In this article, the authors analyzed ribosome profiling data from amino acid-starved pancreatic cancer cells to explore whether the pattern of ribosome distribution along transcripts under normal conditions can predict the degree of ribosome stalling under stress. The authors found that ribosomes in amino acid-deprived cells stalled more along elongation-limited transcripts. By contrast, they observed no relationship between read density near start and stop and disparities between mRNA sequencing reads and ribosome profiling reads. This research identifies an important relationship between read distribution and propensity for ribosomes to stall, although more work is needed to fully understand the patterns of ribosome distribution along transcripts in ribosome profiling data.
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A Scientific Investigation of Alternative Growing Methods to Cultivate Lactuca sativa
In this article, the authors compare different resource-efficient farming methods for the vegetable Lactuca sativa. They compared hydroponics (solid growth medium with added nutrients) to aquaponics (water with fish waste to provide nutrients) and determined efficacy by measuring plant height over time. While both systems supported plant growth, the authors concluded that aquaponics was the superior method for supporting Lactuca sativa growth. These findings are of great relevance as we continue to find the most sustainable and efficient means for farming.
Read More...Simulating natural selection via autonomous agents: Environmental factors create unstable equilibria
Natural selection shapes the evolution of all organisms, and one question of interest is whether natural selection will reach a "stopping point": a stable, ideal, value for any particular trait. Madhan and Kanagavel tackle this question by building a computer simulation of trait evolution in organisms.
Read More...Effects of microconvection on bubble displacement during water electrolysis under microgravity
The authors looked at the effect of microconvection on displacing bubbles during electrolysis. They found that microconvection does have a role in bubble displacement in water electrolysis which can be applied in the production of hydrogen.
Read More...Evaluation of in vitro anti-inflammatory effect of PLAY® on UC-MSCs: A COX-2 expression study
The authors seek to accelerate wound healing by reducing inflammation with a cocktail containing growth factors and bioactive modulators.
Read More...Bacteroides thetaiotaomicron Growth Numbers Are Unchanged in the Presence of Yogurt
Disruptions to the microbiome, specifically the imbalance in the two major phyla, the Firmicutes and the Bacteroidetes, have been linked to the development of obesity. This study explored whether or not Fage plain total 0% Greek yogurt, which contains live and active bacterial cultures belonging to the Firmicute phylum, could decrease the numbers of Bacteroides thetaiotaomicron, an organism found in the human gut that belongs to the Bacteroidetes phylum.
Read More...A novel CNN-based machine learning approach to identify skin cancers
In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.
Read More...Who is at Risk for a Spinal Fracture? – A Comparative Study of National Health and Nutrition Examination Survey Data
One common age-related health problem is the loss of bone mineral density (BMD), which can lead to a variety of negative health outcomes, including increased risk of spinal fracture. In this study, the authors investigate risk factors that may be predictive of an individual's risk of spinal fracture. Their findings provide valuable information that clinicians can use in patient evaluations.
Read More...Design and implementation of a cryptographically secure electronic voting infrastructure
In this study, the authors present proposed cryptographic controls for election sites with the hypothesis that this will mitigate risk and remediate vulnerabilities.
Read More...Development of a novel machine learning platform to identify structural trends among NNRTI HIV-1 reverse transcriptase inhibitors
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.
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