This study aims to analyze the screening results and epidemiological characteristics of prostate cancer (PCa) among elderly males in the rural areas of Songjiang, Shanghai City, through the implementation of a preliminary prostate-specific antigen (PSA) screening based on a community-linkage model, and to explore an effective screening approach. A retrospective observational study design was employed to collect data from residents who underwent PSA screening at Songjiang Hospital affiliated to Shanghai Jiao Tong University School of Medicine, in collaboration with multiple community health service centers in Songjiang District, Shanghai City, between June 2022 and June 2024, through free clinics and annual health examinations. Prostate biopsy was recommended for individuals with total PSA (tPSA) levels >10 ng/ml and those with 4 ng/ml≤tPSA≤10 ng/ml and abnormal free-to-total PSA (f/tPSA) ratios. Clinical characteristics of detected PCa patients were analyzed. Follow-up was conducted through phone calls and home visits by family doctors, coupled with enhanced health education. The results indicated that a total of 17 198 residents participated in the screening, among which 2 234 (12.99%) had tPSA levels between 4 ng/ml and 10 ng/ml, and 257 (1.49%) had tPSA levels >10 ng/ml. Ultimately, 417 residents underwent prostate biopsy, with 171 being diagnosed with PCa, yielding a positive biopsy rate of 41.00% and a PCa detection rate of 0.99%. The predominant pathological subtype among PCa patients was adenocarcinoma (168 cases, 98.24%). Of the 146 PCa patients who received treatment, the majority were classified as intermediate or high-risk (124 cases, 84.93%). Furthermore, with the optimization of the screening model, there was a significant increase in the proportion of subsequent outpatient visits. In conclusion, the community-linkage-based PSA screening model demonstrated high effectiveness in screening for PCa among elderly males in the rural areas of Songjiang, Shanghai City. Epidemiological findings revealed that PCa patients in this region are primarily composed of intermediate and high-risk groups, highlighting the need for intensified early screening and health education.

With the development of education and technology, the construction of research public platforms has emerged as a critical initiative for many universities and top-tier public hospitals. The core and most fundamental function of a basic public platform is to aggregate large instruments and specific resources, providing open services for instrumental analysis and sample testing. Optimized management and high-quality, efficient services are essential for such platforms. This article elucidates the construction of a research public platform in West China Hospital, focusing on the adoption of hierarchical management and precise services. The core of the hierarchical management lies in building a multi-level service platform composed of routine support platforms, advanced technology platforms, and specially qualification platforms, while establishing a talent hierarchy that differentiates between core and routine positions. This structure is designed to accurately meet the diverse needs of users and enhance resource efficiency. By implementing user access control with differentiated permissions for internal and external users and a dynamic credit-based review system, the laboratory can ensure safe and efficient operations. The four service modes-instrument usage, in-lab experiments, sample testing, and collaborative projects-are precisely aligned with various research scenarios. Proactive engagement with grant-funded projects, customized services for research groups, and a multidimensional training system further strengthen the platform's support for major scientific research tasks. Through systematic management and service innovation, this model achieves efficient integration and sustainable development of platform resources, providing a valuable reference for the construction of public platforms in similar medical institutions.
China ; Research ; Laboratories/organization & administration*

Objective To investigate the clinical characteristics of colorectal polyps in patients with melanosis coli(MC),analyze the recurrence risk after polypectomy,and construct a prediction model for polyp recurrence.Methods A total of 1,763 patients who underwent colorectal polypec-tomy at the First Hospital of Handan from January 2017 to June 2023 were divided into MC group(n=149)and non-MC group(n=1,614).Among them,122 patients in the MC group underwent colonoscopic re-examination one year later and were further divided into recurrence group(n=52)and non-recurrence group(n=70)based on polyp recurrence.The characteristics of colorectal polyps and recurrence risk after polypectomy in MC patients were analyzed.A multivariable Logistic regression analysis was used to construct a polyp recurrence risk model,and the nomogram model was plotted using R studio software.The receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis were employed to evaluate the discrimination,calibration,and clinical practicality of the model.Results The detection rates of large polyps(≥1.0 cm),right-sided colon polyps,multiple polyps(≥3 polyps),and Yamada type Ⅰ polyps in the MC group were significantly higher than those in the non-MC group,while the detection rates of left-sided co-lon polyps and Yamada type Ⅳ polyps were significantly lower(P＜0.05).The detection rates of adenomatous polyps and polyps with mild dysplasia in the MC group were significantly higher than those in the non-MC group,whereas the detection rate of polyps with moderate dysplasia in the MC group was significantly lower(P＜0.05).Significant differences were observed between the recur-rence and non-recurrence groups in terms of a history of cholecystectomy,Helicobacter pylori(Hp)in-fection,and family history of colorectal cancer(P＜0.05).There were also significant differences in the distribution,size,and the number of initial polyps between the two groups(P＜0.05).Multivari-able Logistic regression analysis identified cholecystectomy,Hp infection,first-degree relatives with colorectal cancer,polyp size(≥1 cm),and multiple polyps(≥3 polyps)as independent risk factors for polyp recurrence after polypectomy(P＜0.05).Based on these factors,a recurrence prediction model was constructed.The area under the curve(AUC)of this model was 0.824(95％CI,0.753 to 0.895),indicating good discrimination.The calibration curve showed a good fit.Decision curve anal-ysis demonstrated a high net benefit within the threshold range of 0.1 to 0.8,suggesting that the mod-el had a wide range of beneficial thresholds and clinical practical value.Conclusion Compared with the non-MC group,the MC group has higher detection rates of large polyps,right-sided colon pol-yps,multiple polyps,Yamada type Ⅰ polyps,adenomatous polyps,and polyps with low-grade dys-plasia,but lower detection rates of left-sided colon polyps,Yamada type Ⅳ polyps,and polyps with moderate dysplasia.Cholecystectomy,Hp infection,first-degree relatives with colorectal cancer,large polyps(≥1 cm),and multiple polyps(≥3 polyps)are independent risk factors for polyp re-currence after colorectal polypectomy in MC patients.The recurrence prediction model constructed based on these factors has high practical value.

Objective To identify risk factors for colorectal adenomatous polyps using logistic regression analysis,construct a prediction model based on these identified factors,and subsequently evaluate the performance of the model.Methods Encompassed 1,023 patients who underwent large intestine polyp resection at the First Hospital of Handan between January 2017 and January 2022.Among these patients,676 had adenomatous polyps(adenomatous polyp group)and 347 had non-adenomatous polyps(non-adenomatous polyp group).We collected data on basic information,medical history,colonoscopy results,and polyp pathology.By comparing the two groups,we identified significant differences in various indicators,which were selected as candidate factors for model construction.Patients were randomly divided into a training set and a validation set at an 8∶2 ratio.Using the training set data,we constructed a risk prediction model and developed a nomogram using R Studio software to visually present the model.Finally,we internally validated the model using the validation set.The model's discrimination ability was evaluated using the ROC curve,its accuracy was assessed via the calibration curve,and its clinical utility was evaluated through decision curve analysis(DCA).Results Significant differences were observed between the two groups in terms of age,drinking habits,family history of colorectal cancer,hyperlipid-emia,history of cholecystectomy,HP infection,and history of appendectomy(P<0.05).These variables were included in the model construction.A total of 818 participants were randomly assigned to the training set,while 205 were allocated to the validation set.Multivariate logistic regression analysis on the training set confirmed that age(OR=1.021,95%CI:1.006～1.036,P=0.006),alcohol consumption(OR=3.440,95%CI:2.251～5.257,P<0.001),first-degree relatives with colorectal cancer(OR=3.775,95%CI:1.881～7.577,P<0.001),hyperlipidemia(OR=3.428,95%CI:2.443～4.808,P<0.001),history of cholecystectomy(OR=3.916,95%CI:1.756～8.735,P<0.001),Helicobacter pylori(HP)infection(OR=3.292,95%CI:2.309～4.693,P<0.001),and history of appendectomy(OR=3.819,95%CI:2.002～7.286,P<0.001)were independent risk factors for adenomatous polyps.Consequently,a prediction model for large intestine adenomatous polyps was developed using the formula P=1/(1+e-Y),where Y=0.020×age+1.328×first-degree relatives with colorectal cancer+1.235×alcohol consumption+1.232×hyperlipidemia+1.365×cholecystectomy+1.192×HP infection+1.340×appendectomy-1.995.The model demonstrated good performance with AUC values of 0.763(95%CI:0.729～0.797)for the training set and 0.769(95%CI:0.644～0.787)for the validation set.The calibration curve indicated a good fit,and decision curve analysis showed that the model could achieve positive net benefit across a wide range of threshold probabilities,confirming its clinical utility.Conclusions Age,alcohol consumption,a family history of colorectal cancer in first-degree relatives,hyperlipidemia,cholecystectomy,HP infection,and appendectomy were identified as independent risk factors for adenomatous polyps.A prediction model incorporating these risk factors holds significant practical value for predicting the occurrence of colorectal adenomatous polyps.

Objective To identify risk factors for colorectal adenomatous polyps using logistic regression analysis,construct a prediction model based on these identified factors,and subsequently evaluate the performance of the model.Methods Encompassed 1,023 patients who underwent large intestine polyp resection at the First Hospital of Handan between January 2017 and January 2022.Among these patients,676 had adenomatous polyps(adenomatous polyp group)and 347 had non-adenomatous polyps(non-adenomatous polyp group).We collected data on basic information,medical history,colonoscopy results,and polyp pathology.By comparing the two groups,we identified significant differences in various indicators,which were selected as candidate factors for model construction.Patients were randomly divided into a training set and a validation set at an 8∶2 ratio.Using the training set data,we constructed a risk prediction model and developed a nomogram using R Studio software to visually present the model.Finally,we internally validated the model using the validation set.The model's discrimination ability was evaluated using the ROC curve,its accuracy was assessed via the calibration curve,and its clinical utility was evaluated through decision curve analysis(DCA).Results Significant differences were observed between the two groups in terms of age,drinking habits,family history of colorectal cancer,hyperlipid-emia,history of cholecystectomy,HP infection,and history of appendectomy(P<0.05).These variables were included in the model construction.A total of 818 participants were randomly assigned to the training set,while 205 were allocated to the validation set.Multivariate logistic regression analysis on the training set confirmed that age(OR=1.021,95%CI:1.006～1.036,P=0.006),alcohol consumption(OR=3.440,95%CI:2.251～5.257,P<0.001),first-degree relatives with colorectal cancer(OR=3.775,95%CI:1.881～7.577,P<0.001),hyperlipidemia(OR=3.428,95%CI:2.443～4.808,P<0.001),history of cholecystectomy(OR=3.916,95%CI:1.756～8.735,P<0.001),Helicobacter pylori(HP)infection(OR=3.292,95%CI:2.309～4.693,P<0.001),and history of appendectomy(OR=3.819,95%CI:2.002～7.286,P<0.001)were independent risk factors for adenomatous polyps.Consequently,a prediction model for large intestine adenomatous polyps was developed using the formula P=1/(1+e-Y),where Y=0.020×age+1.328×first-degree relatives with colorectal cancer+1.235×alcohol consumption+1.232×hyperlipidemia+1.365×cholecystectomy+1.192×HP infection+1.340×appendectomy-1.995.The model demonstrated good performance with AUC values of 0.763(95%CI:0.729～0.797)for the training set and 0.769(95%CI:0.644～0.787)for the validation set.The calibration curve indicated a good fit,and decision curve analysis showed that the model could achieve positive net benefit across a wide range of threshold probabilities,confirming its clinical utility.Conclusions Age,alcohol consumption,a family history of colorectal cancer in first-degree relatives,hyperlipidemia,cholecystectomy,HP infection,and appendectomy were identified as independent risk factors for adenomatous polyps.A prediction model incorporating these risk factors holds significant practical value for predicting the occurrence of colorectal adenomatous polyps.

This study aims to analyze the screening results and epidemiological characteristics of prostate cancer (PCa) among elderly males in the rural areas of Songjiang, Shanghai City, through the implementation of a preliminary prostate-specific antigen (PSA) screening based on a community-linkage model, and to explore an effective screening approach. A retrospective observational study design was employed to collect data from residents who underwent PSA screening at Songjiang Hospital affiliated to Shanghai Jiao Tong University School of Medicine, in collaboration with multiple community health service centers in Songjiang District, Shanghai City, between June 2022 and June 2024, through free clinics and annual health examinations. Prostate biopsy was recommended for individuals with total PSA (tPSA) levels >10 ng/ml and those with 4 ng/ml≤tPSA≤10 ng/ml and abnormal free-to-total PSA (f/tPSA) ratios. Clinical characteristics of detected PCa patients were analyzed. Follow-up was conducted through phone calls and home visits by family doctors, coupled with enhanced health education. The results indicated that a total of 17 198 residents participated in the screening, among which 2 234 (12.99%) had tPSA levels between 4 ng/ml and 10 ng/ml, and 257 (1.49%) had tPSA levels >10 ng/ml. Ultimately, 417 residents underwent prostate biopsy, with 171 being diagnosed with PCa, yielding a positive biopsy rate of 41.00% and a PCa detection rate of 0.99%. The predominant pathological subtype among PCa patients was adenocarcinoma (168 cases, 98.24%). Of the 146 PCa patients who received treatment, the majority were classified as intermediate or high-risk (124 cases, 84.93%). Furthermore, with the optimization of the screening model, there was a significant increase in the proportion of subsequent outpatient visits. In conclusion, the community-linkage-based PSA screening model demonstrated high effectiveness in screening for PCa among elderly males in the rural areas of Songjiang, Shanghai City. Epidemiological findings revealed that PCa patients in this region are primarily composed of intermediate and high-risk groups, highlighting the need for intensified early screening and health education.

Purpose::Cerebral edema (CE) is the main secondary injury following traumatic brain injury (TBI) caused by road traffic accidents (RTAs). It is challenging to be predicted timely. In this study, we aimed to develop a prediction model for CE by identifying its risk factors and comparing the timing of edema occurrence in TBI patients with varying levels of injuries.Methods::This case-control study included 218 patients with TBI caused by RTAs. The cohort was divided into CE and non-CE groups, according to CT results within 7 days. Demographic data, imaging data, and clinical data were collected and analyzed. Quantitative variables that follow normal distribution were presented as mean ± standard deviation, those that do not follow normal distribution were presented as median (Q 1, Q 3). Categorical variables were expressed as percentages. The Chi-square test and logistic regression analysis were used to identify risk factors for CE. Logistic curve fitting was performed to predict the time to secondary CE in TBI patients with different levels of injuries. The efficacy of the model was evaluated using the receiver operator characteristic curve. Results::According to the study, almost half (47.3%) of the patients were found to have CE. The risk factors associated with CE were bilateral frontal lobe contusion, unilateral frontal lobe contusion, cerebral contusion, subarachnoid hemorrhage, and abbreviated injury scale (AIS). The odds ratio values for these factors were 7.27 (95% confidence interval ( CI): 2.08 -25.42, p = 0.002), 2.85 (95% CI: 1.11 -7.31, p = 0.030), 2.62 (95% CI: 1.12 -6.13, p = 0.027), 2.44 (95% CI: 1.25 -4.76, p = 0.009), and 1.5 (95% CI: 1.10 -2.04, p = 0.009), respectively. We also observed that patients with mild/moderate TBI (AIS ≤ 3) had a 50% probability of developing CE 19.7 h after injury (χ 2= 13.82, adjusted R2 = 0.51), while patients with severe TBI (AIS > 3) developed CE after 12.5 h (χ 2= 18.48, adjusted R2 = 0.54). Finally, we conducted a receiver operator characteristic curve analysis of CE time, which showed an area under the curve of 0.744 and 0.672 for severe and mild/moderate TBI, respectively. Conclusion::Our study found that the onset of CE in individuals with TBI resulting from RTAs was correlated with the severity of the injury. Specifically, those with more severe injuries experienced an earlier onset of CE. These findings suggest that there is a critical time window for clinical intervention in cases of CE secondary to TBI.

Objective To investigate the causality between dietary factors and gastroesophageal reflux disease (GERD) based on Mendelian randomization (MR) analysis. Methods Twenty-nine dietary factors were considered as exposure factors, and GERD as the outcome factors. Relevant data were obtained from the IEU open genome-wide association study (GWAS) database, and appropriate instrumental variables (IVs) were selected for MR analysis. The inverse variance weighted (IVW) method was primarily used to evaluate the results, with MR-Egger regression and the weighted median estimator (WME) serving as supplementary MR analysis methods to explore the associations between various dietary factors and GERD. Different models and tests were employed for sensitivity analysis to examine heterogeneity, horizontal pleiotropy, and robustness of the results. Results A total of eight dietary factors were identified to have significant associations with GERD through MR analysis. Specifically, intake of dried fruits (OR=0.530, 95%CI, 0.418 to 0.674, P < 0.001), amount of fresh fruits (OR=0.631, 95%CI, 0.480 to 0.829, P=0.001), intake of herbal tea (OR=0.995, 95%CI, 0.990 to 0.999, P=0.026), intake of oily fish (OR=0.793, 95%CI, 0.643 to 0.976, P=0.029), and intake of cheese (OR=0.718, 95%CI, 0.597 to 0.868, P=0.001) were negatively associated with GERD, while alcohol consumption frequency (OR=1.329, 95%CI, 1.207 to 1.463, P < 0.001), pork intake (OR=1.806, 95%CI, 1.116 to 2.922, P=0.016), and intake of sugary food/beverage (OR=4.062, 95%CI, 1.543 to 10.696, P=0.001) were positively associated with GERD. Conclusion Intake of dried fruits, fresh fruit, herbal tea, oily fish, and cheese may reduce the risk of GERD, while high alcohol consumption frequency, pork intake, and intake of sugary foods or beverages are associated with an increased risk of GERD.

Hypertension, a primary cause of cardiovascular and cerebrovascular events, has become a major global public health problem and caused a heavy burden of health economics on the society. In "the 20 Most Important and Most Preventable Health Problems" released by the Chinese Academy of Engineering, hypertension was ranked the second. Due to the disease complexity, many hypertension patients need to take antihypertensive drugs for life. Although significant progress has been achieved in blood pressure lowering by western medicines, the problems including adverse reactions, poor compliance due to long-term medication, and ineffective mitigation in clinical symptoms related to hypertension remain to be addressed. In the last decade, the research on traditional Chinese medicine(TCM) treatment of hypertension has received much attention and achieved remarkable progress. The TCM treatment of hypertension is the most active area of research with integrated Chinese and western medicine in China. In addition to lowering blood pressure smoothly, TCM can alleviate clinical symptoms, reverse risk factors, improve the quality of life, and protect target organs from the damage caused by hypertension. This article systematically reviews the research progress of TCM in treating hypertension in the last decade from the following four aspects: consensus on guideline, clinical trial, experimental study, and systematic review/Meta-analysis. It summarized the evidence of TCM in reducing blood pressure and clarified the mechanism of TCM in reducing blood pressure, aiming to provide a reference for the TCM diagnosis and treatment of hypertension and the development of new drugs.
Humans ; Antihypertensive Agents/therapeutic use* ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/drug therapy* ; Medicine, Chinese Traditional

This study evaluated the scientific nature and effectiveness of iterative optimization of prevention and control measures for local outbreaks caused by the BA.2 and BA.5.2 COVID-19 strains in Fujian Province in 2022,to provide a scientif-ic basis for responding to future new or recurrent respiratory infectious diseases.According to the theory of infectious disease dynamics,relevant information regarding the local epidemic situation caused by the BA.2 sub-type Omicron virus strain in March 2022 and BA.5.2 sub-type Omicron virus strain in October 2022 in Fujian Province was collected.The susceptible exposed infectious removed(SEIAR)model of COVID-19 infection with a latent period and asymptomatic infected persons was used to analyze the transmission dynam-ics of two local epidemic situations,and evaluate the preven-tion and control effects.The incubation period of the BA.2 epidemic was 3 days(1～9 days),the intergenerational inter-val was 3 days(1～5 days),and the initial Rt was 3.0(95％CI:2.7～3.3).The incubation period of the BA.5.2 epidemic was 2 days(1～6 days),the intergenerational interval was 1 day(0～2 days),and the initial R,was 1.9(95％CI:1.7～2.1).The fittingresults for the BA.2 and BA.5.2 epidemics were good,and no statistical difference was observed between the predic-ted and actual numbers of cases(x2BA.2=31.53,x2BA.5.2=27.88,P＞0.05).If an emergency response had not been initiated,the BA.2 epidemic would have continued to spread andpeak on April 7th,with an estimated 638 035 cases.The BA.5.2 epidemic would have rapidly spread,reaching a peak on November 14th,with an estimated 685 940 cases.If one incubation period were detected early,the scale of the BA.2 epidemic would have decreased by 25.73％;if two incubation periods were detected early,the scale would have decreased by 79.56％,and if one incubation period had been delayed,the scale would have expanded by 13.72％.If one incubation period had been detected early in the BA.5.2 epidemic,the scale would have decreased by 35.04％;if two incubation periods had been detected early,the scale would have decreased by 92.47％;and if one incubation period had been delayed,the scale would have increased by 19.75％.The guiding ideology,and the prevention and control measures for handling two local epidemics were optimized and iterated.Our study indicated that implementing the"four early"measures ef-fectively decreased the scale of the epidemic,and earlier detection was associated with more significant control effects.This study provides valuable information for the prevention and control of new or recurrent respiratory infectious diseases.