4 research outputs found

    Active vitamin D activates chondrocyte autophagy to reduce osteoarthritis via mediating the AMPK–mTOR signaling pathway

    No full text
    Osteoarthritis (OA) is a common joint degenerative disease. Vitamin D (VD) is essential for bone health. We hypothesized that active VD could be used as a therapeutic treatment for OA. Low serum levels of 25-hydroxyvitamin D [25(OH)D] have been found in patients with OA, and thus the serum level of VD could be diagnostic of OA. To test this, we established a mouse model of OA. The results from staining with hematoxylin–eosin and Safranin O – Fast Green indicated that active VD reduced the symptoms of OA in mice. The results from Western blotting indicated that treatment with VD increased the activity of the p-AMPK–AMPK signaling pathway and decreased the p-mTOR–mTOR pathway; it also increased the ratio of LC3II:LC3I antibodies and the protein expression levels of Beclin-1, but decreased the level of p62. Further, treatment with VD reduced the levels of tumor necrosis factor-α and interleukin-6 both in cartilage tissues and in chondrocytes. Administration of the AMPK inhibitor compound C and autophagy inhibitor 3-methyladenine (3-MA) reversed these changes following VD treatment. In addition, the results from transfection with mRFP-GFP-LC3 indicated that active VD led to autophagosome aggregation in OA chondrocytes. 3-MA inhibited cell autophagy and promoted inflammation in OA. This study provides evidence that active VD activate chondrocyte autophagy to reduce OA inflammation via activating the AMPK–mTOR signaling pathway. Treatment with active VD could be a novel therapeutic option for OA.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

    Risk assessment in systemic lupus erythematosus-associated pulmonary arterial hypertension: CSTAR-PAH cohort study

    No full text
    Objective: This study evaluated the prognostic value of the multivariable risk assessment for systemic lupus erythematosus (SLE)-associated pulmonary arterial hypertension (PAH). Methods: A multicenter prospective cohort of SLE-associated PAH (CSTAR-PAH cohort) diagnosed based on right heart catheterization (RHC) was established. Baseline and follow-up records were collected. Three methods of risk assessment, including (1) the number of low-risk criteria, based on World Health Organization functional class (WHO FC), 6-min walking distance (6MWD), right atrial pressure (RAP), and cardiac index (CI); (2) the three-strata stratification based on the average risk score of four variables (WHO FC, 6MWD, RAP, and CI); and (3) the four-strata stratification based on COMPARE 2.0 model were applied. A risk-assessment method using three noninvasive low-risk criteria was applied at the first follow-up visit. Survival curves between patients with different risk groups were compared by Kaplan–Meier’s estimation and log-rank test. Results: Three-hundred and ten patients were enrolled from 14 PAH centers. All methods of stratification at baseline and first follow-up significantly discriminated long-term survival. Survival rates were also significantly different based on the noninvasive risk assessment in first follow-up visit. Survival deteriorated with the escalation of risk from baseline to first follow-up. Patients with baseline serositis had a higher rate of risk improvement in their follow-up. Conclusion: The risk assessment has a significant prognostic value at both the baseline and first follow-up assessment of SLE-associated PAH. A noninvasive risk assessment can also be useful when RHC is not available during follow-up. Baseline serositis may be a predictor of good treatment response in patients with SLE-associated PAH

    A prognostic model for systemic lupus erythematosus-associated pulmonary arterial hypertension: CSTAR-PAH cohort study

    No full text
    Abstract Background Pulmonary arterial hypertension is a major cause of death in systemic lupus erythematosus, but there are no tools specialized for predicting survival in systemic lupus erythematosus-associated pulmonary arterial hypertension. Research question To develop a practical model for predicting long-term prognosis in patients with systemic lupus erythematosus-associated pulmonary arterial hypertension. Methods A prognostic model was developed from a multicenter, longitudinal national cohort of consecutively evaluated patients with systemic lupus erythematosus-associated pulmonary arterial hypertension. The study was conducted between November 2006 and February 2020. All-cause death was defined as the endpoint. Cox regression and least absolute shrinkage and selection operators were used to fit the model. Internal validation of the model was assessed by discrimination and calibration using bootstrapping. Results Of 310 patients included in the study, 81 (26.1%) died within a median follow-up of 5.94 years (interquartile range 4.67–7.46). The final prognostic model included eight variables: modified World Health Organization functional class, 6-min walking distance, pulmonary vascular resistance, estimated glomerular filtration rate, thrombocytopenia, mild interstitial lung disease, N-terminal pro-brain natriuretic peptide/brain natriuretic peptide level, and direct bilirubin level. A 5-year death probability predictive algorithm was established and validated using the C-index (0.77) and a satisfactory calibration curve. Risk stratification was performed based on the predicted probability to improve clinical decision-making. Conclusions This new risk stratification model for systemic lupus erythematosus-associated pulmonary arterial hypertension may provide individualized prognostic probability using readily obtained clinical risk factors. External validation is required to demonstrate the accuracy of this model's predictions in diverse patient populations
    corecore