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http://dx.doi.org/10.1007/s13238-015-0218-5 | DOI Listing |
Blood
January 2025
IDIBAPS, Barcelona, Spain.
Previous studies have reported that chronic lymphocytic leukemia (CLL) shows a de novo chromatin activation pattern as compared to normal B cells. Here, we explored whether the level of chromatin activation is related to the clinical behavior of CLL. We identified that in some regulatory regions, increased de novo chromatin activation is linked to clinical progression whereas, in other regions, it is associated with an indolent course.
View Article and Find Full Text PDFBlood
January 2025
University Hospital, LMU Munich, Munich, Germany.
Platelets are crucial players in hemostasis and thrombosis, but also contribute to immune regulation and host defense, using different receptors, signaling pathways and effector functions, respectively. Whether distinct subsets of platelets specialize in these diverse tasks is insufficiently understood. Here, we employed an in vivo pulse-labelling method in Mus musculus models for tracking in vivo platelet ageing and its functional implications.
View Article and Find Full Text PDFProtein Sci
February 2025
Department of Biostatistics and Bioinformatics, Institute of Health Sciences, Acibadem University, Atasehir, Istanbul, Turkey.
Protein structure holds immense potential for pathogenicity prediction, albeit structure-based predictors are limited compared to the sequence-based counterparts due to the "structure knowledge gap" between large number of available protein sequences and relatively limited number of structures. Leveraging the highly accurate protein structures predicted by AlphaFold2 (AF2), we introduce AFFIPred, an ensemble machine learning classifier that combines sequence and AF2-based structural characteristics to predict missense variant pathogenicity. Based on the assessments on unseen datasets, AFFIPred reached a comparable level of performance with the state-of-the-art predictors such as AlphaMissense.
View Article and Find Full Text PDFJ Proteome Res
January 2025
Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, 69120 Heidelberg, Germany.
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, different algorithms come with different strengths and weaknesses and choosing the appropriate algorithm poses a challenge for the user. Here we introduce PeptideForest, a semisupervised machine learning approach that integrates the assignments of multiple algorithms to train a random forest classifier to alleviate that issue.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Institute of Biomedicine and Translational Medicine, University of Tartu, Ravila 14B, Tartu, 50411, Estonia.
In triple-negative breast cancer (TNBC), pro-tumoral macrophages promote metastasis and suppress the immune response. To target these cells, a previously identified CD206 (mannose receptor)-binding peptide, mUNO was engineered to enhance its affinity and proteolytic stability. The new rationally designed peptide, MACTIDE, includes a trypsin inhibitor loop, from the Sunflower Trypsin Inhibitor-I.
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