Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Objective:To compare minimally invasive surgery with traditional open surgery, analyze the current application status of health economic evaluations in the treatment of digestive tract cancers, such as esophageal cancer, gastric cancer, and colorectal cancer by minimally invasive surgery and provide evidence for the rational selection of clinical treatment, alleviation of disease-related economic burdens, and rational allocation of healthcare resources.Methods:By using five databases, i.e. China National Knowledge Infrastructure, Wanfang data, Chinese Biomedical Literature Database, PubMed, and Embase, a database was established to retrieve all the papers about health economic studies of minimally invasive surgery for esophageal cancer, gastric cancer, and colorectal cancer published until December 31, 2023. Literature was analyzed by using software NoteExpress 3.8, and data were processed using Excel 2021. The quality of included papers was evaluated using the CHEERS 2022 checklist, and Meta-analysis was conducted by using software Stata 17.0.Results:A total of 10 919 relevant papers were retrieved, and 59 studies were included. Only 14 studies (23.7%) used standard health economic evaluation methods. Meta-analysis results revealed no significant differences in direct medical expenditure and total expenditure between minimally invasive surgery and open surgery. However, the expenditure for minimally invasive surgery exhibited a significant increase [mean difference ( MD)=5 973.12 yuan, P<0.001], while hospital stay and indirect expenditure significantly decreased ( MD: -4.85 days and -733.79 yuan, P<0.001). In China, for gastric cancer, the direct medical expenditure of endoscopic surgery was lower than that of open surgery ( MD=-33 000.00 yuan) with no significant difference ( P<0.001). In colorectal cancer cases, the direct medical and surgical expenditures for laparoscopic surgery were higher than those for open surgery ( MD: 4 277.94 yuan and 4 267.80 yuan, P<0.001), while the indirect and total medical expenditures decreased ( MD: -768.34 yuan and -159.10 yuan). Hospital stays in patients who had minimally invasive surgery for all three types of cancer were shorter than those who had open surgery ( P<0.001). Conclusions:In the treatment of gastrointestinal cancer, compared with open surgery, minimally invasive surgery shows higher expenditure, but has advantages, such as shorter hospital stay and lower indirect expenditure, and there were no significant differences in direct medical and total expenditures between the two approaches. When conducting health economic evaluation, factors such as postoperative complications, hospital stay, and patient's economic status should be considered for their impact on total medical expenditure. It is necessary to pay attention to the application of health economic evaluations in healthcare decision-making.

Objective:To study the association between subtypes of hypertension and risk for all-cause mortality and cardio-cerebrovascular mortalities in the elderly in communities of Beijing.Methods:The data were collected from the Beijing Healthy Aging Cohort Study. The elderly in 5 urban areas (former Xicheng, former Xuanwu, Fangshan, Haidian and Tongzhou) and 4 rural areas (Yanqing, Miyun, Huairou and Daxing) in Beijing were selected as the study subjects by multi-stage stratified cluster random sampling. The baseline survey was conducted from July 2009 to September 2015. The follow-up was conducted until March 31, 2021, and a total of 6 326 participants were enrolled. Cox proportional hazard regression model was used to analyze the association of SBP, DBP, normal blood pressure, high normal blood pressure, simple systolic hypertension, simple diastolic hypertension and systolic diastolic hypertension with all-cause mortality and cardio-cerebrovascular mortality.Results:By March 31, 2021, the median follow-up time was 6.30 years, the all-cause mortality density was 201.67/10 000 person-years, and the cardio-cerebrovascular mortality density was 90.20/10 000 person-years. Multivariate Cox proportional hazard regression model analysis showed that the risk for all-cause mortality increased by 5.6% ( HR=1.056, 95% CI: 1.020-1.092), and the risk for cardio-cerebrovasculvar mortality increased by 12.5% ( HR=1.125, 95% CI: 1.071-1.182) for every 10 mmHg increase in SBP. The risk for all-cause mortality increased by 8.6% ( HR=1.086, 95% CI: 1.023-1.152), and the risk for cardio-cerebrovascular mortality increased by 19.9% ( HR=1.199, 95% CI: 1.101-1.306) for every 10 mmHg increase in DBP. Compared with the normal blood pressure group, the risk for all-cause mortality increased by 64.8% ( HR=1.648, 95% CI: 1.049-2.591) and the risk for cardio- cerebrovascular mortality increased by 112.8% ( HR=2.128, 95% CI: 1.069-4.233) in the simple diastolic hypertension group. The risk for all-cause mortality increased by 34.4% ( HR=1.344, 95% CI: 1.023-1.467) and the risk for cardio-cerebrovascular mortality increased by 111.3% ( HR=2.113, 95% CI: 1.384-3.225) in the systolic-diastolic hypertension group. Conclusions:In the elderly in communities of Beijing, beside systolic-diastolic hypertension. It is necessary to pay close attention to the simple diastolic hypertension, which has lower prevalence, and give targeted prevention and treatment.

Objective:To investigate the association of urinary albumin-to-creatinine ratio (UACR) in normal range and cardiovascular health (CVH) score with cardio-cerebroascular and all-cause mortality in urban elderly residents in Beijing.Methods:Based on Beijing Healthy Aging Cohort Study, data from 1 817 elderly participants with normal UACR were analyzed, and UACR was used as both continuous and categorical variable. "Life's Essential 8" was used to develop a CVH score. Statistical analysis was performed by using software SPSS 26.0 and R 4.2.1, including two independent samples t-test, χ2 test and non-parametric test. Multivariable Cox proportional hazard regression models stratified by CVH score and the restricted cubic spline were used to analyse the association of UACR with the risk for cardio-cerebrovascular and all-cause mortality. Results:By March 31, 2021, the median follow-up time M ( Q1, Q3) was 11.28 (10.84, 11.36) years, a total of 308 deaths were recorded during follow-up, and the mortality density was 163.87/10 000 person-years. The age of the participants was (71.4±6.6) years, and 1 070 participants were women. The results showed that the risk for both cardio-cerebrovascular disease and all-cause mortality decreased with the decrease of UACR in the low CVH score group ( HR=0.500, 95% CI: 0.341-0.734; HR=0.793, 95% CI: 0.647-0.971), and in the high CVH score group, there was a decreasing trend in the risk for cardio-cerebrovascular mortality with the decrease of UACR ( HR=0.665, 95% CI: 0.447-0.990). Compared with the participants with low CVH score and higher UACR, the risk for cardio-cerebrovascular and all-cause mortality decreased by 68.9% and 45.6%, respectively, in the participants with high CVH score and lower UACR ( HR=0.311, 95% CI: 0.131-0.739; HR=0.544, 95% CI: 0.360-0.822), and the risk for all-cause mortality decreased by 26.7% in the participants with high CVH score and higher UACR ( HR=0.733, 95% CI: 0.542-0.993). Conclusions:In urban elderly residents in Beijing, higher UACR were associated with a significantly increased risk for cardio-cerebrovascular and all-cause mortality, and in the low-CVH score group, decreased UACR was protective factor against cardio-cerebrovascular and all-cause mortality. The combined effect of cardiovascular health status and normal UACR had a greater protection against the risk for cardio-cerebrovascular and all-cause mortality.

Objective:To describe and analyze the distribution characteristics of a body shape index (ABSI) and its association with all-cause mortality in the elderly in communities of Beijing.Methods:The baseline and follow-up data of 10 423 subjects in Beijing Healthy Aging Cohort Study were used. The endpoint outcome was all-cause mortality in follow-up. The associations of ABSI, BMI and waist circumference with all-cause mortality were analyzed with a Cox proportional hazard regression model.Results:The mean follow-up time in this cohort was 6.36 years and the all-cause mortality was 15.27%. The restricted cubic spline results showed that ABSI showed a "U" association with all-cause mortality in the total population. After adjustment for confounding factors, compared with the normal ABSI group, the risk for all-cause mortality was higher in the low ABSI group ( HR=1.69, 95% CI: 1.32-2.17) and high ABSI group ( HR=1.75, 95% CI: 1.40-2.18). Compared with the normal BMI group, low BMI was associated with an increased risk for all-cause mortality ( HR=1.70, 95% CI: 1.40-2.08). Compared with the normal waist circumference group, central obesity was associated with a decreased risk for all-cause mortality ( HR=0.89, 95% CI: 0.80-0.99). The results of gender specific analysis on ABSI association with all-cause mortality were similar to that in total population, but the strength of association varied among different age groups. Cross-grouping results showed that older people with normal BMI and waist circumference and abnormal ABSI had an increased risk of all-cause mortality ( HR=1.91, 95% CI: 1.22-2.99). Conclusions:In Beijing, ABSI is correlated with the risk for all-cause mortality in the elderly population, which is more sensitive and specific than the traditional indicators (BMI and waist circumference). They can be used as one of the physical measurement indicators for all-cause mortality risk prediction in the health risk assessment and management in the elderly.

Objective:To explore the association between physical activity (PA) level and all-cause mortality in the elderly with different obesity status in Beijing.Methods:The study subjects were from the Cardiovascular and Cognitive Healthy Study in Middle-Aged and Elderly Residents of Beijing, a total of 3 746 individuals aged ≥60 years in the baseline survey between 2013 and 2015 were included in the study. Questionnaire survey and physical examination were conducted to collect the basic information of the individuals. The metabolic equivalent of the elderly was used to calculate the PA level, and an international PA questionnaire was used to determine the PA intensity. BMI, waist-to-height ratio (WHtR) and a body shape index (ABSI) were used to evaluate individuals' obesity status. The distribution of different PA levels under different obesity states was described by using bar chart and cumulative percentage bar chart. Cox proportional hazard regression model was used to analyze the correlation between the level of PA and all-cause mortality risk in different types of obesity status.Results:By December 31, 2019, the median follow-up time was 5.46 years, and the mortality density was 244.55/10 000 person-years. Compared with the individuals in high-PA intensity group, the all-cause mortality risk increased by 41% ( HR=1.41, 95% CI: 1.14-1.76) and 122% ( HR=2.22, 95% CI: 1.76-2.81), respectively, in moderate and low PA intensity groups. Compared with the individuals in high-PA intensity-high-obesity group, based on the BMI, the all-cause mortality risk increased by 85% ( HR=1.85, 95% CI: 1.08-3.16) and 250% ( HR=3.50, 95% CI: 2.01-6.10) in those in moderate-PA intensity-high-obesity group and in low-intensity-high-obesity group. Based on the WHtR, the all-cause mortality risk increased by 53% ( HR=1.53, 95% CI: 1.02-2.29) and 218% ( HR=3.18, 95% CI: 2.09-4.86), respectively, in those with moderate-PA intensity-high-obesity and those with low-PA intensity-high-obesity. According to the ABSI, the all-cause mortality risk increased by 120% in those in low-PA intensity-high-obesity group ( HR=2.20, 95% CI: 1.53-3.18). Based on any one of the indicators BMI, WHtR, or ABSI, there was no significant difference in all-cause mortality risk between high-intensity-moderate-obesity group and high-intensity-low-obesity group (all P>0.05). Conclusions:PA level is closely associated with the all-cause mortality risk in the elderly in communities of Beijing. Increasing PA level can not only reduce the all-cause mortality risk but also reduce even eliminate the excess all-cause mortality risk associated with obesity.

Objective:To analyze the association between different lipid indicators and cardio-cerebrovascular mortality in the elderly, identify a better lipid indicator for the risk for cardio-cerebrovascular mortality in the elderly in communities of Beijing.Methods:The elderly aged 60 years and above were selected from the Beijing Healthy Aging Cohort Study from July 2009 to September 2015. Remnant cholesterol (RC) was derived by calculation. The Cox proportional hazard regression models determined the HR and 95% CI incidating the associations of baseline different lipid indicators with cardio-cerebrovascular and all-cause mortality. Results:By March 31, 2021, with a mean follow-up duration of 6.88 years in the study population, a total of 492 cardio-cerebrovascular deaths and 1 056 all-cause deaths wre recorded. The HR values indicating the association between LDL-C, HDL-C, and RC were 0.87 (95% CI: 0.78-0.97), 0.46 (95% CI: 0.35-0.62), and 1.29 (95% CI: 1.14-1.45) for cardio-cerebrovascular mortality, respectively, and 0.93 (95% CI: 0.86-1.00), 0.66 (95% CI: 0.55-0.80) and 1.22 (95% CI: 1.12-1.33) for all-cause mortality. The associations of RC and HDL-C with cardio-cerebrovascular mortality were consistent regardless of hyperlipidemia in the elderly. Subgroup analyses showed that elevated RC was associated with increased risk for cardio-cerebrovascular mortality, and elevated HDL-C was associated with decreased risk for cardio-cerebrovascular mortality in the elderly in different gender, age, smoking status, drinking status, and diabetes status groups in communities of Beijing. Conclusion:RC might be a better potential lipid indicator for the risk for cardio-cerebrovascular mortality in the elderly in communities compared with traditional cholesterol indicator.

Recently, intelligent care is gradually changing the traditional care way, and artificial intelligence (AI) application is gradually broadening in the field of assisted reproduction. This review systematically analyzes the AI application in multiple aspects of reproductive health care. It also indicates the challenge during the process, including data privacy, technical reliability, ethics and legal provisions, and humanistic care. Both the opportunities of AI in assisted reproduction are highlighted and the ensuing problems are analyzed in depth. The purpose is to provide ideas for future studies to ensure that AI technology can be safely, efficiently and responsibly integrated with the field of reproductive health care.

Oocyte maturation disorders and fertilization failures are caused by a variety of factors, including complex factors such as chromosomal abnormalities and poor oocyte quality. With the widespread use of high-throughput sequencing technology, more and more genetic mutations have been found to be associated with oocyte maturation and fertilization process in infertile patients. This paper summarizes and discusses 11 key genes ( TRIP13, TBPL2, LHX8, PATL2, TUBB8, CDC20, WEE2, ZP, ASTL, JUNO and CD9) related to oocyte maturation and fertilization-related disorders in females, providing a basis for research on the prevention of diseases associated with oocyte maturation blockage and fertilization failure and the development of targeted therapies.

Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.