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http://dx.doi.org/10.1007/s00277-019-03680-4 | DOI Listing |
Int J Mol Sci
January 2025
Department Hamm 1, Hamm-Lippstadt University of Applied Science, 59063 Hamm, Germany.
An obstacle for many microfluidic developments is the fabrication of its structures, which is often complex, time-consuming, and expensive. Additive manufacturing can help to reduce these barriers. This study investigated whether the results of a microfluidic assay for the detection of the promyelocytic leukemia (PML)-retinoic acid receptor α (RARα) fusion protein (PML::RARA), and thus for the differential diagnosis of acute promyelocytic leukemia (APL), could be transferred from borosilicate glass microfluidic structures to additively manufactured fluidics.
View Article and Find Full Text PDFInt J Mol Sci
October 2023
CHU de Poitiers, Service de Cancérologie Biologique, F86000 Poitiers, France.
Cancer Immunol Immunother
July 2023
Department of Hematology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Qiaokou District, 1095 Jiefang Avenue, Wuhan, China.
Background: Acute myeloid leukemia (AML) treatment remains challenging. CD70 was reported as a promising AML-specific antigen. Preclinically, CAR T-cell with single-chain-variable fragment (scFv) or truncated CD27 targeting CD70 has been reported to treat AML.
View Article and Find Full Text PDFPLOS Digit Health
March 2023
Institute of AI for Health, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Explainable AI is deemed essential for clinical applications as it allows rationalizing model predictions, helping to build trust between clinicians and automated decision support tools. We developed an inherently explainable AI model for the classification of acute myeloid leukemia subtypes from blood smears and found that high-attention cells identified by the model coincide with those labeled as diagnostically relevant by human experts. Based on over 80,000 single white blood cell images from digitized blood smears of 129 patients diagnosed with one of four WHO-defined genetic AML subtypes and 60 healthy controls, we trained SCEMILA, a single-cell based explainable multiple instance learning algorithm.
View Article and Find Full Text PDFBlood Adv
April 2022
Department of Hematology, and.
Acute myeloid leukemia (AML) often presents as an oligoclonal disease whereby multiple genetically distinct subclones can coexist within patients. Differences in signaling and drug sensitivity of such subclones complicate treatment and warrant tools to identify them and track disease progression. We previously identified >50 AML-specific plasma membrane (PM) proteins, and 7 of these (CD82, CD97, FLT3, IL1RAP, TIM3, CD25, and CD123) were implemented in routine diagnostics in patients with AML (n = 256) and myelodysplastic syndrome (n = 33).
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