The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program
Read More...Solving the Schrödinger equation computationally using the Lanczos algorithm
The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program
Read More...Homology modeling of clinically-relevant rilpivirine-resistant HIV-RT variants identifies novel rilpivirine analogs with retained binding affinity against NNRTI-resistant HIV mutations
Human immunodeficiency virus (HIV), which affects tens of millions of individuals worldwide, can lead to acquired immunodeficiency syndrome (AIDS). While there is currently no cure for HIV, the development of small molecule antiretroviral agents has greatly improved the prognosis of infected individuals, especially in developed countries. Here, the authors employ homology modeling and molecular docking towards the identification of novel rilpivirine analogs that retain high binding affinity to clinically relevant rilpivirine-resistant mutations of the HIV reverse transcriptase enzyme.
Read More...Deuterated solvent effects in the kinetics and thermodynamics of keto-enol tautomerization of ETFAA
In this study, the authors determined whether tautomerization dynamics in protic and aprotic solvents displayed differences in reaction rates and in the proportion of the keto and enol tautomers present.
Read More...A novel approach to determine which organism best displays Gijswijt's Sequence in its genome
The sequence of nitrogenous bases that make up the DNA of organisms can contain hidden mathematical sequences. Here the authors used BioPython, a programming tool, to find an organism that displays Gijswijt’s Sequence in its genome. In this manner they found that the common carp best displays Gijswijt’s Sequence in its genome.
Read More...A comparative analysis of machine learning approaches to predict brain tumors using MRI
The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
Read More...Temporal characterization of electroencephalogram slowing activity types
The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia
Read More...Convolutional neural network-based analysis of pediatric chest X-ray images for pneumonia detection
The authors test various machine learning models to improve the accuracy and efficiency of pneumonia diagnosis from X-ray images.
Read More...Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone
Thymoquinone is a compound of great therapeutic potential and scientific interest. However, its clinical administration and synthetic modifications are greatly limited by its instability in the presence of light. This study employed quantitative 1H nuclear magnetic resonance (NMR) spectroscopy to identify the effect of solvation on the degradation of thymoquinone under ultraviolet light (UV). It found that the rate of degradation is highly solvent dependent occurs maximally in chloroform.
Read More...Hammett linear free-energy relationships in the biocatalytic hydrolysis of para-substituted nitrophenyl benzoate esters
As the world moves towards more eco-friendly methods for chemical synthesis, there's a strong interest in employing enzymes in chemical synthetic processes. Here, the authors explore how the activity of enzymes such as trypsin, lipase and nattokinase is affected by the electronic effects of the substrate they are acting on.
Read More...The effects of UV-C and ionizing radiation on the functions of Escherichia Coli
In this study, the authors send E. coli cultures to space via the Cubes in SpaceTM program to determine if ultraviolet C and ionizing radiation negatively affect bacterial growth.
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