Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.

Objective: To investigate the current status and influencing factors of overweight and obesity among adults in Jiaxing City, Zhejiang Province, so as to provide a basis for developing targeted weight management measures. Methods: In 2024, a multistage stratified random cluster sampling method was employed to recruit permanent residents aged ≥18 years from Jiaxing City for questionnaire surveys. Data on basic information, lifestyle behaviors, and history of chronic diseases were collected. Height and body weight were measured, and overweight and obesity were determined based on body mass index (BMI). The influencing factors of overweight and obesity among adults were analyzed by a multivariable logistic regression model. Results: Totally 10 509 questionnaires were allocated, and 9 802 valid questionnaires were recovered, with an effective recovery rate of 93.27%. Among the respondents, 4 808 (49.05%) were males and 4 994 (50.95%) were females, with a mean age of (51.27±17.26) years. A total of 4 884 overweight and obesity individuals were identified, with a detection rate of 49.83%. Multivariable logistic regression analysis showed that gender (male, OR=1.719, 95%CI: 1.578-1.873), age (≥60 years, OR=0.802, 95%CI: 0.652-0.986), educational level (bachelor and above, OR=0.640, 95%CI: 0.518-0.791), marital status (being married/cohabiting, OR=1.224, 95%CI: 1.009-1.486), adequate nut intake (OR=0.910, 95%CI: 0.832-0.995), hypertension (OR=2.462, 95%CI: 2.219-2.732), and dyslipidemia (OR=1.629, 95%CI: 1.444-1.837) were statistically associated with overweight and obesity among adults. Conclusion The detected rate of overweight and obesity among adults in Jiaxing City was relatively high, and was mainly associated with gender, age, education level, marital status, nut intake, hypertension, and dyslipidemia.

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Objective: To investigate the trend in mortality of injury in Jiaxing City, Zhejiang Province, from 2010 to 2022, so as to provide the evidence for developing injury prevention and intervention strategies. Methods: Data on injury mortality in Jiaxing City from 2010 to 2022 were obtained from the Jiaxing Chronic Disease Monitoring Information Management System. Crude mortality was calculated, and standardized mortality was computed using data of the Sixth National Population Census in 2010. Descriptive analysis of injury mortality and cause of injury death was conducted by gender and age. The average annual percent change (AAPC) was used to analyze the trend in mortality of injury from 2010 to 2022. Results: From 2010 to 2022, the crude injury mortality in Jiaxing City was 79.24/100 000, and the standardized mortality was 47.08/105. The crude injury mortality was higher in males than in females (80.51/100 000 vs. 78.01/100 000, P<0.05). The standardized injury mortality for the total population, males, and females showed significant declining trends (AAPC=-2.011%, -2.373% and -1.542%, all P<0.05). The crude injury mortality increased with age (P<0.05), peaking in the age group of ≥85 years (1 806.46/100 000). Decreasing trends were observed in the age groups of 0-<15 years, 15-<45 years, and 45-<65 years (AAPC=-7.794%, -4.698% and -4.521%, all P<0.05), while no significant trend was found in the age group of ≥65 years. The top five causes of injury death were falls (29.96/100 000), motor vehicle traffic accidents (17.81/100 000), drowning (6.50/100 000), suicide (5.40/100 000), and poisoning (0.69/100 000). Drowning was the leading cause of injury death in the age group of 0-<15 years, while falls were the primary cause in the age group of ≥65 years. Motor vehicle traffic accidents were the top cause of injury death in age groups of 15-<45 years and 45-<65 years. From 2010 to 2022, the standardized mortality of falls showed an upward trend (AAPC=1.094%, P<0.05), while the standardized mortality of motor vehicle traffic accidents, drowning, and suicide demonstrated downward trends (AAPC=-7.576%, -2.745% and -2.786%, all P<0.05). Conclusions The standardized injury mortality in Jiaxing City showed an overall downward trend from 2010 to 2022. Falls were the leading cause of injury death, and particular attention should be paid to the prevention and control of falls among the elderly aged ≥65 years.

Objective To investigate the risk factors for post-traumatic epilepsy(PTE)after traumatic brain injury(TBI).Methods According to PTE,169 patients with TBI were divided into PTE group and non-PTE group.Clinical data of the patients were collected and compared.Non-parametric test and binary Logistic regression were used to analyze the risk factors of PTE.Results Compared with those in non-PTE group,there were significant differences in psychiatric symptoms,GCS score,abnormal imaging examination type,injury type and post-traumatic seizures(PTS)ratio in the PTE group(P<0.05-0.01).Binary Logistic regression showed that GCS score,abnormal imaging examination type,psychiatric symptoms and PTS were independent risk factors for PTE(OR=5.825,95%CI:1.062-31.947,P=0.042;OR=6.942,95%CI:1.542-31.244,P=0.012;OR=31.059,95%CI:9.295-103.786,P<0.001;OR=0.099,95%CI:0.042-0.231,P<0.001).Conclusion GCS score,abnormal imaging examination type,psychiatric symptoms and PTS are independent risk factors PTE after TBI.

Polymyxin B and polymyxin E (colistin) are presently considered the last line of defense against human infections caused by multidrug-resistant Gram-negative organisms such as carbapenemase-producer Enterobacterales, Acinetobacter baumannii, and Klebsiella pneumoniae. Yet resistance to this last-line drugs is a major public health threat and is rapidly increasing. Polymyxin S₂ (S₂) is a polymyxin B analogue previously synthesized in our institute with obviously high antibacterial activity and lower toxicity than polymyxin B and colistin. To predict the possible resistant mechanism of S₂ for wide clinical application, we experimentally induced bacterial resistant mutants and studied the preliminary resistance mechanisms. Mut-S, a resistant mutant of K. pneumoniae ATCC BAA-2146 (Kpn2146) induced by S₂, was analyzed by whole genome sequencing, transcriptomics, mass spectrometry and complementation experiment. Surprisingly, large-scale genomic inversion (LSGI) of approximately 1.1 Mbp in the chromosome caused by IS26 mediated intramolecular transposition was found in Mut-S, which led to mgrB truncation, lipid A modification and hence S₂ resistance. The resistance can be complemented by plasmid carrying intact mgrB. The same mechanism was also found in polymyxin B and colistin induced drug-resistant mutants of Kpn2146 (Mut-B and Mut-E, respectively). This is the first report of polymyxin resistance caused by IS26 intramolecular transposition mediated mgrB truncation in chromosome in K. pneumoniae. The findings broaden our scope of knowledge for polymyxin resistance and enriched our understanding of how bacteria can manage to survive in the presence of antibiotics.

Objective To investigate the HIV-1 genotype and distribution of newly diagnosed HIV-1 cases in Fujian Province in 2020, so as to provide insights into formulation of the precise AIDS control strategy in the province. Methods Newly diagnosed HIV-1 cases without antiretroviral therapy (excluding AIDS patients) were randomly sampled from each city of Fujian Province in 2020 at a proportion of 50% of the mean number of HIV-infected cases reported across 9 cities of Fujian Province during the past three years. Subjects’ demographic and epidemiological data were collected and blood samples were collected. The HIV-1 pol gene was amplified using nested reverse-transcription PCR assay, and the gene sequences were used for HIV-1 genotyping and phylogenetic analysis. The gene sequences were uploaded to the HIV Drug Resistance Database (http://hivdb.stanford.edu) for genotypic drug resistance assays, and the scores and level of HIV drug resistance were estimated using the HIVDB Algorithm version 9.5. Results A total of 1 043 newly diagnosed HIV-1 cases were reported in Fujian Province in 2020, and 936 gene sequences were successfully obtained following sequencing of blood samples. There were 9 HIV-1 genotypes characterized in blood samples from 936 newly diagnosed HIV-1 cases, with CRF07_BC (52.1%) and CRF01_AE (30.4%) as predominant subtypes, followed by CRF08_BC (4.9%), CRF55_01B (3.0%), subtype C (2.5%), subtype B (2.1%), CRF85_BC (1.7%), CRF59_01B (0.3%) and CRF65_CPX (0.1%), and unidentified subtypes were found in 26 blood samples. HIV-1 drug resistance was detected in 43 out of the 936 newly diagnosed HIV-1 cases, with 4.6% prevalence of HIV-1 drug resistance prior to therapy, and the highest drug resistance was found in the HIV CRF59_01B subtype, followed by in CRF08_BC, B, C, CRF01_AE, CRF07_BC and other subtypes, with a significant difference in the genotype-specific prevalence of HIV-1 drug resistance (χ² = 45.002, P < 0.05). Conclusions There was a HIV-1 genotype diversity in Fujian Province in 2020, and emerging recombinant and drug-resistant HIV-1 strains were detected and spread across patients and regions. Monitoring of HIV-1 genotypes is recommended to be reinforced for timely understanding of the transmission and spread of novel recombinant and drug-resistant HIV-1 strains.

ObjectiveTo evaluate the current situation of human resource allocation in district and county centers for disease control and prevention （CDCs） in Kashgar ， identify existing problems and influencing factors， and to provide scientific evidence for optimizing the human resource allocation. MethodsA survey was conducted among all CDCs in Kashgar in February 2022. The questionnaire included the institutional and individual questions. ResultsThe overall staff size approved for the CDCs in Kashgar was 604， with a staffing rate of 76.17%， among which the staffing rates in 5 county CDCs were less than 60%. Currently， there were a total of 524 approved staff members in all CDCs， resulting in a vacancy rate of 13.25%. In the district CDC， 85 staff members were on duty， while the median of staff on duty was 34 in each county CDC. The staff in the district CDC was ageing， of which those aged over 45 accounted for 67.06%. The staff in the county CDCs was generally young， of which those aged less than 35 accounted for 54.22%. Moreover， the proportion of staff with bachelor’s degree or above in the district and county CDCs was 31.76% and 24.95%， respectively. The proportion of staff without professional title was 32.94% and 48.03%， respectively. In contrast， the proportion of those with middle and senior professional title was 57.89% and 22.02%， respectively. In addition， in recent 3 years， 24 staff members resigned in the CDCs， all of whom had professional titles. ConclusionHuman resources are insufficient in CDCs in Kashgar. Furthermore， staff structure is unreasonable， with a serious loss of human resources. In particular， the district CDC needs to optimize the allocation of human resources.

Objective:To research the metabolomic alterations of human lung bronchial epithelial cells infected with human rhinovirus 1B (HRV1B).Methods:Untargeted metabolomics was used to determine the metabolomic alterations in human lung bronchial epithelial cells (BEAS-2B) 6 h, 12 h and during the dynamic process (6 h∶12 h) after HRV1B infection.Results:A total of 93 differentially significant metabolites (DSMs) (47 DSMs were up-regulated and 46 DSMs were down-regulated) and 88 DSMs (37 DSMs were up-regulated and 51 DSMs were down-regulated) at post infection of HRV1B in BEAS-2B at 6 h or 12 h, respectively. A total of 30 DSMs (12 DSMs were up-regulated and 18 DSMs were down-regulated) in a dynamic process (6 h∶12 h) after HRV1B infection. Unknown metabolites took up most proportions. The trends of fatty acid, lipid, amino acid, nucleotide and carbohydrate were increased along with the prolonging of HRV1B infection. DSMs such as Diisononyl phthalate was co-detected DSMs among three groups.Conclusions:Metabolites such as fatty acid, lipid, amino acid, nucleotide and carbohydrate of BEAS-2B cells are changed induced by HRV1B infection.

Objective:To develop a prediction model of acute gastrointestinal injury (AGI) grading combined with qSOFA score for the diagnosis of sepsis, and evaluate its value.Methods:This was a prospective observational study. The patients with infection or suspected infection in the General Ward of Changshu Hospital Affiliated to Soochow University from September 2018 to September 2019 were included. Patients younger than 18 years, pregnant, abandoned treatment and died within 3 days after admission were excluded. Clinical characteristics, laboratory test results and AGI grading from 48 h before the infection to 24 h after the onset of infection were recorded. The patients were divided into the sepsis and non-sepsis groups according to whether they were diagnosed with sepsis. The patients were allocated randomly to a modeling cohort and a validation cohort with a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to analyze the relevant risk factors for sepsis in the modeling cohort. Three types of diagnostic models were constructed in the modeling cohort: model A (qSOFA model), model B (the combined model of AGI grading and qSOFA score), and model C (the combined model of clinical parameters). The clinical usefulness of the diagnostic models was assessed by receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) in the validation cohort. The nomograms were developed based on these models.Results:A total of 2 553 patients were enrolled in the study, 1 789 patients in the modeling cohort and 764 patients in the validation cohort. and 326 were diagnosed with sepsis. There was no statistical difference in the basic conditions of patients in the two groups. Univariate analysis showed that age, gender, the source of infection, temperature, heart rate, polypnea, changes in consciousness, severe edema, hyperglycemia, white blood cell, C-reactive protein and procalcitonin, hypotension, hypoxemia, acute oliguria, coagulation disorders, hyperlacticemia, capillary filling damage or piebaldskin, AGI grading and qSOFA score were significantly correlated with sepsis (all P<0.01). Multivariate logistic regression analysis showed that age ( OR=1.027, P<0.01), source of infection ( OR=2.809, P=0.03), hypotension ( OR=35.449, P<0.01), hypoxemia ( OR=57.018, P<0.01), and AGI grading ( OR=19.313, P<0.01) were significantly associated with sepsis. ROC analysis showed that the area under the curve (AUC) of model A, B and C were 0.784, 0.944 and 0.971 in the modeling cohort, and 0.832, 0.975 and 0.980 in the validation cohort, respectively. The sensitivities were 63.9%, 89.5% and 97.5% in the modeling cohort, and 72.7%, 90.9% and 96.6% in the validation cohort; and the specificities were 90.8%, 90.3% and 88.1% in the modeling cohort, and 92.2%, 94.5% and 92.8% in the validation cohort, respectively. AUC of model B and C were significantly higher than that of model A ( P<0.01). Model A in the validation cohort was poorly calibrated, with low accuracy and high risk of missed sepsis diagnosis ( P=0.044). The net benefits of model B and C were better than that of model A. Conclusions:AGI grading combined with qSOFA score has a high predictive value and accuracy in the diagnosis of sepsis.