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The polypharmacy combination of the BCL-2 inhibitor venetoclax (VEN) and the FLT3 inhibitor gilteritinib (GIL) is more active in acute myeloid leukemia cells than novel polypharmacologic BCL-2/FLT3 VEN-GIL hybrid single-molecule inhibitors.
Eur J Med Chem
December 2024
Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 N. Pine St., Baltimore, MD, 21201, USA; University of Maryland Marlene & Stewart Greenebaum Comprehensive Cancer Center, 22 S. Greene St., Baltimore, MD, 21201, USA. Electronic address:
Current treatments for acute myeloid leukemias (AMLs) cure fewer than 30 % of patients. This low efficacy is due, in part, to the inter-patient and intra-patient heterogeneity of AMLs; accordingly, all current AML treatment regimens involve drug combinations (polypharmacy). A recently-completed clinical trial in relapsed/refractory AML using a combination of two newer targeted antileukemics, the BCL-2 inhibitor venetoclax (VEN) plus the FLT3 inhibitor gilteritinib (GIL), yielded highly promising results for this two-drug polypharmacy combination.
View Article and Find Full Text PDF3d freehand ultrasound reconstruction by reference-based point cloud registration.
Int J Comput Assist Radiol Surg
January 2025
Institute of Medical Informatics, University of Lübeck, Lübeck, Germany.
Purpose: This study aims to address the challenging estimation of trajectories from freehand ultrasound examinations by means of registration of automatically generated surface points. Current approaches to inter-sweep point cloud registration can be improved by incorporating heatmap predictions, but practical challenges such as label-sparsity or only partially overlapping coverage of target structures arise when applying realistic examination conditions.
Methods: We propose a pipeline comprising three stages: (1) Utilizing a Free Point Transformer for coarse pre-registration, (2) Introducing HeatReg for further refinement using support point clouds, and (3) Employing instance optimization to enhance predicted displacements.
A Comprehensive Study of Reactive Oxygen Species Explicit Dosimetry for Pleural Photodynamic Therapy.
Antioxidants (Basel)
November 2024
Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Photodynamic therapy (PDT) relies on the interactions between light, photosensitizers, and tissue oxygen to produce cytotoxic reactive oxygen species (ROS), primarily singlet oxygen (O) through Type II photochemical reactions, along with superoxide anion radicals (O), hydrogen peroxide (HO), and hydroxyl radicals (OH) through Type I mechanisms. Accurate dosimetry, accounting for all three components, is crucial for predicting and optimizing PDT outcomes. Conventional dosimetry tracks only light fluence rate and photosensitizer concentration, neglecting the role of tissue oxygenation.
View Article and Find Full Text PDFAnalyzing the TotalSegmentator for facial feature removal in head CT scans.
Radiography (Lond)
January 2025
Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health, Berlin, Germany.
Background: Facial recognition technology in medical imaging, particularly with head scans, poses privacy risks due to identifiable facial features. This study evaluates the use of facial recognition software in identifying facial features from head CT scans and explores a defacing pipeline using TotalSegmentator to reduce re-identification risks while preserving data integrity for research.
Methods: 1404 high-quality renderings from the UCLH EIT Stroke dataset, both with and without defacing were analysed.
Clonal phylogenies inferred from bulk, single cell, and spatial transcriptomic analysis of epithelial cancers.
PLoS One
January 2025
Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prior studies of primary prostate cancer tumour genetics revealed extensive inter and intra-patient genomic tumour heterogeneity. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data.
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