Results 81 to 90 of about 75,759 (281)

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu   +4 more
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong   +5 more
wiley   +1 more source

Comparative Analysis of the ADAM and ADAMTS Families

open access: yes, 2016
The “A Disintegrin And Metalloproteinase” (ADAM) protein family and the “A Disintegrin-like And Metalloproteinase with ThromboSpondin motifs” (ADAMTS) protein family are two related families of human proteins.
Lucia Banci (120160)   +4 more
core   +1 more source

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang   +9 more
wiley   +1 more source

Ectodomain shedding of Limbic System-Associated Membrane Protein (LSAMP) by ADAM Metallopeptidases promotes neurite outgrowth in DRG neurons

open access: yesScientific Reports, 2017
IgLONs are members of the immunoglobulin superfamily of cell adhesion proteins implicated in the process of neuronal outgrowth, cell adhesion and subdomain target recognition.
Ricardo L. Sanz   +3 more
doaj   +1 more source

Relapse of congenital thrombotic thrombocytopenic purpura, after spontaneous remission, in a second-trimester primigravida: case report and review of the literature

open access: yesSão Paulo Medical Journal, 2017
CONTEXT: Thrombotic microangiopathy syndrome or thrombotic thrombocytopenic purpura-hemolytic uremic syndrome (TTP-HUS) describes distinct diseases sharing common pathological features: microangiopathic hemolytic anemia and thrombocytopenia, without any
Donavan de Souza Lúcio   +3 more
doaj   +1 more source

[The importance of ADAM family proteins in malignant tumors].

open access: yesPostepy higieny i medycyny doswiadczalnej (Online), 2016
Increasing numbers of reports about the role of adamalysins (ADAM) in malignant tumors are being published. To date, more than 30 representatives of this group, out of which about 20 occur in humans, have been described. The ADAM family is a homogeneous group of proteins which regulate, from the stage of embryogenesis, a series of processes such as ...
Katarzyna, Walkiewicz   +4 more
openaire   +1 more source

Counteraction of APOBEC3 Proteins by Herpesvirus Ribonucleotide Reductases [PDF]

open access: yes, 2019
University of Minnesota Ph.D. dissertation. August 2019. Major: Microbiology, Immunology and Cancer Biology. Advisor: Reuben Harris. 1 computer file (PDF); xvi, 208 pages.The APOBEC3 family of DNA cytosine deaminases plays an important role in antiviral
Cheng, Adam
core  

ADAM 10 is over expressed in oral squamous cell carcinoma and contributes to invasive behaviour through a functional association with αvβ6 integrin

open access: yes, 2013
A disintegrin and metalloprotease (ADAM) proteins are upregulated in cancer and can interact with integrin receptors. We investigated whether such interactions may have functional significance in oral squamous cell carcinoma (OSCC).ADAM 10 expression was
Lambert, Daniel W.   +3 more
core   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

open access: yesAdvanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal   +3 more
wiley   +1 more source

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