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Machine learning methods have been used in identifying omics markers for a variety of phenotypes. We aimed to examine whether a supervised machine learning algorithm can improve identification of alcohol-associated transcriptomic markers. In this study, we analysed array-based, whole-blood derived expression data for 17 873 gene transcripts in 5508 Framingham Heart Study participants. By using the Boruta algorithm, a supervised random forest (RF)-based feature selection method, we selected twenty-five alcohol-associated transcripts. In a testing set (30 % of entire study participants), AUC (area under the receiver operating characteristics curve) of these twenty-five transcripts were 0·73, 0·69 and 0·66 for non-drinkers v. moderate drinkers, non-drinkers v. heavy drinkers and moderate drinkers v. heavy drinkers, respectively. The AUC of the selected transcripts by the Boruta method were comparable to those identified using conventional linear regression models, for example, AUC of 1958 transcripts identified by conventional linear regression models (false discovery rate < 0·2) were 0·74, 0·66 and 0·65, respectively. With Bonferroni correction for the twenty-five Boruta method-selected transcripts and three CVD risk factors (i.e. at P < 6·7e-4), we observed thirteen transcripts were associated with obesity, three transcripts with type 2 diabetes and one transcript with hypertension. For example, we observed that alcohol consumption was inversely associated with the expression of DOCK4 , IL4R , and SORT1 , and DOCK4 and SORT1 were positively associated with obesity, and IL4R was inversely associated with hypertension. In conclusion, using a supervised machine learning method, the RF-based Boruta algorithm, we identified novel alcohol-associated gene transcripts. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the role of oral microbiome in promoting oral squamous cell carcinoma (OSCC) development. Materials and Methods: We investigated the salivary microbiome of 108 controls and 70 OSCC cases by16S rRNA gene sequencing and detected the fluorescence signal of OSCC‐related pathological bacteria by fluorescence in situ hybridization assay (FISH). The invasion and migration assays were used to show the differences of invasive and migrative abilities between control and experimental groups. Quantitative real‐time PCR and Western blotting were used to verify the epithelial‐to‐mesenchymal transition (EMT). Results: In our study, the overall microbiome abundance and composition were richer in the 108 controls than in the 70 OSCC cases. We demonstrated that Streptococcus, Capnocytophaga, Peptostreptococcus, and Lactobacillus were highly abundant in the saliva of OSCC patients by 16S rDNA sequencing and FISH. Moreover, we found that Capnocytophaga gingivalis (C. gingivalis) was highly presented in OSCC tissues by FISH. We focused on C. gingivalis and found that its supernatant induced OSCC cells to undergo EMT, causing the cells to acquire a mesenchymal phenotype associated with highly invasive and metastatic properties. Conclusion: Taken together, these results indicated that C. gingivalis might invade OSCC tissues and played an important role in OSCC by promoting OSCC invasion and metastasis by inducing EMT. Hence, the role of C. gingivalis in cancer progression revealed a new direction for the research of OSCC. [ABSTRACT FROM AUTHOR]

Dimethachlon, a dicarboximide fungicide, has gained widespread usage in Asian countries. While considered a low-toxicity fungicide, concerns regarding potential health effects, such as nephrotoxicity, have emerged. To date, neither China nor other countries have established maximum residue limit (MRL) for dimethachlon on grapes, and exposure risk assessment of dimethachlon is lacking. Here, we developed a QuEChERS method coupled with gas chromatography-mass spectrometry (GC–MS) to investigate the dissipation rates and terminal residues of dimethachlon in grapes, along with an assessment of dietary risk to consumers. Our results indicated that the average recoveries of dimethachlon in grapes ranged from 74 to 76%. The limit of quantification (LOQ) was 0.050 mg/kg. After undergoing 112 days of storage at −18 °C, the dissipation rate of dimethachlon in grapes was found to be less than 30%, suggesting a state of stable storage. In the context of good agricultural practice (GAP) guidelines, the half-lives of dimethachlon in grapes were 14.3–18.1 days, which is notably longer compared to the reported values for other crops. The terminal residues of dimethachlon in grapes at 14 and 21 days were found to be < 0.05–0.53 mg/kg and < 0.05–0.29 mg/kg, respectively. Regarding the dietary risk assessment, the calculated risk quotient (RQ) value was significantly below 100%, indicating a negligible chronic risk of dimethachlon in grapes at the recommended dosage. This study provides an important reference for the analysis of dimethachlon and offers valuable empirical data to support the establishment of MRL. [ABSTRACT FROM AUTHOR]

Background: Car use has been associated with higher risk of coronary heart disease (CHD). However, whether the associations of transport modes with CHD vary by genetic susceptibility to CHD are unknown. This study aims to investigate the associations of genetic susceptibility and modes of transport with incidence of CHD. Methods: We included 339,588 white British participants from UK Biobank with no history of CHD or stroke at baseline or within two years of follow-up (52.3% in work). Genetic susceptibility to CHD was quantified through weighted polygenic risk scores derived from 300 single-nucleotide polymorphisms related to CHD risk. Categories of transport mode included exclusive car use and alternatives to the car (e.g., walking, cycling and public transport), separately for non-commuting (e.g., getting about [n=339,588] excluding commuting for work), commuting (in the sub-set in work [n=177,370] who responded to the commuting question), and overall transport (transport mode for both commuting and non-commuting [n=177,370]). We used Cox regression with age as the underlying timescale to estimate hazard ratios (HR) of CHD (n=13,730; median 13.8-year follow-up) and tested the interaction between genetic susceptibility and travel modes with adjustment for confounders. Results: Compared to those using alternatives to the car, hazards of CHD were higher for exclusive use of cars for overall transport (HR: 1.16, 95% confidence interval (CI): 1.08-1.25), non-commuting (HR: 1.08, 95% CI: 1.04-1.12) and commuting (HR: 1.16, 95% CI: 1.09-1.23), after adjusting for confounders plus genetic susceptibility. HRs of CHD were 1.45 (95% CI: 1.38-1.52) and 2.04 (95% CI: 1.95-2.12) for the second and third tertile of genetic susceptibility to CHD, respectively, compared to the first. There was, in general, no strong evidence of interactions between genetic susceptibility and categories of overall, non-commuting and commuting transport. Estimated 10-year absolute risk of CHD was lower for the alternatives to the car across strata of genetic susceptibility, compared with exclusive use of cars for overall, non-commuting and commuting transport. Conclusion: Exclusive use of cars was associated with a relatively higher risk of CHD across all strata of genetic susceptibility. Using alternatives to the car should be encouraged for prevention of CHD for the general population including individuals at high genetic risk. [ABSTRACT FROM AUTHOR]