Spatial Epitope Prediction server for Protein Antigens (SEPPA) has received lots of feedback since being published in 2009. In this improved version, relative ASA preference of unit patch and consolidated amino acid index were added as further classification parameters in addition to unit-triangle propensity and clustering coefficient which were previously reported. Then logistic regression model was adopted instead of the previous simple additive one. Most importantly, subcellular localization of protein antigen and species of immune host were fully taken account to improve prediction. The result shows that AUC of 0.745 (5-fold cross-validation) is almost the baseline performance with no differentiation like all the other tools. Specifying subcellular localization of protein antigen and species of immune host will generally push the AUC up. Secretory protein immunized to mouse can push AUC to 0.823. In this version, the false positive rate has been largely decreased as well. As the first method which has considered the subcellular localization of protein antigen and species of immune host, SEPPA 2.0 shows obvious advantages over the other popular servers like SEPPA, PEPITO, DiscoTope-2, B-pred, Bpredictor and Epitopia in supporting more specific biological needs. SEPPA 2.0 can be accessed at http://badd.tongji.edu.cn/seppa/. Batch query is also supported.

The mole fraction solubility data of l-proline in five monosolvents (water, methanol, ethanol, acetone, and acetonitrile) and four binary solvent systems (methanol + acetone, ethanol + acetone, methanol + acetonitrile, and ethanol + acetonitrile) were experimentally measured by gravimetric method at temperatures ranging from 283.15 to 323.15 K. The results showed that l-proline solubility and experimental temperature were positively correlated when the solvent composition was constant. On the basis of the solubility scatter diagrams and our investigation of solvent properties, the solubility behavior of l-proline in the pure and binary solvent systems was influenced by a combination of many factors. The solubility data were correlated by the modified Apelblat model, CNIBS/R-K model, and Apelblat-Jouyban-Acree model. The fitting results were generally acceptable.

Alcohol abuse is a major public health crisis. Relative evidences supported that the gut microbiota (GM) played an important role in central nervous system (CNS) function, and the composition of them had changed after alcohol drinking. We sought to explore the changes of GM in alcohol dependence. In our study, the GM of mice with alcohol administration was detected through analyzed 16S rRNA gene sequencing and the fecal metabolites were analyzed by LC-MS. The microbial diversity was significantly higher in the alcohol administration group, the abundance of phylum Firmicutes and its class Clostridiales were elevated, meanwhile the abundance of Lachnospiraceae, Alistipes, and Odoribacter showed significant differences among the three groups. Based on LC-MS results, bile acid, secondary bile acid, serotonin and taurine level had varying degrees of changes in alcohol model. From paraffin sections, tissue damage was observed in liver and colon. These findings provide direct evidence that alcohol intake affects the composition of GM, enable a better understanding of the function of GM in the microbiota-gut-brain (MGB) axis, and give a new thought for alcohol addiction treatment.

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The solubility of moroxydine hydrochloride was determined by the gravimetrical method (temperature from 283.15 to 323.15 K, pressure at 101.325 kPa) in 12 pure solvents (water, methanol, ethanol, 1-propanol, 1-butanol, 2-methyl-1propanol, 2-propanol, 1-pentanol, 2-butanol, acetonitrile, ethyl acetate, and acetone) and a binary system (water + 2-propanol). The results of this experiment suggested that the solubility data of moroxydine hydrochloride increased with increasing mole fraction of water and experimental temperature in all investigated neat and mixed solvent systems. The moroxydine hydrochloride solubility order in the 12 neat solvents was shown as water > methanol > ethanol > 1-propanol > 1-butanol > 2-methyl-1propanol > 2-propanol > 1-pentanol > 2-butanol > acetonitrile ≈ ethyl acetate ≈ acetone. For polar protic solvents except for 1-pentanol, the main factor influencing the solubility behavior was the polarity. While it was affected by complicating factors in polar aprotic solvents. The fitting results of the moroxydine hydrochloride solubility data obtained by the modified Apelblat, Jouyban−Acree, and Apelblat−Jouyban−Acree models were all satisfactory.