Objective To estimate the flexion and extension torques of the hip,knee,and ankle joints during straight-line walking using depth cameras and neural networks.Methods Gait information was collected from 20 individuals using an optical motion capture system,force plates,and an Azure Kinect depth camera.The subjects were asked to walk straight at their preferred speed while stepping on the force plates.The joint torques were obtained using visual 3D simulation as a reference value,and an artificial neural network(ANN)and long short-term memory(LSTM)network were trained to estimate the joint torques.Results The relative root mean square errors(rRMSEs)of the ANN model for estimating the joint torques of hip,knee,and ankle were 15.87％-17.32％,18.36％-25.34％,and 14.11％-16.82％,respectively,and the correlation coefficients were 0.81-0.85,0.69-0.74 and 0.76-0.82,respectively.The LSTM model had a better estimation effect,with rRMSEs of 8.53％-12.18％,14.32％-18.78％,and 6.51％-11.83％,and correlation coefficients of 0.89-0.95,0.85-0.91 and 0.90-0.97,respectively.Conclusions This study confirms the feasibility of using a depth camera and neural network for noncontact estimation of lower limb joint torques,and LSTM has a better performance.Compared with existing studies,the joint torque estimation results have better accuracy,and the potential application scenarios include telemedicine,personalized rehabilitation program development,and orthosis-assisted design.

Lymphatic metastasis is the main metastatic route for colorectal cancer, which increases the risk of cancer recurrence and distant metastasis. The properties of the lymph node metastatic colorectal cancer (LNM-CRC) cells are poorly understood, and effective therapies are still lacking. Here, we found that hypoxia-induced fibroblast activation protein alpha (FAPα) expression in LNM-CRC cells. Gain- or loss-function experiments demonstrated that FAPα enhanced tumor cell migration, invasion, epithelial-mesenchymal transition, stemness, and lymphangiogenesis via activation of the STAT3 pathway. In addition, FAPα in tumor cells induced extracellular matrix remodeling and established an immunosuppressive environment via recruiting regulatory T cells, to promote colorectal cancer lymph node metastasis (CRCLNM). Z-GP-DAVLBH, a FAPα-activated prodrug, inhibited CRCLNM by targeting FAPα-positive LNM-CRC cells. Our study highlights the role of FAPα in tumor cells in CRCLNM and provides a potential therapeutic target and promising strategy for CRCLNM.

Objective To explore the correlation of serum Chemerin level with disease activity and the ratio of T helper 17/regulatory T cells(Th17/Treg)in patients with rheumatoid arthritis(RA).Methods A total of 180 patients with RA who were admitted to our hospital were regarded as the observation group.According to the DAS28 score,the observation group was divided into the high activity group(60 cases),the moderate activity group(60 cases)and the low activity group(60 cases).Another 180 healthy people who underwent physical examination in our hospital during the same period were regarded as the control group.Enzyme-linked immunosorbent assay(ELISA)was used to detect serum levels of Chemerin,interleukin-9(IL-9),interleukin-10(IL-10)and interleukin-17(IL-17).Flow cytometry was used to detect the Th17/Treg ratio.Spearman correlation analysis was applied to analyze the correlation between serum Chemerin level and DAS28 score.Pearson correlation analysis was used to analyze the correlation between serum Chemerin level and Th17,Treg cell percentage and Th17/Treg ratio.Results The results of this study showed that the serum level of Chemerin was higher in the observation group than that in the control group(P＜0.05).The serum Chemerin level was positively correlated with DAS28 score(P＜0.05).Serum Chemerin levels and DAS28 scores decreased in turn in the high,moderate and low activity groups(P＜0.05).The percentage of Th17 cells and the ratio of Th17/Treg were higher in the observation group than those in the control group,and the percentage of Treg cells was lower in the observation group than that in the control group(P＜0.05).The level of IL-10 was lower in the observation group than that in the control group,while levels of IL-17 and IL-9 were higher in the observation group than those in the control group(P＜0.05).The results of Pearson correlation analysis showed that serum Chemerin level was positively correlated with the percentage of Th17 cells and the ratio of Th17/Treg,and negatively correlated with the percentage of Treg cells(P＜0.05).Conclusion Serum Chemerin level is elevated in patients with RA,which is closely related to disease activity and Th17/Treg ratio.

Objective:To explore the correlation between time in range (TIR) after short-term treatment and glycated hemoglobin after 3 months (HbA lc-3m) in patients with newly-diagnosed type 2 diabetes mellitus (T2DM). Methods:In this cross-sectional study, a total of 94 patients with newly-diagnosed T2DM who received treatment in the Department of Endocrinology of Inner Mongolia Autonomous Region People′s Hospital were enrolled from January 2018 to September 2022. The patients were followed-up for 3 months and had complete medical record. TIR was divided into three groups according to different target ranges of blood glucose (TIR1: TIR with blood glucose between 3.9 and 10.0 mmol/L, TIR2: TIR with blood glucose between 3.9 and 7.8 mmol/L, TIR3: TIR with fasting, premeal or bedtime blood glucose <6.1 mmol/L and 2 h postprandial blood glucose <8.0 mmol/L). The patients were divided into two groups based on whether their HbA 1c-3m level was less than 6.5%, and the baseline data and variations in TIR for distinct target glucose levels were compared between the two groups. Spearman′s correlation analysis and binary logistic regression analysis were used to analyze the relationship between baseline indicators, TIR after short-term treatment and HbA 1c-3m. Receiver operating characteristic curve (ROC) was drawn to evaluate the predictive ability of different TIR after short-term therapy for HbA 1c-3m. Results:There were statistically significant differences in TIR1 [81.0 (67.5, 94.6)% vs 71.4 (51.7, 85.7)%], TIR2 [57.7 (29.7, 70.8)% vs 40.9 (22.4, 52.3)%] and TIR3 [23.8 (10.2, 39.5)% vs 13.0 (4.8, 25.0)%] between patients with a HbA 1c-3m<6.5% and patients with a HbA 1c-3m≥6.5% (all P<0.05). Spearman correlation analysis showed that among all the patients with newly-diagnosed T2DM, TIR1, TIR2 and TIR3 were all negatively correlated with HbA 1c-3m [6.4 (6.1, 6.9)%] ( r=-0.322, -0.348, -0.303, respectively, all P<0.01). Logistic regression analysis showed that after adjusting for the confounding factors, TIR1 ( OR=1.021, 95% CI: 1.002-1.041; P=0.034), TIR2 ( OR=1.024, 95% CI: 1.006-1.043; P=0.011), TIR3 ( OR=1.037, 95% CI: 1.010-1.065; P=0.008) were all independently related to HbA 1c-3m. When HbA lc-3m<6.5% was taken as the target value, the area under the ROC curve: TIR1 was 0.639 (95% CI: 0.528-0.751), TIR2 was 0.671 (95% CI: 0.560-0.782), TIR3 was 0.659 (95% CI: 0.549-0.770), respectively. When HbA lc-3m<7.0% was taken as the target value, the area under the ROC curve: TIR1 was 0. 730 (95% CI: 0.619-0.841), TIR2 was 0.744 (95% CI: 0.642-0.846), TIR3 was 0.701 (95% CI: 0.588-0.814). There was no significant difference in the area among the three statistics ( P>0.05). Conclusions:For newly-diagnosed T2DM patients, TIR after short-term treatment is negatively correlated with HbA 1c after 3 months and has good predictive value for it.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.