AIMC Topic: Cell Line
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Segmentation aware probabilistic phenotyping of single-cell spatial protein expression data.
Nature communications
Jan 4, 2025
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentati...
BiGM-lncLoc: Bi-level Multi-Graph Meta-Learning for Predicting Cell-Specific Long Noncoding RNAs Subcellular Localization.
Interdisciplinary sciences, computational life sciences
Dec 26, 2024
The precise spatiotemporal expression of long noncoding RNAs (lncRNAs) plays a pivotal role in biological regulation, and aberrant expression of lncRNAs in different subcellular localizations has been intricately linked to the onset and progression o...
Preparation, characterization, and protective effects of carbon dots against oxidative damage induced by LPS in IPEC-J2 cells.
Frontiers in cellular and infection microbiology
Dec 18, 2024
This study aimed to prepare carbon dots (GF-CDs) and examine their efficacy in mitigating oxidative stress and apoptosis in intestinal porcine epithelial cells from the jejunum (IPEC-J2 cells) induced by lipopolysaccharide (LPS). The GF-CDs were syn...
Machine Learning-Assisted "Shrink-Restricted" SERS Strategy for Classification of Environmental Nanoplastic-Induced Cell Death.
Environmental science & technology
Dec 13, 2024
The biotoxicity of nanoplastics (NPs), especially from environmental sources, and "NPs carrier effect" are in the early stages of research. This study presents a machine learning-assisted "shrink-restricted" SERS strategy (SRSS) to monitor molecular ...
A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.
Artificial intelligence in medicine
Nov 20, 2024
Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune disease. The Indirect Immunofluorescence (IIF) microscopy performed with human epithelial type 2 (HEp-2) cells as the substrate is the reference metho...
Dynamic changes in pyroptosis following spinal cord injury and the identification of crucial molecular signatures through machine learning and single-cell sequencing.
Journal of pharmaceutical and biomedical analysis
Aug 26, 2024
The pathological cascade of spinal cord injury (SCI) is highly intricate. The onset of neuroinflammation can exacerbate the extent of damage. Pyroptosis is a form of inflammation-linked programmed cell death (PCD), the inhibition of pyroptosis can pa...
Deep learning large-scale drug discovery and repurposing.
Nature computational science
Aug 21, 2024
Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA) is crucial, yet current approaches are costly and low-throughput. Here we present an approach for MOA identification by profiling changes in mitochon...
Machine learning-driven QSAR models for predicting the cytotoxicity of five common microplastics.
Toxicology
Aug 11, 2024
In the field of microplastics (MPs) toxicity prediction, machine learning (ML) computer simulation techniques are showing great potential. In this study, six ML algorithms were utilized to predict the toxicity of MPs on BEAS-2B cells based on quantit...
Exploring the roles of RNAs in chromatin architecture using deep learning.
Nature communications
Jul 29, 2024
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA...
AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.
Nature communications
Jul 26, 2024
Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this ...
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