Rigidity of the outer shell predicted by a protein intrinsic disorder model sheds light on the COVID-19 (Wuhan-2019-nCoV) infectivity.

We consider the penalized generalized estimating equations (GEEs) for analyzing longitudinal data with high-dimensional covariates, which often arise in microarray experiments and large-scale health studies. Existing high-dimensional regression procedures often assume independent data and rely on the likelihood function. Construction of a feasible joint likelihood function for high-dimensional longitudinal data is challenging, particularly for correlated discrete outcome data. The penalized GEE procedure only requires specifying the first two marginal moments and a working correlation structure. We establish the asymptotic theory in a high-dimensional framework where the number of covariates p(n) increases as the number of clusters n increases, and p(n) can reach the same order as n. One important feature of the new procedure is that the consistency of model selection holds even if the working correlation structure is misspecified. We evaluate the performance of the proposed method using Monte Carlo simulations and demonstrate its application using a yeast cell-cycle gene expression data set.

Background. Renal diseases in diabetes include diabetic nephropathies (DN) and non-diabetic renal diseases (NDRD). The clinical differentiation between these two categories is usually not so clear and effective. This study aims to develop a quantified differential diagnostic model. Methods. We consecutively screened the diabetic patients with overt proteinuria but no severe renal failure for kidney biopsy from 1993 to 2003. The finally enrolled 110 patients were divided into two groups according to pathological features (60 in DN group and 50 in NDRD group). Clinical and laboratory data were compared between two groups. Then a diagnostic model was developed based on the logistic regression analysis. Results. Forty-six percent of patients were NDRD including a variety of pathological types. Many differences between DN and NDRD were found by comparison of the clinical indices. In the final logistic regression analysis, only diabetes duration (Dm), systolic blood pressure (Bp), HbA1c (Gh), haematuria (Hu) and diabetic retinopathy (Dr) showed statistical significance. Based on the logistic regression model: π = e z /(1 + e z ), a diagnostic model was constructed as follows: P DN = exp(−13.5922 + 0.0371Dm + 0.0395Bp + 0.3224Gh − 4.4552Hu + 2.9613Dr)/ [1 + exp(−13.5922 + 0.0371Dm + 0.0395Bp + 0.3224Gh − 4.4552Hu + 2.9613Dr)]. P DN was the probability of DN diagnosis (P DN ≥ 0.5 as DN, P DN < 0.5 as NDRD). Validation tests showed that this model had good sensitivity (90%) and specificity (92%).Conclusions. This diagnostic model may be helpful to clinical differentiation of DN and NDRD in type 2 diabetic patients with overt proteinuria.

Semiparametric models are often considered for analyzing longitudinal data for a good balance between flexibility and parsimony. In this paper, we study a class of marginal partially linear quantile models with possibly varying coefficients. The functional coefficients are estimated by basis function approximations. The estimation procedure is easy to implement, and it requires no specification of the error distributions. The asymptotic properties of the proposed estimators are established for the varying coefficients as well as for the constant coefficients. We develop rank score tests for hypotheses on the coefficients, including the hypotheses on the constancy of a subset of the varying coefficients. Hypothesis testing of this type is theoretically challenging, as the dimensions of the parameter spaces under both the null and the alternative hypotheses are growing with the sample size. We assess the finite sample performance of the proposed method by Monte Carlo simulation studies, and demonstrate its value by the analysis of an AIDS data set, where the modeling of quantiles provides more comprehensive information than the usual least squares approach.Comment: Published in at http://dx.doi.org/10.1214/09-AOS695 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

BackgroundMesothelial cell injury plays an important role in peritoneal fibrosis. Present clinical therapies aimed at alleviating peritoneal fibrosis have been largely inadequate. Mesenchymal stem cells (MSCs) are efficient for repairing injuries and reducing fibrosis. This study was designed to investigate the effects of MSCs on injured mesothelial cells and peritoneal fibrosis.Methodology/Principal FindingsRat bone marrow-derived MSCs (5 ×106) were injected into Sprague-Dawley (SD) rats via tail vein 24 h after peritoneal scraping. Distinct reductions in adhesion formation; infiltration of neutrophils, macrophage cells; number of fibroblasts; and level of transforming growth factor (TGF)-β1 were found in MSCs-treated rats. The proliferation and repair of peritoneal mesothelial cells in MSCs-treated rats were stimulated. Mechanically injured mesothelial cells co-cultured with MSCs in transwells showed distinct increases in migration and proliferation. In vivo imaging showed that MSCs injected intravenously mainly accumulated in the lungs which persisted for at least seven days. No apparent MSCs were observed in the injured peritoneum even when MSCs were injected intraperitoneally. The injection of serum-starved MSCs-conditioned medium (CM) intravenously reduced adhesions similar to MSCs. Antibody based protein array of MSCs-CM showed that the releasing of TNFα-stimulating gene (TSG)-6 increased most dramatically. Promotion of mesothelial cell repair and reduction of peritoneal adhesion were produced by the administration of recombinant mouse (rm) TSG-6, and were weakened by TSG-6-RNA interfering.Conclusions/SignificanceCollectively, these results indicate that MSCs may attenuate peritoneal injury by repairing mesothelial cells, reducing inflammation and fibrosis. Rather than the engraftment, the secretion of TSG-6 by MSCs makes a major contribution to the therapeutic benefits of MSCs.

BackgroundRenal injuries in patients with diabetes include diabetic nephropathy (DN) and non-diabetic renal diseases (NDRD). The value of a clinical diagnosis of DN and NDRD remains inconclusive. We conducted a meta-analysis of the literature to identify predictive factors of NDRD and to compare the clinical characteristics of DN and NDRD for differential diagnosis.MethodsWe searched PubMed (1990 to January 2012), Embase (1990 to February 2009), and CNKI (1990 to January 2012) to identify studies that enrolled patients with DN and NDRD. Then, the quality of the studies was assessed, and data were extracted. The results were summarized as odds ratios (ORs) for dichotomous outcomes and weighted mean differences (WMDs) for continuous outcomes.ResultsTwenty-six relevant studies with 2,322 patients were included. The meta-analysis showed that the absence of diabetic retinopathy (DR) predicts NDRD (OR, 0.15; 95% confidence interval [CI], 0.09–0.26, p<0.00001). A shorter duration of diabetes mellitus (DM) also predicted NDRD (weighted mean difference, −34.67; 95% CI, −45.23–−24.11, p<0.00001). The levels of glycosylated hemoglobin (HbA1C%), blood pressure (BP), and total cholesterol were lower in patients with NDRD, whereas triglycerides and body mass index were higher. Other clinical parameters, including age, 24-h urinary protein excretion, serum creatinine, creatinine clearance, blood urea nitrogen, and glomerular filtration rate were not different between patients with NDRD and DN.ConclusionsWe identified that the absence of DR, shorter duration of DM, lower HbA1C, and lower BP may help to distinguish NDRD from DN in patients with diabetes. This could assist clinicians in making a safe and sound diagnosis and lead to more effective treatments.

Background Effective therapies are urgently needed for the SARS-CoV-2 pandemic. Chloroquine has been proved to have antiviral effect against coronavirus in vitro. In this study, we aimed to assess the efficacy and safety of chloroquine with different doses in COVID-19. Method In this multicenter prospective observational study, we enrolled patients older than 18 years old with confirmed SARS-CoV-2 infection excluding critical cases from 12 hospitals in Guangdong and Hubei Provinces. Eligible patients received chloroquine phosphate 500 mg, orally, once (half dose) or twice (full dose) daily. Patients treated with non-chloroquine therapy were included as historical controls. The primary endpoint is the time to undetectable viral RNA. Secondary outcomes include the proportion of patients with undetectable viral RNA by day 10 and 14, hospitalization time, duration of fever, and adverse events. Results A total of 197 patients completed chloroquine treatment, and 176 patients were included as historical controls. The median time to achieve an undetectable viral RNA was shorter in chloroquine than in non-chloroquine (absolute difference in medians -6.0 days; 95% CI -6.0 to -4.0). The duration of fever is shorter in chloroquine (geometric mean ratio 0.6; 95% CI 0.5 to 0.8). No serious adverse events were observed in the chloroquine group. Patients treated with half dose experienced lower rate of adverse events than with full dose. Conclusions Although randomised trials are needed for further evaluation, this study provides evidence for safety and efficacy of chloroquine in COVID-19 and suggests that chloroquine can be a cost-effective therapy for combating the COVID-19 pandemic.

The podocyte functions as a glomerular filtration barrier. Autophagy of postmitotic cells is an important protective mechanism that is essential for maintaining the homeostasis of podocytes. Exploring an in vivo rat model of passive Heymann nephritis and an in vitro model of puromycin amino nucleotide (PAN)-cultured podocytes, we examined the specific mechanisms underlying changing autophagy levels and podocyte injury. In the passive Heymann nephritis model rats, the mammalian target-of-rapamycin (mTOR) levels were upregulated in injured podocytes while autophagy was inhibited. In PAN-treated podocytes, mTOR lowered the level of autophagy through the mTOR-ULK1 pathway resulting in damaged podocytes. Rapamycin treatment of these cells reduced podocyte injury by raising the levels of autophagy. These in vivo and in vitro experiments demonstrate that podocyte injury is associated with changes in autophagy levels, and that rapamycin can reduce podocyte injury by increasing autophagy levels via inhibition of the mTOR-ULK1 pathway. These results provide an important theoretical basis for future treatment of diseases involving podocyte injury.