Extracellular vesicle (EVs)-mediated cell-to-cell communication is crucial for cell growth, signaling, and metabolism. Exosomes are a subtype of EVs originating from endosomal cellular machinery and have a relatively smaller size (30–150 nM). They carry nucleic acids, proteins, miRNA, lipids, metabolites, and growth factors, making them an exciting research tool for understanding the pathophysiology of complex human diseases. Different brain cells also communicate with themselves by the release of exosomes which helps in overall brain growth and in cell signaling. Recent studies have highlighted the importance of exosomes in neurodegenerative diseases (NDDs) of Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), prion, and Huntington’s disease (HD). Exosomes are involved in the spread of amyloid-like protein aggregates formed in these diseases, but a comprehensive understanding of this spread mechanism is limited. In this article, we have analyzed the roles of exosomes in the spread of amyloid protein aggregates in the NDDs. Furthermore, we have discussed possible measures to address several gaps in our current understanding of cross talks between exosomes and protein aggregates in neurodegenerative disorders (NDDs). We have also discussed the therapeutic opportunities to delay or prevent pathogenic amyloid aggregate spread by exploiting exosomal transport. Overall, the review will contribute to develop a better understanding vesicular transport of amyloids and will help contend their propagation in different NDDs.
Soy okara, a nutrient-rich byproduct of tofu production, has limited use in food and feed due to its high content of oligosaccharides and enzyme inhibitors. Its high moisture content causes quick spoilage, leading to frequent waste and environmental concerns. To overcome these challenges, drying can extend its shelf life and enhance its potential for higher-value applications. This study investigates microwave-assisted foam mat drying (MFD) of okara, aiming to optimize foaming conditions and enhance drying and product quality. The optimal conditions-48.06% okara pulp, 2.64% egg white powder (EWP), 2.91% maltodextrin (MD), and 3.52 min of whipping time (WT)-enhanced foam stability and expansion. Drying at 300, 450, and 600 W followed the Page model (R-2 > 0.989), with higher power accelerating moisture removal. Microwave drying reduced moisture content and bulk density, resulting in improved water solubility index and flowability with increasing wattage. Foam-dried samples exhibited brighter color, lower browning index, and a porous microstructure. Structural analysis through XRD and SEM confirmed increased porosity and reduced crystallinity. FTIR spectra highlighted changes in functional groups due to the foaming agents, while TGA revealed that the foamed samples were thermally less stable, with lower degradation temperatures (Tp) and higher weight loss (Delta W) compared to the control samples. Additionally, foam samples retained total phenolic content (TPC) and antioxidant activity (DPPH inhibition), further increasing the potential value of dried okara. MFD offers a potentially scalable solution for valorizing soy okara, reducing waste, and enhancing resource efficiency, with promising applications in functional foods and nutraceuticals.
War-traumatized refugees face significant mental health challenges, yet access to care is often limited due to financial, logistical, and awareness barriers. The present review aims to identify the existing digital self-help tools for mental health problems among war-traumatized refugees and assess their effectiveness via meta-analysis. Databases such as PubMed, Google Scholar, SAGE, PsycNET, ScienceDirect, Scopus, Web of Science, and JSTOR were searched in July 2024. A comprehensive literature search yielded 11 studies. The review identified self-help apps, including Tetris Gameplay, Step-by-Step, Happy Helping Hand Game, Sanadak, Self-Help Plus, Digital Audio Files, and a Web-Based Module (Tell Your Story), as effective in managing mental health problems. The results of the meta-analysis revealed that digital self-help tools have a mild, yet significant, overall effect (SMD = -0.34, 95
This systematic review presents a comprehensive analysis of hybrid optimization frameworks that combine hyperparameter-tuning and feature selection to enhance machine learning (ML) models for disease classification. Unlike previous studies that treat these processes separately, this study demonstrates how their integration improves diagnostic accuracy, computational efficiency, and clinical interpretability. Hyperparameter-tuning—optimizing learning rates, regularization terms, and architectural parameters—ensures models adapt effectively to complex biomedical data. Meanwhile, feature selection techniques (filter, wrapper, and embedded methods) identify critical biomarkers, reducing dimensionality and mitigating overfitting risks. This review findings reveal that simultaneous optimization strategies, such as metaheuristic algorithms combined with ML, outperform sequential approaches, achieving 12–15
A 2D bimetallic chalcogenide—cobalt manganese sulfide (CoMn 2 S 4 ) nanoflakes—designed using density functional theory (DFT) calculations, works as a binder free standalone electrode material for asymmetric supercapacitor devices.
