Browse Articles

In this study, the authors studied the ability for bacteria to develop antibiotic resistance over successive generations and modeled the trajectory to predict how antibiotic resistance is developed.

Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.

Oligodendrocytes are specialized brain cells that can change to cells that produce myelin and protect nerves. This study investigates the capacity for different extracellular matrix cues to induce this effect in culture.

In this study, the authors address the concerns of heavy metal contamination in industrial and feedlot water waste. They test whether added probiotics are capable of taking up heavy metals in water to attenuate pollution.

This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.

In this article, the authors investigate the effects of fungus E. muscae on fruit fly behavior. More specifically, they investigate whether this fungus affects olfaction. Their findings contribute to a broader set of studies seeking to understand how host's central nervous systems can be affected by infections.

Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.

In this study, the authors investigate the effect of a herbal formulation on Cyclooxygenase-2 (COX-2) expression in cancer cells. High levels of COX-2 correlates with worsened cancer outcomes and the authors hypothesize that the formulation will inhibit COX-2 levels.

In this study, the authors send E. coli cultures to space via the Cubes in Space^TM program to determine if ultraviolet C and ionizing radiation negatively affect bacterial growth.

This study follows the process of single-cloning and the growth of a homogeneous cell population in a superficial environment over the course of six weeks with the end goal of showing which of five tumor growth models commonly used to predict heterogeneous cancer cell population growth (Exponential, Logistic, Gompertz, Linear, and Bertalanffy) would also best exemplify that of homogeneous cell populations.