In the context of the digital-intelligent era of traditional Chinese medicine （TCM）， the lack of clinical thinking is a pressing issue that limits the overall effectiveness of TCM and talent cultivation. The "disease-pulse-syndrome-treatment differentiation" thinking model， originally developed by ZHANG Zhongjing in the Treatise on Cold Damage and Miscellaneous Diseases （Shang Han Za Bing Lun）， has served as a guideline and paradigm followed by generations of medical practitioners. This study aims to construct a digitalized "disease-pulse-syndrome-treatment differentiation" thinking system， develop a digital assessment system， and implement it for practical application. The goal is to recommend a digitalized assessment model for TCM and provide a reference for the integrated innovation of talent cultivation in medicine， education， and research. First， based on the complex diagnostic and treatment framework of the Treatise on Cold Damage Diseases （Shang Han Lun）， the research team previously established a "process" + "result" thinking model that included four processes and ten steps. This study integrates knowledge unit theory and digital technology to create a digital system for "disease-pulse-syndrome-treatment differentiation" with a dual-control model of "process control" and "result control". The system consists of 46 items across three categories： knowledge body （W=20%）， knowledge element （W=30%）， and knowledge element associations （W=50%）. Second， a mixed-methods research design was employed， combining qualitative and quantitative approaches. The Delphi method was used to establish hierarchical levels and screen items， while the analytic hierarchy process （AHP） was used to assign weights. Expert surveys were conducted to reach a consensus and further validate the rationale and necessity of the system. Finally， based on the system architecture and integrating key computer technologies， a digital assessment system for "disease-pulse-syndrome-treatment differentiation" was developed. The Treatise on Cold Damage Diseases （Shang Han Lun） was used as a case study to validate the system's feasibility. Statistical results showed that the difficulty level of the assessment question bank was moderate （DL ranging from 0.65 to 0.89）， with good discrimination （D>0.4）， and reasonable reliability and validity （Cronbach's α=0.84， KMO=0.72， Bartlett's test P<0.01）. The system can perform process-oriented evaluations of candidates' thinking in "disease-pulse-syndrome-treatment differentiation" and effectively achieve the goal of clinical thinking assessment through a combination of "process control" and "result control". The examination system offers three major advantages. It standardizes， objectifies， and streamlines the assessment of thought processes， facilitates the organic transformation of TCM education from outcome-based education to thinking-based education， and from exam-oriented education to competency-oriented education， and promotes the practical transformation of TCM assessments from qualitative to quantitative evaluation， as well as from theory to practice. In summary， this system not only represents a technological upgrade to traditional examinations but also empowers the cultivation and assessment of clinical talent in the digital-intelligent era， demonstrating broad application prospects.

Objective To investigate the predictive value of serum interleukin-17(IL-17)combined with eotaxin-3 for poor prognosis in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD).Methods A total of 213 patients with AECOPD admitted to Beijing Municipal Armed Police Force Hospital from May 2018 to July 2023 were selected as the disease group.According to the prognosis of patients,they were divided into good prognosis group(133 cases)and poor prognosis group(80 cases).At the same time,205 physical examination healthy people in Beijing Municipal Armed Police Force Hospital were selected as the healthy group.The serum levels of IL-17 and eotaxin-3 were detected by enzyme-linked immu-nosorbent assay.The clinical data of poor prognosis group and good prognosis group were compared.Pearson correlation analysis was used to analyze the correlation between serum IL-17 level and eotaxin-3 in AECOPD patients.Multivariate Logistic regression analysis was used to analyze the related factors affecting the progno-sis of AECOPD patients.The receiver operating characteristic(ROC)curve was used to evaluate the predic-tive value of serum IL-17 and eotaxin-3 levels for the prognosis of AECOPD patients.Results Compared with the healthy group,the serum levels of IL-17 and eotaxin-3 were increased in the disease group(P<0.05).Compared with the good prognosis group,the poor prognosis group had significant increases in serum IL-17 and eotaxin-3 levels(P<0.05).Serum IL-17 level was positively correlated with eotaxin-3 in AECOPD pa-tients(r=0.537,P<0.001).There were significant differences in Global Initiative for Chronic Obstructive Lung Disease(GOLD)grade,blood oxygen partial pressure(PaO2)and carbon dioxide partial pressure(PaCO2)between the poor prognosis group and the good prognosis group(P<0.05).GOLD grade,PaCO2,serum IL-17 and eotaxin-3 levels were risk factors for poor prognosis in patients with AECOPD(P<0.05),and PaO2 was a protective factor for poor prognosis in patients with AECOPD(P<0.05).The area under the curve of serum IL-17 and eotaxin-3 combined to predict the prognosis of AECOPD patients was 0.885,the sensitivity was 80.00%,and the specificity was 83.46%,which was better than that of IL-17 and eotaxin-3 a-lone(Zcombiation-IL-17=4.045,P<0.001,Zcombiation-eotaxin-3=3.254,P=0.001).Conclusion The serum levels of IL-17 and eotaxin-3 are increased in AECOPD patients.The combination of IL-17 and eotaxin-3 has predictive value for the prognosis of AECOPD patients.

In recent years, the situation of climate change has intensified, posing a threat to public health. There is an urgent need to promote public health adaptation actions to climate change. In January 2025, the National Disease Control and Prevention Administration issued the "Guidelines for Public Health Adaptation Actions to Climate Change" (hereinafter referred to as the "Guidelines"). The Guidelines put forward 20 items of guidance on six categories of public health adaptation actions, including understanding basic concepts, comprehending important policies, learning core knowledge, paying attention to key populations, practicing a low-carbon lifestyle, and mastering protection skills. It elaborates on the key concepts and the latest policies that the public needs to understand, and also provides the behavioral concepts and protection skills that should be mastered to adapt to climate change. This article provides a systematic interpretation of the Guidelines, introducing the background, ideas, connotations, and applications of their compilation, with the aim of enhancing society′s cognitive understanding of the Guidelines.

In recent years, the situation of climate change has intensified, posing a threat to public health. There is an urgent need to promote public health adaptation actions to climate change. In January 2025, the National Disease Control and Prevention Administration issued the "Guidelines for Public Health Adaptation Actions to Climate Change" (hereinafter referred to as the "Guidelines"). The Guidelines put forward 20 items of guidance on six categories of public health adaptation actions, including understanding basic concepts, comprehending important policies, learning core knowledge, paying attention to key populations, practicing a low-carbon lifestyle, and mastering protection skills. It elaborates on the key concepts and the latest policies that the public needs to understand, and also provides the behavioral concepts and protection skills that should be mastered to adapt to climate change. This article provides a systematic interpretation of the Guidelines, introducing the background, ideas, connotations, and applications of their compilation, with the aim of enhancing society′s cognitive understanding of the Guidelines.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

ObjectiveSerum metabolomics of acute lung injury（ALI） in rats was conducted using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） to explore the similarities and differences in the mechanism of Qingqiao（harvested when the fruits of Forsythiae Fructus were initially ripe and still green in color） and Laoqiao（harvested when the fruits of Forsythiae Fructus were ripe） in the treatment of ALI. MethodA total of 24 SD male rats were acclimatized and fed for 1 week， 6 of them were randomly selected for the blank group and 18 for the experimental group. The ALI model was induced in the experimental group by tracheal intubation with lipopolysaccharide（LPS）. After successfully constructing the ALI model， these rats was randomly divided into model group， Qingqiao group and Laoqiao group， with 6 rats in each group. The Qingqiao and Laoqiao groups were administered orally once a day at a dose of 1.5 g·kg^-1， while the blank and model groups received an equivalent volume of saline for 3 consecutive days. The pathological conditions of rat lung tissues were comprehensively assessed by hematoxylin-eosin（HE） staining， wet-to-dry mass ratio（W/D） of lung tissues， and protein concentration in rat bronchoalveolar lavage fluid（BALF）. The levels of interleukin（IL）-6， IL-1β and tumor necrosis factor（TNF）-α in BALF were quantified using enzyme-linked immunosorbent assay（ELISA）. UPLC-Q-TOF-MS was used to identify and analyze the chemical compositions of Qingqiao and Laoqiao， and serum metabolomics of rats in each group was analyzed， combined with multivariate statistical analysis with variable importance in the projection（VIP） value>1， P<0.05 from t-test， and fold change（FC）≥1.5 or FC≤0.5 to screen the differential metabolites Qingqiao and Laoqiao for the treatment of ALI. The Kyoto Encyclopedia of Genes and Genomes（KEGG） database was used in combination with MetaboAnalyst for the metabolic pathway analysis of the screened differential metabolites. ResultCompared with the blank group， rats in the model group exhibited enlarged alveolar lumen， ruptured alveoli， interstitial hemorrhage， bronchial exudation of a large number of neutrophils and erythrocytes， and a significant increase in the protein concentration in the BALF and the W/D value of the lung tissues（P<0.01）. In contrast， compared with the model group， rats in the Qingqiao group and the Laoqiao group showed reduced bronchial hemorrhage in the lungs， and the protein concentration in the BALF and the W/D value of the lung tissues were significantly decreased（P<0.01）， the lung injury was significantly alleviated， but more obvious in the Qingqiao group. Compared with the blank group， the expression levels of IL-6， IL-1β and TNF-α in the BALF of the model group were significantly higher（P<0.01）. Additionally， compared with the model group， the expression levels of IL-6， IL-1β and TNF-α in the Qingqiao and Laoqiao groups were significantly lower（P<0.01）. The chemical composition analysis of Qingqiao and Laoqiao revealed that 63 components were detected in Qingqiao and 55 components were detected in Laoqiao， with 47 common components， 16 components unique to Qingqiao and 8 components unique to Laoqiao. Characterizing the differences in serum metabolomics in rats， 19 and 12 metabolites were called back by Qingqiao and Laoqiao， respectively. The metabolic pathway enrichment analysis showed that Qingqiao exerted its therapeutic effects by affecting 6 key metabolic pathways， including linoleic acid metabolism， phenylalanine metabolism， phenylalanine， tyrosine and tryptophan biosynthesis， glycerophospholipid metabolism， α-linolenic acid metabolism， and arachidonic acid metabolism， and Laoqiao exerted therapeutic effects by affecting 6 key metabolic pathways， including linoleic acid metabolism， arachidonic acid metabolism， sphingolipid metabolism， phenylalanine metabolism， ascorbate and aldarate metabolism， and glycerophospholipid metabolism. ConclusionQingqiao and Laoqiao have therapeutic effects on ALI， and Qingqiao is more effective. Both of them can play a therapeutic role in ALI by regulating amino acid metabolism and lipid metabolism， but the metabolic pathways affected by them are different.

This paper reviews the current situation of dementia care in the emergency setting at home and abroad, and compares the contents of person-centred care practices, such as identifying and assessing dementia patients, changing caregivers ′ attitudes, creating a good emergency environment, and mastering and providing effective nurse-patient communication, with the aim of providing a reference basis for developing a standardised care plan for dementia patients in the emergency setting, with a view to providing more scientific and efficient emergency care for dementia patients.

Objective:To investigate the current status of pertussis laboratory diagnosis and confirmed pertussis cases reporting in Shaanxi Province, and evaluate the quality of case reports.Methods:The information of confirmed pertussis cases reported in Shaanxi Province from January to July 2022 was collected through the China Disease Control and Prevention Information System. The laboratory diagnostic methods and pertussis vaccine immunization history of confirmed cases were investigated, and the descriptive epidemiological method was used for statistical description.Results:Of the 164 confirmed cases of pertussis reported from January to July 2022, two were not tested in the laboratory and 162 were tested in the laboratory. The proportions of different detection methods were 1.85% (3/162) of isolation and culture, 31.48% (51/162) of serum antibody IgG, 14.20% (23/162) of serum antibody IgM, 49.38% (80/162) of serum antibody PCR and 3.09% (5/162) of serum antibody IgM+ PCR. Among the 79 serological positive cases, 12 cases (15.19%)had no history of pertussis immunization, and 15 cases (18.99%), 11 cases (13.92%) and 41 cases (51.90%) had the time interval from vaccination to detection of <1 year, 1-3 years and >3 years, respectively. Based on the analysis of laboratory testing methods and vaccination history, 38 cases were misdiagnosed/misreported among 164 cases, with a misdiagnosis or misreported rate of 23.17%. There were 17, 12 and 9 cases of misdiagnosis/misreport in 0-2 years old group, 3-6 years old group and≥7 years old group, and the misdiagnosis or misreported rates were 27.42%(17/62), 26.67%(12/45) and 15.79%(9/57), respectively.Conclusions:The selection of pertussis laboratory testing methods in some medical institutions in Shaanxi Province is incorrect, which leads to a certain proportion of misdiagnosis or misreport, and it is necessary to further strengthen the training and standardization.

Objective:To construct an evaluation index system for the core competence of hospital specialist service operation assistants and provide reference for the evaluation of such competence.Methods:From January to March 2022, literature analysis and behavioral event interviews were used to initially establish a core competence evaluation index system of hospital specialist service operation assistants, based on the Donabedian model. Subsequently, the Delphi expert consultation method was applied to conduct correspondence consultation, inviting experts to evaluate the contents and importance of the index system, using analytic hierarchy process to determine the weights of the indexes at all levels.Results:Two rounds of expert consultation were carried out, and the valid recovery rate of the questionnaire was 100%. The familiarity coefficient of the second round of correspondence was 0.87, the basis of judgment coefficient was 0.90, and the authority coefficient was 0.89. The final evaluation index system for core competence of hospital specialist service operation assistant consisted of 3 first-level indexes, 13 second-level indexes and 81 third-level indexes. The weight of the first-level index structure index was 0.266, and the highest weight among the second-level indexes was the operational development ability (0.083), while the highest weight among the third-level indexes of operational development ability was the comprehensive coordination ability (0.193); The weight of the first-level index process index was 0.405, and the corresponding second-level and third-level indexes with the highest weight were department operation practice work (0.157) and reasonable resource allocation (0.303), respectively; The weight of the first-level index result index was 0.329, and the corresponding second-level and third-level indexes with the highest weight were the weight of medical quality and safety (0.103) and drug adverse reaction reporting rate (0.237), respectively.Conclusions:The evaluation index system constructed in this study proves scientific and reasonable in weight assignment, proving a reference for the management of the specialist service operation assistants.