Objective: To detect the different proteomic characteristics of microvesicles (MVs) and exosomes (EXOs) released from apheresis platelets during storage, and to explore their role in mediating platelet storage damage lesion (PSL). Methods: Apheresis platelets were collected from the retention bag on the third day of storage. MVs and EXOs were isolated using differential centrifugation. Platelet, MVs and EXOs protein samples were extracted respectively, and the differentially expressed proteins were detected by quantitative proteomics technology. Further, the co-incubation model of MVs, EXOs and fresh platelets was adopted to evaluate the effect of extracellular vesicles on PSL. The aggregation response of platelets to collagen agonizers and the changes in ATP release rate were evaluated by optical turbidimetry. Flow cytometry was used to evaluate the changes of platelet early activation indicators (P-selectin and PAC-1) and mitochondrial membrane potentia. Western blot was used to detect the changes in the expression of key proteins for platelet activation and apoptosis (P-selectin, Integrin β3 and Bcl-xl). Results: Proteomic analysis revealed a significantly separation in protein expression profiles of platelet, MVs and EXOs samples within the latent variable space. Energy metabolization-related proteins such as mitochondrial respiratory chain complex and oxidative phosphorylation were enriched specifically, in MVs while EXOs were enriched with inflammation-related proteins. Co-incubation experiments confirmed that extracellular vesicles could significantly induce platelet responses to agonists (the maximum aggregation rate in the MVs group increased by 187.36%, P<0.001; 71.26%, in the EXOs group P=0.002). The maximum ATP release rate of platelets also increased (275.44% in the MVs group, P<0.001; 70.18% in the EXOs group, P=0.015). The expression of P-selectin increased (119.33% in the MVs group, P<0.001; 25.61% in the EXOs group, P=0.013), as detected by flow cytometry. The binding rate of PAC-1 increased (132.18% in MVs group, P<0.001; 21.41% in EXOs group, P=0.043), and the mitochondrial membrane potential decreased (20.49% in MVs group, P<0.001; 9.73% in EXOs group, P=0.044). In the MVs group, platelet P-selectin and Integrin β3 expression were significantly increased (100.83% and 395.64%, P<0.001), while Bcl-xl expression was lower than that in the control group (83.94%, P<0.001). Compared with the control group, P-selectin and Integrin β3 expression were also increased (27.89% and 181.91%, P=0.007和P=0.002), while Bcl-xl was decreased in the EXOs group (36.52%, P<0.001). Conclusion: MVs and EXOs derived from stored platelets show different proteomic characteristics. Compared with EXOs, MVs exhibits a stronger effect in inducing mitochondrial dysfunction. Mvs also promots PSL responses including platelet activation and apoptosis.

Objective To address the challenges of constructing large language models for traditional Chinese medicine(TCM)classics,which are complex and expensive to fine-tune,this study explores a lightweight fine-tuning method for such models,aiming to develop a question-answering model centered on TCM classics,particularly various editions of Shang Han Lun through the ages.Methods Dataset construction involved designing prompts to guide GPT-4 in generating Q&A pairs based on Shang Han Lun and integrating them with the ShenNong_TCM_Dataset and cMedQA2 datasets.Five general-purpose large models were selected for Lora fine-tuning.The best model was chosen through evaluation,and the performance of multiple quantized versions was validated.Results After fine-tuning,the BLEU,ROUGE-1,ROUGE-2,and ROUGE-L metrics for the Qwen-7B-Chat model improved by 17.61,19.63,14.3,and 21.4,respectively,compared to the base model.Conclusion The selected model in this study is capable of effectively understanding and utilizing professional terms and concepts from TCM classics,such as Shang Han Lun,to provide accurate answers to user queries.Compared to similar models,it requires lower fine-tuning costs and computational power,contributing to the dissemination of TCM knowledge and the development of intelligent systems.

Objective To address the challenges of constructing large language models for traditional Chinese medicine(TCM)classics,which are complex and expensive to fine-tune,this study explores a lightweight fine-tuning method for such models,aiming to develop a question-answering model centered on TCM classics,particularly various editions of Shang Han Lun through the ages.Methods Dataset construction involved designing prompts to guide GPT-4 in generating Q&A pairs based on Shang Han Lun and integrating them with the ShenNong_TCM_Dataset and cMedQA2 datasets.Five general-purpose large models were selected for Lora fine-tuning.The best model was chosen through evaluation,and the performance of multiple quantized versions was validated.Results After fine-tuning,the BLEU,ROUGE-1,ROUGE-2,and ROUGE-L metrics for the Qwen-7B-Chat model improved by 17.61,19.63,14.3,and 21.4,respectively,compared to the base model.Conclusion The selected model in this study is capable of effectively understanding and utilizing professional terms and concepts from TCM classics,such as Shang Han Lun,to provide accurate answers to user queries.Compared to similar models,it requires lower fine-tuning costs and computational power,contributing to the dissemination of TCM knowledge and the development of intelligent systems.

The high-quality development of Traditional Chinese Medicine(TCM)is a significant issue faced by the development of TCM in the new era.Artificial Intelligence(AI),as one of the representatives of new productive forces,is expected to provide strong momentum for the inheritance,innovation,and development of TCM.By focusing on three major directions—intelligent TCM early warning and diagnosis,intelligent TCM treatment and rehabilitation,and intelligent TCM research and teaching—the paper reviews the existing problems and challenges in AI-empowered TCM and proposes solutions.In terms of intelligent TCM early warning and diagno-sis,there are issues with the normalization and standardization of TCM theory itself,insufficient open and high-quality large-scale TCM annotation data resources,and lack of TCM theory and thinking guidance in the design of intelligent methods.In terms of intelli-gent TCM treatment and rehabilitation,there are issues such as the feedback and adjustment mechanism are not yet sound,the depth of multidisciplinary collaborative innovation is insufficient,and technical safety and laws and regulations are not perfect.In terms of intel-ligent TCM research and teaching,there are issues such as insufficient mining and interpretation of TCM implicit knowledge,and insuf-ficient learning and simulation of TCM expert thinking.Based on the above issues,corresponding solutions are proposed to explore ide-as for the research in the interdisciplinary field of"artificial intelligence+TCM"and to provide reference for the high-quality develop-ment of TCM inheritance and innovation.

OBJECTIVE To propose an approach based on monocular optical camera-captured full-body two-dimensional ima-ges.Through a three-dimensional reconstruction algorithm,to extract three-dimensional shape parameters and utilize them for intelli-gent identification of phlegm-dampness,yin-deficiency,and other constitutions.METHODS Standard static standing posture ima-ges of subjects in their natural state were collected,and subjects filled out constitution assessment forms or were assessed by the chief TCM physician to obtain constitution information.Constitution served as data labels.A parametric human body three-dimensional re-construction algorithm was employed to extract three-dimensional shape features.Sample distribution was improved using synthetic mi-nority oversampling technique(SMOTE),and a neural network was utilized to establish the connection between human body shape and constitution.RESULTS Experimental results indicate that the accuracy of the phlegm-dampness and yin-deficiency constitution iden-tification model based on human body three-dimensional reconstruction could reach 86.16%,with an F1 score of 79.35%.After using SMOTE to enhance sample distribution,the model accuracy increases to 89.91%,with an F1 score of 84.33%.This demonstrated the feasibility and accuracy of the identification model based on human body three-dimensional reconstruction.CONCLUSION The ex-traction of human body shape features based on three-dimensional reconstruction can effectively identify phlegm-dampness and yin de-ficiency constitutions.Compared to existing methods,this approach is more convenient and enables the rapid detection of potential bia-ses in individual constitutions.Early intervention and correction can be applied to achieve the goal of"preventing disease before it oc-curs".In outpatient clinics,health checkups,and other clinical scenarios,this method has high potential and value for clinical appli-cation.Additionally,this method provides new insights for the intelligent and objective identification of TCM constitution.

The high-quality development of Traditional Chinese Medicine(TCM)is a significant issue faced by the development of TCM in the new era.Artificial Intelligence(AI),as one of the representatives of new productive forces,is expected to provide strong momentum for the inheritance,innovation,and development of TCM.By focusing on three major directions—intelligent TCM early warning and diagnosis,intelligent TCM treatment and rehabilitation,and intelligent TCM research and teaching—the paper reviews the existing problems and challenges in AI-empowered TCM and proposes solutions.In terms of intelligent TCM early warning and diagno-sis,there are issues with the normalization and standardization of TCM theory itself,insufficient open and high-quality large-scale TCM annotation data resources,and lack of TCM theory and thinking guidance in the design of intelligent methods.In terms of intelli-gent TCM treatment and rehabilitation,there are issues such as the feedback and adjustment mechanism are not yet sound,the depth of multidisciplinary collaborative innovation is insufficient,and technical safety and laws and regulations are not perfect.In terms of intel-ligent TCM research and teaching,there are issues such as insufficient mining and interpretation of TCM implicit knowledge,and insuf-ficient learning and simulation of TCM expert thinking.Based on the above issues,corresponding solutions are proposed to explore ide-as for the research in the interdisciplinary field of"artificial intelligence+TCM"and to provide reference for the high-quality develop-ment of TCM inheritance and innovation.

OBJECTIVE To propose an approach based on monocular optical camera-captured full-body two-dimensional ima-ges.Through a three-dimensional reconstruction algorithm,to extract three-dimensional shape parameters and utilize them for intelli-gent identification of phlegm-dampness,yin-deficiency,and other constitutions.METHODS Standard static standing posture ima-ges of subjects in their natural state were collected,and subjects filled out constitution assessment forms or were assessed by the chief TCM physician to obtain constitution information.Constitution served as data labels.A parametric human body three-dimensional re-construction algorithm was employed to extract three-dimensional shape features.Sample distribution was improved using synthetic mi-nority oversampling technique(SMOTE),and a neural network was utilized to establish the connection between human body shape and constitution.RESULTS Experimental results indicate that the accuracy of the phlegm-dampness and yin-deficiency constitution iden-tification model based on human body three-dimensional reconstruction could reach 86.16%,with an F1 score of 79.35%.After using SMOTE to enhance sample distribution,the model accuracy increases to 89.91%,with an F1 score of 84.33%.This demonstrated the feasibility and accuracy of the identification model based on human body three-dimensional reconstruction.CONCLUSION The ex-traction of human body shape features based on three-dimensional reconstruction can effectively identify phlegm-dampness and yin de-ficiency constitutions.Compared to existing methods,this approach is more convenient and enables the rapid detection of potential bia-ses in individual constitutions.Early intervention and correction can be applied to achieve the goal of"preventing disease before it oc-curs".In outpatient clinics,health checkups,and other clinical scenarios,this method has high potential and value for clinical appli-cation.Additionally,this method provides new insights for the intelligent and objective identification of TCM constitution.

Objective Aiming at the problems of many items and long time to fill in the Constitution in Chinese Medicine Questionnaire(CCMQ)when evaluating individual constitution,the research uses artificial intelligence technology to select attributes,and to help construct a short version of the CCMQ.Methods Analyzing the constitution data provided by the Physical Examination Department of Jiangsu Province Hospital of Traditional Chinese Medicine,there are specific target variables as the classification of constitution types.Feature selection of genetic algorithm,cross-validation and KNN classification algorithm are used as filters to select problems,and the effect is evaluated by problem subset size,KNN classification accuracy and filling time.Results The method selected a short version of the CCMQ with 31 problems,and the average classification accuracy in the model was 86.16%,and the time was improved by 47.7%.Conclusion The algorithm can effectively find a better problem subset,achieve dimensionality reduction and have certain accuracy,thus helping to simplify the CCMQ.

Animals ; Bacterial Infections/metabolism* ; Glucose/metabolism* ; Homeostasis ; Insulin Secretion ; Mice ; Mice, Knockout ; Sirtuins/metabolism*

AIM: To study the effects of hypertonic NaCl-NaAc on microcirculation in hemorrhage-shocked rats.METHODS: SD rats were randomized into three groups of 7 5% NaCl(hypertonic saline, HS),5% NaCl-3 5% NaAc(hypertonic sodium acetate, HSA) and 0 9% NaCl(normal saline, NS) 4 mL/kg HS,HSA or NS was given intravenously following hemorrhagic shock The microcirculation of spinotrapezius muscle was observed RESULTS: HS increased mean aortic pressure more significant than HSA Variables including arteriolar and venular diameter,velocity and volumetric flow rate and open capillaries were increased and erythrocyte aggregation was decreased in 5 min after resuscitation with both HS and HSA solutions 5 min later,variables were deteriorated in HS group After local treatment, arteriolar and venular diameters were dilated significantly in HSA group CONCLUSION:HSA had superior effects to HS in improving microcirculation of hemorrhage-shocked rats