Sound waves can be amazingly powerful, especially when they work together. Here the authors create an “acoustic lens” that focuses sound waves on a single location. This makes the sound waves very powerful, capable of causing damage at a precise point. In the future, acoustic lenses like this could potentially be used to treat cancer by killing small tumors without surgery.

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.

Here the authors sought to better understand glioma, cancer that occurs in the glial cells of the brain with gene expression profile analysis. They considered the expression of complement system genes across the transcriptional and IDH-mutational subtypes of low-grade glioma and glioblastoma. Based on their results of their differential gene expression analysis, they found that outcomes vary across different glioma subtypes, with evidence suggesting that categorization of the transcriptional subtypes could help inform treatment by providing an expectation for treatment responses.

Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.

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.

Nitrogen-fixing bacteria, such as the legume mutualist rhizobia, convert atmospheric nitrogen into a form that is usable by living organisms. Leguminous plants, like the model species Medicago truncatula, directly benefit from this process by forming a symbiotic relationship with rhizobia. Here, Rathod and Rowe investigate how M. truncatula responds to non-rhizobial bacterial partners.

Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

Solar and radio frequency harvesters serve as a viable alternative energy source to batteries in many cases where the battery cannot be easily replaced. Using specifically designed circuit models, the authors quantify the reliability of different harvested energy sources to identify the most practical and efficient forms of renewable energy.

The purpose of our study was to determine if direct administration of CXCL1/KC to cardiomyocytes causes negative changes to cell density or proliferation. This molecule has been shown to reduce inflammation in certain instances. Homocysteine models the direct effect of an inflammatory agent on cardiomyocytes. Our question was whether these molecules directly impact cell density through an interaction with the cell proliferation process. We hypothesized that cells treated with CXCL1/KC would maintain the same cell density as untreated cells. In contrast, cells treated with Homocysteine or both Homocysteine and CXCL1/KC, were expected to have a higher cell density that than that of untreated cells.