ObjectiveTo analyze the epidemiological characteristics of latent tuberculosis infection (LTBI) among newly detained populations in eastern China, to identify high-risk groups, and to provide a scientific basis for formulating tuberculosis prevention and control strategies in the prison system. MethodsA cross-sectional study was conducted among the newly admitted detainees in two prisons in eastern China in 2022. Data on demographic characteristics, behavioral risk factors and previous disease history of the research subjects were collected through a structured questionnaire survey. The LTBI status of the detainees was determined using the QuantiFERON-TB Gold In-Tube (QFT-GIT) method. Lasso regression was used to screen variables, followed by multivariate logistic regression analysis to investigate the influencing factors of LTBI. ResultsA total of 305 detainees were included in the study. The median age of detainees was 35 (31, 43) years. The study population was predominantly male (67.21%), of Han ethnicity (95.41%), had a junior or senior high school education (59.34%), and was unemployed (31.80%). A history of smoking was reported by 52.79% of participants, while 57.70% reported no alcohol consumption. The majority had no history of hypertension (85.90%), diabetes mellitus (93.77%), human immunodeficiency virus (HIV) infection (97.38%), familial genetic diseases (95.08%), surgery or trauma (73.77%), drug use (92.79%), or hepatitis (93.77%). The LTBI rate was 14.75%. After comparing the demographic characteristics of LTBI and non-infected groups, it was found that smoking history (χ²=7.40, P=0.025), drug use history (χ²=5.49, P=0.019), and HIV infection (χ²=8.12, P=0.004) were statistically correlated with LTBI infection. The results of multivariate logistic regression analyses showed that smoking [adjusted odds ratio (aOR)=4.08, 95%CI: 1.60‒10.42, P=0.003], HIV infection (aOR=11.57, 95%CI: 2.50‒53.51, P=0.002) and drug use (aOR=3.04, 95%CI: 1.02‒9.09, P=0.046) were risk factors for LTBI. ConclusionThe LTBI rate among newly detainees in two prisons in eastern China is slightly lower than that among long-term detainees. Early screening and intervention should be implemented for newly detainees, with particular attention focused on high-risk groups such as those with a history of smoking, HIV infection, or drug use.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective To evaluate the efficacy and safety of a combination therapy regimen comprising stereotactic body radiation therapy (SBRT) combined with liposomal irinotecan, camrelizumab, and anti-angiogenic therapy (CAP) in patients with advanced bone and soft tissue sarcomas. Methods This study is a prospective subgroup analysis of the multicenter, open-label, single-arm phase Ⅱ CAP trial (NCT04569916), which enrolled 60 patients with advanced solid tumors who had progressed after standard therapy between November 2020 and February 2023, including 11 patients with advanced bone and soft tissue sarcomas. All patients received sequential liposomal irinotecan within 48 hours after stereotactic body radiotherapy (SBRT), followed by maintenance therapy with camrelizumab and an anti-angiogenic agent until disease progression or intolerable toxicity. The primary efficacy endpoint was objective response rate (ORR). Secondary endpoints included disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety. Results In the bone and soft tissue sarcoma subgroup (n=11), three patients achieved partial response (PR), five had stable disease (SD), and three experienced disease progression (PD). ORR was 27.3%, and DCR was 72.7%. mPFS was 5.8 months (95%CI: 2.2-10.3), and mOS not reached. Regarding safety, adverse reactions primarily included bone marrow suppression, fatigue, and gastrointestinal reactions, indicating overall manageable toxicity. Conclusion As a subgroup analysis of the CAP study, this research suggests that radiotherapy combined with liposomal irinotecan, camrelizumab, and anti-angiogenic therapy demonstrates certain efficacy in advanced bone and soft tissue sarcomas that have failed multiple lines of treatment, with overall manageable adverse reactions. Future studies should expand the sample size.

Objective: To analyze near work illuminance patterns on school days and weekends among third and fourth grade primary school students by using objectively monitored data, and to examine the associations of the duration of near work under different illuminance levels and time weighted average near work illuminance with screening myopia. Methods: From April to June 2024, students from grades 3 and 4 in two primary schools in Jiading District, Shanghai were selected as study subjects by using stratified random cluster sampling method. Continuous objective monitoring of near work behavior was conducted for 7 days while information from uncorrected visual acuity and refractive assessment was collected, and an online questionnaire survey was administered to their parents. Valid samples comprised 372 students on school days and 292 on weekends. Welch s t test was used to compare differences in the duration of near work under different illuminance levels between the screening myopia and non-myopia groups. Multivariable binary Logistic regression analysis was employed to assess the association between the duration of near work under different illuminance levels and screening myopia. Restricted cubic spline (RCS) model was used to explore the nonlinear association between time weighted average near work illuminance with 60 cm and screening myopia, and the critical thresholds identified by the RCS model were used to categorize illuminance levels for subsequent Logistic regression analyses. Results: Objective monitoring of near work behavior showed that the duration of near work in the low illuminance range of [0,125)lx was significantly longer on weekends[(4.12±2.21)h] than on school days [(2.42±1.22)h]. Multivariate Logistic regression analysis revealed that only on school days, each additional hour of near work duration in the [0,125)lx ( OR =1.56, 95% CI =1.23-1.98) and ≥1 000 lx range ( OR =5.92, 95% CI =1.48-23.73) were significantly associated with higher odds of screening myopia(both P < 0.05). RCS plot showed that on school days, time weighted average near work illuminance with 60 cm had a non-linear association with screening myopia ( P non-linear <0.05). On weekends, no significant association was found between near work illuminance indicators and screening myopia (all P >0.05). Conclusions Primary school students engage in near work for considerable durations in insufficient lighting environments on both school days and weekends. Increased duration of near work in overly dim or bright environments on school days may increase the risk of screening myopia.

The risk prediction of paroxysmal atrial fibrillation (PAF) is a challenge in the field of biomedical engineering. This study integrated the advantages of machine learning feature engineering and end-to-end modeling of deep learning to propose a PAF risk prediction method based on multimodal feature fusion. Additionally, the study utilized four different feature selection methods and Pearson correlation analysis to determine the optimal multimodal feature set, and employed random forest for PAF risk assessment. The proposed method achieved accuracy of (92.3 ± 2.1)% and F1 score of (91.6 ± 2.9)% in a public dataset. In a clinical dataset, it achieved accuracy of (91.4 ± 2.0)% and F1 score of (90.8 ± 2.4)%. The method demonstrates generalization across multi-center datasets and holds promising clinical application prospects.
Humans ; Atrial Fibrillation/diagnosis* ; Machine Learning ; Deep Learning ; Risk Assessment/methods*

Automatic classification of medical questions is of great significance in improving the quality and efficiency of online medical services, and belongs to the task of intent recognition. Joint entity recognition and intent recognition perform better than single task models. Currently, most publicly available medical text intent recognition datasets lack entity annotation, and manual annotation of these entities requires a lot of time and manpower. To solve this problem, this paper proposes a medical text classification model, bidirectional encoder representation based on transformer-recurrent convolutional neural network-entity-label-semantics (BRELS), which integrates medical entity label semantics. This model firstly utilizes an adaptive fusion mechanism to absorb prior knowledge of medical entity labels, achieving local feature enhancement. Then in global feature extraction, a lightweight recurrent convolutional neural network (LRCNN) is used to suppress parameter growth while preserving the original semantics of the text. The ablation and comparison experiments are conducted on three public medical text intent recognition datasets to validate the performance of the model. The results show that F1 score reaches 87.34%, 81.71%, and 77.74% on each dataset, respectively. The results show that the BRELS model can effectively identify and understand medical terminology, thereby effectively identifying users' intentions, which can improve the quality and efficiency of online medical services.
Semantics ; Neural Networks, Computer ; Humans ; Natural Language Processing

OBJECTIVE: To evaluate the early effectiveness of transosseous suture fixation in treating recurrent acute patellar dislocation with patellar osteochondral fractures (OCFs). METHODS: A retrospective analysis was conducted on 19 patients with recurrent acute patellar dislocation and patellar OCFs, who underwent transosseous suture fixation between January 2018 and December 2022 and were followed up 2 years. The cohort included 8 males and 11 females, aged 13-21 years (mean, 16.2 years). Patients experienced 2-5 times of patellar dislocation (mean, 3.2 times). The interval from the last dislocation to operation ranged from 3 to 15 days (mean, 9.6 days). Preoperative imaging revealed the intra-articular osteochondral fragments and medial patellofemoral ligament (MPFL) injury. Clinical outcomes were evaluated using the visual analogue scale (VAS) score for pain, the International Knee Documentation Committee (IKDC) score, the Hospital for Special Surgery (HSS) knee score, the Lysholm score, and the Tegner score. Postoperative complications were recorded. During follow-up, the knee X-ray films, CT, and MRI were taken to evaluate fragment healing, displacement, and the morphology and tension of the MPFL reconstruction graft. RESULTS: All incisions healed primarily, and no complication occurred such as infection, joint stiffness, patellofemoral arthritis, or redislocation. Patients were followed up 24-60 months (mean, 43.5 months). At 12 months postoperatively and the last follow-up, significant improvements ( P<0.05) were observed in VAS, Lysholm, IKDC, HSS, and Tegner scores compared to preoperative values. Further improvements were observed at last follow-up compared with the 12 months postoperatively, and the differences were significant ( P<0.05). Imaging studies demonstrated satisfactory osteochondral fragment positioning with stable fixation. At last follow-up, all fragments had healed, and MPFL reconstruction grafts exhibited optimal morphology and tension. No joint adhesion or fragment displacement occurred. CONCLUSION For recurrent acute patellar dislocation with patellar OCFs, transosseous suture fixation proves to be both safe and effective, achieving satisfactory early effectiveness.
Humans ; Male ; Female ; Patellar Dislocation/surgery* ; Adolescent ; Young Adult ; Retrospective Studies ; Patella/surgery* ; Suture Techniques ; Treatment Outcome ; Recurrence ; Fracture Fixation, Internal/methods* ; Fractures, Bone/surgery* ; Follow-Up Studies

An ideal dermal filler should integrate filling, repair, and anti-aging effects, with immediate tissue augmentation, slow degradation, and progressive stimulation of collagen regeneration. However, commonly used hyaluronic acid (HA) hydrogels, while effective for rapid filling, suffer from limited duration of support, weak cell adhesion, and an inability to promote collagen regeneration. Silk fibroin (SF), a natural protein from silkworm cocoons, is known for its excellent cell adhesion and collagen-stimulating abilities. However, its limited gelation capability restricts its potential application as a standalone injectable hydrogel. Based on a complementary strategy, this study combines the rapid gelling properties of HA with the collagen regenerative properties of SF to create a co-crosslinked HA-SF hydrogel. The composite hydrogel merges HA's rapid filling effect with SF's strong tissue adhesion and collagen-stimulating abilities. The formulation, physicochemical properties, degradation, biocompatibility, and filling effects of the HA-SF hydrogel were systematically investigated. HA-SF hydrogel exhibits excellent mechanical properties and ensures long-term support while maintaining injectability. Interestingly, after intradermal injection in the UVB-induced photoaging model, HA-SF hydrogel not only enhances hydrogel-cell interaction but also continues to stimulate collagen regeneration, especially type III collagen. This dual action achieves the biological effects of repair and anti-aging while maintaining the filling effect. Proteomic analysis confirms that repair and anti-aging effects are enhanced by the regulation of skin fibroblasts and modulation of amino acid and lipid metabolism. This composite hydrogel holds strong promise for clinical applications, offering a safer, long-lasting, and more natural injectable filler that combines filling, repair, and anti-aging into one system.

Objective:To analyze risk factors for early trauma-induced coagulopathy (TIC) in pediatric patients with moderate-to-severe traumatic brain injury (msTBI), develop a predictive model and evaluate its predictive performance.Methods:A retrospective cohort study was conducted to analyze the clinical data of 290 pediatric patients with msTBI who were admitted to Children′s Hospital of Soochow University between January 2016 and December 2024, including 188 boys and 102 girls, aged 0.2-15.7 years [5.2(2.8, 9.3)years]. Based on the coagulation test results at admission, the patients were divided into TIC group ( n=162) and non-TIC group ( n=128). The patients were randomly allocated into training set ( n=203) and validation set ( n=87) at a ratio of 7∶3. Demographic characteristics, clinical data, vital signs, imaging findings, arterial blood gas analysis results, and coagulation profiles of the patients were collected. Univariate analysis and Lasso regression analysis were used to identify risk factors associated with early TIC in children with msTBI and multivariate Logistic regression analysis was performed to determine independent risk factors and construct a predictive model. The model′s discrimination and calibration were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow (H-L) test, and calibration curve. Its clinical utility was assessed through decision curve analysis (DCA). Results:Significant differences were observed between the TIC group and non-TIC group in terms of age, weight, time from injury to admission, child′s Glasgow coma scale (CGCS) score, pediatric trauma score (PTS), shock index, heart rate, respiratory rate, systolic blood pressure, Rotterdam CT score, intraventricular hemorrhage, cerebral contusion, brain herniation, long bone fracture, pelvic fracture, hemopneumothorax, pulmonary contusion, intra-abdominal organ injury, actual bicarbonate, base excess, base excess in the extracellular fluid, blood glucose, hemoglobin (Hb), osmolarity, blood calcium, anion gap, blood lactate, prothrombin time, activated partial thromboplastin time, international normalized ratio, and platelet count ( P<0.05). With coagulation-related variables excluded, the following features were identified with Lasso regression including CGCS score, PTS, heart rate, systolic blood pressure, long bone fracture, blood glucose, and Hb. Multivariate Logistic regression analysis revealed that CGCS score≤8 points ( OR=3.05, 95% CI 1.65, 5.63), PTS>5 points ( OR=0.45, 95% CI 0.23, 0.89), systolic blood pressure ( OR=0.98, 95% CI 0.97, 0.99), blood glucose ( OR=1.09, 95% CI 1.01, 1.17), and long bone fracture ( OR=2.47, 95% CI 1.13, 5.42) were influencing factors for early TIC in children with msTBI ( P<0.05). The regression equation of the predictive model was established as follows: Logit[ P/(1- P)]=1.01×"CGCS score≤8 points"-0.69×"PTS>5 points"- 0.02×"systolic blood pressure"+0.89×"long bone fracture"+0.08×"blood glucose"+1.32. The ROC curve analysis showed that the training set had an AUC of 0.86 (95% CI 0.78, 0.94), with sensitivity and specificity of 76.6% and 92.5%, while the AUC was 0.80 (95% CI 0.74, 0.86), with sensitivity and specificity of 75.7% and 79.6% in the validation set. H-L test results showed a χ2 value of 8.18 ( P=0.416) in the training set and 5.30 ( P=0.216) in the validation set. The calibration curves for both sets demonstrated good agreement with the actual curves, indicating that the predicted probabilities closely matched the observed probabilities. The DCA results indicated that both the training set and validation set demonstrated positive net benefits within threshold probabilities ranges of 10%-100% and 15%-96%. Conclusions:Independent risk factors for early TIC in pediatric msTBI patients include CGCS score≤ 8 points, PTS≤5 points, low systolic blood pressure, long bone fracture, and high blood glucose. The predictive model constructed based on these factors demonstrates favorable predictive performance and clinical application value.

Objective:To investigate the association between hearing loss and the type of indoor fuel applications in Chinese middle-aged and elderly people through longitudinal cohort study.Methods:Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), including adults aged 45 years and older enrolled in 2011, with follow-up for cooking and heating analyses extending to 2018 and 2015, respectively. The study calculated the incidence of hearing loss based on an indoor cooking or heating fuel type and expressed in terms of per 100 person-years. The Cox proportional hazard model was used to assess the association between solid fuel use and hearing loss, and covariates such as gender, education, and economy were controlled. We also analyzed the impact of indoor fuel type and its switching on hearing loss.Results:A total of 6, 772 participants using household fuels for cooking (2011-2018) and 4, 618 for heating (2011-2015) were included. Those using solid fuels for cooking [(58.0±8.2) years] and heating [(58.1±8.5) years] were generally slightly older than that of those who used clean fuels. In the cooking analysis, the overall incidence of hearing loss was higher among solid fuel users compared to clean fuel users (Clean fuel: 2.6 cases per 100 person-years; solid fuel: 3.6 cases per 100 person-years; the difference between the two was statistically significant, P<0.05). However, no significant difference was observed in the heating analysis ( P>0.05). Further classification of fuel-type use revealed that the incidence of hearing loss was the highest among people who had been using solid fuels consistently. Compared to the clean fuel group, the fully adjusted hazard ratio (HR) was 1.5 (95% CI: 1.3-1.7) in the cooking analysis and 1.5 (95% CI: 1.1-2.0) in the heating analysis. Compared with using clean fuels, switching from clean fuels to solid fuels increased the risk of hearing loss both during cooking and heating processes. Conclusion:In the CHARLS database, individuals who use solid fuels for indoor cooking and heating are older than those who use clean fuels. Compared with clean fuel use, the use of solid fuels increases the risk of hearing loss in middle-aged and elderly people. Reducing the use of solid fuels, choosing clean fuels as substitutes for solid fuels, and avoiding the switch from clean fuels to solid fuels will help protect the hearing health of middle-aged and elderly individuals.