopy has been investigated. For comparison, measurements were also made in conventional backscatter mode. The experimental setup consisted of a Raman probe-based spectrometer with 785 nm excitation for measurements in backscatter mode. In transmission mode the same system was used to detect the Raman scattered light, while an external diode laser of the same type was used as excitation source. Quantitative partial least squares models were developed for both measurement modes. The results for tablets show that the prediction error for an independent test set was lower for the transmission measurements with a relative root mean square error of about 2.2% as compared with 2.9% for the backscatter mode. Furthermore, the models were simpler in the transmission case, for which only a single partial least squares (PLS) component was required to explain the variation. The main reason for the improvement using the transmission mode is a more representative sampling of the tablets compared with the backscatter mode. Capsules containing mixtures of pharmaceutical powders were also assessed by transmission only. The quantitative results for the capsules' contents were good, with a prediction error of 3.6% w/w for an independent test set. The advantage of transmission Raman over backscatter Raman spectroscopy has been demonstrated for quantitative analysis of pharmaceutical formulations, and the prospects for reliable, lean calibrations for pharmaceutical analysis is discussed.

Another Look at the Influence of Maternal Education on Preschoolers' Performance on Two Norm-Referenced Measures

ERIC Educational Resources Information Center

Abel, Alyson D.; Schuele, C. Melanie; Arndt, Karen Barako; Lee, Marvin W.; Blankenship, Kathryn Guillot

2017-01-01

The purpose of this study was (a) to describe the performance of preschool children from families with college-educated mothers on two norm-referenced measures, the Preschool Language Scale-4 (PLS-4) and Peabody Picture Vocabulary Tests-III (PPVT-III), and (b) to compare the findings with Qi and colleagues who reported PLS and PPVT scores for…

Using multiple calibration sets to improve the quantitative accuracy of partial least squares (PLS) regression on open-path fourier transform infrared (OP/FT-IR) spectra of ammonia over wide concentration ranges

USDA-ARS?s Scientific Manuscript database

A technique of using multiple calibration sets in partial least squares regression (PLS) was proposed to improve the quantitative determination of ammonia from open-path Fourier transform infrared spectra. The spectra were measured near animal farms, and the path-integrated concentration of ammonia...

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes

PubMed Central

2012-01-01

Background Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Methods Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. Results After modification by dropping two indicators that showed poor measures in the measurement models’ quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of ‘transparency’, ‘participation’, ‘scientific rigour’ and ‘reasonableness’. Conclusions The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies. PMID:22856325

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes.

PubMed

Fischer, Katharina E

2012-08-02

Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. After modification by dropping two indicators that showed poor measures in the measurement models' quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of 'transparency', 'participation', 'scientific rigour' and 'reasonableness'. The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies.

Variation of metabolic profiles in developing maize kernels up- and down-regulated for the hda101 gene

PubMed Central

Castro, Cecilia; Motto, Mario; Rossi, Vincenzo; Manetti, Cesare

2008-01-01

To shed light on the specific contribution of HDA101 in modulating metabolic pathways in the maize seed, changes in the metabolic profiles of kernels obtained from hda101 mutant plants have been investigated by a metabonomic approach. Dynamic properties of chromatin folding can be mediated by enzymes that modify DNA and histones. The enzymes responsible for the steady-state of histone acetylation are histone acetyltransferase and histone deacetylase (HDA). Therefore, it is interesting to evaluate the effects of up- and down-regulation of a Rpd-3 type HDA on the development of maize seeds in terms of metabolic changes. This has been reached by analysing nuclear magnetic resonance spectra by different chemometrician approaches, such as Orthogonal Projection to Latent Structure-Discriminant Analysis, Parallel Factors Analysis, and Multi-way Partial Least Squares-Discriminant Analysis (N-PLS-DA). In particular, the latter approaches were chosen because they explicitly take time into account, organizing data into a set of slices that refer to different steps of the developing process. The results show the good discriminating capabilities of the N-PLS-DA approach, even if the number of samples ought be increased to obtain better predictive capabilities. However, using this approach, it was possible to show differences in the accumulation of metabolites during development and to highlight the changes occuring in the modified seeds. In particular, the results confirm the role of this gene in cell cycle control. PMID:18836140

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy

DOE PAGES

Payne, Courtney E.; Wolfrum, Edward J.

2015-03-12

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. Here are the results: We present individual model statistics tomore » demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. In conclusion, it is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.« less

Imaging Findings Associated with Cognitive Performance in Primary Lateral Sclerosis and Amyotrophic Lateral Sclerosis

PubMed Central

Meoded, Avner; Kwan, Justin Y.; Peters, Tracy L.; Huey, Edward D.; Danielian, Laura E.; Wiggs, Edythe; Morrissette, Arthur; Wu, Tianxia; Russell, James W.; Bayat, Elham; Grafman, Jordan; Floeter, Mary Kay

2013-01-01

Introduction Executive dysfunction occurs in many patients with amyotrophic lateral sclerosis (ALS), but it has not been well studied in primary lateral sclerosis (PLS). The aims of this study were to (1) compare cognitive function in PLS to that in ALS patients, (2) explore the relationship between performance on specific cognitive tests and diffusion tensor imaging (DTI) metrics of white matter tracts and gray matter volumes, and (3) compare DTI metrics in patients with and without cognitive and behavioral changes. Methods The Delis-Kaplan Executive Function System (D-KEFS), the Mattis Dementia Rating Scale (DRS-2), and other behavior and mood scales were administered to 25 ALS patients and 25 PLS patients. Seventeen of the PLS patients, 13 of the ALS patients, and 17 healthy controls underwent structural magnetic resonance imaging (MRI) and DTI. Atlas-based analysis using MRI Studio software was used to measure fractional anisotropy, and axial and radial diffusivity of selected white matter tracts. Voxel-based morphometry was used to assess gray matter volumes. The relationship between diffusion properties of selected association and commissural white matter and performance on executive function and memory tests was explored using a linear regression model. Results More ALS than PLS patients had abnormal scores on the DRS-2. DRS-2 and D-KEFS scores were related to DTI metrics in several long association tracts and the callosum. Reduced gray matter volumes in motor and perirolandic areas were not associated with cognitive scores. Conclusion The changes in diffusion metrics of white matter long association tracts suggest that the loss of integrity of the networks connecting fronto-temporal areas to parietal and occipital areas contributes to cognitive impairment. PMID:24052798

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy

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

Payne, Courtney E.; Wolfrum, Edward J.

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. Here are the results: We present individual model statistics tomore » demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. In conclusion, it is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.« less

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

PubMed Central

Afendi, Farit M.; Ono, Naoaki; Nakamura, Yukiko; Nakamura, Kensuke; Darusman, Latifah K.; Kibinge, Nelson; Morita, Aki Hirai; Tanaka, Ken; Horai, Hisayuki; Altaf-Ul-Amin, Md.; Kanaya, Shigehiko

2013-01-01

Molecular biological data has rapidly increased with the recent progress of the Omics fields, e.g., genomics, transcriptomics, proteomics and metabolomics that necessitates the development of databases and methods for efficient storage, retrieval, integration and analysis of massive data. The present study reviews the usage of KNApSAcK Family DB in metabolomics and related area, discusses several statistical methods for handling multivariate data and shows their application on Indonesian blended herbal medicines (Jamu) as a case study. Exploration using Biplot reveals many plants are rarely utilized while some plants are highly utilized toward specific efficacy. Furthermore, the ingredients of Jamu formulas are modeled using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. This model produces 71.6% correct classification in predicting efficacy. Permutation test then is used to determine plants that serve as main ingredients in Jamu formula by evaluating the significance of the PLS-DA coefficients. Next, in order to explain the role of plants that serve as main ingredients in Jamu medicines, information of pharmacological activity of the plants is added to the predictor block. Then N-PLS-DA model, multiway version of PLS-DA, is utilized to handle the three-dimensional array of the predictor block. The resulting N-PLS-DA model reveals that the effects of some pharmacological activities are specific for certain efficacy and the other activities are diverse toward many efficacies. Mathematical modeling introduced in the present study can be utilized in global analysis of big data targeting to reveal the underlying biology. PMID:24688691

Three-way analysis of the UPLC-PDA dataset for the multicomponent quantitation of hydrochlorothiazide and olmesartan medoxomil in tablets by parallel factor analysis and three-way partial least squares.

PubMed

Dinç, Erdal; Ertekin, Zehra Ceren

2016-01-01

An application of parallel factor analysis (PARAFAC) and three-way partial least squares (3W-PLS1) regression models to ultra-performance liquid chromatography-photodiode array detection (UPLC-PDA) data with co-eluted peaks in the same wavelength and time regions was described for the multicomponent quantitation of hydrochlorothiazide (HCT) and olmesartan medoxomil (OLM) in tablets. Three-way dataset of HCT and OLM in their binary mixtures containing telmisartan (IS) as an internal standard was recorded with a UPLC-PDA instrument. Firstly, the PARAFAC algorithm was applied for the decomposition of three-way UPLC-PDA data into the chromatographic, spectral and concentration profiles to quantify the concerned compounds. Secondly, 3W-PLS1 approach was subjected to the decomposition of a tensor consisting of three-way UPLC-PDA data into a set of triads to build 3W-PLS1 regression for the analysis of the same compounds in samples. For the proposed three-way analysis methods in the regression and prediction steps, the applicability and validity of PARAFAC and 3W-PLS1 models were checked by analyzing the synthetic mixture samples, inter-day and intra-day samples, and standard addition samples containing HCT and OLM. Two different three-way analysis methods, PARAFAC and 3W-PLS1, were successfully applied to the quantitative estimation of the solid dosage form containing HCT and OLM. Regression and prediction results provided from three-way analysis were compared with those obtained by traditional UPLC method. Copyright © 2015 Elsevier B.V. All rights reserved.

Study on feasibility of determination of glucosamine content of fermentation process using a micro NIR spectrometer.

PubMed

Sun, Zhongyu; Li, Can; Li, Lian; Nie, Lei; Dong, Qin; Li, Danyang; Gao, Lingling; Zang, Hengchang

2018-08-05

N-acetyl-d-glucosamine (GlcNAc) is a microbial fermentation product, and NIR spectroscopy is an effective process analytical technology (PAT) tool in detecting the key quality attribute: the GlcNAc content. Meanwhile, the design of NIR spectrometers is under the trend of miniaturization, portability and low-cost nowadays. The aim of this study was to explore a portable micro NIR spectrometer with the fermentation process. First, FT-NIR spectrometer and Micro-NIR 1700 spectrometer were compared with simulated fermentation process solutions. The R c 2 , R p 2 , RMSECV and RMSEP of the optimal FT-NIR and Micro-NIR 1700 models were 0.999, 0.999, 3.226 g/L, 1.388 g/L and 0.999, 0.999, 1.821 g/L, 0.967 g/L. Passing-Bablok regression method and paired t-test results showed there were no significant differences between the two instruments. Then the Micro-NIR 1700 was selected for the practical fermentation process, 135 samples from 10 batches were collected. Spectral pretreatment methods and variables selection methods (BiPLS, FiPLS, MWPLS and CARS-PLS) for PLS modeling were discussed. The R c 2 , R p 2 , RMSECV and RMSEP of the optimal GlcNAc content PLS model of the practical fermentation process were 0.994, 0.995, 2.792 g/L and 1.946 g/L. The results have a positive reference for application of the Micro-NIR spectrometer. To some extent, it could provide theoretical supports in guiding the microbial fermentation or the further assessment of bioprocess. Copyright © 2018. Published by Elsevier B.V.

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS)

NASA Astrophysics Data System (ADS)

Krepper, Gabriela; Romeo, Florencia; Fernandes, David Douglas de Sousa; Diniz, Paulo Henrique Gonçalves Dias; de Araújo, Mário César Ugulino; Di Nezio, María Susana; Pistonesi, Marcelo Fabián; Centurión, María Eugenia

2018-01-01

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12 mg kg- 1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (w w- 1). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59 mg kg- 1, REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis.

The use of chemometrics to study multifunctional indole alkaloids from Psychotria nemorosa (Palicourea comb. nov.). Part II: Indication of peaks related to the inhibition of butyrylcholinesterase and monoamine oxidase-A.

PubMed

Klein-Júnior, Luiz C; Viaene, Johan; Tuenter, Emmy; Salton, Juliana; Gasper, André L; Apers, Sandra; Andries, Jan P M; Pieters, Luc; Henriques, Amélia T; Vander Heyden, Yvan

2016-09-09

Psychotria nemorosa is chemically characterized by indole alkaloids and displays significant inhibitory activity on butyrylcholinesterase (BChE) and monoamine oxidase-A (MAO-A), both enzymes related to neurodegenerative disorders. In the present study, 43 samples of P. nemorosa leaves were extracted and fractionated in accordance to previously optimized methods (see Part I). These fractions were analyzed by means of UPLC-DAD and assayed for their BChE and MAO-A inhibitory potencies. The chromatographic fingerprint data was first aligned using correlation optimized warping and Principal Component Analysis to explore the data structure was performed. Multivariate calibration techniques, namely Partial Least Squares (PLS1), PLS2 and Orthogonal Projections to Latent Structure (O-PLS1), were evaluated for modelling the activities as a function of the fingerprints. Since the best results were obtained with O-PLS1 model (RMSECV=9.3 and 3.3 for BChE and MAO-A, respectively), the regression coefficients of the model were analyzed and plotted relative to the original fingerprints. Four peaks were indicated as multifunctional compounds, with the capacity to impair both BChE and MAO-A activities. In order to confirm these results, a semi-prep HPLC technique was used and a fraction containing the four peaks was purified and evaluated in vitro. It was observed that the fraction exhibited an IC50 of 2.12μgmL(-1) for BChE and 1.07μgmL(-1) for MAO-A. These results reinforce the prediction obtained by O-PLS1 modelling. Copyright © 2016 Elsevier B.V. All rights reserved.

Immobilization of β-galactosidase from Kluyveromyces lactis onto polymeric membrane surfaces: effect of surface characteristics.

PubMed

Güleç, Hacı Ali

2013-04-01

The aim of this study was to investigate the effects of surface characteristics of plain and plasma modified cellulose acetate (CA) membranes on the immobilization yield of β-galactosidases from Kluyveromyces lactis (KLG) and its galacto-oligosaccharide (GOS) yield, respectively. Low pressure plasma treatments involving oxygen plasma activation, plasma polymerization (PlsP) of ethylenediamine (EDA) and PlsP of 2-mercaptoethanol were used to modify plain CA membrane surfaces. KLG enzyme was immobilized onto plain and oxygen plasma treated membrane surfaces by simple adsorption. Oxygen plasma activation increased the hydrophylicity of CA membrane surfaces and it improved the immobilization yield of the enzyme by 42%. KLG enzyme was also immobilized onto CA membrane surfaces through amino groups created by PlsP of EDA via covalent binding. Plasma action at 60W plasma power and 15 min. exposure time improved the amount of membrane bounded enzyme by 3.5-fold. The enrichment of the amount of amino groups via polyethyleneimine (PEI) addition enhanced this increase from 3.5-fold to 4.5-fold. Although high enzyme loading was achived (65-83%), both of the methods dramatically decreased the enzyme activity (11-12%) and GOS yield due to probably negative effects of active amino groups. KLG enzyme was more effectively immobilized onto thiolated CA membrane surface created by PlsP of 2-mercaptoethanol with high immobilization yield (70%) and especially high enzyme activity (46%). Immobilized enzymes on the CA membranes treated by PlsP were successively reutilized for 5-8 cycles at 25°C and enzymatic derivatives retained approximately 75-80% of their initial activites at the end of the reactions. Copyright © 2012 Elsevier B.V. All rights reserved.

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS).

PubMed

Krepper, Gabriela; Romeo, Florencia; Fernandes, David Douglas de Sousa; Diniz, Paulo Henrique Gonçalves Dias; de Araújo, Mário César Ugulino; Di Nezio, María Susana; Pistonesi, Marcelo Fabián; Centurión, María Eugenia

2018-01-15

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12mgkg -1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (ww -1 ). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59mgkg -1 , REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass.

PubMed

Dabros, Michal; Dennewald, Danielle; Currie, David J; Lee, Mark H; Todd, Robert W; Marison, Ian W; von Stockar, Urs

2009-02-01

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory results.

Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.

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

Teague, Melissa Christine; Teague, Melissa Christine; Rodgers, Theron

Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modelingmore » is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.« less

Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction

PubMed Central

Song, Jingwei; He, Jiaying; Zhu, Menghua; Tan, Debao; Zhang, Yu; Ye, Song; Shen, Dingtao; Zou, Pengfei

2014-01-01

A simulated annealing (SA) based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN), and partial least square support vector machine (PLS-SVM) to build a more accurate forecast model. The hybrid model was built and multistep ahead prediction ability was tested based on daily MSW generation data from Seattle, Washington, the United States. The hybrid forecast model was proved to produce more accurate and reliable results and to degrade less in longer predictions than three individual models. The average one-week step ahead prediction has been raised from 11.21% (chaotic model), 12.93% (ANN), and 12.94% (PLS-SVM) to 9.38%. Five-week average has been raised from 13.02% (chaotic model), 15.69% (ANN), and 15.92% (PLS-SVM) to 11.27%. PMID:25301508

Preschool life skills: Recent advancements and future directions.

PubMed

Fahmie, Tara A; Luczynski, Kevin C

2018-01-01

Over the past decade, researchers have replicated and extended research on the preschool life skills (PLS) program developed by Hanley, Heal, Tiger, and Ingvarsson (2007). This review summarizes recent research with respect to maximizing skill acquisition, improving generality, evaluating feasibility and acceptability, and testing predictions of the initial PLS study. For each area, we suggest directions for future research. © 2018 Society for the Experimental Analysis of Behavior.

"There Was a Lot of Learning Going on" Using a Digital Medium to Support Learning in a Professional Course for New HE Lecturers

ERIC Educational Resources Information Center

Chesney, Sarah; Marcangelo, Caroline

2010-01-01

This small scale action research study investigated the experiences of learners over two iterations as they completed a patchwork text assignment within the digital medium of a personal learning system (PLS). The aim was to investigate the extent to which using a PLS can facilitate formative and collaborative feedback to assist student learning. A…

Navy Fuel Composition and Screening Tool (FCAST) v2.8

DTIC Science & Technology

2016-05-10

allowed us to develop partial least squares (PLS) models based on gas chromatography–mass spectrometry (GC-MS) data that predict fuel properties. The...Chemometric property modeling Partial least squares PLS Compositional profiler Naval Air Systems Command Air-4.4.5 Patuxent River Naval Air Station Patuxent...Cumulative predicted residual error sum of squares DiEGME Diethylene glycol monomethyl ether FCAST Fuel Composition and Screening Tool FFP Fit for

Differential Item Functioning Analysis of the "Preschool Language Scale-4" between English-Speaking Hispanic and European American Children from Low-Income Families

ERIC Educational Resources Information Center

Qi, Cathy Huaqing; Marley, Scott C.

2009-01-01

The study examined whether item bias is present in the "Preschool Language Scale-4" (PLS-4). Participants were 440 children (3-5 years old; 86% English-speaking Hispanic and 14% European American) who were enrolled in Head Start programs. The PLS-4 items were analyzed for differential item functioning (DIF) using logistic regression and…

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

PubMed

Zhao, Jianhua; Lui, Harvey; Kalia, Sunil; Zeng, Haishan

2015-11-01

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

PubMed Central

Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

2016-01-01

Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

Dysgraphia in Patients with Primary Lateral Sclerosis: A Speech-Based Rehearsal Deficit?

PubMed Central

Zago, S.; Poletti, B.; Corbo, M.; Adobbati, L.; Silani, V.

2008-01-01

The present study aims to demonstrate that errors when writing are more common than expected in patients affected by primary lateral sclerosis (PLS) with severe dysarthria or complete mutism, independent of spasticity. Sixteen patients meeting Pringle’s et al. [34] criteria for PLS underwent standard neuropsychological tasks and evaluation of writing. We assessed writing abilities in spelling through dictation in which a set of words, non-words and short phrases were presented orally and by composing words using a set of preformed letters. Finally, a written copying task was performed with the same words. Relative to controls, PLS patients made a greater number of spelling errors in all writing conditions, but not in copy task. The error types included: omissions, transpositions, insertions and letter substitutions. These were equally distributed on the writing task and the composition of words with a set of preformed letters. This pattern of performance is consistent with a spelling impairment. The results are consistent with the concept that written production is critically dependent on the subvocal articulatory mechanism of rehearsal, perhaps at the level of retaining the sequence of graphemes in a graphemic buffer. In PLS patients a disturbance in rehearsal opportunity may affect the correct sequencing/assembly of an orthographic representation in the written process. PMID:19096141

Characterization and relative quantification of phospholipids based on methylation and stable isotopic labeling[S

PubMed Central

Cai, Tanxi; Shu, Qingbo; Liu, Peibin; Niu, Lili; Guo, Xiaojing; Ding, Xiang; Xue, Peng; Xie, Zhensheng; Wang, Jifeng; Zhu, Nali; Wu, Peng; Niu, Lili; Yang, Fuquan

2016-01-01

Phospholipids (PLs), one of the lipid categories, are not only the primary building blocks of cellular membranes, but also can be split to produce products that function as second messengers in signal transduction and play a pivotal role in numerous cellular processes, including cell growth, survival, and motility. Here, we present an integrated novel method that combines a fast and robust TMS-diazomethane-based phosphate derivatization and isotopic labeling strategy, which enables simultaneous profiling and relative quantification of PLs from biological samples. Our results showed that phosphate methylation allows fast and sensitive identification of the six major PL classes, including their lysophospholipid counterparts, under positive ionization mode. The isotopic labeling of endogenous PLs was achieved by deuterated diazomethane, which was generated through acid-catalyzed hydrogen/deuterium (H/D) exchange and methanolysis of TMS-diazomethane during the process of phosphate derivatization. The measured H/D ratios of unlabeled and labeled PLs, which were mixed in known proportions, indicated that the isotopic labeling strategy is capable of providing relative quantitation with adequate accuracy, reproducibility, and a coefficient of variation of 9.1%, on average. This novel method offers unique advantages over existing approaches and presents a powerful tool for research of PL metabolism and signaling. PMID:26733148

Noninvasive Recognition and Biomarkers of Early Allergic Asthma in Cats Using Multivariate Statistical Analysis of NMR Spectra of Exhaled Breath Condensate

PubMed Central

Fulcher, Yan G.; Fotso, Martial; Chang, Chee-Hoon; Rindt, Hans; Reinero, Carol R.

2016-01-01

Asthma is prevalent in children and cats, and needs means of noninvasive diagnosis. We sought to distinguish noninvasively the differences in 53 cats before and soon after induction of allergic asthma, using NMR spectra of exhaled breath condensate (EBC). Statistical pattern recognition was improved considerably by preprocessing the spectra with probabilistic quotient normalization and glog transformation. Classification of the 106 preprocessed spectra by principal component analysis and partial least squares with discriminant analysis (PLS-DA) appears to be impaired by variances unrelated to eosinophilic asthma. By filtering out confounding variances, orthogonal signal correction (OSC) PLS-DA greatly improved the separation of the healthy and early asthmatic states, attaining 94% specificity and 94% sensitivity in predictions. OSC enhancement of multi-level PLS-DA boosted the specificity of the prediction to 100%. OSC-PLS-DA of the normalized spectra suggest the most promising biomarkers of allergic asthma in cats to include increased acetone, metabolite(s) with overlapped NMR peaks near 5.8 ppm, and a hydroxyphenyl-containing metabolite, as well as decreased phthalate. Acetone is elevated in the EBC of 74% of the cats with early asthma. The noninvasive detection of early experimental asthma, biomarkers in EBC, and metabolic perturbation invite further investigation of the diagnostic potential in humans. PMID:27764146

Partial Least Squares for Discrimination in fMRI Data

PubMed Central

Andersen, Anders H.; Rayens, William S.; Liu, Yushu; Smith, Charles D.

2011-01-01

Multivariate methods for discrimination were used in the comparison of brain activation patterns between groups of cognitively normal women who are at either high or low Alzheimer's disease risk based on family history and apolipoprotein-E4 status. Linear discriminant analysis (LDA) was preceded by dimension reduction using either principal component analysis (PCA), partial least squares (PLS), or a new oriented partial least squares (OrPLS) method. The aim was to identify a spatial pattern of functionally connected brain regions that was differentially expressed by the risk groups and yielded optimal classification accuracy. Multivariate dimension reduction is required prior to LDA when the data contains more feature variables than there are observations on individual subjects. Whereas PCA has been commonly used to identify covariance patterns in neuroimaging data, this approach only identifies gross variability and is not capable of distinguishing among-groups from within-groups variability. PLS and OrPLS provide a more focused dimension reduction by incorporating information on class structure and therefore lead to more parsimonious models for discrimination. Performance was evaluated in terms of the cross-validated misclassification rates. The results support the potential of using fMRI as an imaging biomarker or diagnostic tool to discriminate individuals with disease or high risk. PMID:22227352

Triacylglycerol is produced from starch and polar lipids in the green alga Dunaliella tertiolecta.

PubMed

Pick, Uri; Avidan, Omri

2017-10-13

The halotolerant green alga Dunaliella tertiolecta accumulates starch and triacylglycerol (TAG) amounting to 70% and 10-15% of total cellular carbon, respectively, when exposed to nitrogen (N) deprivation. The purpose of this study was to clarify the inter-relationships between the biosynthesis of TAG, starch, and polar lipids (PLs) in this alga. Pulse labeling with [14C]bicarbonate was utilized to label starch and [14C]palmitic acid (PlA) to label lipids. Transfer of 14C into TAG was measured and used to calculate rates of synthesis. About two-thirds of the carbon in TAG originates from starch, and one-third is made de novo by direct CO2 assimilation. The level made from degradation of pre-formed PLs is estimated to be very small. Most of the de novo synthesis involves fatty acid transfer through PLs made during the first day of N deprivation. The results suggest that starch made by photosynthetic carbon assimilation at the early stages of N deprivation is utilized for synthesis of TAG. Trans-acylation from PLs is the second major contributor to TAG biosynthesis. The utilization of starch for TAG biosynthesis may have biotechnological applications to optimize TAG biosynthesis in algae. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

A multi-model fusion strategy for multivariate calibration using near and mid-infrared spectra of samples from brewing industry

NASA Astrophysics Data System (ADS)

Tan, Chao; Chen, Hui; Wang, Chao; Zhu, Wanping; Wu, Tong; Diao, Yuanbo

2013-03-01

Near and mid-infrared (NIR/MIR) spectroscopy techniques have gained great acceptance in the industry due to their multiple applications and versatility. However, a success of application often depends heavily on the construction of accurate and stable calibration models. For this purpose, a simple multi-model fusion strategy is proposed. It is actually the combination of Kohonen self-organizing map (KSOM), mutual information (MI) and partial least squares (PLSs) and therefore named as KMICPLS. It works as follows: First, the original training set is fed into a KSOM for unsupervised clustering of samples, on which a series of training subsets are constructed. Thereafter, on each of the training subsets, a MI spectrum is calculated and only the variables with higher MI values than the mean value are retained, based on which a candidate PLS model is constructed. Finally, a fixed number of PLS models are selected to produce a consensus model. Two NIR/MIR spectral datasets from brewing industry are used for experiments. The results confirms its superior performance to two reference algorithms, i.e., the conventional PLS and genetic algorithm-PLS (GAPLS). It can build more accurate and stable calibration models without increasing the complexity, and can be generalized to other NIR/MIR applications.

Towards molecular design using 2D-molecular contour maps obtained from PLS regression coefficients

NASA Astrophysics Data System (ADS)

Borges, Cleber N.; Barigye, Stephen J.; Freitas, Matheus P.

2017-12-01

The multivariate image analysis descriptors used in quantitative structure-activity relationships are direct representations of chemical structures as they are simply numerical decodifications of pixels forming the 2D chemical images. These MDs have found great utility in the modeling of diverse properties of organic molecules. Given the multicollinearity and high dimensionality of the data matrices generated with the MIA-QSAR approach, modeling techniques that involve the projection of the data space onto orthogonal components e.g. Partial Least Squares (PLS) have been generally used. However, the chemical interpretation of the PLS-based MIA-QSAR models, in terms of the structural moieties affecting the modeled bioactivity has not been straightforward. This work describes the 2D-contour maps based on the PLS regression coefficients, as a means of assessing the relevance of single MIA predictors to the response variable, and thus allowing for the structural, electronic and physicochemical interpretation of the MIA-QSAR models. A sample study to demonstrate the utility of the 2D-contour maps to design novel drug-like molecules is performed using a dataset of some anti-HIV-1 2-amino-6-arylsulfonylbenzonitriles and derivatives, and the inferences obtained are consistent with other reports in the literature. In addition, the different schemes for encoding atomic properties in molecules are discussed and evaluated.

ATR-FTIR spectroscopy for the determination of Na4EDTA in detergent aqueous solutions.

PubMed

Suárez, Leticia; García, Roberto; Riera, Francisco A; Diez, María A

2013-10-15

Fourier transform infrared spectroscopy in the attenuated total reflectance mode (ATR-FTIR) combined with partial last square (PLS) algorithms was used to design calibration and prediction models for a wide range of tetrasodium ethylenediaminetetraacetate (Na4EDTA) concentrations (0.1 to 28% w/w) in aqueous solutions. The spectra obtained using air and water as a background medium were tested for the best fit. The PLS models designed afforded a sufficient level of precision and accuracy to allow even very small amounts of Na4EDTA to be determined. A root mean square error of nearly 0.37 for the validation set was obtained. Over a concentration range below 5% w/w, the values estimated from a combination of ATR-FTIR spectroscopy and a PLS algorithm model were similar to those obtained from an HPLC analysis of NaFeEDTA complexes and subsequent detection by UV absorbance. However, the lowest detection limit for Na4EDTA concentrations afforded by this spectroscopic/chemometric method was 0.3% w/w. The PLS model was successfully used as a rapid and simple method to quantify Na4EDTA in aqueous solutions of industrial detergents as an alternative to HPLC-UV analysis which involves time-consuming dilution and complexation processes. © 2013 Elsevier B.V. All rights reserved.

Simultaneous determination of specific alpha and beta emitters by LSC-PLS in water samples.

PubMed

Fons-Castells, J; Tent-Petrus, J; Llauradó, M

2017-01-01

Liquid scintillation counting (LSC) is a commonly used technique for the determination of alpha and beta emitters. However, LSC has poor resolution and the continuous spectra for beta emitters hinder the simultaneous determination of several alpha and beta emitters from the same spectrum. In this paper, the feasibility of multivariate calibration by partial least squares (PLS) models for the determination of several alpha ( nat U, 241 Am and 226 Ra) and beta emitters ( 40 K, 60 Co, 90 Sr/ 90 Y, 134 Cs and 137 Cs) in water samples is reported. A set of alpha and beta spectra from radionuclide calibration standards were used to construct three PLS models. Experimentally mixed radionuclides and intercomparision materials were used to validate the models. The results had a maximum relative bias of 25% when all the radionuclides in the sample were included in the calibration set; otherwise the relative bias was over 100% for some radionuclides. The results obtained show that LSC-PLS is a useful approach for the simultaneous determination of alpha and beta emitters in multi-radionuclide samples. However, to obtain useful results, it is important to include all the radionuclides expected in the studied scenario in the calibration set. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simultaneous determination of vitamin B12 and its derivatives using some of multivariate calibration 1 (MVC1) techniques

NASA Astrophysics Data System (ADS)

Samadi-Maybodi, Abdolraouf; Darzi, S. K. Hassani Nejad

2008-10-01

Resolution of binary mixtures of vitamin B12, methylcobalamin and B12 coenzyme with minimum sample pre-treatment and without analyte separation has been successfully achieved by methods of partial least squares algorithm with one dependent variable (PLS1), orthogonal signal correction/partial least squares (OSC/PLS), principal component regression (PCR) and hybrid linear analysis (HLA). Data of analysis were obtained from UV-vis spectra. The UV-vis spectra of the vitamin B12, methylcobalamin and B12 coenzyme were recorded in the same spectral conditions. The method of central composite design was used in the ranges of 10-80 mg L -1 for vitamin B12 and methylcobalamin and 20-130 mg L -1 for B12 coenzyme. The models refinement procedure and validation were performed by cross-validation. The minimum root mean square error of prediction (RMSEP) was 2.26 mg L -1 for vitamin B12 with PLS1, 1.33 mg L -1 for methylcobalamin with OSC/PLS and 3.24 mg L -1 for B12 coenzyme with HLA techniques. Figures of merit such as selectivity, sensitivity, analytical sensitivity and LOD were determined for three compounds. The procedure was successfully applied to simultaneous determination of three compounds in synthetic mixtures and in a pharmaceutical formulation.

Experiments on Supervised Learning Algorithms for Text Categorization

NASA Technical Reports Server (NTRS)

Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.

2005-01-01

Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

The Sun: the Earth light source

NASA Astrophysics Data System (ADS)

Berrilli, Francesco; Giovannelli, Luca; Del Moro, Dario; Piazzesi, Roberto; Catena, Liu` Maria; Amicucci, Giordano; Vittorio, Nicola

2015-04-01

We have implemented at Department of Physics of University of Rome Tor Vergata a project called "The Sun: the Earth light source". The project obtained the official endorsement from the IAU Executive Committee Working Group for the International Year of Light. The project, specifically designed for high school students, is focused on the "scientific" study of Sun light by means of a complete acquisition system based on "on the shelf" appropriately CMOS low-cost sensor with free control s/w and self-assembled telescopes. The project (hereafter stage) plan is based on a course of two weeks (60 hours in total). The course contains 20 hours of theoretical lectures, necessary to learn basics about Sun, optics, telescopes and image sensors, and 40 hours of laboratory. During the course, scientists and astronomers share with high schools students, work activities in real research laboratories. High schools teachers are intensely involved in the project. Their role is to share activities with university teachers and realize outreach actions in the home institutions. Simultaneously, they are introduced to innovative teaching methods and the project in this way is regarded as a professional development course. Sun light analysis and Sun-Earth connection through light are the main scientific topics of this project. The laboratory section of the stage is executed in two phases (weeks): First phase aims are the realization of a keplerian telescope and low-cost acquisition system. During this week students are introduced to astronomical techniques used to safety collect and acquire solar light; Second phase aims is the realization of a low-cost instrument to analyse sunlight extracting information about the solar spectrum, solar irradiance and Sun-Earth connection. The proposed stage has been already tested in Italy reached the fifth edition in 2014. Since 2010, the project has been a cornerstone outreach program of the University of Rome Tor Vergata, the Italian Ministry of Education and the National Program for the diffusion of Scientific Degrees (Progetto Lauree Scientifiche or PLS). In the last years has been mainly aimed to underline the connections between Astronomy, Astrophysics and the new materials involved in the astronomical techniques. The Sun has always been used in the course as a key element since the final product was the production of a self-constructed solar telescope able to be used to monitor the solar activity through Wolf's number estimation. In the third edition the project has been extended to other three Universities on the Italian territory: University of l'Aquila, University of Camerino and University of Calabria. Over the years more than 80 students and 50 teachers where directly involved and more than 50 different high schools on all the national territory, reaching thousands of their students in the final dissemination part of the program. 25 telescopes are currently in use in high school institutes all-over Italy. A book describing the project has been published by Springer in 2013 (STUDENTI-RICERCATORI per cinque giorni "Stage a Tor Vergata" Editors: Liù M. Catena, Francesco Berrilli, Ivan Davoli, Paolo Prosposito, ISBN: 978-88-470-5271-0 (Online) ), the link to the book describing the project and reporting student interviews is at: http://link.springer.com/book

Online information search behaviour of physicians.

PubMed

Mikalef, Patrick; Kourouthanassis, Panos E; Pateli, Adamantia G

2017-03-01

Although doctors increasingly engage in online information seeking to complement their medical practice, little is known regarding what online information sources are used and how effective they are. Grounded on self-determination and needs theory, this study posits that doctors tend to use online information sources to fulfil their information requirements in three pre-defined areas: patient care, knowledge development and research activities. Fulfilling these information needs is argued to improve doctors' perceived medical practice competence. Performing PLS-SEM analysis on primary survey data from 303 medical doctors practicing in four major Greek hospitals, a conceptual model is empirically tested. Using authoritative online information sources was found to fulfil all types of information needs. Contrarily, using non-authoritative information sources had no significant effect. Satisfying information requirements relating to patient care and research activities enhanced doctors' perceptions about their medical practice competence. In contrast, meeting knowledge development information needs had the opposite result. Consistent with past studies, outcomes indicate that doctors tend to use non-authoritative online information sources; yet their use was found to have no significant value in fulfilling their information requirements. Authoritative online information sources are found to improve perceived medical practice competence by satisfying doctors' diverse information requirements. © 2017 Health Libraries Group.

Narrowing historical uncertainty: probabilistic classification of ambiguously identified tree species in historical forest survey data

USGS Publications Warehouse

Mladenoff, D.J.; Dahir, S.E.; Nordheim, E.V.; Schulte, L.A.; Guntenspergen, G.R.

2002-01-01

Historical data have increasingly become appreciated for insight into the past conditions of ecosystems. Uses of such data include assessing the extent of ecosystem change; deriving ecological baselines for management, restoration, and modeling; and assessing the importance of past conditions on the composition and function of current systems. One historical data set of this type is the Public Land Survey (PLS) of the United States General Land Office, which contains data on multiple tree species, sizes, and distances recorded at each survey point, located at half-mile (0.8 km) intervals on a 1-mi (1.6 km) grid. This survey method was begun in the 1790s on US federal lands extending westward from Ohio. Thus, the data have the potential of providing a view of much of the US landscape from the mid-1800s, and they have been used extensively for this purpose. However, historical data sources, such as those describing the species composition of forests, can often be limited in the detail recorded and the reliability of the data, since the information was often not originally recorded for ecological purposes. Forest trees are sometimes recorded ambiguously, using generic or obscure common names. For the PLS data of northern Wisconsin, USA, we developed a method to classify ambiguously identified tree species using logistic regression analysis, using data on trees that were clearly identified to species and a set of independent predictor variables to build the models. The models were first created on partial data sets for each species and then tested for fit against the remaining data. Validations were conducted using repeated, random subsets of the data. Model prediction accuracy ranged from 81% to 96% in differentiating congeneric species among oak, pine, ash, maple, birch, and elm. Major predictor variables were tree size, associated species, landscape classes indicative of soil type, and spatial location within the study region. Results help to clarify ambiguities formerly present in maps of historic ecosystems for the region and can be applied to PLS datasets elsewhere, as well as other sources of ambiguous historical data. Mapping the newly classified data with ecological land units provides additional information on the distribution, abundance, and associations of tree species, as well as their relationships to environmental gradients before the industrial period, and clarifies the identities of species formerly mapped only to genus. We offer some caveats on the appropriate use of data derived in this way, as well as describing their potential.

pLS010 plasmid vector

DOEpatents

Lacks, Sanford A.; Balganesh, Tanjore S.

1988-01-01

Disclosed is recombinant plasmid pLS101, consisting essentially of a 2.0 Kb malM gene fragment ligated to a 4.4 Kb T.sub.c r DNA fragment, which is particularly useful for transforming Gram-positive bacteria. This plasmid contains at least four restriction sites suitable for inserting exogeneous gene sequences. Also disclosed is a method for plasmid isolation by penicillin selection, as well as processes for enrichment of recombinant plasmids in Gram-positive bacterial systems.

Synergistic antioxidant activity of milk sphingomyeline and its sphingoid base with α-tocopherol on fish oil triacylglycerol.

PubMed

Shimajiri, Junki; Shiota, Makoto; Hosokawa, Masashi; Miyashita, Kazuo

2013-08-21

The effects of milk phospholipids (PLs), sphingolipids (SLs), and their sphingoid backbone on the oxidation of fish oil triacylglycerol (TAG) were examined with or without α-tocopherol. All compounds had little effect on the TAG oxidation in the absence of α-tocopherol. On the other hand, they could act synergistically with α-tocopherol. The highest synergistic activity was shown by sphingoid bases, followed by sphingomyelin (SPM) and other amine-containing PLs and SLs. This result showed that the synergistic activity increased with an increasing concentration of amine group of PLs, SLs, or sphingoid bases in the reaction mixture. The comparison of changes in α-tocopherol content in fish oil TAG and tricaprylin suggested that antioxidant compounds would be formed from the amine group and the lipid oxidation products in a mild oxidation condition controlled by α-tocopherol.

Multivariate analysis of standoff laser-induced breakdown spectroscopy spectra for classification of explosive-containing residues

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

De Lucia, Frank C. Jr.; Gottfried, Jennifer L.; Munson, Chase A.

2008-11-01

A technique being evaluated for standoff explosives detection is laser-induced breakdown spectroscopy (LIBS). LIBS is a real-time sensor technology that uses components that can be configured into a ruggedized standoff instrument. The U.S. Army Research Laboratory has been coupling standoff LIBS spectra with chemometrics for several years now in order to discriminate between explosives and nonexplosives. We have investigated the use of partial least squares discriminant analysis (PLS-DA) for explosives detection. We have extended our study of PLS-DA to more complex sample types, including binary mixtures, different types of explosives, and samples not included in the model. We demonstrate themore » importance of building the PLS-DA model by iteratively testing it against sample test sets. Independent test sets are used to test the robustness of the final model.« less

Data Mining of Chemogenomics Data Using Bi-Modal PLS Methods and Chemical Interpretation for Molecular Design.

PubMed

Hasegawa, Kiyoshi; Funatsu, Kimito

2014-12-01

Chemogenomics is a new strategy in drug discovery for interrogating all molecules capable of interacting with all biological targets. Because of the almost infinite number of drug-like organic molecules, bench-based experimental chemogenomics methods are not generally feasible. Several in silico chemogenomics models have therefore been developed for high-throughput screening of large numbers of drug candidate compounds and target proteins. In previous studies, we described two novel bi-modal PLS approaches. These methods provide a significant advantage in that they enable direct connections to be made between biological activities and ligand and protein descriptors. In this special issue, we review these two PLS-based approaches using two different chemogenomics datasets for illustration. We then compare the predictive and interpretive performance of the two methods using the same congeneric data set. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Primary Lateral Sclerosis

PubMed Central

Statland, Jeffrey M.; Barohn, Richard J.; Dimachkie, Mazen M.; Floeter, Mary Kay; Mitsumoto, Hiroshi

2015-01-01

Synopsis Primary lateral sclerosis (PLS) is characterized by insidious onset of progressive upper motor neuron dysfunction in the absence of clinical signs of lower motor neuron involvement. Patients experience stiffness, decreased balance and coordination, and mild weakness, and if the bulbar region is affected, difficulty speaking and swallowing, and emotional lability. The diagnosis is made based on clinical history, typical exam findings, and diagnostic testing negative for other causes of upper motor neuron dysfunction. EMG is normal, or only shows mild neurogenic findings in a few muscles, not meeting El Escorial criteria. Although no test is specific for PLS, some neurodiagnostic tests are supportive: including absent or delayed central motor conduction times; and changes in the precentral gyrus or corticospinal tracts on MRI, DTI or MR Spectroscopy. Treatment is largely supportive, and includes medications for spasticity, baclofen pump, and treatment for pseudobulbar affect. The prognosis in PLS is more benign than ALS, making this a useful diagnostic category. PMID:26515619

Detection of drug active ingredients by chemometric processing of solid-state NMR spectrometry data -- the case of acetaminophen.

PubMed

Paradowska, Katarzyna; Jamróz, Marta Katarzyna; Kobyłka, Mariola; Gowin, Ewelina; Maczka, Paulina; Skibiński, Robert; Komsta, Łukasz

2012-01-01

This paper presents a preliminary study in building discriminant models from solid-state NMR spectrometry data to detect the presence of acetaminophen in over-the-counter pharmaceutical formulations. The dataset, containing 11 spectra of pure substances and 21 spectra of various formulations, was processed by partial least squares discriminant analysis (PLS-DA). The model found coped with the discrimination, and its quality parameters were acceptable. It was found that standard normal variate preprocessing had almost no influence on unsupervised investigation of the dataset. The influence of variable selection with the uninformative variable elimination by PLS method was studied, reducing the dataset from 7601 variables to around 300 informative variables, but not improving the model performance. The results showed the possibility to construct well-working PLS-DA models from such small datasets without a full experimental design.

Determination of butter adulteration with margarine using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Boyaci, Ismail Hakki; Genis, Hüseyin Efe; Tamer, Ugur

2013-12-15

In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined with chemometric methods (principal component analysis (PCA), principal component regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different butter and margarine samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA analysis was applied for the classification of butters, margarines and mixtures. PCR, PLS and ANN were used for the detection of adulteration ratios of butter. Models were created using a calibration data set and developed models were evaluated using a validation data set. The coefficient of determination (R(2)) values between actual and predicted values obtained for PCR, PLS and ANN for the validation data set were 0.968, 0.987 and 0.978, respectively. In conclusion, a combination of Raman spectroscopy with chemometrics and ANN methods can be applied for testing butter adulteration. Copyright © 2013 Elsevier Ltd. All rights reserved.

Combined orthodontic and periodontic treatment in a child with Papillon Lefèvre syndrome.

PubMed

AlSarheed, Maha A; Al-Sehaibany, Fares S

2015-08-01

A 9-year-old girl with Papillon-Lefèvre syndrome (PLS) was treated orthodontically 24 months after the start of mechanical and antibiotic therapy in adjunct with periodontal treatment every 6 weeks. After achieving stable periodontal conditions, orthodontic treatment was commenced to correct the teeth position, facial profile, and maxillary protraction. Following the combination therapy and a failure to detect Actinobacillus actinomycetemcomitans from any site in the oral cavity, orthodontic treatment with a fixed appliance was performed aside from creating space for eruption of permanent teeth. We found that combined periodontal and orthodontic treatment of PLS may be successful with a complex interdisciplinary regimen and close follow up. This is a 2-year follow-up case report of a girl with PLS. Orthodontic and periodontic therapy were offered using combined treatments of orthodontic and periodontal with the benefit of prosthodontic consultation, resulting in a treatment plan.

Combined orthodontic and periodontic treatment in a child with Papillon Lefèvre syndrome

PubMed Central

AlSarheed, Maha A.; Al-Sehaibany, Fares S.

2015-01-01

A 9-year-old girl with Papillon-Lefèvre syndrome (PLS) was treated orthodontically 24 months after the start of mechanical and antibiotic therapy in adjunct with periodontal treatment every 6 weeks. After achieving stable periodontal conditions, orthodontic treatment was commenced to correct the teeth position, facial profile, and maxillary protraction. Following the combination therapy and a failure to detect Actinobacillus actinomycetemcomitans from any site in the oral cavity, orthodontic treatment with a fixed appliance was performed aside from creating space for eruption of permanent teeth. We found that combined periodontal and orthodontic treatment of PLS may be successful with a complex interdisciplinary regimen and close follow up. This is a 2-year follow-up case report of a girl with PLS. Orthodontic and periodontic therapy were offered using combined treatments of orthodontic and periodontal with the benefit of prosthodontic consultation, resulting in a treatment plan. PMID:26219452

A spectroscopic tool for identifying sources of origin for materials of military interest

NASA Astrophysics Data System (ADS)

Miziolek, Andrzej W.; De Lucia, Frank C.

2014-05-01

There is a need to identify the source of origin for many items of military interest, including ammunition and weapons that may be circulated and traded in illicit markets. Both fieldable systems (man-portable or handheld) as well as benchtop systems in field and home base laboratories are desired for screening and attribution purposes. Laser Induced Breakdown Spectroscopy (LIBS) continues to show significant capability as a promising new tool for materials identification, matching, and provenance. With the use of the broadband, high resolution spectrometer systems, the LIBS devices can not only determine the elemental inventory of the sample, but they are also capable of elemental fingerprinting to signify sources of origin of various materials. We present the results of an initial study to differentiate and match spent cartridges from different manufacturers and countries. We have found that using Partial Least Squares Discriminant Analysis (PLS-DA) we are able to achieve on average 93.3% True Positives and 5.3% False Positives. These results add to the large body of publications that have demonstrated that LIBS is a particularly suitable tool for source of origin determinations.

Multiple beneficial lipids including lecithin detected in the edible invasive mollusk Crepidula fornicata from the French Northeastern Atlantic coast.

PubMed

Dagorn, Flore; Buzin, Florence; Couzinet-Mossion, Aurélie; Decottignies, Priscilla; Viau, Michèle; Rabesaotra, Vony; Barnathan, Gilles; Wielgosz-Collin, Gaëtane

2014-12-22

The invasive mollusk Crepidula fornicata, occurring in large amounts in bays along the French Northeastern Atlantic coasts, may have huge environmental effects in highly productive ecosystems where shellfish are exploited. The present study aims at determining the potential economic value of this marine species in terms of exploitable substances with high added value. Lipid content and phospholipid (PL) composition of this mollusk collected on the Bourgneuf Bay were studied through four seasons. Winter specimens contained the highest lipid levels (5.3% dry weight), including 69% of PLs. Phosphatidylcholine (PC) was the major PL class all year, accounting for 63.9% to 88.9% of total PLs. Consequently, the winter specimens were then investigated for PL fatty acids (FAs), and free sterols. Dimethylacetals (DMAs) were present (10.7% of PL FA + DMA mixture) revealing the occurrence of plasmalogens. More than forty FAs were identified, including 20:5n-3 (9.4%) and 22:6n-3 (7.3%) acids. Fourteen free sterols were present, including cholesterol at 31.3% of the sterol mixture and about 40% of phytosterols. These data on lipids of C. fornicata demonstrate their positive attributes for human nutrition and health. The PL mixture, rich in PC and polyunsaturated FAs, offers an interesting alternative source of high value-added marine lecithin.

Multiple Beneficial Lipids Including Lecithin Detected in the Edible Invasive Mollusk Crepidula fornicata from the French Northeastern Atlantic Coast

PubMed Central

Dagorn, Flore; Buzin, Florence; Couzinet-Mossion, Aurélie; Decottignies, Priscilla; Viau, Michèle; Rabesaotra, Vony; Barnathan, Gilles; Wielgosz-Collin, Gaëtane

2014-01-01

The invasive mollusk Crepidula fornicata, occurring in large amounts in bays along the French Northeastern Atlantic coasts, may have huge environmental effects in highly productive ecosystems where shellfish are exploited. The present study aims at determining the potential economic value of this marine species in terms of exploitable substances with high added value. Lipid content and phospholipid (PL) composition of this mollusk collected on the Bourgneuf Bay were studied through four seasons. Winter specimens contained the highest lipid levels (5.3% dry weight), including 69% of PLs. Phosphatidylcholine (PC) was the major PL class all year, accounting for 63.9% to 88.9% of total PLs. Consequently, the winter specimens were then investigated for PL fatty acids (FAs), and free sterols. Dimethylacetals (DMAs) were present (10.7% of PL FA + DMA mixture) revealing the occurrence of plasmalogens. More than forty FAs were identified, including 20:5n-3 (9.4%) and 22:6n-3 (7.3%) acids. Fourteen free sterols were present, including cholesterol at 31.3% of the sterol mixture and about 40% of phytosterols. These data on lipids of C. fornicata demonstrate their positive attributes for human nutrition and health. The PL mixture, rich in PC and polyunsaturated FAs, offers an interesting alternative source of high value-added marine lecithin. PMID:25532566

Determination of fat and total protein content in milk using conventional digital imaging.

PubMed

Kucheryavskiy, Sergey; Melenteva, Anastasiia; Bogomolov, Andrey

2014-04-01

The applicability of conventional digital imaging to quantitative determination of fat and total protein in cow's milk, based on the phenomenon of light scatter, has been proved. A new algorithm for extracting features from digital images of milk samples has been developed. The algorithm takes into account spatial distribution of light, diffusely transmitted through a sample. The proposed method has been tested on two sample sets prepared from industrial raw milk standards, with variable fat and protein content. Partial Least-Squares (PLS) regression on the features calculated from images of monochromatically illuminated milk samples resulted in models with high prediction performance when analysed the sets separately (best models with cross-validated R(2)=0.974 for protein and R(2)=0.973 for fat content). However when analysed the sets jointly with the obtained results were significantly worse (best models with cross-validated R(2)=0.890 for fat content and R(2)=0.720 for protein content). The results have been compared with previously published Vis/SW-NIR spectroscopic study of similar samples. Copyright © 2013 Elsevier B.V. All rights reserved.

pLS101 plasmid vector

DOEpatents

Lacks, S.A.; Balganesh, T.S.

1985-02-19

Disclosed is recombinant plasmid pLS101, consisting essentially of a 2.0 Kb ma1M gene fragment ligated to a 4.4 Kb Tcr DNA fragment, which is particularly useful for transforming Gram-positive bacteria. This plasmid contains at least four restriction sites suitable for inserting exogeneous gene sequences. Also disclosed is a method for plasmid isolation by penicillin selection, as well as processes for enrichment of recombinant plasmids in Gram-positive bacterial systems. 5 figs., 2 tabs.

Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2015-01-01

The non-sugar solids (NSS) content is one of the most important nutrition indicators of Chinese rice wine. This study proposed a rapid method for the measurement of NSS content in Chinese rice wine using near infrared (NIR) spectroscopy. We also systemically studied the efficient spectral variables selection algorithms that have to go through modeling. A new algorithm of synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was proposed for modeling. The performance of the final model was back-evaluated using root mean square error of calibration (RMSEC) and correlation coefficient (Rc) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (Rp) in prediction set. The optimum model by Si-CARS-PLS algorithm was achieved when 7 PLS factors and 18 variables were included, and the results were as follows: Rc=0.95 and RMSEC=1.12 in the calibration set, Rp=0.95 and RMSEP=1.22 in the prediction set. In addition, Si-CARS-PLS algorithm showed its superiority when compared with the commonly used algorithms in multivariate calibration. This work demonstrated that NIR spectroscopy technique combined with a suitable multivariate calibration algorithm has a high potential in rapid measurement of NSS content in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

A multi-model fusion strategy for multivariate calibration using near and mid-infrared spectra of samples from brewing industry.

PubMed

Tan, Chao; Chen, Hui; Wang, Chao; Zhu, Wanping; Wu, Tong; Diao, Yuanbo

2013-03-15

Near and mid-infrared (NIR/MIR) spectroscopy techniques have gained great acceptance in the industry due to their multiple applications and versatility. However, a success of application often depends heavily on the construction of accurate and stable calibration models. For this purpose, a simple multi-model fusion strategy is proposed. It is actually the combination of Kohonen self-organizing map (KSOM), mutual information (MI) and partial least squares (PLSs) and therefore named as KMICPLS. It works as follows: First, the original training set is fed into a KSOM for unsupervised clustering of samples, on which a series of training subsets are constructed. Thereafter, on each of the training subsets, a MI spectrum is calculated and only the variables with higher MI values than the mean value are retained, based on which a candidate PLS model is constructed. Finally, a fixed number of PLS models are selected to produce a consensus model. Two NIR/MIR spectral datasets from brewing industry are used for experiments. The results confirms its superior performance to two reference algorithms, i.e., the conventional PLS and genetic algorithm-PLS (GAPLS). It can build more accurate and stable calibration models without increasing the complexity, and can be generalized to other NIR/MIR applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Crop/weed discrimination using near-infrared reflectance spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Zhang, Yun; He, Yong

2006-09-01

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

Application of dielectric spectroscopy for monitoring high cell density in monoclonal antibody producing CHO cell cultivations.

PubMed

Párta, László; Zalai, Dénes; Borbély, Sándor; Putics, Akos

2014-02-01

The application of dielectric spectroscopy was frequently investigated as an on-line cell culture monitoring tool; however, it still requires supportive data and experience in order to become a robust technique. In this study, dielectric spectroscopy was used to predict viable cell density (VCD) at industrially relevant high levels in concentrated fed-batch culture of Chinese hamster ovary cells producing a monoclonal antibody for pharmaceutical purposes. For on-line dielectric spectroscopy measurements, capacitance was scanned within a wide range of frequency values (100-19,490 kHz) in six parallel cell cultivation batches. Prior to detailed mathematical analysis of the collected data, principal component analysis (PCA) was applied to compare dielectric behavior of the cultivations. PCA analysis resulted in detecting measurement disturbances. By using the measured spectroscopic data, partial least squares regression (PLS), Cole-Cole, and linear modeling were applied and compared in order to predict VCD. The Cole-Cole and the PLS model provided reliable prediction over the entire cultivation including both the early and decline phases of cell growth, while the linear model failed to estimate VCD in the later, declining cultivation phase. In regards to the measurement error sensitivity, remarkable differences were shown among PLS, Cole-Cole, and linear modeling. VCD prediction accuracy could be improved in the runs with measurement disturbances by first derivative pre-treatment in PLS and by parameter optimization of the Cole-Cole modeling.

Quantitative determination of wool in textile by near-infrared spectroscopy and multivariate models.

PubMed

Chen, Hui; Tan, Chao; Lin, Zan

2018-08-05

The wool content in textiles is a key quality index and the corresponding quantitative analysis takes an important position due to common adulterations in both raw and finished textiles. Conventional methods are maybe complicated, destructive, time-consuming, environment-unfriendly. Developing a quick, easy-to-use and green alternative method is interesting. The work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy and several partial least squares (PLS)-based algorithms and elastic component regression (ECR) algorithms for measuring wool content in textile. A total of 108 cloth samples with wool content ranging from 0% to 100% (w/w) were collected and all the compositions are really existent in the market. The dataset was divided equally into the training and test sets for developing and validating calibration models. When using local PLS, the original spectrum axis was split into 20 sub-intervals. No obvious difference of performance can be seen for the local PLS models. The ECR model is comparable or superior to the other models due its flexibility, i.e., being transition state from PCR to PLS. It seems that ECR combined with NIR technique may be a potential method for determining wool content in textile products. In addition, it might have regulatory advantages to avoid time-consuming and environmental-unfriendly chemical analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of pork adulteration in beef meatball using Fourier transform infrared (FTIR) spectroscopy.

PubMed

Rohman, A; Sismindari; Erwanto, Y; Che Man, Yaakob B

2011-05-01

Meatball is one of the favorite foods in Indonesia. The adulteration of pork in beef meatball is frequently occurring. This study was aimed to develop a fast and non destructive technique for the detection and quantification of pork in beef meatball using Fourier transform infrared (FTIR) spectroscopy and partial least square (PLS) calibration. The spectral bands associated with pork fat (PF), beef fat (BF), and their mixtures in meatball formulation were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure PF and BF. For quantitative analysis, PLS regression was used to develop a calibration model at the selected fingerprint regions of 1200-1000 cm(-1). The equation obtained for the relationship between actual PF value and FTIR predicted values in PLS calibration model was y = 0.999x + 0.004, with coefficient of determination (R(2)) and root mean square error of calibration are 0.999 and 0.442, respectively. The PLS calibration model was subsequently used for the prediction of independent samples using laboratory made meatball samples containing the mixtures of BF and PF. Using 4 principal components, root mean square error of prediction is 0.742. The results showed that FTIR spectroscopy can be used for the detection and quantification of pork in beef meatball formulation for Halal verification purposes. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

A Sulfated-Polysaccharide Fraction from Seaweed Gracilaria birdiae Prevents Naproxen-Induced Gastrointestinal Damage in Rats

PubMed Central

Silva, Renan O.; Santana, Ana Paula M.; Carvalho, Nathalia S.; Bezerra, Talita S.; Oliveira, Camila B.; Damasceno, Samara R. B.; Chaves, Luciano S.; Freitas, Ana Lúcia P.; Soares, Pedro M. G.; Souza, Marcellus H. L. P.; Barbosa, André Luiz R.; Medeiros, Jand-Venes R.

2012-01-01

Red seaweeds synthesize a great variety of sulfated galactans. Sulfated polysaccharides (PLSs) from seaweed are comprised of substances with pharmaceutical and biomedical potential. The aim of the present study was to evaluate the protective effect of the PLS fraction extracted from the seaweed Gracilaria birdiae in rats with naproxen-induced gastrointestinal damage. Male Wistar rats were pretreated with 0.5% carboxymethylcellulose (control group—vehicle) or PLS (10, 30, and 90 mg/kg, p.o.) twice daily (at 09:00 and 21:00) for 2 days. After 1 h, naproxen (80 mg/kg, p.o.) was administered. The rats were killed on day two, 4 h after naproxen treatment. The stomachs were promptly excised, opened along the greater curvature, and measured using digital calipers. Furthermore, the guts of the animals were removed, and a 5-cm portion of the small intestine (jejunum and ileum) was used for the evaluation of macroscopic scores. Samples of the stomach and the small intestine were used for histological evaluation, morphometric analysis and in assays for glutathione (GSH) levels, malonyldialdehyde (MDA) concentration, and myeloperoxidase (MPO) activity. PLS treatment reduced the macroscopic and microscopic naproxen-induced gastrointestinal damage in a dose-dependent manner. Our results suggest that the PLS fraction has a protective effect against gastrointestinal damage through mechanisms that involve the inhibition of inflammatory cell infiltration and lipid peroxidation. PMID:23342384

A sulfated-polysaccharide fraction from seaweed Gracilaria birdiae prevents naproxen-induced gastrointestinal damage in rats.

PubMed

Silva, Renan O; Santana, Ana Paula M; Carvalho, Nathalia S; Bezerra, Talita S; Oliveira, Camila B; Damasceno, Samara R B; Chaves, Luciano S; Freitas, Ana Lúcia P; Soares, Pedro M G; Souza, Marcellus H L P; Barbosa, André Luiz R; Medeiros, Jand-Venes R

2012-12-01

Red seaweeds synthesize a great variety of sulfated galactans. Sulfated polysaccharides (PLSs) from seaweed are comprised of substances with pharmaceutical and biomedical potential. The aim of the present study was to evaluate the protective effect of the PLS fraction extracted from the seaweed Gracilaria birdiae in rats with naproxen-induced gastrointestinal damage. Male Wistar rats were pretreated with 0.5% carboxymethylcellulose (control group-vehicle) or PLS (10, 30, and 90 mg/kg, p.o.) twice daily (at 09:00 and 21:00) for 2 days. After 1 h, naproxen (80 mg/kg, p.o.) was administered. The rats were killed on day two, 4 h after naproxen treatment. The stomachs were promptly excised, opened along the greater curvature, and measured using digital calipers. Furthermore, the guts of the animals were removed, and a 5-cm portion of the small intestine (jejunum and ileum) was used for the evaluation of macroscopic scores. Samples of the stomach and the small intestine were used for histological evaluation, morphometric analysis and in assays for glutathione (GSH) levels, malonyldialdehyde (MDA) concentration, and myeloperoxidase (MPO) activity. PLS treatment reduced the macroscopic and microscopic naproxen-induced gastrointestinal damage in a dose-dependent manner. Our results suggest that the PLS fraction has a protective effect against gastrointestinal damage through mechanisms that involve the inhibition of inflammatory cell infiltration and lipid peroxidation.

Statistical process control of cocrystallization processes: A comparison between OPLS and PLS.

PubMed

Silva, Ana F T; Sarraguça, Mafalda Cruz; Ribeiro, Paulo R; Santos, Adenilson O; De Beer, Thomas; Lopes, João Almeida

2017-03-30

Orthogonal partial least squares regression (OPLS) is being increasingly adopted as an alternative to partial least squares (PLS) regression due to the better generalization that can be achieved. Particularly in multivariate batch statistical process control (BSPC), the use of OPLS for estimating nominal trajectories is advantageous. In OPLS, the nominal process trajectories are expected to be captured in a single predictive principal component while uncorrelated variations are filtered out to orthogonal principal components. In theory, OPLS will yield a better estimation of the Hotelling's T 2 statistic and corresponding control limits thus lowering the number of false positives and false negatives when assessing the process disturbances. Although OPLS advantages have been demonstrated in the context of regression, its use on BSPC was seldom reported. This study proposes an OPLS-based approach for BSPC of a cocrystallization process between hydrochlorothiazide and p-aminobenzoic acid monitored on-line with near infrared spectroscopy and compares the fault detection performance with the same approach based on PLS. A series of cocrystallization batches with imposed disturbances were used to test the ability to detect abnormal situations by OPLS and PLS-based BSPC methods. Results demonstrated that OPLS was generally superior in terms of sensibility and specificity in most situations. In some abnormal batches, it was found that the imposed disturbances were only detected with OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques.

PubMed

Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, A; Huang, Zhiwei

2011-10-21

This study aimed to evaluate the clinical utility of applying near-infrared (NIR) Raman spectroscopy and genetic algorithm-partial least squares-discriminant analysis (GA-PLS-DA) to identify biomolecular changes of cervical tissues associated with dysplastic transformation during colposcopic examination. A total of 105 in vivo Raman spectra were measured from 57 cervical sites (35 normal and 22 precancer sites) of 29 patients recruited, in which 65 spectra were from normal sites, while 40 spectra were from cervical precancerous lesions (i.e., 7 low-grade CIN and 33 high-grade CIN). The GA feature selection technique incorporated with PLS was utilized to study the significant biochemical Raman bands for differentiation between normal and precancer cervical tissues. The GA-PLS-DA algorithm with double cross-validation (dCV) identified seven diagnostically significant Raman bands in the ranges of 925-935, 979-999, 1080-1090, 1240-1260, 1320-1340, 1400-1420, and 1625-1645 cm(-1) related to proteins, nucleic acids and lipids in tissue, and yielded a diagnostic accuracy of 82.9% (sensitivity of 72.5% (29/40) and specificity of 89.2% (58/65)) for precancer detection. The results of this exploratory study suggest that Raman spectroscopy in conjunction with GA-PLS-DA and dCV methods has the potential to provide clinically significant discrimination between normal and precancer cervical tissues at the molecular level.

Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution.

PubMed

Koch, Cosima; Posch, Andreas E; Goicoechea, Héctor C; Herwig, Christoph; Lendl, Bernhard

2014-01-07

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline during Pencillium chrysogenum fermentations by FTIR spectroscopy and partial least squares (PLS) regression and multivariate curve resolution - alternating least squares (MCR-ALS). First, the applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by measuring standards of the analytes of interest and investigating matrix effects of the fermentation broth. Then measurements were performed inline during four fed-batch fermentations with online HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and MCR-ALS models were built using these data and validated by comparison of single analyte spectra with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L(-1) for Penicillin V and 0.32 g L(-1) for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L(-1) for Penicillin V and 0.15 g L(-1) for phenoxyacetic acid. A general work-flow for building and assessing chemometric regression models for the quantification of multiple analytes in bioprocesses by FTIR spectroscopy is given. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates.

PubMed

Gottfried, Jennifer L

2011-07-01

The potential of laser-induced breakdown spectroscopy (LIBS) to discriminate biological and chemical threat simulant residues prepared on multiple substrates and in the presence of interferents has been explored. The simulant samples tested include Bacillus atrophaeus spores, Escherichia coli, MS-2 bacteriophage, α-hemolysin from Staphylococcus aureus, 2-chloroethyl ethyl sulfide, and dimethyl methylphosphonate. The residue samples were prepared on polycarbonate, stainless steel and aluminum foil substrates by Battelle Eastern Science and Technology Center. LIBS spectra were collected by Battelle on a portable LIBS instrument developed by A3 Technologies. This paper presents the chemometric analysis of the LIBS spectra using partial least-squares discriminant analysis (PLS-DA). The performance of PLS-DA models developed based on the full LIBS spectra, and selected emission intensities and ratios have been compared. The full-spectra models generally provided better classification results based on the inclusion of substrate emission features; however, the intensity/ratio models were able to correctly identify more types of simulant residues in the presence of interferents. The fusion of the two types of PLS-DA models resulted in a significant improvement in classification performance for models built using multiple substrates. In addition to identifying the major components of residue mixtures, minor components such as growth media and solvents can be identified with an appropriately designed PLS-DA model.

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

PubMed

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Characterization of Endogenous Plasmids from Lactobacillus salivarius UCC118▿ †

PubMed Central

Fang, Fang; Flynn, Sarah; Li, Yin; Claesson, Marcus J.; van Pijkeren, Jan-Peter; Collins, J. Kevin; van Sinderen, Douwe; O'Toole, Paul W.

2008-01-01

The genome of Lactobacillus salivarius UCC118 comprises a 1.83-Mb chromosome, a 242-kb megaplasmid (pMP118), and two smaller plasmids of 20 kb (pSF118-20) and 44 kb (pSF118-44). Annotation and bioinformatic analyses suggest that both of the smaller plasmids replicate by a theta replication mechanism. Furthermore, it appears that they are transmissible, although neither possesses a complete set of conjugation genes. Plasmid pSF118-20 encodes a toxin-antitoxin system composed of pemI and pemK homologs, and this plasmid could be cured when PemI was produced in trans. The minimal replicon of pSF118-20 was determined by deletion analysis. Shuttle vector derivatives of pSF118-20 were generated that included the replication region (pLS203) and the replication region plus mobilization genes (pLS208). The plasmid pLS203 was stably maintained without selection in Lactobacillus plantarum, Lactobacillus fermentum, and the pSF118-20-cured derivative strain of L. salivarius UCC118 (strain LS201). Cloning in pLS203 of genes encoding luciferase and green fluorescent protein, and expression from a constitutive L. salivarius promoter, demonstrated the utility of this vector for the expression of heterologous genes in Lactobacillus. This study thus expands the knowledge base and vector repertoire of probiotic lactobacilli. PMID:18390685

OLED lighting devices having multi element light extraction and luminescence conversion layer

DOEpatents

Krummacher, Benjamin Claus; Antoniadis, Homer

2010-11-16

An apparatus such as a light source has a multi element light extraction and luminescence conversion layer disposed over a transparent layer of the light source and on the exterior of said light source. The multi-element light extraction and luminescence conversion layer includes a plurality of light extraction elements and a plurality of luminescence conversion elements. The light extraction elements diffuses the light from the light source while luminescence conversion elements absorbs a first spectrum of light from said light source and emits a second spectrum of light.

Investigation of natural phosphatidylcholine sources: separation and identification by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS2) of molecular species.

PubMed

Le Grandois, Julie; Marchioni, Eric; Zhao, Minjie; Giuffrida, Francesca; Ennahar, Saïd; Bindler, Françoise

2009-07-22

This study is a contribution to the exploration of natural phospholipid (PL) sources rich in long-chain polyunsaturated fatty acids (LC-PUFAs) with nutritional interest. Phosphatidylcholines (PCs) were purified from total lipid extracts of different food matrices, and their molecular species were separated and identified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS(2)). Fragmentation of lithiated adducts allowed for the identification of fatty acids linked to the glycerol backbone. Soy PC was particularly rich in species containing essential fatty acids, such as (18:2-18:2)PC (34.0%), (16:0-18:2)PC (20.8%), and (18:1-18:2)PC (16.3%). PC from animal sources (ox liver and egg yolk) contained major molecular species, such as (16:0-18:2)PC, (16:0-18:1)PC, (18:0-18:2)PC, or (18:0-18:1)PC. Finally, marine source (krill oil), which was particularly rich in (16:0-20:5)PC and (16:0-22:6)PC, appeared to be an interesting potential source for food supplementation with LC-PUFA-PLs, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA).

Consumers' choice of drinking water: Is it dependent upon perceived quality, convenience, price and attitude?

NASA Astrophysics Data System (ADS)

Wahid, Nabsiah Abdul; Cheng, Patrick Tan Foon; Abustan, Ismail; Nee, Goh Yen

2017-10-01

Tap water is one of the many sources of water that the public as consumers can choose for drinking. This study hypothesized that perceived quality, convenience, price and environmental attitude would determine consumers's choice of drinking water following the Attribution Theory as the underlying model. A survey was carried out on Malaysia's public at large. From 301 usable data, the PLS analysis revealed that only perceived quality, convenience and price attributed towards the public's choice of drinking water while attitude was not significant. The findings are beneficial for the water sector industry, particularly for drinking water operators, state governments, and alternative drinking water manufacturers like bottled water companies. The ability to identify factors for why consumers in the marketplace choose the source of their drinking water would enable the operators to plan and strategize tactics that can disseminate accurate knowledge about the product that can motivate marketability of drinking water in Malaysia.

Modeling of temperature-induced near-infrared and low-field time-domain nuclear magnetic resonance spectral variation: chemometric prediction of limonene and water content in spray-dried delivery systems.

PubMed

Andrade, Letícia; Farhat, Imad A; Aeberhardt, Kasia; Bro, Rasmus; Engelsen, Søren Balling

2009-02-01

The influence of temperature on near-infrared (NIR) and nuclear magnetic resonance (NMR) spectroscopy complicates the industrial applications of both spectroscopic methods. The focus of this study is to analyze and model the effect of temperature variation on NIR spectra and NMR relaxation data. Different multivariate methods were tested for constructing robust prediction models based on NIR and NMR data acquired at various temperatures. Data were acquired on model spray-dried limonene systems at five temperatures in the range from 20 degrees C to 60 degrees C and partial least squares (PLS) regression models were computed for limonene and water predictions. The predictive ability of the models computed on the NIR spectra (acquired at various temperatures) improved significantly when data were preprocessed using extended inverted signal correction (EISC). The average PLS regression prediction error was reduced to 0.2%, corresponding to 1.9% and 3.4% of the full range of limonene and water reference values, respectively. The removal of variation induced by temperature prior to calibration, by direct orthogonalization (DO), slightly enhanced the predictive ability of the models based on NMR data. Bilinear PLS models, with implicit inclusion of the temperature, enabled limonene and water predictions by NMR with an error of 0.3% (corresponding to 2.8% and 7.0% of the full range of limonene and water). For NMR, and in contrast to the NIR results, modeling the data using multi-way N-PLS improved the models' performance. N-PLS models, in which temperature was included as an extra variable, enabled more accurate prediction, especially for limonene (prediction error was reduced to 0.2%). Overall, this study proved that it is possible to develop models for limonene and water content prediction based on NIR and NMR data, independent of the measurement temperature.

Chemometric-assisted spectrophotometric methods and high performance liquid chromatography for simultaneous determination of seven β-blockers in their pharmaceutical products: A comparative study

NASA Astrophysics Data System (ADS)

Abdel Hameed, Eman A.; Abdel Salam, Randa A.; Hadad, Ghada M.

2015-04-01

Chemometric-assisted spectrophotometric methods and high performance liquid chromatography (HPLC) were developed for the simultaneous determination of the seven most commonly prescribed β-blockers (atenolol, sotalol, metoprolol, bisoprolol, propranolol, carvedilol and nebivolol). Principal component regression PCR, partial least square PLS and PLS with previous wavelength selection by genetic algorithm (GA-PLS) were used for chemometric analysis of spectral data of these drugs. The compositions of the mixtures used in the calibration set were varied to cover the linearity ranges 0.7-10 μg ml-1 for AT, 1-15 μg ml-1 for ST, 1-15 μg ml-1 for MT, 0.3-5 μg ml-1 for BS, 0.1-3 μg ml-1 for PR, 0.1-3 μg ml-1 for CV and 0.7-5 μg ml-1 for NB. The analytical performances of these chemometric methods were characterized by relative prediction errors and were compared with each other. GA-PLS showed superiority over the other applied multivariate methods due to the wavelength selection. A new gradient HPLC method had been developed using statistical experimental design. Optimum conditions of separation were determined with the aid of central composite design. The developed HPLC method was found to be linear in the range of 0.2-20 μg ml-1 for AT, 0.2-20 μg ml-1 for ST, 0.1-15 μg ml-1 for MT, 0.1-15 μg ml-1 for BS, 0.1-13 μg ml-1 for PR, 0.1-13 μg ml-1 for CV and 0.4-20 μg ml-1 for NB. No significant difference between the results of the proposed GA-PLS and HPLC methods with respect to accuracy and precision. The proposed analytical methods did not show any interference of the excipients when applied to pharmaceutical products.

The experiences of leaders of self-management courses in Queensland: exploring Health Professional and Peer Leaders' perceptions of working together.

PubMed

Catalano, Tara; Kendall, Elizabeth; Vandenberg, Avanka; Hunter, Beth

2009-03-01

This paper describes the experiences of volunteers who have been trained to deliver the Stanford Chronic Disease Self-Management Program course. In Queensland, Australia, Leaders usually work in pairs (a Health Professional Leader (HPL) and a Peer Leader (PL)). Qualitative data were collected to explore volunteers' experiences as Leaders and their opinions about working together to deliver self-management courses. The data were collected from September 2005 to December 2005. In-depth, semistructured telephone interviews were conducted with a purposive sample of 34 Leaders (17 PL, 17 HPLs). Thematic analysis revealed two core themes that described Leaders' perceptions and experiences of working relationships between HPLs and PLs: (i) The Value of Working Together and (2) Relationship Tensions. Both HPLs and PLs believed that working together represented 'the best of both worlds' and that the combination of peers and health professionals enhanced the sustainability of the approach. However, a number of tensions were revealed that undermined the development and sustainability of these working relationships. From HPLs' perspective, the benefits of working with volunteer PLs did not always justify the 'burden'. Finding the 'right person' for the PL role was difficult and a higher value was often placed on the contribution of professionals. The tensions that were most prominent for PLs were grounded in the disparity between their status and that of HPLs, their lack of ownership over courses coupled with lack of a strong voice in the co-Leader relationship, and the absence of connection and engagement among Leaders. Working relationships between HPLs and PLs have potential to deliver positive outcomes for people with chronic disease, but the current study has highlighted the necessity of developing a culture of mutual respect and a system that values both forms of knowledge and expertise (i.e. experiential and professional).

Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis.

PubMed

Kehimkar, Benjamin; Parsons, Brendon A; Hoggard, Jamin C; Billingsley, Matthew C; Bruno, Thomas J; Synovec, Robert E

2015-01-01

Recent efforts in predicting rocket propulsion (RP-1) fuel performance through modeling put greater emphasis on obtaining detailed and accurate fuel properties, as well as elucidating the relationships between fuel compositions and their properties. Herein, we study multidimensional chromatographic data obtained by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC-TOFMS) to analyze RP-1 fuels. For GC × GC separations, RTX-Wax (polar stationary phase) and RTX-1 (non-polar stationary phase) columns were implemented for the primary and secondary dimensions, respectively, to separate the chemical compound classes (alkanes, cycloalkanes, aromatics, etc.), providing a significant level of chemical compositional information. The GC × GC-TOFMS data were analyzed using partial least squares regression (PLS) chemometric analysis to model and predict advanced distillation curve (ADC) data for ten RP-1 fuels that were previously analyzed using the ADC method. The PLS modeling provides insight into the chemical species that impact the ADC data. The PLS modeling correlates compositional information found in the GC × GC-TOFMS chromatograms of each RP-1 fuel, and their respective ADC, and allows prediction of the ADC for each RP-1 fuel with good precision and accuracy. The root-mean-square error of calibration (RMSEC) ranged from 0.1 to 0.5 °C, and was typically below ∼0.2 °C, for the PLS calibration of the ADC modeling with GC × GC-TOFMS data, indicating a good fit of the model to the calibration data. Likewise, the predictive power of the overall method via PLS modeling was assessed using leave-one-out cross-validation (LOOCV) yielding root-mean-square error of cross-validation (RMSECV) ranging from 1.4 to 2.6 °C, and was typically below ∼2.0 °C, at each % distilled measurement point during the ADC analysis.

[Research on fast detecting tomato seedlings nitrogen content based on NIR characteristic spectrum selection].

PubMed

Wu, Jing-zhu; Wang, Feng-zhu; Wang, Li-li; Zhang, Xiao-chao; Mao, Wen-hua

2015-01-01

In order to improve the accuracy and robustness of detecting tomato seedlings nitrogen content based on near-infrared spectroscopy (NIR), 4 kinds of characteristic spectrum selecting methods were studied in the present paper, i. e. competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variables elimination (MCUVE), backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS). There were totally 60 tomato seedlings cultivated at 10 different nitrogen-treatment levels (urea concentration from 0 to 120 mg . L-1), with 6 samples at each nitrogen-treatment level. They are in different degrees of over nitrogen, moderate nitrogen, lack of nitrogen and no nitrogen status. Each sample leaves were collected to scan near-infrared spectroscopy from 12 500 to 3 600 cm-1. The quantitative models based on the above 4 methods were established. According to the experimental result, the calibration model based on CARS and MCUVE selecting methods show better performance than those based on BiPLS and SiPLS selecting methods, but their prediction ability is much lower than that of the latter. Among them, the model built by BiPLS has the best prediction performance. The correlation coefficient (r), root mean square error of prediction (RMSEP) and ratio of performance to standard derivate (RPD) is 0. 952 7, 0. 118 3 and 3. 291, respectively. Therefore, NIR technology combined with characteristic spectrum selecting methods can improve the model performance. But the characteristic spectrum selecting methods are not universal. For the built model based or single wavelength variables selection is more sensitive, it is more suitable for the uniform object. While the anti-interference ability of the model built based on wavelength interval selection is much stronger, it is more suitable for the uneven and poor reproducibility object. Therefore, the characteristic spectrum selection will only play a better role in building model, combined with the consideration of sample state and the model indexes.

Year-class formation of upper St. Lawrence River northern pike

USGS Publications Warehouse

Smith, B.M.; Farrell, J.M.; Underwood, H.B.; Smith, S.J.

2007-01-01

Variables associated with year-class formation in upper St. Lawrence River northern pike Esox lucius were examined to explore population trends. A partial least-squares (PLS) regression model (PLS 1) was used to relate a year-class strength index (YCSI; 1974-1997) to explanatory variables associated with spawning and nursery areas (seasonal water level and temperature and their variability, number of ice days, and last day of ice presence). A second model (PLS 2) incorporated four additional ecological variables: potential predators (abundance of double-crested cormorants Phalacrocorax auritus and yellow perch Perca flavescens), female northern pike biomass (as a measure of stock-recruitment effects), and total phosphorus (productivity). Trends in adult northern pike catch revealed a decline (1981-2005), and year-class strength was positively related to catch per unit effort (CPUE; R2 = 0.58). The YCSI exceeded the 23-year mean in only 2 of the last 10 years. Cyclic patterns in the YCSI time series (along with strong year-classes every 4-6 years) were apparent, as was a dampening effect of amplitude beginning around 1990. The PLS 1 model explained over 50% of variation in both explanatory variables and the dependent variable, YCSI first-order moving-average residuals. Variables retained (N = 10; Wold's statistic ??? 0.8) included negative YCSI associations with high summer water levels, high variability in spring and fall water levels, and variability in fall water temperature. The YCSI exhibited positive associations with high spring, summer, and fall water temperature, variability in spring temperature, and high winter and spring water level. The PLS 2 model led to positive YCSI associations with phosphorus and yellow perch CPUE and a negative correlation with double-crested cormorant abundance. Environmental variables (water level and temperature) are hypothesized to regulate northern pike YCSI cycles, and dampening in YCSI magnitude may be related to a combination of factors, including wetland habitat changes, reduced nutrient loading, and increased predation by double-crested cormorants. ?? Copyright by the American Fisheries Society 2007.

PLS and first derivative of ratio spectra methods for determination of hydrochlorothiazide and propranolol hydrochloride in tablets.

PubMed

Vignaduzzo, Silvana E; Maggio, Rubén M; Castellano, Patricia M; Kaufman, Teodoro S

2006-12-01

Two new analytical methods have been developed as convenient and useful alternatives for simultaneous determination of hydrochlorothiazide (HCT) and propranolol hydrochloride (PRO) in pharmaceutical formulations. The methods are based on the first derivative of ratio spectra (DRS) and on partial least squares (PLS) analysis of the ultraviolet absorption spectra of the samples in the 250-350-nm region. The methods were calibrated between 8.7 and 16.0 mg L(-1) for HCT and between 14.0 and 51.5 mg L(-1) for PRO. An asymmetric full-factorial design and wavelength selection (277-294 nm for HCT and 297-319 for PRO) were used for the PLS method and signal intensities at 276 and 322 nm were used in the DRS method for HCT and PRO, respectively. Performance characteristics of the analytical methods were evaluated by use of validation samples and both methods showed to be accurate and precise, furnishing near quantitative analyte recoveries (100.4 and 99.3% for HCT and PRO by use of PLS) and relative standard deviations below 2%. For PLS the lower limits of quantification were 0.37 and 0.66 mg L(-1) for HCT and PRO, respectively, whereas for DRS they were 1.15 and 3.05 mg L(-1) for HCT and PRO, respectively. The methods were used for quantification of HCT and PRO in synthetic mixtures and in two commercial tablet preparations containing different proportions of the analytes. The results of the drug content assay and the tablet dissolution test were in statistical agreement (p < 0.05) with those furnished by the official procedures of the USP 29. Preparation of dissolution profiles of the combined tablet formulations was also performed with the aid of the proposed methods. The methods are easy to apply, use relatively simple equipment, require minimum sample pre-treatment, enable high sample throughput, and generate less solvent waste than other procedures.

Temporal deformation pattern in acute and late phases of ST-elevation myocardial infarction: incremental value of longitudinal post-systolic strain to assess myocardial viability.

PubMed

Huttin, Olivier; Marie, Pierre-Yves; Benichou, Maxime; Bozec, Erwan; Lemoine, Simon; Mandry, Damien; Juillière, Yves; Sadoul, Nicolas; Micard, Emilien; Duarte, Kevin; Beaumont, Marine; Rossignol, Patrick; Girerd, Nicolas; Selton-Suty, Christine

2016-10-01

Identification of transmural extent and degree of non-viability after ST-segment elevation myocardial infarction (STEMI) is clinically important. The objective of the present study was to assess the regional mechanics and temporal deformation patterns using speckle tracking echocardiography (STE) in acute and later phases of STEMI to predict myocardial damage in these patients. Ninety-eight patients with first STEMI underwent both echocardiography and cardiac magnetic resonance imaging in acute phase and at 6 months follow-up with 2D STE-derived measurements of peak longitudinal strain (PLS), Pre-STretch index (PST) and post-systolic deformation index (PSI). For each segment, late gadolinium enhancement (LGE) was defined as transmural (LGE >66 %) or non-transmural (<66 %). Global deformation values were significantly correlated with LVEFCMR and infarct size at both visits. A significantly lower value of segmental PLS and higher PSI and PST in necrotic segments were observed comparatively to control, adjacent and remote segments. The best parameters to predict transmural extent in acute phase were PSI with a cutoff value of 8 % (AUC: 0.84) and PLS with a cutoff value of -13 % (AUC: 0.86). PST showed high specificity, but poor sensitivity in predicting transmural extent. More importantly, the addition of PSI and PST to PLS in acute phase was associated with improved prediction of viability at 6 months (integrated discrimination improvement 2.5 % p < 0.01; net reclassification improvement 27 %; p < 0.01). All systolic deformation values separated transmural from non-transmural scarring. PLS combined with additional information relative to post-systolic deformation appears to be the most informative parameters to predict the transmural extent of MI in the early and late phases of MI. http://clinicaltrials.gov/show/NCT01109225 ; NCT01109225.

Voltammetric fingerprinting of oils and its combination with chemometrics for the detection of extra virgin olive oil adulteration.

PubMed

Tsopelas, Fotios; Konstantopoulos, Dimitris; Kakoulidou, Anna Tsantili

2018-07-26

In the present work, two approaches for the voltammetric fingerprinting of oils and their combination with chemometrics were investigated in order to detect the adulteration of extra virgin olive oil with olive pomace oil as well as the most common seed oils, namely sunflower, soybean and corn oil. In particular, cyclic voltammograms of diluted extra virgin olive oils, regular (pure) olive oils (blends of refined olive oils with virgin olive oils), olive pomace oils and seed oils in presence of dichloromethane and 0.1 M of LiClO 4 in EtOH as electrolyte were recorded at a glassy carbon working electrode. Cyclic voltammetry was also employed in methanolic extracts of olive and seed oils. Datapoints of cyclic voltammograms were exported and submitted to Principal Component Analysis (PCA), Partial Least Square- Discriminant Analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). In diluted oils, PLS-DA provided a clear discrimination between olive oils (extra virgin and regular) and olive pomace/seed oils, while SIMCA showed a clear discrimination of extra virgin olive oil in regard to all other samples. Using methanolic extracts and considering datapoints recorded between 0.6 and 1.3 V, PLS-DA provided more information, resulting in three clusters-extra virgin olive oils, regular olive oils and seed/olive pomace oils-while SIMCA showed inferior performance. For the quantification of extra virgin olive oil adulteration with olive pomace oil or seed oils, a model based on Partial Least Square (PLS) analysis was developed. Detection limit of adulteration in olive oil was found to be 2% (v/v) and the linearity range up to 33% (v/v). Validation and applicability of all models was proved using a suitable test set. In the case of PLS, synthetic oil mixtures with 4 known adulteration levels in the range of 4-26% were also employed as a blind test set. Copyright © 2018 Elsevier B.V. All rights reserved.

Culture Medium Supplements Derived from Human Platelet and Plasma: Cell Commitment and Proliferation Support

PubMed Central

Muraglia, Anita; Nguyen, Van Thi; Nardini, Marta; Mogni, Massimo; Coviello, Domenico; Dozin, Beatrice; Strada, Paolo; Baldelli, Ilaria; Formica, Matteo; Cancedda, Ranieri; Mastrogiacomo, Maddalena

2017-01-01

Present cell culture medium supplements, in most cases based on animal sera, are not fully satisfactory especially for the in vitro expansion of cells intended for human cell therapy. This paper refers to (i) an heparin-free human platelet lysate (PL) devoid of serum or plasma components (v-PL) and (ii) an heparin-free human serum derived from plasma devoid of PL components (Pl-s) and to their use as single components or in combination in primary or cell line cultures. Human mesenchymal stem cells (MSC) primary cultures were obtained from adipose tissue, bone marrow, and umbilical cord. Human chondrocytes were obtained from articular cartilage biopsies. In general, MSC expanded in the presence of Pl-s alone showed a low or no proliferation in comparison to cells grown with the combination of Pl-s and v-PL. Confluent, growth-arrested cells, either human MSC or human articular chondrocytes, treated with v-PL resumed proliferation, whereas control cultures, not supplemented with v-PL, remained quiescent and did not proliferate. Interestingly, signal transduction pathways distinctive of proliferation were activated also in cells treated with v-PL in the absence of serum, when cell proliferation did not occur, indicating that v-PL could induce the cell re-entry in the cell cycle (cell commitment), but the presence of serum proteins was an absolute requirement for cell proliferation to happen. Indeed, Pl-s alone supported cell growth in constitutively activated cell lines (U-937, HeLa, HaCaT, and V-79) regardless of the co-presence of v-PL. Plasma- and plasma-derived serum were equally able to sustain cell proliferation although, for cells cultured in adhesion, the Pl-s was more efficient than the plasma from which it was derived. In conclusion, the cells expanded in the presence of the new additives maintained their differentiation potential and did not show alterations in their karyotype. PMID:29209609

Application of NIRS coupled with PLS regression as a rapid, non-destructive alternative method for quantification of KBA in Boswellia sacra

NASA Astrophysics Data System (ADS)

Al-Harrasi, Ahmed; Rehman, Najeeb Ur; Mabood, Fazal; Albroumi, Muhammaed; Ali, Liaqat; Hussain, Javid; Hussain, Hidayat; Csuk, René; Khan, Abdul Latif; Alam, Tanveer; Alameri, Saif

2017-09-01

In the present study, for the first time, NIR spectroscopy coupled with PLS regression as a rapid and alternative method was developed to quantify the amount of Keto-β-Boswellic Acid (KBA) in different plant parts of Boswellia sacra and the resin exudates of the trunk. NIR spectroscopy was used for the measurement of KBA standards and B. sacra samples in absorption mode in the wavelength range from 700-2500 nm. PLS regression model was built from the obtained spectral data using 70% of KBA standards (training set) in the range from 0.1 ppm to 100 ppm. The PLS regression model obtained was having R-square value of 98% with 0.99 corelationship value and having good prediction with RMSEP value 3.2 and correlation of 0.99. It was then used to quantify the amount of KBA in the samples of B. sacra. The results indicated that the MeOH extract of resin has the highest concentration of KBA (0.6%) followed by essential oil (0.1%). However, no KBA was found in the aqueous extract. The MeOH extract of the resin was subjected to column chromatography to get various sub-fractions at different polarity of organic solvents. The sub-fraction at 4% MeOH/CHCl3 (4.1% of KBA) was found to contain the highest percentage of KBA followed by another sub-fraction at 2% MeOH/CHCl3 (2.2% of KBA). The present results also indicated that KBA is only present in the gum-resin of the trunk and not in all parts of the plant. These results were further confirmed through HPLC analysis and therefore it is concluded that NIRS coupled with PLS regression is a rapid and alternate method for quantification of KBA in Boswellia sacra. It is non-destructive, rapid, sensitive and uses simple methods of sample preparation.

Device structure for OLED light device having multi element light extraction and luminescence conversion layer

DOEpatents

Antoniadis,; Homer, Krummacher [Mountain View, CA; Claus, Benjamin [Regensburg, DE

2008-01-22

An apparatus such as a light source has a multi-element light extraction and luminescence conversion layer disposed over a transparent layer of the light source and on the exterior of said light source. The multi-element light extraction and luminescence conversion layer includes a plurality of light extraction elements and a plurality of luminescence conversion elements. The light extraction elements diffuses the light from the light source while luminescence conversion elements absorbs a first spectrum of light from said light source and emits a second spectrum of light.

Dietary Phospholipids and Intestinal Cholesterol Absorption

PubMed Central

Cohn, Jeffrey S.; Kamili, Alvin; Wat, Elaine; Chung, Rosanna W. S.; Tandy, Sally

2010-01-01

Experiments carried out with cultured cells and in experimental animals have consistently shown that phospholipids (PLs) can inhibit intestinal cholesterol absorption. Limited evidence from clinical studies suggests that dietary PL supplementation has a similar effect in man. A number of biological mechanisms have been proposed in order to explain how PL in the gut lumen is able to affect cholesterol uptake by the gut mucosa. Further research is however required to establish whether the ability of PLs to inhibit cholesterol absorption is of therapeutic benefit. PMID:22254012

Asteroid families - An initial search

NASA Technical Reports Server (NTRS)

Williams, James G.

1992-01-01

A stereo examination was conducted for clusters in three-dimensional proper element space within a sample of both numbered and faint Palomar-Leiden Survey (PLS) asteroids. The clusters were then objectively filtered for small Poisson probability of chance occurrence; 104 were accepted as families with 4- to 12-member populations, and are interpreted as impact-generated. Structure is common in the well-populated families: the better-sampled families are accordingly discussed in terms of their geometry and taxonomy. Some families are very rich in faint PLS members.

Backscatter absorption gas imaging systems and light sources therefore

DOEpatents

Kulp, Thomas Jan [Livermore, CA; Kliner, Dahv A. V. [San Ramon, CA; Sommers, Ricky [Oakley, CA; Goers, Uta-Barbara [Campbell, NY; Armstrong, Karla M [Livermore, CA

2006-12-19

The location of gases that are not visible to the unaided human eye can be determined using tuned light sources that spectroscopically probe the gases and cameras that can provide images corresponding to the absorption of the gases. The present invention is a light source for a backscatter absorption gas imaging (BAGI) system, and a light source incorporating the light source, that can be used to remotely detect and produce images of "invisible" gases. The inventive light source has a light producing element, an optical amplifier, and an optical parametric oscillator to generate wavelength tunable light in the IR. By using a multi-mode light source and an amplifier that operates using 915 nm pump sources, the power consumption of the light source is reduced to a level that can be operated by batteries for long periods of time. In addition, the light source is tunable over the absorption bands of many hydrocarbons, making it useful for detecting hazardous gases.

Driver circuit for solid state light sources

DOEpatents

Palmer, Fred; Denvir, Kerry; Allen, Steven

2016-02-16

A driver circuit for a light source including one or more solid state light sources, a luminaire including the same, and a method of so driving the solid state light sources are provided. The driver circuit includes a rectifier circuit that receives an alternating current (AC) input voltage and provides a rectified AC voltage. The driver circuit also includes a switching converter circuit coupled to the light source. The switching converter circuit provides a direct current (DC) output to the light source in response to the rectified AC voltage. The driver circuit also includes a mixing circuit, coupled to the light source, to switch current through at least one solid state light source of the light source in response to each of a plurality of consecutive half-waves of the rectified AC voltage.

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy

NASA Astrophysics Data System (ADS)

Jintao, Xue; Liming, Ye; Yufei, Liu; Chunyan, Li; Han, Chen

2017-05-01

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

Rapid and Accurate Evaluation of the Quality of Commercial Organic Fertilizers Using Near Infrared Spectroscopy

PubMed Central

Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

2014-01-01

The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers. PMID:24586313

Rapid and accurate evaluation of the quality of commercial organic fertilizers using near infrared spectroscopy.

PubMed

Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

2014-01-01

The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers.

Determination of polyphenolic compounds of red wines by UV-VIS-NIR spectroscopy and chemometrics tools.

PubMed

Martelo-Vidal, M J; Vázquez, M

2014-09-01

Spectral analysis is a quick and non-destructive method to analyse wine. In this work, trans-resveratrol, oenin, malvin, catechin, epicatechin, quercetin and syringic acid were determined in commercial red wines from DO Rías Baixas and DO Ribeira Sacra (Spain) by UV-VIS-NIR spectroscopy. Calibration models were developed using principal component regression (PCR) or partial least squares (PLS) regression. HPLC was used as reference method. The results showed that reliable PLS models were obtained to quantify all polyphenols for Rías Baixas wines. For Ribeira Sacra, feasible models were obtained to determine quercetin, epicatechin, oenin and syringic acid. PCR calibration models showed worst reliable of prediction than PLS models. For red wines from mencía grapes, feasible models were obtained for catechin and oenin, regardless the geographical origin. The results obtained demonstrate that UV-VIS-NIR spectroscopy can be used to determine individual polyphenolic compounds in red wines. Copyright © 2014 Elsevier Ltd. All rights reserved.

Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

NASA Astrophysics Data System (ADS)

De Lucia, Frank C., Jr.; Gottfried, Jennifer L.

2011-02-01

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.

Design for effective development and prototyping of the HL-20

NASA Astrophysics Data System (ADS)

Urie, David M.; Floreck, Paul A.; McMorris, John A.; Elvin, John D.

1993-10-01

A feasibility study of the HL-20 personnel launch system (PLS) concept was conducted by a team which focused on creating a PLS design approach and an accelerated development plan consistent with the historical 'Skunk Works' approach to rapid prototyping. Technical design, manufacturing, system testing, and operations and support elements of the predefined baseline concept were evaluated. An initial phase program, featuring a concurrent system test during design and development, leading to the orbital flight of an unmanned HL-20 prototype on a Titan III launch system, was prescribed. A second-phase development and manufacturing plan leading to system operational status was also formulated. Baseline design feature modifications were made when necessary, without compromise to performance, to satisfy the prototype development plan. Technical design details and off-the-shelf hardware candidates were also identified for several subsystems, including the launch-system interface adapter/emergency escape system. The technical feasibility of the system and applicability of the Skunk Works approach to development of the HL-20/PLS were verified.

Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue.

PubMed

El Alami El Hassani, Nadia; Tahri, Khalid; Llobet, Eduard; Bouchikhi, Benachir; Errachid, Abdelhamid; Zine, Nadia; El Bari, Nezha

2018-03-15

Moroccan and French honeys from different geographical areas were classified and characterized by applying a voltammetric electronic tongue (VE-tongue) coupled to analytical methods. The studied parameters include color intensity, free lactonic and total acidity, proteins, phenols, hydroxymethylfurfural content (HMF), sucrose, reducing and total sugars. The geographical classification of different honeys was developed through three-pattern recognition techniques: principal component analysis (PCA), support vector machines (SVMs) and hierarchical cluster analysis (HCA). Honey characterization was achieved by partial least squares modeling (PLS). All the PLS models developed were able to accurately estimate the correct values of the parameters analyzed using as input the voltammetric experimental data (i.e. r>0.9). This confirms the potential ability of the VE-tongue for performing a rapid characterization of honeys via PLS in which an uncomplicated, cost-effective sample preparation process that does not require the use of additional chemicals is implemented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhancement of partial robust M-regression (PRM) performance using Bisquare weight function

NASA Astrophysics Data System (ADS)

Mohamad, Mazni; Ramli, Norazan Mohamed; Ghani@Mamat, Nor Azura Md; Ahmad, Sanizah

2014-09-01

Partial Least Squares (PLS) regression is a popular regression technique for handling multicollinearity in low and high dimensional data which fits a linear relationship between sets of explanatory and response variables. Several robust PLS methods are proposed to accommodate the classical PLS algorithms which are easily affected with the presence of outliers. The recent one was called partial robust M-regression (PRM). Unfortunately, the use of monotonous weighting function in the PRM algorithm fails to assign appropriate and proper weights to large outliers according to their severity. Thus, in this paper, a modified partial robust M-regression is introduced to enhance the performance of the original PRM. A re-descending weight function, known as Bisquare weight function is recommended to replace the fair function in the PRM. A simulation study is done to assess the performance of the modified PRM and its efficiency is also tested in both contaminated and uncontaminated simulated data under various percentages of outliers, sample sizes and number of predictors.

Partial least-squares with residual bilinearization for the spectrofluorimetric determination of pesticides. A solution of the problems of inner-filter effects and matrix interferents.

PubMed

Piccirilli, Gisela N; Escandar, Graciela M

2006-09-01

This paper demonstrates for the first time the power of a chemometric second-order algorithm for predicting, in a simple way and using spectrofluorimetric data, the concentration of analytes in the presence of both the inner-filter effect and unsuspected species. The simultaneous determination of the systemic fungicides carbendazim and thiabendazole was achieved and employed for the discussion of the scopes of the applied second-order chemometric tools: parallel factor analysis (PARAFAC) and partial least-squares with residual bilinearization (PLS/RBL). The chemometric study was performed using fluorescence excitation-emission matrices obtained after the extraction of the analytes over a C18-membrane surface. The ability of PLS/RBL to recognize and overcome the significant changes produced by thiabendazole in both the excitation and emission spectra of carbendazim is demonstrated. The high performance of the selected PLS/RBL method was established with the determination of both pesticides in artificial and real samples.

Changes in fatty acid composition and lipid profile during koji fermentation and their relationships with soy sauce flavour.

PubMed

Feng, Yunzi; Chen, Zhiyao; Liu, Ning; Zhao, Haifeng; Cui, Chun; Zhao, Mouming

2014-09-01

Evolution of lipids during koji fermentation and the effect of lipase supplementation on the sensory properties of soy sauce were investigated. Results showed that total lipids of the koji samples were in the range of 16-21%. The extracted lipid of initial koji consisted mainly of triacylglycerols (TAGs, >98%), followed by phospholipids (PLs), diglycerides (DAGs), monoacylglycerols (MAGs) and free fatty acids (FFAs). As the fermentation proceeded, peroxide value of the lipids decreased while carbonyl value increased (p<0.05). Linoleic acid was utilised fastest according to the fatty acid composition of total lipids, and preferential degradation of PLs to liberate FFAs was also observed. Moreover, phospholipase supplementation had significant influence on the sensory characteristics of soy sauce, especially enhanced (p<0.05) scores for the umami and kokumi taste attributes. All these results indicated that the control of PLs utilisation during fermentation was a potential method to improve soy sauce's characteristic taste. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a multivariate calibration model for the determination of dry extract content in Brazilian commercial bee propolis extracts through UV-Vis spectroscopy

NASA Astrophysics Data System (ADS)

Barbeira, Paulo J. S.; Paganotti, Rosilene S. N.; Ássimos, Ariane A.

2013-10-01

This study had the objective of determining the content of dry extract of commercial alcoholic extracts of bee propolis through Partial Least Squares (PLS) multivariate calibration and electronic spectroscopy. The PLS model provided a good prediction of dry extract content in commercial alcoholic extracts of bee propolis in the range of 2.7 a 16.8% (m/v), presenting the advantage of being less laborious and faster than the traditional gravimetric methodology. The PLS model was optimized with outlier detection tests according to the ASTM E 1655-05. In this study it was possible to verify that a centrifugation stage is extremely important in order to avoid the presence of waxes, resulting in a more accurate model. Around 50% of the analyzed samples presented content of dry extract lower than the value established by Brazilian legislation, in most cases, the values found were different from the values claimed in the product's label.

Application of partial least squares near-infrared spectral classification in diabetic identification

NASA Astrophysics Data System (ADS)

Yan, Wen-juan; Yang, Ming; He, Guo-quan; Qin, Lin; Li, Gang

2014-11-01

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum - a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip's NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups - i.e. 53 samples as calibration set and 25 as prediction set - then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

Position Index for the Matrix Light Source

NASA Astrophysics Data System (ADS)

Takahashi, Hiroshi; Kobayashi, Yoshinori; Onda, Shou; Irikura, Takashi

It is expected that in the future white LEDs will be widely used in practical applications including replacing conventional lighting in offices and homes. The white LED light source of matrix arrangement is also considered in it. On the other hand, although now the unified glare rating (UGR) is widely used for evaluation of the discomfort glare of the interior lighting, UGR is a thing for a uniform light source, and its application to the matrix light sources that have non-uniform luminance has not been considered. The aim of this study is to clarify the position index which is one of element of UGR for the matrix light source. In this case, to apply the position index for a matrix light source to UGR, the concept of the revised position index is invented. As the preliminary experiment, method for measuring the position index was conducted, and as the experiment, position index for the matrix light source was conducted and compared with the uniform light source. The results of the experiments show that the position index is decided by the relative angle between line of sight and light source. It is also found that the matrix light source have larger position index than uniform light source. Furthermore, it is shown that the discomfort glare caused by a matrix light source can be evaluated by applying the revised position index to the UGR.

Utility and safety of a novel surgical microscope laser light source

PubMed Central

Bakhit, Mudathir S.; Suzuki, Kyouichi; Sakuma, Jun; Fujii, Masazumi; Murakami, Yuta; Ito, Yuhei; Sugano, Tetsuo; Saito, Kiyoshi

2018-01-01

Objective Tissue injuries caused by the thermal effects of xenon light microscopes have previously been reported. Due to this, the development of a safe microscope light source became a necessity. A newly developed laser light source is evaluated regarding its effectiveness and safety as an alternative to conventional xenon light source. Methods We developed and tested a new laser light source for surgical microscopes. Four experiments were conducted to compare xenon and laser lights: 1) visual luminance comparison, 2) luminous and light chromaticity measurements, 3) examination and analysis of visual fatigue, and 4) comparison of focal temperature elevation due to light source illumination using porcine muscle samples. Results Results revealed that the laser light could be used at a lower illumination value than the xenon light (p < 0.01). There was no significant difference in visual fatigue status between the laser light and the xenon light. The laser light was superior to the xenon light regarding luminous intensity and color chromaticity. The focal temperature elevation of the muscle samples was significantly higher when irradiated with xenon light in vitro than with laser light (p < 0.01). Conclusion The newly developed laser light source is more efficient and safer than a conventional xenon light source. It lacks harmful ultraviolet waves, has a longer lifespan, a lower focal temperature than that of other light sources, a wide range of brightness and color production, and improved safety for the user’s vision. Further clinical trials are necessary to validate the impact of this new light source on the patient’s outcome and prognosis. PMID:29390016

Peculiarities of energy trapping of the UHF elastic waves in diamond-based piezoelectric layered structure. I. Waveguide criterion.

PubMed

Kvashnin, G M; Sorokin, B P; Novoselov, A S

2018-03-01

Finite Element Modeling of the peculiarities of the trapping energy phenomenon in application to the piezoelectric layered structure (PLS) "Al/(0 0 1) AlN/Mo/(1 0 0) diamond" has been fulfilled. The resonant properties of longitudinal bulk acoustic waves (BAW) as well as frequency dependence of impedance within the 1 - 6 GHz band have been studied. The investigation of distribution of elastic energy flow and elastic displacements in a PLS cross-section allowed us to obtain an important information on energy trapping (ET) in PLS. Experimentally and as a result of modeling, it has been found that Q minimums are observed in PLS at quarter-wave resonance in the thin-film piezoelectric transducer (TFPT). Maximal Q value was observed at half-wave resonance in TFPT. It has been established that the ET-effect depends considerably on the mutual location of the n-th overtone's antiresonant frequency f a , n and cut-off frequencies of substrate f s , n-k- 1 and f s , n-k where f s , n-k- 1 f s , n-k , when the BAW energy excites the symmetrical or antisymmetrical Lamb waves. Copyright © 2017. Published by Elsevier B.V.

Tailor-made purified human platelet lysate concentrated in neurotrophins for treatment of Parkinson's disease.

PubMed

Chou, Ming-Li; Wu, Joe-Wei; Gouel, Flore; Jonneaux, Aurélie; Timmerman, Kelly; Renn, Ting-Yi; Laloux, Charlotte; Chang, Hung-Ming; Lin, Liang-Tzung; Devedjian, Jean-Christophe; Devos, David; Burnouf, Thierry

2017-10-01

Human platelet lysates (PLs), which contain multiple neurotrophins, have been proposed for treating neurodegenerative disorders, including Parkinson's disease (PD). However, current PLs suspended in plasma have high protein content and contain fibrinogen/fibrin and, following activation, also proteolytic and thrombogenic enzymes. Upon brain administration, such PLs may saturate the cerebrospinal fluid and exert neurotoxicity. We assessed whether purified PLs, concentrated in neurotrophins, protected dopaminergic neurons in PD models. Platelet concentrates were collected by apheresis and centrifuged to eliminate plasma and recover the platelets. Platelets were lysed by freeze-thaw cycles, and the 10-fold concentrated platelet pellet lysates (PPLs) were heat-treated (at 56 °C for 30 min). The heat-treated PPLs were low in total proteins, depleted in both plasma and platelet fibrinogen, and devoid of thrombogenic and proteolytic activities. They exerted very high neuroprotective activity when non-oncogenic, Lund human mesencephalic (LUHMES) cells that had differentiated into dopaminergic neurons were exposed to the MPP + neurotoxin. Heat treatment improved the neuroprotection and inactivated the neurotoxic blood-borne hepatitis C virus. PPL did not induce inflammation in BV2 microglial cells and inhibited COX-2 expression upon lipopolysaccharide exposure. Intranasal administration in mice revealed (a) diffusion of neurotrophins in the striatum and cortex, and (b) MPTP intoxication neuroprotection in the substantia nigra and striatum and the absence of neuroinflammation. These dedicated heat-treated PPLs can be a safe and valuable candidate for a therapeutic strategy for PD. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Effect of green alga Ulva lactuca polysaccharides supplementation on blood pressure and on atherogenic risk factors, in rats fed a high fat diet].

PubMed

Tair, Z I; Bensalah, F; Boukortt, F

2018-05-15

To highlight the benefits of green alga Ulva lactuca polysaccharides supplementation on blood pressure and atherogenic risk factors in rats fed a high fat diet. Wistar male rats were fed a high fat diet (30% sheep fat) for 3 months. At an average body weight (BW) of 360g, the rats (n=18) were divided into 3 groups and consumed, for 28 days, either a high fat diet (HFD) or a high fat diet enriched with 1% of whole green algae (WGA) powder or with 1% of its polysaccharides (PLS). In HFD, WGA and PLS supplementation reduced BW and food intake. WGA and PLS compared to HFD reduced systolic (PAS) (-17% and -19%) and diastolic (PAD) blood pressure (-38% and -39%), serum glucose (-37% and -30%, respectively), insulinemia (-55% and -74%, respectively), serum and hepatic total lipids, triglycerides, total cholesterol levels, as well as the total cholesterol concentration of low and very low density lipoproteins. The same, atherogenicity ratios and membrane fluidity decreased in the WGA and PLS vs HFD while lecithin: cholesterol acyltransferase (LCAT) activity increased (51 and 41% respectively). Ulva lactuca and its polysaccharides, one of the bioactive compounds of this macroalga, seem to have hypotensive, hypoglycemic, hypolipaemic and antiatherogenic properties that can correct or prevent certain cardiovascular complications linked to a high fat diet. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369

Molecular characterization of the NADPH oxidase complex in the ergot fungus Claviceps purpurea: CpNox2 and CpPls1 are important for a balanced host-pathogen interaction.

PubMed

Schürmann, Janine; Buttermann, Dagmar; Herrmann, Andrea; Giesbert, Sabine; Tudzynski, Paul

2013-10-01

Reactive oxygen species producing NADPH oxidase (Nox) complexes are involved in defense reactions in animals and plants while they trigger infection-related processes in pathogenic fungi. Knowledge about the composition and localization of these complexes in fungi is limited; potential components identified thus far include two to three catalytical subunits, a regulatory subunit (NoxR), the GTPase Rac, the scaffold protein Bem1, and a tetraspanin-like membrane protein (Pls1). We showed that, in the biotrophic grass-pathogen Claviceps purpurea, the catalytical subunit CpNox1 is important for infection. Here, we present identification of major Nox complex partners and a functional analysis of CpNox2 and the tetraspanin CpPls1. We show that, as in other fungi, Nox complexes are important for formation of sclerotia; CpRac is, indeed, a complex partner because it interacts with CpNoxR, and CpNox1/2 and CpPls1 are associated with the endoplasmatic reticulum. However, unlike in all other fungi, Δcppls1 is more similar to Δcpnox1 than to Δcpnox2, and CpNox2 is not essential for infection. In contrast, Δcpnox2 shows even more pronounced disease symptoms, indicating that Cpnox2 controls the infection process and moderates damage to the host. These data confirm that fungal Nox complexes have acquired specific functions dependent of the lifestyle of the pathogen.

The Role of Safety Culture in Influencing Provider Perceptions of Patient Safety.

PubMed

Bishop, Andrea C; Boyle, Todd A

2016-12-01

To determine how provider perceptions of safety culture influence their involvement in patient safety practices. Health-care providers were surveyed in 2 tertiary hospitals located in Atlantic Canada, composed of 4 units in total. The partial least squares (PLS) approach to structural equation modeling was used to analyze the data. Latent variables provider PLS model encompassed the hypothesized relationships between provider characteristics, safety culture, perceptions of patient safety practices, and actual performance of patient safety practices, using the Health Belief Model (HBM) as a guide. Data analysis was conducted using SmartPLS. A total of 113 health-care providers completed a survey out of an eligible 318, representing a response rate of 35.5%. The final PLS model showed acceptable internal consistency with all four latent variables having a composite reliability score above the recommended 0.70 cutoff value (safety culture = 0.86, threat = 0.76, expectations = 0.83, PS practices = 0.75). Discriminant validity was established, and all path coefficients were found to be significant at the α = 0.05 level using nonparametric bootstrapping. The survey results show that safety culture accounted for 34% of the variance in perceptions of threat and 42% of the variance in expectations. This research supports the role that safety culture plays in the promotion and maintenance of patient safety activities for health-care providers. As such, it is recommended that the introduction of new patient safety strategies follow a thorough exploration of an organization's safety culture.

Loss of ERLIN2 function leads to juvenile primary lateral sclerosis.

PubMed

Al-Saif, Amr; Bohlega, Saeed; Al-Mohanna, Futwan

2012-10-01

Primary lateral sclerosis (PLS) is a motor neuron disorder that exclusively affects upper motor neurons leading to their degeneration. Mutations in the ALS2 gene encoding the protein Alsin have been described previously in the juvenile form of the disease. In this study, we identify mutation of the ERLIN2 gene in juvenile PLS patients and describe an in vitro model for loss of ERLIN2 function. Single nucleotide polymorphism arrays were used for homozygosity mapping. DNA sequencing of candidate genes was used to detect the underlying mutation. Level of ERLIN2 mRNA was measured by quantitative real time polymerase chain reaction. Knocking down ERLIN2 in NSC34 cells was accomplished by short-hairpin RNA interference. We identified a splice junction mutation in the ERLIN2 gene-a component of the endoplasmic reticulum (ER) lipid rafts-that resulted in abnormal splicing of ERLIN2 transcript and nonsense-mediated decay of ERLIN2 mRNA. Knocking down ERLIN2 in NSC34 cells suppressed their growth in culture. Recently, we found that mutation of SIGMAR1, a component of ER lipid rafts, leads to juvenile amyotrophic lateral sclerosis. The identification of mutation in another component of the ER lipid rafts in juvenile PLS patients emphasizes their role in motor neuron function. Furthermore, the discovered effect of ERLIN2 loss on cell growth may advance understanding of the mechanism behind motor neuron degeneration in PLS. Copyright © 2012 American Neurological Association.

Simultaneous quantification of Aroclor mixtures in soil samples by gas chromatography/mass spectrometry with solid phase microextraction using partial least-squares regression.

PubMed

Zhang, Mengliang; Harrington, Peter de B

2015-01-01

Multivariate partial least-squares (PLS) method was applied to the quantification of two complex polychlorinated biphenyls (PCBs) commercial mixtures, Aroclor 1254 and 1260, in a soil matrix. PCBs in soil samples were extracted by headspace solid phase microextraction (SPME) and determined by gas chromatography/mass spectrometry (GC/MS). Decachlorinated biphenyl (deca-CB) was used as internal standard. After the baseline correction was applied, four data representations including extracted ion chromatograms (EIC) for Aroclor 1254, EIC for Aroclor 1260, EIC for both Aroclors and two-way data sets were constructed for PLS-1 and PLS-2 calibrations and evaluated with respect to quantitative prediction accuracy. The PLS model was optimized with respect to the number of latent variables using cross validation of the calibration data set. The validation of the method was performed with certified soil samples and real field soil samples and the predicted concentrations for both Aroclors using EIC data sets agreed with the certified values. The linear range of the method was from 10μgkg(-1) to 1000μgkg(-1) for both Aroclor 1254 and 1260 in soil matrices and the detection limit was 4μgkg(-1) for Aroclor 1254 and 6μgkg(-1) for Aroclor 1260. This holistic approach for the determination of mixtures of complex samples has broad application to environmental forensics and modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Antiphospholipid antibodies promote tissue factor-dependent angiogenic switch and tumor progression.

PubMed

Wu, Yuan-Yuan; V Nguyen, Andrew; Wu, Xiao-Xuan; Loh, Mingyu; Vu, Michelle; Zou, Yiyu; Liu, Qiang; Guo, Peng; Wang, Yanhua; Montgomery, Leslie L; Orlofsky, Amos; Rand, Jacob H; Lin, Elaine Y

2014-12-01

Progression to an angiogenic state is a critical event in tumor development, yet few patient characteristics have been identified that can be mechanistically linked to this transition. Antiphospholipid autoantibodies (aPLs) are prevalent in many human cancers and can elicit proangiogenic expression in several cell types, but their role in tumor biology is unknown. Herein, we observed that the elevation of circulating aPLs among breast cancer patients is specifically associated with invasive-stage tumors. By using multiple in vivo models of breast cancer, we demonstrated that aPL-positive IgG from patients with autoimmune disease rapidly accelerates tumor angiogenesis and consequent tumor progression, particularly in slow-growing avascular tumors. The action of aPLs was local to the tumor site and elicited leukocytic infiltration and tumor invasion. Tumor cells treated with aPL-positive IgG expressed multiple proangiogenic genes, including vascular endothelial growth factor, tissue factor (TF), and colony-stimulating factor 1. Knockdown and neutralization studies demonstrated that the effects of aPLs on tumor angiogenesis and growth were dependent on tumor cell-derived TF. Tumor-derived TF was essential for the development of pericyte coverage of tumor microvessels and aPL-induced tumor cell expression of chemokine ligand 2, a mediator of pericyte recruitment. These findings identify antiphospholipid autoantibodies as a potential patient-specific host factor promoting the transition of indolent tumors to an angiogenic malignant state through a TF-mediated pathogenic mechanism. Copyright © 2014 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using visible-NIR hyperspectral imaging.

PubMed

Moscetti, Roberto; Sturm, Barbara; Crichton, Stuart Oj; Amjad, Waseem; Massantini, Riccardo

2018-05-01

The potential of hyperspectral imaging (500-1010 nm) was evaluated for monitoring of the quality of potato slices (var. Anuschka) of 5, 7 and 9 mm thickness subjected to air drying at 50 °C. The study investigated three different feature selection methods for the prediction of dry basis moisture content and colour of potato slices using partial least squares regression (PLS). The feature selection strategies tested include interval PLS regression (iPLS), and differences and ratios between raw reflectance values for each possible pair of wavelengths (R[λ 1 ]-R[λ 2 ] and R[λ 1 ]:R[λ 2 ], respectively). Moreover, the combination of spectral and spatial domains was tested. Excellent results were obtained using the iPLS algorithm. However, features from both datasets of raw reflectance differences and ratios represent suitable alternatives for development of low-complex prediction models. Finally, the dry basis moisture content was high accurately predicted by combining spectral data (i.e. R[511 nm]-R[994 nm]) and spatial domain (i.e. relative area shrinkage of slice). Modelling the data acquired during drying through hyperspectral imaging can provide useful information concerning the chemical and physicochemical changes of the product. With all this information, the proposed approach lays the foundations for a more efficient smart dryer that can be designed and its process optimized for drying of potato slices. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Characterizing the proton loading site in cytochrome c oxidase.

PubMed

Lu, Jianxun; Gunner, M R

2014-08-26

Cytochrome c oxidase (CcO) uses the energy released by reduction of O2 to H2O to drive eight charges from the high pH to low pH side of the membrane, increasing the electrochemical gradient. Four electrons and protons are used for chemistry, while four more protons are pumped. Proton pumping requires that residues on a pathway change proton affinity through the reaction cycle to load and then release protons. The protonation states of all residues in CcO are determined in MultiConformational Continuum Electrostatics simulations with the protonation and redox states of heme a, a3, Cu(B), Y288, and E286 used to define the catalytic cycle. One proton is found to be loaded and released from residues identified as the proton loading site (PLS) on the P-side of the protein in each of the four CcO redox states. Thus, the same proton pumping mechanism can be used each time CcO is reduced. Calculations with structures of Rhodobacter sphaeroides, Paracoccus denitrificans, and bovine CcO derived by crystallography and molecular dynamics show the PLS functions similarly in different CcO species. The PLS is a cluster rather than a single residue, as different structures show 1-4 residues load and release protons. However, the proton affinity of the heme a3 propionic acids primarily determines the number of protons loaded into the PLS; if their proton affinity is too low, less than one proton is loaded.

Characterizing the proton loading site in cytochrome c oxidase

PubMed Central

Lu, Jianxun; Gunner, M. R.

2014-01-01

Cytochrome c oxidase (CcO) uses the energy released by reduction of O2 to H2O to drive eight charges from the high pH to low pH side of the membrane, increasing the electrochemical gradient. Four electrons and protons are used for chemistry, while four more protons are pumped. Proton pumping requires that residues on a pathway change proton affinity through the reaction cycle to load and then release protons. The protonation states of all residues in CcO are determined in MultiConformational Continuum Electrostatics simulations with the protonation and redox states of heme a, a3, CuB, Y288, and E286 used to define the catalytic cycle. One proton is found to be loaded and released from residues identified as the proton loading site (PLS) on the P-side of the protein in each of the four CcO redox states. Thus, the same proton pumping mechanism can be used each time CcO is reduced. Calculations with structures of Rhodobacter sphaeroides, Paracoccus denitrificans, and bovine CcO derived by crystallography and molecular dynamics show the PLS functions similarly in different CcO species. The PLS is a cluster rather than a single residue, as different structures show 1–4 residues load and release protons. However, the proton affinity of the heme a3 propionic acids primarily determines the number of protons loaded into the PLS; if their proton affinity is too low, less than one proton is loaded. PMID:25114210

Separation of motor oils, oily wastes and hydrocarbons from contaminated water by sorption on chrome shavings.

PubMed

Gammoun, A; Tahiri, S; Albizane, A; Azzi, M; Moros, J; Garrigues, S; de la Guardia, M

2007-06-25

In this paper, the ability of chrome shavings to remove motor oils, oily wastes and hydrocarbons from water has been studied. To determine amount of hydrocarbons sorbed on tanned wastes, a FT-NIR methodology was used and a multivariate calibration based on partial least squares (PLS) was employed for data treatment. The light density, porous tanned waste granules float on the surface of water and remove hydrocarbons and oil films. Wastes fibers from tannery industry have high sorption capacity. These tanned solid wastes are capable of absorbing many times their weight in oil or hydrocarbons (6.5-7.6g of oil and 6.3g of hydrocarbons per gram of chrome shavings). The removal efficiency of the pollutants from water is complete. The sorption of pollutants is a quasi-instantaneous process.

Volatiles Mediated Interactions Between Aspergillus oryzae Strains Modulate Morphological Transition and Exometabolomes.

PubMed

Singh, Digar; Lee, Choong H

2018-01-01

Notwithstanding its mitosporic nature, an improbable morpho-transformation state i. e., sclerotial development (SD), is vaguely known in Aspergillus oryzae . Nevertheless an intriguing phenomenon governing mold's development and stress response, the effects of exogenous factors engendering SD, especially the volatile organic compounds (VOCs) mediated interactions (VMI) pervasive in microbial niches have largely remained unexplored. Herein, we examined the effects of intra-species VMI on SD in A. oryzae RIB 40, followed by comprehensive analyses of associated growth rates, pH alterations, biochemical phenotypes, and exometabolomes. We cultivated A. oryzae RIB 40 (S1 VMI : KACC 44967) opposite a non-SD partner strain, A. oryzae (S2: KCCM 60345), conditioning VMI in a specially designed "twin plate assembly." Notably, SD in S1 VMI was delayed relative to its non-conditioned control (S1) cultivated without partner strain (S2) in twin plate. Selectively evaluating A. oryzae RIB 40 (S1 VMI vs. S1) for altered phenotypes concomitant to SD, we observed a marked disparity for corresponding growth rates (S1 VMI < S1) 7days , media pH (S1 VMI > S1) 7days , and biochemical characteristics viz ., protease (S1 VMI > S1) 7days , amylase (S1 VMI > nS1) 3-7 days , and antioxidants (S1 VMI > S1) 7days levels. The partial least squares-discriminant analysis (PLS-DA) of gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) datasets for primary metabolites exhibited a clustered pattern (PLS1, 22.04%; PLS2, 11.36%), with 7 days incubated S1 VMI extracts showed higher abundance of amino acids, sugars, and sugar alcohols with lower organic acids and fatty acids levels, relative to S1. Intriguingly, the higher amino acid and sugar alcohol levels were positively correlated with antioxidant activity, likely impeding SD in S1 VMI . Further, the PLS-DA (PLS1, 18.11%; PLS2, 15.02%) based on liquid chromatography-mass spectrometry (LC-MS) datasets exhibited a notable disparity for post-SD (9-11 days) sample extracts with higher oxylipins and 13-desoxypaxilline levels in S1 VMI relative to S1, intertwining Aspergillus morphogenesis and secondary metabolism. The analysis of VOCs for the 7 days incubated samples displayed considerably higher accumulation of C-8 compounds in the headspace of twin-plate experimental sets (S1 VMI :S2) compared to those in non-conditioned controls (S1 and S2-without respective partner strains), potentially triggering altered morpho-transformation and concurring biochemical as well as metabolic states in molds.

Method and apparatus for acquisition and tracking of light sources in a transient event rich environment

NASA Technical Reports Server (NTRS)

Bolin, Kenneth (Inventor); Flynn, David (Inventor); Fowski, Walter (Inventor); Miklus, Kenneth (Inventor); Kissh, Frank (Inventor); Abreu, Rene (Inventor)

1993-01-01

A method and apparatus for tracking a light source in a transient event rich environment locks on to a light source incident on a field-of-view 1 of a charge-coupled-device (CCD) array 6, validates the permanence of said light source and transmits data relating to the brilliance and location of said light source if said light source is determined to be permanent.

Non-contact pumping of light emitters via non-radiative energy transfer

DOEpatents

Klimov, Victor I.; Achermann, Marc

2010-01-05

A light emitting device is disclosed including a primary light source having a defined emission photon energy output, and, a light emitting material situated near to said primary light source, said light emitting material having an absorption onset equal to or less in photon energy than the emission photon energy output of the primary light source whereby non-radiative energy transfer from said primary light source to said light emitting material can occur yielding light emission from said light emitting material.

Conceptual designs study for a Personnel Launch System (PLS)

NASA Technical Reports Server (NTRS)

Wetzel, E. D.

1990-01-01

A series of conceptual designs for a manned, Earth to Low Earth Orbit transportation system was developed. Non-winged, low L/D vehicle shapes are discussed. System and subsystem trades emphasized safety, operability, and affordability using near-term technology. The resultant conceptual design includes lessons learned from commercial aviation that result in a safe, routine, operationally efficient system. The primary mission for this Personnel Launch System (PLS) would be crew rotation to the SSF; other missions, including satellite servicing, orbital sortie, and space rescue were also explored.

Genetic and Physiological Studies of Bacillus Anthracis Related to Development of an Improved Vaccine

DTIC Science & Technology

1990-07-01

charartorization of the conjugative pl&a.dd, PLS2O, of Baci~llu sbtllis ( natto ) amd its ability to tranisfer pla&iuids v" iitrains of B. inthraci~s, B...2-r-ich atms;hwre. A smll amount of effort wa spent on further’ characterization of the Bacillus subtilis ( natto ) fertility plasmid. pLS2I, which...previously cured of pX02. All transcipients that inherited the pXO2::Tn9l7 derivatives exhibited the donor phenotype. The 64.2-kb Bacillus subtilis ( natto

Screening soy hydrolysates for the production of a recombinant therapeutic protein in commercial cell line by combined approach of near-infrared spectroscopy and chemometrics.

PubMed

Li, Guiyang; Wen, Zai-Qing

2013-03-01

Soy hydrolysates are widely used as the major nutrient sources for cell culture processes for industrial manufacturing of therapeutic recombinant proteins. The primary goal of this study was to develop a spectroscopy based chemometric method, a partial least squares (PLS), to screen soy hydrolysates for better yield of protein production (titers) in cell culture medium. Harvest titer values of 29 soy hydrolysate lots with production yield between 490 and 1,350 mg/L were obtained from shake flask models or from manufacture engineering runs. The soy hydrolysate samples were measured by near-infrared (NIR) in reflectance mode using an infrared fiber optic probe. The fiber optic probe could easily enable in situ measurement of the soy hydrolysates for convenient raw material screening. The best PLS calibration has a determination coefficient of R (2) = 0.887 utilizing no spectral preprocessing, the two spectral ranges of 10,000-5,376 cm(-1) and 4,980-4,484 cm(-1), and a rank of 6 factors. The cross-validation of the model resulted in a determination coefficient of R (2) = 0.741 between the predicted and actual titer values with an average standard deviation of 72 mg/L. Compared with the resource demanding shake flask model, the combination of NIR and chemometric modeling provides a convenient method for soy hydrolysate screening with the advantage of fast speed, low cost and non-destructive.

Source Attribution of Cyanides Using Anionic Impurity Profiling, Stable Isotope Ratios, Trace Elemental Analysis and Chemometrics.

PubMed

Mirjankar, Nikhil S; Fraga, Carlos G; Carman, April J; Moran, James J

2016-02-02

Chemical attribution signatures (CAS) for chemical threat agents (CTAs), such as cyanides, are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. Herein, stocks of KCN and NaCN were analyzed for trace anions by high performance ion chromatography (HPIC), carbon stable isotope ratio (δ(13)C) by isotope ratio mass spectrometry (IRMS), and trace elements by inductively coupled plasma optical emission spectroscopy (ICP-OES). The collected analytical data were evaluated using hierarchical cluster analysis (HCA), Fisher-ratio (F-ratio), interval partial least-squares (iPLS), genetic algorithm-based partial least-squares (GAPLS), partial least-squares discriminant analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminant analysis (SVMDA). HCA of anion impurity profiles from multiple cyanide stocks from six reported countries of origin resulted in cyanide samples clustering into three groups, independent of the associated alkali metal (K or Na). The three groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries each having one known solid cyanide factory: Czech Republic, Germany, and United States. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). Classification errors for two validation studies using anion impurity profiles collected over five years on different instruments were as low as zero for KNN and SVMDA, demonstrating the excellent reliability associated with using anion impurities for matching a cyanide sample to its factory using our current cyanide stocks. Variable selection methods reduced errors for those classification methods having errors greater than zero; iPLS-forward selection and F-ratio typically provided the lowest errors. Finally, using anion profiles to classify cyanides to a specific stock or stock group for a subset of United States stocks resulted in cross-validation errors ranging from 0 to 5.3%.

Quantification of microwave-induced amorphization of celecoxib in PVP tablets using transmission Raman spectroscopy.

PubMed

Edinger, Magnus; Knopp, Matthias Manne; Kerdoncuff, Hugo; Rantanen, Jukka; Rades, Thomas; Löbmann, Korbinian

2018-05-30

In this study, the influence of drug load on the microwave-induced amorphization of celecoxib (CCX) in polyvinylpyrrolidone (PVP) tablets was investigated using quantitative transmission Raman spectroscopy. A design of experiments (DoE) setup was applied for developing the quantitative model using two factors: drug load (10, 30, and 50% w/w) and amorphous fraction (0, 25, 50, 75 and 100%). The data was modeled using partial least-squares (PLS) regression and resulted in a robust model with a root mean-square error of prediction of 2.5%. The PLS model was used to study the amorphization kinetics of CCX-PVP tablets with different drug content (10, 20, 30, 40 and 50% w/w). For this purpose, transition Raman spectra were collected in 60 s intervals over a total microwave time of 10 min with an energy input of 1000 W. Using the quantitative model it was possible to measure the amorphous fraction of the tablets and follow the amorphization as a function of microwaving time. The relative amorphous fraction of CCX increased with increasing microwaving time and decreasing drug load, hence 90 ± 7% of the drug was amorphized in the tablets with 10% drug load whereas only 31 ± 7% of the drug was amorphized in the 50% CCX tablets. It is suggested that the degree of amorphization depends on drug loading. The likelihood of drug particles being in direct contact with the polymer PVP is a requirement for the dissolution of the drug into the polymer upon microwaving, and this is reduced with increasing drug load. This was further supported by polarized light microscopy that revealed evidence of crystalline particles and clusters in all the microwaved tablets. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera)

PubMed Central

Zhi, Yao; Taylor, Matthew C.; Campbell, Peter M.; Warden, Andrew C.; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R.; White, Rosemary G.; Chen, Wenli; Singh, Surinder P.; Liu, Qing

2017-01-01

Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera. Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues. PMID:28824675

Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera).

PubMed

Zhi, Yao; Taylor, Matthew C; Campbell, Peter M; Warden, Andrew C; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R; White, Rosemary G; Chen, Wenli; Singh, Surinder P; Liu, Qing

2017-01-01

Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera . Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues.

Seized cannabis seeds cultivated in greenhouse: A chemical study by gas chromatography-mass spectrometry and chemometric analysis.

PubMed

Mariotti, Kristiane de Cássia; Marcelo, Marcelo Caetano Alexandre; Ortiz, Rafael S; Borille, Bruna Tassi; Dos Reis, Monique; Fett, Mauro Sander; Ferrão, Marco Flôres; Limberger, Renata Pereira

2016-01-01

Cannabis sativa L. is cultivated in most regions of the world. In 2013, the Brazilian Federal Police (BFP) reported 220 tons of marijuana seized and about 800,000 cannabis plants eradicated. Efforts to eradicate cannabis production may have contributed to the development of a new form of international drug trafficking in Brazil: the sending of cannabis seeds in small amounts to urban centers by logistics postal. This new and increasing panorama of cannabis trafficking in Brazil, encouraged the chemical study of cannabis seeds cultivated in greenhouses by gas-chromatography coupled with mass spectrometry (GC-MS) associated with exploratory and discriminant analysis. Fifty cannabis seeds of different varieties and brands, seized by the BFP were cultivated under predefined conditions for a period of 4.5 weeks, 5.5 weeks, 7.5 weeks, 10 weeks and 12 weeks. Aerial parts were analyzed and cannabigerol, cannabinol, cannabidiol, cannabichromene Δ9-tetrahydrocannabinol (THC) and other terpenoids were detected. The chromatographic chemical profiles of the samples were significantly different, probably due to different variety, light exposition and age. THC content increased with the age of the plant, however, for other cannabinoids, this correlation was not observed. The chromatograms were plotted in a matrix with 50 rows (samples) and 3886 columns (abundance in a retention time) and submitted to PCA, HCA and PLS-DA after pretreatment (normalization, first derivative and autoscale). The PCA and HCA showed age separation between samples however it was not possible to verify the separation by varieties and brands. The PLS-DA classification provides a satisfactory prediction of plant age. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

A(1)H NMR-based metabonomic study on the SAMP8 and SAMR1 mice and the effect of electro-acupuncture.

PubMed

Qiao-feng, Wu; Ling-ling, Guo; Shu-guang, Yu; Qi, Zhang; Sheng-feng, Lu; Fang, Zeng; Hai-yan, Yin; Yong, Tang; Xian-zhong, Yan

2011-10-01

A (1)H NMR-based metabonomic method was used to investigate the metabolic change of plasma in senescence-prone 8 (SAMP8) mice before and after electro-acupuncture (EA). Sixteen SAMP8 male mice (aged 8 months) were randomly divided into model group and acupuncture treatment group while the later group received EA treatment for 21 days. Eight senescence-resistant 1 (SAMR1) mice were used as the control group. Morris water maze was used to evaluate the effects of EA. All mice plasma samples obtained from different groups were analyzed by using 600 MHz (1)H nuclear magnetic resonances ((1)H NMR) spectroscopy. The data sets were analyzed by Principal Components Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) to discriminate the key plasma metabolites among different groups. Results indicated that both the escape and probe tasks of SAMP8 could be improved by EA treatment. Metabonomic study showed that SAMR1 and SAMP8 were separated clearly in both CPMG_OSC_PLS and LED _OSC_PLS score plots. Interestingly, samples obtained from EA group were distributed closely to SAMR1 group in CPMG_OSC_PLS score plot, but away from SAMP8 group in LED_OSC_PLS score plot. Corresponding loading plots showed that much less lactate was seen in SAMP8 mice plasma. Other changes including higher levels of dimethylamine (DMA) Choline and α-glucose but lower levels of leucine/isoleucine, HDL, LDL/VLDL, 3-Hydroxybutyrate (3-HB), and Trimethylamine N-oxide (TMAO) were observed in the SAMP8 mice plasma than in the SAMR1. After EA treatment, the levels of lactate, DMA, choline and TMAO were improved. Results of this work can provide valuable clues to the understanding of the metabolic changes in the senile impairment of mice. It is also hoped that the methodology can be used in evaluating the effects of EA and understanding the underlying acupuncture mechanism in treating neurodegenerative diseases. Copyright © 2011 Elsevier Inc. All rights reserved.

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in Sorghum bicolor

PubMed Central

2013-01-01

Background A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency. Results A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R 2 ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R 2 of 0.94 and RMSEP of 0.64 μg.mgDW-1.h-1. Conclusions This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential. PMID:24365407

Exposure to mixtures of organohalogen contaminants and associative interactions with thyroid hormones in East Greenland polar bears (Ursus maritimus).

PubMed

Villanger, Gro D; Jenssen, Bjørn M; Fjeldberg, Rita R; Letcher, Robert J; Muir, Derek C G; Kirkegaard, Maja; Sonne, Christian; Dietz, Rune

2011-05-01

We investigated the multivariate relationships between adipose tissue residue levels of 48 individual organohalogen contaminants (OHCs) and circulating thyroid hormone (TH) levels in polar bears (Ursus maritimus) from East Greenland (1999-2001, n=62), using projection to latent structure (PLS) regression for four groupings of polar bears; subadults (SubA), adult females with cubs (AdF_N), adult females without cubs (AdF_S) and adult males (AdM). In the resulting significant PLS models for SubA, AdF_N and AdF_S, some OHCs were especially important in explaining variations in circulating TH levels: polybrominated diphenylether (PBDE)-99, PBDE-100, PBDE-153, polychlorinated biphenyl (PCB)-52, PCB-118, cis-nonachlor, trans-nonachlor, trichlorobenzene (TCB) and pentachlorobenzene (QCB), and both negative and positive relationships with THs were found. In addition, the models revealed that DDTs had a positive influence on total 3,5,3'-triiodothyronine (TT3) in AdF_S, and that a group of 17 higher chlorinated ortho-PCBs had a positive influence on total 3,5,3',5'-tetraiodothyronine (thyroxine, TT4) in AdF_N. TH levels in AdM seemed less influenced by OHCs because of non-significant PLS models. TH levels were also influenced by biological factors such as age, sex, body size, lipid content of adipose tissue and sampling date. When controlling for biological variables, the major relationships from the PLS models for SubA, AdF_N and AdF_S were found significant in partial correlations. The most important OHCs that influenced TH levels in the significant PLS models may potentially act through similar mechanisms on the hypothalamic-pituitary-thyroid (HPT) axis, suggesting that both combined effects by dose and response addition and perhaps synergistic potentiation may be a possibility in these polar bears. Statistical associations are not evidence per se of biological cause-effect relationships. Still, the results of the present study indicate that OHCs may affect circulating TH levels in East Greenland polar bears, adding to the "weight of evidence" suggesting that OHCs might interfere with thyroid homeostasis in polar bears. Copyright © 2011 Elsevier Ltd. All rights reserved.

The role of disappeared disturbances in driving the North American prairie-forest boundary

NASA Astrophysics Data System (ADS)

Heilman, K.; McLachlan, J. S.; Staver, A. C.

2016-12-01

Globally, transitions from savanna to forest are often characterized by abrupt changes in tree density that cannot be fully explained by climate and edaphic factors. In the tropics, fire-vegetation feedbacks drive a bimodal distribution in tree cover that leads to alternative forest and savanna stable states within the same climate space. In temperate North America, the pre-European settlement prairie-forest transition has also been hypothesized to be influenced by widespread fires (anthropogenic or natural). However, large scale evidence for fire disturbance feedbacks on tree density in the temperate zone is currently lacking. We investigate both the pre-European and modern tree density along the North American prairie-forest boundary. We hypothesized that the pre-European distribution of tree density was distinctly bimodal due to intact vegetation-disturbance feedbacks along the prairie-forest boundary before settlement, but that fragmentation and fire suppression has produced a modern prairie-forest boundary that is less abrupt and less bimodal. We estimated tree density from aggregated Public Land Survey (PLS) data collected before the time of European agricultural settlement in Minnesota, Wisconsin, Michigan, Indiana, and Illinois and compared PLS density distributions to tree density estimated from modern USFS Forest Inventory Analysis (FIA) data. PLS tree density follows a bimodal distribution that abruptly shifts from savanna to forest at the boundary. Only 15% of the variance in pre-settlement tree density is explained by historical Mean Annual Precipitation (MAP), suggesting that the bimodality may be due to internal feedbacks in the vegetation-disturbance system, rather than to the past underlying environmental gradient. On the modern landscape, MAP explains 6% of FIA tree density variance, and tree density is not bimodal. Regions that had low tree density savannas in the PLS era have significantly increased in tree density, suggesting that the disappearance of disturbances that accompanied agricultural settlement resulted in closed forests where savannas were once an alternative stable state (p < 0.01). Additionally, the once high tree density forests in the PLS have significantly declined in density, suggesting that logging has contributed to land cover change in North America.

Batch statistical process control of a fluid bed granulation process using in-line spatial filter velocimetry and product temperature measurements.

PubMed

Burggraeve, A; Van den Kerkhof, T; Hellings, M; Remon, J P; Vervaet, C; De Beer, T

2011-04-18

Fluid bed granulation is a batch process, which is characterized by the processing of raw materials for a predefined period of time, consisting of a fixed spraying phase and a subsequent drying period. The present study shows the multivariate statistical modeling and control of a fluid bed granulation process based on in-line particle size distribution (PSD) measurements (using spatial filter velocimetry) combined with continuous product temperature registration using a partial least squares (PLS) approach. Via the continuous in-line monitoring of the PSD and product temperature during granulation of various reference batches, a statistical batch model was developed allowing the real-time evaluation and acceptance or rejection of future batches. Continuously monitored PSD and product temperature process data of 10 reference batches (X-data) were used to develop a reference batch PLS model, regressing the X-data versus the batch process time (Y-data). Two PLS components captured 98.8% of the variation in the X-data block. Score control charts in which the average batch trajectory and upper and lower control limits are displayed were developed. Next, these control charts were used to monitor 4 new test batches in real-time and to immediately detect any deviations from the expected batch trajectory. By real-time evaluation of new batches using the developed control charts and by computation of contribution plots of deviating process behavior at a certain time point, batch losses or reprocessing can be prevented. Immediately after batch completion, all PSD and product temperature information (i.e., a batch progress fingerprint) was used to estimate some granule properties (density and flowability) at an early stage, which can improve batch release time. Individual PLS models relating the computed scores (X) of the reference PLS model (based on the 10 reference batches) and the density, respectively, flowabililty as Y-matrix, were developed. The scores of the 4 test batches were used to examine the predictive ability of the model. Copyright © 2011 Elsevier B.V. All rights reserved.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

A statistical framework to model the meeting-in-the-middle principle using metabolomic data: application to hepatocellular carcinoma in the EPIC study

PubMed Central

Assi, Nada; Fages, Anne; Vineis, Paolo; Chadeau-Hyam, Marc; Stepien, Magdalena; Duarte-Salles, Talita; Byrnes, Graham; Boumaza, Houda; Knüppel, Sven; Kühn, Tilman; Palli, Domenico; Bamia, Christina; Boshuizen, Hendriek; Bonet, Catalina; Overvad, Kim; Johansson, Mattias; Travis, Ruth; Gunter, Marc J.; Lund, Eiliv; Dossus, Laure; Elena-Herrmann, Bénédicte; Riboli, Elio; Jenab, Mazda; Viallon, Vivian; Ferrari, Pietro

2015-01-01

Abstract Metabolomics is a potentially powerful tool for identification of biomarkers associated with lifestyle exposures and risk of various diseases. This is the rationale of the ‘meeting-in-the-middle’ concept, for which an analytical framework was developed in this study. In a nested case–control study on hepatocellular carcinoma (HCC) within the European Prospective Investigation into Cancer and nutrition (EPIC), serum 1H nuclear magnetic resonance (NMR) spectra (800 MHz) were acquired for 114 cases and 222 matched controls. Through partial least square (PLS) analysis, 21 lifestyle variables (the ‘predictors’, including information on diet, anthropometry and clinical characteristics) were linked to a set of 285 metabolic variables (the ‘responses’). The three resulting scores were related to HCC risk by means of conditional logistic regressions. The first PLS factor was not associated with HCC risk. The second PLS metabolomic factor was positively associated with tyrosine and glucose, and was related to a significantly increased HCC risk with OR = 1.11 (95% CI: 1.02, 1.22, P = 0.02) for a 1SD change in the responses score, and a similar association was found for the corresponding lifestyle component of the factor. The third PLS lifestyle factor was associated with lifetime alcohol consumption, hepatitis and smoking, and had negative loadings on vegetables intake. Its metabolomic counterpart displayed positive loadings on ethanol, glutamate and phenylalanine. These factors were positively and statistically significantly associated with HCC risk, with 1.37 (1.05, 1.79, P = 0.02) and 1.22 (1.04, 1.44, P = 0.01), respectively. Evidence of mediation was found in both the second and third PLS factors, where the metabolomic signals mediated the relation between the lifestyle component and HCC outcome. This study devised a way to bridge lifestyle variables to HCC risk through NMR metabolomics data. This implementation of the ‘meeting-in-the-middle’ approach finds natural applications in settings characterised by high-dimensional data, increasingly frequent in the omics generation. PMID:26130468

Augmented classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2004-02-03

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-07-26

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-01-11

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Heating device for semiconductor wafers

DOEpatents

Vosen, Steven R.

1999-01-01

An apparatus for heat treating semiconductor wafers is disclosed. The apparatus includes a heating device which contains an assembly of light energy sources for emitting light energy onto a wafer. In particular, the light energy sources are positioned such that many different radial heating zones are created on a wafer being heated. For instance, in one embodiment, the light energy sources form a spiral configuration. In an alternative embodiment, the light energy sources appear to be randomly dispersed with respect to each other so that no discernable pattern is present. In a third alternative embodiment of the present invention, the light energy sources form concentric rings. Tuning light sources are then placed in between the concentric rings of light.

Heating device for semiconductor wafers

DOEpatents

Vosen, S.R.

1999-07-27

An apparatus for heat treating semiconductor wafers is disclosed. The apparatus includes a heating device which contains an assembly of light energy sources for emitting light energy onto a wafer. In particular, the light energy sources are positioned such that many different radial heating zones are created on a wafer being heated. For instance, in one embodiment, the light energy sources form a spiral configuration. In an alternative embodiment, the light energy sources appear to be randomly dispersed with respect to each other so that no discernible pattern is present. In a third alternative embodiment of the present invention, the light energy sources form concentric rings. Tuning light sources are then placed in between the concentric rings of light. 4 figs.

[NIR Assignment of Magnolol by 2D-COS Technology and Model Application Huoxiangzhengqi Oral Liduid].

PubMed

Pei, Yan-ling; Wu, Zhi-sheng; Shi, Xin-yuan; Pan, Xiao-ning; Peng, Yan-fang; Qiao, Yan-jiang

2015-08-01

Near infrared (NIR) spectroscopy assignment of Magnolol was performed using deuterated chloroform solvent and two-dimensional correlation spectroscopy (2D-COS) technology. According to the synchronous spectra of deuterated chloroform solvent and Magnolol, 1365~1455, 1600~1720, 2000~2181 and 2275~2465 nm were the characteristic absorption of Magnolol. Connected with the structure of Magnolol, 1440 nm was the stretching vibration of phenolic group O-H, 1679 nm was the stretching vibration of aryl and methyl which connected with aryl, 2117, 2304, 2339 and 2370 nm were the combination of the stretching vibration, bending vibration and deformation vibration for aryl C-H, 2445 nm were the bending vibration of methyl which linked with aryl group, these bands attribut to the characteristics of Magnolol. Huoxiangzhengqi Oral Liduid was adopted to study the Magnolol, the characteristic band by spectral assignment and the band by interval Partial Least Squares (iPLS) and Synergy interval Partial Least Squares (SiPLS) were used to establish Partial Least Squares (PLS) quantitative model, the coefficient of determination Rcal(2) and Rpre(2) were greater than 0.99, the Root Mean of Square Error of Calibration (RM-SEC), Root Mean of Square Error of Cross Validation (RMSECV) and Root Mean of Square Error of Prediction (RMSEP) were very small. It indicated that the characteristic band by spectral assignment has the same results with the Chemometrics in PLS model. It provided a reference for NIR spectral assignment of chemical compositions in Chinese Materia Medica, and the band filters of NIR were interpreted.

Differences in chewing sounds of dry-crisp snacks by multivariate data analysis

NASA Astrophysics Data System (ADS)

De Belie, N.; Sivertsvik, M.; De Baerdemaeker, J.

2003-09-01

Chewing sounds of different types of dry-crisp snacks (two types of potato chips, prawn crackers, cornflakes and low calorie snacks from extruded starch) were analysed to assess differences in sound emission patterns. The emitted sounds were recorded by a microphone placed over the ear canal. The first bite and the first subsequent chew were selected from the time signal and a fast Fourier transformation provided the power spectra. Different multivariate analysis techniques were used for classification of the snack groups. This included principal component analysis (PCA) and unfold partial least-squares (PLS) algorithms, as well as multi-way techniques such as three-way PLS, three-way PCA (Tucker3), and parallel factor analysis (PARAFAC) on the first bite and subsequent chew. The models were evaluated by calculating the classification errors and the root mean square error of prediction (RMSEP) for independent validation sets. It appeared that the logarithm of the power spectra obtained from the chewing sounds could be used successfully to distinguish the different snack groups. When different chewers were used, recalibration of the models was necessary. Multi-way models distinguished better between chewing sounds of different snack groups than PCA on bite or chew separately and than unfold PLS. From all three-way models applied, N-PLS with three components showed the best classification capabilities, resulting in classification errors of 14-18%. The major amount of incorrect classifications was due to one type of potato chips that had a very irregular shape, resulting in a wide variation of the emitted sounds.

Exploration of attenuated total reflectance mid-infrared spectroscopy and multivariate calibration to measure immunoglobulin G in human sera.

PubMed

Hou, Siyuan; Riley, Christopher B; Mitchell, Cynthia A; Shaw, R Anthony; Bryanton, Janet; Bigsby, Kathryn; McClure, J Trenton

2015-09-01

Immunoglobulin G (IgG) is crucial for the protection of the host from invasive pathogens. Due to its importance for human health, tools that enable the monitoring of IgG levels are highly desired. Consequently there is a need for methods to determine the IgG concentration that are simple, rapid, and inexpensive. This work explored the potential of attenuated total reflectance (ATR) infrared spectroscopy as a method to determine IgG concentrations in human serum samples. Venous blood samples were collected from adults and children, and from the umbilical cord of newborns. The serum was harvested and tested using ATR infrared spectroscopy. Partial least squares (PLS) regression provided the basis to develop the new analytical methods. Three PLS calibrations were determined: one for the combined set of the venous and umbilical cord serum samples, the second for only the umbilical cord samples, and the third for only the venous samples. The number of PLS factors was chosen by critical evaluation of Monte Carlo-based cross validation results. The predictive performance for each PLS calibration was evaluated using the Pearson correlation coefficient, scatter plot and Bland-Altman plot, and percent deviations for independent prediction sets. The repeatability was evaluated by standard deviation and relative standard deviation. The results showed that ATR infrared spectroscopy is potentially a simple, quick, and inexpensive method to measure IgG concentrations in human serum samples. The results also showed that it is possible to build a united calibration curve for the umbilical cord and the venous samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterization of human breast cancer tissues by infrared imaging.

PubMed

Verdonck, M; Denayer, A; Delvaux, B; Garaud, S; De Wind, R; Desmedt, C; Sotiriou, C; Willard-Gallo, K; Goormaghtigh, E

2016-01-21

Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.

Selection of molecular descriptors with artificial intelligence for the understanding of HIV-1 protease peptidomimetic inhibitors-activity.

PubMed

Sirois, S; Tsoukas, C M; Chou, Kuo-Chen; Wei, Dongqing; Boucher, C; Hatzakis, G E

2005-03-01

Quantitative Structure Activity Relationship (QSAR) techniques are used routinely by computational chemists in drug discovery and development to analyze datasets of compounds. Quantitative numerical methods like Partial Least Squares (PLS) and Artificial Neural Networks (ANN) have been used on QSAR to establish correlations between molecular properties and bioactivity. However, ANN may be advantageous over PLS because it considers the interrelations of the modeled variables. This study focused on the HIV-1 Protease (HIV-1 Pr) inhibitors belonging to the peptidomimetic class of compounds. The main objective was to select molecular descriptors with the best predictive value for antiviral potency (Ki). PLS and ANN were used to predict Ki activity of HIV-1 Pr inhibitors and the results were compared. To address the issue of dimensionality reduction, Genetic Algorithms (GA) were used for variable selection and their performance was compared against that of ANN. Finally, the structure of the optimum ANN achieving the highest Pearson's-R coefficient was determined. On the basis of Pearson's-R, PLS and ANN were compared to determine which exhibits maximum performance. Training and validation of models was performed on 15 random split sets of the master dataset consisted of 231 compounds. For each compound 192 molecular descriptors were considered. The molecular structure and constant of inhibition (Ki) were selected from the NIAID database. Study findings suggested that non-covalent interactions such as hydrophobicity, shape and hydrogen bonding describe well the antiviral activity of the HIV-1 Pr compounds. The significance of lipophilicity and relationship to HIV-1 associated hyperlipidemia and lipodystrophy syndrome warrant further investigation.

Novel function of vitamin E in regulation of zebrafish (Danio rerio) brain lysophospholipids discovered using lipidomics

PubMed Central

Choi, Jaewoo; Leonard, Scott W.; Kasper, Katherine; McDougall, Melissa; Stevens, Jan F.; Tanguay, Robert L.; Traber, Maret G.

2015-01-01

We hypothesized that brains from vitamin E-deficient (E−) zebrafish (Danio rerio) would undergo increased lipid peroxidation because they contain highly polyunsaturated fatty acids, thus susceptible lipids could be identified. Brains from zebrafish fed for 9 months defined diets without (E−) or with (E+) added vitamin E (500 mg RRR-α-tocopheryl acetate per kilogram diet) were studied. Using an untargeted approach, 1-hexadecanoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine [DHA-PC 38:6, PC 16:0/22:6]was the lipid that showed the most significant and greatest fold-differences between groups. DHA-PC concentrations were approximately 1/3 lower in E− (4.3 ± 0.6 mg/g) compared with E+ brains (6.5 ± 0.9 mg/g, mean ± SEM, n = 10 per group, P = 0.04). Using lipidomics, 155 lipids in brain extracts were identified. Only four phospholipids (PLs) were different (P < 0.05) between groups; they were lower in E− brains and contained DHA with DHA-PC 38:6 at the highest abundances. Moreover, hydroxy-DHA-PC 38:6 was increased in E− brains (P = 0.0341) supporting the hypothesis of DHA peroxidation. More striking was the depletion in E− brains of nearly 60% of 19 different lysophospholipids (lysoPLs) (combined P = 0.0003), which are critical for membrane PL remodeling. Thus, E− brains contained fewer DHA-PLs, more hydroxy-DHA-PCs, and fewer lysoPLs, suggesting that lipid peroxidation depletes membrane DHA-PC and homeostatic mechanisms to repair the damage resulting in lysoPL depletion. PMID:25855633

[Rapid determination of COD in aquaculture water based on LS-SVM with ultraviolet/visible spectroscopy].

PubMed

Liu, Xue-Mei; Zhang, Hai-Liang

2014-10-01

Ultraviolet/visible (UV/Vis) spectroscopy was studied for the rapid determination of chemical oxygen demand (COD), which was an indicator to measure the concentration of organic matter in aquaculture water. In order to reduce the influence of the absolute noises of the spectra, the extracted 135 absorbance spectra were preprocessed by Savitzky-Golay smoothing (SG), EMD, and wavelet transform (WT) methods. The preprocessed spectra were then used to select latent variables (LVs) by partial least squares (PLS) methods. Partial least squares (PLS) was used to build models with the full spectra, and back- propagation neural network (BPNN) and least square support vector machine (LS-SVM) were applied to build models with the selected LVs. The overall results showed that BPNN and LS-SVM models performed better than PLS models, and the LS-SVM models with LVs based on WT preprocessed spectra obtained the best results with the determination coefficient (r2) and RMSE being 0. 83 and 14. 78 mg · L(-1) for calibration set, and 0.82 and 14.82 mg · L(-1) for the prediction set respectively. The method showed the best performance in LS-SVM model. The results indicated that it was feasible to use UV/Vis with LVs which were obtained by PLS method, combined with LS-SVM calibration could be applied to the rapid and accurate determination of COD in aquaculture water. Moreover, this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters.

A multiple hold-out framework for Sparse Partial Least Squares.

PubMed

Monteiro, João M; Rao, Anil; Shawe-Taylor, John; Mourão-Miranda, Janaina

2016-09-15

Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (SPLS), may provide insights into the brain's mechanisms by finding relationships between neuroimaging and clinical/demographic data. The identification of these relationships has the potential to improve the current understanding of disease mechanisms, refine clinical assessment tools, and stratify patients. SPLS finds multivariate associative effects in the data by computing pairs of sparse weight vectors, where each pair is used to remove its corresponding associative effect from the data by matrix deflation, before computing additional pairs. We propose a novel SPLS framework which selects the adequate number of voxels and clinical variables to describe each associative effect, and tests their reliability by fitting the model to different splits of the data. As a proof of concept, the approach was applied to find associations between grey matter probability maps and individual items of the Mini-Mental State Examination (MMSE) in a clinical sample with various degrees of dementia. The framework found two statistically significant associative effects between subsets of brain voxels and subsets of the questions/tasks. SPLS was compared with its non-sparse version (PLS). The use of projection deflation versus a classical PLS deflation was also tested in both PLS and SPLS. SPLS outperformed PLS, finding statistically significant effects and providing higher correlation values in hold-out data. Moreover, projection deflation provided better results. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Novel pure component contribution, mean centering of ratio spectra and factor based algorithms for simultaneous resolution and quantification of overlapped spectral signals: An application to recently co-formulated tablets of chlorzoxazone, aceclofenac and paracetamol

NASA Astrophysics Data System (ADS)

Toubar, Safaa S.; Hegazy, Maha A.; Elshahed, Mona S.; Helmy, Marwa I.

2016-06-01

In this work, resolution and quantitation of spectral signals are achieved by several univariate and multivariate techniques. The novel pure component contribution algorithm (PCCA) along with mean centering of ratio spectra (MCR) and the factor based partial least squares (PLS) algorithms were developed for simultaneous determination of chlorzoxazone (CXZ), aceclofenac (ACF) and paracetamol (PAR) in their pure form and recently co-formulated tablets. The PCCA method allows the determination of each drug at its λmax. While, the mean centered values at 230, 302 and 253 nm, were used for quantification of CXZ, ACF and PAR, respectively, by MCR method. Partial least-squares (PLS) algorithm was applied as a multivariate calibration method. The three methods were successfully applied for determination of CXZ, ACF and PAR in pure form and tablets. Good linear relationships were obtained in the ranges of 2-50, 2-40 and 2-30 μg mL- 1 for CXZ, ACF and PAR, in order, by both PCCA and MCR, while the PLS model was built for the three compounds each in the range of 2-10 μg mL- 1. The results obtained from the proposed methods were statistically compared with a reported one. PCCA and MCR methods were validated according to ICH guidelines, while PLS method was validated by both cross validation and an independent data set. They are found suitable for the determination of the studied drugs in bulk powder and tablets.

Estimation of soil sorption coefficients of veterinary pharmaceuticals from soil properties.

PubMed

ter Laak, Thomas L; Gebbink, Wouter A; Tolls, Johannes

2006-04-01

Environmental exposure assessment of veterinary pharmaceuticals requires estimating the sorption to soil. Soil sorption coefficients of three common, ionizable, antimicrobial agents (oxytetracycline [OTC], tylosin [TYL], and sulfachloropyridazine [SCP]) were studied in relation to the soil properties of 11 different soils. The soil sorption coefficient at natural pH varied from 950 to 7,200, 10 to 370, and 0.4 to 35 L/kg for OTC, TYL, and SCP, respectively. The variation increased by almost two orders of magnitude for OTC and TYL when pH was artificially adjusted. Separate soil properties (pH, organic carbon content, clay content, cation-exchange capacity, aluminum oxyhydroxide content, and iron oxyhydroxide content) were not able to explain more than half the variation observed in soil sorption coefficients. This reflects the complexity of the sorbent-sorbate interactions. Partial-least-squares (PLS) models, integrating all the soil properties listed above, were able to explain as much as 78% of the variation in sorption coefficients. The PLS model was able to predict the sorption coefficient with an accuracy of a factor of six. Considering the pH-dependent speciation, species-specific PLS models were developed. These models were able to predict species-specific sorption coefficients with an accuracy of a factor of three to four. However, the species-specific sorption models did not improve the estimation of sorption coefficients of species mixtures, because these models were developed with a reduced data set at standardized aqueous concentrations. In conclusion, pragmatic approaches like PLS modeling might be suitable to estimate soil sorption for risk assessment purposes.

Europa's Interaction with Jupiter's Magnetosphere: Galileo Plasma Observations Revisited.

NASA Astrophysics Data System (ADS)

Heuer, S. V.; Rymer, A. M.; Westlake, J. H.; Paterson, W. R.; Collinson, G.

2017-12-01

The Galileo spacecraft was active at Jupiter from December 1995 to September 2003, carrying the Galileo Plasma Science Instrument (PLS), an electrostatic analyzer with three spherical-segment plates which directed energy selected particles into one of seven electron sensors or seven ion channels with field-of-views which combined to cover 80% of the 4pi-sr unit sphere (Frank et al., 1992). While Galileo accomplished most of its primary scientific objectives, the mission did not reach its full potential due to a failed high-gain antenna deployment which severely limited the available bandwidth for data transmission. Consequently, the PLS was limited by bandwidth availability, and only collected data with high temporal and energy resolution for short periods of time (e.g. review by Bagenal et al., 2016). The electron sensors were also negatively affected by the gaseous environment around Jupiter, which is suspected to have deposited a layer of contaminants on the detectors, raising the threshold energy required to pass through the aperture and effectively preventing the measurement of electrons below 1keV (Frank et al., 2002). As a result, data from the PLS is challenging to process and interpret. Ion plasma moments have been computed (and published on the PDS) in the magnetosphere, but moon flybys were excluded (Bagenal et al., 2016). In anticipation of future in-situ exploration of the Europa plasma environment, we present analysis of full-resolution plasma data acquired by the PLS during the nine Europa flybys and compare our results with existing data in order to further inform designs currently being worked for the Europa Clipper and JUICE missions.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

PubMed

Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-05

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Non-targeted analyses of animal plasma: betaine and choline represent the nutritional and metabolic status.

PubMed

Katayama, K; Sato, T; Arai, T; Amao, H; Ohta, Y; Ozawa, T; Kenyon, P R; Hickson, R E; Tazaki, H

2013-02-01

Simple liquid chromatography-mass spectrometry (LC-MS) was applied to non-targeted metabolic analyses to discover new metabolic markers in animal plasma. Principle component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were used to analyse LC-MS multivariate data. PCA clearly generated two separate clusters for artificially induced diabetic mice and healthy control mice. PLS-DA of time-course changes in plasma metabolites of chicks after feeding generated three clusters (pre- and immediately after feeding, 0.5-3 h after feeding and 4 h after feeding). Two separate clusters were also generated for plasma metabolites of pregnant Angus heifers with differing live-weight change profiles (gaining or losing). The accompanying PLS-DA loading plot detailed the metabolites that contribute the most to the cluster separation. In each case, the same highly hydrophilic metabolite was strongly correlated to the group separation. The metabolite was identified as betaine by LC-MS/MS. This result indicates that betaine and its metabolic precursor, choline, may be useful biomarkers to evaluate the nutritional and metabolic status of animals. © 2011 Blackwell Verlag GmbH.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Quantitative analysis of red wine tannins using Fourier-transform mid-infrared spectrometry.

PubMed

Fernandez, Katherina; Agosin, Eduardo

2007-09-05

Tannin content and composition are critical quality components of red wines. No spectroscopic method assessing these phenols in wine has been described so far. We report here a new method using Fourier transform mid-infrared (FT-MIR) spectroscopy and chemometric techniques for the quantitative analysis of red wine tannins. Calibration models were developed using protein precipitation and phloroglucinolysis as analytical reference methods. After spectra preprocessing, six different predictive partial least-squares (PLS) models were evaluated, including the use of interval selection procedures such as iPLS and CSMWPLS. PLS regression with full-range (650-4000 cm(-1)), second derivative of the spectra and phloroglucinolysis as the reference method gave the most accurate determination for tannin concentration (RMSEC = 2.6%, RMSEP = 9.4%, r = 0.995). The prediction of the mean degree of polymerization (mDP) of the tannins also gave a reasonable prediction (RMSEC = 6.7%, RMSEP = 10.3%, r = 0.958). These results represent the first step in the development of a spectroscopic methodology for the quantification of several phenolic compounds that are critical for wine quality.

On-line milk spectrometry: analysis of bovine milk composition

NASA Astrophysics Data System (ADS)

Spitzer, Kyle; Kuennemeyer, Rainer; Woolford, Murray; Claycomb, Rod

2005-04-01

We present partial least squares (PLS) regressions to predict the composition of raw, unhomogenised milk using visible to near infrared spectroscopy. A total of 370 milk samples from individual quarters were collected and analysed on-line by two low cost spectrometers in the wavelength ranges 380-1100 nm and 900-1700 nm. Samples were collected from 22 Friesian, 17 Jersey, 2 Ayrshire and 3 Friesian-Jersey crossbred cows over a period of 7 consecutive days. Transmission spectra were recorded in an inline flowcell through a 0.5 mm thick milk sample. PLS models, where wavelength selection was performed using iterative PLS, were developed for fat, protein, lactose, and somatic cell content. The root mean square error of prediction (and correlation coefficient) for the nir and visible spectrometers respectively were 0.70%(0.93) and 0.91%(0.91) for fat, 0.65%(0.5) and 0.47%(0.79) for protein, 0.36%(0.49) and 0.45%(0.43) for lactose, and 0.50(0.54) and 0.48(0.51) for log10 somatic cells.

Chemical durability and leaching mechanism of Ce0.5Eu0.5PO4 ceramics: Effects of temperature and pH values

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Teng, Yuancheng; Wu, Lang; Huang, Yi; Ma, Jiyan; Wang, Guolong

2015-11-01

Ce0.5Eu0.5PO4 ceramics with high relative density were prepared by hot-press (HPS) and pressureless (PLS) sintering. The effects of temperature and pH values on the chemical durability of the ceramics were investigated. The results show that an increase of acidity significantly accelerated the corrosion of the samples. In alkaline leachates, further release elements were prevented by the newborn surface precipitation. The leach rate (Rn) of HPS sample was similar to that of PLS specimen in deionized water, but higher Rn for PLS sample was found in pH = 11 solution. Moreover, apparent activation energy of the dissolution of Eu (40 ± 4 kJ mol-1) is much higher than that of Ce (20 ± 1 kJ mol-1), leading to the higher normalized elemental leach rate of Eu. Both the Eu and Ce elements have low leach rates (10-12-10-9 m d-1) after 42 days in all the leachates studied in this work.

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas.

PubMed

Son, Hong-Seok; Kim, Ki Myong; van den Berg, Frans; Hwang, Geum-Sook; Park, Won-Mok; Lee, Cherl-Ho; Hong, Young-Shick

2008-09-10

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.

Simultaneous measurement of two enzyme activities using infrared spectroscopy: A comparative evaluation of PARAFAC, TUCKER and N-PLS modeling.

PubMed

Baum, Andreas; Hansen, Per Waaben; Meyer, Anne S; Mikkelsen, Jørn Dalgaard

2013-08-06

Enzymes are used in many processes to release fermentable sugars for green production of biofuel, or the refinery of biomass for extraction of functional food ingredients such as pectin or prebiotic oligosaccharides. The complex biomasses may, however, require a multitude of specific enzymes which are active on specific substrates generating a multitude of products. In this paper we use the plant polymer, pectin, to present a method to quantify enzyme activity of two pectolytic enzymes by monitoring their superimposed spectral evolutions simultaneously. The data is analyzed by three chemometric multiway methods, namely PARAFAC, TUCKER3 and N-PLS, to establish simultaneous enzyme activity assays for pectin lyase and pectin methyl esterase. Correlation coefficients Rpred(2) for prediction test sets are 0.48, 0.96 and 0.96 for pectin lyase and 0.70, 0.89 and 0.89 for pectin methyl esterase, respectively. The retrieved models are compared and prediction test sets show that especially TUCKER3 performs well, even in comparison to the supervised regression method N-PLS. Copyright © 2013 Elsevier B.V. All rights reserved.

Following a trend with an exponential moving average: Analytical results for a Gaussian model

NASA Astrophysics Data System (ADS)

Grebenkov, Denis S.; Serror, Jeremy

2014-01-01

We investigate how price variations of a stock are transformed into profits and losses (P&Ls) of a trend following strategy. In the frame of a Gaussian model, we derive the probability distribution of P&Ls and analyze its moments (mean, variance, skewness and kurtosis) and asymptotic behavior (quantiles). We show that the asymmetry of the distribution (with often small losses and less frequent but significant profits) is reminiscent to trend following strategies and less dependent on peculiarities of price variations. At short times, trend following strategies admit larger losses than one may anticipate from standard Gaussian estimates, while smaller losses are ensured at longer times. Simple explicit formulas characterizing the distribution of P&Ls illustrate the basic mechanisms of momentum trading, while general matrix representations can be applied to arbitrary Gaussian models. We also compute explicitly annualized risk adjusted P&L and strategy turnover to account for transaction costs. We deduce the trend following optimal timescale and its dependence on both auto-correlation level and transaction costs. Theoretical results are illustrated on the Dow Jones index.

Application of a Novel S3 Nanowire Gas Sensor Device in Parallel with GC-MS for the Identification of Rind Percentage of Grated Parmigiano Reggiano.

PubMed

Abbatangelo, Marco; Núñez-Carmona, Estefanía; Sberveglieri, Veronica; Zappa, Dario; Comini, Elisabetta; Sberveglieri, Giorgio

2018-05-18

Parmigiano Reggiano cheese is one of the most appreciated and consumed foods worldwide, especially in Italy, for its high content of nutrients and taste. However, these characteristics make this product subject to counterfeiting in different forms. In this study, a novel method based on an electronic nose has been developed to investigate the potentiality of this tool to distinguish rind percentages in grated Parmigiano Reggiano packages that should be lower than 18%. Different samples, in terms of percentage, seasoning and rind working process, were considered to tackle the problem at 360°. In parallel, GC-MS technique was used to give a name to the compounds that characterize Parmigiano and to relate them to sensors responses. Data analysis consisted of two stages: Multivariate analysis (PLS) and classification made in a hierarchical way with PLS-DA ad ANNs. Results were promising, in terms of correct classification of the samples. The correct classification rate (%) was higher for ANNs than PLS-DA, with correct identification approaching 100 percent.

Evaluation of in-line Raman data for end-point determination of a coating process: Comparison of Science-Based Calibration, PLS-regression and univariate data analysis.

PubMed

Barimani, Shirin; Kleinebudde, Peter

2017-10-01

A multivariate analysis method, Science-Based Calibration (SBC), was used for the first time for endpoint determination of a tablet coating process using Raman data. Two types of tablet cores, placebo and caffeine cores, received a coating suspension comprising a polyvinyl alcohol-polyethylene glycol graft-copolymer and titanium dioxide to a maximum coating thickness of 80µm. Raman spectroscopy was used as in-line PAT tool. The spectra were acquired every minute and correlated to the amount of applied aqueous coating suspension. SBC was compared to another well-known multivariate analysis method, Partial Least Squares-regression (PLS) and a simpler approach, Univariate Data Analysis (UVDA). All developed calibration models had coefficient of determination values (R 2 ) higher than 0.99. The coating endpoints could be predicted with root mean square errors (RMSEP) less than 3.1% of the applied coating suspensions. Compared to PLS and UVDA, SBC proved to be an alternative multivariate calibration method with high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

A rapid tool for determination of titanium dioxide content in white chickpea samples.

PubMed

Sezer, Banu; Bilge, Gonca; Berkkan, Aysel; Tamer, Ugur; Hakki Boyaci, Ismail

2018-02-01

Titanium dioxide (TiO 2 ) is a widely used additive in foods. However, in the scientific community there is an ongoing debate on health concerns about TiO 2 . The main goal of this study is to determine TiO 2 content by using laser induced breakdown spectroscopy (LIBS). To this end, different amounts of TiO 2 was added to white chickpeas and analyzed by using LIBS. Calibration curve was obtained by following Ti emissions at 390.11nm for univariate calibration, and partial least square (PLS) calibration curve was obtained by evaluating the whole spectra. The results showed that Ti calibration curve at 390.11nm provides successful determination of Ti level with 0.985 of R 2 and 33.9ppm of limit of detection (LOD) value, while PLS has 0.989 of R 2 and 60.9ppm of LOD. Furthermore, commercial white chickpea samples were used to validate the method, and validation R 2 for simple calibration and PLS were calculated as 0.989 and 0.951, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Qualitative and quantitative detection of honey adulterated with high-fructose corn syrup and maltose syrup by using near-infrared spectroscopy.

PubMed

Li, Shuifang; Zhang, Xin; Shan, Yang; Su, Donglin; Ma, Qiang; Wen, Ruizhi; Li, Jiaojuan

2017-03-01

Near-infrared spectroscopy (NIR) was used for qualitative and quantitative detection of honey adulterated with high-fructose corn syrup (HFCS) or maltose syrup (MS). Competitive adaptive reweighted sampling (CARS) was employed to select key variables. Partial least squares linear discriminant analysis (PLS-LDA) was adopted to classify the adulterated honey samples. The CARS-PLS-LDA models showed an accuracy of 86.3% (honey vs. adulterated honey with HFCS) and 96.1% (honey vs. adulterated honey with MS), respectively. PLS regression (PLSR) was used to predict the extent of adulteration in the honeys. The results showed that NIR combined with PLSR could not be used to quantify adulteration with HFCS, but could be used to quantify adulteration with MS: coefficient (R p 2 ) and root mean square of prediction (RMSEP) were 0.901 and 4.041 for MS-adulterated samples from different floral origins, and 0.981 and 1.786 for MS-adulterated samples from the same floral origin (Brassica spp.), respectively. Copyright © 2016. Published by Elsevier Ltd.

Atmospheric pressure chemical ionisation mass spectrometry analysis linked with chemometrics for food classification - a case study: geographical provenance and cultivar classification of monovarietal clarified apple juices.

PubMed

Gan, Heng-Hui; Soukoulis, Christos; Fisk, Ian

2014-03-01

In the present work, we have evaluated for first time the feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics (PLS-DA) as a new strategy for rapid and non-destructive food classification. For this purpose 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origin were used for evaluation of the performance of APCI-MS as a classification tool. For an independent test set PLS-DA analyses of pre-treated spectral data gave 100% and 94.2% correct classification rate for the classification by cultivar and geographical origin, respectively. Moreover, PLS-DA analysis of APCI-MS in conjunction with GC-MS data revealed that masses within the spectral ACPI-MS data set were related with parent ions or fragments of alkyesters, carbonyl compounds (hexanal, trans-2-hexenal) and alcohols (1-hexanol, 1-butanol, cis-3-hexenol) and had significant discriminating power both in terms of cultivar and geographical origin. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Partial Least Squares Based Procedure for Upstream Sequence Classification in Prokaryotes.

PubMed

Mehmood, Tahir; Bohlin, Jon; Snipen, Lars

2015-01-01

The upstream region of coding genes is important for several reasons, for instance locating transcription factor, binding sites, and start site initiation in genomic DNA. Motivated by a recently conducted study, where multivariate approach was successfully applied to coding sequence modeling, we have introduced a partial least squares (PLS) based procedure for the classification of true upstream prokaryotic sequence from background upstream sequence. The upstream sequences of conserved coding genes over genomes were considered in analysis, where conserved coding genes were found by using pan-genomics concept for each considered prokaryotic species. PLS uses position specific scoring matrix (PSSM) to study the characteristics of upstream region. Results obtained by PLS based method were compared with Gini importance of random forest (RF) and support vector machine (SVM), which is much used method for sequence classification. The upstream sequence classification performance was evaluated by using cross validation, and suggested approach identifies prokaryotic upstream region significantly better to RF (p-value < 0.01) and SVM (p-value < 0.01). Further, the proposed method also produced results that concurred with known biological characteristics of the upstream region.

Harvest-time prediction of apple physiological indices using fiber optic Fourier transform near-infrared spectrometer

NASA Astrophysics Data System (ADS)

Liu, Yande; Ying, Yibin; Lu, Huishan; Fu, Xiaping

2004-12-01

This work evaluates the feasibility of Fourier transform near infrared (FT-NIR) spectrometry for rapid determining the total soluble solids content and acidity of apple fruit. Intact apple fruit were measured by reflectance FT-NIR in 800-2500 nm range. FT-NIR models were developed based on partial least square (PLS) regression and principal component regress (PCR) with respect to the reflectance and its first derivative, the logarithms of the reflectance reciprocal and its second derivative. The above regression models, related the FT-NIR spectra to soluble solids content (SSC), titratable acidity (TA) and available acidity (pH). The best combination, based on the prediction results, was PLS models with respect to the logarithms of the reflectance reciprocal. Predictions with PLS models resulted standard errors of prediction (SEP) of 0.455, 0.044 and 0.068, and correlation coefficients of 0.968, 0.728 and 0.831 for SSC, TA and pH, respectively. It was concluded that by using the FT-NIR spectrometry measurement system, in the appropriate spectral range, it is possible to nondestructively assess the maturity factors of apple fruit.

Combining FT-IR spectroscopy and multivariate analysis for qualitative and quantitative analysis of the cell wall composition changes during apples development.

PubMed

Szymanska-Chargot, M; Chylinska, M; Kruk, B; Zdunek, A

2015-01-22

The aim of this work was to quantitatively and qualitatively determine the composition of the cell wall material from apples during development by means of Fourier transform infrared (FT-IR) spectroscopy. The FT-IR region of 1500-800 cm(-1), containing characteristic bands for galacturonic acid, hemicellulose and cellulose, was examined using principal component analysis (PCA), k-means clustering and partial least squares (PLS). The samples were differentiated by development stage and cultivar using PCA and k-means clustering. PLS calibration models for galacturonic acid, hemicellulose and cellulose content from FT-IR spectra were developed and validated with the reference data. PLS models were tested using the root-mean-square errors of cross-validation for contents of galacturonic acid, hemicellulose and cellulose which was 8.30 mg/g, 4.08% and 1.74%, respectively. It was proven that FT-IR spectroscopy combined with chemometric methods has potential for fast and reliable determination of the main constituents of fruit cell walls. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Prevention of problem behavior by teaching functional communication and self-control skills to preschoolers.

PubMed

Luczynski, Kevin C; Hanley, Gregory P

2013-01-01

We evaluated the effects of the preschool life skills program (PLS; Hanley, Heal, Tiger, & Ingvarsson, 2007) on the acquisition and maintenance of functional communication and self-control skills, as well as its effect on problem behavior, of small groups of preschoolers at risk for school failure. Six children were taught to request teacher attention, teacher assistance, and preferred materials, and to tolerate delays to and denial of those events during child-led, small-group activities. Teaching strategies included instruction, modeling, role play, and differential reinforcement. Six additional children randomly assigned to similarly sized control groups participated in small-group activities but did not experience the PLS program. Within-subject and between-groups designs showed that the PLS teaching procedures were functionally related to the improvements and maintenance of the skills and prevention of problem behavior. Stakeholder responses on a social acceptability questionnaire indicated that they were satisfied with the form of the targeted social skills, the improvements in the children's performance, and the teaching strategies. © Society for the Experimental Analysis of Behavior.

Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

NASA Astrophysics Data System (ADS)

Bai, Xue-Mei; Liu, Tie; Liu, De-Long; Wei, Yong-Ju

2018-02-01

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of ;mathematical separation;. Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.