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Protein glycation is initiated by a nucleophilic addition reaction between the free amino group from a protein, lipid or nucleic acid and the carbonyl group of a reducing sugar. This reaction forms a reversible Schiff base, which rearranges over a period of days to produce ketoamine or Amadori products. The Amadori products undergo dehydration and rearrangements and develop a cross-link between adjacent proteins, giving rise to protein aggregation or advanced glycation end products (AGEs). A number of studies have shown that glycation induces the formation of the β-sheet structure in β-amyloid protein, α-synuclein, transthyretin (TTR), copper-zinc superoxide dismutase 1 (Cu, Zn-SOD-1), and prion protein. Aggregation of the β-sheet structure in each case creates fibrillar structures, respectively causing Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, familial amyloid polyneuropathy, and prion disease. It has been suggested that oligomeric species of glycated α-synuclein and prion are more toxic than fibrils. This review focuses on the pathway of AGE formation, the synthesis of different types of AGE, and the molecular mechanisms by which glycation causes various types of neurodegenerative disease. It discusses several new therapeutic approaches that have been applied to treat these devastating disorders, including the use of various synthetic and naturally occurring inhibitors. Modulation of the AGE-RAGE axis is now considered promising in the prevention of neurodegenerative diseases. Additionally, the review covers several defense enzymes and proteins in the human body that are important anti-glycating systems acting to prevent the development of neurodegenerative diseases.

Problems with erroneous forecasts of electricity production from solar farms create serious operational, technological, and financial challenges to both Solar farm owners and electricity companies. Accurate prediction results are necessary for efficient spinning reserve planning as well as regulating inertia and power supply during contingency events. In this work, the impact of several climatic conditions on solar electricity generation in Amherst. Furthermore, three machine learning models using Lasso Regression, ridge Regression, ElasticNet regression, and Support Vector Regression, as well as deep learning models for time series analysis include long short-term memory, bidirectional LSTM, and gated recurrent unit along with their variants for estimating solar energy generation for every five-minute interval on Amherst weather power station. These models were evaluated using mean absolute error root means square error, mean square error, and mean absolute percentage error. It was observed that horizontal solar irradiance and water saturation deficiency had a highly proportional relationship with Solar PV electricity generation. All proposed machine learning models turned out to perform well in predicting electricity generation from the analyzed solar farm. Bi-LSTM has performed the best among all models with 0.0135, 0.0315, 0.0012, and 0.1205 values of MAE, RMSE, MSE, and MAPE, respectively. Comparison with the existing methods endorses the use of our proposed RNN variants for higher efficiency, accuracy, and robustness. Multistep-ahead solar energy prediction is also carried out by exploiting hybrids of LSTM, Bi-LSTM, and GRU.

Conformational alterations of bovine hemoglobin (Hb) upon sequential addition of glyoxal over a range of 0-90% v/v were investigated. At 20% v/v glyoxal, molten globule (MG) state of Hb was observed by altered tryptophan fluorescence, high ANS binding, existence of intact heme, native-like secondary structure as depicted by far-UV circular dichroism (CD) and ATR-FTIR spectra as well as loss in tertiary structure as confirmed by near-UV CD spectra. In addition, size exclusion chromatography analysis depicted that MG state at 20% v/v glyoxal corresponded to expanded pre-dissociated dimers. Aggregates of Hb were detected at 70% v/v glyoxal. These aggregates of Hb had altered tryptophan environment, low ANS binding, exposed heme, increased β-sheet secondary structure, loss in tertiary structure, enhanced thioflavin T (ThT) fluorescence and red shifted Congo Red (CR) absorbance. On incubating Hb with 30% v/v glyoxal for 0-20 days, advanced glycation end products (AGEs) were detected on day 20. These AGEs were characterised by enhanced tryptophan fluorescence at 450 nm, exposure of heme, increase in intermolecular β-sheets, enhanced ThT fluorescence and red shift in CR absorbance. Comet assay revealed aggregates and AGEs to be genotoxic in nature. Scanning electron microscopy confirmed the amorphous structure of aggregates and branched fibrils of AGEs. The transformation of α-helix to β-sheet usually alters the normal protein to amyloidogenic resulting in a variety of protein conformational disorders such as diabetes, prion and Huntington's.

Binding of hippuric acid (HA), a uremic toxin, with human serum albumin (HSA) has been examined by isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC), molecular docking, circular dichroism (CD) and fluorescence spectroscopy to understand the reason that govern its impaired elimination through hemodialysis. ITC results shows that the HA binds with HSA at high (K b ~10(4)) and low affinity (K b ~10(3)) sites whereas spectroscopic results predict binding at a single site (K b~10(3)). The HA form complex with HSA that involves electrostatic, hydrogen and hydrophobic binding forces as illustrated by calculated thermodynamic parameters. Molecular docking and displacement studies collectively revealed that HA bound to both site I and site II; however, relatively strongly to the later. Esterase-like activity of HSA confirms the involvement of Arg410 and Tyr411 of Sudlow site II in binding of HA. CD results show slight conformational changes occurs in the protein upon ligation that may be responsible for the discrepancy in van't Hoff and calorimetric enthalpy change. Furthermore, an increase in T(1)(m) and T(2)(m) is observed from DSC results that indicate increase in stability of HSA upon binding to HA. The combined results provide that HA binds to HSA and thus its elimination is hindered.

In this work, a ternary composite containing a Schiff base adduct (chitosan-glutaraldehyde) along with activated charcoal (Ch-Glu/AC) was successfully prepared that contains activated charcoal with cross-linked chitosan. The Schiff base adduct was obtained by reaction of a dialdehyde bifunctional cross-linker agent (glutaraldehyde; Glu), where various methods were employed to study the morphology, material crystallinity, surface area, and surface functional group of the ternary composite (Ch-Glu/AC). Ch-Glu/AC was applied as an adsorbent to remove a cationic dye (thionine dye, TH) from aqueous media. The effect of various independent variables on the adsorption process including adsorbent dose (A: 0.02–0.1 g), solution pH (B: 4–10), temperature (C: 30–50 °C), and time (D: 30–180 min) were investigated and optimized using response surface methodology-Box–Behnken design (RSM-BBD). The results demonstrated that TH dye adsorption on the Ch-Glu/AC surface obeyed the pseudo-first order (PFO) kinetic model, and the Freundlich isotherm was obeyed at equilibrium. The maximum adsorption capacity (qm) of the TH dye was 30.8 mg/g at 50 °C. The TH dye adsorption mechanism onto the composite surface was attributed to the electrostatic interaction, π-π interaction, and H-bonding. The findings of this work reveal the feasibility of Ch-Glu/AC as a candidate adsorbent for effective removal of cationic dyes from aquatic media.

Real-world models, like those used in social studies, epidemiology, energy transport, engineering, and finance, are often called “multi-layer networks.” In this work, we have described a controller that connects the paths of synchronized models that are grouped together in clusters. We did this using Lyapunov theory and a variety of coupled matrices to look into the link between the groups of chaotic systems based on influenza and covid-19. Our work also includes the use of external synchrony in biological systems. For example, we have explained in detail how the pandemic disease covid-19 will get weaker over time and become more like influenza. The analytical way to get these answers is to prove a theorem, and the numerical way is to use MATLAB to run numerical simulations.

Over the past two decades, there has been considerable research interest in the use of nanoparticles in the study of protein and peptide aggregation, and of amyloid-related diseases. The influence of nanoparticles on amyloid formation yields great interest due to its small size and high surface area-to-volume ratio. Targeting nucleation kinetics by nanoparticles is one of the most searched for ways to control or induce this phenomenon. The observed effect of nanoparticles on the nucleation phase is determined by particle composition, as well as the amount and nature of the particle's surface. Various thermodynamic parameters influence the interaction of proteins and nanoparticles in the solution, and regulate the protein assembly into fibrils, as well as the disaggregation of preformed fibrils. Metals, organic particles, inorganic particles, amino acids, peptides, proteins, and so on are more suitable candidates for nanoparticle formulation. In the present review, we attempt to explore the effects of nanoparticles on protein and peptide fibrillation processes from both perspectives (ie, as inducers and inhibitors on nucleation kinetics and in the disaggregation of preformed fibrils). Their formulation and characterization by different techniques have been also addressed, along with their toxicological effects, both in vivo and in vitro.

Ets-related gene (ERG) is overexpressed as a fusion protein in prostate cancer. During metastasis, the pathological role of ERG is associated with cell proliferation, invasion, and angiogenesis. Here, we hypothesized that miRNAs regulate ERG expression through its 3ʹUTR. Several bioinformatics tools were used to identify miRNAs and their binding sites on 3ʹUTR of ERG. The selected miRNAs expression was analyzed in prostate cancer samples by qPCR. The miRNAs overexpression was induced in prostate cancer cells (VCaP) to analyze ERG expression. Reporter gene assay was performed to evaluate the ERG activity in response to selected miRNAs. The expression of ERG downstream target genes was also investigated through qPCR after miRNAs overexpression. To observe the effects of selected miRNAs on cell proliferation and migration, scratch assay was performed to calculate the cell migration rate. miR-4482 and miR-3912 were selected from bioinformatics databases. miR-4482 and -3912 expression were decreased in prostate cancer samples, as compared to controls ( p<0 . 05 and p<0 . 001 ), respectively. Overexpression of miR-4482 and miR-3912 significantly reduced ERG mRNA ( p<0 . 001 and p<0 . 01 ), respectively ) and protein ( p<0 . 01 ) in prostate cancer cells. The transcriptional activity of ERG was significantly reduced ( p<0 . 01 ) in response to miR-4482 and-3912. ERG angiogenic targets and cell migration rate was also reduced significantly ( p<0 . 001 ) after miR-4482 and -3912 over-expression. This study indicates that miR-4482 and -3912 can suppress the ERG expression and its target genes, thereby, halt prostate cancer progression. These miRNAs may be employed as a potential therapeutic target for the miRNA-based therapy against prostate cancer.

In this paper, we discussed the impossibility of achieving zero-covid cases per day for all time with the help of fuzzy theory, while how a single case can trigger chaotic situation in the nearby city is elaborated using multi-scrolls. To accomplish this goal, we consider the number of new cases per day; x 1 to be the preferred state variable by restricting its value to the interval (0, 1). One can need to think of x 1 as a member of a fuzzy set and provide that set with appropriate membership functions. Moreover, how a single incident in one city can spread chaos to other cities is also addressed at length, using multi-scroll attractors and the signal excitation function. In addition, a bifurcation diagram of daily new instances vs the parameter α 1 is shown, elaborating that daily new cases may show a decrease under strict rules and regulations, but can again lead to chaos. Apart from biologist, this paper can play vital role for engineers as well in a sense that, a signal function can be embedded in non-symmetric systems for the creation of multi-scroll attractors in all directions using a generalized algorithm that has been designed in the current work. Finally, it is our future target to show that the covid is leading towards influenza and will be no more dangerous as was in the past.

The rate of death or major bleeding was significantly higher among preterm infants with severe thrombocytopenia assigned to transfusions at higher platelet-count thresholds (50,000 per cubic millimeter) than among those assigned to lower thresholds (25,000 per cubic millimeter).