Comment on "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate", author Coro.

In this letter we present comments on the article "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus" by Coro published in 2020.

Effect of a glucagon receptor antibody (REMD-477) in type 1 diabetes: A randomized controlled trial.

The aim of the current study (Clinical trial reg. no. NCT02715193, clinicaltrials.gov) was to study the efficacy and safety of REMD-477, a glucagon receptor antagonist, in type 1 diabetes. This was a randomized controlled trial in which 21 patients with type 1 diabetes were enrolled. Glycaemic control and insulin use were evaluated in outpatient and inpatient settings, before and after a single 70-mg dose of REMD-477 (half-life 7-10 days) or placebo. Inpatient insulin use was 26% (95% CI, 47%, 4%) lower 1 day after dosing with REMD-477 than with placebo (P = .02). Continuous glucose monitoring during post-treatment days 6 to 12 showed that average daily glucose was 27 mg/dL lower (P < .001), percent time-in-target-range (70-180 mg/dL) was ~25% greater (~3.5 h/d) (P = .001), and percent time-in-hyperglycaemic-range (> 180 mg/dL) was ~40% lower (~4 h/d) (P = .001) in the REMD-477 group than in the placebo group, without a difference in percent time-in-hypoglycaemic-range (<70 mg/dL). No serious adverse events were reported. Glucagon receptor antagonism decreases insulin requirements and improves glycaemic control in patients with type 1 diabetes.

Pace and parity predict the short-term persistence of small plant populations.

Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near-term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decrease when the reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near-term odds of extinction.

skelesim: an extensible, general framework for population genetic simulation in R.

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares' complex capabilities, composing code and input files, a daunting bioinformatics barrier and a steep conceptual learning curve. skelesim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics and organizing data output, in a reproducible pipeline within the R environment. skelesim is designed to be an extensible framework that can 'wrap' around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skelesim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skelesim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skelesim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny).