ObjectiveTo investigate the optimal termination time for acupuncture in treating patients with acute peripheral facial paralysis and its cost-effectiveness. MethodsA total of 120 eligible patients with acute-stage peri-pheral facial paralysis were randomly assigned to either the mild dysfunction termination group and the complete recovery termination group， with 60 patients in each group. Both groups received the standard acupuncture treatment protocol. Treatment in the mild dysfunction termination group was terminated when the Sunnybrook facial grade scale （SFGS） score first reached or exceeded 83 points， while that in the complete recovery termination group was terminated when the SFGS score first reached or exceeded 95 points. Assessments were conducted before treatment， 6 and 12 months after onset. SFGS， facial disability index （FDI） including physical function （FDIp） and social function （FDIs）， self-rating anxiety scale （SAS）， and self-rating depression scale （SDS） scores were assessed before treatment， and 6 and 12 months after onset. Any acupuncture-related adverse events during treatment were recorded for safety evaluation. Treatment sessions and medical costs including direct costs， indirect costs， insurance coverage， total societal costs， and patient out-of-pocket expenses were also recorded， and an economic evaluation was conducted including cost-effectiveness ratio （CER） and incremental cost-effectiveness ratio （ICER）. ResultsUltimately， 56 patients in the mild dysfunction termination group and 55 in the complete recovery termination group completed the follow-up. At 6 and 12 months after onset， SFGS and FDIp scores in both groups improved significantly while FDIs， SAS and SDS scores decreased （P＜0.05）. Comparison of scores between groups 6 months and 12 months after onset showed no statistically significant differences （P＞0.05）. During the trial， the incidence of adverse events was 13.3% （8/60） in the mild dysfunction termination group and 18.3% （11/60） in the complete recovery termination group， with no statistically significant difference （P＞0.05）. The number of treatment sessions， total social costs， and out-of-pocket expenses in the mild dysfunction termination group were significantly lower than those in the complete recovery termination group （P＜0.05）. The CER of the mild dysfunction termination group in SFGS， FDIp， FDIs， SAS， and SDS scores was lower than that of the complete recovery termination group. The ICER analysis showed that continuing treatment until full recovery incurred an additional cost of 573.30 CNY/point in SFGS improvement， whereas 1-point improvement in FDIp， FDIs， SAS， and SDS required 21,355.25 CNY， 1779.60 CNY， 3713.96 CNY， and 2755.52 CNY， respectively. ConclusionFor acupuncture in treating acute peripheral facial palsy， terminating treatment when mild dysfunction is achieved yields long-term efficacy comparable to that of continuing treatment until complete recovery， while significantly reducing medical costs and socioeconomic burden.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

A natural experiment is a causal inference study design grounded in real-world research. Its core concept is to use quasi-random variation in exposure generated by external factors to evaluate the effects of interventions or exposures on outcomes. It is particularly suitable for research settings in which randomized controlled trials （RCTs） are infeasible or ethically constrained， and it combines causal inference capacity with relatively strong external validity. This article provides an overview of the definition， key features， and current application status of natural experiments， and proposes the application scenarios for applying natural experiment strategies to the evaluation of therapeutic effects in traditional Chinese medicine （TCM）， including policy implementation or policy change evaluation， assessment of variations in clinical practice within hospitals， and evaluation of differences in resource allocation across regions or institutions. The design pathway includes starting from clinical or policy-related TCM questions， systematically collecting relevant data， performing statistical modeling and effect estimation， and interpreting effect estimates in the context of clinical practice. It further analyzes the advantages and challenges of using natural experiments in TCM.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

A natural experiment is a causal inference study design grounded in real-world research. Its core concept is to use quasi-random variation in exposure generated by external factors to evaluate the effects of interventions or exposures on outcomes. It is particularly suitable for research settings in which randomized controlled trials （RCTs） are infeasible or ethically constrained， and it combines causal inference capacity with relatively strong external validity. This article provides an overview of the definition， key features， and current application status of natural experiments， and proposes the application scenarios for applying natural experiment strategies to the evaluation of therapeutic effects in traditional Chinese medicine （TCM）， including policy implementation or policy change evaluation， assessment of variations in clinical practice within hospitals， and evaluation of differences in resource allocation across regions or institutions. The design pathway includes starting from clinical or policy-related TCM questions， systematically collecting relevant data， performing statistical modeling and effect estimation， and interpreting effect estimates in the context of clinical practice. It further analyzes the advantages and challenges of using natural experiments in TCM.

OBJECTIVES: To explore the mechanism of Pingchuanning Formula (PCN) for inhibiting airway inflammation in rats with asthmatic cold syndrome. METHODS: A total of 105 SD rats were randomized equally into 7 groups, including a control group, an asthmatic cold syndrome model group, 3 PCN treatment groups at high, medium and low doses, a Guilong Kechuanning (GLCKN) treatment group, and a dexamethasone (DEX) treatment group. In all but the control rats, asthma cold syndrome models were established and daily gavage of saline, PCN, GLCKN or DEX was administered 29 days after the start of modeling. The changes in general condition, lung function and lung histopathology of the rats were observed, and inflammatory factors in the alveolar lavage fluid (BALF), oxidative stress, lung tissue ultrastructure, cytokine levels, and expressions of the genes related to the HMGB1/Beclin-1 axis and autophagy were analyzed. RESULTS: The rat models had obvious manifestations of asthmatic cold syndrome with significantly decreased body mass, food intake, and water intake, reduced FEV_0.3, FVC, and FEV_0.3/FVC, obvious inflammatory cell infiltration in the lung tissue, and increased alveolar inflammation score and counts of neutrophils, eosinophils, lymphocytes, macrophages, and leukocytes in the BALF. The rat models also had significantly increased MDA level and decreased SOD level and exhibited obvious ultrastructural changes in the lung tissues, where the expressions of HMGB1, Beclin-1, ATG5, TNF-α, IL-6,IL-1β, and IL-13 and the LC3II/I ratio were increased, while the levels of Bcl-2 and IFN-γ were decreased. PCN treatment significantly improved these pathological changes in the rat models, and its therapeutic effect was better than that of GLKCN and similar to that of DEX. CONCLUSIONS PCN can effectively alleviate airway inflammation in rat models of asthmatic cold syndrome possibly by modulating the HMGB1/Beclin-1 signaling axis to suppress cell autophagy, thereby attenuating airway inflammatory damages.
Animals ; Rats ; Autophagy/drug effects* ; Rats, Sprague-Dawley ; Asthma/pathology* ; Beclin-1 ; HMGB1 Protein/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Male ; Lung/pathology* ; Inflammation

Diabetic cardiomyopathy (DCM) is a medical condition characterized by cardiac remodeling and dysfunction in individuals with diabetes mellitus. Sarcoplasmic reticulum (SR) and mitochondrial Ca²⁺ overload in cardiomyocytes have been recognized as biological hallmarks in DCM; however, the specific factors underlying these abnormalities remain largely unknown. In this study, we aimed to investigate the role of a cardiac-specific long noncoding RNA, D830005E20Rik (Trdn-as), in DCM. Our results revealed the remarkably upregulation of Trdn-as in the hearts of the DCM mice and cardiomyocytes treated with high glucose (HG). Knocking down Trdn-as in cardiac tissues significantly improved cardiac dysfunction and remodeling in the DCM mice. Conversely, Trdn-as overexpression resulted in cardiac damage resembling that observed in the DCM mice. At the cellular level, Trdn-as induced Ca²⁺ overload in the SR and mitochondria, leading to mitochondrial dysfunction. RNA-seq and bioinformatics analyses identified calsequestrin 2 (Casq2), a primary calcium-binding protein in the junctional SR, as a potential target of Trdn-as. Further investigations revealed that Trdn-as facilitated the recruitment of METTL14 to the Casq2 mRNA, thereby enhancing the m⁶A modification of Casq2. This modification increased the stability of Casq2 mRNA and subsequently led to increased protein expression. When Casq2 was knocked down, the promoting effects of Trdn-as on Ca²⁺ overload and mitochondrial damage were mitigated. These findings provide valuable insights into the pathogenesis of DCM and suggest Trdn-as as a potential therapeutic target for this condition.
Animals ; Diabetic Cardiomyopathies/pathology* ; RNA, Long Noncoding/genetics* ; Myocytes, Cardiac/metabolism* ; Mice ; Calsequestrin/genetics* ; Calcium/metabolism* ; Male ; Sarcoplasmic Reticulum/metabolism* ; Methyltransferases/metabolism* ; Mice, Inbred C57BL ; Mitochondria, Heart/metabolism* ; Disease Models, Animal ; Mitochondria/metabolism*

Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and gouty arthritis (GA), is a prevalent inflammatory disease that significantly impacts quality of life. Natural products (NPs), derived from animals, plants, marine organisms, and microorganisms, have demonstrated beneficial effects in arthritis treatment both domestically and internationally. These natural compounds offer advantages in drug discovery due to their skeletal diversity, structural complexity, and multi-effect, multi-target, and low-toxicity properties compared to conventional small-molecule medicines. However, unclear mechanisms have hindered the development and clinical application of NPs. This review summarizes recent experimental studies from the past decade on natural medicine for arthritis treatment, emphasizing key NPs with therapeutic effects on OA, RA, and GA. It examines the effects and molecular mechanisms of NPs acting on different cells to treat arthritis. Furthermore, this review provides insights into the future prospects of NP research in this field, which is crucial for advancing NP-based arthritis treatments.
Humans ; Biological Products/therapeutic use* ; Animals ; Arthritis, Rheumatoid/drug therapy* ; Arthritis, Gouty/drug therapy* ; Arthritis/drug therapy* ; Osteoarthritis/drug therapy*