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.

ObjectiveType 2 diabetes mellitus (T2DM) often causes severe hepatic metabolic complications, dominated by metabolic associated fatty liver disease (MAFLD). Persistent hepatic steatosis and oxidative stress further trigger steatohepatitis and progressive liver damage, increasing the mortality risk of diabetic patients. Aerobic exercise effectively improves hepatic lipid metabolism and antioxidant capacity, but poor patient adherence restricts its long-term clinical application. Mitochondrial-derived mitochondrial open reading frame of the 12S rRNA type-c (MOTS-c) is a key peptide regulating insulin sensitivity and hepatic redox homeostasis. This study aimed to explore the protective mechanism of MOTS-c against T2DM-related liver injury and its combined beneficial effect with aerobic exercise via the NRF2/PPARγ signaling axis. This study aimed to investigate whether MOTS-c cooperates with aerobic exercise to alleviate T2DM-associated hepatic oxidative stress and metabolic dysfunction by activating the NRF2/PPARγ axis, and to clarify the molecular and transcriptomic characteristics of their combined intervention. MethodsStable MOTS-c overexpression and knockdown HepG2 cell lines were constructed using lentiviral transfection. An oleic acid-induced cellular lipid accumulation model and NRF2-knockout cell model were applied to verify the NRF2-dependent mechanism ofMOTS-c. Intracellular lipid deposition, triglyceride levels, antioxidant enzyme activities, and the expression of NRF2/PPARγ pathway-related genes and proteins were detected. In vivo, a T2DM rat model with obvious hepatic steatosis was established via a high-fat and high-sucrose diet combined with streptozotocin injection. Model rats received aerobic exercise, MOTS-c intraperitoneal injection, or combined intervention. We detected systemic glycolipid metabolic indicators, hepatic histopathological changes, and the expression of core proteins in the hepatic NRF2/PPARγ axis. Hepatic transcriptomic sequencing was performed to screen differentially expressed genes (DEGs) and enrich key pathways co-regulated by MOTS-c and aerobic exercise. ResultsCellular results showed that MOTS-c overexpression significantly reduced oleic acid-induced lipid deposition, enhanced antioxidant enzyme activity, and upregulated NRF2 and PPARγ expression. Conversely, MOTS-c knockdown aggravated hepatic lipid accumulation and oxidative damage and inhibited NRF2/PPARγ pathway activation. NRF2 knockout completely eliminated the protective effects of MOTS-c on lipid metabolism and redox balance, confirming its NRF2-dependent regulatory mechanism. In T2DM rats, both MOTS-c supplementation and aerobic exercise effectively improved insulin resistance, corrected glycolipid metabolic disorders, and alleviated hepatic steatosis, while consistently activating the hepatic NRF2/PPARγ axis. Compared with single intervention, the combined treatment showed a better improvement trend in hepatic metabolic and oxidative injury, without definitive synergistic effects. Transcriptomic analysis revealed that the co-regulated DEGs of MOTS-c and aerobic exercise were primarily enriched in lipid metabolism and PPAR signaling pathways, with multiple antioxidant and lipid-regulating genes significantly modulated by combined intervention. ConclusionMOTS-c exhibits obvious exercise-mimetic hepatoprotective effects in T2DM. It activates the hepatic NRF2/PPARγ axis to strengthen antioxidant defense, stabilize lipid metabolism, and relieve T2DM-associated hepatic steatosis and oxidative damage. Furthermore, MOTS-c produces additive beneficial effects with aerobic exercise, showing a superior intervention trend on diabetic liver dysfunction. This study identifies the NRF2/PPARγ axis as the core mechanism of MOTS-c-regulated hepatic protection, elucidates the transcriptomic basis of combined intervention, and provides a reliable theoretical basis and potential therapeutic target for clinical intervention in T2DM-complicated MAFLD.

Fecal microbiota transplantation (FMT) technology originated in China during the Eastern Jin Dynasty and has rapidly developed over the past two decades, becoming a primary method for studying the causal relationship between gut microbiota and the occurrence and progression of diseases. At the same time, the therapeutic effects of FMT in the field of gastrointestinal diseases have gained widespread recognition and are gradually expanding into other disease areas. The FMT procedure is relatively complex, and there is currently no standardized method; its success is influenced by various factors, including the donor, recipient, processing of the fecal material, and the method of implantation. Given the increasingly recognized relationship between gut microbiota and various diseases, FMT has become a research hotspot in both scientific studies and clinical applications, achieving a series of significant advancements. To help researchers better understand this technology, this paper will outline the development history of FMT, summarize common operational methods in research and clinical settings, review its application progress, and look forward to future development directions.

Bacterial biofilms can make traditional antibiotics impenetrable and even promote the development of antibiotic-resistant strains. Therefore, non-antibiotic strategies to effectively penetrate and eradicate the formed biofilms are urgently needed. Here, we demonstrate the development of self-propelled biohybrid microrobots that can enhance the degradation and penetration effects for Pseudomonas aeruginosa biofilms in minimally invasive strategy. The biohybrid microrobots (CR@Alg) are constructed by surface modification of Chlamydomonas reinhardtii (CR) microalgae with alginate lyase (Alg) via biological orthogonal reaction. By degrading the biofilm components, the number of CR@Alg microrobots with fast-moving capability penetrating the biofilm increases by around 2.4-fold compared to that of microalgae. Massive reactive oxygen species are subsequently generated under laser irradiation due to the presence of chlorophyll, inherent photosensitizers of microalgae, thus triggering photodynamic therapy (PDT) to combat bacteria. Our algae-based microrobots with superior biocompatibility eliminate biofilm-infections efficiently and tend to suppress the inflammatory response in vivo, showing huge promise for the active treatment of biofilm-associated infections.

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

Objective To analyze the spatial distribution patterns of the potential suitable habitats for Cremastrae Pseudobulbus Pleiones Pseudobulbus,including Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe under current climatic conditions,and the factors influencing the spatial differentiation of their habitats.Methods Based on the maximum entropy(MaxEnt)model,a species distribution model was established using the screened species distribution data and environmental variable data.The factor detection and interaction detection of geographical detector were applied to quantify the factors influencing the spatial differentiation of the suitable areas.By overlaying the suitable areas with land cover types,the distribution characteristics of forest land and arable land in the potential suitable areas were quantified.Results Under the current climatic scenario,environmental variables such as solar radiation intensity,precipitation and temperature were closely related to the spatial distribution of Cremastrae Pseudobulbus Pleiones Pseudobulbus.The potential suitable areas for Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe were 2.20×106 km2,2.75×106 km2 and 7.22×105 km2,respectively.Considering land cover types,the actual possible suitable areas for Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe were 1.86×106 km2,2.20×106 km2 and 5.77×105 km2,respectively.Among these,the area of forest land was 1.17×106 km2,1.34×106 km2 and 3.67×105 km2,respectively,and the area of arable land was 6.95×105 km2,8.64×105 km2 and 2.10×105 km2,respectively.Conclusion This study can provide a basis for the protection and sustainable utilization of wild resources of the original plant materials of Cremastrae Pseudobulbus Pleiones Pseudobulbus.

Objective To investigate the spatial distribution pattern of the suitable habitats for Codonopsis pilosula(Franch.)Nannf.and the factors influencing the spatial differentiation of its habitat under current climatic conditions in China.Methods Based on maximum entropy(MaxEnt)model,a species distribution model was established with filtered species occurrence data and environmental variable data.The geographical detector was applied to quantify the factors influencing the spatial differentiation of the suitable areas,employing both factor detection and interaction detection functionalities.Additionally,an overlay analysis with land cover types was conducted to quantify the distribution characteristics of arable land and forest land within the potential suitable areas for Codonopsis pilosula(Franch.)Nannf..Results Based on the contribution rate of environmental factors and the Jackknife method,average solar radiation intensity in December,precipitation in July,and highest temperature in December were identified as key environmental factors affecting the suitability of Codonopsis pilosula(Franch.)Nannf.habitats,which were further validated by the geographical detector.The total suitable area for Codonopsis pilosula(Franch.)Nannf.in China under current climatic conditions was approximately 4.46×106 km2,with the areas of high,moderate,and low suitability being 1.08×106 km2,1.70×106 km2,and 1.68×106 km2,respectively.After overlaying with arable and forest lands,the potentially suitable total forest area for Codonopsis pilosula(Franch.)Nannf.was 1.55×106 km2,and the arable land area was 1.63×106 km2.Conclusion This study provides reference for the optimization of cultivation areas for Codonopsis pilosula(Franch.)Nannf.and the conservation of its wild resources.

Processing for deodorization is widely used in the production of animal-derived Chinese medicinal materials. In this study, Heracles Neo ultra-fast gas-phase electronic nose combined with chemometrics was employed to analyze the overall odor difference of Cervi Cornu Pantotrichum(focusing on that derived from Cervus nippon Temminck in this study) before and after processing. The results showed that the electronic nose effectively distinguished between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. HS-GC-MS was used to identify and quantify the volatile components in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum, and 35 and 37 volatile components were detected in the medicinal materials and decoction pieces, respectively. The medicinal materials and decoction pieces contained 28 common volatile components contributing to the odor of Cervi Cornu Pantotrichum. The odor activity value(OAV) of each volatile component was calculated based on the olfactory threshold and relative content. The results showed that there were 17 key odor substances such as isovaleraldehyde, 2-methylbutanal, isobutyraldehyde, hexanal, and methanethiol in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. All of them had bad odor and were the main source of the odor of Cervi Cornu Pantotrichum. The results of principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) showed that there were significant differences in volatile components between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. Based on the thresholds of P<0.05 and Variable Importance in Projection(VIP)>1, 21 differential volatile odor components were screened out. Among them, isopentanol, isovaleraldehyde, 2-methylbutanal, n-nonanal, and dimethylamine were the key differential odor compounds between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. The odor compounds and their relative content reduced, and some flavor substances such as esters were produced after processing with wine, which was the main reason for the reduction of the odor after processing of Cervi Cornu Pantotrichum.
Odorants/analysis* ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods* ; Animals ; Volatile Organic Compounds/analysis* ; Deer ; Drugs, Chinese Herbal/chemistry*

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*