To explore the mediating role of activities of daily living (ADL) and depression between chronic disease comorbidity and self-rated health in empty-nest elderly, and to provide a reference for improving the self-rated health and quality of life of empty-nest elderly.

A total of 3 542 empty-nest elderly aged 60 years and older from the 2020 China Health and Retirement Longitudinal Study were selected as study subjects. Spearman’s correlation analysis was employed to explore the associations between chronic disease comorbidity, ADL, depression, and self-rated health among empty-nest elderly. The Process 4.1 plugin model 6 in SPSS was used to analyse the mediating effects of ADL and depression on the relationship between chronic disease comorbidity and self-rated health among empty-nest elderly.

The direct effect of chronic disease comorbidity on self-rated health among empty-nest elderly individuals was statistically significant (β=-1.2397, 95% CI: -1.4139~-1.0655), the separate mediating effect of ADL was statistically significant (β=-0.159, 95% CI: -0.278~-0.079), the separate mediating effect of depression was statistically significant (β=-0.160, 95% CI: -0.214~-0.115), and the chain mediating effect of ADL and depression was statistically significant (β=-0.073, 95% CI:-0.094~-0.056).

Chronic disease comorbidity can directly negatively impact the self-rated health status of empty-nest elderly individuals. It may also influence their self-rated health through the independent or chain mediating effects of activities of ADL and depression. Consequently, it is recommended that policy measures prioritise empty-nest elderly individuals within health interventions to reduce their risk of chronic disease comorbidity. This should involve establishing a comprehensive support system centred on functional assessment and psychological intervention, thereby improving the self-rated health status of this demographic.

To explore the relationship between smartphone addiction and resilience of college students, and the chain mediating effect of sleep quality and perceived social support.

A total of 843 college students from a university in Shandong Province were selected as the research objects. The general information questionnaire, smartphone addiction scale,resilience scale, Pittsburgh Sleep Quality Index Scale and Perceived Social Support Scale were used to investigate. AMOS 26.0 software was used to establish structural equation model and bootstrap method was used to verify the mediators.

Among the college students, 37.25% had smartphone addiction, and smartphone addiction had a significant direct negative effect on college students’ resilience. The effect value was -0.51 (95% CI: -0.59~-0.43), accounting for 60.71% of the total effect. In addition, the mediating effect of sleep quality was -0.12 (95% CI: -0.17~-0.07), accounting for 14.29% of the total effect. The mediating effect of perceived social support was -0.14 (95% CI: -0.20~-0.10), accounting for 16.67% of the total effect. At the same time, the chain mediating effect of sleep quality and perceived social support between smartphone addiction and resilience was -0.06 (95% CI: -0.10~-0.03), accounting for 7.14% of the total effect.

There is a significant negative correlation between smartphone addiction and college students' psychological resilience. By improving their sleep quality and the ability to understand social support, they can reduce negative emotions such as anxiety and depression, and improve their ability to maintain physical and mental health in the digital age.

To establish a QuEChERS-gas chromatography-mass spectrometry method for the simultaneous determination of seven parabens in beef tallow hotpot seasoning.

To an accurately weighed quantity of the homogenized sample, water, the internal standard and acetronitrile were added, and the analytes were extracted and purified by QuEChERS, analyzed by gas chromatography-mass spectrometry and quantified by internal standard method.

Good linearity was observed for all seven analytes over the range of 0.05 to 5.00 μg/mL, with r≥0.999. The limits of detection (LODs) were between 0.05 and 0.06 mg/kg, and the limits of quantitation (LOQs) were between 0.15 and 0.20 mg/kg.The average recoveries of the method were between 91.4% and 108%, with the relative standard deviations (RSDs) between 0.6% and 7.2%.

The method is simple, accurate and sensitive, and is suitable for the simultaneous determination of seven parabens in beef tallow hotpot seasoning.

To develop and validate a nomogram prediction model for assessing drug resistance risk in patients with pulmonary tuberculosis and diabetes mellitus comorbidity (PTB-DM), identify associated risk factors, and provide a scientific basis for preventing and controlling drug resistance in this population.

A retrospective study was conducted on 546 PTB-DM patients hospitalized in the Department of Pulmonary Medicine at Shenzhen Third People’s Hospital between January 1, 2019, and December 31, 2024. Data collected included sex, age, marital status, smoking, alcohol use, hypertension, hepatitis B, admission type,pulmonary cavity formation, sputum smear results, drug resistance status, diabetes duration, glycated hemoglobin (HbA1c),hemoglobin (Hb), and albumin (ALB).

The indicators filtered by the lasso regression model were included in the multivariate logistic regression analysis, identifying age, admission type, diabetes duration, HbA1c, Hb, and ALB as six predictive factors. A predictive risk nomogram model was developed based on these risk factors. Internal validation using the bootstrap method demonstrated that the model exhibited good discrimination and calibration, with a corrected AUC of 0.781 (95% CI: 0.768-0.789). The calibration slope and intercept were 1.020 and -0.003, respectively, and the Hosmer-Lemeshow test indicated good model fit (χ²=4.06,P=0.852). The Brier score was 0.113 (95% CI: 0.111-0.116). This model may serve as a reference for clinical assessment of drug resistance risk in patients with PTB-DM.

The nomogram model, developed based on LASSO and Logistic regression analyses, demonstrated satisfactory performance in internal validation. It provides an initial predictive tool for assessing the risk of drug resistance in PTB-DM patients. However, its clinical applicability requires further validation with external data.

To analyze the reported incidence of pulmonary tuberculosis (TB) in Qinghai Province from 2005 to 2024, and to provide a scientific basis for developing adaptive TB prevention and control strategies.

Data on reported TB cases in Qinghai, categorized by year, sex, occupation, age group, and region, were extracted from the infectious disease surveillance module of the China Information System for Disease Control and Prevention. The joinpoint regression model was used to analyze the temporal trends in the reported incidence under different categories.

From 2005 to 2024, a total of 119 984 TB cases were reported in Qinghai Province, with an average of approximately 5 999 cases annually. The average annual reported incidence rate was 104.12 per 100 000 population. Joinpoint regression analysis indicated no significant overall trend for the entire period. However, the reported incidence showed a slow upward trend from 2005 to 2018 [Annual Percent Change (APC)=4.24%, P<0.001], followed by a significant downward trend from 2018 to 2024 (APC=-10.89%, P=0.001). A turning point occurred in 2018 for both males and females: incidence increased during 2005—2018(male: APC=2.91%, P=0.005; female: APC=6.17%, P<0.001) and decreased markedly during 2018—2024 (male: APC=-11.85%, P<0.001; female: APC=-10.00%, P=0.003). By age group, the 0-14 years group showed a significant increasing trend [Average Annual Percent Change (AAPC)=5.05%, P<0.001], while the ≥65 years group showed a significant decreasing trend (AAPC=-2.47%, P=0.042). Regarding occupational distribution, farmers constituted the highest proportion at 42.16%,followed by herdsmen (24.08%), and students (11.93%). The reported incidence among herdsmen and students showed increasing trends from 2005 to 2024. Among the prefectures, Xining City and Haixi Prefecture showed decreasing trends(Xining: AAPC=-4.84%, P<0.001; Haixi: AAPC=-5.23%, P<0.001), while Huangnan Prefecture showed an increasing trend(AAPC=3.87%, P=0.003).

The reported incidence of pulmonary tuberculosis in Qinghai Province showed an initial increase followed by a decrease between 2005 and 2024. Sustained efforts are needed to enhance etiological detection capacity,strengthen active screening in key regions and high-risk populations, and improve TB surveillance and early warning capabilities among students/children to further reduce the disease burden.

To investigate the distribution and pathogenic characteristics of Vibrio cholerae in aquatic products (such as soft-shelled turtles), aquatic environments and humans in Shaanxi Province.

Vibrio cholerae strains reported through the National Pathogen Identification Network from 2021 to 2024 were collected. The distribution of strains from humans and environmental sources was described and analyzed. Serogroup identification and virulence gene detection were performed.Core-genome multilocus sequence typing(cgMLST) and core-genome single nucleotide polymorphism (cgSNP) analyses were performed.

A total of 198 Vibrio cholerae strains were collected from 2021 to 2024, including 14 clinical isolates (9 cases of diarrhea and 5 blood samples) and 184 environmental isolates. The overall environmental positivity rate was 34.65% (184/531), with the highest rate in Xi’an City (66.35%), followed by Ankang City (32.66%) and Hanzhong City (21.93%). The positivity rate in sales part was 42.07%, higher than that in farming part (26.92%). The positivity rate in soft-shelled turtle samples was 46.56%, significantly higher than that in other aquatic products (23.77%). Serotyping revealed 3 O1 strains, 13 O139 strains, and the remainder as non-O1/non-O139. Nine strains were positive for the ctxA gene. cgMLST analysis identified 26 MST Clusters, with all ctxA-positive strains clustering in a single lineage: three ST69 strains formed one cluster and five ST168 strains formed another, while the remaining strains were genetically distant. cgSNP analysis of the 9 ctxA-positive strains showed that ST69 and ST168 strains belonged to distinct lineages, differing by 8 100 SNPs, whereas strains of the same ST type exhibited minimal SNP differences, indicating high genetic stability. The patient isolate from Hanzhong City and the soft-shelled turtle isolate from Ankang City differed by only 2 SNPs.

In Shaanxi Province, Vibrio cholerae in the environment poses a relatively high risk at the farming and sales stages of soft-shelled turtles and other aquatic products, and a small proportion of isolates carry the ctxA virulence gene. Core-genome analysis indicates that toxigenic strains are genetically stable and may be indirectly linked to clinical cases. Surveillance and early warning for diarrheal cases and along the soft-shelled turtle-related production and supply chain should be strengthened to ensure the timely prevention and control of outbreaks.

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterized by its propensity for metastasis and poor prognosis, with pathogenesis closely linked to oxidative stress, metabolic reprogramming, and tumor microenvironment. As a key regulator of antioxidant responses, nuclear factor erythroid 2-related factor 2 (Nrf2) promotes TNBC progression by orchestrating antioxidant defense mechanisms, ferroptosis-protective systems, metabolic reprogramming, and remodeling of the tumor microenvironment. This review summarizes current advances in the mechanisms by which Nrf2 drives TNBC progression, with a particular focus on the molecular pathways through which it regulates oxidative stress,metabolic reprogramming, and the tumor microenvironment to promote tumor progression. Additionally, it evaluates the potential applications of Nrf2 in preventive medicine and public health, providing a theoretical foundation for early intervention and targeted therapy in TNBC.

To establish the epidemic thresholds and intensity classification criteria for varicella in Sichuan Province by applying the Moving Epidemic Method (MEM), so as to provide a scientific basis for precision prevention and control.

Based on the weekly incidence data of varicella in Sichuan Province from 2014 to 2024, obtained from the China Information System for Disease Control and Prevention, the MEM model was constructed separately for each epidemic season, accounting for its characteristic bimodal peaks (the spring-summer peak from week 8 to week 34 and the autumn-winter peak from week 35 to week 7 of the following year). The optimal parameter (δ) was determined through cross-validation. Model performance was evaluated using sensitivity, specificity, and the Youden index.

In the autumn-winter model, after excluding data from weeks 35 to 7 of the 2014-2015 season, the model was built based on nine years of historical data (δ=2.9), yielding a sensitivity of 0.837, a specificity of 0.933, and a Youden index of 0.770. In the spring-summer model, after excluding data from weeks 8 to 34 of 2020, the model was constructed using nine years of historical data (δ=2.6), which resulted in a sensitivity of 0.902, a specificity of 0.943, and a Youden index of 0.845.

The seasonal stratification approach combined with the MEM epidemic intensity assessment model enables accurate identification of varicella epidemic periods in Sichuan Province, thereby providing a scientific basis for implementing differentiated prevention and control measures based on epidemic intensity levels.

To analyze the prevalence and influencing factors of physical pain among Chinese elderly, providing evidence for pain identification and intervention.

Data from 6 191 elderly participants in the China Health and Retirement Longitudinal Study (CHARLS) were analyzed using ordinal logistic regression and random forest algorithms to assess the impact and importance of various factors on pain severity.

59.13% of elderly individuals reported pain, with over 30% experiencing moderate or severe pain. The most common pain sites were the lower back, knees, and legs. Male gender (OR=0.695, 95% CI=0.614-0.787), higher education (OR=0.870, 95% CI=0.766-0.988), and retirement (OR=0.802, 95% CI=0.699-0.921) are protective factors. BADL disability (OR=2.071, 95% CI=1.832-2.340), IADL disability (OR=1.990, 95% CI=1.756-2.235), depressive symptoms (OR=1.548, 95% CI=1.378-1.739), poor sleep quality (OR=1.530, 95% CI=1.334-1.756), arthritis or rheumatism (OR=2.486, 95% CI=2.244-2.753), Parkinson’s disease (OR=1.679, 95% CI=1.160-2.428), digestive diseases (OR=1.642, 95% CI=1.478-1.824), cancer (OR=1.554, 95% CI=1.143-2.112), kidney disease (OR=1.543, 95% CI=1.331-1.788), heart disease (OR=1.457, 95% CI=1.299-1.636), and chronic lung diseases (OR=1.190, 95% CI=1.034-1.371) are risk factors. Random forest analysis showed that arthritis, BADL, IADL, depression, and sleep quality were key factors influencing pain severity.

The physical pain burden among elderly Chinese is significant and influenced by multiple factors. Pain management should focus on early identification and individualized interventions for high-risk groups to improve quality of life.