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Three-dimensional (3D) disease modeling and drug screening systems have become important in tissue engineering, drug screening, and development. The newly developed systems support cell and extracellular matrix (ECM) interactions, which are necessary for the formation of the tissue or an accurate model of a disease. Hydrogels are favorable biomaterials due to their properties: biocompatibility, high swelling capacity, tunable viscosity, mechanical properties, and their ability to biomimic the structure and function of ECM. They have been used to model various diseases such as tumors, cancer diseases, neurodegenerative diseases, cardiac diseases, and cardiovascular diseases. Additive manufacturing approaches, such as 3D printing/bioprinting, stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), enable the design of scaffolds with high precision; thus, increasing the accuracy of the disease models. In addition, the aforementioned methodologies improve the design of the hydrogel-based scaffolds, which resemble the complicated structure and intricate microenvironment of tissues or tumors, further advancing the development of therapeutic agents and strategies. Thus, 3D hydrogel-based disease models fabricated through additive manufacturing approaches provide an enhanced 3D microenvironment that empowers personalized medicine toward targeted therapeutics, in accordance with 3D drug screening platforms.
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http://dx.doi.org/10.1007/5584_2025_851 | DOI Listing |
Chembiochem
September 2025
School of Biological and Chemical Sciences, Ryan Institute, University of Galway, University Road, Galway, H91 TK33, Ireland.
Activated B-cell diffuse large B-cell lymphoma (ABC-DLBCL) is an aggressive cancer with poor response to standard chemotherapy. In search of new therapeutic leads, a library of 435 fractions prepared from the Irish marine biorepository was screened against 2 ABC-DLBCL cell lines (TMD8 and OCI-Ly10) and a non-cancerous control cell line (CB33). Active fractions are prioritized based on potency and selectivity.
View Article and Find Full Text PDFOpen Res Eur
September 2025
Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, 1870, Denmark.
Background: Innovative antibiotic discovery strategies are urgently needed to successfully combat infections caused by multi-drug-resistant bacteria.
Methods: We employed a direct screening approach to identify compounds with antimicrobial and antimicrobial helper-drug activity against Gram-positive and Gram-negative bacteria. We used this platform in two different strains of methicillin-resistant (MRSA) and aminoglycoside-resistant strains of to screen for antimicrobials compounds, which potentiate the activity of aminoglycoside antibiotics.
Rev Med Liege
September 2025
Service de Diabétologie, Nutrition et Maladies métaboliques, CHU Liège, Belgique.
Type 1 diabetes (T1D) is an autoimmune chronic disease that leads to the destruction of pancreatic beta cells and thus requires lifelong insulin therapy. Constraints and adverse events associated to insulin therapy are well known as well as the risk of long-term complications linked to chronic hyperglycaemia. Symptomatic T1D is preceded by a preclinical asymptomatic period, which is characterized by the presence of at least two auto-antibodies against beta cell without disturbances of blood glucose control (stage 1) or, in addition to immunological biomarkers, by the presence of mild dysglycaemia reflecting a defect of early insulin secretion (stage 2).
View Article and Find Full Text PDFChembiochem
September 2025
School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, P. R. China.
The ATPase caseinolytic protease X (ClpX), forming the ClpXP complex with caseinolytic protease P (ClpP), is essential for mitochondrial protein homeostasis. While ClpP targeting is a recognized anticancer strategy, the role of ClpX in cancer remains underexplored. In pancreatic ductal adenocarcinoma (PDAC), elevated CLPX expression correlates with poor prognosis, suggesting its oncogenic function.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2025
Dipartimento di Chimica, Università di Pavia, Via Taramelli 12, Pavia 27100, Italy.
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' predictions. Indeed, we previously demonstrated that combining molecular dynamics (MD)-derived descriptors with ML models allows to effectively classify kinase ligands as allosteric or orthosteric.
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