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Posttranslational modifications play a crucial role in governing cellular functions and protein behavior. Researchers have implicated dysregulated posttranslational modifications in protein misfolding, which results in cytotoxicity, particularly in neurodegenerative diseases such as Alzheimer disease, Parkinson disease, and Huntington disease. These aberrant posttranslational modifications cause proteins to gather in certain parts of the brain that are linked to the development of the diseases. This leads to neuronal dysfunction and the start of neurodegenerative disease symptoms. Cognitive decline and neurological impairments commonly manifest in neurodegenerative disease patients, underscoring the urgency of comprehending the posttranslational modifications' impact on protein function for targeted therapeutic interventions. This review elucidates the critical link between neurodegenerative diseases and specific posttranslational modifications, focusing on Tau, APP, α‐synuclein, Huntingtin protein, Parkin, DJ‐1, and Drp1. By delineating the prominent aberrant posttranslational modifications within Alzheimer disease, Parkinson disease, and Huntington disease, the review underscores the significance of understanding the interplay among these modifications. Emphasizing 10 key abnormal posttranslational modifications, this study aims to provide a comprehensive framework for investigating neurodegenerative diseases holistically. The insights presented herein shed light on potential therapeutic avenues aimed at modulating posttranslational modifications to mitigate protein aggregation and retard neurodegenerative disease progression. [ABSTRACT FROM AUTHOR]

Lung cancer is indeed a major cause of cancer‐related deaths worldwide. The development of tumors involves a complex interplay of genetic, epigenetic, and environmental factors. Epigenetic mechanisms, including DNA methylation (DNAm), histone modifications, and microRNA expression, play a crucial role in this process. Changes in DNAm patterns can lead to the silencing of important genes involved in cellular functions, contributing to the development and progression of lung cancer. MicroRNAs and exosomes have also emerged as reliable biomarkers for lung cancer. They can provide valuable information about early diagnosis and treatment assessment. In particular, abnormal hypermethylation of gene promoters and its effects on tumorigenesis, as well as its roles in the Wnt signaling pathway, have been extensively studied. Epigenetic drugs have shown promise in the treatment of lung cancer. These drugs target the aberrant epigenetic modifications that are involved in the development and progression of the disease. Several factors have been identified as drug targets in non‐small cell lung cancer. Recently, combination therapy has been discussed as a successful strategy for overcoming drug resistance. Overall, understanding the role of epigenetic mechanisms and their targeting through drugs is an important area of research in lung cancer treatment. [ABSTRACT FROM AUTHOR]

Antimicrobial Peptides (AMPs) have been considered as potential alternatives for infection therapeutics since antibiotic resistance has been raised as a global problem. The AMPs are a group of natural peptides that play a crucial role in the immune system in various organisms AMPs have features such as a short length and efficiency against microbes. Importantly, they have represented low toxicity in mammals which makes them potential candidates for peptide-based drugs. Nevertheless, the discovery of AMPs is accompanied by several issues which are associated with labour-intensive and time-consuming wet-lab experiments. During the last decades, numerous studies have been conducted on the investigation of AMPs, either natural or synthetic type, and relevant data are recently available in many databases. Through the advancement of computational methods, a great number of AMP data are obtained from publicly accessible databanks, which are valuable resources for mining patterns to design new models for AMP prediction. However, due to the current flaws in assessing computational methods, more interrogations are warranted for accurate evaluation/analysis. Considering the diversity of AMPs and newly reported ones, an improvement in Machine Learning algorithms are crucial. In this review, we aim to provide valuable information about different types of AMPs, their mechanism of action and a landscape of current databases and computational tools as resources to collect AMPs and beneficial tools for the prediction and design of a computational model for new active AMPs. [ABSTRACT FROM AUTHOR]

This study has been focused on the batch culture removal of Cu2+and Ni2+ions from the aqueous solution using marine brown algaeSargassum angustifolium. Influences of parameters like pH, initial metal ions concentration and biosorbent dosage on nickel and copper adsorption were also examined using the Box–Behnken design matrix. For biosorption of Cu2+the optimum pH value was determined as 5.0, optimum biosorbent concentration to 1.0 g/L and optimum initial concentration 0.15 mmol/L. For the biosorption of Ni2+, the optimal condition was the same but the optimum pH value was determined as 6.0. Desorption experiments indicated that CH3COOH and EDTA were efficient desorbents for recovery from Cu2+and Ni2+. The Langmuir isotherm model was applied to describe the biosorption of the Cu2+and Ni2+intoS. angustifolium. The maximum uptake of Cu2+and Ni2+ions by theS. angustifoliumbiomass under the optimal conditions was approximately 0.94 and 0.78 mmol/g dry alga, respectively. Response surface models showed that the data were adequately fitted to a second-order polynomial model. Analysis of variance showed a high coefficient of determination value (R2=0.993 for Cu2+and 0.991 for Ni2+) and a satisfactory second-order regression model was derived. In addition, results reported in this research demonstrated the feasibility of employingS. angustifoliumas biosorbent for Ni2+and Cu2+removal. [ABSTRACT FROM PUBLISHER]

Organ-on-a-chip technology has gained great interest in recent years given its ability to control the spatio-temporal microenvironments of cells and tissues precisely. While physical parameters of the respective niche such as microchannel network sizes, geometric features, flow rates, and shear forces, as well as oxygen tension and concentration gradients, have been optimized for stem cell cultures, little has been done to improve cell-matrix interactions in microphysiological systems. Specifically, detailed research on the effect of matrix elasticity and extracellular matrix (ECM) nanotopography on stem cell differentiation are still in its infancy, an aspect that is known to alter a stem cell's fate. Although a wide range of hydrogels such as gelatin, collagen, fibrin, and others are available for stem cell chip cultivations, only a limited number of elasticities are generally employed. Matrix elasticity and the corresponding nanotopography are key factors that guide stem cell differentiation. Given this, we investigated the addition of gold nanowires into hydrogels to create a tunable biointerface that could be readily integrated into any organ-on-a-chip and cell chip system. In the presented work, we investigated the matrix elasticity (Young's modulus, stiffness, adhesive force, and roughness) and nanotopography of gold nanowire loaded onto fibrin hydrogels using the bio-AFM (atomic force microscopy) method. Additionally, we investigated the capacity of human amniotic mesenchymal stem cells (hAMSCs) to differentiate into osteo- and chondrogenic lineages. Our results demonstrated that nanogold structured-hydrogels promoted differentiation of hAMSCs as shown by a significant increase in Collagen I and II production. Additionally, there was enhanced calcium mineralization activity and proteoglycans formation after a cultivation period of two weeks within microfluidic devices. [ABSTRACT FROM AUTHOR]

Studying interactions between drugs and cell membranes is of great interest to designing novel drugs, optimizing drug delivery, and discerning drug mechanism action. In this study, we investigated the physical properties of the bilayer membrane model of POPC upon interaction with ibuprofen (IBU) using molecular dynamics simulations. The area per lipid (APL) was calculated to describe the effect of ibuprofen on the packing properties of the lipid bilayer. The APL was 0.58 nm 2 and 0.63 nm 2 for the membrane in low and high IBU respectively, and 0.57 nm 2 for the membrane without IBU. Our finding showed that the mean square deviation (MSD) increased with increased ibuprofen content. In addition, the order parameter for the hydrocarbon chain of lipids increased with increased ibuprofen content. There was an increment in the transfer free energy after the head group region while it was maximum in the hydrophobic core for hydrogen peroxide (H 2 O 2 ) (∼6.2 kcal.mol -1 ) and H 2 O (∼3.4 kcal.mol -1 ) which then decreased to respective values of (∼4.6 kcal.mol -1 ), and (∼2.3 kcal.mol -1 ) at the center of the bilayer in the presence of IBU. It seems that in the presence of ibuprofen, the free energy profile of the permeability of water and H 2 O 2 significantly decreased. These findings show that ibuprofen significantly influences the physical properties of the bilayer by decreasing the packing and intermolecular interaction in the hydrocarbon chain region and increasing the water permeability of the bilayer. These results may provide insights into the local cytotoxic side effects of ibuprofen and its underlying molecular mechanisms.Communicated by Ramaswamy H. Sarma.