Results 271 to 280 of about 895,463 (333)

Recent Insights in Multi‐Target Drugs in Pharmacology and Medicinal Chemistry

open access: yesChemMedChem, EarlyView.
This review highlights the rationale behind multitarget drug design as a promising approach to address diseases with complex etiologies. By combining pharmacophore features from different single‐target drugs, multitarget compounds can interact with multiple biological targets simultaneously.
Sadık Hüseyin Cemali   +7 more
wiley   +1 more source

A novel prognostic signature integrating disulfidptosis- and ferroptosis-related genes in acute myeloid leukemia. [PDF]

open access: yesClin Exp Med
Jiang H   +10 more
europepmc   +1 more source

Microbiome‐Informed Dosing: Exploring Gut Microbial Communities Impact on Mycophenolate Enterohepatic Circulation and Therapeutic Target Achievement

open access: yesClinical Pharmacology &Therapeutics, EarlyView.
Pharmacomicrobiomics is an emerging field due to important microbiome effects on pharmacokinetics and clinical outcomes. However, the application of this knowledge remains limited. Mycophenolic acid (MPA) is the primary active metabolite of the immunosuppressant, mycophenolate mofetil (MMF).
Abdelrahman Saqr   +4 more
wiley   +1 more source

Corrigendum to Identification of CD84 as a potent survival factor in acute myeloid leukemia. [PDF]

open access: yesJ Clin Invest
Zhu Y   +27 more
europepmc   +1 more source

Development of a 29‐Color Single‐Tube Full Spectrum Flow Cytometry Assay for the Detection of Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

open access: yesCytometry Part A, EarlyView.
ABSTRACT Multiparametric flow cytometry (MFC) is widely used to detect measurable residual disease (MRD) in acute myeloid leukemia (AML). However, conventional flow assays require multiple tubes, with an additional tube for leukemia stem cell (LSC) analysis and lack hemodilution evaluation.
Zhong Zhang   +4 more
wiley   +1 more source

Clinical validation of a real‐time machine learning‐based system for the detection of acute myeloid leukemia by flow cytometry

open access: yesCytometry Part B: Clinical Cytometry, EarlyView.
Abstract Machine‐learning (ML) models in flow cytometry have the potential to reduce error rates, increase reproducibility, and boost the efficiency of clinical labs. While numerous ML models for flow cytometry data have been proposed, few studies have described the clinical deployment of such models.
Lauren M. Zuromski   +10 more
wiley   +1 more source

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