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.

AIM:This study aims to design pH/near-infrared(NIR)dual-responsive metal-organic framework composite nanoparticles co-loaded with indocyanine green(ICG)and sphingosine kinase 1(SphK1)siRNA(siSphK1),and to evaluate their anticancer efficacy against non-small-cell lung cancer A549 cells.METHODS:The ZIF-8 nanopar-ticles were synthesized and loaded with ICG and siSphK1 to prepare ZIF-8@ICG@siSphK1 nanoparticles.Their morpholo-gy,particle size,surface charge,and crystalline structure were characterized through transmission electron microscopy,dynamic light scattering,and X-ray diffraction.Stability,siSphK1 encapsulation and protection,and pH/NIR response were assessed.The gene silencing efficacy and anticancer activity in A549 cells were evaluated using Western blot,RT-qPCR,MTT assay,flow cytometry,and reactive oxygen species(ROS)fluorescence staining.RESULTS:The ZIF-8@ICG@siSphK1 nanoparticles exhibited a typical polyhedral structure with an average particle size of(76.8±0.9)nm and a ζ potential of(9.2±0.1)mV.The nanoparticles effectively encapsulated siSphK1,protecting it from RNase degra-dation,and demonstrated excellent NIR responsiveness with a photothermal conversion efficiency of 39.7%.After 10 h of 808 nm laser irradiation,siRNA cumulative release was significantly higher at pH 5.5 compared with pH 7.4.In A549 cells,the nanoparticles efficiently delivered siSphK1 under NIR irradiation,significantly down-regulated SphK1 gene ex-pression,inhibited cell proliferation,induced apoptosis,and increased intracellular ROS levels.CONCLUSION:The ZIF-8@ICG@siSphK1 nanoparticles effectively induce cytotoxic effects against A549 cells through gene silencing and pho-tothermal therapy.

Objective To design a digital intelligence-driven critical treatment platform to implement integrated treatment procedure inside and outside the hospital and intelligent whole-course managment from pre-hospital emergency care to discharge for critically ill patients.Methods The platform was designed with 5G,IoT,big data and aritificial intelligence techniques and developed with Java language,which adopted Oracle database-based data management and front-end and back-end separation mode,with the front end realized by Vue.js framework and the back end by microservice architecture.There were five functional modules for pre-hospital emergency care,multidisciplinary joint diagnosis and treatment,critical care,quality control management and post-discharge follow-up involved in the platform.Results The platform developed simplified the treatment procedure,enhanced the timeliness of emergency care,decreased the workload of nursing staffs and improved medical service efficiency and working efficiency effectively.Conclusion The platform increases first aid quality and treatment efficiency and provides critically ill patients with high-quality medical experience.[Chinese Medical Equipment Journal,2025,46(1):38-43]

Objective To investigate the significance and clinical value of preoperative three-dimensional CT reconstruction of the whole abdomen guiding preserving the left colonic artery during laparoscopic radical resection of rectal cancer. Methods Patients with rectal cancer who underwent laparoscopic radical resection of rectal cancer in our hospital from January 2021 to January 2022 were selected,then 87 patients with left colonic artery were screened out through three-dimensional CT reconstruction of the whole abdomen before surgery,who were randomly divided into the observation group (received intraoperative low ligation of the inferior mesenteric artery,with preservation of the left colonic artery) with 40 cases and the control group (received intraoperative high ligation of the inferior mesenteric artery without preservation of the left colonic artery) with 47 cases. The perioperative indexes and postoperative pathological results of the two groups were compared. Results The intraoperative blood loss in the observation group was higher than that in the control group,and the operation time was longer than that in the control group,with statistically significant differences (P<0.05). The incidences of postoperative intestinal obstruction and anastomotic leakage in the observation group were lower than those in the control group,and the first postoperative discharge time was earlier than that in the control group,with statistically significant differences (P<0.05). There was no significant difference in the degree of tumor differentiation,tumor size,adenocarcinoma classification,number of lymph nodes dissected at the root of the inferior mesenteric artery,or the stage of intestinal wall invasion depth of tumor between the two groups (P>0.05). Conclusion The application of the three-dimensional CT reconstruction of the whole abdomen before surgery can understand the branch classification of the inferior mesenteric artery in advance,determine the location of the tumor and its adjacent relationship with the surrounding tissues,and determine the resection extent of intestinal segment. Intraoperative preservation of the left colonic artery can reduce the occurrence of postoperative complications in patients,which has positive clinical significance.

Rectal cancer is one of the most common gastrointestinal malignant tumors,and patients with early rectal cancer can achieve radical tumor resection by surgical treatment alone,while most patients with rectal cancer are in the locally advanced stage when admitted to hospital.For this group of people,it is difficult to obtain a good prognosis through surgical treatment alone,and interventional chemoradio-therapy before surgery is of important clinical significance.A large number of clinical studies have proved that preoperative neoadjuvant therapy can effectively reduce tumor stage,increase pathological complete response(pCR)rate,thereby greatly improving the prognosis of patients.At present,the core methods of neoadjuvant therapy for locally advanced rectal cancer are radiotherapy and chemotherapy,as well as the emerging targeted therapy and immunotherapy,while the optimal combination order of various treatments remains in dispute.This article summarizes various neoadjuvant therapy regimens in recent years,in order to provide evidence for the multidisciplinary and comprehensive treatment of rectal cancer.

To investigate the molecular mechanisms underlying the mechanosensitive ion channel PI-EZO2 in osteoarthritis(OA),we developed a lentiviral vector for endogenous PIEZO2 overexpression and established a stable PIEZO2-high-expressing immortalized human primary chondrocyte line.By map-ping the open reading frame of the PIEZO2 locus and designing sequence-specific sgRNA,we employed the CRISPR/Cas9 synergistic activation mediator(SAM)system to precisely integrate transcriptional ac-tivation elements into the PIEZO2 promoter region.Lentiviral-mediated targeted genomic integration en-sured endogenous PIEZO2 overexpression,confirmed by mCherry fluorescence tracing coupled with flow cytometric sorting,which revealed membrane-specific localization of PIEZO2 protein(localization effi-ciency:78.49％).Quantitative PCR demonstrated a 17-fold upregulation of PIEZO2 mRNA,while Western blotting validated enhanced membrane-localized protein expression.Strikingly,PIEZO2-overex-pressing chondrocytes exhibited hallmark OA metabolic phenotypes compared to wild-type controls:typeⅡ collagen mRNA expression decreased to 50％of baseline levels,whereas matrix metalloproteinase 13(MMP13)mRNA surged by 20-fold.These alterations recapitulated the pathological matrix metabolic phenotype observed in biomechanical OA models induced by cyclic mechanical stress(10％strain,0.5 Hz,8 h/day for 2 consecutive days).Collectively,we successfully generated a human chondrocyte model with stable PIEZO2 overexpression,which faithfully mirrors mechanotransduction-driven OA progression.This engineered cellular system provides a robust platform for dissecting PIEZO2-mediated mechanosig-naling networks and advancing targeted therapeutic discovery.

OBJECTIVE The emergence of evolving variants of Coronavirus disease 2019(COVID-19)has fostered the need for change of newer and adaptive treatments for these infections.During the COVID-19 pandemic and persists,traditional Chinese medicine(TCM)herbs exhibit significant bioactivity and therapeutic effect.This study is aimed to evaluate the efficacy of four TCM preparations on 28-day mortality risk of patients and changes of the laboratory indicators.METHODS The retrospective cohort study included patients with COVID-19 who were admitted to the Jiangsu Province Hospital of Chinese Medicine from December 15,2022 to January 15,2023,and those died within 48 hours of admission or cannot be tracked for outcomes were excluded.The pri-mary outcome was survival status in 28 days(death or survival)starting from the day of admission.The second outcomes were labora-tory indicators,including absolute lymphocyte count,lactate dehydrogenase,creatinine,and blood urea nitrogen.Binary logistic re-gressions were used to estimate the effect of TCM preparations on the primary and secondary outcomes in main analysis.Meanwhile,heterogeneity and robustness of results from main analysis were assessed by subgroup analyses and multiple sensitivity analyses.RESULTS 1 816 eligible patients were included in analysis dataset,including 573 patients received standard care(control group)and 1 243 patients received TCM preparations(hospital preparation group).The 28-day mortality rate of hospital preparation group was lower than that of control group(4.75%vs.14.83%),and the difference was statistically significant(χ2=54.666,P<0.001).The risk of 28-day mortality was 0.535 times lower in the hospital preparation group as compared with the control group(OR=0.46,95%CI:0.305-0.708,P<0.001)showed by multivariable binary logistic regressions.Subgroup analyses showed that taking TCM preparations reduced the 28-day mortality risk.Sensitivity analyses demonstrated that the results of the main analysis for primary outcomes were robust.For secondary outcomes,the risk of abnormal absolute lymphocyte counts at discharge in the hospital prepara-tion group decreased by 0.284 times(OR=0.703,95%CI:0.515-0.961,P=0.027).CONCLUSION Compared with standard of care,taking four hospital preparations including Kanggan Heji,Feining Heji,Qishen Gubiao Keli,and Qianghuo Qushi Qingwen Heji decreased risk of 28-day mortality among hospitalized COVID-19 patients.TCM therapy achieves adequate therapeutic effects in COVID-19.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective To design a digital intelligence-driven critical treatment platform to implement integrated treatment procedure inside and outside the hospital and intelligent whole-course managment from pre-hospital emergency care to discharge for critically ill patients.Methods The platform was designed with 5G,IoT,big data and aritificial intelligence techniques and developed with Java language,which adopted Oracle database-based data management and front-end and back-end separation mode,with the front end realized by Vue.js framework and the back end by microservice architecture.There were five functional modules for pre-hospital emergency care,multidisciplinary joint diagnosis and treatment,critical care,quality control management and post-discharge follow-up involved in the platform.Results The platform developed simplified the treatment procedure,enhanced the timeliness of emergency care,decreased the workload of nursing staffs and improved medical service efficiency and working efficiency effectively.Conclusion The platform increases first aid quality and treatment efficiency and provides critically ill patients with high-quality medical experience.[Chinese Medical Equipment Journal,2025,46(1):38-43]