Cell Reports Physical Science最新文献

Efficient long-distance energy transport is a cornerstone of photosynthetic light harvesting, enabling excitation energy to traverse multiple antenna proteins to reach the reaction center (RC), where it drives photochemistry. While extensive studies on energy transfer dynamics within individual light-harvesting complexes (LHCs) have been conducted, the inter-protein transfers crucial for understanding the overall efficiency of these systems have remained experimentally elusive. This arises mainly because the spectral signatures of the subunits are often remarkably similar, complicating the identification of energy transfer pathways among them. This study bridges this gap by utilizing ultrafast transient absorption spectroscopy, under conditions with and without singlet-singlet annihilation, on the photosystem II (PSII) LHCII-CP24-CP29 subcomplex and on its constituents. Our findings reveal rapid equilibration within monomeric complexes, contrasted by six-times slower equilibration in the LHCII trimer and eight-times slower equilibration in the LHCII-CP24-CP29 subcomplex, highlighting the inter-complex energy transfer as the rate-limiting step in excitation delivery to the RC.

The actomyosin network, consisting of actin filaments and myosin motors, is essential for cell dynamic behaviors. The sliding motion of actin filaments propelled by myosin motors is converted into contraction of the cytoskeleton network, leading to cell deformation. Here, we demonstrated that active gels of actomyosin networks exhibited varied contraction geometries such as local radial patterns and global network contraction depending on the motor mobility condition at the boundary. Under two motor conditions (immobile and mobile), both experimental and computational methods were utilized to characterize the contraction dynamics at varied network connectivities. We revealed that the effect of network connectivity on the contraction dynamics depends on the motor mobility condition. Our computational models simulate the cellular functions such as cell division and muscle contraction, providing insights into disease development related to motor mobility conditions. Our study helps to explain the dynamics of active materials under varied mechanical environments.

Mass transfer in electrolyte films on electrodes is crucial to the performance of electrochemical energy devices, which is difficult or impossible to observe experimentally. Here, we develop a framework utilizing deep learning to analyze vast molecular dynamics (MD) data to reveal the molecular-level transport properties in electrolyte films. This framework contains physical feature analysis and selection based on MD simulations, surrogate model training, structure-transport relationship analysis, and structure discovery. This framework is then applied to explore oxygen transport in fuel cells, which allows the transport properties and their relationships to the structural characteristics of electrolyte films to be revealed, and thus, the critical features limiting oxygen transport are identified. Accordingly, increasing the catalyst surface hydrophilicity and suppressing the electrolyte film density fluctuation are favorable for oxygen transport. Moreover, this framework is transferable to revealing similar molecular-level transport phenomena in electrolyte films that widely exist in other electrochemical energy devices.

Contact lens (CL)-associated bacterial keratitis (BK), a prevalent and underestimated disorder caused by unhygienic CL wear, poses a risk to permanent loss of visual acuity. Clinically, low drug-delivery efficiency, frequent administration, hormone complications, and antibiotic resistance remain the major unsolved challenges. Here, we introduce a chlorogenic acid (CGA)-conjugated CL material based on gelatin methacrylate via cryogelation(cGelMA/CGA-CL) to strengthen the prevention and treatment of BK. The cGelMA/CGA-CL features a highly moist, macroporous, adjustable structure for sustained release of CGA and is favorably biocompatible to cells, providing antimicrobial protection against opportunistic pathogens and inhibiting excessive ocular inflammatory responses through the JAK2-STAT1/STAT2 signaling pathway. Furthermore, the cGelMA/CGA-CL effectively alleviates the symptoms of BK with immunoregulation of macrophage recruitment and anti-inflammatory factor release in a mouse model of BK. The cGelMA/CGA-CL offers a promising candidate for the prevention and treatment of BK, which may significantly reduce the risk of infection for CL wearers.

The rapid advancement of highly flexible and reliable artificial intelligence (AI) holds the promise of unlocking transformative capabilities in response to imminent energy and environmental challenges. Toward future energy, we propose this perspective and introduce a groundbreaking paradigm for a versatile energy AI, termed artificial general intelligence for energy (AGIE). AGIE is designed to address a spectrum of energy-related issues with flexibility, drawing upon information such as energy parameters, equipment images, and expert voice feedback. The applications of AGIE are diverse, ranging from energy diagnostics and operational optimization to offering advice on energy policies. By incorporating human-in-the-loop interactions and leveraging domain knowledge, AGIE has the capacity to assimilate the habits of energy users. Through continuous reinforcement learning, it aspires to establish a new paradigm of explainable reasoning, paving the way for the development of credible energy robots with attributes similar to human understanding. We anticipate that AGIE-enabled applications will lead to new approaches in energy usage and the consideration of serious technical and societal challenges ranging from data integration to privacy and security concerns, environmental impacts, and constraints in hardware and software. Addressing these issues is crucial for realizing the full potential of generalist energy intelligence, leading to enhanced energy efficiency and contributing to the resolution of global energy problems.

A persistent challenge in operating S-scheme photocatalysts involves maintaining complete neutralization of low-energy electrons and holes between reducing and oxidizing photocatalysts. To address this, we propose a charge replenishment-assisted S-scheme mechanism that combines a compatible host catalyst with a luminescence phosphor semiconductor capable of long-term storage of photogenerated electrons. Stored electrons can replenish the host photocatalyst, depleting the low-oxidizing holes, thus prolonging the charge-separated state. The concept is demonstrated in a core-shell-structured SrGa₂O₄:Cu²⁺/g-C₃N₄ (SGO/CN) photocatalyst, where stored electrons with a lifetime of up to several hours can continuously consume holes in the CN. The well-defined core-shell structure, abundant interfacial Sr-N bonds, and staggered band alignment between SGO and CN are crucial for this S-scheme interfacial charge transfer, which contributes to the enhanced CO₂-to-CO transformation activity and selectivity. This S-scheme heterojunction, incorporating a charge-storing material as an excess electron reservoir, offers a promising template for designing efficient photocatalytic systems.

In precision therapy, patient-derived cancer cells are inoculated into the same organ from which they are derived to simulate the microenvironment of the original tumor. However, due to the high technical difficulty and low success rate of the required surgical operation, appropriate animal models are lacking, which restricts its application. Here, we report a surgery-free method for creating a desired tumor mouse model using cancer cell microrobots guided by rotating gradient magnetic fields. The uptake of magnetic particles produces cancer cell microrobots. The external magnetic field enables the microrobots to hover around the target localization, enhancing their ability to penetrate the vascular endothelium. In vivo tests in mice demonstrate the capability of creating a desired tumor mass in a particular body location. This work provides a promising method to generate a targeted tumor mouse model without using conventional surgery operations for further precision medicine treatment study of cancer.

The acidic microenvironment of solid tumors is a potential source of selectivity in the anti-cancer activity of ionophores, which requires delicate control of their biophysical properties. In this context, we have systematically studied fluorine substitutions in the aromatic side chains of HCl-binding pseudopeptidic cages. Interconnected factors like chloride binding, protonation, lipophilicity, and conformation and diffusiveness of the cages can impact their ability to transport HCl through the aqueous-lipid interphase, as demonstrated by robust experimental (X-ray, nuclear magnetic resonance [NMR], fluorescence) and theoretical results. The fine-tuning of these properties allows the modulation of their pH-dependent cytotoxicity against cancer cells, from essentially non-cytotoxic at pH 7.5 (like the extracellular surroundings of healthy tissues) to highly toxic in slightly acidic microenvironments (like those around solid tumors). Thus, a distal fluorine substitution produces a big impact on the physicochemical and biological properties of the cages, improving their selectivity as potential therapeutic ionophores.

Ever since the birth of the first air conditioner (Carrier air conditioner) in 1902, over one hundred years ago, it has been accompanied by several technical problems, e.g., (1) low energy efficiency in large open spaces, (2) spread of pollutants, airborne pandemic transmission (e.g., severe acute respiratory syndrome [SARS], COVID-19) through air-conditioning systems, and (3) low comfort caused by fan noise and blowing sounds. Here, we report a personalized pure radiant cooling device that decouples the fresh air supply from space cooling to achieve air conditioning without conditioning the air. Condensation-free radiant cooling with a radiant cooling capacity of 152 W/m² is achieved with a polyethylene (PE) film-covered super-cold infrared-emissive surface. By optimizing the design and operation parameters, the device saves up to 50.4% of cooling energy in a typical summer building environment. Our concept opens up the possibility of pandemic-free personalized thermal management with high energy efficiency and thermal comfort.

Inhibitors of amyloid fibril formation can act in diverse ways and aid in elucidating the mechanisms of protein aggregation. The engineered binding protein β-wrapin AS69 binds monomers of Parkinson-disease-associated α-synuclein (αS), yet achieves inhibition at substoichiometric concentration. The substoichiometric activity was not attributed to the binding protein per se, but to its 1:1 complex with αS, in which AS69 sequesters αS residues 30–60 into a globular protein fold, whereas other αS parts remain intrinsically disordered regions (IDRs). Here, we investigate AS69-αS fusion constructs that form the AS69:αS complex by intramolecular folding and expose different IDRs. We find that not only the globular part of the complex but also αS IDRs are critical for substoichiometric inhibition, which is achieved by interference with primary and secondary fibril nucleation. The effects in vitro are reproduced in cellular seeding assays, indicating that secondary nucleation drives seeding in aggregate biosensing.