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University students always suffer from technostress and experience burnout during technology-enhanced learning (TEL). Research revealing whether and how university support contributes to eliminate them lacks. This study aims to investigate the structural relationship among "university support" (i.e., "administration support" and "peer support"), students' "ICT competence," "technostress," and "learning burnout." Altogether 1,785 students studying at three Chinese universities participated in this study by filling out a self-reported questionnaire revised from previous literatures and validated with confirmatory factor analysis (CFA). Structural equation modelling (SEM) revealed that: (a) university students' "technostress" significantly predicted their "learning burnout" in TEL; (b) "administration support" was essential in alleviating students' "technostress" and "burnout"; (c) "peer support" negatively predicted students' "learning burnout" but did not predict their "technostress"; (d) "ICT competence" alone had no significant effects on "technostress." Moreover, multiple group comparisons based on genders found that females benefited more from "administrator support" in alleviating "learning burnout" than males. In contrast, males benefit more from "peer support" in improving their "ICT competence" than females. Implications for alleviating university students' technostress and learning burnout in TEL were discussed.

Background The incidence of diabetic kidney disease (DKD) and the proportion of its related end-stage renal disease in dialysis patients in China are increasing. So it is urgent to take measures to prevent and control DKD. Intensified multifactorial interventions may prevent or delay the progression of DKD. Therefore, developing a personalized risk prediction model can effectively delay or even prevent the progression of DKD and be useful for the prevention and treatment of DKD. Objective The purpose of this study was to develop and validate a nomogram for the risk prediction of the progression from microalbuminuria (MAU) to macroalbuminuria (CAU) in type 2 diabetes mellitus (T2DM) patients. Methods A total of 1 263 T2DM patients with albuminuria who were hospitalized in Department of Endocrinology, the First Affiliated Hospital of Air Force Medical University from October 2016 to March 2020 were retrospectively recruited and divided into a development cohort of 906 cases and a validation cohort of 357 cases, according to the admission time. LASSO regression was used to screen the optimized variables measured at baseline for CAU. A Nomogram was constructed based on selected predictive factors identified by the multivariate logistic regression model of the development sub-cohort. The receiver operating characteristic (ROC) curve, calibration curve and Hosmer-Lemeshow (H-L) test were employed to assess the calibration and discrimination of the model. Decision curve analysis (DCA) was performed to evaluate the net clinical benefit of the Nomogram. Results The diabetes duration, systolic blood pressure (SBP), glycosylated hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), cystatin C (Cys-C), estimated glomerular filtration rate (eGFR), and diabetic retinopathy (DR) were screened as predictive factors for progression from MAU to CAU by LASSO penalty regression. Multivariable Logistic regression analysis using these factors indicated that seven of those potential predictors were present in the final model, diabetes duration≥10 years, SBP≥140 mmHg, HbA1c≥7.0 mmol/L, LDL-C≥1.8 mmol/L, Cys-C>1.09 mg/L, and DR were risk factors for the progression from MAU to CAU in T2DM patients (P0.05). External and internal validations of the nomogram indicated a good predictive performance. The AUC of the model was 0.814〔95%CI (0.782, 0.846) 〕 in the development cohort, and was 0.768〔95%CI (0.713, 0.823) 〕 in the validation cohort. The model was well fit according to the calibration curve and the H-L goodness of fit test (internal validation: P=0.065; external validation: P=0.451). DCA curve showed that the Nomogram's net benefit was higher than both extreme curves when the threshold probability set between 0.08 and 0.74 in the development cohort, and between 0.14 and 0.70 in the external validation cohort, suggesting potential clinical benefits provided by this Nomogram. Conclusion This study finally constructed a prediction model with seven indicators containing diabetes duration, SBP, HbA1c, LDL-C, Cys-C, eGFR, and DR, and will be a useful clinical predictive tool for the risk of progression from MAU to CAU in T2DM patients.

Objective To investigate the protective effect of Platycodin D (PD) on renal ischemia-reperfusion injury in rats. Methods The rats were divided into sham group, model group, low, middle and high-dose groups with 10 animals in each. The rat model of ischemia reperfusion injury was established by clamping the bilateral renal pedicles in model group, low, middle and high-dose group. The rats in sham group underwent the same modeling operation but did not clamp the renal pedicles. Before 5 minutes of modeling, the rats of low, middle and high-dose group were intra-peritoneally injected with 12.5, 25 and 50 mg/kg PD, respectively. After 24 h of modeling, the serum creatinine (Cr) and blood urea nitrogen (BUN) levels, as well as antioxidant markers[superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and malondialdehyde (MDA)] levels in kidney tissues were measured. HE staining was used to evaluate renal tissue lesions. Immuno-histochemical staining was used to detect the expression of caspase-3 in renal tissue, the apoptosis index of renal tubular epithelial cells was evaluated by the counting of caspase-3 positive cells. RT-qPCR was used to detect the expression of interleukin-1β (IL-1β), IL-6 and IL-10 mRNA in renal tissues. Western blot was used to detect the expression of Toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), p65, p-p65, inhibitor of nuclear factor kappa B (NF-κB) (IκB) and p-IκB. Results Compared with sham group, the kidney lesions, serum Cr and BUN levels, apoptosis index of renal tubular epithelial cells in model group were all increased (P＜0.05). Compared with model group, the kidney lesions, serum Cr and BUN levels, apoptosis index of renal tubular epithelial cells in low, middle and high-dose group were decreased (P＜0.05). Compared with sham group, the level of MDA and mRNA of IL-1β and IL-6, the protein expression of TLR4/MyD88/NF-κB signaling pathway in kidney tissue in model group were all significantly increased while the level of SOD and GSH-Px and mRNA of IL-10 in rat kidney tissue were decreased(P＜0.05). Compared with model group, the level of MDA, mRNA of IL-1β and IL-6, the protein expression of TLR4/MyD88/NF-κB signaling pathway in kidney tissue in low, middle and high-dose group were all decreased, SOD and GSH-Px and IL-10 mRNA in rat kidney tissue were increased (P＜0.05). Conclusions Platycodin D has a protective effect on renal ischemia-reperfusion injury in rats, and the underlying mechanism may be related to the improvement of antioxidant capacity and inhibition of TLR4/MyD88/NF-κB signaling pathway.