Discrimination and quantification of volatile compounds in beer by FTIR combined with machine learning approaches.

The composition of volatile compounds in beer is crucial to the quality of beer. Herein, we identified 23 volatile compounds, namely, 12 esters, 4 alcohols, 5 acids, and 2 phenols, in nine different beer types using GC-MS. By performing PCA of the data of the flavor compounds, the different beer types were well discriminated. Ethyl caproate, ethyl caprylate, and phenylethyl alcohol were identified as the crucial volatile compounds to discriminate different beers. PLS regression analysis was performed to model and predict the contents of six crucial volatile compounds in the beer samples based on the characteristic wavelength of the FTIR spectrum. The R2 value of each sample in the prediction model was 0.9398-0.9994, and RMSEP was 0.0122-0.7011. The method proposed in this paper has been applied to determine flavor compounds in beer samples with good consistency compared with GC-MS.

Structure-guided discovery of food-derived GABA-T inhibitors as hunters for anti-anxiety compounds.

With the acceleration of the pace of life, people may face all kinds of pressure, and anxiety has become a common mental issue that is seriously affecting human life. Safe and effective food-derived compounds may be used as anti-anxiety compounds. In this study, anti-anxiety compounds were collected and curated for database construction. Quantitative structure-activity relationship (QSAR) models were developed using a combination of various machine-learning approaches and chemical descriptors to predict natural compounds in food with anti-anxiety effects. High-throughput molecular docking was used to screen out compounds that could function as anti-anxiety molecules by inhibiting γ-aminobutyrate transaminase (GABA-T) enzyme, and 7 compounds were screened for in vitro activity verification. Pharmacokinetic analysis revealed three compounds (quercetin, lithocholic acid, and ferulic acid) that met Lipinski's Rule of Five and inhibited the GABA-T enzyme to alleviate anxiety in vitro. The established QSAR model combined with molecular docking and molecular dynamics was proved by the synthesis and discovery of novel food-derived anti-anxiety compounds.

[Expression of FANCG gene in acute myeloid leukemia].

This study was purposed to investigate the relationship between expression of the FANCG gene and adult sporadic acute myeloid leukemia (AML), real-time PCR with SYBR Green I technique was used for detecting FANCG gene expression level in bone marrow mononuclear cells of 54 newly diagnosed AML patients, 46 AML patients in complete remission (CR) and 36 control samples. ß-actin gene was used as internal reference. Relative changes of FANCG gene expression level were detected by 2(-ΔΔCT) method in newly diagnosed AML patients and control samples, in newly diagnosed AML and patient in CR, as well as in AML patients in CR and control samples. The results showed that the relative expression level of FANCG mRNA was 0.56 ± 0.27 in newly diagnosed group, 0.75 ± 0.54 in AML CR group, and 0.85 ± 0.45 in control group. The expression level of FANCG mRNA in newly diagnosed group was significantly lower than that in control and AML CR groups (P < 0.05). There was no statistically significant deference in comparison of AML CR group with the control group (P > 0.05). It is concluded that the expression of FANCG gene decrease in the newly diagnosed AML patients. There is no significant difference between AML CR group and control group, which indicated that FANCG gene may be related with the onset and the prognosis of AML, and may provide a clinical value for evaluating effect of chemotherapy.