Objective:To analyze the association between visceral fat area (VFA) and fatty liver based on quantitative CT (QCT) in people receiving health examination with normal body mass index (BMI).Methods:A cross-sectional study. A total of 1 305 physical examiners who underwent chest CT and QCT examination in the Department of Health Management of Henan Provincial People′s Hospital from January to December 2021 were retrospectively selected as subjects. The physical components at the central level of the lumbar two cone were measured with QCT, including subcutaneous fat area (SFA), VFA and liver fat content (LFC). And the metabolic indexes, such as blood lipids and blood glucose, were collected. The t-test and χ2 test were used to analyze the correlation between the detection rate of fatty live and LFCr and age and gender. According to level of VFA (<100 cm 2, 100-150 cm 2 and≥150 cm 2), the subjects were divided into three groups, and one-way ANOVA and χ2 test were used in comparison between groups. Multiple linear regression was used to analyze the correlation between VFA and metabolic indexes and LFC. Results:Of the 1 305 subjects, there were 634 males and 671 females. The detection rate of fatty liver in normal BMI population was 65.67%, and it was 72.71% and 59.02% respectively in men and women ( χ2=27.12, P<0.001), and the detection rate of fatty liver and LFC increased with age (both P<0.05). With the increase of VFA, the age, BMI, SFA, LFC, total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), alanine aminotransferase (ALT), blood uric acid and prevalence of fatty liver increased (all P<0.05), and the low-density lipoprotein cholesterol (HDL-C) decreased ( P<0.001). Multiple linear regression analysis showed that after adjustment for age factors, regardless of male or female, LFC was independently positively related with VFA, BMI, and ALT (male β=0.206, 0.145, 0.174, female β=0.194, 0.150, 0.184; all P<0.05). FBG was positively correlated with male independently ( β=0.134; P<0.001). The indicators related to female independently were TC, TG, and blood uric acid ( β=-0.121, 0.145, 0.141, all P<0.05) Conclusion:In the population receiving health examination with normal BMI, the VFA measured by QCT technique is closely related to fatty liver.

Objective:To analyze the correlation between body fat distribution measured by quantitative CT (QCT) and body mass index in adults receiving physical examination.Methods:It was a cross-sectional study. From January to December 2021, 3 205 adults undergoing physical examination who met the inclusion criteria and underwent chest CT and QCT examination in the health management discipline of Henan Provincial People′s Hospital were selected as the research objects. The general data were collected; and the subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate were measured by QCT. According to body mass index, the subjects were divided into normal group (18.5-<24.0 kg/m 2, 1 343 cases), overweight group (24.0-<28.0 kg/m 2, 1 427 cases) and obesity group (≥28.0 kg/m 2, 435 cases). One-way analysis of variance and χ2 test were used to compare the differences of QCT indexes among the three groups. Pearson and Spearman correlation analysis were used to evaluate the correlation between QCT indexes and body mass index. Receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic effect of QCT on obesity and fatty liver. Results:Subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate in obese group were all significantly higher than those in overweight group and normal group [males, (147.60±46.44) vs (104.33±27.68), (73.46±22.65) cm 2; (297.46±54.70) vs (229.40±53.12), (159.57±49.68) cm 2; (445.06±70.24) vs (333.73±62.91), (233.02±61.87) cm 2; 11.30% (7.90%, 15.55%) vs 8.75% (6.50%, 11.70%), 6.60% (4.80%, 8.70%); 100.0% vs 96.0%, 64.0%; 92.9% vs 86.7%, 73.3%; females, (213.96±48.61) vs (155.85±35.31), (107.24±31.01) cm 2; (185.41±43.88) vs (142.48±41.75), (96.56±36.50) cm 2; (399.37±68.07) vs (298.33±56.86), (203.80±57.53) cm 2; 9.80% (6.90%, 13.30%) vs 7.30% (5.05%, 9.80%), 5.40%(3.50%, 7.20%); 96.4% vs 74.8%, 28.9%; 87.3% vs 75.6%, 56.5%], and were all positively correlated with body mass index (males, r/ rs=0.709, 0.738, 0.831, 0.402, 0.464, 0.225; females, r/ rs=0.798, 0.695, 0.841, 0.416, 0.605, 0.276) (all P<0.001). In both male and female subjects, the detection rates of obesity based on QCT were significantly higher than those based on body mass index (male, 86.9% vs 16.6%; female, 49.3% vs 8.9%), and the detection rates of fatty liver based on QCT were significantly higher than those based on ultrasound (male, 83.6% vs 57.1%; female, 65.2% vs 27.6%) (all P<0.001). ROC curve showed that when the visceral fat area of 142 cm 2 was used as the cut-off value for the diagnosis of obesity in male subjects, the sensitivity and specificity was 100% and 15.8%, respectively; and when the cut-off value of liver fat content 5.0% was used to diagnose fatty liver, the sensitivity and specificity was 88.9% and 25.1%, respectively. When the visceral fat area of 115 cm 2 was set as the cut-off value for the diagnosis of obesity in female subjects, the sensitivity and specificity was 96.4% and 55.3%, respectively; when the liver fat content of 5.0% was set as the cut-off value for the diagnosis of fatty liver, the sensitivity and specificity was 83.7% and 43.2%, respectively. Conclusions:The indexes of abdominal fat and liver fat measured by QCT in adults receiving physical examination are all positively correlated with body mass index. The effect of QCT in the diagnosis of obesity and fatty liver are both better than body mass index and ultrasound.

Objective:To analyze the distribution of body fat with quantitative computed tomography (QCT) in people with normal body mass index (BMI).Methods:A cross-sectional study was conducted in the physical examination population who underwent chest CT and QCT examination in the Department of Health Management, Henan Provincial People′s Hospital from January to December in 2021, and 1 395 physical examination subjects who met the inclusion criteria were selected as the research subjects. The subjects were divided into five groups according to their age. The general data of the subjects were collected. The total abdominal fat area (TFA), visceral fat area (VFA), subcutaneous fat area (SFA), total abdominal muscle area (TMA) and muscle fat content (MFC) in the subjects were measured by QCT. One-way analysis of variance, Welch test and Kruskal-Wallis test were used to compare the above QCT measurement indexes between the two genders among different age groups with normal BMI. Pearson correlation analysis was used to analyze the correlation between VFA and sarcopenia indexes. Multivariate linear regression was used to analyze the relationship between VFA and linear correlation variables in the related indicators of sarcopenia.Results:There were significant differences in TFA, VFA, TMA and SMI among different age groups in subjects with normal BMI (all P<0.05). Pearson correlation analysis showed that VFA was negatively correlated with TMA in some age groups (male: 18-39 years group: r=-0.351; 40-49 years group: r=-0.278; 60-69 years group: r=-0.245; female:40-49 years group: r=-0.251; 50-59 years group: r=-0.270;≥70 years group: r=-0.391; all P<0.01); it was negatively correlated with SMI (male: 18-39 years group: r=-0.352; 40-49 years group: r=-0.340; 50-59 years group: r=-0.266; 60-69 years group: r=-0.316; female: 40-49 years group: r=-0.240; 50-59 years group: r=-0.284; all P<0.001); it was positively correlated with MFC (male: 18-39 years group: r=0.342; 40-49 years group: r=0.291; female: 50-59 years group: r=0.133; 60-69 years group: r=0.284; all P<0.05). Multivariate linear regression analysis showed that VFA was independently and negatively correlated with SMI in both men and women after adjusting for age interference factors (male B=-1.881, t=-6.025, P<0.001; female B=-0.603, t=-2.887, P=0.004), and it was independently positively correlated with MFC (male B=1.230, t=4.271, P<0.001;female B=0.893, t=3.836, P<0.001). There was an independent negative correlation between VFA and TMA in male subjects ( B=0.263, t=2.478, P=0.013). Conclusions:VFA is correlated with TMA, SMI and MFC in people with normal BMI. Regardless of gender, SMI has a negative effect on VFA, and MFC has a positive effect on VFA.

BACKGROUND: Biliary tract carcinomas (BTCs) are relatively rare but lethal primary malignant tumors derived from the biliary tract system. The burden of BTCs varies according to sex, age, region, and country, but limited attention has been paid to the burden of BTCs. We sought to explore the up-to-date data from the Global Burden of Disease Study (GBD) and expand findings by accessing the demographic features of BTC disease burden. METHODS: Using the latest data from the GBD 2021, we evaluated and analyzed the distributions and patterns of BTC disease burden in various age groups, sexes, regions, and countries. RESULTS: The number of incident cases, deaths, and disability-adjusted life-years (DALYs) tended to increase and peaked at 216,770 (95% uncertainty interval [UI]: 181,890-245,240), 171,960 (95% UI: 142,350-194,240), and 3,732,100 (95% UI: 3,102,900-4,317,000) person-years, respectively, in 2021. However, the average global age-standardized rates (ASRs) of incident cases, deaths, and DALYs shrunk by -11.46% (95% UI: -21.91 to 3.35%), -24.09% (95% UI: -33.19 to 16.88%), and -26.25% (95% UI: -35.53 to 18.36%), respectively, from 1990 to 2021. Meanwhile, the male/female ratio (male per 100 female) of incidence, deaths, and DALYs changed from 76.40, 75.41, and 74.72 to 86.89, 79.11, and 82.29, respectively. In 2021, the highest number of incident cases, deaths, and DALYs occurred in East Asia. The top three highest incidences, deaths, and DALYs were observed in China, India, and Japan, and the highest ASRs were observed in Chile in 2021. Analysis of the Human Development Index along with disease burden estimates of BTCs also suggests that the burden of the disease is related to the level of comprehensive development of the society. CONCLUSION This study provided a comprehensive comparison of differences in the burden of disease across populations and over time, and further presented evidence concerning the formulation of prevention and control policies and etiologic studies for BTCs and proposed logical hypotheses to investigate.
Humans ; Global Burden of Disease ; Biliary Tract Neoplasms/epidemiology* ; Male ; Female ; Disability-Adjusted Life Years ; Middle Aged ; Aged ; Adult ; Incidence ; Aged, 80 and over ; Quality-Adjusted Life Years ; Cost of Illness

Objective:To investigate the effects of personalized intermittent energy restriction (IER) diet on sleep related gut microbiome in obese patients.Methods:In this single-arm clinical trial, a total of 35 obese patients who visited Henan Provincial People′s Hospital from April to November 2018 were recruited as research subjects. They underwent a strict 32-day IER diet intervention, divided into 4 stages of 8 days each. Nutritional recipes were formulated and nutritious meals were provided to each obese patient with timed meals, including 55% carbohydrates, 15% protein, and 30% fat per meal. In stages 1, 2, 3, and 4, patients were provided with 2/3, 1/2, 1/3, and 1/4 of their previous calorie intake every other day, respectively, with meals at 8:00 and 16:00. During the remaining time, patients were allowed unrestricted eating at home. Physiological indicators (weight, body mass index, body fat percentage, waist circumference, hip circumference, fasting blood glucose, glycosylated hemoglobin, blood pressure, triglycerides, total cholesterol, high-density lipoprotein, low-density lipoprotein and Pittsburgh Sleep Quality Index (PSQI) scores were observed before and after the intervention. Gut microbiota changes were analyzed using metagenomic sequencing technology, and Spearman′s correlation analysis was used to assess the correlation between significantly different bacterial species and PSQI scores.Results:After the intervention, the body weight, body mass index, and PSQI scores of obese patients were all significantly lower than before intervention [(89.92±14.98) vs (97.53±15.67) kg, (31.94±3.95) vs (34.64±4.05) kg/m 2, (3.43±1.16) vs (5.42±2.27)], the abundance of gut microbiota was significantly higher after the intervention (all P<0.05). There were 45 significantly different bacterial species before and after the intervention, of which 6 bacterial species ( Enterobacter cloacae, Escherichia coli, Odoribacter splanchnicus, Oribacterium sinus, Streptococcus gordonii, and Streptococcus parasanguinis) showed significantly positive correlations with PSQI scores ( r=0.476, 0.475, 0.369, 0.391, 0.401, 0.423) (all P<0.05), and they were mainly enriched in the glutamate and tryptophan synthesis pathways. Conclusions:The personalized IER diet intervention can improve the sleep of obese patients while reducing weight, possibly mediated by changes in gut microbiota through the glutamate and tryptophan pathways.

Objective:To analyze the correlation between quantified body fat distribution measured by computed tomography (CT) and blood lipids in overweight and obese individuals undergoing physical examinations.Methods:In this retrospective cohort study, a total of 3 463 physical examination subjects who underwent chest CT combined with quantified CT examination in the Department of Health Management at Henan Provincial People′s Hospital from January to December 2021 were selected using a comprehensive sampling method. The subjects were divided into three groups: normal group (1, 424 cases), overweight group (1, 531 cases), and obese group (508 cases) based on their body mass index: 18.5 to <24.0 kg/m 2, 24.0 to <28.0 kg/m 2, and≥28.0 kg/m 2, respectively. General information, blood lipid parameters, and different body fat distributions measured by quantified CT (subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, muscle fat content) were collected in the three groups. One-way analysis of variance was used to compare differences in body fat distribution and blood lipid parameters, and Pearson correlation analysis was performed to evaluate the correlation between body fat distribution and blood lipids. Results:In the obese group, compared to the normal and overweight groups, subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, muscle fat content, total cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride levels were significantly higher [males: (152.80±49.27) vs (72.94±22.68), (103.79±28.30) cm 2; (287.95±57.55) vs (156.36±49.40), (224.67±53.10) cm 2; (440.75±72.44) vs (229.31±62.01), (328.46±62.77) cm 2; (12.92±8.61)% vs (6.82±3.31)%, (9.39±4.88)%; (9.06±9.34)% vs (4.55±5.06)%, (6.70±6.73)%; (6.52±0.94) vs (4.87±1.03), (6.27±0.96) mmol/L; (3.05±0.76) vs (2.92±0.86), (2.97±0.77) mmol/L; (2.34±1.42) vs (1.53±0.82), (1.99±1.28) mmol/L; females: (213.82±46.87) vs (104.69±30.62), (155.05±34.90) cm 2; (184.88±46.54) vs (90.67±34.09), (138.92±42.06) cm 2; (398.71±71.28) vs (195.37±55.32), (293.97±57.05) cm 2; (11.36±6.34)% vs (5.51±3.02)%, (7.98±4.77)%; (7.44±7.60)% vs (3.70±3.90)%, (5.56±5.94)%; (5.27±0.96) vs (5.04±0.86), (5.11±0.96) mmol/L; (3.26±0.84) vs (2.92±0.79), (3.01±0.74) mmol/L; (1.74±0.69) vs (1.27±0.65), (1.57±0.77) mmol/L], while high-density lipoprotein cholesterol (HDL-C) was significantly lower [males: (1.17±0.19) vs (1.38±0.28), (1.25±0.25) mmol/L; females: (1.36±0.22) vs (1.59±0.32), (1.42±0.27) mmol/L] (all P<0.001). In males, the visceral fat area and total abdominal fat area in the overweight group were positively correlated with triglycerides ( r=0.175, 0.113) and negatively correlated with HDL-C ( r=-0.125, -0.113), while liver fat content was positively correlated with total cholesterol, LDL-C, and triglycerides ( r=0.083, 0.075, 0.206) and negatively correlated with HDL-C ( r=-0.093) (all P<0.05). In the obese group, the liver fat content was positively correlated with triglycerides ( r=0.170) and negatively correlated with HDL-C ( r=-0.166) in males (both P<0.05). In females, the visceral fat area and total abdominal fat area in the overweight group were positively correlated with total cholesterol, LDL-C, and triglycerides (visceral fat area: r=0.129, 0.160, 0.348; total abdominal fat area: r=0.121, 0.130, 0.283) and negatively correlated with HDL-C ( r=-0.264, -0.173), while liver fat content was positively correlated with triglycerides ( r=0.352) and negatively correlated with HDL-C ( r=-0.195) (all P<0.05). In the obese group, the visceral fat area was positively correlated with triglycerides ( r=0.213) and negatively correlated with HDL-C ( r=-0.223) in females (both P<0.05). Conclusion:Blood lipids are correlated with body fat distribution in overweight and obese individuals undergoing physical examinations, and the degree of correlation varies between different genders and body regions, with triglycerides showing the strongest correlation with liver fat content.

Explainable artificial intelligence aims to interpret how machine learning models make decisions,and many model explainers have been developed in the computer vision field.However,understanding of the applicability of these model explainers to biological data is still lacking.In this study,we comprehensively evaluated multiple explainers by interpreting pre-trained models for pre-dicting tissue types from transcriptomic data and by identifying the top contributing genes from each sample with the greatest impacts on model prediction.To improve the reproducibility and interpretability of results generated by model explainers,we proposed a series of optimization strategies for each explainer on two different model architectures of multilayer perceptron(MLP)and convolutional neural network(CNN).We observed three groups of explainer and model architecture combinations with high reproducibility.Group Ⅱ,which contains three model explainers on aggregated MLP models,identified top contributing genes in different tissues that exhibited tissue-specific manifestation and were potential cancer biomarkers.In summary,our work provides novel insights and guidance for exploring biological mechanisms using explainable machine learning models.

Receptor activity-modulating proteins (RAMPs) are accessory molecules that form complexes with specific G protein-coupled receptors (GPCRs) and modulate their functions. It is established that RAMP interacts with the glucagon receptor family of GPCRs but the underlying mechanism is poorly understood. In this study, we used a bioluminescence resonance energy transfer (BRET) approach to comprehensively investigate such interactions. In conjunction with cAMP accumulation, Gα _q activation and β-arrestin1/2 recruitment assays, we not only verified the GPCR-RAMP pairs previously reported, but also identified new patterns of GPCR-RAMP interaction. While RAMP1 was able to modify the three signaling events elicited by both glucagon receptor (GCGR) and glucagon-like peptide-1 receptor (GLP-1R), and RAMP2 mainly affected β-arrestin1/2 recruitment by GCGR, GLP-1R and glucagon-like peptide-2 receptor, RAMP3 showed a widespread negative impact on all the family members except for growth hormone-releasing hormone receptor covering the three pathways. Our results suggest that RAMP modulates both G protein dependent and independent signal transduction among the glucagon receptor family members in a receptor-specific manner. Mapping such interactions provides new insights into the role of RAMP in ligand recognition and receptor activation.

Hyaluronic acid is widely present in the human body. It is an important component of extracellular matrix. It has unique hydrodynamic properties, good viscoelasticity and strain properties. At present, hyaluronic acid has been widely used in biomaterials, targeted-drug preparations, cosmetics and prevention of adhesion after abdominal surgery. With the expansion of the application scope of hyaluronic acid and the continuous emergence of new medical materials, the research on hyaluronic acid has been increasing in recent years. This paper reviews the clinical application of hyaluronic acid and its mechanism, in order to provide reference for the further development and safe application of hyaluronic acid products.

Abstract Socioeconomic status is an important factor affecting all-cause mortality. Income, education and occupation alone or in combination have been employed as a measure of socioeconomic status; however, the study results vary in measures. Material mechanism, lifestyle mechanism, psychological mechanism and community neighborhood mechanism have been accepted as the main intermediate mechanisms for the impact of socioeconomic status on all-cause mortality; however, the contribution of these mechanisms remains controversial. Based on the international and national publications pertaining to the association between socioeconomic status and all-cause mortality from 2012 to 2021, this review summarizes the relationship between socioeconomic status and all-cause mortality in different metrics and the intermediate mechanism of the impact of socioeconomic status on all-cause mortality, so as to provide insights for further studies.