Computational approaches are practical when investigating putative peroxisomal proteins and for sub-peroxisomal protein localization in unknown protein sequences. Nowadays, advancements in computational methods and Machine Learning (ML) can be used to hasten the discovery of novel peroxisomal proteins and can be combined with more established computational methodologies. Here, we explain and list some of the most used tools and methodologies for novel peroxisomal protein detection and localization.
This review explores the bidirectional relationship between the human microbiome and SARS-CoV-2 infection, elucidating its implications for COVID-19 susceptibility, severity, and therapeutic strategies. Metagenomic analyses reveal notable alterations in microbiome composition associated with SARS-CoV-2 infection, impacting disease severity and clinical outcomes. Dysbiosis within the respiratory, gastrointestinal, oral, and skin microbiomes exacerbates COVID-19 pathology through immune dysregulation and inflammatory pathways.
Background/aims: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnostic tools, such as MRI and PET scans, are costly and less accessible.
Purpose: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized.
Despite the remarkable resistance of the nucleic acid phosphodiester backbone to degradation affording genetic stability, the P-O bond must be broken during DNA repair and RNA metabolism, among many other critical cellular processes. Nucleases are powerful enzymes that can enhance the uncatalyzed rate of phosphodiester bond cleavage by up to ∼10-fold. Despite the most well accepted hydrolysis mechanism involving two metals (M to activate a water nucleophile and M to stabilize the leaving group), experimental evidence suggests that some nucleases can use a single metal to facilitate the chemical step, a controversial concept in the literature.
Diffusion-weighted imaging (DWI) has been frequently used to examine age-related deterioration of white matter microstructure and its relationship to cognitive decline. However, typical tensor-based analytical approaches are often difficult to interpret due to the challenge of decomposing and (mis)interpreting the impact of crossing fibers within a voxel. We hypothesized that a novel analytical approach capable of resolving fiber-specific changes within each voxel (i.
