ObjectiveTo systematically assess the public health governance capacity in Zhejiang Province, to conduct an in-depth analysis of its strengths and weaknesses, so as to provide scientific basis and strategic recommendations for further enhancement. MethodsA systematic collection of policy documents, public information reports, and research literature related to public health governance capacity in Zhejiang Province from 2002 to 2023 was conducted (encompassing a total of 1 263 policy documents, 138 pieces of information reports and 631 research articles). Based on the evaluation criteria suitable for public health systems previously developed by the research team, the basic status and magnitude of change in public health governance capacity in Zhejiang Province was evaluated. Additionally, normative gap analyses were employed to identify the strengths and weaknesses. ResultsZhejiang Province ranked 4th nationwide in terms of public health governance capacity with a score of 733.4 points (1 000.0-point maximum). The province has effectively implemented the principle of health first (scoring 698.5 points in the assessment of health-first strategy implementation) and attached sufficient importance to health-related goals (scoring 658.2 points in the scientific rationality of goal setting). However, the implementation of inter-departmental coordination and incentive mechanisms only scored 178.7 points, the feasibility of management and monitoring mechanisms scored even lower at only 144.0 points, and the coverage of incentive mechanisms scored 286.0 points. ConclusionZhejiang Province has effectively implemented its health first strategy and attached great importance to health targets, but still needs to strengthen cross-departmental coordination mechanisms and health-oriented incentives.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective: To investigate the prevalence and influencing factors of hypertension and diabetes mellitus comorbidity among residents in Urumqi City, so as to provide the evidence for integrated prevention and management of chronic disease. Methods: From May to August 2024, multistage random sampling was used to recruit permanent residents aged ≥18 years in Urumqi City. Data including demographic characteristics, lifestyles, family disease history, body mass index (BMI), waist circumference, blood pressure and blood biochemical indicators were collected through questionnaires, physical examinations and laboratory tests. Multivariable logistic regression models were used to analyze the influencing factors of hypertension-diabetes mellitus comorbidity. Results: A total of 14 917 residents were included, including 6 087 males (40.81%) and 8 830 females (59.19%) . The mean age of the participants was (55.79±14.88) years. A total of 1 768 hypertension and diabetes mellitus comorbidity cases were identified, with a comorbidity rate of 11.85%. Multivariable logistic regression analysis showed that residents aged ≥35 years (35-<65 years, OR=40.744, 95%CI: 13.076-246.033; ≥65 years, OR=108.834, 95%CI: 34.744-658.624), males (OR=1.120, 95%CI: 1.006-1.146), retirees (OR=1.714, 95%CI: 1.466-2.009), insufficient fruit intake (OR=1.498, 95%CI: 1.324-1.697), poor sleep quality (OR=1.394, 95%CI: 1.251-1.555), family history of diabetes mellitus (OR=2.715, 95%CI: 2.389-3.084), family history of hypertension (OR=1.154, 95%CI: 1.029-1.293), overweight or obesity (overweight, OR=1.156, 95%CI: 1.005-1.330; obesity, OR=1.417, 95%CI: 1.197-1.678), central obesity (OR=1.436, 95%CI: 1.259-1.639) and dyslipidemia (OR=1.491, 95%CI: 1.339-1.659) had a higher risk of comorbidity. Conclusion Hypertension-diabetes mellitus comorbidity among residents in Urumqi City was associated with age, gender, occupation, fruit intake, sleep quality, family history of diabetes mellitus and hypertension, BMI, central obesity and dyslipidemia.

BACKGROUND:Rev-erbα is involved in the regulation of inflammation,but pharmacological activation of Rev-erbα increases the risk for cardiovascular diseases.To reduce the relevant risk,an exploration on SR9009,a Rev-erbα agonist,combined with other drugs to relieve inflammation in skeletal myoblasts was conducted,laying the theoretical foundation for the treatment of inflammation-associated skeletal muscle atrophy. OBJECTIVE:To investigate the relationship of SR9009,indolepropionic acid and nuclear factor-κB signaling pathways in lipopolysaccharide-induced C2C12 myoblasts. METHODS:(1)C2C12 myoblasts were induced to differentiate in the presence of lipopolysaccharide(1 μg/mL).RNA-seq and KEGG pathway analysis were used to study signaling pathways.(2)C2C12 myoblast viability was assessed using the cell counting kit-8 assay to determine optimal concentrations of indolepropionic acid.Subsequently,cells were categorized into control group,lipopolysaccharide(1 μg/mL)group,SR9009(10 μmol/L)+lipopolysaccharide group,indolepropionic acid(80μmol/L)+lipopolysaccharide group,and SR9009+indolepropionic acid+lipopolysaccharide group.ELISA was employed to measure protein expression levels of interleukin-6 in the cultured supernatant.Real-time quantitative PCR were employed to measure mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Western blot assay were employed to measure protein expression levels of NF-κB p65 and p-NF-κB p65.(3)After Rev-erbα was knocked down by siRNA,knockdown efficiency was assessed by RT-qPCR.And mRNA levels of interleukin-6 and tumor necrosis factor α were also measured. RESULTS AND CONCLUSION:Compared with the blank control group,lipopolysaccharide time-dependently inhibited myofibroblast fusion to form myotubes,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were elevated,and the level of interleukin-6 in the cell supernatant was significantly increased.The results of KEGG pathway showed that the nuclear factor-κB signaling pathway was activated by lipopolysaccharide.Indolepropionic acid exhibited significant suppression of C2C12 myoblasts viability when its concentration exceeded 80 μmol/L.Indolepropionic acid and SR9009 inhibited the activation of NF-κB signaling pathway,thereby played an anti-inflammatory role,and suppressed the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Compared with the lipopolysaccharide group,the ratio of p-NF-κB p65/NF-κB p65 protein expression were downregulated.SR9009 combined with indolepropionic acid notably reduced lipopolysaccharide-induced inflammation,further downregulated the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.The ratio of p-NF-κB p65/NF-κB p65 protein expression was significantly lower than that in the SR9009+lipopolysaccharide group or indolepropionic acid+lipopolysaccharide group.Rev-erbα increases time-dependently with lipopolysaccharide induction.The knockdown efficiency of Rev-erbα by siRNA reached over 58%,and lipopolysaccharide was added after Rev-erbα was successfully knocked down.Compared with the lipopolysaccharide group,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were significantly up-regulated.These results conclude that Rev-erbα may act as a promising pharmacological target to reduce inflammation.SR9009 targeted activation of Rev-erbα combined with indolepropionic acid significantly inhibits the nuclear factor-κB signaling pathway and attenuates the inflammatory response of C2C12 myofibroblasts.Moreover,the combined anti-inflammatory effect is superior to that of the intervention alone.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

This report presents a case of a 9-year-old child with a complicated crown-root fracture of the maxillary central incisor, accompanied with a root fracture. The treatment strategy was minimally invasive, focusing on vital pulp preservation, root fracture recovery, and crown restoration. The fractured crown was reattached using resin short posts to enhance retention, resulting in aesthetic and functional restoration of the anterior teeth. A 2-year follow-up revealed favorable clinical and radiographic outcomes.
Humans ; Child ; Tooth Fractures/therapy* ; Tooth Root/injuries* ; Incisor/injuries* ; Tooth Crown/injuries* ; Post and Core Technique ; Dental Restoration, Permanent/methods* ; Maxilla

Objective : To investigate the effects of branched-chain amino acid(BCAA) on the differentiation of 3T3-L1 preadipocytes and its potential mechanism. Methods : 3T3-L1 preadipocytes were divided into the Control, differentiation medium(DM), low-concentration BCAA, and high-concentration BCAA groups. A CCK-8 assay was utilized to evaluate pre-adipocyte survival under various BCAA concentrations. Oil-red O staining was used to observe the formation of lipid droplets in adipocytes. Intracellular triglyceride(TG) and total cholesterol(TC) were detected by enzymatic method. RT-qPCR and Western blot were used to detect the mRNA and protein expression of Stat3 and adipocyte differentiation-related genes. Results : CCK-8 results showed that the viability of 3T3-L1 cells was not affected when the BCAA concentration was ≤ 10 mmol/L. Compared with the DM group, the low-concentration BCAA groups(0.5 and 1.0 mmol/L) had significantly larger intracellular lipid droplets, increased number of lipid droplets, and elevated levels of the intracellular TC(0.88vs0.68 mmol/g; 0.83vs0.68 mmol/g,P<0.01) and TG(0.77vs0.40 mmol/g; 0.62vs0.40 mmol/g,P<0.01). Nevertheless, the cell differentiation in the high-concentration group(5.0 and 10.0 mmol/L) significantly decreased compared with that in the DM group. Further, levels of PPARγ, C/EBPα, Adiponectin, and FABP4 mRNA and protein expression significantly increased in the low-concentration group, but significantly decreased in the high-concentration group than that in the DM group(P<0.01). In addition, low concentrations of BCAA promoted stat3 phosphorylation, while high concentrations inhibited its phosphorylation(P<0.01). Conclusion BCAA have a dual role in regulating the differentiation of preadipocytes through Stat3, i.e. low concentrations of BCAA induce cell differentiation by promoting Stat3 phosphorylation; whereas high concentrations of BCAA inhibit Stat3 phosphorylation and cell differentiation.

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life