ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

The Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use （T/CACM 1563.5—2024）， the first guideline in China specializing for the clinical safety of Chinese patent medicines for external use， was led by the Institute of Basic Research in Clinical Medicine，China Academy of Chinese Medical Sciences，and jointly developed by more than 30 research institutions of medical sciences across the country. Aiming to standardize the pharmacovigilance activities in the clinical application of Chinese patent medicines for external use，the guideline systematically categorizes potential risks and proposes prevention and control measures that cover 11 core sections of risk monitoring and reporting， signal identification，as well as assessment and control， addressing the gap in domestic and international standardization of this field. The compilation of this guideline strictly adhered to international norms and domestic regulations， involving multiple rounds of expert consultations，hybrid interviews， and evidence integration （covering literature，medical insurance，essential medicine，pharmacopoeia data， and regulatory information）. With the scope of application defined to include medical institutions， pharmaceutical manufacturers and distribution enterprises，as well as regulatory authorities， the guideline focuses on key issues such as inherent medicine risks，quality risks，off-label use，risks of combination therapy，and the safety in special populations. During the compilation，core discrepancies such as the definition of application scope and quality risk control were addressed to ensure alignment with regulations such as the Drug Administration Law of the People's Republic of China and the Good Pharmacovigilance Practice. The guideline is registered internationally （PREPARE—2022CN463）. In the future，the implementation of the guideline will be promoted through hierarchical dissemination，dynamic revision，and post-effectiveness evaluation， contributing to rational clinical use and improved patient safety.

Polycystic ovary syndrome （PCOS） is a common endocrine and metabolic disorder among women of reproductive age. Hyperandrogenism （HA）， one of its core pathological features， is closely associated with the clinical manifestations and metabolic complications of the disease. Current western medical treatments for PCOS-HA mainly include anti-androgen therapy and ovulation induction， such as short-acting oral contraceptives like Diane-35 and Yasmin. However， long-term use of these medications may result in adverse reactions like increasing the risk of liver dysfunction and exacerbating lipid metabolism disorders， with unsatisfactory long-term efficacy when used alone. Traditional Chinese medicine offers unique advantages in the treatment of PCOS-HA due to its holistic approach and multi-target regulatory mechanisms. In the view of traditional Chinese medicine， PCOS-HA is classified under the categories such as "delayed menstruation"， "amenorrhea"， and "infertility"， with kidney deficiency as the root， as well as liver stagnation and spleen deficiency as the manifestations. Phlegm and blood stasis are considered to be intertwined throughout the disease course. Modern studies have shown that traditional Chinese medicine is significantly effective in improving the androgen levels， restoring ovulation， and improving insulin resistance in PCOS-HA patients. Representative prescriptions， such as Erxian Tang， Jiawei Xiaoyaosan， Guizhi Fulingwan， and Cangfu Daotantang， exert therapeutic effects through various mechanisms including regulation of the hypothalamic-pituitary-ovarian axis， reduction of ovarian androgen synthase activity， improvement of insulin signaling pathways， and inhibition of inflammation and oxidative stress， which demonstrates the characteristics of comprehensive treatment with traditional Chinese medicine. Based on the perspectives of etiology and pathogenesis of traditional Chinese medicine， modern medical cognition， typical prescriptions， and action mechanisms， this paper reviewed the research progress of traditional Chinese medicine in the treatment of PCOS-HA， aiming to provide a reference for in-depth research and clinical applications in this field.

Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

Objective: To analyze the current burden of autism spectrum disorder (ASD) among children and adolescents in China and globally, and to predict the disease burden from 2024 to 2035, providing a scientific basis for formulating relevant public health policies and intervention measures. Methods: Based on the Global Burden of Disease (GBD) database in 2023, the Joinpoint regression model was used to analyze the changing trends of the disease burden of ASD among children and adolescents in China and globally from 1990 to 2023, and the average annual percent change (AAPC) was calculated. An autoregressive integrated moving average (ARIMA) model was constructed to predict the disease burden trends of ASD among children and adolescents in China and globally from 2024 to 2035. Results: The prevalence and disability adjusted life years (DALYs) rate of ASD among children and adolescents in China increased from 452.69/100 000 and 86.67/100 000 in 1990 to 762.84/100 000 and 148.52/ 100 000 in 2023(AAPC=1.60%, 1.65%, both P <0.01). The prevalence and DALYs rate of ASD among children and adolescents globally increased from 648.49/100 000 and 123.47/100 000 to 862.44/100 000 and 167.16/100 000(AAPC=0.87%, 0.93%, both P <0.01). In 2023, the highest ASD prevalence and DALY rates occurred in children under 5 years old, with China reporting 848.14/100 000 and 166.69/100 000, both below the global averages of 928.80/100 000 and 181.34/100 000. Projections indicated that by 2035, the ASD prevalence and DALY rates in China would rise to 906.83/100 000 and 168.71/100 000, still below the global averages of 938.04/100 000 and 184.49/100 000. Conclusion The disease burden of ASD among children and adolescents in China and globally has generally increased from 1990 to 2023, with a higher risk of disease at younger ages.

Abstract To explore the benefits and risks of active video games (AVGs) for health promotion among children and adolescents, the study reviews relevant domestic and international literature and details the benefits of AVGs, including increased physical activity and energy expenditure, improved physical fitness, better mental health, enhanced social interaction, improved cognitive function and attention, and heightened body awareness. At the same time, it also addresses potential risks, such as gaming addiction and excessive use, sports related injuries and other risks, thereby providing a theoretical reference for children and adolescents to engage in AVGs in a healthy manner.

Objective To explore whether there is a causal relationship between intestinal flora and esophageal cancer. Methods Summary statistics of intestinal flora and esophageal cancer were obtained from the Genome-wide Association Studies (GWAS) database. Five methods, including inverse variance weighted (IVW), weighted median estimation, Mendelian randomization (MR)-Egger regression, single mode, and weighted mode, were used for analysis, with IVW as the main analysis method. Sensitivity analysis was used to evaluate the reliability of MR results. Results In the IVW method, Oxalobacteraceae [OR=1.001, 95%CI (1.000, 1.002), P=0.023], Faecalibacterium [OR=1.001, 95%CI (1.000, 1.002), P=0.028], Senegalimassilia [OR=1.002, 95%CI (1.000, 1.003), P=0.006] and Veillonella [OR=1.001, 95%CI (1.000, 1.002), P=0.018] were positively correlated with esophageal cancer, while Burkholderiales [OR=0.999, 95%CI (0.998, 1.000), P=0.002], Eubacterium oxidoreducens [OR=0.998, 95%CI (0.997, 0.999), P=0.038], Romboutsia [OR=0.999, 95%CI (0.998, 1.000), P=0.048] and Turicibacter [OR=0.998, 95%CI (0.997, 0.999), P=0.013] were negatively correlated with esophageal cancer. Sensitivity analysis showed no evidence of heterogeneity, horizontal pleiotropy and reverse causality. Conclusion Oxalobacteraceae, Faecalibacterium, Senegalimassilia and Veillonella increase the risk of esophageal cancer, while Burkholderiales, Eubacterium oxidoreducens, Romboutsia and Turicibacter decrease the risk of esophageal cancer. Further studies are needed to explore how these bacteria affect the progression of esophageal cancer.

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.

A portion of patients undergoing implant restoration require bone augmentation procedures to ensure that there is sufficient bone volume around the implant. For the patients with horizontal bone ridge defects at edentulous sites, with or without mild to moderate vertical bone defects, the shell technique serves as a reliable and minimally invasive bone augmentation method with effective space maintenance. The shell technique involves fixating 1 mm cortical bone blocks to the recipient site, using retention screws and filling the gap between the bone block and recipient bed with particulate bone substitute materials, and covering the barrier membrane to achieve bone augmentation. The overlying tension-free soft tissue closure seals the surgical site while local peripheral blood releases osteoclasts and cytokines that gradually degrade the bone block. The rigid fixation of the bone block ensures a stable internal environment for osteogenesis and a new bone regeneration cycle. Although this technique demonstrates favorable bone augmentation outcomes, it is highly technique-sensitive. There are certain differences in the application scenarios and osteogenic processes for autologous and allogeneic bone shells. The selection of bone blocks and particulate bone substitute materials significantly influences the osteogenic biological process and the predictability of bone augmentation results. Complications associated with the shell technique possess distinct characteristics, such as the immunogenicity of allogeneic bone fragments, soft tissue cracking, and bone fragment loosening. Their prevention and subsequent management substantially impact the success rate of osteogenesis. This article delves into the biological mechanisms of osteogenesis in the bone block technique, summarizing the indications, clinical outcomes, classification of bone blocks, and surgical workflow management, as well as complication prevention and management, aiming to provide a reference for the future application and development of the bone shell technique.

Objective: To explore the latent profile characteristics of regulatory emotional self-efficacy and its relationship with non-suicidal self-injurious (NSSI) behavior among junior and senior high school students, so as to provide a basis for effectively reducing NSSI behaviors. Methods: From April to October 2023, a total of 1 217 junior and senior high school students were selected from Tongren City, Zunyi City and Qiannan Prefecture of Guizhou Province by stratified cluster random sampling method. The Scale of Regulatory Emotional Self-efficacy and the Adolescent Self-injury Scale were administered. Latent profile analysis (LPA) was employed to explore distinct profiles of regulatory emotional self-efficacy, and the Lanza, Tan, and Bray s method (LTB) was used to analyze the relationship between these profiles and NSSI behavior. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 28.6%. Among males, regulatory emotional self-efficacy was categorized into two types: moderate positive expression-low negative management group (59.1%, n =353) and high efficacy group (40.9%, n =244); among females, regulatory emotional self-efficacy was classified into three categories: low efficacy group (18.4%, n =114), high positive expression-low negative management group (56.3%, n =349), and high efficacy group (25.3%, n =157). There were statistically significant differences in total NSSI scores across different potential categories of regulatory emotional self-efficacy within both males and females ( Z/H = -5.75 , 57.58, both P <0.01). The differences in NSSI prevalence rates across the potential categories of regulatory emotional self-efficacy were statistically significant for both males and females ( χ 2=38.00, 69.14, both P <0.01), and among females, the differences in NSSI prevalence rates between the high efficacy group and the low efficacy group ( χ 2=60.01) and between the high efficacy group and the high positive expression-low negative management group ( χ 2=31.34) were also statistically significant (both P < 0.016 7 ). Binary Logistic regression analysis revealed that, compared with the high efficacy group within each gender, the moderate positive expression-low negative management group among males ( OR =2.36), and both the low efficacy group and the high positive expression-low negative management group among females ( OR =6.19, 2.97), were at an increased risk of engaging in NSSI (all P <0.01). Conclusion Different latent profiles of regulatory emotional self efficacy among junior and senior high school students are associated with NSSI behavior.