Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

Objective To explore the research hotspots and development trends in the field of cancer treatment in the past decade. Methods The CNKI and Web of Science Core Collection databases were searched for Chinese and English articles related to cancer treatment published over the last 10 years. Bibliometric research methods were employed, including keyword cluster analysis of published literature. Results A total of 45 455 Chinese articles and 866 958 English articles were retrieved. Combining the visualization analysis results and the current research dilemma of tumor treatment revealed that the current research hotspots of tumor treatment domestically and internationally can primarily focus on four key areas. In the realm of targeted therapy, efforts are directed towards the discovery of new drug targets, overcoming resistance to targeted therapy, and the development of monoclonal antibodies and antibody–drug conjugates. In the field of immunotherapy, the emphasis lies in enhancing the response rate to immune checkpoint inhibitors, determining the mechanisms behind resistance to immunotherapy, and improving the safety of treatment. The research in traditional Chinese medicine (TCM) covers evidence-based evaluation studies on TCM treatment, the identification of populations that can gain the most benefit from TCM, and strategies for improving the quality of life. In the area of novel drug development, cutting-edge technologies, such as organoid-based screening for anticancer drugs, synthetic biology, and artificial intelligence, are under investigation. Conclusion New targeted drugs, immune efficacy improvement, multidisciplinary integration, nano-delivery, and TCM innovation are the key research directions in the field of tumor therapy in the future.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

A wealth of prior studies has confirmed that intratumoral microbiota can survive within tumor tissue, thereby promoting or inhibiting tumor growth. With the development of high-throughput sequencing and metabolomics, increasing attention has been paid to the correlation between intratumoral microbiota and host metabolism, and their effect on tumorigenesis and progression. This review focuses on the interaction between intratumoral microbiota and tumor metabolism. It emphasizes the effects of intratumoral microbiota on tumor sugar, lipid, and amino acid metabolism and explores emerging therapeutic strategies for guiding tumor prevention and treatment by modulating tumor metabolism. Although the specific role of intratumoral microbiota in tumor metabolism remains to be further studied, a deepened understanding of the interaction between tumor-specific microbiota and tumor metabolism may provide new directions and application prospects for tumor prevention and treatment.

In this article,the mechanism of Shanxian Granule in inhibiting liver cancer,lung cancer,sarcoma,melanoma and other tumors was reviewed,with a view to providing a theoretical basis for the clinical research of Shanxian Granules in the treatment of malignant tumors.Shanxian Granule are the pure Chinese medicine preparation for counteracting malignant tumor developed by the Oncology Research Team of Shaanxi University of Chinese Medicine on the basis of the theory of traditional Chinese medicine syndrome differentiation and treatment combined with decades of clinical experience as well as the achievements of modern pharmacological research.Shanxian Granule are mainly composed of Crataegi Fructus,Agrimoniae Herba,Panacis Quinquefolii Radix,Curcumae Rhizoma,Testudinis Carapax et Plastrum,Trionycis Carapax,Corydalis Rhizoma,and Polyporus,and have the actions of benefiting qi and nourishing yin,supporting healthy-qi and cultivating the essence,activating blood and removing stasis,and eliminating swelling and counteracting cancer.The compatibility of Shanxian Granule embodies the principle of supporting healthy-qi but avoiding maintaining pathogens,and eliminating pathogens but avoiding injuring healthy-qi.The granules can effectively inhibit the growth and metastasis of liver cancer,lung cancer,sarcoma,melanoma and other tumors both in vivo and in vitro,alleviate the clinical symptoms of tumor patients,and improve their prognosis.The anti-tumor mechanism of Shanxian Granules is related to the enhancement of body immune function,inhibition of tumor cell proliferation,enhancement of tumor cell apoptosis,inhibition of tumor cell invasion and metastasis as well as the tumor angiogenesis.

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.

Objective To evaluate the relationship between diabetic nephropathy(DN)and diabetic retinopathy(DR)in patients with type 2 diabetes mellitus(T2DM)based on imaging and clinical testing data.Methods Totally 600 T2DM patients who visited the First People's Hospital of Ziyang from March 2021 to December 2022 were included.The fundus photography and fundus fluorescein angiography were performed on all these patients and their age,gender,T2DM duration,cardiovascular diseases,cerebrovascular disease,hypertension,smoking history,drinking history,body mass in-dex,systolic blood pressure,diastolic blood pressure and other clinical data were collected.The levels of fasting blood glu-cose(FPG),triglyceride(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),low-density lipo-protein cholesterol(LDL-C),glycosylated hemoglobin(HbA1c),24 h urinary albumin(UAlb),urinary albumin to creati-nine ratio(ACR),serum creatinine(Scr)and blood urea nitrogen(BUN)were measured.Logistic regression was used to analyze the risk factors associated with DR.DR staging was performed according to fundus images,and the convolutional neural network(CNN)algorithm was used as an image analysis method to explore the correlation between DR and DN based on emission computed tomography(ECT)and clinical testing data.Results The average lesion area rates of DR and DN detected by the CNN in the non-DR,mild-non-proliferative DR(NPDR),moderate-NPDR,severe-NPDR and pro-liferative DR(PDR)groups were higher than those obtained by the traditional algorithm(TCM).As DR worsened,the Scr,BUN,24 h UAlb and ACR gradually increased.Besides,the incidence of DN in the non-DR,mild-NPDR,moderate-NPDR,severe-NPDR and PDR groups was 1.67％,8.83％,16.16％,22.16％and 30.83％,respectively.Logistic regression analysis showed that the duration of T2DM,smoking history,HbA1c,TC,TG,HDL-C,LDL-C,24 h UAlb,Scr,BUN,ACR and glomerular filtration rate(GFR)were independent risk factors for DR.Renal dynamic ECT analysis demonstrated that with the aggravation of DR,renal blood flow perfusion gradually decreased,resulting in diminished renal filtration.Conclusion The application of CCN in the early stage DR and DN image analysis of T2DM patients will improve the diag-nosis accuracy of DR and DN lesion area.The DN is worsening as the aggravation of DR.

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.