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.     

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.     

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.     

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.     

An organoselenium-based highly sensitive and selective fluorescent "turn-on" probe for the Hg2+ ion

An organoselenium-based NSe(3) type of tripodal system 2 as a Hg(2+)-selective fluorescence "turn-on" probe is described. The "turn-on" fluorescence behavior of this selenotripod 2 is significant because it depends on Hg-Se bond formation and acts as a reporting unit for this system. The system exhibits immediate response (15 s) with a subnanomolar detection limit (0.1 nM) for the Hg(2+) ion. It efficiently detects both aqueous and nonaqueous Hg(2+) at 2 nM concentration.     

Procedures for construction of anisotropic elastic-plastic property closures for face-centered cubic polycrystals using first-order bounding relations

Microstructure-sensitive design (MSD) is a novel mathematical framework that facilitates a rigorous consideration of the material microstructure as a continuous design variable in the engineering design enterprise [Adams, B.L., Henrie, A., Henrie, B., Lyon, M., Kalidindi, S.R., Garmestani, H., 2001. Microstructure-sensitive design of a compliant beam. J. Mech. Phys. Solids 49(8), 1639-1663; Adams, B.L., Lyon, M., Henrie, B., 2004. Microstructures by design: linear problems in elastic-plastic design. Int. J. Plasticity 20(8-9), 1577-1602; Kalidindi, S.R., Houskamp, J.R., Lyons, M., Adams, B.L., 2004. Microstructure sensitive design of an orthotropic plate subjected to tensile load. Int. J. Plasticity 20(8-9), 1561-1575]. MSD employs spectral representations of the local state distribution functions in describing the microstructure quantitatively, and these in turn enable development of invertible linkages between microstructure and effective properties using established homogenization (composite) theories. As a natural extension of the recent publications in MSD, we provide in this paper a detailed account of the methods that can be readily used by mechanical designers to construct first-order elastic-plastic property closures. The main focus in this paper is on the crystallographic texture (also called Orientation Distribution Function or ODF) as the main microstructural parameter controlling the elastic and yield properties of cubic (fcc and bcc) polycrystalline metals. The following specific advances are described in this paper: (i) derivation of rigorous first-order bounds for the off-diagonal terms of the effective elastic stiffness tensor and their incorporation in the MSD framework, (ii) delineation of the union of the property closures corresponding to both the upper and lower bound theories resulting in comprehensive first-order closures, (iii) development of generalized and readily usable expressions for effective anisotropic elastic-plastic properties that could be applied to all cubic polycrystals, and (iv) identification of the locations of readily available or easily processable ODFs (e.g. textures that are produced by rolling, drawing, etc.) on the property closures. It is anticipated that the advances communicated in this paper will make the mathematical framework of MSD highly accessible to the mechanical designers.     

A four-arm Sagnac interferometric switch

A four-arm Sagnac interferometric switch is demonstrated. The switch works on the nonlinearity of the Pancharatnam's phase in a Young's interference set-up with differently polarized coherent laser beams.     

Dynamics of a supercooled liquid

The theory of collective motion in liquids suggested by the authors has been found to explain successfully the recent experimental results of temperature dependent disorder in supercooled liquid gallium. Metastability limit is exhibited through a singularity of S(k, ω = 0) and corresponds to a critical value of correlation between different particles beyond which the supercooled liquid goes to the thermodynamically stable solid state.