Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

With the rapid evolution of artificial intelligence,machine learning has become widely applied in the realm of acupuncture clinical research.However,in comparison to the extensive utilization of supervised and unsupervised learning,attempts at employing reinforcement learning in the field of acupuncture clinical research remain relatively limited.In this article,we briefly introduce the concept and process of reinforcement learning,elucidating distinctions from both supervised and unsupervised learning.Then we discuss the potential applications of reinforcement learning in acupuncture clinical research,and summarizes the challenges that may arise during its implementation.Furthermore,a preliminary discussion on potential solutions to these issues is presented.Finally,a contemplation is offered on the combination of reinforcement learning with acupuncture clinical research,anticipating a meaningful reference for the advancement of reinforcement learning in the exploration and application within acupuncture clinical research and practice.

Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

Objective To analyze the research literature on fire needling therapy published on China National Knowledge Infrastructure(CNKI),Wanfang Data Knowledge Service Platform(Wanfang),and China Science and Technology Journal Database(VIP)in the last 20 years,and to explore the current status and the hotspots of the research,thus to summarize and analyze the spectrum of the dominant diseases and technological transformations of fire needling therapy.Methods CiteSpace and VOSviewer were applied to analyze the keywords,authors and institutions,to draw the scientific knowledge map,and to summarize the disease spectrum.Results A total of 4 226 literature were included,from 2000 to 2023,the number of publications on fire needling therapy research showed an increasing trend,with each of the four periods showing its own characteristics of the times.The"filiform fire needling"and"pricking of fire needling"were widely used as acupuncture tools and acupuncture techniques in the studies,the emergence of high-frequency disease keywords such as"shingles""vitiligo"and"acne"indicates that research on the treatment of skin diseases with fire needling has attracted much attention.The disease spectrum of fire needling therapy was enlarged,involving a total of 356 diseases distributed in 20 disease systems.Conclusion Skin diseases and arthralgia became the dominant diseases of fire needling therapy,the rise of research hot words such as"acne vulgaris""vitiligo""stroke""chronic eczema""filiform fire needling"and"Lingnan fire needling"indicates that fire needling therapy is developing towards research standardization,theoretical diversification and disease diversification.

With the rapid evolution of artificial intelligence,machine learning has become widely applied in the realm of acupuncture clinical research.However,in comparison to the extensive utilization of supervised and unsupervised learning,attempts at employing reinforcement learning in the field of acupuncture clinical research remain relatively limited.In this article,we briefly introduce the concept and process of reinforcement learning,elucidating distinctions from both supervised and unsupervised learning.Then we discuss the potential applications of reinforcement learning in acupuncture clinical research,and summarizes the challenges that may arise during its implementation.Furthermore,a preliminary discussion on potential solutions to these issues is presented.Finally,a contemplation is offered on the combination of reinforcement learning with acupuncture clinical research,anticipating a meaningful reference for the advancement of reinforcement learning in the exploration and application within acupuncture clinical research and practice.

This study was designed to evaluate the correlation between immune antibodies and pelvic inflammatory disease(PID)using retrospective analysis.Cases were selected from 171 patients who met the diagnosis of PID in Liuzhou People's Hospital of Guangxi Province from January 2022 to March 2023,and the PID patients were further divided into simple PID group(53 cases)and in PID combined with reproductive tract infection group(118 cases)according to the presence or absence of reproductive tract infections,while 83 cases of women who did not meet the specific diagnostic criteria of PID and did not have reproductive tract infections were selected as the control group during the same period.The positive rate of immune antibodies in the three groups were observed and compared to explore the relationship between immune antibodies and PID.Data showed that the positive rates of immune antibodies were significantly higher in the PID alone group and the PID combined with reproductive tract infection group than that in the control group.Furthermore,the positive rate of immune antibody TPOAb was significant difference in the PID combined with reproductive tract infection group and the PID alone group(P<0.05).In conclusion,TPOAb is closely associated with reproductive tract infections.

Objective To investigate the prognostic value of plasma thrombomodulin(TM)in patients with septic shock.Methods A retrospective analysis was conducted on the clinical data of 180 patients with septic shock admitted to the intensive care unit of the 908th Hospital from May 2018 to November 2022.The patients were divided into survival group(106 cases)and death group(74 ca-ses)based on the 30-day follow-up outcomes.Propensity score matching(PSM)was used to match 57 surviving patients with 57 de-ceased patients in a 1∶1 ratio,based on confounding factors such as age,gender,underlying diseases,primary infection site,laborato-ry results and disease severity scores.TM and other coagulation molecular markers were compared between the two groups,and logistic regression,receiver operating characteristic(ROC)curve,survival and correlation analyses were performed.Results After PSM,the TM levels in the death group(18.3[13.2,22.3]TU/mL)were significantly higher than those in the survival group(13.7[9.0,18.3]TU/mL)(P＜0.05).Multivariate logistic regression analysis showed that TM was an independent risk factor for 30-day mortality in the patients with septic shock(OR=1.137,95％CI:1.023-1.262,P＜0.005).ROC curve analysis revealed that the areas under the curve(AUCs)for predicting 30-day mortality were 0.665,0.627 and 0.600 for TM,Acute Physiology and Chronic Health EvaluationⅡ(APACHE Ⅱ)and Sequential Organ Failure Assessment(SOFA)scores,respectively.Kaplan-Meier survival analysis stratified by the optimal TM cut-off value(17.9 TU/mL)showed that the 30-day survival rate of the TM＜17.9 TU/mL group was 1.56 times that of the TM≥17.9 TU/mL group(Log-Rank test,P＜0.000 1).Spearman correlation analysis demonstrated that TM levels were positively correlated with APACHE Ⅱ(r=0.10,P＜0.005)and SOFA scores(r=0.35,P＜0.005).Conclusion Plasma TM has showed a good predictive value for assessing the prognosis of patients with septic shock and may serve as a potential biomarker for determining the prognosis of septic shock.

Objective To investigate the clinical values of heparinase-modified thromboelastography(hmTEG)in heparin monitoring during continuous renal replacement therapy.Methods A total of 97 cases who were undergoing continuous renal replacement therapy(CRRT)in the intensive care unit of the 94th People's Liberation Army Hospital from Jan 2014 to Jun 2019 were enrolled in this stud-y.The patients were divided into TEG group and APTT group according to different means of heparin monitoring during continuous renal replacement therapy.In total,278 hemofilters were used in all the blood purification therapies.Complication of bleeding,CRRT time,total heparin dose and SOFA(sequential organ failure assessment)score of the patients were compared between the TEG and APTT groups.The filter life span and survival time in hospital were also compared using Kaplan-Meier analysis.Rusults Compared with APTT group,the total heparin dose in TEG group were significantly higher(P＜0.05).The CRRT time of patients and the average filter life span in TEG group were significantly longer than those of APTT group(P＜0.05).Compared to APTT group,the 28-day SOFA in TEG group was significantly lower(P＜0.05).Survival analysis showed that the 28-day risk of death in the patients of APTT group was 2.01 times higher than that in TEG group(P＜0.05).The 72-hour filter life of TEG group was significantly longer than that of APTT group(P＜0.05).Conclusion The use of hmTEG for monitoring heparin in blood purification should be superior in terms of safety and efficacy with longer filter life span and higher survival rate of patients.

Cohort study is one of the important research methods in analytical epidemiology because of its clear time sequence relationship, which is better than other observational studies in demonstrating causal association. However, screening diagnosis or other methods are often used to exclude the individuals with outcome events during the enrollment process of the subjects in cohort studies. The accuracy of screening diagnosis and the effectiveness of exclusion will affect the accuracy of the baseline status assessment of the subjects included in the study, which may lead to the causal time sequence reversal of exposure-outcome in the estimation of causal effect. Landmark analysis can be used to control reverse causality by excluding subjects with potentially unknown expose-outcome timing. In this paper, we describe the basic principles and analytical steps of landmark analysis, and use data from the Chinese Longitudinal Healthy Longevity Survey to explore the relationship between physical activity and frailty, and introduce the specific application of landmark analysis for the purpose of facilitating its application and inferring causal effects more accurately in cohort studies.

With completing a baseline survey of a large natural population cohort, conducting regular follow-up has become a key factor in further improving the quality of cohort construction and ensuring its sustainable development. Typical cohort follow-up methods include repeat surveys, routine monitoring, and community-oriented surveillance. However, in practical applications, there are often issues such as high costs, difficulty, and high error rates. Telephone follow-up is an important supplementary method to the methods mentioned above, as it has the characteristics of low cost, fast response, and high quality. However, the with difficult organization, quality control is challenging, response rates are low, and management levels vary widely, which limits its widespread use in large-scale population cohort studies. Given the above problems, this study draws on customer relationship management based on the actual needs of the China Northwest Cohort follow-up. It relies on the REDCap electronic data collection platform to build a telephone follow-up management and quality control system. Targeted solutions are provided for key issues in telephone follow-up implementation, including organizational structure, project management, data collection, and process quality control, to improve the quality control level of telephone follow-up comprehensively and thereby enhance the quality and efficiency of follow-up. We hope to provide standardized follow-up programs and efficient quality control tools for newly established and existing cohort studies.