History of the streptothricin antibiotics and evidence for the neglect of the streptothricin resistome.

The streptothricin antibiotics were among the first antibiotics to be discovered from the environment and remain some of the most recovered antimicrobials in natural product screens. Increasing rates of antibiotic resistance and recognition that streptothricin antibiotics may play a role in countering so-called super-bugs has led to the re-evaluation of their clinical potential. Here we will review the current state of knowledge of streptothricins and their resistance in bacteria, with a focus on the potential for new resistance mechanisms and determinants to emerge in the context of potential widespread clinical adoption of this antibiotic class.

Volume-preserving geometric shape optimization of the Dirichlet energy using variational neural networks.

In this work, we explore the numerical solution of geometric shape optimization problems using neural network-based approaches. This involves minimizing a numerical criterion that includes solving a partial differential equation with respect to a domain, often under geometric constraints like a constant volume. We successfully develop a proof of concept using a flexible and parallelizable methodology to tackle these problems.

Spatial modeling and ecological suitability of Ebola virus disease in Africa.

This paper looks into the MaxEnt model in a trial to comprehend the ecological and environmental conditions that propagate and drive the spread of Ebola Virus Disease in Africa. We use the MaxEnt model to assess risk determinants associated with the occurrence and distribution of EVD, taking into account non-correlated variables such as neighborhood mean temperature, rainfall, and human population density. Our findings indicate that among the factors that significantly shape the geographical distribution of EVD risk are human population density, annual rainfall, temperature variability, and seasonality.