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 investigate the equivalence of different decoction processes based on rat model of hypertension with liver-yang hyperactivity. METHODS Inductively coupled plasma mass spectrometry （ICP-MS） was used to compare the dissolution differences of inorganic elements in the powder-directly-decocted decoction versus the pieces-decocted-first decoction of Ostreae Concha- Haliotidis Concha- Margaritifera Concha drug pair. Six SD rats were included in the normal group. The spontaneously hypertensive rats were given Aconite decoction for six weeks to induce the hypertension model with liver-yang hyperactivity. After successful modeling， 48 rats were randomly divided into the model group， the captopril group [positive control， 8 mL/（kg·d） ] ， as well as low-， medium-， and high-dose groups of pieces decocted first or directly powder decocted [2.02， 4.05， 8.10 mL/（kg·d） ] ， with 6 rats in each group. Each group received the corresponding drug or equal volume of pure water intragastrically， once a day， for two consecutive weeks. After the last administration， the degree of irritability， facial temperature， pressure pain threshold， blood pressure， and pathological changes of the thoracic aorta were observed in each group. Serum nitric oxide （NO） and plasma angiotensin Ⅱ （Ang Ⅱ）， renin， and aldosterone （ALD） levels were also measured. RESULTS ICP-MS analysis results showed statistically significant differences in the contents of macroelements Li， Na， Mg， Ca， Mn， Ga， Sr， Mo， Cd， Sn， and Sb， between the powder-directly-decocted decoction and the pieces-decocted-first decoction （ P ＜0.05） ，the elements P， Cr， Fe， Ni， Zn， Hg， Tl， and Pb were not detected in either decoction. Animal experiments showed that after two weeks of administration， compared with the model group， the facial temperature， and blood pressure decreased in all treatment groups， while the pressure pain threshold increased； plasma levels of Ang Ⅱ， renin and ALD， as well as the serum level of NO were all decreased， and thoracic aortic media thickness was significantly reduced， most of the differences in the above indicators were statistically significant （ P ＜0.05 or P ＜0.01 or P ＜0.001）. Pathological observation showed improvement in thoracic aortic pathological injury. CONCLUSIONS The powder-directly-decocted process for the Ostreae Concha- Haliotidis Concha- Margaritifera Concha drug pair significantly promotes the dissolution of key elements such as Ca， Mg， and Sr without increasing the dissolution of harmful elements. It is equivalent to the traditional pieces-decocted-first in alleviating liver-yang hyperactivity syndrome， lowering blood pressure， and protecting the vascular endothelium， and even shows better performance in some indicators.

Objective To evaluate the cost–utility of lecanemab and donanemab in the treatment of early Alzheimer’s disease （AD） in China. Methods A Markov model was developed from a societal perspective to compare standard of care （SOC）, lecanemab plus SOC, and donanemab plus SOC in terms of costs, quality-adjusted life years （QALY）, and incremental cost–utility ratios （ICUR）. Deterministic and probabilistic sensitivity analyses were conducted to assess parameter uncertainty. Results Both intervention strategies increased QALY compared with SOC but were associated with substantially higher costs, and neither was cost-effective under the current willingness-to-pay threshold. Conclusion Lecanemab and donanemab may be more appropriately considered within a multi-tiered healthcare reimbursement framework in China rather than relying solely on basic medical insurance.

ObjectiveTo evaluate the clinical efficacy and safety of Xiaozhen Formula （消疹方） in preventing skin toxicity induced by epidermal growth factor receptor inhibitors （EGFRIs） in patients with EGFR-mutant non-small cell lung cancer （NSCLC）. MethodsA randomized， double-blind， placebo-controlled， multicenter clinical study was conducted. A total of 120 patients with EGFR-mutant NSCLC from seven centers were enrolled and randomly assigned to a treatment group （60 cases） or a control group （60 cases）. On the basis of EGFRI-targeted therapy， patients in the treatment group received Xiaozhen Formula granules， whereas those in the control group received Xiaozhen Formula placebo granules， both at 10 g twice daily for 4 consecutive weeks. The primary outcomes were the grading of skin toxicity evaluated using the National Cancer Institute Common Terminology Criteria for Adverse Events （NCI-CTCAE） version 5.0 and the incidence of rash. Secondary outcomes included the time to onset and time to resolution of the highest-grade rash， the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 （EORTC QLQ-C30） scores， the Hospital Anxiety and Depression Scale （HADS） scores， and disease control rate， together with safety assessments. ResultsBased on the full analysis set （FAS）， the incidence of skin toxicity in the treatment group was 18.33% （11/60）， significantly lower than 45.00% （27/60） in the control group （P＜0.01）， with the highest severity of skin toxicity in both groups was grade 2. Among patients who developed rash， the resolution rate in the treatment group was 90.91% （10/11）， higher than that 33.33% （9/27） in the control group. The median time to resolution was 15 days （95%CI： 8-17 days） in the treatment group and it was not reached in the control group； the distribution of time to resolution differed significantly between groups （P＜0.001）. After treatment， the treatment group had higher EORTC QLQ-C30 functional scale and global health status/quality-of-life scores， and lower symptom scale， single-item scores， as well as HADS-A， and HADS-D scores than the control group （P＜0.05）. In the FAS analysis， the disease control rate （DCR） was 85.0% （51/60） in the treatment group， lower than 100.0% （60/60） in the control group （P=0.003）， whereas no significant between-group difference was observed in the per-protocol set （PPS） analysis （P=0.464）. The incidence of adverse events did not differ significantly between the two groups （P＞0.05）， and no definite safety signals related to the investigational drug were observed. ConclusionXiaozhen Formula can reduce the incidence of EGFRI-induced skin toxicity， and improve the outcome of rash regression， the patients' quality of life and psychological status in EGFR-mutant NSCLC patients.

With the rapid advancement of medical technology and the increasing complexity of clinical environments, competence in clinical ethical decision-making has become an indispensable core competency for exemplary physicians. However, traditional medical ethics education has long been confronted with the persistent challenges of theory-practice dissociation and the disconnect between pedagogical settings and clinical realities. Thus, how to construct a "Clinical Ethics" curriculum that aligns with the objectives of training high-caliber medical professionals has emerged as a critical and challenging issue in current medical education reform. To effectively address this challenge, the Office of Education at Peking University Third Hospital, since 2021, has assembled a multidisciplinary "Clinical Ethics" teaching and management team comprising faculty from Peking University School of Humanities and key clinical specialists from the hospital. In 2022, the "Clinical Ethics" elective course was formally launched for fourth-year students in the eight-year MD program who had completed coursework in "Medical Ethics" and organ-system-based curricula, with the aim of exploring and operationalizing a pre-clinical ethics education model tailored for senior medical students. The course employs a modular instructional design encompassing "theoretical review-case-based deliberation-clinical workshop", which effectively facilitates the deep integration of medical humanities with clinical practice.Following four years of iterative refinement through the "plan-act-observe-reflect" cycle, the course has demonstrated positive outcomes in enhancing students' ethical awareness and decision-making capabilities, and has preliminarily established a sustainable collaborative mechanism among the multidisciplinary faculty team. This article systematically delineates the course development background, pedagogical model and methodological innovations, and the multidisciplinary collaborative framework, alongside reflections and summaries based on implementation outcomes, with the intent of providing references for the future development of "Clinical Ethics" curricula.

[Objective] To investigate the infection status and characteristics of HEV among voluntary blood donors in Ningbo, and to provide a basis for improving the blood screening strategy. [Methods] A total of 12 227 blood samples from voluntary blood donors in Ningbo from June 2022 to May 2023 were tested for HEV serology, enzymology, and nucleic acid testing. Furthermore, HEV gene sequencing was performed for genotyping analysis, and donors with reactive nucleic acid testing results were followed up to confirm their infection status. [Results] The reactivity rate of HEV Ag, anti-HEV IgM and anti-HEV IgG was 0.098%, 0.899% and 29.198%, respectively. There was no difference in the reactivity of anti-HEV IgM and anti-HEV IgG between genders, donation frequencies and donation types (P>0.05). The reactivity rate increased significantly with age (P<0.05). The rate of ALT disqualification (ALT>50U/L) was significantly higher than that in non-reactive samples (P<0.05). The HEV Ag reactivity rate (0.098%) was not correlated with gender, donation frequency, donation type or age. One HEV RNA positive case was found, with a positive rate of 0.008%(1/12 227). It was confirmed to be hepatitis E virus genotype 3 by sequencing analysis. Apart from HEV Ag reactivity, all other blood safety screening items were non-reactive, suggesting this case might be in the acute infection phase. The follow-up results showed that all indicators of the donor's previous blood donation were non-reactive. [Conclusion] Pre-donation ALT detection can reduce the risk of transfusion-transmitted HEV (TT-HEV) to a certain extent, and the effective way to prevent TT-HEV is to detect HEV RNA and serology of donor blood.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.