Objective: To analyze the spatio-temporal distribution of pulmonary tuberculosis (PTB) among students in Suzhou City, Jiangsu Province from 2015 to 2023, so as to provide the evidence for the prevention and control of PTB in schools. Methods: Data of PTB cases among students in Suzhou City from 2015 to 2023 were collected from Chinese Disease Prevention and Control Information System and Suzhou Report of Investigation and Disposal of Tuberculosis in Schools. The seasonal incidence of PTB among students was analyzed using seasonal index (SI). The spatio-temporal clustering characteristics of PTB among students were analyzed using spatial autocorrelation and retrospective spatio-temporal permutation scanning. Results: Totally 1 374 PTB cases among students were reported in Suzhou City from 2015 to 2023. PTB cases were reported in each month, and the SIs were 100.69%, 124.38%, 108.98%, 135.04%, 106.61% and 106.61% in April, May, July, September, October and November, respectively, indicating the prevalence of PTB among students. Spatial autocorrelation analysis showed there was a positive spatial correlation of PTB among students in 2019 and 2020 (Moran's I=0.053 and 0.089, both P<0.05). From 2015 to 2023, there were high-high clustering sites mainly in Hengtang Street and Shishan Street. Retrospective spatio-temporal permutation scanning showed a primary cluster in Hengtang Street, with aggregation time in 2017, and 6 secondary clusters covering 25 towns (streets). Conclusion From 2015 to 2023, the PTB cases among students in Suzhou City were mainly concentrated in summer and autumn, and were predominantly clustered in Hengtang Street and Shishan Street.

Diabetic cardiomyopathy （DCM） is a myocardium-specific microvascular disease caused by diabetes mellitus that impairs the structure and function of the heart. It is the major cause of morbidity and mortality in diabetic individuals. Traditional Chinese medicine （TCM） has extensive clinical experience and precise efficacy in treating DCM， and its multi-target， multi-pathway， multi-component， and low side effect approach can slow the progression of DCM and improve the symptoms while effectively dealing with the complexity and long-term nature of its pathological process. Many recent studies have demonstrated that pyroptosis accompanied by inflammatory response is one of the main types of myocardial injury in DCM， which promotes the development of DCM and is closely related to pathological changes such as oxidative stress， myocardial fibrosis， myocardial hypertrophy， and decreased cardiac function in the course of DCM. These findings also provide a theoretical foundation for future research into potential therapy techniques and intervention mechanisms for DCM. By searching and analyzing relevant literature from several databases， including CNKI， PubMed， Web of Science， Excerpt Medica， Science Direct， and Springer， this study aimed to comprehensively analyze the characteristics of the effects of TCM and compounds in intervening in cardiomyocyte pyroptosis in DCM in recent years and explore the potential mechanisms. It also reveals the potential of effective components of TCM and compounds in preventing and controlling DCM from the standpoint of cardiomyocyte pyroptosis and provides a new way of thinking and more experimental evidence for the clinical application of TCM in treating DCM.

OBJECTIVE To investigate the effects and mechanism of Wenpi tongluo kaiqiao formula （WPTL） against neuronal necroptosis in Alzheimer’s disease （AD） mice based on the Z-DNA binding protein 1 （ZBP1）/mixed lineage kinase domain-like protein （MLKL） signaling pathway. METHODS Forty APP/PS1 transgenic AD mice were randomly divided into model group， WPTL low-dose （WPTL-L） group （10.4 g/kg， calculated by the raw medicine）， WPTL high-dose （WPTL-H） group （20.8 g/kg， calculated by the raw medicine） and donepezil hydrochloride group （3 mg/kg）， with 10 mice in each group； another 10 C57BL/6J mice were selected as normal control group. Intragastric administration， once a day， for 30 consecutive days. Twenty-four hours after the last administration， Morris water maze test was performed to evaluate learning and memory abilities； the pathological morphology of hippocampal tissues was observed； the serum levels of tumor necrosis factor-α （TNF-α） and interleukin-4 （IL-4） were determined； the expressions of amyloid precursor protein （APP）， Tau protein， and ZBP1/MLKL signaling pathway-related proteins in hippocampal tissues were detected； the positive expression of phosphorylated receptor-interacting protein kinase 3 （p-RIPK3） in the neurons of hippocampal tissues and mRNA expression of ZBP1 were measured in hippocampal tissues. RESULTS Compared with normal control group， the escape latency of mice in model group was prolonged significantly on day 3 to 5 （P＜0.05）， the times of crossing platform reduced significantly （P＜0.05）， and obvious pathological changes were observed in the hippocampal tissue. The level of TNF- α， the expressions of APP， p-Tau and ZBP1， the phosphorylation levels of RIPK1， RIPK3 and MLKL， the fluorescence intensity of p-RIPK3 as well as the mRNA expression of ZBP1 were significantly increased （P＜0.05）， while the serum level of IL-4 was decreased significantly （P＜0.05）. Compared with model group， above indexes were reversed significantly in administration groups （P＜0.05）， and pathological damage of hippocampal tissue was alleviated. CONCLUSIONS WPTL can inhibit the ZBP1/MLKL signaling pathway， reduce neuronal necroptosis in AD mice， and inhibit inflammatory responses， thereby improving learning and spatial memory abilities in AD mice.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

OBJECTIVE To investigate the intervention effect and its potential mechanism of Yifei xuanfei jiangzhuo formula by inhibiting mitochondrial fission in a vascular dementia （VaD） model rats. METHODS VaD rat model was established by bilateral common carotid artery ligation. The experimental animals were randomly divided into sham operation group （SHAM）， model group （MOD），Yifei xuanfei jiangzhuo formula low-dose group （YFXF-L）， Yifei xuanfei jiangzhuo formula high-dose group （YFXF-H）， and Donepezil hydrochloride group （positive control）， with 9 animals in each group. After 30 days of intervention， the spatial learning memory ability was assessed by Morris water maze experiment； HE staining was used to observe histopathological changes in CA1 area of hippocampus； ELISA was used to detect the levels of serum inflammatory factors [interleukin-1β （IL-1β） and IL-4]； Western blot was used to detect the expressions of heat shock protein 90 （HSP90）/mixed lineage kinase domain-like protein （MLKL）/dynamin-related protein 1 （Drp1） pathway-related proteins， mitochondrial fusion proteins （MFN1， MFN2）， and adenosine triphosphate synthase 5A （ATP5A） in hippocampal tissues. The immunohistochemistry was used to detect the level of phosphorylated MLKL （p-MLKL）； real-time fluorescence quantitative PCR was adopted to detect mRNA expressions ofHSP90， MFN1， MFN2 and ATP5A. RESULTS Compared with SHAM group， the escape latency of rats in the MOD group was significantly prolonged， the number of crossing the platform was significantly reduced， and the hippocampal tissues showed typical neuronal damage characteristics， the positive expression level of p-MLKL and the serum level of IL-1β significantly increased， while the serum level of IL-4 significantly decreased， the protein and mRNA expression of HSP90， as well as the protein expressions of p-MLKL/MLKL and p-Drp1（Ser616）/Drp1 were all significantly increased in hippocampal tissue， the protein and mRNA expressions of MFN1， MFN2 and ATP5A， and protein expression of p-Drp1（Ser637）/Drp1 were all significantly decreased （P＜0.05）. After the intervention of Yifei xuanfei jiangzhuo formula， above indicators in each treatment group were all significantly reversed （P＜0.05）. CONCLUSIONS Yifei xuanfei jiangzhuo formula may alleviate neuronal damage and neuroinflammatory responses in VaD rats by regulating the HSP90/MLKL/Drp1 signaling pathway， inhibiting mitochondrial fission， thereby maintaining mitochondrial dynamic balance and improving mitochondrial function.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To analyze the relationship between the risk of tuberculosis outbreaks in schools and the visit interval of index cases, so as to provide a scientific reference for predicting the risks of tuberculosis outbreak and making preventive measures. Methods: A total of 630 index cases from school tuberculosis outbreaks were studied during January, 2015 to December, 2022. Data on demographics, consultation history, etiological diagnosis, and methods of detection were collected. Restricted Cubic Splines (RCS), unconditional Logistic regression, and the receiver operating characteristic curve (ROC curve) were used for analysis. Results: The RCS fitted curve showed that the risk of a tuberculosis outbreak linearly increased when the consultation interval for etiologically negative patients exceeded 5.79 days, or for etiologically positive patients exceeded 8.37 days. After multi factor adjustment, for every additional day in the visit interval of the index case, the odds ratio ( OR ) value for a high risk outbreak was 1.10 (95% CI =1.07-1.13)( P <0.05). When analyzed by tertiles of visit intervals, compared to an interval of <14 days, the OR values (95% CI ) for high risk outbreaks in schools with intervals of 14-<28 days and ≥28 days were 10.32(3.04-35.10) and 82.58( 28.42 -239.95), respectively( P <0.01), indicating a trend of increasing outbreak risk with longer visit intervals. Based on the ROC curve analysis, the optimal threshold for predicting a high risk school tuberculosis outbreak was 23.5 days, with an area under the curve ( AUC ) of 0.93 (95% CI =0.89-0.98). Conclusion An extended visit interval of index cases is a good early warning indicator for high risk tuberculosis outbreaks in schools and could be considered a key factor in early intervention and risk control strategies.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.

α7 nicotinic acetylcholine receptor(α7nAChR)is widely expressed in the central nervous system and immune system,and plays a neuro-immunoregulatory role.On the one hand,α7nAChR is involved in the transmission of neurotransmitters,the conduction of excitatory signals and the maintenance of synaptic plasticity,which is of great significance for maintaining the normal and stable neurocognitive function.On the other hand,as an important part of the cholinergic anti-inflammatory pathway,α7nAChR is involved in the regulation of physiological and pathological processes such as inflammatory response,oxidative stress,apoptosis and autophagy in the central system,and plays an immunomodulatory and neuroprotective role,thus being potential target for improving perioperative neurocognitive function.This article reviews the biological characteristics of α7nAChR and its effect on perioperative neurocognitive function,in order to provide ideas and methods for clinical improvement of perioperative neurocognitive function in surgical patients.

The COVID-19 epidemic has spread to the whole world for three years and has had a serious impact on human life, health and economic activities. China's epidemic prevention and control has gone through the following stages: emergency unconventional stage, emergency normalization stage, and the transitional stage from the emergency normalization to the "Category B infectious disease treated as Category B" normalization, and achieved a major and decisive victory. The designated hospitals for prevention and control of COVID-19 epidemic in Tianjin has successfully completed its tasks in all stages of epidemic prevention and control, and has accumulated valuable experience. This article summarizes the experience of constructing a hospital infection prevention and control system during the "Category B infectious disease treated as Category A" period in designated hospital. The experience is summarized as the "Cluster" hospital infection prevention and control system, namely "three rings" outside, middle and inside, "three districts" of green, orange and red, "three things" before, during and after the event, "two-day pre-purification" and "two-director system", and "one zone" management. In emergency situations, we adopt a simplified version of the cluster hospital infection prevention and control system. In emergency situations, a simplified version of the "Cluster" hospital infection prevention and control system can be adopted. This system has the following characteristics: firstly, the system emphasizes the characteristics of "cluster" and the overall management of key measures to avoid any shortcomings. The second, it emphasizes the transformation of infection control concepts to maximize the safety of medical services through infection control. The third, it emphasizes the optimization of the process. The prevention and control measures should be comprehensive and focused, while also preventing excessive use. The measures emphasize the use of the least resources to achieve the best infection control effect. The fourth, it emphasizes the quality control work of infection control, pays attention to the importance of the process, and advocates the concept of "system slimming, process fattening". Fifthly, it emphasizes that the future development depends on artificial intelligence, in order to improve the quality and efficiency of prevention and control to the greatest extent. Sixth, hospitals need to strengthen continuous training and retraining. We utilize diverse training methods, including artificial intelligence, to ensure that infection control policies and procedures are simple. We have established an evaluation and feedback mechanism to ensure that medical personnel are in an emergency state at all times.