AIMC Topic: Benzimidazoles

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Candesartan Mitigates Perioperative Neurocognitive Disorders by Modulating Hypertension-Linked Neuroinflammatory Factor.

Neurochemical research Jul 29, 2025
Perioperative neurocognitive disorders (PND) are linked to neuroinflammation, a key factor in hypertension, but their causal relationship is underexplored. This study aims to investigate whether hypertension is a risk factor for PND, identify related...
Animals Male Mice Tetrazoles Benzimidazoles Angiotensin II Type 1 Receptor Blockers Neurocognitive Disorders Thrombospondin 1 Hypertension Mice, Inbred C57BL Neuroinflammatory Diseases Biphenyl Compounds
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Efficacy and safety of first-line CDK4/6 inhibitors plus AI therapy for patients with HR +/HER2- advanced breast cancer: a network meta-analysis.

BMC cancer May 8, 2025
BACKGROUND: CDK4/6 inhibitors plus aromatase inhibitors (AI) significantly improve the therapeutic effect of initial treatment for HR + /HER2- advanced breast cancer. However, there is a lack of head-to-head randomized controlled trials involving the...
Benzimidazoles Receptors, Estrogen Purines Cyclin-Dependent Kinase 4 Receptors, Progesterone Humans Progression-Free Survival Breast Neoplasms Cyclin-Dependent Kinase 6 Female Receptor, ErbB-2 Antineoplastic Combined Chemotherapy Protocols Network Meta-Analysis as Topic Aromatase Inhibitors Treatment Outcome Aminopyridines Protein Kinase Inhibitors Randomized Controlled Trials as Topic
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Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A receptor antagonists.

Journal of biomolecular structure & dynamics Dec 22, 2023
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cancer, and AAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of ben...
Receptor, Adenosine A2B Molecular Structure Humans Molecular Dynamics Simulation Molecular Docking Simulation Benzimidazoles Drug Design Adenosine A2 Receptor Antagonists Deep Learning Protein Binding Pyrazines Structure-Activity Relationship
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In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques.

Carbohydrate polymers Sep 29, 2021
Ternary cyclodextrin (CD) complexes (drug/CD/polymer) can effectively improve the solubility of water-insoluble drugs with large size than binary CD formulations. However, ternary formulations are screened by a trial-and-error approach, which is labo...
Benzimidazoles Hydrocortisone Quinolones Cyclodextrins Drug Compounding Machine Learning Models, Molecular Polymers
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Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

Archives of toxicology Jul 10, 2021
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it re...
Humans Automation, Laboratory Deep Learning Mutagens Carbamates Micronucleus Tests Benzimidazoles Cytokinesis Dose-Response Relationship, Drug Cell Line DNA Damage Flow Cytometry Methyl Methanesulfonate
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Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences Mar 26, 2021
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...
Toona Pesticide Residues Benzimidazoles Terahertz Imaging Thiabendazole Deep Learning Fuzzy Logic Cluster Analysis Plant Leaves Density Functional Theory Pesticides Food Safety Carbamates Neural Networks, Computer Reproducibility of Results
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Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology Jul 8, 2020
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...
Epistasis, Genetic Aminopyridines Survival Analysis Benzimidazoles Fatty Acid-Binding Proteins Gastrointestinal Hormones Molecular Docking Simulation Humans Gene Expression Profiling Machine Learning Cell Line, Tumor Algorithms Gene Expression Regulation, Neoplastic Prognosis Adenocarcinoma Drug Repositioning Databases, Protein Neoplasm Staging Colonic Neoplasms
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A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.

Interdisciplinary sciences, computational life sciences Sep 4, 2019
BACKGROUND: Computational prediction of inhibition efficiency (IE) for inhibitor molecules is a crucial supplementary way to design novel molecules that can efficiently inhibit corrosion onto metallic surfaces.
Computational Biology Support Vector Machine Cluster Analysis Predictive Value of Tests Hydrazines Static Electricity Linear Models Machine Learning Benzimidazoles Conservation of Natural Resources Algorithms Chemistry Quantitative Structure-Activity Relationship Metals Corrosion Imaging, Three-Dimensional
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Preparation of a chemiluminescence sensor for multi-detection of benzimidazoles in meat based on molecularly imprinted polymer.

Food chemistry Dec 19, 2018
In this study, a molecularly imprinted polymer capable of recognizing 8 benzimidazoles was first synthesized. The computation simulation showed that the shape and size of used template were the main factors influencing its recognition ability. Then t...
Benzimidazoles Hydrogen Peroxide Luminescent Measurements Food Contamination Mebendazole Food Analysis Luminol Meat Polymers Molecular Imprinting
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Prediction of Farnesoid X Receptor Disruptors with Machine Learning Methods.

Chemical research in toxicology Nov 8, 2018
The farnesoid X receptor (FXR) emerges as a promising drug target involved in regulating various metabolic pathways, yet some xenobiotic compounds binding to FXR would be an important determinant to induce the receptor dysfunctions that lead to undes...
Humans Area Under Curve Machine Learning Benzimidazoles Databases, Factual Receptors, Cytoplasmic and Nuclear ROC Curve Xenobiotics
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