Results 121 to 130 of about 83,637 (272)

Type 1 secretion necessitates a tight interplay between all domains of the ABC transporter

Scientific Reports
Type I secretion systems (T1SS) facilitate the secretion of substrates in one step across both membranes of Gram-negative bacteria. A prime example is the hemolysin T1SS which secretes the toxin HlyA.
Manuel T. Anlauf, Florestan L. Bilsing, Jens Reiners, Olivia Spitz, Eymen Hachani, Sander H. J. Smits, Lutz Schmitt   +6 more
doaj   +1 more source

Molecular mechanism of substrate specificity for delta 6 desaturase from Mortierella alpina and Micromonas pusilla

Journal of Lipid Research, 2015
The ω6 and ω3 pathways are two major pathways in the biosynthesis of PUFAs. In both of these, delta 6 desaturase (FADS6) is a key bifunctional enzyme desaturating linoleic acid or α-linolenic acid.
Haisu Shi (史海粟), Haiqin Chen (陈海琴), Zhennan Gu (顾震南), Yuanda Song (宋元达), Hao Zhang (张灏), Wei Chen (陈卫), Yong Q. Chen (陈永泉)   +6 more
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Homoleptic and Heteroleptic Borylones L1‐B(Ph)‐L2

Angewandte Chemie, EarlyView.
Density functional theory and CCSD(T) calculations reveal that homoleptic and heteroleptic borylones L1–B(Ph)–L2 are thermodynamically accessible. Remarkably, the homoleptic borylones B(Ph)(N2)2 and B(Ph)(SPh2)2 exhibit higher bond dissociation energies than the related carbones.
Qin Ma, Wei Li, Ya Hu, Lili Zhao, Gernot Frenking   +4 more
wiley   +2 more sources

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

Advanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith, Ryan D. McKenzie, Alban Joseph, Robert L. Stamps, Rair Macêdo   +4 more
wiley   +1 more source

Structural and thermodynamic insights into antibody light chain tetramer formation through 3D domain swapping. [PDF]

Nat Commun, 2023
Sakai T, Mashima T, Kobayashi N, Ogata H, Duan L, Fujiki R, Hengphasatporn K, Uda T, Shigeta Y, Hifumi E, Hirota S.   +10 more
europepmc   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source

Domain swapping of the C-terminal helix promotes the dimerization of a novel ribonuclease protein from Mycobacterium tuberculosis. [PDF]

Protein Sci, 2023
Kim DH, Na Y, Chang H, Boo JH, Kang SM, Jin C, Kang SJ, Lee SY, Lee BJ.   +8 more
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source