Publications by authors named "J Michels"
Macromolecular crowding agents, such as poly(ethylene glycol) (PEG), are often used to mimic cellular cytoplasm in protein assembly studies. Despite the perception that crowding agents have an inert nature, we demonstrate and quantitatively explore the diverse effects of PEG on the phase separation and maturation of protein condensates. We use two model proteins, the FG domain of Nup98 and bovine serum albumin (BSA), which represent an intrinsically disordered protein and a protein with a well-established secondary structure, respectively.
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- - The study explores how evaporation affects the phase separation of a binary fluid mixture in a thin film on a moving surface, focusing on scenarios where phase separation occurs away from the coating device.
- - It analyzes the transport processes during this phase separation, noting that initial stages are dominated by diffusive and evaporative mass transport, while later stages exhibit a mix of different coarsening mechanisms influenced by solvent evaporation rates and material properties.
- - A new hydrodynamic coarsening regime is identified for off-critical mixtures, where solute-rich droplets move towards thinner areas of the film, leading to their accumulation and coalescence in those regions.
Since the last FIGO classification in 2009, numerous studies and recommendations have contributed to improving the management of endometrial cancer. The introduction of molecular classification (including POLE, MMR, and P53 status) has enabled better categorization of these cancers by defining specific patient groups, thus allowing for more tailored surgical management and adjuvant treatment. The data and analyses on molecular and histological classification developed in the 2021 guidelines from the European Societies of Gynecologic Oncology (ESGO), Radiation Therapy and Oncology (ESTRO), and Anatomical Pathology (ESP) have been utilized to develop the new 2023 FIGO classification for endometrial cancer.
View Article and Find Full Text PDFFindings from clinical trials have led to advancement of care for patients with gynecologic malignancies. However, restrictive inclusion of patients into trials has been widely criticized for inadequate representation of the real-world population. Ideally, patients enrolled in clinical trials should represent a broader population to enhance external validity and facilitate translation of outcomes across all relevant groups.
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- NLP is transforming how computers analyze human languages and is now being applied to study protein-ligand interactions, crucial for drug discovery.
- * Techniques like LSTM networks and transformers are utilized to process diverse protein and ligand data for predicting these interactions.
- * The review points out challenges, including limited negative data and model interpretability, and calls for better data quality and collaboration to improve predictions.*