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 systematically evaluate the risk prediction models for postoperative pulmonary infection in patients with esophageal cancer, providing an objective basis for clinical selection and optimization of models. Methods A systematic search was conducted in Chinese and English databases such as VIP, Wanfang, CNKI, CBM, PubMed, Cochrane Library, Embase, and Web of Science for studies related to the risk prediction models of postoperative pulmonary infection in patients with esophageal cancer from the inception to September 30, 2024. The PROBAST tool was used to assess the quality of prognostic model research, and the RevMan 5.4 software was used for meta-analysis of predictive factors. Results A total of 17 articles were included, containing 26 pulmonary infection risk prediction models. The area under the receiver operating characteristic curve (AUC) ranged from 0.627 to 0.942, among which 21 models had good predictive performance (AUC>0.7). Quality assessment through the PROBAST tool revealed that all 17 articles had a high risk of bias. Meta-analysis results showed that common predictive factors for postoperative pulmonary infection in esophageal cancer included smoking history (OR=1.97), smoking index ≥200 (cigarettes-years) (OR=4.38), smoking index ≥400 (cigarettes-years) (OR=2.00), age (OR=1.27), comorbid diabetes (OR=2.13), comorbid emphysema or chronic obstructive pulmonary disease (OR=1.55), low plasma albumin levels (OR=1.17), prognostic nutritional index (OR=4.45), history of related lung diseases (OR=2.10), tumor location (OR=2.32), surgical approach (OR=2.21), operation time (OR=1.73), preoperative serum procalcitonin levels (OR=3.06), anastomotic leakage (OR=3.39), reduced forced expiratory volume in the first second/forced vital capacity ratio (OR=0.86), and hoarseness (OR=2.23). Conclusion At present, the risk prediction models for postoperative pulmonary infection in esophageal cancer are still in the stage of continuous development and optimization, and their research quality needs to be further improved. Future research can refer to the predictive factors summarized in this study based on meta-analysis, combined with clinical practice, to select appropriate methods to construct and validate the risk prediction models for postoperative pulmonary infection in esophageal cancer, thus providing early targeted preventive strategies for high-risk patients.

According to the work goals and tasks determined by edition outline of the Chinese Pharmacopoeia 2025 Edition, the Chinese Pharmacopoeia 2025 Edition has been completed. Among them, 52 new pharmaceutical excipients monographs have been added, an increase of 15.5% compared with the 2020 Edition, and the total number has reached 387. This article focuses on the general framework and the main characteristics of the standards of pharmaceutical excipients in the Chinese Pharmacopoeia 2025 Edition, which can contribute to accurately understand and utilize the standards in Chinese Pharmacopoeia.

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.

Polycystic ovary syndrome （PCOS）， a common reproductive endocrine disorder in women， is one of the leading causes of ovulatory infertility in women of reproductive age. Due to its heterogeneous etiology， complex symptoms， and challenging treatment， PCOS has become a focal point of research in gynecological and reproductive medicine globally. The pathogenesis of PCOS is complex and may involve regulatory mechanisms such as inflammatory responses， oxidative stress， and cellular autophagy. Crown-like structures （CLSs） refer to pro-inflammatory microenvironments formed by macrophages engulfing adipocytes. The inflammatory disorders induced by CLSs are one of the key factors contributing to the development of PCOS and its complications. Current studies have indicated that the obese status in PCOS accelerates the formation of CLSs， and the density of CLSs can predict the progression of metabolic disorders and influence the outcomes of various metabolic diseases. Traditional Chinese Medicine （TCM） offers the unique advantages of a holistic view， four diagnostic methods， and syndrome differentiation and treatment to ameliorate the symptoms and signs of PCOS through multiple levels， pathways， and targets. Although studies on the mechanisms of metabolic diseases and CLS formation have been reported in China and abroad， there is still a lack of literature on the correlation between CLSs and PCOS， as well as reviews on TCM interventions targeting CLSs for treating this disease. Therefore， this paper summarized the correlation between obese PCOS and CLSs and reviewed recent studies on TCM interventions based on CLS formation （adipose tissue-macrophage inflammatory crosstalk） in the treatment of obese PCOS， aiming to provide new research perspectives for the prevention and treatment of PCOS using TCM.

Polycystic ovary syndrome （PCOS）， a common reproductive endocrine disorder in women， is one of the leading causes of ovulatory infertility in women of reproductive age. Due to its heterogeneous etiology， complex symptoms， and challenging treatment， PCOS has become a focal point of research in gynecological and reproductive medicine globally. The pathogenesis of PCOS is complex and may involve regulatory mechanisms such as inflammatory responses， oxidative stress， and cellular autophagy. Crown-like structures （CLSs） refer to pro-inflammatory microenvironments formed by macrophages engulfing adipocytes. The inflammatory disorders induced by CLSs are one of the key factors contributing to the development of PCOS and its complications. Current studies have indicated that the obese status in PCOS accelerates the formation of CLSs， and the density of CLSs can predict the progression of metabolic disorders and influence the outcomes of various metabolic diseases. Traditional Chinese Medicine （TCM） offers the unique advantages of a holistic view， four diagnostic methods， and syndrome differentiation and treatment to ameliorate the symptoms and signs of PCOS through multiple levels， pathways， and targets. Although studies on the mechanisms of metabolic diseases and CLS formation have been reported in China and abroad， there is still a lack of literature on the correlation between CLSs and PCOS， as well as reviews on TCM interventions targeting CLSs for treating this disease. Therefore， this paper summarized the correlation between obese PCOS and CLSs and reviewed recent studies on TCM interventions based on CLS formation （adipose tissue-macrophage inflammatory crosstalk） in the treatment of obese PCOS， aiming to provide new research perspectives for the prevention and treatment of PCOS using TCM.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

OBJECTIVES: To investigate the mechanism by which transforming growth factor‑β (TGF‑β) regulates major histocompatibility complex class I (MHC-I) expression in hepatocellular carcinoma (HCC) cells and its role in immune evasion of HCC. METHODS: HCC cells treated with TGF‑β alone or in combination with SB-431542 (a TGF-β type I receptor inhibitor) were examined for changes in MHC-I expression using RT-qPCR and Western blotting. A RNA interference experiment was used to explore the role of miR-23a-3p/IRF1 signaling in TGF‑β‑mediated regulation of MHC-I. HCC cells with different treatments were co-cultured with human peripheral blood mononuclear cells (PBMCs), and the changes in HCC cell proliferation was assessed using CCK-8 and colony formation assays. T-cell cytotoxicity in the co-culture systems was assessed with lactate dehydrogenase (LDH) release and JC-1 mitochondrial membrane potential assays, and T-cell activation was evaluated by flow cytometric analysis of CD69 cells and ELISA for TNF-α secretion. RESULTS: TGF‑β treatment significantly suppressed MHC-I expression in HCC cells and reduced T-cell activation, leading to increased tumor cell proliferation and decreased HCC cell death in the co-culture systems. Mechanistically, TGF-β upregulated miR-23a-3p, which directly targeted IRF1 to inhibit MHC-I transcription. Overexpression of miR-23a-3p phenocopied TGF‑β‑induced suppression of IRF1 and MHC-I. CONCLUSIONS We reveal a novel immune escape mechanism of HCC, in which TGF‑β attenuates T cell-mediated antitumor immunity by suppressing MHC-I expression through the miR-23a-3p/IRF1 signaling axis.
Humans ; MicroRNAs/genetics* ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Interferon Regulatory Factor-1/metabolism* ; Transforming Growth Factor beta/metabolism* ; Signal Transduction ; Histocompatibility Antigens Class I/metabolism* ; Cell Line, Tumor ; Tumor Escape ; Coculture Techniques

This study is designed to address the development, synthesis, and screening of non-animal-derived nanoantibody libraries. Furthermore, it seeks to elucidate the impact of framework region selection and complementarity-determining region (CDR) design on the characteristics of synthesized nanoantibody libraries. These investigations aim to establish a robust theoretical and technical foundation for enhancing the efficacy, diversity, and practical applicability of synthetic nanoantibody libraries. In this study, a new framework (IGHV3S65*01-IGHJ4*01) was identified based on the high-throughput sequencing results of natural nanobodies, and degenerate primers were designed based on the frequency of amino acids at each position in the complementarity-determining region (CDR) region to synthesize the coding fragments of nanobodies by overlap PCR. After 40 times of electro-transformation, a single-frame synthesized nanobody library (SS-Library) containing 6×10⁹ clones was obtained, and the titer of the library was demonstrated to be 10¹³ PFU/mL after rescue by the helper phage M13K07. Random 48 single colonies were picked for PCR, which revealed an insertion rate of 95.8%. Sanger sequencing results showed that 38 clones had complete sequences, none of which showed cysteines or stop codons, and no identical sequences appeared, suggesting that the library had higher diversity. The library was screened and validated with three antigens, including bovine serum albumin (BSA), acetylcholinesterase (AchE), and immunoglobulin G (IgG). Finally, 2 nanobodies against BSA, 10 against AchE, and 15 against IgG were obtained. One positive clone of each antigen was singled out for recombinant expression, and the results showed that all the three nanobodies were expressed in a soluble form. The binding activity of recombinantly expressed nanobodies was evaluated using indirect enzyme-linked immunosorbent assay (ELISA) and bio-layer interferometry (BLI). The results demonstrated that the anti-AChE and anti-IgG nanobodies exhibited specific binding to their respective antigens, with affinity constants (KD) of 294 nmol/L and 250 nmol/L, respectively. The nanobody synthetic library preparation method proposed in this study is simple and easy to use with low preference, and it is expected to be a universal nanobody discovery platform for the preparation and development of lead specific nanobodies.
Single-Domain Antibodies/biosynthesis* ; Peptide Library ; Complementarity Determining Regions/immunology* ; Animals