Objective: To explore the relationship between serum homocysteine (Hcy), interleukin-5 (IL-5), folate and core symptoms in children with autism spectrum disorders, so as to provide potential biomarkers for early diagnosis and intervention of diseases. Methods: A total of 106 children with autism spectrum disorders and 106 healthy children with matched sex and age in Lu an People s Hospital were enrolled as autism group and healthy group between May 2020 to December 2023. On the day of admission, levels of serum Hcy, IL-5 and folate were detected. The core symptoms in autism group were evaluated by Autism Behavior Checklist (ABC), Wechsler Preschool and Primary Scale of Intelligence-fourth edition(WPPSI-IV), Childhood Autism Rating Scale (CARS) and Social Responsiveness Scale (SRS). The levels of serum Hcy, IL-5 and folate in the two groups were compared by t- test. The relationship between serum Hcy, IL-5, folate and core symptoms in children with autism spectrum disorders was determined by Pearson correlation analysis. Results: The levels of serum Hcy and IL-5 in autism group were (7.48±0.32) μmol/L and (345.77±32.51) pg/mL, higher than those in healthy group [(6.11±0.54) μmol/L, (274.04±25.17) pg/mL], while folate level was lower than that in healthy group [(15.24±3.47) ng/mL, (22.51±4.69) ng/mL], the differences were statistically significant ( t =22.47, 17.96, 12.83, all P < 0.05 ). In autism group, levels of serum Hcy and IL-5 were positively correlated with scores of ABC, CARS and SRS ( r =0.29, 0.53 , 0.54; 0.45, 0.41, 0.50), while negatively correlated with WPPSI-IV score ( r =-0.28, -0.26)(all P <0.05). The folate level was negatively correlated with scores of ABC, CARS and SRS ( r =-0.55, -0.40, -0.25), while positively correlated with WPPSI-IV score ( r =0.41) (all P <0.05). Conclusion Children with ASD show elevated serum Hcy and IL-5 alongside decreased folate,and three markers correlate with core symptoms and intellectual level.

Objective: To propose an improved method for constructing the internal quality control (IQC) framework for ELISA assays and validate its efficacy by statistically analyzing IQC data from nine blood center laboratories. Methods: 1) IQC data was collected from nine blood centers and analyzed using a domestic HBsAg ELISA detection kit as an example. 2) Differences between IQC values across batches within Blood Center 1 were assessed. 3) Statistical analyses were performed on batch usage, number of batches used, days of use, number of QC points, batch-specific means, and coefficients of variation (CV) across all nine centers. 4) Using the improved construction method for IQC framework, provisional and permanent frames were established for batches within Blood Center 1 and Blood Center 9, followed by outlier determination. Results: 1) Statistically significant differences were observed in IQC data between batches within Blood Center 1 (P<0.01). It is recommended that both the control material/reagents and the control chart framework be replaced simultaneously. 2) There were substantial differences among 9 blood centers regarding the control material/reagent lot numbers used, the number of QC runs per batch, and the QC values for identical lots. Therefore, individual laboratories should establish their own IQC chart frameworks. 3) The improved IQC framework construction method for ELISA assays is as follows: provisional frames are established via frame-shifting, using the pre-experimental mean and cumulative coefficient of variation (CV) from the preceding batch. For batches used >20 days with >20 QC points, permanent frames are constructed by aggregating in-control data accumulated over ≥20 days with ≥20 points to calculate cumulative mean and standard deviation. The provisional and permanent frames constructed by this method identified all 26 extreme outliers across Blood Centers 1 and 9 as out-of-control. Among the 218 general outliers, 10 were classified as normal by the provisional frames, while the remainder were designated as warnings or out-of-control. This method effectively monitors assay stability. Conclusion: Based on the statistical analysis of IQC practices across blood centers of varying scales, combined with the inherent characteristics of ELISA assays and the batch-to-batch instability of reagents/QC materials, it is recommended to reconstruct QC charts upon lot changes. The proposed method—utilizing frame-shifting for provisional frames and establishing permanent frames based on cumulative data—is applicable to blood center laboratories of differing sizes and effectively monitors the stability of the ELISA assay process.

The benefit of postoperative adjuvant therapy for patients with resectable esophageal squamous cell carcinoma (ESCC) is not yet supported by high-level evidence. This review analyzes the role of adjuvant therapy by examining the discrepancy between clinical needs and guidelines, its historical evolution, recent advances in high-risk factors, and future outlooks. We provide a detailed discussion of high-risk factors used for patient selection, including lymph node positivity, and for node-negative patients, features such as tumor length, location, T stage, extent of lymph node dissection, differentiation, vascular and neural invasion, laboratory indices, and molecular markers. The goal is to inform the development of individualized precision treatment strategies for resectable ESCC.

Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

Artificial intelligence （AI） and population pharmacokinetics （PPK） technologies have demonstrated significant potential in the personalized medication of immunosuppressants after organ transplantation, enabling precise prediction of drug dosages. This article provides a comprehensive review of the application status of AI and PPK in the individualized administration of immunosuppressants after organ transplantation， focuses on monitoring blood drug concentration， predicting efficacy/adverse reactions， and establishing individualized dosing models for organ transplant recipients after immunosuppressant administration， and analyzes and compares the application characteristics of different methods in different organ transplant patients as well as the integration and future development of AI and PPK technologies. AI and PPK technologies can not only significantly reduce the dependence on human resources， but also greatly improve the level of individualized treatment of immunosuppressants after organ transplantation， and reduce the discomfort and burden caused by frequent blood concentration monitoring to patients.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective To investigate the efficacy of leaflet augmentation technique to repair the recurrent mitral valve (MV) regurgitation after mitral repair in children. Methods A retrospective analysis was conducted on the clinical data of children who underwent redo MV repair for recurrent regurgitation after initial MV repair, using a leaflet augmentation technique combined with a standardized repair strategy at Fuwai Hospital, Chinese Academy of Medical Sciences, from 2018 to 2022. The pathological features of the MV, key intraoperative procedures, and short- to mid-term follow-up outcomes were analyzed. Results A total of 24 patients (12 male, 12 female) were included, with a median age of 37.6 (range, 16.5–120.0) months. The mean interval from the initial surgery was (24.9±17.0) months. All children had severe mitral regurgitation preoperatively. The cardiopulmonary bypass time was (150.1±49.5) min, and the aortic cross-clamp time was (94.0±24.2) min. There were no early postoperative deaths. During a mean follow-up of (20.3±9.1) months, 3 (12.5%) patients developed moderate or severe mitral regurgitation (2 severe, 1 moderate). One (4.2%) patient died during follow-up, and one (4.2%) patient underwent a second MV reoperation. The left ventricular end-diastolic diameter was significantly reduced postoperatively compared to preoperatively [ (43.5±8.6) mm vs. (35.8±7.8)mm, P<0.001]. Conclusion The leaflet augmentation technique combined with a standardized repair strategy can achieve satisfactory short- to mid-term outcomes for the redo mitral repair after previous MV repair. It can be considered a safe and feasible technical option for cases with complex valvular lesions and severe pathological changes.

Glucagon-like peptide-1 （GLP-1） receptor agonists are a novel class of antidiabetic drugs that also possess lipid- lowering and cardiovascular protective effects， with liraglutide and semaglutide being their representative medications. Based on a systematic literature search， this review summarizes the lipid-lowering mechanisms by which liraglutide and semaglutide exert direct effects on the liver and kidney （regulating autophagy， key lipid metabolism pathways， reverse cholesterol transport， etc.）， direct actions on adipose tissue （affecting adipocyte proliferation and differentiation， expression of lipid metabolism proteins， and gene transcription）， activation of sympathetic pathways through the central nervous system， and modulation of the gut microbiota. Additionally， it summarizes the clinical evidence of their lipid-lowering effects in populations with type 2 diabetes mellitus， overweight individuals， and others. These findings indicate that GLP-1 receptor agonists exert lipid-lowering effects by acting on multiple tissues or systems， providing crucial evidence for further elucidating the molecular mechanisms of these drugs in lipid regulation and exploring potential new ideas for their clinical applications.

Numerous research conducted in recent years has revealed that gut microbial dysbiosis, such as modifications in composition and activity, might influence lung tissue homeostasis through specific pathways, thereby promoting susceptibility to lung diseases. The development and progression of lung cancer, as well as the effectiveness of immunotherapy are closely associated with gut flora and metabolites, which influence immunological and inflammatory responses. During abnormal proliferation, non-small cell lung cancer cells acquire more substances and energy by altering their own metabolic pathways. Glucose and amino acid metabolism reprogramming provide tumor cells with abundant ATP, carbon, and nitrogen sources, respectively, providing optimal conditions for tumor cell proliferation, invasion, and immune escape. This article reviews the relationship of immune response with gut flora and metabolic reprogramming in non-small cell lung cancer, and discusses the potential mechanisms by which gut flora and metabolic reprogramming affect the occurrence, development, and immunotherapy of non-small cell lung cancer, in order to provide new ideas for precision treatment of lung cancer patients.
Humans ; Gastrointestinal Microbiome/immunology* ; Carcinoma, Non-Small-Cell Lung/therapy* ; Lung Neoplasms/therapy* ; Immunotherapy ; Metabolic Reprogramming

Signal detection is a critical task in drug safety regulation. However, it inevitably generates irrelevant or false signals, posing challenges for resource allocation by marketing authorization holders. To reasonably assess these signals, different countries have established various principles for prioritizing the evaluation of risk signals. This study systematically compares these principles and finds that the U.S. Food and Drug Administration(FDA) focuses on practical issues, such as identifying drug confusion or drug interactions. However, China's Good Pharmacovigilance Practices and the European Medicines Agency(EMA) emphasize a comprehensive evaluation framework. The Council for International Organizations of Medical Sciences(CIOMS) emphasizes the consistency of multiple data sources, highlighting the reliability of signal evaluation. China practices a multidisciplinary approach combining traditional Chinese and western medicine, and the risk signals related to traditional Chinese medicine(TCM) have unique characteristics, including complex components, cumulative toxicity, specific theoretical foundations, and drug interactions. The different priorities in risk signal evaluation principles across countries suggest that China should strengthen clinical trial research, emphasize corroboration with evidence of multiple sources, and pay particular attention to the risks of drug interactions in the TCM regulatory science. Establishing the risk signal prioritization principles that align with the characteristics of TCM enables more precise and efficient scientific regulation of TCM.
Humans ; Medicine, Chinese Traditional/standards* ; China ; Drugs, Chinese Herbal/adverse effects* ; United States ; United States Food and Drug Administration