To explore the relationship between the interaction of health literacy and mobile phone dependence and sub-health status of college students, so as to provide evidence-based evidence for improving sub-health status of college students.

Cluster sampling was used to investigate the social demographic characteristics, health literacy, mobile phone dependence and sub-health of college students in Shandong Second Medical University. logistic regression model was used to analyze the correlation between each factor and sub-health status, and the interaction between health literacy and mobile phone dependence and sub-health status was analyzed.

The total detection rates of mobile phone dependence and sub-health were 83.8% (461/550) and 66.7% (367/550), respectively. After adjusting relevant variables, logistic regression analysis found that college students with low health literacy and dependence on mobile phones had the highest risk of sub-health, which was 31.901 times that of college students with high health literacy and no dependence on mobile phones, and the college students without mobile phone dependence and high health literacy were taken as the reference group, and mobile phone dependence and medium and low health literacy had positive synergistic interactions with sub-health, OR values were 5.030 (95% CI: 3.079 - 8.217) and 8.014 (95% CI: 4.404 - 14.583). The calculated relative values of RERI, AP and SI didn’t meet the conditions and cannot indicate the existence of additive interaction.

The interaction between health literacy and mobile phone dependence is associated with sub-health status of college students, which can be used as an evidence-based basis to improve health.

To explore the potential categories and influencing factors of complication risk perception in inpatient with type 2 diabetes mellitus.

A total of 400 patients with type 2 diabetes mellitus who were hospitalized in three tertiary-level hospitals in Tangshan city from August 2023 to January 2024 were randomly selected and included in the whole group. General information questionnaire, Risk Perception Survey-Diabetes Mellitus, Connor-Davidson Resilience Scale, Brief Illness Perception Questionnaire were used for investigation. Using multi-categorical logistic regression analysis to explore the influencing factors.

Inpatients with type 2 diabetes could be divided into high confidence low disease risk perception group (40.25%), appropriate risk perception group (40%), and high concern high disease risk perception group (19.75%). Multi-categorical logistic regression analysis showed that high disease perception score(OR=0.808, 95% CI:0.762-0.858)was a protective factor for the high confidence low disease risk perception group, high psychological resilience score(OR=1.159, 95% CI:1.087-1.235)was a risk factor for the high confidence low disease risk perception group; educational attainment of college and above (OR=23.567, 95% CI:2.807-198.242),havingdiabetes complications(OR=3.408,95% CI:1.315-8.834), high disease perception score (OR=1.320, 95% CI:1.202-1.451)were risk factors for the high concern high disease risk perception group, the main access to diabetes knowledge was healthcare professionals(OR=0.101, 95% CI:0.029-0.355)and high psychological resilience score (OR=0.817, 95% CI:0.747-0.894)were protective factors for the high concern high disease risk perception group.

Perceived risk of complications in inpatients with type 2 diabetes can be categorized into 3 classes, and there are obvious classification characteristics among groups. Healthcare professionals can implement precise measures for different categories of patients to improve their level of perceived risk of complications.

To explore the effects of tooth loss and denture use on cognitive impairment in the elderly.

Based on the data of China Health and Retirement Longitudinal Study (CHARLS), over 60-year-old elderlies were selected as the research subjects.Logistic regression was conducted to explore the effects of tooth loss, denture use on cognitive impairment in elderly and subgroup analysis, and interaction analysis were performed for gender and social participation.

A total of 4 372 elderly people were enrolled, and the rate of cognitive impairment was 16.20% (709/4 372). Older age, female, rural living, lower education, no spouse, with depressive symptoms, and without social-participation are risk factors for cognitive impairment. Group of non-total tooth loss without dentures (OR=1.382; 95% CI: 1.145-1.669) and group of total tooth loss without dentures (OR=2.074; 95% CI: 1.186-3.627) were associated with an increased risk of cognitive impairment. The results of subgroup analysis showed that the male population with non-total tooth loss and no dentures (OR=1.413; 95% CI: 1.077-1.853), with total tooth loss and no dentures (OR=2.600; 95% CI: 1.263-5.352) was still associated with an increased risk of cognitive impairment, while the female with non-total tooth loss and no dentures (OR=1.363; 95% CI: 1.046-1.776) was significantly associated with an increased risk of cognitive impairment.The non-social-participation-group with non-total tooth loss and no dentures (OR=1.475; 95% CI: 1.123-1.937), with total tooth loss and no dentures (OR=2.720; 95% CI: 1.294-5.715) were associated with an increased risk of cognitive impairment.There was no interaction between tooth loss, denture use, genderand social participation in the incidence of cognitive impairment(P>0.05).

The combination of tooth loss and denture use is an independent influence factor for cognitive impairment. The use of dentures can reduce the adverse effects of tooth loss on cognitive dysfunction, especially for those with partial tooth loss. The elderly should be encouraged to retain natural teeth, restore missing teeth in time. Although there is no interaction between tooth loss, denture use and social participation, older adults are suggested to take part in social activities.

To study the rifampicin resistance, genotypic characteristics and clustering of Mycobacterium tuberculosis in Ningxia from 2020-2023.

98 strains of Mycobacterium tuberculosis were tested for rifampicin resistance using the GeneXpert MTB/RIF method, and the strains were genotyped by the McSpoligotyping method and analyzed by clustering at the MIRU-VNTRplus website.

The risk of developing rifampicin-resistant TB was significantly increased in retreatment patients (OR=33.22, 95% CI: 3.11-355.43, P<0.05), and TB patients from Zhongwei and Wuzhong cities showed a higher risk of rifampicin resistance (OR=19.42, 95% CI: 1.12-336.75, P<0.05; OR=43.25, 95% CI: 1.76-1062.70, P<0.05). 98 strains of Mycobacterium tuberculosis were typed by McSpoligotyping to present three lineages, with the largest lineage being the Beijing-type 80 strains (81.63%); the non-Beijing-type accounted for 18 strains (18.37%), of which 12 strains were of the T-type (12.24%), 1 strain of the U-type (1.02%), and the newly 5 strains (5.10%) were newly discovered or undefined genotypes. The Beijing type was widely distributed in all cities of Ningxia, with only the Beijing type in Guyuan and Shizuishan, and the T-type and newly discovered or undefined genotypes were mostly found in Zhongwei, Wuzhong and Yinchuan. Cluster analysis showed that the 98 strains were divided into two genetic clusters, Beijing-type and non-Beijing-type, with SIT1 accounting for the largest proportion of Beijing-type in the clusters (75.51%), T1-type in the non-Beijing-type, and the remaining 9 strains (9.18%) were independent scattered genotypes, with a cluster rate of 90.82% (89/98).

Health education has been actively carried out for retreatment patients and high-risk areas in the Ningxia region to improve treatment adherence, and TB screening and drug resistance surveillance has been strengthened in Zhongwei and Wuzhong cities. In addition, Mycobacterium tuberculosis is genetically polymorphic in this region, and Beijing SIT 1 is the main prevalent strain. Strengthening the monitoring of this gene and understanding its mode of transmission is important for controlling the spread of tuberculosis, slowing down the development of drug resistance, and ultimately improving the public health situation in the region.

To understand the epidemiological characteristics of student TB patients in the province and analyze their spatial aggregation, 2018-2023, and to further optimize the TB prevention and control measures in schools in the province, as well as to provide scientific reference bases for the relevant departments to formulate practical and effective TB prevention and control policies in schools.

From the “Infectious Disease Reporting Information Management System”, the case data of tuberculosis patients whose current address was within the counties (cities and districts) under the jurisdiction of Guizhou Province and whose occupations were students from January 1, 2018 to December 31, 2023 were derived according to the date of onset, and the epidemiological characteristics and spatial aggregation of tuberculosis among students were analyzed by using Excel 2010, SPSS 26 0 and Arc GIS 10 7 software, SPSS 26.0 and Arc GIS 10.7 software to organize and analyze the epidemiological characteristics and spatial aggregation of students' tuberculosis.

There were 23 699 cases of tuberculosis among students in Guizhou Province from 2018 to 2023, with an average annual registration rate of 40.67/100 000, showing a decreasing trend (trend χ²=1 244, P<0.001). The registration time was mainly concentrated in March-April and August-September each year; the regional distribution was mainly concentrated in Bijie City, Qiandongnan Prefecture, and Zunyi City; the age was mainly 15-19 years old (60.15%); the source of the patients was the largest proportion of referrals (40.08%), and the diagnostic results were mainly pathogenetically negative (65.80%), and the overall delayed rate of consultation for student TB patients during 2018-2023 was 49.01%.The global Moran's I values of student TB registration rates in Guizhou Province during 2018-2023 were all >0, ranging from 0.135 to 0.221, and all were statistical significance (P<0.05). The results of local autocorrelation analysis showed that there were different types of aggregation in the province's aggregation zones in each year, and the number of “high-high” aggregation zones in 2018-2023 were: 3, 2, 5, 4, 3, 4, and the number of “low-low” aggregation zones were: 3, 2, 5, 4, 3, and 4, respectively. The number of “high-low” agglomerations in 2018-2023 are: 3, 2, 5, 4, 3, 4, the number of “low-low” agglomerations in 2018-2023 are: 18, 15, 11, 9, 4, 5, the number of “high-low” agglomerations in 2018-2023 are: 0, 0, 1, 1, 1, 2, 4, the number of “low-high” agglomerations in 2018-2023 are: 1, 1, 2, 1, 1, 1, 1.

Guizhou Province, the student tuberculosis patient registration rate is a year-on-year decline in the trend of three inter-distribution is obvious, and the student tuberculosis patient registration non-uniform distribution between areas, and there is obvious spatial aggregation. It is recommended to strengthen active detection in schools, to strengthen health education, and to increase the prevention and control of tuberculosis in schools in areas of aggregation.

To analyze the genotypes and characteristics of HIV-1 transmission network of newly reported HIV/AIDS cases aged 50 and above in Yubei District of Chongqing and provide evidence for effective HIV-1 transmission prevention in Yubei District.

Blood sample of newly reported cases aged 50 and above in 2020-2023 were collected for genetic analysis, partial Pol gene sequences were obtained to construct molecular transmission network. The factors associated with the subjects entering network and characteristics of cluster were further analyzed.

A total of 351 Pol gene sequences were obtained and 9 HIV-1 genotypes were detected. CRF07_BC (57.0%, 200/351) was the major subtypes, followed by CRF08_BC(19.4%, 68/351), the rate of network entry was 57.3%, and 44 clusters were formed. The number of nodes in clusters was between 2-25. People aged 60 and above (60-69years old: aOR=2.25, 95% CI: 1.34-3.80; 70-79years old: aOR=2.93,95% CI: 1.52-5.65), with local household registration in Yubei (aOR=3.10, 95% CI: 1.74-5.52) and genotype CRF07_BC (aOR=2.57, 95% CI: 1.47-4.50) were more likely to have internet access. The proportion of high-risk spreaders was higher among males than among females.

CRF07_BC and CRF08_BC are the major genotypes of HIV/AIDS in people aged 50 years and abovein Yubei District, and CRF07_BC is the genotype of key transmission cluster with high transmission risk.We should strengthen the intervention for the high-risk elderly, and monitor the molecular network dynamically to guide the precise intervention.

To explore the characteristics of HIV molecular transmission network of men who have sex with men (MSM) among newly reported HIV cases in Jinan, China.

The plasma samples of newly reported HIV-1 MSM in Jinan from 2022 to 2023 were collected. The pol region gene was amplified using nested PCR followed by sequencing. The obtained sequences were used to construct phylogenetic tree and molecular transmission network. The related factors for participants entering a cluster were analyzed. Drug resistance mutations were identified and analyzed using the online software of HIV drug resistance database of Stanford University.

This study obtained 207 sequences and identified 15 HIV-1 subtypes. The dominant subtypes were CRF07_BC (76/207, 36.7%) and CRF01_AE (74/207, 35.7%), followed by B subtypes (21/207, 10.1%), CRF114_0155 (9/207, 4.3%), and CRF55_01B (8/207, 3.9%). Setting 1.5% as the gene distance threshold, a total of 15 molecular clusters were formed by 42 sequences, with a transmission network entry rate of 20.3%. Multivariate Logistic Analysis results showed that MSM with college or above education level and CD4 count>500 cells/μl were more likely to enter the molecular transmission network. Among the 207 participants, 11(5.3%) were detected with drug resistance mutations, including 2 with PI resistance mutations, 6 with NRTI resistance mutations, 2 with NNRTI resistance mutations, and 2 with INSTI resistance mutations. One participant was detected with both NRTI and NNRTI resistance mutations.

The gene subtypes of newly reported HIV cases are diverse, mainly were CRF07_BC and CRF01_AE. MSM with younger age and higher education level are active populations in the HIV transmission network. HIV transmission network monitoring is a long-term and continuous work, and it is necessary to strengthen the traceability of key populations in the network and provide more effective intervention strategies to reduce the HIV transmission.

To analyze the reasons of late HIV diagnosis in Chengdu, and to provide scientific basis for promoting early detection.

A cross-sectional survey was used, and the questionnaires were conducted among HIV/AIDS cases in 9 districts in Chengdu. The socio-demographic data, AIDS knowledge awareness, health seeking habits, testing behavior and other information were collected. The chi-square test and binary Logistic regression model were used to analyze the influencing factors. In-depth interviews were conducted, and the sample size was determined according to the principle of "information saturation".

A total of 757 HIV/AIDS cases were investigated, of which 258 (34.1%) were found late diagnosis. Multivariate Logistic regression analysis showed that the risk of late diagnosis was higher in age group 30-49 years old (aOR=3.350, 95% CI: 1.725-6.506) and ≥50 years old (aOR=3.913, 95% CI: 1.876-8.161) than 18-29 years old. Passive detection (aOR=2.002, 95% CI: 1.098-3.649) had a higher risk of late diagnosis than active detection. High school education or higher (aOR=0.472, 95% CI: 0.289-0.770) had a lower risk of late diagnosis than middle school education or lower. Among the 258 late diagnosis cases, 218 (84.5%) never had the idea of HIV testing in the past, mainly because they had not heard of AIDS (106 cases/48.6%) and felt that AIDS was far away from them (82 cases/37.6%). Among the 40 cases who had ever considering taking an HIV test, 17 (42.5%) did not take, mainly because they were worried about their privacy being exposed (12 cases/70.6%), worried about what others think during the test process (7 cases/41.2%), and worried about being discriminated against if they tested positive (7 cases/41.2%). In-depth interviews were conducted on 16 patients with late diagnosis. The reasons for late diagnosis mainly included: never heard of AIDS, serious misunderstanding of AIDS cognition, lack of risk perception awareness, and fluke mentality.

In order to effectively reduce the level of late HIV diagnosis, it is necessary to promote high-quality AIDS health education, improve the awareness of AIDS knowledge and risk perception after high risk behaviors, and encourage people with high risk behaviors to take the initiative to receive HIV testing as soon as possible. Building a supportive social environment to avoid giving up active testing for fear of discrimination is also essential.

To explore the association between disulfidptosis related genes (DRGs) and the prognosis of breast cancer patients and establish a risk prognosis model and verify it, and provide new biomarkers for the prognosis of breast cancer patients.

CNV landscape was drawnin R language. DRGs of co-correlations and differences were identified.The risk score prognostic model was constructed by using univariate Cox regression analysis and Lasso-Cox regression analysis. Kaplan-Meier survival curve,ROC curve and calibration curve for the model was drawn.A nomogram prognostic prediction model was constructed by combining the clinical features.

A risk prognostic model of breast cancer patients composed of 8 DRGs was constructed, and AUC of the ROC curve at 1,3, and 5 years was 0.809,0.848,0.883. DCA showed that the model could better predict breast cancer prognosis.

This research department has constructed a risk score model with 8 DRGs, which has a good prognostic value and can provide a new direction for the study of breast cancer prognosis.

To explore the association between Triglyceride Glucose-Body Mass Index (TyG-BMI) and the risk of developing type 2 diabetes mellitus (T2DM).

The data were obtained from the natural population cohort of Shanghai suburbs established from April 2016 to September 2017 (Songjiang subcohort). 29,351 nondiabetic subjects with normal blood glucose levels aged 20-74 years at baseline were included in the analysis. The association and dose-response relationship between baseline TyG-BMI level and the risk of developing T2DM were assessed by Cox proportional risk regression model and restricted cubic spline model. Covariates such as gender and age were stratified according to their covariates and their interaction with TyG-BMI was analyzed.

A total of 584 men and 777 women were initially diagnosed with T2DM after a median follow-up time of 6.98 years. After correcting for confounders, the Cox regression model showed a 58% increase in the risk of T2DM incidence for every 1 SD increase in TyG-BMI (HR=1.58, 95% CI: 1.50-1.66). After grouping TyG-BMI by quartiles and then including it as a categorical variable in the Cox regression model analysis, the risk of T2DM incidence increased progressively in the Q2, Q3, and Q4 groups with HR (95% CI) of 1.42 (1.15-1.75), 2.02(1.66-2.46), and 3.47(2.88-4.19), respectively (P_trend<0.001), using the Q1 group as the control. Restricted cubic spline plots showed a nonlinear association between TyG-BMI and the risk of T2DM incidence (P_nonlinear =0.048). In addition, subgroup analyses showed that the association between TyG-BMI and the risk of developing T2DM was significantly higher in young and middle-aged (less than 60 years old) residents than in older residents (P_interaction < 0.05).

Under normal blood glucose levels, baseline TyG-BMI was positively associated with the risk of developing T2DM, and this association was more significant in the young and middle-aged groups.