AIMC Topic: Cell Line, Tumor

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Evaluation of Machine Learning Classifiers to Predict Compound Mechanism of Action When Transferred across Distinct Cell Lines.

SLAS discovery : advancing life sciences R & D
Multiparametric high-content imaging assays have become established to classify cell phenotypes from functional genomic and small-molecule library screening assays. Several groups have implemented machine learning classifiers to predict the mechanism...

Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome.

BMC bioinformatics
BACKGROUND: To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data...

In vitro bioactivity and degradation behaviour of β-wollastonite derived from natural waste.

Materials science & engineering. C, Materials for biological applications
Calcium silicate ceramics, in particular wollastonite (CaSiO), is the most commonly used bioactive material for bone regeneration and repairing applications. The present study aims to synthesize cost effective wollastonite using natural waste materia...

Glucose-holmium for radiotherapy: Characterization and in vitro assays.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
BACKGROUND: The existence of saccharide-holmium complexes, containing mono or polysaccharide molecules, is an attractive hypothesis toward a radiation therapy (RT) with beta-emitters targeting high glucose metabolic human sites. To exam such hypothes...

Predicting tumor cell line response to drug pairs with deep learning.

BMC bioinformatics
BACKGROUND: The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity.

Grape Seed Proanthocyanidin Extract Inhibits Human Esophageal Squamous Cancerous Cell Line ECA109 via the NF-B Signaling Pathway.

Mediators of inflammation
Esophageal squamous cell carcinoma is the most common type of squamous cell carcinoma. Grape seed proanthocyanidin extract (GSPE) is considered to exhibit anticancer activity against several different types of cancer. We aimed to determine whether GS...

Synthesis and characterization of Zinc oxide nanoparticles utilizing seed source of Ricinus communis and study of its antioxidant, antifungal and anticancer activity.

Materials science & engineering. C, Materials for biological applications
ZnO nanoparticles have been synthesized using solution combustion technique and its antioxidant, antifungal, anticancer activity was studied. Ricinus communis plant seed extract used as fuel in synthesis by the solution combustion technique. Powder X...

Genotoxicity evaluation of titanium dioxide nanoparticles using the mouse lymphoma assay and the Ames test.

Mutation research. Genetic toxicology and environmental mutagenesis
Titanium dioxide nanoparticles (TiO-NPs) are widely used in the cosmetics, health, and food industries, but their safety and genotoxicity remain a matter of debate. We investigated whether TiO-NPs could induce gene mutations in mouse lymphoma L5178Y ...

Preliminary study on alginate/NIPAM hydrogel-based soft microrobot for controlled drug delivery using electromagnetic actuation and near-infrared stimulus.

Biomedical microdevices
Currently, microrobots are receiving attention because of their small size and motility, which can be applied to minimal invasive therapy. Additionally, various microrobots using hydrogel with the characteristics of biocompatibility and biodegradabil...

Prediction of early metastatic disease in experimental breast cancer bone metastasis by combining PET/CT and MRI parameters to a Model-Averaged Neural Network.

Bone
Macrometastases in bone are preceded by bone marrow invasion of disseminated tumor cells. This study combined functional imaging parameters from FDG-PET/CT and MRI in a rat model of breast cancer bone metastases to a Model-averaged Neural Network (av...