Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

ObjectiveTo investigate the epidemiological characteristics of human parainfluenza virus (HPIV) in Pudong New Area, Shanghai, and to provide a basis for the prevention and control of HPIV infections in this area. MethodsA total of 8 180 cases with acute respiratory infection (ARI)/influenza-like illness (ILI) attending the fever outpatient clinics, pediatric outpatient clinics, respiratory outpatient clinics, pediatric wards, emergency departments, respiratory wards, and intensive care units (ICUs) and other monitoring departments in 9 sentinel hospitals in Pudong New Area from 2017 to 2022 were selected as the research subjects, and their nasopharyngeal/ throat swabs were collected. Polymerase chain reaction (PCR) method was performed for testing the respiratory virus such as influenza virus, human adenovirus, human parainfluenza virus, respiratory syncytial virus (RSV), human enterovirus, rhinovirus, et al. HPIV serotypes were analyzed, and the detection rates of HPIV were compared between different times, seasons, and population groups. ResultsThe overall HPIV detection rate of ARI/ILI cases in Pudong New Area was 3.73% (305/8 180) in 2017‒2022, with HPIV-3 being the predominant serotype. The detection rate of HPIV decreased significantly in 2017‒2022, peaking at 7.66% (99/1 293) in 2017 and falling to 0.80% (13/1 617) in 2021. Statistically significant differences were observed in HPIV detection rates across different years (χ²_trend=80.037, P_trend<0.001). The detection rate was higher in 2017‒2019 than that in 2020‒2022 (χ²_trend=38.990, P_trend<0.001). HPIV exhibited seasonal patterns in 2017‒2019, with higher detection rates in summer and autumn and lower in spring and winter, whereas no seasonal patterns were observed in 2020‒2022. Children aged <6 years had the highest detection rate (7.07%, 139/1 967), followed by adults aged ≥60 years (4.78%, 85/1 779). Statistically significant differences were observed in the detection rates of HPIV among different age groups (χ²=111.210, P<0.001). Symptoms of HPIV infection were predominantly cough, fever, and runny nose in pre-school children, fever, cough, and sore throat in school-age children, and adults, and cough, expectoration, and fever in the elderly. ConclusionThe HPIV detection rate in Pudong New Area was low in 2017‒2022. The seasonal pattern of HPIV circulation in Pudong New Area disappeared in 2020‒2022 due to the influence of infectious disease epidemics. Young children and the elderly should be prioritized in HPIV prevention and control efforts.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

To analyze the prevalence, drug resistance and whole genome characteristics of Mycoplasma pneumoniae (MP) in respiratory throat swab samples of hospitalized children with pneumonia in Suzhou City from 2023 to 2024. Throat swab samples of hospitalized children aged 0-14 years old with pneumonia in Suzhou were collected from September 2023 to September 2024. Real-time fluorenscence quantitative PCR technology was used to detect MP nucleic acid. The results showed that the positive rate of MP in 3 235 samples was 22.44% (726/3 235), with a rate of 55.00% in week 47 of 2023. The positive rate of MP increased with age ( χ2=45.842, P<0.001). The study selected MP nucleic acid test positive samples from week 20 (5.13-5.19) to week 23 (6.3-6.9) of 2024 for isolation, culture and resistance phenotype detection. About 31 MP strains were successfully isolated and cultured, all of which were resistant to macrolides. The next-generation sequencing technology and nanopore sequencing technology were used for genome sequencing. All 31 strains carried the A2063G mutation, with the main prevalent genotype being the P1-1, and the main mlST type being the ST3. Despite the overall genomic similarity between strains being over 99%, there were significant differences between the P1-1 and P1-2 strains in the P1 gene region. In summary, from 2023 to 2024, the main MP type prevalent in Suzhou City is the P1-1 genotype. All isolated MP strains carry an A2063G resistance site mutation and are resistant to macrolides, requiring continuous monitoring and further research.

Objective To investigate the efficacy of Castor branching stent in treating Stanford type B aortic dissection(TBAD)involving aortic arch.Methods The clinical data of 18 patients with Stanford TBAD,who were treated with Castor branching stent at the Suining Municipal Central Hospital of China from January 2020 to January 2022,were retrospectively analyzed.Results The main bracket and branch bracket of Castor branching stent were successfully released in all the 18 patients with a surgical success rate of 100％,and no internal leakage occurred during operation.During the perioperative period,there were neither aorta-related deaths nor serious complications such as stroke,upper limb ischemia,internal leakage,or stent displacement.The patients were followed up for(14.7±8.3)months,no aorta-related death,stroke,upper limb ischemia,internal leakage,or stent displacement was observed,the blood flow of the left subclavian artery(LSA)was unobstructed,but there was thrombosis formation within the false lumen of the covered stent segment.Conclusion The Castor branching stent has the advantages of reasonable release mode,accurate positioning,effective isolation of the first rupture of Stanford TBAD and reconstruction of LSA,with no serious short-term complications.However,further follow-up observation is needed before its long-term efficacy can be clarified.

Objective:To investigate effect of comprehensive management intervention based on WeChat multimedia classroom on cardiac function and prognosis in elderly patients with acute myocardial infarction(AMI).Methods:Clinical data of 118 elderly patients diagnosed with AMI in the Second Affiliated Hospital of Chinese PLA Air Force Military Medical University between August 2021 and December 2022 were retrospectively collected.According to nursing way after operation,they were divided into control group(n=60,comprehensive management interven-tion)and intervention group(n=58,comprehensive management intervention based on WeChat multimedia class-room),both groups were intervened for 5 months.Cardiac function,exercise tolerance,compliance to rehabilita-tion management,self-efficacy and healthy behavior were compared between two groups.Kaplan-Meier survival curve was employed to compare incidence of adverse cardiovascular events during follow-up between two groups.Results:After 5-month intervention,compared with patients in control group,those in intervention group had sig-nificant higher left ventricular ejection fraction(LVEF)[(58.14±1.88)％vs.(54.48±1.34)％],6min walking distance(6MWD)[(490.41±59.59)m vs.(394.97±28.20)m],scores of compliance to rehabilitation manage-ment[(6.97±2.03)points vs.(5.03±1.40)points],General Self-Efficacy Scale(GSES)[(30.34±4.67)points vs.(23.55±4.86)points]and Health Promoting Lifestyle Profile-Ⅱ[(137.62±30.17)points vs.(115.95±22.66)points],and significant lower left ventricular end-diastolic volume(LVEDV)[(117.90±4.22)ml vs.(131.28±3.61)ml],left ventriadar end-systolic volume(LVESV)[(54.46±2.10)ml vs.(63.15±2.06)ml],serum brain natriuretic peptide(BNP)[(362.32±25.36)pg/ml vs.(567.58±21.90)pg/ml]and incidence of ad-verse cardiovascular events(6.90％vs.21.67％)(P＜0.05 or＜0.01).Conclusion:Comprehensive management intervention based on the WeChat multimedia classroom could significantly improve cardiac function,exercise toler-ance,compliance to rehabilitation,self-efficacy and healthy behavior,and reduce incidence of adverse cardiovas-cular events after operation in elderly AMI patients.

Objective:Analyze the risk factors for acute lung injury of postoperative acute lung injury(ALI)in patients with Stanford type A aortic dissection(STAAD),and construct a nomogram predictive model.Methods:A retrospective cohort study design was adopted.A total of 112 patients with STAAD who underwent surgical treatment in our hopital from January 2021 to August 2024 were included.They were divided into two groups according to the occurrence of ALI after the surgical:non-ALI group(73 cases)and ALI group(39 cases).Clinical data were collected from both groups of patients.The influencing factors of postoperative ALI in patients with STAAD were analyzed by multivariate logistic regression.Established nomogram prediction model based on influencing factors and validated.Results:Among 112 patients with STAAD who underwent surgical treatment,39 case postoperative ALI occurred,with an incidence rate of 34.82％.Age,preoperative creatinine,body mass index(BMI),preoperative white blood cell count,preoperative lactate and other aspects compared,The difference were statistically significant(P＜0.05).The length of stay in the intensive care unit(ICU)of the ALI group was longer than that of the non ALI group(P＜0.05).The intraoperative red blood cell transfusion volume and extracorporeal circulation time in the ALI group were higher than those in the non ALI group(P＜0.05).Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count were risk factors for postoperative ALI(P＜0.05).The receiver operating characteristic(ROC)curve analysis results show that,the Area under the curve(AUC)of the nomogram prediction model was 0.871.When the optimal critical value was 0.472,its sensitivity and specificity wew 0.887 and 0.776,respectively.The internal validation results of Bootstrap show that,the C-index of the column chart prediction model was 0.862,with an absolute error of 0.032.The calibration curve is close to the ideal curve and the original curve,with a slope close to 1.Conclusions:Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count are independent risk factors for postoperative ALI in patients with STAAD.The nomogram model constructed based on the above risk factors can effectively evaluate the risk of postoperative ALI in patients with STAAD.

Objective To investigate the relationships of serum microRNA-9-3p(miR-9-3p),microRNA-27b-3p(miR-27b-3p),with brain glioma(BG)grading and their impacts on prognosis.Methods A total of 172 BG patients admitted in Suqian Hospital of Jiangsu Provincial People's Hos-pital from May 2020 to May 2023 were enrolled and divided into high-grade group(grade Ⅲ to Ⅳ,n=101)and low-grade group(grade Ⅰ to Ⅱ,n=71)according to the World Health Organization(WHO)classification of central nervous system tumors.Additionally,85 healthy individuals of the same age range during the same period were selected as control group.General information,serum levels of miR-9-3p,and miR-27b-3p were compared among the three groups.The correlations of pre-treatment serum levels of miR-9-3p and miR-27b-3p with BG grading were analyzed.The prognosis of BG patients one year after treatment was recorded,and clinical data were compared between the poor prognosis group and the good prognosis group.Factors influencing poor prognosis in BG patients as well as the value of pretreatment serum miR-9-3p and miR-27b-3p in predicting poor prognosis were analyzed.Conventional factors influencing poor prognosis were used to establish a conventional prediction mod-el,and model combined with pretreatment serum miR-9-3p and miR-27b-3p levels was used as a new prediction model.The value of these two models in predicting poor prognosis in BG patients was compared.Results Before treatment,serum levels of miR-9-3p and miR-27b-3p were lower in the high-grade group than those in the low-grade and control groups,and lower in the low-grade group than those in the control group(P＜0.05).Correlation analysis showed that pretreatment serum levels of miR-9-3p and miR-27b-3p were negatively correlated with BG grading(r=-0.573,P＜0.001;r=-0.498,P＜0.001),and serum miR-9-3p level was positively correlated with miR-27b-3p level in BG patients(r=0.509,P＜0.05).Before treatment,the poor prognosis group had a higher proportion of patients with WHO grade Ⅲ to Ⅳ,low differentiation,Karnofsky Performance Scale(KPS)＜70,and higher serum interleukin-17(IL-17)levels compared to the good prognosis group,while serum levels of miR-9-3p and miR-27b-3p were lower(P＜0.05).Logistic regression analysis showed that pretreatment WHO grading,differentiation,KPS,serum IL-17,miR-9-3p,and miR-27b-3p levels were all influencing factors of poor prognosis in BG patients(P＜0.05).Receiver operating characteristic(ROC)curves showed that the areas under the curve(AUCs)for pretreatment serum miR-9-3p and miR-27b-3p alone in predicting poor prognosis in BG patients were 0.714 and 0.720,respectively,with no statistically significant difference(Z=0.086,P=0.413).The AUC of the conventional prediction model for predicting poor prognosis in BG patients was 0.829,and the AUC of the new prediction model was 0.926(P＜0.05).Conclusion Serum levels of miR-9-3p and miR-27b-3p are negatively correlated with BG grading and are factors influ-encing poor prognosis,demonstrating certain value in predicting poor prognosis.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.