Results 111 to 120 of about 4,947,350 (304)
UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová +2 more
wiley +1 more source
Machine learning assisted prediction of organic salt structure properties
We demonstrate a machine learning-based approach which predicts the properties of crystal structures following relaxation based on the unrelaxed structure. Use of crystal graph singular values reduces the number of features required to describe a crystal
Ethan P. Shapera +3 more
doaj +1 more source
The Crystal Structure of Topaz [PDF]
An investigation of the orthorhombic crystal topaz, Al2SiO4F2, with x-rays has been reported by Leonhardt. With the aid of data from Laue and rotation photographs he found for the edges of the unit of structure, containing 4Al2SiO4F2, the values d100 = 4.64 A, d010 = 8.78 A, and d001 = 8.37 A, and determined the space-group of the crystal to be V16h. A
openaire +2 more sources
Guiding AlphaFold to predict how Munc13‐1 opens Syntaxin‐1
The syntaxin‐1 Habc‐domain (orange), linker (pink) and SNARE motif (yellow) form a closed conformation that binds to Munc18‐1 (violet) and is opened by the Munc13‐1 MUN domain (cyan) to form the SNARE complex that triggers neurotransmitter release.
Madhurima Chattopadhyay +2 more
wiley +1 more source
TisIBP8, a fungal‐derived hyperactive ice‐binding protein, helps Caenorhabditis elegans survive dehydration. It localizes near cell membranes, reduces cell damage, and helps maintain membrane structure during drying. These results suggest that ice‐binding proteins can protect cells from dehydration stress as well as freezing stress.
Daiki Shimose +9 more
wiley +1 more source
The crystal diffusion variational autoencoder (CDVAE) is a machine learning model that leverages score matching to generate realistic crystal structures that preserve crystal symmetry.
Teerachote Pakornchote +6 more
doaj +1 more source
The theoretical prediction and characterization of the solid-state structure of organic semiconductors has tremendous potential for the discovery of new high performance materials.
Atahan-Evrenk, Şule +4 more
core +1 more source
Molecular characterization of covRS mutations in M1UK Streptococcus pyogenes
Group A Streptococcus (GAS) acquires covRS mutations driving a hypervirulent bacterial state, frequently associated with invasive disease‐like necrotizing fasciitis. We demonstrate that the newly emerged M1UK GAS lineage can also acquire these mutations.
Jarrad Pritchard +12 more
wiley +1 more source
Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya +2 more
wiley +1 more source
Shotgun crystal structure prediction using machine-learned formation energies
Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy calculations,
Chang Liu +7 more
doaj +1 more source

