The impact of tea consumption on the risk of depression: A Mendelian randomization and Bayesian weighting algorithm study.

BACKGROUND AND OBJECTIVES: The precise impact of tea consumption on the risk of depression remains unclear. This study aimed to explore the relationship between the consumption patterns of tea and the likelihood of depression onset, utilizing a two-sample Mendelian randomization (MR) methodology. METHODS AND STUDY DESIGN: We utilized available genome-wide association study (GWAS) datasets on tea intake and depressive disorders. To investigate the causal relationship between tea consumption and depression, we employed a set of two-sample Mendelian Randomization (MR) methods. These included the inverse-variance weighted (IVW) analysis, weighted median approach, and MR-Egger regression. Additionally, we utilized MR-PRESSO and the MR-Egger intercept test for the detection of pleiotropic effects. To ensure the robustness and consistency of our findings, a sensitivity analysis was carried out, applying the 'leave-one-out' strategy. The Bayesian weighted Mendelian randomization (BWMR) was employed to conduct additional testing on the obtained results. RESULTS: The study's outcomes revealed a causal association between increased tea intake and an increased risk of depression (Inverse-Variance Weighted Analysis: Odds Ratio [OR] = 1.029, 95% Confidence Interval [CI]: 1.003-1.055, p = 0.027). This was observed despite variations in instrumental variables and the nonexistence of horizontal pleiotropy. Furthermore, the robustness of our Mendelian Randomization investigation was affirmed through the implementation of the 'leave-one-out' method in our sensitivity analysis. The findings from BWMR were in line with those obtained from IVW (BWMR: OR=1.030, 95% CI: 1.003-1.057, p = 0.029). CONCLUSIONS: The results from this study indicate a substantial and positive causal link between the regularity of tea drinking and the risk of depression onset.

Optimization of the driver's seat belt and injury biomechanical analysis in real-world minivan small offset impact accident scenarios.

To minimize injuries and protect the safety of the driver in minivan small offset collisions, an optimized pre-tensioned force-limiting seat belt was proposed herein. An accident with detailed information, such as medical reports, vehicle inspection reports, and accident scene photographs, was reconstructed using HyperMesh software. The effectiveness of both the accident model and the pre-tensioned force-limiting seat belt was evaluated. To obtain the optimal seat belt parameters for driver protection, first, force-limiting A, pre-tensioned force B, and pre-tensioned time C factors were selected in designing an orthogonal test with different factor levels. The influence laws of each factor on the injury biomechanical characteristics of the driver were analyzed via the direct analysis method. Moreover, each kind of critical injury value of the human body was synthesized, and the radial basis function surrogate model was constructed. The three seat belt parameters were optimized using the NSGA-II multi-objective genetic algorithm. The results showed that the optimal balance variable parameter of the seat belt was 4751.618 N-2451.839 N-17.554 ms (A-B-C). Finally, the optimal scheme was verified in a system simulating a minivan small offset collision. The results showed that after optimization, the skull von Mises stress was reduced by 36.9%, and the stress of the cervical vertebra cortical bone and cancellous bone decreased by 29.1% and 30.8%, respectively. In addition, the strains of the ribs and lungs decreased by 31.2% and 30.7%, respectively.

Digital signal extraction approach for cardiotocography image.

BACKGROUND AND OBJECTIVE: Cardiotocography, commonly called CTG, has become an indispensable auxiliary examination in obstetrics. Generally, CTG is provided in the form of a report, so the fetal heart rate and uterine contraction signals have to be extracted from the CTG images. However, most studies focused on reading data for a single curve, and the influence of complex backgrounds was usually not considered. METHODS: An efficient signal extraction method was proposed for the binary CTG images with complex backgrounds. Firstly, the images' background grids and symbol noise were removed by templates. Then a morphological method was used to fill breakpoints of curves. Moreover, the projection map was utilized to localize the area and the starting and ending positions of curves. Subsequently, data of the curves were extracted by column scanning. Finally, the amplitude of the extracted signal was calibrated. RESULTS: This study had tested 552 CTG images simulated using the CTU-UHB database. The correlation coefficient between the extracted and original signals was 0.9991 ± 0.0030 for fetal heart rate and 0.9904 ± 0.0208 for uterine contraction, and the mean absolute error of fetal heart rate and uterine contraction were 2.4658 ± 1.8446 and 1.8025 ± 0.6155, and the root mean square error of fetal heart rate and uterine contraction were 4.2930 ± 2.9771 and 2.5214 ± 0.9640, respectively. After being validated using 293 clinical authentic CTG images, the extracted signals were remarkably similar to the original counterparts, and no significant differences were observed. CONCLUSIONS: The proposed method could effectively extract the fetal heart rate and uterine contraction signals from the binary CTG images with complex backgrounds.

Whole Transcriptome Sequencing of Peripheral Blood Shows That Immunity/GnRH/PI3K-Akt Pathways Are Associated With Opioid Use Disorder.

Background: Opioid use disorder (OUD), which is most commonly exhibited as addiction, is a persistent chronic disease that places a burden on families and society. Various peripheral traits have been linked to OUD in the past, but research on this topic is insufficient. Methods: Seven male patients with OUD and 7 male healthy controls with matched demographic and clinical data were enrolled in this study. Peripheral blood RNA was used to construct an rRNA-removed library and a small RNA library. The peripheral transcriptomic differences between the two groups were investigated using RNA-seq. Differentially expressed messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and microRNAs (miRNAs) were identified by bioinformatics methods, and functional enrichment analysis with differentially expressed RNAs was performed to investigate the potential biological mechanisms of OUD. Results: A total of 229 mRNAs (115 upregulated, 114 downregulated), 416 lncRNAs (191 upregulated, 225 downregulated), 17 circRNAs (16 upregulated, 1 downregulated) and 74 miRNAs (42 upregulated, 32 downregulated) were differentially expressed between the OUD group and the healthy control group. Functional enrichment analysis with differentially expressed mRNAs showed that immunity, GnRH secretion, and PI3K-Akt signaling pathways were associated with OUD. Immunity-, JAK-STAT-, and insulin-related pathways were enriched in functional enrichment analysis of target genes predicted by differentially expressed miRNAs. Conclusion: We identified hundreds of differentially expressed genes that were enriched in immunity, GnRH secretion and PI3K-Akt signaling pathways. Some genes with significant changes might be used as potential biomarkers for progression and treatment of OUD.

Possible Avoidant Personality Disorder Magnifies the Association Between Bullying Victimization and Depressive Symptoms Among Chinese University Freshmen.

BACKGROUND: Bullying victimization has been associated with depressive symptoms in Chinese university students. This study examined the moderating effect of possible avoidant personality disorder (APD) on association between bullying victimization and depressive symptoms in university freshmen. METHODS: A total of 1,453 freshmen were recruited from a comprehensive university in Wuhan, China, and administered a self-report questionnaire. The APD subscale of Personality Diagnostic Questionnaire-Version 4 and Beck Depression Inventory were used to measure the presence of possible APD and depressive symptoms, respectively. The moderating effect of possible APD was examined by testing the statistical significance of the interaction between victimization and possible APD in multiple logistic regression analysis. RESULTS: The prevalence of depressive symptoms was 24.8%. In multiple logistic regression analysis, the interaction between bullying victimization and possible APD was significantly associated with depressive symptoms (OR: 1.80, P = 0.029). Subsequent subgroup analyses according to the status of possible APD showed that, the victimization-depression association was stronger among freshmen with possible APD (OR: 3.23, P < 0.001) than those without possible APD (OR: 1.82, P = 0.001). CONCLUSION: In Chinese university freshmen, bullying victimization is significantly associated with depressive symptoms, and possible APD magnifies the victimization-depression association. Bullied freshmen, particularly freshmen with possible APD, could be considered as the target group of campus-based depression intervention programs.