To standardize the clinical application of oral Chinese patent medicines （CPMs）， and address the safety issues arising from their dosage form characteristics， irrational clinical use， and the lack of targeted pharmacovigilance systems， the China Association of Chinese Medicine organized the formulation and release of Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines， aiming to inform the safe clinical use of oral CPMs and related pharmacovigilance work. According to the principles of GB/T1.1—2020 and the Drug Administration Law of the People's Republic of China （2019 revision）， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， led a drafting group comprising 18 institutions. After multiple rounds of expert interviews， literature retrieval， evidence screening， and extensive solicitation of opinions， the Guidelines were registered internationally. Systematic standardization focused on safety monitoring， risk identification， assessment， control， and other aspects. The Guidelines clarified the characteristics of oral CPMs in terms of safety monitoring， known risks， and potential risks， compared to non-oral CPMs. Then， risk control measures were proposed， including medication in special populations and irrational medication. As a special guideline for pharmacovigilance in the clinical application of oral CPMs， the Guidelines systematically construct a technical system in line with the characteristics of traditional Chinese medicine （TCM）， which is essential for improving the clinical safety management of oral CPMs and provides an important reference for medical institutions， pharmaceutical manufacturers， and regulatory authorities.

ObjectiveTo express and purify the endolysin PlyL from the Bacillus anthracis prophage LambdaBa02 in prokaryotic cells, and to explore its role in the detection of Bacillus anthracis, so as to provide a novel strategy for the specific and rapid detection of Bacillus anthracis.MethodsAccording to the sequence of Bacillus anthracis vaccine strain CVCC40205 registered in GenBank, the plyL gene was amplified by PCR with plyL gene-specific primers and inserted into the prokaryotic expression vector pET28a(+) to construct the recombinant expression plasmid pET28a(+)-His-plyL, which was then transformed into E.coli BL21(DE3) and induced by IPTG. The induced expression conditions were optimized to enhance soluble expression, and the recombinant PlyL protein was purified via nickel-affinity chromatography. The lytic activity of recombinant PlyL protein was assessed by measuring absorbance values, and an ELISA method was established to evaluate the sensitivity and specificity of Bacillus anthracis detection.ResultsThe recombinant expression plasmid pET28a(+)-His-plyL was confirmed to be correctly constructed by NdeⅠ and XhoⅠ double digestion and sequencing. The optimal induction conditions were 0. 5 mmol/L IPTG at 16 ℃ for 16 h. The relative molecular mass of the expressed recombinant PlyL protein was about 28 600. After purification and concentration, the final concentration of the protein was2. 55 mg/mL, and the purity reached 80. 6%. The purified recombinant PlyL protein could reduce the A_(600)value of Bacillus anthracis culture solution. The sensitivity of the preliminarily established ELISA method for detecting Bacillus anthracis was1 × 10~3 CFU/mL, and there was no cross-reactivity against closely related strains such as Bacillus cereus and Bacillus thuringiensis(P < 0. 000 1).ConclusionThe recombinant PlyL protein was successfully expressed and purified in prokaryotic cells, which exhibits both efficient lytic activity and species specificity, making it a promising novel tool for the rapid detection of Bacillus anthracis.

The thymus is a key organ for T-cell development and the establishment of central immune tolerance. Research on immune function changes and long-term health risks following thymectomy is characterized by significant population heterogeneity and controversial conclusions. This article systematically reviews the key immunological alterations after thymectomy - including reduced T-cell receptor (TCR) repertoire diversity, regulatory T cell (Treg) dysfunction, accelerated immune aging, and compensatory immune responses, and clarifies population differences in postoperative risks of infection, autoimmune diseases, and tumors, as well as the impact of surgical approaches. The clinical outcome after thymectomy is not solely determined by thymus loss, but rather depends on a dynamic balance between "immune deficiency risk" and "host compensatory capacity," which is modulated by multiple factors such as age at surgery, extent of resection, and individual immune status. This review proposes a "risk-compensation balance model" framework, providing an integrated theoretical basis for explaining the heterogeneity in outcomes across different populations and surgical methods. It also holds significant implications for future efforts in individualized surgical decision-making, establishment of stratified immune monitoring systems, and exploration of targeted immune intervention strategies.

Objective: To explore the intervention effects of different exercise modalities on executive function in school aged children, providing references for formulating exercise prescriptions to promote school aged children executive function. Methods: A systematic literature search was conducted using PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP and CBM to identify studies on the effects of exercises on executive function in school aged children. The search period spanned from the database inception to August 2025. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias of the included studies. Network Meta analysis was performed using Stata 16.0. Results: A total of 51 studies involving 5 710 school aged children and seven modalities of exercises(control group,small ball sports,large ball sports,aerobic exercise,combined exercise,sport game,gymnastic and dance sports) were finally included. Network Meta analysis showed that, in terms of inhibitory control development of school aged children, small ball sports ( SMD =-0.98,95% CI =-1.32 to -0.64 ), large ball sports ( SMD =-0.64,95% CI =-0.91 to -0.36), and mixed sports ( SMD =-0.26,95% CI =-0.50 to -0.02]) were more effective than the control group; in terms of working memory, largeball sports ( SMD =-1.26,95% CI =-1.88 to -0.65) and small ball sports ( SMD =-0.91,95% CI =-1.64 to -0.19) were superior to the control group; in terms of improving cognitive flexibility, large ball sports ( SMD =-1.02,95% CI =-1.28 to -0.76), gymnastics and dance sports ( SMD =-0.80,95% CI =-1.21 to -0.40), and small ball sports ( SMD =-0.75,95% CI =-1.15 to -0.36) were more effective than the control group (all P <0.05). Surface under cumulative ranking curve(SUCRA) showed that small ball sports had the highest value (SUCRA=98.9%) in improving inhibitory control, while large ball sports achieved the highest score(SUCRA=92.6%) in enhancing working memory, and large ball sports also had the highest value(SUCRA=94.7%) in promoting cognitive flexibility. Conclusions For developing inhibitory control in school aged children, small ball sports are recommended as a priority. For enhancing working memory and cognitive flexibility, large ball sports are recommended.

Objective To systematically analyze the characteristics of the disease burden of hypertensive heart disease (HHD) in the elderly (≥60 years) globally and in China from 1990 to 2021, and to predict its future trends from 2022 to 2040, with the aim of providing data support for optimizing comprehensive prevention and control strategies for HHD. Methods Based on the Global Burden of Disease (GBD) 2021 database, the number of prevalent cases and disability-adjusted life years (DALYs) of HHD in the elderly were extracted for the world, China, and five regions categorized by sociodemographic index (SDI). Joinpoint regression was used to analyze the temporal trends of age-standardized prevalence rate and age-standardized DALYs rate of HHD in the elderly. A three-factor decomposition method was applied to evaluate the relative contributions of aging, population growth, and epidemiological changes to the variations in the elderly HHD burden. Additionally, a Bayesian age-period-cohort model was used to predict the elderly HHD burden from 2022 to 2040. Results In 2021, the number of prevalent elderly HHD cases reached 10 283 000 globally and 3 412 400 in China, representing increases of 179.20% and 159.20% respectively, compared with 1990. The DALYs of elderly HHD were 18 812 700 person-years globally and 4 731 400 person-years in China, rising by 76.08% and 29.45% respectively from 1990. Meanwhile, the growth rates of the number of prevalent cases and DALYs of elderly HHD varied across different SDI regions. From 1990 to 2021, the age-standardized prevalence rate of elderly HHD in China, as well as the age-standardized DALYs rate of elderly HHD both globally and in China, showed significant downward trends (all average annual percentage changes<0, all P<0.001). In 2021, the 70-74 years age group accounted for the highest proportion of prevalent cases and DALYs of elderly HHD, both globally and in China. Decomposition analysis revealed that population growth was the dominant factor driving the increase in the elderly HHD burden across all regions. The prediction model results indicated that the number of prevalent cases and DALYs of elderly HHD would continue to rise globally and in China from 2022 to 2040, with the growth rate of the elderly HHD burden in China between 2021 and 2040 expected to exceed the global average. Conclusion Over the past 32 years, although the age-standardized disease rates of elderly HHD have mainly shown a downward trend globally and in China, the absolute number of the disease burden has increased substantially. The projection model indicates a continued upward trajectory, with the growth rate in China higher than the global average. Therefore, there is an urgent need to implement precise prevention and control strategies to effectively mitigate the disease burden of elderly HHD.

Objective: To understand the epidemiological characteristics of a pertussis outbreak in Guangzhou, so as to provide references for outbreak response and prevention strategies. Methods: From April 5 to June 9, 2024, case screening was conducted among 246 preschool children, 35 staff members, and one full time school nurse in a kindergarten in Guangzhou based on case definition. Field epidemiological investigation methods were employed to collect relevant information, and screening samples were collected from individuals involved in the outbreak. The clinical manifestations, epidemiological characteristics, and risk factors for transmission of the outbreak were analyzed, with rate comparisons performed using the χ 2 test. Results: There were a total of 15 confirmed cases of pertussis in the kindergarten. The main clinical manifestations included intermittent cough in 14 cases ( 93.33 %), sputum production in 5 cases (33.33%), fever in 2 cases (13.33%), paroxysmal spasmodic cough in 1 case (6.67%), and vomiting in 1 case (6.67%). There was no statistically significant difference in the reporting rates of interrupted cough symptoms between pertussis cases (93.33%) and non pertussis cases (92.86%)( χ 2=3.74, P >0.05). The cases were aged 4-5 years, including 5 males and 10 females. The interval between symptom onset and diagnosis ranged from 2 to 25 days, with a median of 10 days. The outbreak involved two classes, with attack rates of 48.28% and 3.45%, respectively. Laboratory testing confirmed 14 close contacts positive for Bordetella pertussisnucleic acid. Among close contacts, only one received prophylactic medication as required. Conclusion The outbreak is a pertussis outbreak in a kindergarten caused by Bordetella pertussis infection, demonstrating distinct temporal and spatial clustering characteristics.

Objective To compare the clinical outcomes of subxiphoid robot-assisted thoracoscopic surgery (SRATS) and intercostal robot-assisted thoracoscopic surgery (IRATS) in the treatment of anterior mediastinal tumors. Methods A retrospective analysis was conducted on patients with anterior mediastinal tumors who underwent robot-assisted surgery in the Department of Thoracic Surgery, Gansu Provincial Hospital, from May 2020 to July 2022. According to the surgical approach, patients were divided into an SRATS group and an IRATS group. Perioperative data were compared between the two groups. Results A total of 87 patients were included. There were 41 patients in the SRATS group [23 males, 18 females; mean age, (44.51±11.28) years] and 46 patients in the IRATS group [21 males, 25 females; mean age, (46.67±8.76) years]. Compared with the IRATS group, the SRATS group had significantly less intraoperative blood loss [(24.41±6.67) mL vs. (37.93±9.23) mL, P<0.001], shorter postoperative drainage duration [(1.73±0.59) days vs. (2.54±0.50) days, P<0.001], lower postoperative drainage volume [(94.46±34.08) mLvs. (116.72±24.90) mL, P=0.001], lower visual analogue scale (VAS) pain scores on postoperative day 1 [(3.66±0.76) points vs. (4.15±0.84) points, P=0.005] and day 3 [(2.41±0.59) points vs. (2.89±0.82) points, P=0.003], shorter postoperative hospital stay [(4.12±0.81) days vs. (4.98±1.02) days, P<0.001], and lower hospitalization costs [(4.51±0.65) ten thousand yuan vs. (4.86±0.68) ten thousand yuan, P=0.020]. There were no statistical differences between the two groups in operative time or incidence of postoperative complications (P>0.05). Conclusion Both SRATS and IRATS are safe and effective for the treatment of anterior mediastinal tumors. However, SRATS is less invasive and more conducive to enhanced postoperative recovery.

Objective To evaluate the impact of an integrated management mode of prenatal diagnosis-postnatal treatment for congenital heart disease (CHD) on perioperative and long-term outcomes of the arterial switch operation (ASO), and to analyze the efficacy of ASO in a single center. Methods This retrospective study analyzed the clinical data of 183 children who underwent ASO at Guangdong Provincial People’s Hospital from 2018 to 2024. The cohort included 106 (57.9%) patients of transposition of the great arteries with intact ventricular septum (TGA/IVS), 61 (33.3%) patients of transposition of the great arteries with ventricular septal defect (TGA/VSD), and 16 (8.7%) patients of Taussig-bing anomaly (TBA). Perioperative indicators were compared between 91 patients in the prenatal-postnatal integrated management group (an integrated group) and 92 patients in the traditional management group (a non-integrated group). Long-term survival and reoperation rates were analyzed using Kaplan-Meier curves. Results The overall perioperative mortality rate was 4.9% (9/183), showing a downward trend year by year. The primary cause of perioperative mortality was low cardiac output syndrome (LCOS), which occurred in 12 patients (6.6% incidence) with a mortality rate of 75.0%. The integrated group had a higher proportion of males (89.0% vs. 72.8%, P<0.05) and lower body weight [3.1 (2.7, 3.3) kg vs. 3.3 (3.0, 3.7) kg, P<0.05] compared to the non-integrated group. The age at surgery was significantly earlier in the integrated group [7 (3, 10) d vs. 14 (9, 48) d, P<0.05], and all children in the integrated group underwent ASO within the optimal surgical window (100.0% vs. 82.6%, P<0.05). Intraoperatively, cardiopulmonary bypass time [173 (150, 207) min vs. 186 (159, 237) min, P<0.05] and aortic cross-clamp time [100 (90, 117) min vs. 116 (97, 142) min, P<0.05] were significantly shorter in the integrated group. Although the integrated group had longer postoperative mechanical ventilation time [145 (98, 214) h vs. 116 (77, 147) h, P<0.05] and higher 48-hour maximum vasoactive inotropic score [15 (10, 21) points vs. 12 (8, 16) points, P<0.05], there was no statistically significant difference in the incidence of severe complications (LCOS, necrotizing enterocolitis, extracorporeal membrane oxygenation) or mortality rate (3.3% vs. 6.5%, P=0.51) between the two groups, despite earlier surgical intervention and a higher proportion of critically ill cases in the integrated group. The length of hospital stay in the emergency surgery group was significantly shorter than that in the elective surgery group [20 (15, 28) d vs. 25 (21, 30) d, P<0.05], suggesting that early surgery may be of potential benefit. A total of 163 patients were successfully followed up for a median of 4.7 years, with a 5-year survival rate of 95.1% and a freedom from reintervention survival rate of 95.1%. There were no late deaths, and the most common postoperative complication was pulmonary artery stenosis. Conclusion The integrated management model allowed critically ill children with lower body weights to safely undergo surgery, significantly optimizing the timing of surgery and shortening intraoperative times. The long-term risk of reoperation after ASO is primarily concentrated on pulmonary artery stenosis, necessitating long-term follow-up and monitoring.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.