Background Benign prostatic hyperplasia (BPH) is a common chronic urinary disease in middle-aged and older men, yet the impact of long-term exposure to atmospheric particulate matter (PM) on its pathogenesis remains unclear. Objective To investigate the association between PM exposure and the risk of incident BPH in middle-aged and older men. Methods Based on four waves of follow-up data (2011–2018) from the China Health and Retirement Longitudinal Study (CHARLS), 4766 participants were enrolled. Robust Poisson regression models were employed to assess the association between exposure to PM (PM₁, PM_2.5, and PM₁₀) and the risk of incident BPH. Relative risks (RR) and their corresponding 95% confidence intervals (95%CI) were calculated. Dose-response relationships were fitted using restricted cubic splines (RCS). Subgroup analyses were performed to explore potential effect modifications, and multiple imputation was used to handle missing data. Results Over a mean follow-up of 6 years, 914 incident BPH cases were identified among the4766 participants (cumulative incidence: 19.18%). After adjusting for confounders, each 10 μg·m⁻³ increase in PM₁, PM_2.5, and PM₁₀ concentrations was associated with a 13.1% (RR=1.131, 95%CI: 1.063, 1.203), 8.5% (RR=1.085, 95%CI: 1.050, 1.122), and 5.1% (RR=1.051, 95%CI: 1.034, 1.069) increased risk of BPH, respectively. RCS analysis showed that no nonlinear relationship was found between PM₁ and PM_2.5 and the risk of BPH (P>0.05); however, a nonlinear association was observed for PM₁₀ (P=0.03), with the risk increment slowing beyond 100 μg·m⁻³. Subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion Long-term exposure to ambient particulate matter may be associated with an increased risk of incident BPH in middle-aged and older men.

Background Benign prostatic hyperplasia (BPH) is a common chronic urinary disease in middle-aged and older men, yet the impact of long-term exposure to atmospheric particulate matter (PM) on its pathogenesis remains unclear. Objective To investigate the association between PM exposure and the risk of incident BPH in middle-aged and older men. Methods Based on four waves of follow-up data (2011–2018) from the China Health and Retirement Longitudinal Study (CHARLS), 4766 participants were enrolled. Robust Poisson regression models were employed to assess the association between exposure to PM (PM₁, PM_2.5, and PM₁₀) and the risk of incident BPH. Relative risks (RR) and their corresponding 95% confidence intervals (95%CI) were calculated. Dose-response relationships were fitted using restricted cubic splines (RCS). Subgroup analyses were performed to explore potential effect modifications, and multiple imputation was used to handle missing data. Results Over a mean follow-up of 6 years, 914 incident BPH cases were identified among the4766 participants (cumulative incidence: 19.18%). After adjusting for confounders, each 10 μg·m⁻³ increase in PM₁, PM_2.5, and PM₁₀ concentrations was associated with a 13.1% (RR=1.131, 95%CI: 1.063, 1.203), 8.5% (RR=1.085, 95%CI: 1.050, 1.122), and 5.1% (RR=1.051, 95%CI: 1.034, 1.069) increased risk of BPH, respectively. RCS analysis showed that no nonlinear relationship was found between PM₁ and PM_2.5 and the risk of BPH (P>0.05); however, a nonlinear association was observed for PM₁₀ (P=0.03), with the risk increment slowing beyond 100 μg·m⁻³. Subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion Long-term exposure to ambient particulate matter may be associated with an increased risk of incident BPH in middle-aged and older men.

Objective To analyze the pollution characteristics of PM_2.5-bound polycyclic aromatic hydrocarbons (PAHs) during the non-heating period, heating period, and haze period in Harbin, and infer their possible sources, and to evaluate their impact on population carcinogenesis. Methods From 2020 to 2022, sampling points were set up in different districts of Harbin. PM_2.5 samples were regularly collected every month to analyze the contents of 10 types of PM_2.5-bound 4-6 rings PAHs. The pollution characteristics of PAHs were analyzed during different monitoring periods (non-heating period, heating period, and haze period). The excess carcinogenesis risks of PM_2.5-bound PAHs were assessed according to the Technical Specifications for Health Risk Assessment of Ambient Air Pollution and the U. S. Environmental Protection Agency (US EPA) risk assessment method. The characteristic ratio method and the positive matrix factorization (PMF) model were used to infer the sources of PAHs. Results The median mass concentrations of ambient PM_2.5-bound 4-6 rings PAHs (ΣPAHs) during the non-heating period, heating period, and haze period were 6.44 ng/m³, 37.85 ng/m³, and 106.79 ng/m³, respectively. During the heating season and haze period, the concentrations of benzo[a]anthracene, benzo[k]fluoranthene, pyrene and fluoranthene were relatively high. The excess carcinogenic risks for ASF_>16, ASF_2-16 and ASF_<2 caused by exposure to PM_2.5-bound 4-6rings PAHs during the heating season were 2.34×10^-6, 1.82×10^-6, and 0.88×10^-6, respectively, while the excess carcinogenic risks for the whole population during the heating season and haze period were 5.05×10^-6 and 1.75×10^-6, respectively. The results of the two source methods showed that the main characteristic elements during the heating season were fluoranthene, pyrene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, and benzo[a]pyrene. According to the emission source standards, it was determined that the sources were mainly coal and biomass combustion, accompanied by traffic source emissions. Conclusion In Harbin, the PM_2.5-bound 4-6 rings PAHs during the haze period is significantly higher than that during the heating period. The pollution is mainly from coal combustion emissions, accompanied by continuous traffic source pollution. The exposure to PAHs during the heating period poses a potential carcinogenic risk to the population.

Yi and Gui,its physiological characteristics and pathological manifestations are closely related to the lumbar spine.The intervertebral disc,chamber of arthrosis,requires nourishment from qi and blood circulation,as well as support from liver and kidney functions to maintain its health.Chinese medicine master Shi Qi has based on the pathological manifestations of discogenic low back pain patients at different stages and followed the guidelines of the Visceral manifestation theory.Combining more than 60 years of experience in traditional Chinese medicine diagnosis and treatment,he has used external observations to infer internal conditions and examined causes to find solutions.By entering the body from the outside and focusing on the"Homology of Yi and Gui"as a benchmark,he emphasizes the distinctive characteristic of traditional Chinese medicine in medical treatment.He states that"visceral pattern is fundamental"and"qi-blood is first,"emphasizing the importance of treating liver and kidney together.This article aims to draw on the wisdom of Taishan to provide a bridge for colleagues.

Objective To establish a rat model of venous thrombosis in a plateau hypobaric hypoxic environment and to investigate the effect of this environment on venous thrombosis.Methods A total of 144 healthy male SD rats were assigned randomly to four groups(n=36 rats per group):a plains sham operation(A)group,plains operation(B)group,plateau altitude 6000 m+sham operation(C)group,and plateau altitude 6000 m+surgery(D)group.Rats in A and B groups were maintained in a plains normoxic environment,while rats in C and D groups C and D were subjected to a plateau environment.Rats in the surgical groups underwent quantitative constriction to incompletely obstruct the inferior vena cava blood flow.Each group was further divided into subgroups based on time:1,3,5,7,14,and 21 d(n=6 rats per group).Regular vascular ultrasound monitoring was conducted,and blood samples were taken for whole blood viscosity testing and the assessment of inflammatory indicators,including endothelin-1(ET-1),interleukin-6(IL-6)and tissue factor(TF).Coagulation function was evaluated through the activated partial thromboplastin time(APTT),prothrombin time(PT),thrombin time(TT),fibrinogen(FIB)and D-dimer.After the observation period,the experimental animals were sacrificed and the limbs were removed.Thrombus samples were stained with hematoxylin/eosin(HE),and the thrombus wet mass was measured.Results The thrombosis incidence was significantly higher in the plateau D group than in B group,accompanied by a marked increase in blood viscosity and hematocrit(P＜0.01).Additionally,levels of ET-1,IL-6,and TF were significantly elevated(P＜0.05),indicating a coagulation disorder.Conclusions A plateau hypoxic environment model can be successfully simulated by quantitative coarctation of the inferior vena cava,combined with a specialized environmental chamber.The findings of this study suggest that a plateau hypoxic environment promotes venous thrombosis.

Objective:To develop and validate machine learning-based radiomics models using preoperative CT images for individualized prediction of mitotic index (MI) in patients with gastrointestinal stromal tumors (GIST).Methods:The study was a case-control study. The data of 348 GIST patients confirmed by pathology were retrospectively collected from two independent medical centers: the Affiliated Hospital of Qingdao University (center 1) and Shandong Provincial Hospital Affiliated to Shandong First Medical University (center 2), covering the period from January 2013 to June 2018. Patients from center 1 were divided into a training cohort (176 cases) and an internal validation cohort (75 cases) at a ratio of 7∶3 using random sampling. Patients from center 2 served as an independent external validation cohort (97 cases). The primary endpoint was MI, categorized into high MI (145 cases) and low MI (203 cases) groups. Radiomic features were extracted from the portal venous phase images of preoperative contrast-enhanced CT scans. Five machine learning algorithms, including logistic regression, support vector machine, random forest, decision tree, and extreme gradient boosting (XGBoost),were employed to construct MI prediction models. The optimal model was identified using receiver operating characteristic curves. An individualized prediction model was developed by integrating the the optimal machine learning model combined with selected independent clinical factors, and the importance of features was visualized using Shapley Additive Explanation (SHAP) analysis. Patients were followed up, and Kaplan-Meier curves along with log-rank tests were used to evaluate recurrence-free survival (RFS) differences between the predicted high MI and low MI groups.Results:Among the five constructed machine learning models, the XGBoost model demonstrated the best predictive performance, with area under the curve (AUC) of 0.809 (95% CI 0.738-0.872), 0.693 (95% CI 0.571-0.809), and 0.718 (95% CI 0.605-0.822) in the training cohort, internal validation cohort, and external validation cohort, respectively. An individualized prediction model combining the XGBoost model with independent clinical factors (tumor location and tumor size) was developed. The model achieved AUC of 0.843 (95% CI 0.785-0.899), 0.791 (95% CI 0.680-0.894), and 0.777 (95% CI 0.678-0.861) in the training cohort, internal validation cohort, and external validation cohort, respectively. SHAP analysis indicated that radiomic features had the highest predictive impact. In both the training cohort and internal validation cohort, the RFS of patients predicted to be in the high MI group was lower than that of the low MI group, with statistically significant differences ( χ2=14.58, 9.52, both P<0.001). However, there was no statistically significant difference in RFS in the external validation set ( χ2=6.18, P=0.080). Conclusions:The optimal XGBoost model based on radiomic features extracted from preoperative portal venous phase CT images, when combined with clinical factors, can effectively predict the MI of GIST patients.

Objective:To evaluate cerebrospinal fluid (CSF) flow dynamics and volume changes of pulsatile tinnitus (PT) patients induced by sigmoid sinus wall dehiscence (SSWD) using MRI.Methods:This was a cross-sectional study. Totally 55 SSWD-PT patients, and 35 age- and sex-matched healthy controls were prospectively enrolled at Beijing Tongren Hospital, Capital Medical University from October 2019 to September 2023. The CSF at the midbrain aqueduct level was analyzed based on phase-contrast MRI to obtain the flow dynamics information. Based on T 1-weighted turbo field echo sequence, the CSF was segmented and the volume of CSF was calculated using ITK-SNAP software. The Mann-Whitney U test was used to compare the differences of each parameter between the two groups. Binary logistic regression was used to analyze the parameters with statistically significant differences to obtain the independent influencing factors of SSWD-PT and establish the combined parameters. Receiver operating characteristic curve analysis was used to evaluate the efficacy of diagnosing SSWD-PT. Results:Compared with controls, the SSWD-PT group showed significantly decreased mean flux (MF), mean velocity, peak velocity( P<0.05), and significantly increased regurgitant fraction (RF), CSF volume ( P<0.05). No significant differences were observed in forward flow volume, backward flow volume, and stroke volume ( P>0.05). The logistic regression results showed that MF ( OR=0.497, 95% CI 0.305-0.808, P=0.005) and RF ( OR=1.809, 95% CI 1.040-3.147, P=0.036) were independent influencing factors of SSWD-PT. The area under the curve (AUC) of MF and RF for diagnosing SSWD-PT were 0.641 (95% CI 0.517-0.766) and 0.675 (95% CI 0.564-0.786), respectively. The AUC of the combination of MF and RF was 0.724 (95% CI 0.614-0.833). Conclusions:SSWD-PT patients have abnormal changes in CSF flow dynamics and volume. The MF and RF demonstrate moderate diagnostic value for diagnosing SSWD-PT.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.