Human body cells and our daily electronic devices both communicate information within their distinct worlds by regulating the flow of electrons across specified membranes. While electronic devices depend on the flow of electrons generated by conductive materials to communicate within a digital network, biological systems use ion gradients, created in analog biochemical reactions, to trigger biological data transmission throughout multicellular systems. Electrogenetics is an emerging concept in synthetic biology in which electrons generated by digital electronic devices program customized electron-responsive biological units within living cells. In this paper, we outline endeavors to design direct electrogenetic interfaces to control cell behaviors in therapeutically engineered mammalian cells. We also discuss prospects for the world of electrogenetics, focusing on how to engineer the next generation of therapeutic cells controlled by electronic devices and the internet of the body.
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http://dx.doi.org/10.1016/j.chembiol.2025.01.003 | DOI Listing |
Front Public Health
January 2025
Department of Product Design, Faculty of Fine Arts and Design, College of Chinese & ASEAN Arts, Chengdu University, Chengdu, China.
Introduction: Differences exist in the rate of aging between individuals residing in urban and rural areas in China, with rural areas experiencing a more pronounced impact. Smart aging represents a prevalent future trend in this regard, though its development will inevitably face challenges. However, studies focusing on rural areas are scarce.
View Article and Find Full Text PDFNpj Spintron
January 2025
Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
The interplay of electronic charge, spin, and orbital currents, coherently driven by picosecond long oscillations of light fields in spin-orbit coupled systems, is the foundation of emerging terahertz lightwave spintronics and orbitronics. The essential rules for how terahertz fields interact with these systems in a nonlinear way are still not understood. In this work, we demonstrate a universally applicable electronic nonlinearity originating from spin-orbit interactions in conducting materials, wherein the interplay of light-induced spin and orbital textures manifests.
View Article and Find Full Text PDFNano Lett
January 2025
Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies (C2N), 91120 Palaiseau, France.
The ability to tune the energy gap in bilayer graphene makes it the perfect playground for the study of the effects of internal electric fields, such as the crystalline field, which are developed when other layered materials are deposited on top of it. Here, we introduce a novel device architecture allowing simultaneous control over the applied displacement field and the crystalline alignment between two materials. Our experimental and numerical results confirm that the crystal field and electrostatic doping due to the interface reflect the 120° symmetry of the bilayer graphene/BN heterostructure and are highly affected by the commensurate state.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Institute of New Energy Technology, College of Physics and Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong, China.
Formamidinium-based perovskites (FA perovskites) often incorporate methylammonium chloride (MACl) to stabilize the α-FAPbI phase and prevent formation of the δ phase. However, MACl undergoes deprotonation and reacts with FA, leading to the generation of unstable byproducts that can cause component degradation and negatively impact the device performance. In this study, we introduce ethylenediaminetetramethylenephosphonic acid as a corrosion inhibitor, which effectively prevents the formation of these byproducts and stabilizes α-FAPbI.
View Article and Find Full Text PDFWater Res
January 2025
Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK; SWING - Department of Built Environment, Oslo Metropolitan University, St Olavs plass 0130, Oslo, Norway. Electronic address:
Climate resilience in water resource recovery facilities (WRRFs) necessitates improved adaptation to shock-loading conditions and mitigating greenhouse gas emission. Data-driven learning methods are widely utilised in soft-sensors for decision support and process optimization due to their simplicity and high predictive accuracy. However, unlike for mechanistic models, transferring machine-learning-based insights across systems is largely infeasible, which limits communication and knowledge sharing.
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