A Simulation Study of the Performance of Statistical Models for Count Outcomes with Excessive Zeros

Background: Outcome measures that are count variables with excessive zeros are common in health behaviors research. There is a lack of empirical data about the relative performance of prevailing statistical models when outcomes are zero-inflated, particularly compared with recently developed approaches. Methods: The current simulation study examined five commonly used analytical approaches for count outcomes, including two linear models (with outcomes on raw and log-transformed scales, respectively) and three count distribution-based models (i.e., Poisson, negative binomial, and zero-inflated Poisson (ZIP) models). We also considered the marginalized zero-inflated Poisson (MZIP) model, a novel alternative that estimates the effects on overall mean while adjusting for zero-inflation. Extensive simulations were conducted to evaluate their the statistical power and Type I error rate across various data conditions. Results: Under zero-inflation, the Poisson model failed to control the Type I error rate, resulting in higher than expected false positive results. When the intervention effects on the zero (vs. non-zero) and count parts were in the same direction, the MZIP model had the highest statistical power, followed by the linear model with outcomes on raw scale, negative binomial model, and ZIP model. The performance of a linear model with a log-transformed outcome variable was unsatisfactory. When only one of the effects on the zero (vs. non-zero) part and the count part existed, the ZIP model had the highest statistical power. Conclusions: The MZIP model demonstrated better statistical properties in detecting true intervention effects and controlling false positive results for zero-inflated count outcomes. This MZIP model may serve as an appealing analytical approach to evaluating overall intervention effects in studies with count outcomes marked by excessive zeros

Sample Size Calculation of Clinical Trials with Correlated Outcomes

In this thesis, we investigate sample size calculation for three kinds of clinical trials: (1). Randomized controlled trials (RCTs) with longitudinal count outcomes; (2). Cluster randomized trials (CRTs) with count outcomes; (3). CRTs with multiple binary co-primary endpoints

Decrotonylation of AKT1 promotes AKT1 phosphorylation and activation during myogenic differentiation

Introduction: Myogenic differentiation plays an important role in pathophysiological processes including muscle injury and regeneration, as well as muscle atrophy. A novel type of posttranslational modification, crotonylation, has been reported to play a role in stem cell differentiation and disease. However, the role of crotonylation in myogenic differentiation has not been clarified. Objectives: This study aims to find the role of crotonylation during myogenic differentiation and explore whether it is a potential target in myogenic dysfunction disease. Methods: C2C12 cell line and skeletal muscle mesenchymal progenitors of Mus musculus were used for myogenic process study in vitro, while muscle injury model of mice was used for in vivo muscle regeneration study. Mass spectrometry favored in discovery of potential target protein of crotonylation and its specific sites. Results: We confirmed the gradual decrease in total protein crotonylation level during muscle differentiation and found decreased crotonylation of AKT1, which facilitated an increase in AKT1 phosphorylation. Then we verified that crotonylation of AKT1 at specific sites weakened its binding with PDK1 and impaired its phosphorylation. In addition, we found that increased expression of the crotonylation eraser HDAC3 decreased AKT1 crotonylation levels during myogenic differentiation, jointly promoting myogenic differentiation. Conclusion: Our study highlights the important role of decrotonylation of AKT1 in the process of muscle differentiation, where it aids the phosphorylation and activation of AKT1 and promotes myogenic differentiation. This is of great significance for exploring the pathophysiological process of muscle injury repair and sarcopenia

Targeting macrophage M1 polarization suppression through PCAF inhibition alleviates autoimmune arthritis via synergistic NF-κB and H3K9Ac blockade

Abstract Sustained inflammatory invasion leads to joint damage and progressive disability in several autoimmune rheumatic diseases. In recent decades, targeting M1 macrophage polarization has been suggested as a promising therapeutic strategy for autoimmune arthritis. P300/CBP-associated factor (PCAF) is a histone acetyltransferase (HAT) that exhibits a strong positive relationship with the proinflammatory microenvironment. However, whether PCAF mediates M1 macrophage polarization remains poorly studied, and whether targeting PCAF can protect against autoimmune arthritis in vivo remains unclear. Commonly used drugs can cause serious side effects in patients because of their extensive and nonspecific distribution in the human body. One strategy for overcoming this challenge is to develop drug nanocarriers that target the drug to desirable regions and reduce the fraction of drug that reaches undesirable targets. In this study, we demonstrated that PCAF inhibition could effectively inhibit M1 polarization and alleviate arthritis in mice with collagen-induced arthritis (CIA) via synergistic NF-κB and H3K9Ac blockade. We further designed dextran sulfate (DS)-based nanoparticles (DSNPs) carrying garcinol (a PCAF inhibitor) to specifically target M1 macrophages in inflamed joints of the CIA mouse model via SR-A–SR-A ligand interactions. Compared to free garcinol, garcinol-loaded DSNPs selectively targeted M1 macrophages in inflamed joints and significantly improved therapeutic efficacy in vivo. In summary, our study indicates that targeted PCAF inhibition with nanoparticles might be a promising strategy for treating autoimmune arthritis via M1 macrophage polarization inhibition

Casirivimab + imdevimab accelerates symptom resolution linked to improved COVID-19 outcomes across susceptible antibody and risk profiles

Abstract Severe, protracted symptoms are associated with poor outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In a placebo-controlled study of casirivimab and imdevimab (CAS + IMD) in persons at high risk of severe coronavirus disease 2019 (COVID-19; n = 3816), evolution of individual symptoms was assessed for resolution patterns across risk factors, and baseline SARS-CoV-2-specific antibody responses against S1 and N domains. CAS + IMD versus placebo provided statistically significant resolution for 17/23 symptoms, with greater response linked to absence of endogenous anti–SARS-CoV-2 immunoglobulin (Ig)G, IgA, or specific neutralizing antibodies at baseline, or high baseline viral load. Resolution of five key symptoms (onset days 3–5)—dyspnea, cough, feeling feverish, fatigue, and loss of appetite—independently correlated with reduced hospitalization and death (hazard ratio range: 0.31–0.56; P < 0.001–0.043), and was more rapid in CAS + IMD-treated patients lacking robust early antibody responses. Those who seroconverted late still benefited from treatment. Thus, highly neutralizing COVID-19-specific antibodies provided by CAS + IMD treatment accelerated key symptom resolution associated with hospitalization and death in those at high risk for severe disease as well as in those lacking early, endogenous neutralizing antibody responses