Enhanced Antistatic and Self-Heatable Wearable Coating with Self-Tiered Structure Caused by Amphiphilic MXene in Waterborne Polymer.

The antistatic and self-heatable flexible coating is highly desired for next-generation multifunctional clothing. MXene is a promising filler that possesses an excellent conductivity, an efficient photothermal conversion, and an outstanding compatibility with the waterborne polymer. In this study, MXene was integrated with waterborne polyacrylate by a solution-blending method. The polyacrylate/MXene composites display a self-tiered structure, and the composite coated leather possesses a surface resistivity of 7.85 × 109 Ω with 2 wt % loading, satisfying the B-level of the antistatic standard. The polyacrylate/MXene-0.5 wt % shows a higher temperature increase of 46.9 °C than that of pure polyacrylate after being irradiated by a 275 W IR light for 5 min, and the surface temperature of polyacrylate/MXene-0.5 wt % composite coated leather is 5.4 °C higher than that of polyacrylate coated leather after being irradiated by sunlight for 30 min. The tensile strength of the polyacrylate/MXene-1 wt % composite is increased by 28.3% compared with that of pure polyacrylate. All of the results prove its promising application in the multifunctional coating. Moreover, amphiphilic MXene was produced by changing the etching degree, which resulted in a self-tiered structure of the polyacrylate/MXene composite owing to the improved interfacial activity of MXene. The amphiphilic MXene possesses a decreased surface tension and can serve as a stabilizer for a Pickering emulsion, which suggests novel routes for constructing a multifunctional polymer/MXene composite.

Autophagy and machine learning: Unanswered questions.

Autophagy is a critical conserved cellular process in maintaining cellular homeostasis by clearing and recycling damaged organelles and intracellular components in lysosomes and vacuoles. Autophagy plays a vital role in cell survival, bioenergetic homeostasis, organism development, and cell death regulation. Malfunctions in autophagy are associated with various human diseases and health disorders, such as cancers and neurodegenerative diseases. Significant effort has been devoted to autophagy-related research in the context of genes, proteins, diagnosis, etc. In recent years, there has been a surge of studies utilizing state of the art machine learning (ML) tools to analyze and understand the roles of autophagy in various biological processes. We taxonomize ML techniques that are applicable in an autophagy context, comprehensively review existing efforts being taken in this direction, and outline principles to consider in a biomedical context. In recognition of recent groundbreaking advances in the deep-learning community, we discuss new opportunities in interdisciplinary collaborations and seek to engage autophagy and computer science researchers to promote autophagy research with joint efforts.