As one of the major public health challenges globally, tuberculosis requires epidemiological research for its control and prevention. With the advent of the big data era, machine learning has advantages over traditional methods in handling complex, high-dimensional datasets and providing accurate predictive results. This paper introduces the application of machine learning in the discovery and diagnosis of tuberculosis cases, risk factor analysis, predictive modeling, and evaluation of intervention strategies, providing new means for more in-depth exploration of the value in tuberculosis epidemiological research.

Objective:To evaluate the association between triglyceride-glucose(TyG) index level, their variability, and the risk of incident hyperuricemia(HUA).Methods:A total of 1 583 cases with good compliance who underwent follow-up at the health examination center of a tertiary hospital physical in Zhengzhou were enrolled. The TyG index mean(TyG-mean) and variability indexes, including standard deviation(TyG-SD), coefficient of variation(TyG-CV), and adjusted standard deviation(adj-TyG-SD), were calculated based on TyG index values from three consecutive annual health check-ups. Cox proportional risk regression model was used to assess the relationship between the variability of TyG index and the risk of new-onset HUA; the dose-response relationship between different TyG indexes and HUA was examined using restricted cubic spline(RCS). Results:After a 3-year follow-up, 146 participants developed incident HUA. Both TyG-mean and TyG index variability indicators were significantly higher in the HUA group compared to the non-HUA group( P<0.05). After adjusting for multiple confounders, each standard deviation σincrease in TyG-SD, TyG-CV, and adj-TyG-SD was associated with a 1.23-fold(95% CI 1.06-1.43), 1.22-fold(95% CI 1.05-1.42), and 1.26-fold(95% CI 1.08-1.45) higher risk of incident HUA, respectively. RCS analysis revealed a nonlinear association between adj-TyG-SD and HUA risk( P<0.05), with a critical threshold of 0.55 at a hazard ratio( HR) of 1. Conclusions:Increased TyG index variability is associated with a higher risk of incident HUA, with adj-TyG-SD showing the strongest correlation with HUA risk.

Objective To construct an evaluation index system for the technical labor value of operators of large-scale medical equipment and conduct a practical measurement of it.Methods The literature survey method and semi-structured interview were used to preliminarily construct the evaluation index framework.The questionnaire survey method and expert consultation method were employed to screen and determine the final evaluation index system,and the entropy method was used to calculate the weight of each evaluation index.Based on the KANO model,the evaluation requirements of the technical labor value of MRI operators were investigated.Results The final expert authority coefficient of the consultation questionnaire was 0.80;the chi-square test results of Kendall's W coefficient were all statistically significant differences(P＜0.05);finally,5 first-level indicators,13 second-level indicators,and 22 third-level indicators were screened out,jointly forming the evaluation index system.The Cronbach's coefficients of the positive and negative questionnaires in the reliability analysis of the KANO model were 0.953 and 0.983 respectively;MRI operators perceived that the cerebral thinking load,the steps taken to operate the imaging equipment,and the difficulty in interpreting imaging results were more reflective of the value of their technical labor.Conclusion The evaluation index system of technical labor value of large medical equipment operators has been scientifically constructed to provide theoretical support for improving the performance evaluation system of large medical equipment operators.

Objective:To explore the impact of air pollution on hospital visits for mental and behavioral disorders among residents in an industrial area in Henan Province from 2016 to 2021.Methods:Daily outpatient visits data for mental and behavioral disorders were collected from Angang General Hospital in Angang Industrial Area at Anyang City between January 2016 and December 2021. And air pollutants and meteorological data during the same period were also collected. A generalized additive model was used for time-series analysis to examine the relationship between daily average concentrations of nitrogen dioxide (NO 2), sulfur dioxide (SO 2), fine particulate matter (PM 2.5), inhalable particulate matter (PM 10), carbon monoxide (CO), and ozone (O 3) with a lag of 0 to 7 days on the number of visits for mental and behavioral disorders among residents. The single-day lag effect (lag0-lag7 d) and cumulative lag effect (lag01-lag07 d) were analyzed. The smooth cubic spline function was used to fit the exposure-response relationship, and subgroup analysis was performed according to different genders, seasons and ages. Results:A total of 26 268 hospital visits for mental and behavioral disorders were collected from the industrial area between 2016 and 2021. The daily average concentrations of SO 2, NO 2, PM 2.5, PM 10, and CO were (27.50±27.33), (43.11±18.33), (73.87±60.30), (134.01±83.81) μg/m 3, and (1.72±1.03) mg/m 3, respectively. The daily maximum 8-hour average concentration of O 3 was (82.18±53.70) μg/m 3. After controlling for long-term trends, temperature, relative humidity, day of the week effects, and holiday effects, the generalized additive model analysis showed that NO 2 had a statistically significant impact on the hospital visits for mental and behavioral disorders at lag0 d, lag2 d and lag01-lag05 d and CO had a statistically significant impact at lag0-lag3 d and lag01-lag06 d (all P<0.05). NO 2 at lag02-lag04 d and CO at lag0-lag2 d and lag01-lag04 d had statistically significant effects on the visits for neurasthenia (both P<0.05). The impacts of NO 2 at lag03-lag04 d, PM 2.5 at lag3 d and lag03-lag04 d, PM 10 at lag3 d and lag03 d, and CO at lag3 d and lag01-lag05 d on visits for generalized anxiety disorder were also statistically significant (all P<0.05). After false discovery rate (FDR) correction, it was shown that for every 10 μg/m 3 increase in NO 2 and every 0.1 mg/m 3 increase in CO, the percentage increase in visits for mental and behavioral disorders and its 95% confidence interval (95% CI) were 3.38% (0.95%-5.87%) and 0.78% (0.38%-1.17%), respectively. For every 0.1 mg/m 3 increase in CO, the visits for neurasthenia increased by 0.78% (0.27%-1.29%). For every 10 μg/m 3 increase in PM 2.5 and every 0.1 mg/m 3 increase in CO, the visits for generalized anxiety disorder increased by 1.07% (0.46%-1.68%) and 1.17% (0.37%-1.97%), respectively (adjusted P<0.05). There was a linear exposure-response relationship between NO 2 and CO and the hospital visits for mental and behavioral disorders, CO and the hospital visits for neurasthenia, and CO and PM 2.5 and the hospital visits for generalized anxiety disorder ( P<0.05 for the overall association test and P>0.05 for the non-linearity test). Stratified analysis showed that air pollutants had an impact on male patients with neurasthenia, female patients with generalized anxiety disorder, individuals aged <45 years with mental and behavioral disorders, and individuals aged ≥65 years with generalized anxiety disorder. The impact of air pollutants was greater during the cold season or winter. Conclusion:Exposure to air pollution can increase hospital visits for mental and behavioral disorders among residents in industrial areas, with a higher risk among those aged<45 years old and during the cold season.

MicroRNA(miRNA)serves as a novel regulatory factor in viral and bacterial co-infections,exhibiting dual regulatory roles during pathogen infections.On the one hand,it exerts protective effects by modulating viral replication cycles and host anti-infection immune responses.On the other hand,it can be exploited by pathogens to promote infection progression,including influencing viral replication,antiviral immune responses,and regulating bacterial adhesion and proliferation.Mixed viral and bacterial infections lead to high mortality rates.By binding to specific target gene mRNA,miRNA degrades or inhibits its translation,thereby regulating target gene expres-sion,which may ultimately serve as potential diagnostic and therapeutic targets.This paper reviews recent ad-vances in research on the role of miRNA in viral and bacterial infections,particularly its mechanisms in co-infec-tions,aiming to provide theoretical reference for further research on the infection mechanisms.

Objective To assess the global and Chinese disease burden of early-onset lung cancer(di-agnosed in patients aged 15-49 years)and its major risk factors.Methods Based on the GLOBOCAN 2022 and Global Burden of Disease(GBD)2021 datasets,we evaluated the disease burden and associated risk fac-tors of early-onset lung cancer globally and in China,stratified by age,sex,geographic location,and human development index(HDI).Key indicators included age-standardized incidence rate(ASIR),age-standardized mortality rate(ASMR),and disability adjusted life years(DALYs)attributable to risk factors.Results In 2022,there were 137 705 new cases and 72 646 deaths from early-onset lung cancer globally,with ASIR and ASMR of 3.43 per 100 000 and 1.82 per 100 000 population,respectively.The disease burden was higher in males than in females(ASIR:3.72 per 100 000 vs.3.14 per 100 000;ASMR:2.31 per 100 000 vs.1.33 per 100 000).High-HDI regions exhibited the highest ASIR(5.51 per 100 000)and ASMR(2.57 per 100 000),with health inequality analysis revealing a concentration of disease burden in higher-HDI areas.China bore the heaviest burden,accounting for 48.69%of global new cases and 35.77%of deaths.China's ASIR(8.21 per 100 000)and ASMR(3.17 per 100 000)exceeded global averages,with incidence higher in fe-males(8.78 per 100 000 vs.7.67 per 100 000)but mortality higher in males(4.01 per 100 000 vs.2.29 per 100 000).Smoking and ambient particulate matter pollution were the leading risk factors globally(DALYs contribution:42.01%and15.62%)and in China(DALYs contribution:46.78%and 20.84%).Globally,household air pollution ranked third,whereas in China,secondhand smoke replaced it as the third leading risk factor,with household air pollution dropping to fifth.Risk factor profiles varied significantly across age groups,with modifiable risks contributing less to disease burden in the 15-24 age group.Conclusions The burden of early-onset lung cancer varies markedly by sex,region,and HDI,with China facing a disproportionately high burden.Policymakers should prioritize equitable resource allocation and targeted interventions,particularly in tobacco control and air pollution mitigation,to enhance cancer prevention and control efforts.

Nanopore sequencing,as a representative of third-generation sequencing technology,is widely used in molecular biology research.It offers several advantages,including high throughput,ultra-long read lengths,real-time sequencing,and the absence of amplification and labeling requirements.This technology has been applied for the detection of various pathogens,genomic typing,structural variation analysis,and personalized treatment guidance,making it valuable for pathogen monitoring and medical research.This article focuses on the principles of nanopore sequencing technology,its advantages,and its applications in molecular biology and molecular medicine.The limitations of nanopore sequencing and its future development directions are also summarized,providing new perspectives for further research in this field.

Objective:To investigate the survival outcomes and prognostic factors of patients with double primary breast cancer (BC) and endometrial cancer (EC).Methods:A retrospective cohort study was conducted using data for the period 1992-2018 from the Surveillance, Epidemiology, and End Results (SEER) database. There were 3 465 patients with BC as the first primary cancer (BC-EC group) and 2 804 patients with EC as the first primary cancer (EC-BC group). Kaplan-Meier analysis and cumulative incidence function were used to estimate overall mortality, breast cancer-specific mortality, and endometrial cancer-specific mortality, respectively. Cox regression and Fine-Gray regression were used to analyze the prognostic factors of overall mortality, breast cancer-specific mortality, and endometrial cancer-specific mortality, respectively.Results:During a median follow-up of 160 months, 1 616 deaths occurred in the BC-EC group, with EC being the leading cause of death (37.69%); 994 deaths occurred in the EC-BC group, with BC being the leading cause of death (28.77%). Cox regression identified patients with older ages at first primary cancer diagnosis (54-61 years: HR=1.46, 95% CI: 1.26-1.69; 62-68 years: HR=2.64, 95% CI: 2.29-3.03; ≥69 years: HR=4.89, 95% CI: 4.27-5.60), shorter time interval between the diagnoses (0-5 months: HR=6.13, 95% CI: 5.21-7.21; 6-23 months: HR=5.69, 95% CI: 4.95-6.55; 24-59 months: HR=3.44, 95% CI: 3.04-3.89; 60-119 months: HR=2.32, 95% CI: 2.07-2.59), mixed ductal-lobular BC ( HR=1.29, 95% CI: 1.11-1.48), endometrial mixed cell adenocarcinoma ( HR=1.23, 95% CI: 1.01-1.50), advanced tumor grade (grade Ⅱ BC: HR=1.13, 95% CI: 1.01-1.27; grade Ⅲ BC: HR=1.24, 95% CI: 1.10-1.41; grade Ⅱ EC: HR=1.19, 95% CI: 1.06-1.33; grade Ⅲ EC: HR=1.68, 95% CI: 1.48-1.90), advanced tumor stage of the two cancers (distant BC: HR=3.14, 95% CI: 2.50-3.94; regional EC: HR=1.53, 95% CI: 1.36-1.71; distant EC: HR=3.00, 95% CI: 2.59-3.47) had increased risk of overall mortality. Fine-Gray regression showed that compared with BC-EC patients, EC-BC patients had a higher risk of breast cancer-specific mortality [sub-distribution hazard ratio (s HR=1.24, 95% CI: 1.04-1.47], but a lower risk of endometrial cancer-specific mortality (s HR=0.37, 95% CI: 0.30-0.46). Older ages at first cancer diagnosis, shorter intervals between the diagnoses, negative ER and PR status, and advanced BC grades/stages were associated with increased breast cancer-specific mortality ( P＜0.05). Similarly, older ages, shorter intervals, endometrial serous carcinoma/mixed cell adenocarcinoma, and advanced EC grades/stages correlated with elevated endometrial cancer-specific mortality ( P＜0.05). Conclusion:The management of double primary BC and EC patients requires multidisciplinary strategies, with particular attention to patients presenting older ages at first cancer diagnosis, shorter intervals between the diagnoses, and unfavorable tumor characteristics.

As one of the major public health challenges globally, tuberculosis requires epidemiological research for its control and prevention. With the advent of the big data era, machine learning has advantages over traditional methods in handling complex, high-dimensional datasets and providing accurate predictive results. This paper introduces the application of machine learning in the discovery and diagnosis of tuberculosis cases, risk factor analysis, predictive modeling, and evaluation of intervention strategies, providing new means for more in-depth exploration of the value in tuberculosis epidemiological research.

"Technology-consumption separation"in pricing of medical testing programs,refers to the medical testing programs in the pricing process will be the cost of technology and consumables cost accounting separately,this is the basis for large-scale centralized procurement of test reagents,for the standardization of medical testing programs to carry out,reduce the cost of medical testing programs is critical.The medical testing programs pricing"technology and consumption separation"of the connotation is deeply analyzed.It is considered that the main difficulties in the implementation of the"technology-consumption separation"in the pricing of medical testing programs are the difficulty of costing,the difficulty of calculating the use of special reagents,and the difficulty of policy implementation.The implementation of the"technology-consumption separation"in the pricing of medical testing programs are proposed from"pricing according to the current price minus the cost of specialized reagents","based on big data to measure the loss of specialized reagents"and"appropriate increase in the pricing level".