AIMC Topic: Apoptosis
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Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.
Nature biomedical engineering
Nov 11, 2021
Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with gliob...
Integrating Statistical and Machine-Learning Approach for Meta-Analysis of Bisphenol A-Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival.
International journal of molecular sciences
Oct 5, 2021
Bisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are bei...
Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.
PLoS computational biology
Feb 22, 2021
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...
Predicting wet age-related macular degeneration (AMD) using DARC (detecting apoptosing retinal cells) AI (artificial intelligence) technology.
Expert review of molecular diagnostics
Dec 28, 2020
OBJECTIVES: To assess a recently described CNN (convolutional neural network) DARC (Detection of Apoptosing Retinal Cells) algorithm in predicting new Subretinal Fluid (SRF) formation in Age-related-Macular-Degeneration (AMD).
Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling.
PLoS computational biology
Dec 14, 2020
Developing an accurate first-principle model is an important step in employing systems biology approaches to analyze an intracellular signaling pathway. However, an accurate first-principle model is difficult to be developed since it requires in-dept...
Piperidine based 1,2,3-triazolylacetamide derivatives induce cell cycle arrest and apoptotic cell death in .
Journal of advanced research
Nov 10, 2020
The fungal pathogen , is a serious threat to public health and is associated with bloodstream infections causing high mortality particularly in patients with serious medical problems. As this pathogen is generally resistant to all the available clas...
Myricitrin inhibits vascular endothelial growth factor-induced angiogenesis of human umbilical vein endothelial cells and mice.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Sep 17, 2020
In the present study, the protective effects of myricitrin against vascular endothelial growth factor (VEGF)-induced angiogenesis of vascular endothelial cells were characterized. Cells were induced with 50 ng/mL VEGF in the presence or absence of va...
Flavonoids
Mice
Humans
Human Umbilical Vein Endothelial Cells
Angiogenesis Inhibitors
Biomarkers
Neovascularization, Pathologic
Caspases
Disease Models, Animal
Animals
Neovascularization, Physiologic
Matrix Metalloproteinases
Apoptosis
Cell Line, Tumor
Vascular Endothelial Growth Factors
Xenograft Model Antitumor Assays
Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.
Scientific reports
Sep 10, 2020
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...
Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.
Pharmacological research
Jun 23, 2020
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...
An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI.
Scientific reports
May 15, 2020
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural re...
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