Objective: To analyze the process of handling a pulmonary tuberculosis(TB) outbreak among senior high school students in a boarding school in Chongqing, as well as to investigate the underlying causes of the outbreak, so as to provide evidence to inform TB prevention and control strategies in school settings. Methods: From November 2023 to April 2024, an epidemiological investigation was conducted into the TB outbreak in a grade 12 class from a boarding high school. Suspected cases were screened using symptom screening, tuberculin skin test (TST), and chest X-ray examinations. Confirmed cases underwent individual epidemiological interviews and sputum culture; Cultured positive mycobacterial strains were subjected to whole genome sequencing after identification as Mycobacterium tuberculosis. Results: A total of 10 active pulmonary TB cases were identified, all from the same class, yielding a student attack rate of 16.67%. Three isolates were culture positive, as well as all strains were of L2 type，and the WGS analysis of the strains suggested a common transmission chain. Excluding the index case, four additional cases were detected through symptom driven health care visits. Notably, 70% of patients presented with "chest tightness and chest pain" symptoms, and 50% had "cough" symptoms,but none were detected during morning health checks or tracking of absences due to illness. A total of 326 contacts were identified and underwent three rounds of screening and one follow up examination. In the initial screening, 35 close contacts from the same class showed strong TST positivity, corresponding to a strong positivity rate of 55.56%, significantly higher than the 20.76% observed among casual contacts ( χ 2=29.80, P <0.01). Among the 35 strongly TST positivvity close contacts and five individuals with moderate TST positivity whose induration had increased by ≥10 mm over two years, none received timely preventive treatment initially; five of them were subsequently diagnosed with active TB within three months. Following this, 25 individuals initiated preventive therapy, resulting in a preventive treatment initiation rate of 62.50%. Among TST negative classmates who converted to strong positivity on repeat TST testing at three months, 75.00% started preventive treatment, but only 22.22% completed the full course. Conclusion Inadequate implementation of morning health checks and cause tracking for absenteeism due to illness, poorly standardized screening procedures, and delayed preventive treatment may have been key factors contributing to the spread of the outbreak.

Innovation entities bear primary responsibility for the management of scientific and technological ethics. Understanding the current construction status of the scientific and technological ethical governance capacity among Chinese innovation entities is conducive to grasping effectiveness and shortcomings of scientific and technological ethical governance of innovation entities， providing a scientific basis and practical guidance for innovation entities to fulfill their primary responsibilities better. Based on a questionnaire survey targeting 313 innovation entities， this paper investigated and analyzed the current status and existing challenges of scientific and technological ethical governance capacity among Chinese innovation entities from five aspects. It was found that China has made certain achievements in scientific and technological ethical governance， yet there were still issues such as incomplete construction of regulatory systems， low efficiency of ethical review， unestablished regular education and training systems， and imperfect dynamic monitoring systems for ethical risks. Among these issues， the scientific and technological ethical governance capacity of enterprises was identified as requiring urgent improvement. Additionally， strengthening multi-stakeholder collaboration remained a key challenge in building a collaborative and co-governance system for scientific and technological ethics. Based on these issues identified in the survey， countermeasures and suggestions were proposed from five perspectives， that is， enhancing the capacity in institutional construction， ethical review， value transmission， risk early warning， and collaborative governance of innovation entities on scientific and technological ethical governance. The aim was to provide references for accelerating the construction of the scientific and technological ethical governance system and improving the scientific and technological ethical governance capacity of innovation entities.

ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Objective:To describes the probability and rate of native liver survival (NLS) in biliary atresia (BA) patients after Kasai portoenterostomy (KPE)over various time periods and analyzes the perioperative factors associated with liver transplantation or death.Methods:A retrospective case-summary.BA patients administrated at the Department of Fetal and Neonatal Surgery in Hunan Children′s Hospital between January 2015 and December 2021.Probability and rate of NLS were calculated by life table.Cox proportional hazards regression model and Logistic model was applied to explore the perioperative factors related to post-Kasai liver transplantation/death.Results:The median age at Kasai surgery was 62 days.The rate of jaundice clearance (JC) was 64.5% within 3 months after Kasai, and 58.3% of the patients had cholangitis.The probability of NLS reached its lowest point in the first 1 year after Kasai (76.2%) and ranged from 93.2% to 98.0% in years 2-8 after Kasai.The rates of NLS in 2 years, 5 years and 8 years were 71.1%, 62.8% and 56.0%, respectively.Cytomegalovirus (CMV) infection before or on the day of Kasai without antiviral treatment can increase the risk of liver transplantation or death[ HR(95% CI): 1.628 (1.081-2.452), P=0.020].Preoperative gamma-glutamyl transferase increased the risk of liver transplantation/death within 1 year after Kasai[ OR(95% CI): 1.001 (1.000-1.001), P=0.021], and early cholangitis was a risk factor for liver transplantation/death within 5 years after Kasai[ OR(95% CI): 1.934 (1.004-3.726), P=0.048].JC within 3 months post-KPE was a protective factor of NLS. Conclusions:The first year after Kasai was the highest risk period for liver transplantation/death, which should be the focus of follow-up management.JC within 3 months after surgery is the protective factor for overall NLS, 1-year NLS and 5-year NLS.

OBJECTIVE To explore the effect of the comprehensive unit-based safety program(CUSP)collaborative action strategy on reducing the incidence of catheter-associated urinary tract infection(CAUTI)in elderly patients.METHODS From Jun.to Nov.2024,the Seventh Medical Center of the PLA General Hospital implemented the CUSP collaborative action strategy for intervention.Comparisons were made between pre-intervention(from Dec.2023 to May 2024)and post-intervention(from Jun.to Nov.2024)regarding nurses' know ledge-attitude-practice(KAP)scores on CAUTI prevention,implementation rates of key nursing measures for elderly CAUTI prevention and CAUTI incidence rates among elderly patients.RESULTS The pre-intervention KAP score of nurses from geriatric de-partment on CAUTI prevention was(83.44±6.67),significantly lower than the post-intervention score(108.19±16.27)(P＜0.001).The implementation rates of 10 key nursing measures for elderly CAUTI prevention improved(P＜0.05).The incidence rate of CAUTI was 2.88‰(16/5 546)among 5 546 catheter days before the intervention,and the incidence rate of CAUTI was 0.73‰(4/5 496)among 5 496 catheter days after the intervention(P=0.008).CONCLUSIONS The CUSP collaborative action strategy effectively enhances the KAP levels of nurses from geriatric department on CAUTI prevention,improves the implementation rates of key nursing measures,and reduces CAUTI incidence rates among elderly patients.

Objective To explore the factors affecting the coefficient of variation(CV)of glucose in type 2 diabetes mellitus(T2DM)patients based on real-time dynamic glucose monitoring system.Methods A total of 354 patients with T2DM hospitalized in the Department of Endocrinology of Jiangsu Shengze Hospital were enrolled in this study from March 2023 to March 2024 and divided into two groups:the glycemic variability(GV,CV>36%)group(n=118)and the glucose stable(GS,CV≤36%)group(n=236).The clinical data of the two groups were compared,and the influencing factors for CV>36%were analyzed.Results The DM duration and HbA1c were higher(P<0.05),while BMI,visceral fat area,subcutaneous fat area(SFA),FC-P,serum uric acid(SUA),and TG were lower in the GV group than in the GS group(P<0.05).Spearman correlation analysis showed that CV was positively correlated with diabetes duration and HbA1c(P<0.05),and negatively correlated with FC-P,SFA and SUA(P<0.05).Logistic regression analysis showed that DM duration,HbA1c,SFA,FC-P and SUA were the influencing factors for GV.Scatter plot analysis showed that there was a linear trend between CV level and log HbA1c and log SFA in T2DM patients.CV level increased with the increase of log HbA1c,and decreased with the increase of log SFA.ROC curve analysis showed that the area under the curve(AUC)of FC-P was 0.703(95%CI:0.640～0.765,P<0.001)for predicting GV in T2DM patients,and the cut-off value was 1.095 ng/ml.The AUC of SUA was 0.622(95%CI:0.555～0.688,P<0.001)for predicting GV,and the cut-off value was 280.5 μmol/L.Conclusions The DM duration,HbA1c,SFA,FC-P and SUA are important factors for GV,and FC-P and SUA have predictive value for GV.

Objective:To investigate and validate the performance of a dosiomics model that utilized 3D dose distribution to forecast radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients following intensity-modulated radiotherapy (IMRT).Methods:Clinical data of 3578 patients diagnosed with NPC admitted to Jiangsu Cancer Hospital from January 2011 to December 2021 were retrospectively analyzed. According to the inclusion and exclusion criteria, 97 NPC patients who developed RTLI were assigned into the case group. A 1:1 propensity score matching (PSM) method was used to match 97 NPC patients without RTLI as the control group. Patients were assigned into the training cohort ( n=135) and the validation cohort ( n=59) at a 7:3 ratio by simple random method. Dosiomics features were extracted from the patients' three-dimensional dose distribution maps. Spearman rho and the least absolute shrinkage and selection operator regression were used to select dosiomics features. Clinical features were collected and screened by univariate and multivariate analyses. Eight machine learning classifiers were then trained to build dosiomics models and clinical models, respectively. The area under the ROC curve (AUC), sensitivity, and specificity were calculated to compare the predictive performance of the dosiomics and clinical models. Multivariate analysis was conducted using logistic regression to assess the influencing factors, while comparisons of the ROC curves between two different models were performed using the DeLong test. Results:A total of 1130 dosiomics features were extracted from the three-dimensional dose distribution maps, and 14 features were retained for model building after feature selection. The model based on the support vector machine (SVM) classifier achieved the highest AUC value of 0.977 (95% CI: 0.949-1.000) in the validation cohort, with an AUC of 1.000 (95% CI: 1.000-1.000) in the training cohort. By conducting univariate and multivariate analyses of the patients' clinical features, 2 clinical features were retained to build the clinical model. The model based on the SVM classifier achieved the optimal AUC value of 0.667 (95% CI: 0.523-0.810) in the validation cohort, with an AUC of 0.804 (95% CI: 0.730-0.878) in the training cohort. DeLong test showed that the difference between the dosiomics and clinical models was statistically significant ( P<0.05). Conclusion:The dosiomics model based on 3D dose distribution yields high predictive performance for RTLI in NPC patients after IMRT, which surpasses the clinical feature model, providing a new approach for early clinical prediction of RTLI.

Objective To explore the factors affecting the coefficient of variation(CV)of glucose in type 2 diabetes mellitus(T2DM)patients based on real-time dynamic glucose monitoring system.Methods A total of 354 patients with T2DM hospitalized in the Department of Endocrinology of Jiangsu Shengze Hospital were enrolled in this study from March 2023 to March 2024 and divided into two groups:the glycemic variability(GV,CV>36%)group(n=118)and the glucose stable(GS,CV≤36%)group(n=236).The clinical data of the two groups were compared,and the influencing factors for CV>36%were analyzed.Results The DM duration and HbA1c were higher(P<0.05),while BMI,visceral fat area,subcutaneous fat area(SFA),FC-P,serum uric acid(SUA),and TG were lower in the GV group than in the GS group(P<0.05).Spearman correlation analysis showed that CV was positively correlated with diabetes duration and HbA1c(P<0.05),and negatively correlated with FC-P,SFA and SUA(P<0.05).Logistic regression analysis showed that DM duration,HbA1c,SFA,FC-P and SUA were the influencing factors for GV.Scatter plot analysis showed that there was a linear trend between CV level and log HbA1c and log SFA in T2DM patients.CV level increased with the increase of log HbA1c,and decreased with the increase of log SFA.ROC curve analysis showed that the area under the curve(AUC)of FC-P was 0.703(95%CI:0.640～0.765,P<0.001)for predicting GV in T2DM patients,and the cut-off value was 1.095 ng/ml.The AUC of SUA was 0.622(95%CI:0.555～0.688,P<0.001)for predicting GV,and the cut-off value was 280.5 μmol/L.Conclusions The DM duration,HbA1c,SFA,FC-P and SUA are important factors for GV,and FC-P and SUA have predictive value for GV.

Jaws and alveolar defects present significant challenges in reconstructive surgery and implant restoration.Calcium phos-phate(CaP)bioceramics are commonly used as bone substitute and play a crucial role in repairing bone defects.Recent studies have shown that T cells play an important regulatory role in bone regeneration.The studies on CaP bioceramics and T cells,including their subpopulations,in bone regeneration,and the mechanisms through which CaP bioceramics regulate the behavior of T cells has been re-viewed.

Objective:To construct and evaluate a risk warning model for enteral nutrition associated diarrhea(ENAD)in acute stroke patients based on logistic regression and Nomogram.Methods:This study was a retrospective study,a total of 172 patients with acute stroke who were admitted to Yancheng First People's Hospital from January 2022 to May 2024 were selected,and clinical data of patients were collected.Multivariate logistic regression analysis was used to identify the influencing factors of ENAD occurrence,based on the results of the multivariate logistic regression analysis,a Nomogram warning model was constructed,the receiver operating characteristic(ROC)curve was applied to analyze the predictive value of the Nomogram warning model for the risk of ENAD occurrence in patients with acute stroke.Results:Univariate analysis showed that,the occurrence of ENAD in patients with acute stroke was related to fasting time,mechanical ventilation,oral potassium preparations,albumin,number of types of antibiotics used,acute physiology and chronic health status Ⅱ(APACHE Ⅱ)score,enteral nutrition infusion rate,length of stay in the intensive care unit(ICU),use of proton pump inhibitors,duration of antibiotic use,use of gastrointestinal prokinetic drugs,and daily enteral nutrition infusion volume(P＜0.05).The results of multiple logistic regression analysis showed that,high APACHE Ⅱ score,prolonged use of antibiotics,low albumin,use of gastrointestinal prokinetic drugs,oral potassium preparations,prolonged fasting time,and rapid enteral nutrition infusion were risk factors for ENAD in patients with acute stroke(P＜0.05).Construct and validate a Nomogram warning model based on the results of multiple logistic regression analysis.After evaluation,the model fits well with an area under the curve(AUC)of 0.823,indicating high predictive value for ENAD occurrence in patients with acute stroke.Conclusion:High APACHE Ⅱ score,prolonged use of antibiotics,low albumin,use of gastrointestinal prokinetic drugs,oral potassium preparations,prolonged fasting time,and rapid enteral nutrition infusion are risk factors for ENAD in patients with acute stroke.The Nomogram warning model constructed based on the above indicators has high predictive value for the occurrence of ENAD in patients with acute stroke.