ObjectiveTo develop a nomogram-based risk prediction model for chronic obstructive pulmonary disease (COPD) incidence among the community-dwelling population aged 40 years old and above, so as to provide targeted references for the screening and prevention of COPD. MethodsBased on a natural population cohort in suburban Shanghai, a total of 3 381 randomly selected participants aged ≥40 years underwent pulmonary function tests between July and October 2021. Cox stepwise regression analysis was used to develop overall and gender-specific risk prediction models, along with the construction of corresponding risk nomograms. Model predictive performance was evaluated using the C-indice, area under the curve (AUC) values, and Brier score. Stability was assessed through 10-fold cross-validation and sensitivity analysis. ResultsA total of 3 019 participants were included, with a median follow-up duration of 4.6 years. The COPD incidence density was 17.22 per 1 000 person-years, significantly higher in males (32.04/1 000 person-years) than that in females (7.38/1 000 person-years) (P<0.001). The overall risk prediction model included the variables such as gender, age, education level, BMI, smoking, passive smoking, and respiratory comorbidities. The male-specific model incorporated the variables such as age, BMI, respiratory comorbidities, and smoking, while the female-specific model included age, marital status, respiratory comorbidities, and pulmonary tuberculosis history. The C-indices for the overall, male-specific, and female-specific models were 0.829, 0.749, and 0.807, respectively. The 5-year AUC values were 0.785, 0.658, and 0.811, with Brier scores of 0.103, 0.176, and 0.059, respectively. Both 10-fold cross-validated C-indices and sensitivity analysis (excluding participants with a follow-up duration of <6 months) yielded C-indices were above 0.740. ConclusionThis study developed concise and practical overall and gender-specific COPD risk prediction models and corresponding nomograms. The models demonstrated robust performance in predicting COPD incidence, providing a valuable reference for identifying high-risk populations and formulating targeted screening and personalized management strategies.

Microbial-derived metabolites are important mediators of host-microbial interactions. In recent years, the role of intestinal microbial metabolites in colorectal cancer has attracted considerable attention. These metabolites, which can be derived from bacterial metabolism of dietary substrates, modification of host molecules such as bile acids, or directly from bacteria, strongly influence the progression of colitis-associated cancer (CAC) by regulating inflammation and immune response. Here, we review how microbiome metabolites short-chain fatty acids (SCFAs), secondary bile acids, polyamines, microbial tryptophan metabolites, and polyphenols are involved in the tumorigenesis and development of CAC through inflammation and immunity. Given the heated debate on the metabolites of microbiota in maintaining gut homeostasis, serving as tumor molecular markers, and affecting the efficacy of immune checkpoint inhibitors in recent years, strategies for the prevention and treatment of CAC by targeting intestinal microbial metabolites are also discussed in this review.
Humans ; Gastrointestinal Microbiome/physiology* ; Animals ; Carcinogenesis/metabolism* ; Colitis-Associated Neoplasms/microbiology* ; Fatty Acids, Volatile/metabolism* ; Bile Acids and Salts/metabolism* ; Colitis/microbiology*

OBJECTIVES: To evaluate the application value of genetic newborn screening (gNBS) in the Yunnan region. METHODS: A prospective study was conducted with a random selection of 3 001 newborns born in the Yunnan region from February to December 2021. Traditional newborn screening (tNBS) was used to test biochemical indicators, and targeted next-generation sequencing was employed to screen 159 genes related to 156 diseases. Positive-screened newborns underwent validation and confirmation tests, and confirmed cases received standardized treatment and long-term follow-up. RESULTS: Among the 3 001 newborns, 166 (5.53%) were initially positive for genetic screening, and 1 435 (47.82%) were genetic carriers. The top ten genes with the highest variation frequency were GJB2 (21.29%), DUOX2 (7.27%), HBA (6.14%), GALC (3.63%), SLC12A3 (3.33%), HBB (3.03%), G6PD (2.94%), SLC25A13 (2.90%), PAH (2.73%), and UNC13D (2.68%). Among the initially positive newborns from tNBS and gNBS, 33 (1.10%) and 47 (1.57%) cases were confirmed, respectively. A total of 48 (1.60%) cases were confirmed using gNBS+tNBS. The receiver operating characteristic curve analysis demonstrated that the areas under the curve for tNBS, gNBS, and gNBS+tNBS in diagnosing diseases were 0.866, 0.982, and 0.968, respectively (P<0.05). DeLong's test showed that the area under the curve for gNBS and gNBS+tNBS was higher than that for tNBS (P<0.05). CONCLUSIONS gNBS can expand the range of disease detection, and its combined use with tNBS can significantly shorten diagnosis time, enabling early intervention and treatment.
Humans ; Infant, Newborn ; Neonatal Screening ; Genetic Testing ; Female ; Male ; Follow-Up Studies ; Prospective Studies ; China

OBJECTIVE: To investigate the genetic causal relationship of leukocyte telomere length (LTL) with prostatitis, orchitis and epididymitis by two-sample Mendelian randomization (MR). METHODS: Using LTL as the exposure factor and prostatitis, orchitis and epididymitis as outcome factors, we mined the Database of Genome-Wide Association Studies (GWAS). Then, we analyzed the causal relationship of LTL with prostatitis, orchitis and epididymitis by Mendelian randomization using inverse variance weighting (IVW) as the main method and weighted median and MR-Egger regression as auxiliary methods, determined the horizontal multiplicity by MR-Egger intercept test, and conducted sensitivity analysis using the leaving-one-out method. RESULTS: A total of 121 related single nucleotide polymorphisms (SNPs) were identified in this study. IVW showed LTL to be a risk factor for prostatitis (OR = 1.383, 95% CI: 1.044－1.832, P = 0.024), and for orchitis and epididymitis as well (OR = 1.770, 95% CI: 1.275－2.456, P = 0.000 6). CONCLUSION Genetic evidence from Mendelian randomized analysis indicates that shortening of LTL reduces the risk of prostatitis, orchitis and epididymitis.
Humans ; Male ; Mendelian Randomization Analysis ; Epididymitis/genetics* ; Prostatitis/genetics* ; Polymorphism, Single Nucleotide ; Leukocytes ; Orchitis/genetics* ; Genome-Wide Association Study ; Telomere ; Risk Factors

Hypercholesterolemia is a significant risk factor for the development of atherosclerosis. 2',3',5'-Tri-O-acetyl-N ⁶-(3-hydroxyphenyl) adenosine (IMM-H007), a novel AMPK agonist, has shown protective effects in metabolic diseases. However, its impact on cholesterol and triglyceride metabolism in hypercholesterolemia remains unclear. In this study, we aimed to elucidate the effects and specific mechanisms by which IMM-H007 regulates cholesterol and triglyceride metabolism. To achieve this goal, we used Apoe ^-/- and Ldlr ^-/- mice to establish a hypercholesterolemia/atherosclerosis model. Additionally, hepatocyte-specific Ampka1/2 knockout mice were subjected to a 5-week high-cholesterol diet to establish hypercholesterolemia, while atherosclerosis was induced via AAV-PCSK9 injection combined with a 16-week high-cholesterol diet. Our results demonstrated that IMM-H007 improved cholesterol and triglyceride metabolism in mice with hypercholesterolemia. Mechanistically, IMM-H007 modulated the AMPKα1/2-LDLR signaling pathway, increasing cholesterol uptake in the liver. Furthermore, IMM-H007 activated the AMPKα1-FXR pathway, promoting the conversion of hepatic cholesterol to bile acids. Additionally, IMM-H007 prevented hepatic steatosis by activating the AMPKα1/2-ATGL pathway. In conclusion, our study suggests that IMM-H007 is a promising therapeutic agent for improving hypercholesterolemia and atherosclerosis through the activation of AMPKα.

Diabetic retinopathy, a prevalent and vision-threatening microvascular complication of diabetes mellitus, is the leading cause of blindness among middle-aged and elderly individuals. Natural diterpenoids isolated from Siegesbeckia pubescens demonstrate potent anti-inflammatory properties. This study aimed to identify novel bioactive diterpenoids from S. pubescens and investigate their effects on oxidative stress and inflammatory responses in diabetic retinopathy, both in vitro and in vivo. Three new ent-pimarane-type diterpenoids (1-3) and six known compounds (4-9) were isolated from the aerial parts of S. pubescens. Their structures were elucidated through spectroscopic data interpretation, and absolute configurations were determined by comparing calculated and experimental electronic circular dichroism (ECD) spectra. Among these compounds, 14β,16-epoxy-ent-3β,15α,19-trihydroxypimar-7-ene (5) exhibited the most potent protective effect against high glucose and interleukin-1β (IL-1β)-stimulated human retinal endothelial cells. Mechanistically, compound 5 promoted endothelial cell survival while ameliorating oxidative stress and inflammatory response in diabetic retinopathy, both in vivo and in vitro. These findings not only suggest that diterpenoids such as compound 5 are important anti-inflammatory constituents in S. pubescens, but also indicate that compound 5 may serve as a lead compound for preventing or treating vascular complications associated with diabetic retinopathy.
Diabetic Retinopathy/metabolism* ; Humans ; Oxidative Stress/drug effects* ; Animals ; Diterpenes, Kaurane/administration & dosage* ; Asteraceae/chemistry* ; Male ; Endothelial Cells/drug effects* ; Abietanes/administration & dosage* ; Molecular Structure ; Mice ; Anti-Inflammatory Agents/chemistry* ; Plant Extracts/chemistry* ; Mice, Inbred C57BL

Objective To investigate the associations of reproductive health indicators with lung function and chronic obstructive pulmonary disease(COPD)among women aged 40 years and above.Methods From Jul to Sep,2021,female subjects aged 40 years and above were randomly selected from the Shanghai Suburban Adult Cohort and Biobank for COPD screening.A questionnaire was used to obtain information on demographic characteristics and reproductive health indicators.Linear regression was used to analyze the effects of reproductive health indicators on forced vital capacity(FVC)and forced expiratory volume in the first second(FEV1).Logistic regression was also used to analyze the effects of reproductive health factors on FVC as a percentage of the predicted value(FVC%Pred)and FEV1%Pred as well as on COPD.Results A total of 1876 women aged 40 years and above were enrolled with mean age of(62.1±8.2)years old,among them,78.1%were menopausal,and 40.9%had been pregnant≥3 times.Multivariate analysis showed that FVC and FEV1 decreased in postmenopausal women,but menopause was not associated with a decrease in their percentage of predicted values.Pregnancies≥3 times was a risk factor for COPD(for 3 times,OR=4.92,95%CI:1.48-19.95,P<0.05;for≥4 times,OR=9.06,95%CI:2.32-41.57,P<0.01),while pregnancies of 2 times did not increase the risk of COPD.Conclusion In women aged 40 years and above,menopause is associated with poorer FVC and FEV1,and excessive pregnancy(≥3 times)is a risk factor for COPD.

Objective:To clone the Helicobacter pylori(Hp)hp0169 gene and conduct the crystallographic study,and to clarify its secondary and tertiary structures.Methods:The hp0169 gene and its encoded protein sequence of the Hp NCTC26695 strain were retrieved from the UniProt database.Bioinformatics method was used to analyze the physicochemical properties of the Hp recombinant protease(HpPrtC)protein;SOPMA and DNAStrar softwares were used to predict the secondary structure characteristics of HpPrtC protein;SWISS-MODEL software was used to construct the tertiary structure of the HpPrtC protein;IEDB and ABCpred softwares were used to predict the antigenic epitopes of the B lymphocytes HpPrtC protein;SYFPEITMI website was used to predict the antigenic epitopes of the T lymphocytes of HpPrtC protein;the expert pool(EP)and random forest(RF)algorithms were used to predict the crystallizability of the HpPrtC protein;the HpPrtC recombinant protein was expressed in the prokaryotic system;the HpPrtC recombinant protein was purified by Ni2+affinity chromatography and size-exclusion chromatography;the crystallization conditions for HpPrtC were screened by crystallization kit.Results:The hp0169 gene contained 1 269 base pairs and encoded the protein of 422 amino acids,the theoretical isoelectric point was 7.64 and the relative molecular weight was 47 300.HpPrtC was a hydrophilic and soluble protein.The number of amino acids of alpha helices of HpPrtC accounted for 35.78%,beta sheets 18.72%,beta turns 6.87%,and random coils 38.63%.The antigen epitope analysis results showed that HpPrtC contained five dominant linear epitopes of B lymphocytes,three conformational epitopes,and multiple potential dominant epitopes of T lymphocytes.The homology modeling results showed that HpPrtC formed a dimer,and each monomer displayed a barrel structure surrounded by β sheets,alpha helices,and random coils.HpPrtC was predicted to have moderate crystallizability without signal peptides and transmembrane helices.Small clustered needle-like crystals of HpPrtC were obtained under the conditions of 0.2 mol·L-1 magnesium chloride,0.1 mol·L-1 tris(hydroxymethyl)amino methane(Tris),3.4 mol·L-1 hexanediol,and pH=8.5.Conclusion:HpPrtC is a hydrophilic protein that forms a dimeric structure and crystallizes into small clustered needle-like crystals under suitable conditions.HpPrtC contains dominant antigenic epitopes of the T lymphocytes and B lymphocytes and can serve as an antigen for the design of Hp vaccines to establish the multivalent fusion vaccines or multi-epitope vaccines;the results provide an experimental basis for the prevention and control of Hp.

Objective To establish an early prediction model for the diagnosis of severe acute pancreatitis based on the improved machine learning models,and to analyze its clinical value.Methods A case-control study was conducted on 352 patients with acute pancreatitis admitted to the Gastroenterology and Hepatobiliary Surgery Departments of the Army Medical Center of PLA and Emergency and Critical Care Medicine Department of No.945 Hospital of Joint Logistics Support Force of PLA from January 2014 to August 2023.According to the severity of the disease,the patients were divided into the severe group(n=88)and the non-severe group(n=264).The RUSBoost model and improved Archimead optimization algorithm was used to analyze 39 routine laboratory biochemical indicators within 48 h after admission to construct an early diagnosis and prediction model for severe acute pancreatitis.The task of feature screening and hyperparameter optimization was completed simultaneously.The ReliefF algorithm feature importance rank and multivariate logistic analysis were used to analyze the value of the selected features.Results In the training set,the area under curve(AUC)of the improved machine learning model was 0.922.In the testing set,the AUC of the improved machine learning model reached 0.888.The 4 key features of predicting severe acute pancreatitis based on the improved Archimedes optimization algorithm were C-reactive protein,blood chlorine,blood magnesium and fibrinogen level,which were consistent with the results of ReliefF algorithm feature importance ranking and multivariate logistic analysis.Conclusion The application of improved machine learning model analyzing the laboratory examination results can help to early predict the occurrence of severe acute pancreatitis.

ObjectiveTo evaluate the efficacy of three screening questionnaires for COPD in the community residents of Songjiang District， Shanghai， and to provide a basis for selecting COPD screening questionnaire and process that are more suitable. MethodsCommunity residents aged 40 years or over were randomly selected from the Shanghai Suburban Adult Cohort and Biobank for the study with screening questionnaires and spirometry. Questionnaires included the COPD screening questionnaire （COPD-SQ）， the COPD population screener （COPD-PS） and the revised COPD diagnostic questionnaire （revised-CDQ）. Evaluation of the efficacy of these questionnaires was based on the area under the receiver operating characteristic curve （AUC） of the subjects. DeLong test was used to compare the accuracy of different questionnaires； Z test was used to compare the accuracy of different cut-off values for the same questionnaire. ResultsAmong 3 184 community residents， a total of 259 （8.1%） COPD patients were screened by spirometry. AUC values of these 3 screening questionnaires were >0.7 indicating that they were reliable COPD screening tools. The sensitivity and specificity of the questionnaires at the recommended cut-off values were COPD-SQ （63.7% and 72.2%）， COPD-PS （12.0% and 96.1%）， and revised CDQ （78.8% and 52.7%）， with the COPD-SQ having the highest screening accuracy （AUC=0.754）. The optimal and recommended cut-off values for the three questionnaires differed in this population， but the difference in accuracy was statistically significant only for COPD-PS. The optimal cut-off values for the three questionnaires differed between male and female， and the sensitivity and accuracy of COPD-SQ and COPD-PS improved when lower cut-off values were used for women. The AUC was greater when two questionnaires were utilized simultaneously for screening， but the differences were not statistically significant. ConclusionThe COPD-SQ is recommended for primary COPD screening； a lower cut-off value for women should be considered. The COPD screening questionnaire needs to be further improved for the early diagnosis and treatment of COPD patients.