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With advancements in machine learning a large data scale, high throughput virtual screening has become a more attractive method for screening drug candidates. This study compared the accuracy of molecular descriptors from two cheminformatics Mordred and PaDEL, software libraries, in characterizing the chemo-structural composition of 53 compounds from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. The classification model built with the filtered set of descriptors from Mordred was superior to the model using PaDEL descriptors. This approach can accelerate the identification of hit compounds and improve the efficiency of the drug discovery pipeline.

In the battle against Alzheimer's disease, early detection is critical to mitigating symptoms in patients. Here, the authors use a collection of MRI scans, layering with deep learning computer modeling, to investigate early stages of AD which can be hard to catch by human eye. Their model is successful, able to outperform previous models, and detected regions of interest in the brain for further consideration.

Cosmic rays are high-energy astronomical particles originating from various sources across the universe. Here, The authors sought to understand how surface-level cosmic-ray muon flux is affected by atmospheric attenuation by measuring the variation in relative muon-flux rate relative to zenith angle, testing the hypothesis that muons follow an exponential attenuation model. The attenuation model predicts an attenuation length of 6.3 km. This result implies that only a maximum of 24% of muons can reach the Earth’s surface, due to both decay and atmospheric interactions.

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.

High-fructose diets consumed widely in modern societies predisposes to metabolic diseases such as diabetes. Using the worm C. elegans, the authors of this study investigated the effect of fructose on the worm's survival rates. They found that worms fed 15% fructose had a lower life expectancy than those on a fructose-free diet. These results suggest that, like in humans, fructose has a negative effect on worm survival, which makes them an easy, attractive model to study the effects of fructose on health.

Alzheimer's disease (AD) involves the reduction of cholinergic activity due to a decrease in neuronal levels of nAChR α7. In this work, Sanyal and Cuellar-Ortiz explore the role of the nAChR α7 in learning and memory retention, using Drosophila melanogaster as a model organism. The performance of mutant flies (PΔEY6) was analyzed in locomotive and olfactory-memory retention tests in comparison to wild type (WT) flies and an Alzheimer's disease model Arc-42 (Aβ-42). Their results suggest that the lack of the D. melanogaster-nAChR causes learning, memory, and locomotion impairments, similar to those observed in Alzheimer's models Arc-42.

Chronic alcohol consumption can cause cardiac myopathy, which afflicts about 500,000 Americans annually. Gunturi et al. wanted to understand the effects of alcohol on heart rate and confirm the role of nitric oxide (NO) signaling in heart rate regulation. Using the model organism Daphnia magna, a water crustacean with a large, transparent heart, they found that the heart rate of Daphnia magna was reduced after treatment with alcohol. This depression could be reversed after treatment with inhibitors of NO synthesis and signaling. Their work has important implications for how we understand alcohol-induced effects on heart rate and potential treatments to reverse heart rate depression as a result of alcohol consumption.

Numerous organisms, including the marine bacterium Aliivibrio fischeri, produce light. This bioluminescence is involved in many important symbioses and may one day be an important source of light for humans. In this study, the authors investigated ways to increase bioluminescence production from the model organism E. coli.

Osteosarcoma is a type of bone cancer that affects young adults and children. Early diagnosis of osteosarcoma is crucial to successful treatment. The current methods of diagnosis, which include imaging tests and biopsy, are time consuming and prone to human error. Hence, we used deep learning to extract patterns and detect osteosarcoma from histological images. We hypothesized that the combination of two different technologies (transfer learning and data augmentation) would improve the efficacy of osteosarcoma detection in histological images. The dataset used for the study consisted of histological images for osteosarcoma and was quite imbalanced as it contained very few images with tumors. Since transfer learning uses existing knowledge for the purpose of classification and detection, we hypothesized it would be proficient on such an imbalanced dataset. To further improve our learning, we used data augmentation to include variations in the dataset. We further evaluated the efficacy of different convolutional neural network models on this task. We obtained an accuracy of 91.18% using the transfer learning model MobileNetV2 as the base model with various geometric transformations, outperforming the state-of-the-art convolutional neural network based approach.

Caenorhabditis elegans xpa-1 and him-1 are orthologs of human XPA and human SMC1A, respectively. Mutations in the XPA are correlated with Xeroderma pigmentosum, a condition that induces hypersensitivity to ultraviolet (UV) radiation. Alternatively, SMC1A mutations may lead to Cornelia de Lange Syndrome, a multi-organ disorder that makes patients more sensitive to UVinduced DNA damage. Both C. elegans genes have been found to be involved in protection against UV radiation, but their combined effects have not been tested when they are both knocked down. The authors hypothesized that because these genes are involved in separate pathways, the simultaneous knockdown of both of these genes using RNA interference (RNAi) in C. elegans will cause them to become more sensitive to UV radiation than either of them knocked down individually. UV protection was measured via the percent survival of C. elegans post 365 nm and 5.4x10-19 joules of UV radiation. The double xpa-1/him-1 RNAi knockdown showed a significantly reduced percent survival after 15 and 30 minutes of UV radiation relative to wild-type and xpa-1 and him-1 single knockdowns. These measurements were consistent with their hypothesis and demonstrated that xpa-1 and him-1 genes play distinct roles in resistance against UV stress in C. elegans. This result raises the possibility that the xpa-1/him-1 double knockdown could be useful as an animal model for studying the human disease Xeroderma pigmentosum and Cornelia de Lange Syndrome.