AIMC Topic: MCF-7 Cells

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Integrating machine-learning and nanotechnology to quantify pH-modulated oxaliplatin release.

Scientific reports
The purpose of this work was to formulate and characterize pH-sensitive, surfactant-based nanomicelles for the targeted delivery of Oxaliplatin to breast cancer cells. A secondary aim was to utilize machine learning (ML) models to interpolate and dis...

Selective cytotoxicity of anhydroicaritin in ER-positive breast cancer via ESR1-mediated MAPK and apoptotic signaling.

Chemico-biological interactions
Anhydroicaritin (AHI), a chemically characterized prenylated flavonoid, exhibits strong and selective cytotoxicity against estrogen receptor-positive (ER+) breast cancer cells. In this study, we aimed to elucidate its molecular and cellular toxicolog...

Developing a predictive QSAR model for FGFR-1 inhibitors: integrating computational and experimental validation.

Journal of computer-aided molecular design
The traditional drug discovery process is often lengthy, costly, and characterized by a high failure rate. There is a pressing need for innovative strategies to optimize this process and improve the chances of identifying effective therapeutic candid...

Harnessing artificial intelligence to identify Bufalin as a molecular glue degrader of estrogen receptor alpha.

Nature communications
Target identification in natural products plays a critical role in the development of innovative drugs. Bufalin, a compound derived from traditional medicines, has shown promising anti-cancer activity; however, its precise molecular mechanism of acti...

Data-Driven Sustainable Campaigns to Decipher Invasive Breast Cancer Features.

ACS biomaterials science & engineering
The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. Microphysiological systems (MPSs) are emerging technological platforms that model dynamics of tissue-...

Antimicrobial Peptides Design Using Deep Learning and Rational Modifications: Activity in Bacteria, Candida albicans, and Cancer Cells.

Current microbiology
Resistance to antimicrobial agents has become a global threat, estimated to cause 10-million deaths annually by 2050. Antimicrobial peptides are emerging as an alternative and offer advantages over traditional antibiotics. Antimicrobial peptides gene...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

Functional & integrative genomics
The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast cancer (BC) is unknown. We tested the hypothesis that inhibition of METTL3, the methyltransferase re...

A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.

Journal of chemical information and modeling
Improved scalability of high-throughput RNA-sequencing technologies has contributed to their proposed use in regulatory contexts for chemical hazard identification. However, the high dimensionality and size of these transcriptomic data sets present a...

A potential new strategy for BC treatment: NPs containing solanine and evaluation of its anticancer and antimetastatic properties.

BMC cancer
Solanine has been shown to inhibit cancer by regulating the expression of apoptosis (Bax, Bcl-2) and metastasis (CDH-1, MMP2) genes in various cancer cell types. We synthesized optimized niosome NPs (NPs) with high solubility and capacity for solanin...

In vitro antimicrobial and anticancer potentials of green synthesized luminescent carbon quantum dots derived from artichoke leaves.

Scientific reports
Naturally derived carbon quantum dots (CQDs) are novel carbon-based nanomaterials with excellent traits. It is highly demanded to develop CQDs from biowaste that have excellent photostability, a simple synthesis approach, and an appealing output so t...