ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

ObjectiveTo investigate the role of Ras-GTPase-activating protein SH3 domain-binding protein 2 （G3BP2） in regulating the activation， proliferation， and migration of hepatic stellate cells （HSCs）. MethodsThe mouse HSCs （JS-1 cell line） were treated with 5 μg/L transforming growth factor-beta 1（TGF-β1） for 24 hours to establish an HSC activation and proliferation model. A G3BP2 knockdown system was constructed using siRNA interference technology. The experiment was divided into four groups： Control， TGF-β1 treatment， TGF-β1+si-NC， and TGF-β1+ G3BP2-siRNA. The expression levels of key fibrosis indicators， including type I collagen （Collagen I）， α-smooth muscle actin （α-SMA）， and G3BP2， were detected by Western blot and RT-qPCR. Cell proliferation activity was assessed using the CCK-8 proliferation assay kit and EdU fluorescence labeling technology. Cell migration ability was analyzed by scratch wound healing assay and Transwell migration assay. The formation level of stress granules was quantified by immunofluorescence microscopy to investigate the effects of G3BP2 on stress granule formation in activated HSCs. ResultsStimulation with TGF-β1 upregulated the expression of G3BP2 in JS-1 cells （RT-qPCR： P0.000 1； Western blot： P0.000 1）， while a downward trend in its expression was observed in the G3BP2‑silenced group （RT-qPCR： P0.01； Western blot： P0.000 1）. Compared with the control group， the TGF-β1 group exhibited increased protein expression levels of α-SMA and Collagen I （RT-qPCR： both P0.01； Western blot： P0.01 and P0.05， respectively）， concomitant with an increased number of stress granules and enhanced cell proliferation and migration capacity （all P0.001）. The experimental results demonstrated that G3BP2 knockout effectively reversed the aforementioned phenotypes， with the G3BP2-silenced group showing reduced expression of fibrotic markers （all P0.01）， decreased stress granule formation （P0.01）， and reduced cell proliferation and migration capacity （all P0.05）， compared to the negative control group. ConclusionG3BP2 enhances the activation， proliferation， and migration of HSCs by promoting the formation of stress granules， thereby accelerating the pathological progression of liver fibrosis. This suggests that stress granules may serve as important regulators in controlling the activation， proliferation， and migration of HSCs.

ObjectiveTo investigate the role of interleukin （IL）-17A in acute inhalational pneumonia induced by the highly drug-resistant and hypervirulent Staphylococcus aureus strain USA300-R in mice. MethodsAn acute inhalational pneumonia model was established in mice using an aerosolized pulmonary delivery technique. RNA sequencing （RNA-seq） and enzyme-linked immunosorbent assay （ELISA） were employed to examine the expression dynamics of Il17a mRNA and IL-17A protein， respectively， in the lungs of infected mice. Il17a knockout （Il17a^-/-） mice were generated using CRISPR/Cas9 gene editing technology. The survival rate， body weight， bacterial load in lung tissue， and histopathological changes were compared between Il17a^-/- and wild-type （WT） mice following inhalational infection with USA300-R. Results12 hours after USA300-R infection， compared to pre-infection， the expression level of Il17a mRNA in lung tissue and the level of IL-17A protein in bronchoalveolar lavage fluid （BALF） increased by approximately 50-fold （P<0.01） and 6-fold （P<0.001）， respectively. Compared to WT mice， Il17a^-/- mice exhibited approximately 10-fold higher bacterial loads in lung tissue at both 12 and 24 hours post-infection （P<0.001， P<0.05）. However， they showed significantly attenuated lung histopathological injury， reduced alveolar wall thickening， markedly decreased neutrophil infiltration， and an approximately 50% improvement in survival rate （P<0.05）. ConclusionIn acute Staphylococcus aureus USA300-R inhalational pneumonia， IL-17A contributes to bacterial clearance by recruiting neutrophils； however， excessive neutrophil infiltration exacerbates pulmonary inflammation and injury， reduces survival rates， and represents a potential therapeutic target.

BACKGROUND:Exosomes derived from mesenchymal stem cells play pivotal roles in cell communication and epigenetic regulation due to their low immunogenicity and targeted delivery effects,and have been clinically applied in the treatment of various diseases.OBJECTIVE:To review the isolation,purification,identification methods,and application progress of mesenchymal stem cell-derived exosomes,and to facilitate the development of large-scale preparation techniques and clinical translation of mesenchymal stem cell-derived exosomes.METHODS:The Chinese search terms"exosome,mesenchymal stem cells,isolation,purification,characterization,clinical application"and the English search terms"exosome,extracellular vesicles,mesenchymal stem cells,isolation,characterization,application"were used to search the literature published before September 2024 in CNKI,PubMed,and Web of Science databases.Articles with poor relevance to the topic,outdated,or duplicated content were excluded,and finally,109 articles were included for review.RESULTS AND CONCLUSION:(1)This paper reviews recent methods for isolating and purifying exosomes,comparing the characteristics of ultracentrifugation,ultrafiltration,size-exclusion chromatography,polymer precipitation,immunoaffinity,microfluidic methods,and other novel approaches based on their underlying principles.(2)Methods for identifying exosomes can be categorized into physical and biochemical analyses,characterizing exosomes based on their shape,size,and characteristic proteins.(3)Mesenchymal stem cell-derived exosomes have broad applications in multiple fields such as medical aesthetics,wound repair,and cancer treatment,due to their immune-regulatory properties and ability to cross biological barriers.(4)The clinical translation of exosomes faces challenges due to their complex structure,lack of universal isolation techniques,and poor stability,making it difficult to achieve in a short period of time.

Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.

Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.

Objective To systematically analyze the spatiotemporal distribution characteristics and epidemiological trends of tracheal, bronchus, and lung cancer (TBL) disease burden attributed to air pollution globally and in China and the United States from 1990 to 2021, and to assess the patterns of disease burden changes from 2022 to 2031 based on predictive models, providing a scientific basis for formulating targeted TBL prevention and control strategies. Methods Based on the Global Burden of Disease (GBD) 2021 database, we analyzed the disease burden data of TBL attributed to air pollution globally and in China and the United States from 1990 to 2021. R Studio 4.3.2 software was used to analyze the corresponding trends and the Bayesian age-period-cohort (BAPC) prediction model was used to predict the status of the disease burden of TBL attributed to air pollution in the world and in China and the United States from 2022 to 2031. Results In 2021, China had the highest number of deaths and disability-adjusted life years attributed to air pollution (211 400 patients and 4.8947 million person-years), followed by the United States (6 000 patients and 124 300 person-years). The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) of TBL due to air pollution in the world and in China and the United States showed a decreasing trend. From 1990 to 2021, the ASMR and ASDR of TBL in China due to air pollution were much higher than those in the United States and the global average. In terms of gender, from 1990 to 2021, the disease burden of male patients with TBL attributed to air pollution was much higher than that of female patients. The BAPC prediction model showed that from 2022 to 2031, the ASMR and ASDR of TBL attributed to air pollution showed an upward trend globally, while they showed a downward trend in China and the United States. Conclusion Over the past 30 years, the air pollution-related TBL disease burden in the world and in China and the United States has continued to decline, but China's disease burden is still significantly higher than the global average. The disease burden in men far exceeds that in women, with men and the population aged ≥50 years being high-risk groups. In the future, the global disease trend may reverse and rise, while China and the United States are expected to continuously decline. However, precise prevention and control for high-risk groups remains a key challenge.

Objective: To analyze the association between drinking behaviors and anxiety symptoms, with the mediating role of insomnia symptoms among college freshmen, so as to provide a reference basis for reducing the occurrence of anxiety symptoms in college freshmen. Methods: From October to December 2021, 31 856 freshmen were selected by the purposive sampling method in 22 colleges across 11 provinces (Fujian, Jiangsu, Guangdong, Henan, Anhui, Hubei, Shanxi, Jiangxi, Shaanxi, Yunnan, Chongqing) in China. The Semi quantitative Food Frequency Questionnaire was used to investigate college freshmen drinking behaviors. The Depression Anxiety Stress Scale 21 and the Insomnia Severity Index were used to assess anxiety symptoms and insomnia symptoms in college freshmen. The generalized linear model was employed to analyze the association between drinking behaviors and anxiety symptoms in college freshmen, and the structural equation modeling was used to assess the mediating effect of insomnia symptoms on the association. Results: The detection rate of anxiety symptoms among college freshmen was 28.2%, the detection rates of the mild, moderate, severe and extremely severe were 6.6%, 15.9%, 3.2% and 2.6%, respectively. While 23.6% of college freshmen reported drinking in the past month, the rates were 39.8% among boys and 15.9% among girls. After adjusting for demographic variables (ethnicity, education, major, etc.) and confounding variables (self evaluation of learning burden, number of close friends, screen time, etc.), the results of generalized linear model analysis showed that beer consumption was associated with anxiety symptoms in college freshmen( β =0.09, 95% CI =0.04-0.14), girls( β =0.14, 95% CI =0.07-0.21) and those aged 19-20 years ( β =0.12, 95% CI =0.05-0.19)(all P <0.05). Red wine consumption was associated with anxiety symptoms in male students ( β =0.13, 95% CI =0.02-0.24, P <0.05). Alcohol and beer consumption were associated with insomnia in college freshmen[ β (95% CI ) =0.22(0.08-0.36),0.31(0.23-0.39),both P <0.01]. Insomnia symptoms partially mediated the association between drinking behaviors and anxiety symptoms among college freshmen with a mediating effect value of 0.05, accounting for 50.49% of the total effect. Conclusions Insomnia symptoms partially mediates the association between drinking behaviors and anxiety symptoms in college freshmen. Measures should be taken to simultaneously intervene in the drinking behaviors and insomnia symptoms of college freshmen to prevent the occurrence of their anxiety symptoms.