AIMC Topic: Cell Line, Tumor

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Cytotoxicity and molecular docking analysis of racemolactone I, a new sesquiterpene lactone isolated from .

Pharmaceutical biology
CONTEXT: Traditionally, Hook. f. (Asteraceae) has been reported to be effective in cancer treatment which motivated the authors to explore the plant for novel anticancer compounds.

Comparative analysis of molecular fingerprints in prediction of drug combination effects.

Briefings in bioinformatics
Application of machine and deep learning methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel computa...

Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.

Briefings in bioinformatics
The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a cr...

DeepDRK: a deep learning framework for drug repurposing through kernel-based multi-omics integration.

Briefings in bioinformatics
Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering ...

Dual-responsive biohybrid neutrobots for active target delivery.

Science robotics
Swimming biohybrid microsized robots (e.g., bacteria- or sperm-driven microrobots) with self-propelling and navigating capabilities have become an exciting field of research, thanks to their controllable locomotion in hard-to-reach areas of the body ...

Anticancer drug synergy prediction in understudied tissues using transfer learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Drug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies...

Deep learning for in vivo near-infrared imaging.

Proceedings of the National Academy of Sciences of the United States of America
Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 ...

Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models.

Methods in molecular biology (Clifton, N.J.)
Intrinsic and acquired drug resistance is a major challenge in cancer therapy. Synergistic drug combinations could help to overcome drug resistance. However, the number of possible drug combinations is enormous, and it is infeasible to experimentally...

Volatile constituents and in vitro activity of Syzygium aromaticum flower buds (clove) against human cancer cell lines.

Pakistan journal of pharmaceutical sciences
The methanolic extract (SA-EXT) of Syzygium aromaticum flower buds and its fractions tested against three human cancer cell lines viz uterine cervix (HeLa), breast (MCF-7) and lung NCI (H-460) using sulforhodamine-B assay. The ethyl acetate soluble s...

Synthesis and evaluation of a novel nanosized anionic linear globular dendrimer G2-ciprofloxacin conjugate against prostate cancer.

Pakistan journal of pharmaceutical sciences
Prostate cancer is the second most common cancer in the world and the fifth cause of cancer deaths in men. Ciprofloxacin enables the inhabitation of the development of prostate cancer. In this regard, we plan to improve the anticancer effect of cipro...