A staphylococcal capsule-producing enzyme that unfolds via multiple intermediates predominantly exists as the trimers at low concentrations.

CapG, an enzyme expressed by , catalyzes an epimerization reaction to synthesize -acetyl-L-fucosamine, a constituent of capsule involved in pathogenesis. This protein has two domains, exists as the homohexamers in the solution, and usually produces products at hundred-nanomolar concentrations. To determine the folding-unfolding mechanism and the oligomeric form of CapG, particularly at low concentrations, we have investigated a recombinant CapG (rCapG) using different probes.

Colossal Reversible Barocaloric Effects in a Plastic Crystal Mediated by Lattice Vibrations and Ion Diffusion.

Solid-state methods for cooling and heating promise a sustainable alternative to current compression cycles of greenhouse gases and inefficient fuel-burning heaters. Barocaloric effects (BCE) driven by hydrostatic pressure (p) are especially encouraging in terms of large adiabatic temperature changes (|ΔT| ≈ 10 K) and isothermal entropy changes (|ΔS| ≈ 100 J K kg). However, BCE typically require large pressure shifts due to irreversibility issues, and sizeable |ΔT| and |ΔS| seldom are realized in a same material.

CodonU: A Python Package for Codon Usage Analysis.

Codon Usage Analysis (CUA) has been accompanied by several web servers and independent programs written in several programming languages. Also this diversity speaks for the need of a reusable software that can be helpful in reading, manipulating and acting as a pipeline for such data and file formats. This kind of analyses use multiple tools to address the multifaceted aspects of CUA.

Modeling and monitoring the effects of three partly conserved Ile residues in the dimerization domain of a Mip-like virulence factor from .

FKBP22, an -made peptidyl-prolyl - isomerase, has shown considerable homology with Mip-like virulence factors. While the C-terminal domain of this enzyme is used for executing catalytic function and binding inhibitor, the N-terminal domain is employed for its dimerization. To precisely determine the underlying factors of FKBP22 dimerization, its structural model, developed using a suitable template, was carefully inspected.

Deep transfer learning for IDC breast cancer detection using fast AI technique and Sqeezenet architecture.

One of the most effective approaches for identifying breast cancer is histology, which is the meticulous inspection of tissues under a microscope. The kind of cancer cells, or whether they are cancerous (malignant) or non-cancerous, is typically determined by the type of tissue that is analyzed by the test performed by the technician (benign). The goal of this study was to automate IDC classification within breast cancer histology samples using a transfer learning technique.