Cohen, D. J. — Page 2 | bioRxiv Science

bioRxiv2019

Membrane proximal F-actin restricts local membrane protrusions and directs cell migration

A major component of cell migration is F-actin polymerization driven membrane protrusion in the front. However, F-actin proximal to the plasma membrane also has a scaffolding role to support and attach the membrane. Here we developed a fluorescent reporter to monitor changes in the density of membrane proximal F-actin during membrane protrusion and cell migration. Strikingly, unlike total F-actin concentration, which is high in the front of migrating cells, the density of membrane proximal F-actin is low in the front and high in the back. Furthermore, local membrane protrusions only form following local decreases in membrane proximal F-actin density. Our study suggests that low density of membrane proximal F-actin is a fundamental structural parameter that locally directs membrane protrusions and globally stabilizes cell polarization during cell migration.\n\nOne Sentence SummaryMembrane protrusion and cell migration are directed by local decreases in the density of membrane proximal F-actin

cell biology↗

bioRxiv2019

Integrating Quality of Life and Survival Outcomes Cardiovascular Clinical Trials: Results from the PARTNER Trial

BackgroundSurvival and health status (e.g., symptoms and quality of life) are key outcomes in clinical trials of heart failure treatment. However, health status can only be recorded on survivors, potentially biasing treatment effect estimates when there is differential survival across treatment groups. Joint modeling of survival and health status can address this bias.\n\nMethods and ResultsWe analyzed patient-level data from the PARTNER 1B trial of transcatheter aortic valve replacement (TAVR) versus standard care. Health status was quantified with the Kansas City Cardiomyopathy Questionnaire (KCCQ) at randomization, 1, 6, and 12 months. We compared hazard ratios for survival and mean differences in KCCQ scores at 12 months using several models: the original growth curve model for KCCQ scores (ignoring death), separate Bayesian models for survival and KCCQ scores, and a Bayesian joint longitudinal-survival model fit to either 12 or 30 months of survival follow-up. The benefit of TAVR on 12-month KCCQ scores was greatest in the joint model fit to all survival data (mean difference = 33.7 points; 95% CrI: 24.2, 42.4), followed by the joint model fit to 12 months of survival follow-up (32.3 points; 95% CrI: 22.5, 41.5), a Bayesian model without integrating death (30.4 points; 95% CrI: 21.4, 39.3), and the original growth curve model (26.0 points; 95% CI: 18.7, 33.3). At 12 months, the survival benefit of TAVR was also greater in the joint model (hazard ratio = 0.50; 95% CrI: 0.32, 0.73) than in the non-joint Bayesian model (0.54; 95% CrI: 0.37, 0.75) or the original Kaplan-Meier estimate (0.55; 95% CI: 0.40, 0.74).\n\nConclusionsIn patients with severe symptomatic aortic stenosis and prohibitive surgical risk, the estimated benefits of TAVR on survival and health status compared with standard care were greater in joint Bayesian models than other approaches.

clinical trials↗