Objective To investigate the role of myeloid dendritic cells(mDC)in the pathogenesis of ankylosing spondylitis (AS),and to study the mechanism of tumour necrosis factor (TNF)-α blocker on the treatment of AS by counting the number of mDC before and after the treatment.Methods Peripheral blood from 21 AS patients treated with 50 mg rhTNFR-Fc and 15 AS patients treated with placebo were investigated at week 0,week 2 and week 6 in a randomized,double-blind,placebo-controlled trial.Three-color flow cytometry analysis was used to investigate the change of the number of mDC before and after the treatment.And their correlation with the clinical parameters was analyzed.Results MHC Class Ⅰ positive mDC(Lin-/CD11c+/HLA-abc+)in AS patients was slightly less than in healthy controls (not statistically significant).No significant change in MHC Class Ⅰ mDC number was observed after drug treatment.The number of MHC Class Ⅱ mDC cells was not correlated with clinical parameters.Conclusion The treatment with rhTNFR-Fc in AS induces a significant upregnlation of MHC-Ⅱ DC.

ObjectiveTo study the effect of menbranous milkvetch root parenteral solution on insulin resistance of gerontism cerebral infarction in recovery stage.Methods66 patients with gerontism cerebral infarction were randomly divided into therapy group(33 cases) which received membranous milkvetch root parenteral solution and control group(33 cases).Both groups adopted routine treatment at the same time, the period was 20 days. Insulin(Ins), free blood sugar(FBS), total cholesterol(CH), triglyceride(TG), hemorheology and insulin resistance(indicating by index of insulin sensitive) of blood on empty stomach were evalutated before and after treatment. ResultsAfter treatment there was decrease in CH, FBS, FINS in therapy group than in control group(P<0.01 or P<0.05); the clinical effect in therapy group was better than in control group(P<0.01).ConclusionMembranous milkvetch root parenteral solution can significantly decrease insulin resistance, blood lipin, blood viscosity in recovery stage of gerontism cerebral infarction, and improve clinical efficiency.

Objective To study the influence of clinical nutritional support on the effects of mechanical ventilation (MV), and to find the factors affecting the outcome of patients undergoing MV. Methods A case-control study was conducted. The clinical data of 235 patients undergoing MV admitted to intensive care unit (ICU) of Tongde Hospital of Zhejiang Province from January 2015 to June 2017 were retrospectively analyzed. The patients were divided into two groups according to whether weaning successfully within 7 days. The clinical data of patients in the two groups were collected including gender, age, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score, underlying disease, nutritional indicators, nutritional support, and complications. The outcome of withdrawal within 7 days was served as a dependent variable, all observed indicators were served as independent variables, and Logistic regression analysis was carried out to screen the influencing factors of the weaning results within 7 days. Results 235 patients undergoing MV were enrolled, 128 patients were successfully withdrawn within 7 days, and 107 were unsuccessfully withdrawn. Compared with the successful weaning group, the patients of weaning failure group were older, and had higher APACHEⅡ score and lower albumin (Alb) and hemoglobin (Hb), more patients with internal medical underlying diseases and receiving parenteral nutrition (PN) and mixed nutrition, and the incidences of secondary infection, vomiting, abdominal distension, abnormal bowel sound, gastric retention, and diarrhea were higher. However, there was no statistical significance in gender between the two groups. The variables of statistical significance in univariate analysis were enrolled in the multifactor analysis model showing that age [odds ratio (OR) = 1.269, 95% confidence interval (95%CI) = 1.119-1.439, P < 0.001], APACHEⅡ score (OR = 1.643, 95%CI = 1.423-1.897, P < 0.001), internal medical underlying diseases (OR = 6.298, 95%CI = 4.012-9.887, P < 0.001), secondary infection (OR = 8.323, 95%CI = 2.568-26.975, P < 0.001), abdominal distension (OR = 3.368, 95%CI = 1.586-7.152, P = 0.002), abnormal bowel sounds (OR = 2.856, 95%CI = 1.215-6.713, P = 0.017), gastric retention (OR = 1.996, 95%CI = 1.183-3.368, P = 0.010), diarrhea (OR = 3.035, 95%CI = 1.337-6.890, P = 0.008) were risk factors for unsuccessful weaning,and compared with PN, enteral nutrition (EN; OR = 0.191, 95%CI = 0.098-0.372, P < 0.001) and mixed nutrition (OR = 0.375, 95%CI = 0.150-0.938, P = 0.037) were protective factors of successful weaning. The gender, Alb and Hb before and after MV, vomiting, gastrointestinal hemorrhage were not associated with weaning outcome within 7 days. Conclusions Elder, high APACHEⅡ score, internal medical underlying diseases, or secondary infection, abdominal distension, abnormal bowel sounds, gastric retention, diarrhea were risk factors of weaning failure within 7 days in patients undergoing MV. Compared with PN, EN and mixed nutrition were protective factors for successful weaning. For patients undergoing MV, EN should be performed early in the case of full recovery, hemodynamic stability, and serious metabolic disorders.

Objective To analyze the changes of endoplasmic reticulum stress (ERS) in the spleen of water-improving fluorosis rat,to explore the mechanism of fluoride-induced immune system damage,and to provide a scientific basis for prevention and control of endemic fluorosis.Methods Forty-eight male Wistar rats of SPF grade were randomly divided into control group and low,medium and high fluoride dose groups according to body mass (120-140 g),12 rats in each group.The sodium fluoride (NaF) content was 0,50,100 and 150 mg/L,respectively.The animals were allowed free access to water and food.After 12 weeks of fluoride exposure,6 rats in each group were selected to isolate the spleen;the remaining rats in each group were changed to drink distilled water containing no NaF,and the spleen was separated after 12 weeks of feeding.The levels of mRNA of glucoseregulated protein (GRP78),spliced X-box binding protein 1 (XBP1-s),activating transcription factor 4 (ATF4),homologous protein (CHOP) and cysteine containing aspartate specific protease 12 (Caspase-12) in spleen were determined by quantitative real-time PCR (qRT-PCR).Results Before the water-improving,the expressions of GRP78 (1.00 ± 0.09,1.69 ± 0.35,1.39 ± 0.29,1.19 ± 0.19),XBP1-s (1.00 ± 0.12,1.40 ± 0.23,1.24 ± 0.26,1.38 ± 0.11),ATF4 (1.00 ± 0.17,1.86 ± 0.56,2.33 ± 0.55,1.95 ± 0.74),CHOP (1.00 ± 0.53,2.84 ± 0.68,3.06 ± 1.29,2.50 ± 0.35) and Caspase-12(1.00 ± 0.12,1.90 ± 0.29,1.56 ± 0.35,1.76 ± 0.23) mRNA in the control group and low,medium and high fluoride dose groups were statistically significant (F =8.45,5.38,6.38,8.21,11.31,P ＜ 0.05).Except for the GRP78 in high fluoride dose group,the above indicators in fluoride groups were higher than the control group (P ＜ 0.05).After the water-improving,the expressions of GRP78 (1.00 ± 0.36,0.75 ± 0.13,0.98 ± 0.41,0.47 ± 0.19),XBP1-s (1.00 ± 0.25,0.70 ± 0.06,0.74 ± 0.17,0.65 ± 0.21),ATF4 (1.00 ± 0.51,0.66 ± 0.09,0.91 ± 0.34,0.81 ± 0.29),CHOP (1.00 ± 0.36,0.92 ± 0.12,0.84 ± 0.16,0.67 ± 0.20) and Caspase-12 (1.00 ± 0.45,0.65 ± 0.11,0.65 ± 0.25,0.51 ± 0.27) mRNA in the control group and low,medium and high fluoride dose groups were not statistically significant (P ＞ 0.05).Before and after the water-improving,the expressions of XBP1-s,ATF4,CHOP and Caspase-12 mRNA were statistically significant in fluoride groups (P ＜ 0.05),and the GRP78 only had a statistically significant difference in the low fluoride dose group (P ＜ 0.05).Conclusions Fluoride exposure causes ERS response in rat spleen,up-regulation of ERS-related gene expression,which is decreased after water-improving,and the ERS response is weakened.The water-improving may contribute to the recovery of fluoride-induced immune function damage.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts. METHODS: We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models. RESULTS: The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749). CONCLUSIONS: The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population. TRIAL REGISTRATION Chictr.org, ChiCTR 1800018895.
Humans ; Aged ; Sarcopenia/diagnosis* ; Deep Learning ; Aging ; Algorithms ; Biomarkers