OBJECTIVE: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy

OBJECTIVE: EPF3 is a fibrinolysin monomer isolated and purified from Pheretima vulgaris Chen, an earthworm used in traditional Chinese medicine as Dilong for treating blood stasis syndrome. Its composition, anticoagulant and fibrinolytic activities, and relevant mechanisms have been confirmed through in vitro experiments. However, whether it has antithrombotic effects in vivo and can be absorbed by the gastrointestinal tract is unknown. This study evaluates the antithrombotic effect in zebrafish and investigates the gastrointestinal stability and intestinal absorption mechanism of this protein in vitro. METHODS: The antithrombotic effect of EPF3 in vivo was verified using the zebrafish thrombus model induced by arachidonic acid and FeCl₃. Then, the protein bands of EPF3 incubated with simulated gastric fluid (SGF), simulated intestinal fluid (SIF), and homogenate of Caco-2 cells (HC2C) were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis to evaluate its gastrointestinal stability. Finally, the transport behavior and absorption mechanism of EPF3 were studied using Caco-2 cell monolayer. RESULTS: EPF3 could significantly enhance the returned blood volume and blood flow velocity in zebrafish with platelet aggregation thrombus induced by arachidonic acid. It could also prolong the formation time of tail artery thrombus and increase the blood flow velocity in zebrafish with vessel injury thrombus induced by FeCl₃. EPF3 was stable in SIF and HC2C and unstable in SGF. The permeability of EPF3 in Caco-2 monolayer was time-dependent and concentration-dependent. The efflux ratio was less than 1.2 during transport, and the transport behavior was not affected by inhibitors. EPF3 could reversibly reduce the expression of tight junction-related proteins, including zonula occludens-1, occludin, and claudin-1 in Caco-2 cells. CONCLUSION EPF3 could play a thrombolytic and antithrombotic role in zebrafish. It could be transported and absorbed into the intestine through cellular bypass pathway by opening the intestinal epithelium tight junction. This study provides a scientific explanation for the antithrombotic effect of earthworm and provides a basis for the feasibility of subsequent development of EPF3 as an antithrombotic enteric-soluble preparation. Please cite this article as: Zhong WL, Yang JQ, Liu H, Wu YL, Shen HJ, Li PY, Du SY. Antithrombotic effect in zebrafish of a fibrinolytic protein EPF3 from Dilong (Pheretima vulgaris Chen) and its transport mechanism in Caco-2 monolayer through cell bypass pathway. J Integr Med. 2025; 23(4): 415-428.
Animals ; Zebrafish ; Humans ; Caco-2 Cells ; Fibrinolytic Agents/pharmacology* ; Thrombosis/drug therapy* ; Intestinal Absorption

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective:To investigate the relationship between 18F-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography(18F-FDG PET/CT)and tumor markers and the prognosis of patients with differentiated thyroid cancer(DTC)treated with surgery combined with iodine-131,and to construct a nomogram prediction model.Methods:The clinical data of 134 patients with DTC who underwent surgery combined with iodine-131 treatment in our hospital from January 2021 to January 2023 were retrospectively analyzed.According to the prognosis after 1 year of treatment,they were divided into a good prognosis group(n=106)and a poor prognosis group(n=28).The general data,18F-FDG PET/CT related parameters[maximum standardized uptake value(SUVmax),metabolic volume(MTV),total lesion gly-colysis(TLG)]and serum tumor markers[thyroglobulin(Tg),thyroglobulin antibody(TgAb)]levels were compared between the two groups.Pearson correlation coefficient was used to analyze the correlation between the related parameters and the tumor marker levels.Logistic multivariate analysis was used to analyze the influencing factors of DTC prognosis.Re-ceiver operating characteristic curve(ROC)was used to analyze the predictive efficacy of related parameters combined with tumor markers on poor prognosis.Anomogram prediction model for poor prognosis was constructed and the predic-tive efficacy of the model was evaluated.Results:The proportion of stage Ⅲ-Ⅳ,the proportion of total resection and the levels of thyroid stimulating hormone(TSH),SUVmax,MTV,TLG,Tg and TgAb in the poor prognosis group were higher than those in the good prognosis group,and the differences were statistically significant(P<0.05).Pearson correlation co-efficient showed that SUVmax,MTV,TLG and Tg,TgAb levels were positively correlated with tumor markers(P<0.05).Lo-gistic analysis showed that after adjusting for confounding variables,SUVmax,MTV,TLG,Tg and TgAb were independent influencing factors for the poor prognosis of DTC(P<0.05).ROC analysis showed that the combination of SUVmax,MTV,TLG,Tg and TgAb was significantly better than each parameter alone in predicting poor prognosis(P<0.05).The nomo-gram prediction model was constructed.ROC evaluation showed that the model had good prediction performance.K-fold cross validation showed that the model had stable performance and good generalization ability.Conclusion:The 18F-FDG PET/CT related parameters SUVmax,MTV,TLG and tumor markers Tg and TgAb are all independent factors affecting the poor prognosis of DTC patients treated with surgery combined with iodine-131.The prognostic nomogram prediction model based on the above factors has good predictive efficacy and can be used to guide clinical decision-making.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Objective:To investigate the relationship between 18F-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography(18F-FDG PET/CT)and tumor markers and the prognosis of patients with differentiated thyroid cancer(DTC)treated with surgery combined with iodine-131,and to construct a nomogram prediction model.Methods:The clinical data of 134 patients with DTC who underwent surgery combined with iodine-131 treatment in our hospital from January 2021 to January 2023 were retrospectively analyzed.According to the prognosis after 1 year of treatment,they were divided into a good prognosis group(n=106)and a poor prognosis group(n=28).The general data,18F-FDG PET/CT related parameters[maximum standardized uptake value(SUVmax),metabolic volume(MTV),total lesion gly-colysis(TLG)]and serum tumor markers[thyroglobulin(Tg),thyroglobulin antibody(TgAb)]levels were compared between the two groups.Pearson correlation coefficient was used to analyze the correlation between the related parameters and the tumor marker levels.Logistic multivariate analysis was used to analyze the influencing factors of DTC prognosis.Re-ceiver operating characteristic curve(ROC)was used to analyze the predictive efficacy of related parameters combined with tumor markers on poor prognosis.Anomogram prediction model for poor prognosis was constructed and the predic-tive efficacy of the model was evaluated.Results:The proportion of stage Ⅲ-Ⅳ,the proportion of total resection and the levels of thyroid stimulating hormone(TSH),SUVmax,MTV,TLG,Tg and TgAb in the poor prognosis group were higher than those in the good prognosis group,and the differences were statistically significant(P<0.05).Pearson correlation co-efficient showed that SUVmax,MTV,TLG and Tg,TgAb levels were positively correlated with tumor markers(P<0.05).Lo-gistic analysis showed that after adjusting for confounding variables,SUVmax,MTV,TLG,Tg and TgAb were independent influencing factors for the poor prognosis of DTC(P<0.05).ROC analysis showed that the combination of SUVmax,MTV,TLG,Tg and TgAb was significantly better than each parameter alone in predicting poor prognosis(P<0.05).The nomo-gram prediction model was constructed.ROC evaluation showed that the model had good prediction performance.K-fold cross validation showed that the model had stable performance and good generalization ability.Conclusion:The 18F-FDG PET/CT related parameters SUVmax,MTV,TLG and tumor markers Tg and TgAb are all independent factors affecting the poor prognosis of DTC patients treated with surgery combined with iodine-131.The prognostic nomogram prediction model based on the above factors has good predictive efficacy and can be used to guide clinical decision-making.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Objective: To explore prevalence and associated factors of nonalcoholic fatty liver disease (NAFLD) in overweight and obese children in Hohhot City, so as to provide the oretical basis for developing health education plans and implementing prevention and treatment of NAFLD in children. Methods: A total of 156 overweight and obese children was enrolled from 4 primary schools in Hohhot City using cluster sampling method during 28th Aug. 2022 to 5th Mar. 2023. Height and weight were measured and body mass index was calculated, and fasting blood was taken in the early morning for fasting blood glucose, alanine aminotransferase, aspartate aminotransferase. Single factor analysis was conducted using ttest, χ2 test and Fishers exact probability method, while multivariate analysis was conducted using Logistic regression analysis and subject characteristic curves. Results: The differences in age, waist circumference, hip circumference, fasting glucose, alanine aminotransferase, aspartate aminotransferase, gamma glutamyltransferase, uric acid, and triglyceride were statistically significant between the nonNAFLD and the NAFLD group (U/t=1 070.0-2 164.0, P<0.05). Significant differences were observed in aspartate aminotransferase (AST) and uric acid levels (AST OR=1.16, 95%CI=1.04-1.28; uric OR=1.01, 95%CI=1.00-1.01, P<0.05). The area under a receiver operating characteristic were 0.737 for aspartate aminotransferase and 0.665 for uric acid, respectively. Conclusions The prevalence of NAFLD is high in overweight/obese children in Hohhot, and both elevated aspartate aminotransferase and hyperuricemia could increase the risk of NAFLD in overweight/obese children. Special attention should be paid to the NAFLD in overweight and obese children. It is recommended to reduce both BMI and uric level in the prevention and treatment of NAFLD to achieve better treatment outcomes.