Role of micro-crystalline parameters in the physical properties of cotton fibers

Karnataka state in India is very well known for its cotton cultivation and there are innumerable varieties of these cotton fibers. Although, the yield and other types of characterization have been carried out on these fibers, the structure-property relation is not well studied till today. We have examined four different raw cotton fibers using Wide Angle X-ray Scattering (WAXS) technique and also we have computed micro-crystalline parameters. This study brings out the structure-property relation in cotton fibers.     

Can Natural Products Targeting EMT Serve as the Future Anticancer Therapeutics?

Cancer is the leading cause of death and has remained a big challenge for the scientific community. Because of the growing concerns, new therapeutic regimens are highly demanded to decrease the global burden. Despite advancements in chemotherapy, drug resistance is still a major hurdle to successful treatment. The primary challenge should be identifying and developing appropriate therapeutics for cancer patients to improve their survival. Multiple pathways are dysregulated in cancers, including disturbance in cellular metabolism, cell cycle, apoptosis, or epigenetic alterations. Over the last two decades, natural products have been a major research interest due to their therapeutic potential in various ailments. Natural compounds seem to be an alternative option for cancer management. Natural substances derived from plants and marine sources have been shown to have anti-cancer activity in preclinical settings. They might be proved as a sword to kill cancerous cells. The present review attempted to consolidate the available information on natural compounds derived from plants and marine sources and their anti-cancer potential underlying EMT mechanisms.     

Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m² on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R² values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment.     

Short peptide-based cross-β amyloids exploit dual residues for phosphoesterase like activity

Herein, we report that short peptides are capable of exploiting their anti-parallel registry to access cross-β stacks to expose more than one catalytic residue, exhibiting the traits of advanced binding pockets of enzymes. Binding pockets decorated with more than one catalytic residue facilitate substrate binding and process kinetically unfavourable chemical transformations. The solvent-exposed guanidinium and imidazole moieties on the cross-β microphases synergistically bind to polarise and hydrolyse diverse kinetically stable model substrates of nucleases and phosphatase. Mutation of either histidine or arginine results in a drastic decline in the rate of hydrolysis. These results not only support the argument of short amyloid peptides as the earliest protein folds but also suggest their interactions with nucleic acid congeners, foreshadowing the mutualistic biopolymer relationships that fueled the chemical emergence of life.

Amyloid based short peptide assemblies use antiparallel registry to expose multiple catalytic residues to bind and cleave kinetically stable phosphoester bonds of nucleic acid congeners, foreshadowing interactions of protein folds with nucleic acids.     

Spin state dependent peroxidase activity of heme bound amyloid β peptides relevant to Alzheimer's disease

The colocalization of heme rich deposits in the senile plaque of Aβ in the cerebral cortex of the Alzheimer''s disease (AD) brain along with altered heme homeostasis and heme deficiency symptoms in AD patients has invoked the association of heme in AD pathology. Heme bound Aβ complexes, depending on the concentration of the complex or peptide to heme ratio, exhibit an equilibrium between a high-spin mono-His bound peroxidase-type active site and a low-spin bis-His bound cytochrome b type active site. The high-spin heme–Aβ complex shows higher peroxidase activity than free heme, where compound I is the reactive oxidant. It is also capable of oxidizing neurotransmitters like serotonin in the presence of peroxide, owing to the formation of compound I. The low-spin bis-His heme–Aβ complex on the other hand shows enhanced peroxidase activity relative to high-spin heme–Aβ. It reacts with H₂O₂ to produce two stable intermediates, compound 0 and compound I, which are characterized by absorption, EPR and resonance Raman spectroscopy. The stability of compound I of low-spin heme–Aβ is accountable for its enhanced peroxidase activity and oxidation of the neurotransmitter serotonin. The effect of the second sphere Tyr10 residue of Aβ on the formation and stability of the intermediates of low-spin heme–Aβ has also been investigated. The higher stability of compound I for low-spin heme–Aβ is likely due to H-bonding interactions involving Tyr10 in the distal pocket.

Low-spin heme-Aβ forms stable compound 0 and compound I in the presence of H₂O₂ where compound I is responsible for its substantial peroxidase activity. This compound I also oxidizes neurotransmitters which is a typical hallmark of Alzheimer''s disease.     

Tailoring a robust Al-MOF for trapping C2H6 and C2H2 towards efficient C2H4 purification from quaternary mixtures

Light hydrocarbon separation is considered one of the most industrially challenging and desired chemical separation processes and is highly essential in polymer and chemical industries. Among them, separating ethylene (C₂H₄) from C2 hydrocarbon mixtures such as ethane (C₂H₆), acetylene (C₂H₂), and other natural gas elements (CO₂, CH₄) is of paramount importance and poses significant difficulty. We demonstrate such separations using an Al-MOF synthesised earlier as a non-porous material, but herein endowed with hierarchical porosity created under microwave conditions in an equimolar water/ethanol solution. The material possessing a large surface area (793 m² g⁻¹) exhibits an excellent uptake capacity for major industrial hydrocarbons in the order of C₂H₂ > C₂H₆ > CO₂ > C₂H₄ > CH₄ under ambient conditions. It shows an outstanding dynamic breakthrough separation of ethylene (C₂H₄) not only for a binary mixture (C₂H₆/C₂H₄) but also for a quaternary combination (C₂H₄/C₂H₆/C₂H₂/CO₂ and C₂H₄/C₂H₆/C₂H₂/CH₄) of varying concentrations. The detailed separation/purification mechanism was unveiled by gas adsorption isotherms, mixed-gas adsorption calculations, selectivity estimations, advanced computer simulations such as density functional theory (DFT), grand canonical Monte Carlo (GCMC) and ab initio molecular dynamics (AIMD), and stepwise multicomponent dynamic breakthrough experiments.

Industrially important C₂H₄ purification from multi-component hydrocarbon mixtures.     

Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure.     

Validated Simultaneous High-Performance Thin-Layer Chromatographic Analysis of Ursolic Acid, β-Sitosterol,Lupeol and Quercetin in the Methanolic Fraction of Ichnocarpus frutescens

JPC – Journal of Planar Chromatography – Modern TLC - A high-performance thin-layer chromatography (HPTLC) method for the simultaneous quantitative determination and validation of...