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Polymer brushes have witnessed extensive utilization and progress, driven by their distinct attributes in surface modification, tethered group functionality, and tailored interactions at the nanoscale, enabling them for various scientific and industrial applications of coatings, sensors, switchable/responsive materials, nanolithography, and lab-on-a-chips. Despite the wealth of experimental investigations into polymer brushes, this review primarily focuses on computational studies of antifouling polymer brushes with a strong emphasis on achieving a molecular-level understanding and structurally designing antifouling polymer brushes. Computational exploration covers three realms of thermotical models, molecular simulations, and machine-learning approaches to elucidate the intricate relationship between composition, structure, and properties concerning polymer brushes in the context of nanotribology, surface hydration, and packing conformation. Upon acknowledging the challenges currently faced, we extend our perspectives toward future research directions by delineating potential avenues and unexplored territories. Our overarching objective is to advance our foundational comprehension and practical utilization of polymer brushes for antifouling applications, leveraging the synergy between computational methods and materials design to drive innovation in this crucial field. 

Antifreezing hydrogels are essential for materials design and practical applications, but their development and understanding have been challenging due to their high-water content. Current antifreezing hydrogels typically rely on organic solvents or the addition of antifreezing agents. In this study, we present a novel crosslinking strategy to fabricate antifreezing hydrogels without the need for additional antifreezing agents. We introduce a new crosslinker, PEGn-EGINA, which combines highly hydrophilic EGINA with polyethylene glycol (PEG) of varying molecular weights. Utilizing PEGn-EGINA as the crosslinker, we synthesize Agar/Polyacrylamide (Agar/PAAm) double-network hydrogels, alongside conventional MBAA-crosslinked hydrogels for comparison. The resulting PEGn-EGINA-crosslinked hydrogels exhibit inherent antifreezing properties and retain their mechanical integrity even at subzero temperatures for extended periods. Molecular dynamics (MD) simulations further reveal that the antifreezing behavior observed in the PEGn-EGINA-crosslinked hydrogels can be attributed to their highly hydrophilic and tightly crosslinked double-network structures. These structures enable strong bindings between water and the hydrogel network, thus effectively preventing the formation of ice crystals within the hydrogels. Notably, PEGn-EGINA-crosslinked hydrogels not only demonstrate superior mechanical performance compared to MBAA-crosslinked hydrogels, but also maintain their mechanical properties even in frozen conditions, making them suitable for a wide range of applications. This study presents a simple yet effective design concept for highlighting the role of novel crosslinker in enhancing antifreezing and mechanical properties, showcasing their potential for various applications that require both antifreezing capabilities and robust mechanical performance. 

The development and understanding of antifreezing hydrogels are crucial both in principle and practice for the design and delivery of new materials. The current antifreezing mechanisms in hydrogels are almost exclusively derived from their incorporation of antifreezing additives, rather than from the inherent properties of the polymers themselves. Moreover, developing a computational model for the independent yet interconnected double-network (DN) structures in hydrogels has proven to be an exceptionally difficult task. Here, we develop a multiscale simulation platform, integrating ‘random walk reactive polymerization’ (RWRP) with molecular dynamics (MD) simulations, to computationally construct a physically-chemically linked PVA/PHEAA DN hydrogels from monomers that mimic a radical polymerization and to investigate water structures, dynamics, and interactions confined in PVA/PHEAA hydrogels with various water contents and temperatures, aiming to uncover antifreezing mechanism at atomic levels. Collective simulation results indicate that the antifreezing property of PVA/PHEAA hydrogels arises from a combination of intrinsic, strong water-binding networks and crosslinkers and tightly crosslinked and interpenetrating double-network structures, both of which enhance polymer-water interactions for competitively inhibiting ice nucleation and growth. These computational findings provide atomic-level insights into the interplay between polymers and water molecules in hydrogels, which may determine their resistance to freezing.

 

Amyloid-β (Aβ) and semen-derived enhancer of viral infection (SEVI) are considered as the two causative proteins for central pathogenic cause of Alzheimer’s disease (AD) and HIV/AIDS, respectively. Separately, Aβ-AD and SEVI-HIV/AIDS systems have been studied extensively both in fundamental research and in clinical trials. Despite significant differences between Aβ-AD and SEVI-HIV/AIDS systems, they share some commonalities on amyloid and antimicrobial characteristics between Aβ and SEVI, there are apparent overlaps in dysfunctional neurological symptoms between AD and HIV/AIDS. Few studies have reported a potential pathological link between Aβ-AD and SEVI-HIV/AIDS at a protein level. Here, we demonstrate the cross-seeding interactions between Aβ and SEVI proteins using in vitro and in vivo approaches. Cross-seeding of SEVI with Aβ enabled to completely prevent Aβ aggregation at sub-stoichiometric concentrations, disaggregate preformed Aβ fibrils, reduce Aβ-induced cell toxicity, and attenuate Aβ-accumulated paralysis in transgenic AD C. elegans. This work describes a potential crosstalk between AD and HIV/AIDS via the cross-seeding between Aβ and SEVI, identifies SEVI as Aβ inhibitor for possible treatment or prevention of AD, and explains the role of SEVI in the gender difference in AD.

 

The past decade has witnessed the growing interest and advances in aggregation-induced emission (AIE) molecules as driven by their unique fluorescence/optical properties in particular sensing applications including biomolecule sensing/detection, environmental/health monitoring, cell imaging/tracking, and disease analysis/diagnosis. In sharp contrast to conventional aggregation-caused quenching (ACQ) fluorophores, AIE molecules possess intrinsic advantages for the study of disease-related protein aggregates, but such studies are still at an infant stage with much less scientific exploration. This outlook mainly aims to provide the first systematic summary of AIE-based molecules for amyloid protein aggregates associated with neurodegenerative diseases. Despite a limited number of studies on AIE–amyloid systems, we will survey recent and important developments of AIE molecules for different amyloid protein aggregates of Aβ (associated with Alzheimer's disease), insulin (associated with type 2 diabetes), (α-syn, associated with Parkinson's disease), and HEWL (associated with familial lysozyme systemic amyloidosis) with a particular focus on the working principle and structural design of four types of AIE-based molecules. Finally, we will provide our views on current challenges and future directions in this emerging area. Our goal is to inspire more researchers and investment in this emerging but less explored subject, so as to advance our fundamental understanding and practical design/usages of AIE molecules for disease-related protein aggregates. 

Prevention and detection of misfolded amyloid proteins and their β-structure-rich aggregates are the two promising but different (pre)clinical strategies to treat and diagnose neurodegenerative diseases including Alzheimer's diseases (AD) and type II diabetes (T2D). Conventional strategies prevent the design of new pharmaceutical molecules with both amyloid inhibition and detection functions. Here, we propose a “like-interacts-like” design principle to de novo design a series of new self-assembling peptides (SAPs), enabling them to specifically and strongly interact with conformationally similar β-sheet motifs of Aβ (association with AD) and hIAPP (association with T2D). Collective in vitro experimental data from thioflavin (ThT), atomic force microscopy (AFM), circular dichroism (CD), and cell assay demonstrate that SAPs possess two integrated functions of (i) amyloid inhibition for preventing both Aβ and hIAPP aggregation by 34–61% and reducing their induced cytotoxicity by 7.6–35.4% and (ii) amyloid sensing for early detection of toxic Aβ and hIAPP aggregates using in-house SAP-based paper sensors and SPR sensors. The presence of both amyloid inhibition and detection in SAPs stems from strong molecular interactions between amyloid aggregates and SAPs, thus providing a new multi-target model for expanding the new therapeutic potentials of SAPs and other designs with built-in amyloid inhibition and detection functions.