Stem cell therapy in coronavirus disease 2019: current evidence and future potential

The end of 2019 saw the beginning of the coronavirus disease 2019 (COVID-19) pandemic that soared in 2020, affecting 215 countries worldwide, with no signs of abating. In an effort to contain the spread of the disease and treat the infected, researchers are racing against several odds to find an effective solution. The unavailability of timely and affordable or definitive treatment has caused significant morbidity and mortality. Acute respiratory distress syndrome (ARDS) caused by an unregulated host inflammatory response toward the viral infection, followed by multi-organ dysfunction or failure, is one of the primary causes of death in severe cases of COVID-19 infection. Currently, empirical management of respiratory and hematological manifestations along with anti-viral agents is being used to treat the infection. The quest is on for both a vaccine and a more definitive management protocol to curtail the spread. Researchers and clinicians are also exploring the possibility of using cell therapy for severe cases of COVID-19 with ARDS. Mesenchymal stromal cells are known to have immunomodulatory properties and have previously been used to treat viral infections. This review explores the potential of mesenchymal stromal cells as cell therapy for ARDS.     

Ecology of Compounding Disturbances: The Effects of Prescribed Burning After Clearcutting

Disturbance regimes in much of the boreal forest have shifted from wildfire to clearcutting over the last century, resulting in concerns for biodiversity. Because the boreal forest has evolved under a natural fire regimes, we hypothesized that application of prescribed burning (PB) after clearcutting would result in plant communities more similar to wildfire than clearcut only. However, because clearcutting + PB involves multiple disturbances in a short interval, we proposed an alternate hypothesis that clearcutting + PB would result in a species composition and trait assemblage that differ from those that develop after a single wildfire or clearcutting event. We determined species composition, diversity, and trait composition of 17 clearcut, 17 clearcut + PB, and 15 wildfire sites of jack pine (Pinus banksiana) dominated forests in northwestern Ontario, Canada 15–37 years after disturbance. Contrary to our primary hypothesis we found that clearcut + PB formed communities different from wildfire and clearcut, the latter two being similar. Clearcut + PB harbored more early successional species associated with seed banking, wind dispersal, deciduous foliage, and alien origin than wildfire or clearcut sites, which showed no specific trait associations. Taxonomic and trait analysis of clearcut + PB sites exhibited effects of compound disturbances, as observed after short-interval fires, supporting our alternate hypothesis. We concluded that PB after clearcutting formed plant communities significantly different from those developed either after clearcutting or wildfire alone. We attribute this community divergence to the compounding effects associated with the addition of prescribed fire to these previously disturbed forests.     

Application of creeping flow through a linearly absorbing slit filled with porous medium to diseased renal tubules

Biomechanics and Modeling in Mechanobiology - In this paper, we have discussed the flow of a Newtonian fluid through a slit filled with porous medium and linearly reabsorbing porous walls. The...     

Elucidating the molecular interaction of Zebrafish (Danio rerio) peptidoglycan recognition protein 2 with diaminopimelic acid and lysine type peptidoglycans using in silico approaches

Abstract

Peptidoglycan recognition proteins (PGRPs) belong to the family of pattern recognition receptor, represent the major constituent of innate immunity. Although PGRPs are structurally conserved through evolution, their involvement in innate immunity is different in vertebrates and invertebrates. They are highly specific towards recognition of ligands and can hydrolyze bacterial peptidoglycans (PGNs). Zebrafish PGRPs (zPGRPs) have both peptidoglycans lytic amidase activity and broad-spectrum bactericidal activity, but far less is known about how these receptors recognize these microbial ligands. Such studies are hindered due to lack of structural and functional configuration of zPGRPs. Therefore, in this study, we predicted the three-dimensional structure of zPGRP2 through theoretical modeling, investigated the conformational and dynamic properties through molecular dynamics simulations. Molecular docking study revealed the microbial ligands, that is, muramyl pentapeptide–DAP , muramyl pentapeptide–LYS, muramyl tripeptide–DAP, muramyl tripeptide–Lys, muramyl tetrapeptide–DAP, muramyl tetrapeptide–LYS and tracheal cytotoxin interacts with the conserved amino acids of the ligand recognition site comprised of β1, α2, α4, β4 and loops connecting β1 ? α2, α2 ? β2, β3 ? β4 and α4 ? α5. Conserved His31, His32, Ala34, Ile35, Pro36, Lys38, Asp60, Trp61, Trp63, Ala89, His90, Asp106, His143 and Arg144 are predicted to essential for binding and provides stability to these zPGRP–PGN complexes. Our study provides basic molecular information for further research on the immune mechanisms of PGRP’s in Zebrafish. The plasticity of the zPGRP’s binding site revealed by these microbial ligands suggests an intrinsic capacity of the innate immune system to rapidly evolve specificities to meet new microbial challenges in the future.

Communicated by Ramaswamy H. Sarma     

Unique corneal tomography features of allergic eye disease identified by OCT imaging and artificial intelligence

The purpose of this study was to assess unique corneal tomographic parameters of allergic eye disease (AED) using optical coherence tomography (OCT) and artificial intelligence (AI). A total of 57 eyes diagnosed with AED were included. The curvature and aberrations of the air‐epithelium (A‐E) and epithelium‐Bowman's layer (E‐B) interfaces were calculated. Random forest AI models were built combing this data with the parameters of healthy, forme fruste keratoconus (FFKC) and KC eyes. The AI models were cross‐validated with 3‐fold random sampling. Each model was limited to 10 trees. The AI model incorporating both A‐E and E‐B parameters provided the best classification of AED eyes (area under the curve = 0.958, sensitivity = 80.7%, specificity = 98.5%, precision = 88.2%). Further, the E‐B interface parameters provided the highest information gain in the AI model. A few AED eyes (n = 9) had tomography parameters similar to FFKC and KC eyes and may be at risk of progression to KC.