AIMC Topic: Caco-2 Cells

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RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design.

Journal of chemical information and modeling
Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural ...

Long chain fatty acid transport via SLC27A1 enhances DAG-3-P synthesis and accelerates colorectal cancer metastasis.

Scientific reports
Colorectal cancer (CRC) is a major global health issue. Despite advancements in treatment, CRC patients still face challenges of metastasis and variable prognosis. Circulating tumor cells (CTCs) shed from the primary tumor into the peripheral blood c...

Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn's disease by bioinformatics analysis and machine learning.

Scientific reports
Crohn's disease (CD) is a chronic inflammatory bowel disease with an unknown etiology. Ubiquitination plays a significant role in the pathogenesis of CD. This study aimed to explore the functional roles of ubiquitination-related genes in CD. Differen...

Butyric acid alleviates LPS-induced intestinal mucosal barrier damage by inhibiting the RhoA/ROCK2/MLCK signaling pathway in Caco2 cells.

PloS one
Butyric acid (BA) can potentially enhance the function of the intestinal barrier. However, the mechanisms by which BA protects the intestinal mucosal barrier remain to be elucidated. Given that the Ras homolog gene family, member A (RhoA)/Rho-associa...

Exploring the Potential of Adaptive, Local Machine Learning in Comparison to the Prediction Performance of Global Models: A Case Study from Bayer's Caco-2 Permeability Database.

Journal of chemical information and modeling
Machine learning (ML) techniques are being widely implemented to fill the gap in simple molecular design guidelines for newer therapeutic modalities in the extended and beyond rule of five chemical space (eRo5, bRo5). These ML techniques predict mole...

Exploring the cytotoxic and antioxidant properties of lanthanide-doped ZnO nanoparticles: a study with machine learning interpretation.

Journal of nanobiotechnology
BACKGROUND: Lanthanide-based nanomaterials offer a promising alternative for cancer therapy because of their selectivity and effectiveness, which can be modified and predicted by leveraging the improved accuracy and enhanced decision-making of machin...

Deciphering the cytotoxicity of micro- and nanoplastics in Caco-2 cells through meta-analysis and machine learning.

Environmental pollution (Barking, Essex : 1987)
Plastic pollution, driven by micro- and nanoplastics (MNPs), poses a major environmental threat, exposing humans through various routes. Despite human colorectal adenocarcinoma Caco-2 cells being used as an in vitro model for studying the intestinal ...

Identification of COL3A1 as a candidate protein involved in the crosstalk between obesity and diarrhea using quantitative proteomics and machine learning.

European journal of pharmacology
BACKGROUND: Increasing epidemiologic studies have shown a positive correlation between obesity and chronic diarrhea. Nevertheless, the precise etiology remains uncertain.

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.

Pharmaceutical research
PURPOSE: Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models ...

Simplex Lattice Design and Machine Learning Methods for the Optimization of Novel Microemulsion Systems to Enhance p-Coumaric Acid Oral Bioavailability: In Vitro and In Vivo Studies.

AAPS PharmSciTech
Novel p-coumaric acid microemulsion systems were developed to circumvent its absorption and bioavailability challenges. Simplex-lattice mixture design and machine learning methods were employed for optimization. Two optimized formulations were charac...