Amplification of Hofmeister Effect by Alcohols

We have demonstrated that Hofmeister effect can be amplified by adding alcohols to aqueous solutions. The lower critical solution temperature behavior of poly­(<i>N</i>-isopropylacrylamide) has been employed as the model system to study the amplification of Hofmeister effect. The alcohols can more effectively amplify the Hofmeister effect following the series methanol < ethanol < 1-propanol < 2-propanol for the monohydric alcohols and following the series d-sorbitol ≈ xylitol ≈ meso-erythritol < glycerol < ethylene glycol < methanol for the polyhydric alcohols. Our study reveals that the relative extent of amplification of Hofmeister effect is determined by the stability of the water/alcohol complex, which is strongly dependent on the chemical structure of alcohols. The more stable solvent complex formed via stronger hydrogen bonds can more effectively differentiate the anions through the anion–solvent complex interactions, resulting in a stronger amplification of Hofmeister effect. This study provides an alternative method to tune the relative strength of Hofmeister effect besides salt concentration

The nuclear architecture of budding yeast and the mC-SAC model genome.

<p><b>(A)</b> Schematic representation of the nucleus and nuclear landmarks of budding yeast and their corresponding coordinates and dimensions (not to scale). <b>(B)</b> An example 3D structure of mC-SAC genome confined in the cell nucleus. <b>(C)</b> Correlation between genome-wide chromatin conformation capture interaction frequencies and interaction frequencies measured from the fully-constrained ensemble of model yeast genomes. <b>(D)</b> Heat map of interaction frequencies measured in the fully-constrained ensemble. Darker color indicates higher interaction frequency. <b>(E)</b> Heat map of interaction frequencies from the experimental measurements [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005658#pcbi.1005658.ref016" target="_blank">16</a>]. <b>(F)</b> Heat map of simulated interactions from the fully-constrained ensemble, with only interactions between restriction fragments of the genome-wide 3C experiment [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005658#pcbi.1005658.ref016" target="_blank">16</a>] are shown for direct comparison. <b>(G)</b> Heat map of interaction frequencies of the fully-constrained ensemble that are corrected after removal of expected interaction frequencies obtained from an ensemble generated using only nuclear confinement and excluded-volume as constraints. <b>(H)</b> Heat map of interaction frequencies of the genome-wide 3C experiments that are corrected after removal of expected interaction frequencies. <b>(I)</b> Correlation of interaction frequencies between genome-wide 3C data and from the fully-constrained ensemble, after removal of expected interactions as obtained from an ensemble generated using only nuclear confinement and excluded-volume as constraints.</p

Interactions among fragile sites and their distribution in the budding yeast genome.

<p><b>(A)</b> Mean interaction frequency between fragile sites (shown as thick green line) and the histogram of mean interaction frequencies between 10,000 sets of 95 random sites. <b>(B)</b> The distribution of fragile sites in the 16 chromosomes. <b>(C)</b> Heat map of interaction frequencies between fragile sites as computed from the fully-constrained ensemble. The length of each chromosome is proportional to the number of fragile sites it contains. All high frequency interactions (red) are predicted to occur between different chromosomes, except those on the diagonal. <b>(D)</b> The distribution of fragile sites by their genomic distances to the corresponding centromeres.</p

Relationship between genomic and spatial positions of eight genes.

<p><b>(A)</b> The correlation between the relative positions of these genes measured by electron microscopy [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005658#pcbi.1005658.ref006" target="_blank">6</a>] (<i>x</i>-axis) and by fully-constrained ensemble (<i>y</i>-axis). <b>(B)</b> The relationship between the experimentally measured relative spatial positions of the important genes and their distance to the corresponding centromeres. The two locations of genes that correlate poorly are on Chr12 and telomere, which are subject to nucleolus and telomere attachment constraints. <b>(C)</b> The same relationship can be seen from computationally generated fully-constrained ensemble. <b>(D)</b> Heat map of interaction frequencies of Artificial Genome 1 (AG1) with 16 total chromosomes. <b>(E)</b> Heat map of interaction frequencies Artificial Genome 2 (AG2) with 12 total chromosomes. <b>(F)</b> The correlation between the relative position of the genes measured experimentally and measured from AG1 (blue) and AG2(red) ensembles. <b>(G)</b> The relationship between the relative positions of the genes measured from AG1 (blue) and AG2 (red) ensembles and their distances to the corresponding centromeres. The distances of these genes to their corresponding centromeres in artificial nuclei are different from each other and are all different from their corresponding distances in real yeast nuclei, as we assign random genomic coordinates to the centromeres in the artificial nuclei. <b>(H)</b> The correlation between the relative positions of the genes measured by electron microscopy [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005658#pcbi.1005658.ref006" target="_blank">6</a>] and by “with only centromere” ensemble. <b>(I)</b> The same correlation between the positions measured by electron microscopy [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005658#pcbi.1005658.ref006" target="_blank">6</a>] and in the “without centromere” ensemble.</p

Detection and Quantification of Bacterial Spoilage in Milk and Pork Meat Using MALDI-TOF-MS and Multivariate Analysis

Microbiological safety is one of the cornerstones of quality control in the food industry. Identification and quantification of spoilage bacteria in pasteurized milk and meat in the food industry currently relies on accurate and sensitive yet time-consuming techniques which give retrospective values for microbial contamination. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), a proven technique in the field of protein and peptide identification and quantification, may be a valuable alternative approach for the rapid assessment of microbial spoilage. In this work we therefore developed MALDI-TOF-MS as a novel analytical approach for the assessment of food that when combined with chemometrics allows for the detection and quantification of milk and pork meat spoilage bacteria. To develop this approach, natural spoilage of pasteurized milk and raw pork meat samples incubated at 15 °C and at room temperature, respectively, was conducted. Samples were collected for MALDI-TOF-MS analysis (which took 4 min per sample) at regular time intervals throughout the spoilage process, with concurrent calculation and documentation of reference total viable counts using traditional microbiological methods (these took 2 days). Multivariate statistical techniques such as principal component discriminant function analysis, canonical correlation analysis, partial least-squares (PLS) regression, and kernel PLS (KPLS) were used to analyze the data. The results from MALDI-TOF-MS combined with PLS or KPLS gave excellent bacterial quantification results for both milk and meat spoilage, and typical root mean squared errors for prediction in test spectra were between 0.53 and 0.79 log unit. Overall these novel findings strongly indicate that MALDI-TOF-MS when combined with chemometric approaches would be a useful adjunct for routine use in the milk and meat industry as a fast and accurate viable bacterial detection and quantification method

Portable, Quantitative Detection of <i>Bacillus</i> Bacterial Spores Using Surface-Enhanced Raman Scattering

Portable rapid detection of pathogenic bacteria such as <i>Bacillus</i> is highly desirable for safety in food manufacture and under the current heightened risk of biological terrorism. Surface-enhanced Raman scattering (SERS) is becoming the preferred analytical technique for bacterial detection, due to its speed of analysis and high sensitivity. However in seeking methods offering the lowest limits of detection, the current research has tended toward highly confocal, microscopy-based analysis, which requires somewhat bulky instrumentation and precisely synthesized SERS substrates. By contrast, in this study we have improved SERS for bacterial analyses using silver colloidal substrates, which are easily and cheaply synthesized in bulk, and which we shall demonstrate permit analysis using portable instrumentation. All analyses were conducted in triplicate to assess the reproducibility of this approach, which was excellent. We demonstrate that SERS is able to detect and quantify rapidly the dipicolinate (DPA) biomarker for <i>Bacillus</i> spores at 5 ppb (29.9 nM) levels which are significantly lower than those previously reported for SERS and well below the infective dose of 10⁴ <i>B. anthracis</i> cells for inhalation anthrax. Finally we show the potential of multivariate data analysis to improve detection levels in complex DPA extracts from viable spores

Compositional Equivalence of Grain from Multi-trait Drought-Tolerant Maize Hybrids to a Conventional Comparator: Univariate and Multivariate Assessments

MON 87460 (D1) maize contains a gene that expresses the cold shock protein B (CSPB) from Bacillus subtilis to confer a yield advantage when yield is limited by water availability. This study evaluated the composition of grain from the D1-containing combined-trait maize hybrids D1 × NK603, D1 × MON 89034 × NK603, and D1 × MON 89034 × MON 88017. These stacks offer a combination of insect protection and herbicide tolerance traits. These hybrids were grown under well-watered and water-limited conditions at three replicated field sites across Chile during the 2006–2007 growing season. Compositional analyses included measurement of proximates, fibers, total amino acids, fatty acids, minerals, vitamins, raffinose, phytic acid, <i>p</i>-coumaric acid, and ferulic acid. The statistical analyses included an evaluation of the applicability of multiblock principal component analysis (MB-PCA) and ANOVA–simultaneous component analysis (ASCA) to studies when more than one experimental factor will contribute to compositional variability. Results from these multivariate procedures highlighted that water treatment was the greatest contributor to compositional variability and, as expected, confirmed that the grain of combined-trait drought-tolerant hybrids was compositionally equivalent to that of conventional comparators as established by traditional statistical significance testing

Supplementary document for Designer Graphene oxide ultrathin flat lens with versatile focusing property - 6839401.pdf

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