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.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Isosteviol is a tetracyclic diterpenoid compound obtained by hydrolysis of natural stevia glycoside under acidic conditions. It has many pharmacological activities, such as anti-tumor, hypoglycemic, anti-inflammatory and antibacterial. Due to its low water solubility, low activity and low bioavailability, isosteviol has poor performance. In order to overcome these shortcomings, scholars have obtained a large number of isosteviol derivatives with novel structures and excellent activity. In this paper, we review the recent progress in the research on the structure modification, biological activity, structure-activity relationship and microbial transformation of isosteviol, in order to provide a reference for the development of new drugs of isosteviol and its derivatives.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

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 investigate the neuroprotective effect of 7,8-dihydroxyflavone(7,8-DHF)on cerebral hemorrhage in mice by regulating the tyrosine kinase receptor B(TrkB)/brain derived neurotrophic factor(BDNF)signal pathway.Methods C57BL/6 mice were injected with bacterial collagenase V Ⅱ to establish cerebral hemorrhage model.The mice were randomly grouped into model group,control group(5 mg·kg-1 7,8-DHF),experimental group(1 mg·kg-1 K252a),and combined group(5 mg·kg-1 7,8-DHF+1 mg·kg-1 K252a),mice injected with normal saline were used as sham-operation group,with 10 mice in each group.After the treatment,the mice were scored for neurological function by Garcia method,brain water contents of the brain tissue were detected by the dry and wet weight method,the blood brain barrier permeability was examined using the Evans blue method,the neuronal apoptosis was detected by TUNEL method,and the protein expression levels of TrkB,phosphorylated TrkB(p-TrkB)and BDNF were detected by Western blot.Results The neurological function scores of control,experimental,combined,model and sham-operation groups were(15.47±1.55),(7.23±0.73),(10.55±1.06),(10.45±1.05)and(16.12±1.62)points;the brain water contents were(62.88±2.19)％,(83.77±3.11)％,(72.71±2.59)％,(72.88±2.61)％and(59.64±2.06)％;the Evans blue contents were(3.26±0.36),(16.23±1.63),(8.78±0.88),(9.47±0.95)and(1.02±0.11)μg·g-1;neuronal apoptosis rates were(9.82±0.99)％,(39.88±3.99)％,(22.15±2.24)％,(25.71±2.58)％and(6.46±0.65)％;p-TrkB/TrkB ratios were 1.01±0.11,0.21±0.03,0.48±0.05,0.49±0.05 and 1.03±0.11;the protein expression levels of BDNF were 1.15±0.12,0.18±0.02,0.46±0.05,0.42±0.05 and 1.18±0.12,respectively.The above indexes of sham-operation,control and experimental groups were compared with those of model group,and the above indexes of control and experimental groups were compared with those of combined group,the differences were statistically significant(all P＜0.05).Conclusion 7,8-DHF has neuroprotective effect on mice with intracerebral hemorrhage,and its mechanism may be related to the activation of TrkB/BDNF signal pathway.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Inflammasome is a kind of intracellular polyprotein complex,which is an important component of the complex system of local inflammatory microenvironment after human tissue damage.When the inflammasome is activated,it induces the activation of cysteine aspartate proteinase 1(caspase-1),mediates the maturation and secretion of proinflammatory cytokines,such as interleukin(IL)-1 β and IL-18,and induces cell death,which plays an important role in regulating the host immune response to pathogen infection and tissue repair of cell damage.Nod-like receptor protein 3(NLRP3)inflammatory body,which is composed of NLRP3,pro-cysteine aspartic acid specific protease-1(pro-caspase-1)and apoptosis-related spot-like protein(ASC),is the most deeply and widely studied type of inflammatory body,which plays an important role in the regulation of inflammation.When NLRP3 inflammatory bodies are activated,inflammatory mediators are produced and released,which participate in the occurrence and development of a variety of inflammatory diseases.Some studies have shown that traditional Chinese medicine can improve the pathological state of a variety of diseases by inhibiting NLRP3 inflammatory bodies,and play a role in the prevention and treatment of a variety of inflammatory diseases,including cardiovascular diseases,joint inflammation,diabetes and so on.This paper systematically combs the mechanism of NLRP3 inflammatory bodies,and summarizes the latest research reports on the effects of traditional Chinese medicine compound prescription,traditional Chinese medicine monomers and traditional Chinese medicine extracts on NLRP3 inflammatory bodies in the treatment of inflammatory diseases,in order to provide new ideas for the further study of the pathogenesis and drug treatment of many inflammatory diseases.

Objective To investigate the effect of temozolomide(TMZ)combined with histone methyltransferase enhancer of Zeke 2(EZH2)inhibitor GSK343 on apoptosis and invasion of GH3 cells and its mechanism.Methods Different concentrations of TMZ treated cells were used to screen TMZ treated dose.GH3 cells were randomly divided into blank group,TMZ-L group(200 μmol·L-1 TMZ),TMZ-H group(400 μmol·L-1 TMZ),GSK343 group(20 μmol·L-1 GSK343)and TMZ+GSK343 group(400 μmol·L-1+20 μmol·L-1 GSK343).After 48 h of drug treatment,cell counting kit-8(CCK-8)assay was used to detect cell survival rate;terminal-deoxynucleoitidyl transferase mediated nick end labeling(TUNEL)and flow cytometry were used to detect cell apoptosis;Transwell assay was used to detect cell invasion ability;Western blot assay was used to detect cell-related protein expression.Results TUNEL positive cell rates in blank group,TMZ-L group,TMZ-H group,GSK343 group and TMZ+GSK343 group were(4.31±0.71)％,(15.36±0.91)％,(22.26±2.13)％,(13.05±0.71)％and(34.55±3.75)％;cell invasion numbers were(247.67±27.23),(183.00±20.66),(152.11±8.82),(182.89±18.24)and(116.11±12.73)cells;the expression levels of Bax protein were 0.44±0.05,0.58±0.06,0.81±0.07,0.66±0.06 and 1.03±0.06;the expression of E-cadherin protein were 0.33±0.05,0.57±0.05,0.84±0.12,0.59±0.07 and 1.00±0.12;Vimentin protein expression levels were 0.91±0.14,0.72±0.09,0.62±0.07,0.77±0.08 and 0.47±0.04;phosphorylated phosphatidyl alcohol 3-kinase(p-PI3K)protein expression levels were 0.99±0.11,0.86±0.06,0.68±0.07,0.72±0.08 and 0.52±0.08;phosphorylated protein kinase B(p-AKT)protein expression levels were 1.01±0.06,0.71±0.07,0.57±0.05,0.80±0.07 and 0.43±0.04.TMZ-L group,TMZ-H group,GSK343 group and TMZ+GSK343 group had significant differences in the above indexes compared with blank group(all P＜0.05);TMZ+GSK343 group was compared with TMZ-L group TM2-H group or GSK343 group,and the above indexes were significantly difference(all P＜0.05).Conclusion TMZ combined with EZH2 inhibitor GSK343 can significantly inhibit GH3 cell invasion and induce apoptosis,which may be related to the regulation of PI3 K/AKT pathway.

Objective To determine the relationship between methylenetetrahydrofolate reductase(MTHFR)C677T,A1298C and multidrug resistance 1(ABCB1)C3435T gene polymorphisms and the adverse reactions of high-dose methotrexate(HD-MTX)in children with acute lymphoblastic leukemia(ALL).Methods Blood samples of ALL children treated with HD-MTX chemotherapy were collected,and the polymorphic polymorphism of MTHFR C677T,A1298C and ABCB1 C3435T genes were detected by sequencing method.The adverse drug reactions after MTX chemotherapy were evaluated according to the common adverse drug reaction grading criteria.The relationship between MTHFR C677T,A1298C and ABCB1 C3435T gene polymorphisms and HD-MTX adverse drug reactions was analyzed.Results The risk of MTHFR A1298C AC+CC type hepatic injury(grade 2)was higher than AA type[odds ratio(OR)2.350,95％confidence interval(CI)=1.038-5.320,P＜0.05],no correlations were found between MTHFR A1298C and myelosuppression,mucositis,gastrointestinal reaction and acute renal impair(all P＞0.05).ABCB1 C3435T CT type hepatic injury(grade 2)was higher than TT type(OR 5.161,95％CI 1.371-19.424,P＜0.05),ABCB1 C3435T CC+CT type hepatic injury(grade 2)was higher than TT type(OR 4.231,95％CI 1.165-15.362,P＜0.05);no correlations were found between ABCB1 C3435T and myelosuppression,mucositis,gastrointestinal reaction and acute renal impair(all P＞0.05).No correlations wre found between MTHFR C677T and HD-MTX adverse drug reactions(all P＞0.05).Conclusion When treating ALL with HD-MTX,adverse drug reactions can be predicted by detecting MTHFR A1298C and ABCB1 C3435T genotypes,so as to implement more scientific individualized medication.