Bariatric surgery is one of the most effective way to lose weight,which suppresses appetite through the central nervous system. The mechanisms of appetite change may include gut hormones, adipokines, as well as microbiota in the intestine.

Objective:To develop and validate a useful predictive model for large gestational age (LGA) in pregnancy using a machine learning (ML) algorithm and compare its performance with the traditional logistic regression model.Methods:Data were obtained from the National Free Preconception Health Examination Project in China, carried out in 220 counties of 31 provinces from 2010 to 2012, covering all rural couples with a planned pregnancy. This study included all teams of childbearing age who delivered newborns within 24-42 weeks of gestational age and their newborns. Ten different ML algorithms were used to establish LGA prediction models, and the prediction performance of these models was evaluated.Results:A total of 104 936 newborns were included, including 54 856 boys (52.3%) and 50 080 girls (47.7%). The incidence of LGA was 11.7% (12 279). The imbalance between the two groups was addressed by the under- sampling technique, after which the overall performance of the ML models was significantly improved. The CatBoost model achieved the highest area under the receiver-operating-characteristic curve (AUC) value of 0.932. The logistic regression model had the worst performance, with an AUC of 0.555.Conclusions:In predicting the risk for LGA in pregnancy, the ML algorithms outperform the traditional logistic regression method. Compared to other ML algorithms, CatBoost could improve the performance, and it deserves further investigation.

3' Untranslated Regions ; Animals ; Antagomirs ; metabolism ; Base Sequence ; Binding Sites ; Cell Line, Tumor ; Cell Movement ; Cell Proliferation ; Humans ; Mice ; MicroRNAs ; antagonists & inhibitors ; genetics ; metabolism ; RNA Interference ; RNA, Messenger ; metabolism ; RNA, Small Interfering ; metabolism ; Rats ; Sequence Alignment ; Snail Family Transcription Factors ; antagonists & inhibitors ; genetics ; metabolism ; Stomach Neoplasms ; genetics ; pathology

Hepatocellular carcinoma (HCC), which makes up the majority of liver cancer, is induced by the infection of hepatitis B/C virus. Biomarkers are needed to facilitate the early detection of HCC, which is often diagnosed too late for effective therapy. The tRNA-derived small RNAs (tsRNAs) play vital roles in tumorigenesis and are stable in circulation. However, the diagnostic values and biological functions of circulating tsRNAs, especially for HCC, are still unknown. In this study, we first utilized RNA sequencing followed by quantitative reverse-transcription PCR to analyze tsRNA signatures in HCC serum. We identified tRF-Gln-TTG-006, which was remarkably upregulated in HCC serum (training cohort: 24 HCC patients vs. 24 healthy controls). In the validation stage, we found that tRF-Gln-TTG-006 signature could distinguish HCC cases from healthy subjects with high sensitivity (80.4%) and specificity (79.4%) even in the early stage (Stage I: sensitivity, 79.0%; specificity, 74.8%; 155 healthy controls vs. 153 HCC patients from two cohorts). Moreover, in vitro studies indicated that circulating tRF-Gln-TTG-006 was released from tumor cells, and its biological function was predicted by bioinformatics assay and validated by colony formation and apoptosis assays. In summary, our study demonstrated that serum tsRNA signature may serve as a novel biomarker of HCC.
Biomarkers ; Biomarkers, Tumor/genetics* ; Carcinoma, Hepatocellular/diagnosis* ; Hepatitis B virus ; Humans ; Liver Neoplasms/diagnosis* ; RNA, Transfer/genetics*