Harnessing Microbial Effectors for Macrophage-Mediated Drug Delivery.

Macrophage-based drug delivery systems are promising, but their development is still in its infancy, with many limitations remaining to be addressed. Our aim was to design a system harnessing microbial effectors to facilitate controlled drug cargo expulsion from macrophages to enable the use of more toxic drugs without adding to the risk of off-target detrimental effects. The pore forming and actin polymerizing effectors listeriolysin-O (LLO) and actin assembly-inducing protein (ActA) were synthesized using a novel green fluorescent protein (GFP)-linked heterologous expression system.

Unresolved intramuscular inflammation, not diminished skeletal muscle regenerative capacity, is at the root of rheumatoid cachexia: insights from a rat CIA model.

Rheumatoid arthritis targets numerous organs in patients, including the skeletal muscle, resulting in rheumatoid cachexia. In the muscle niche, satellite cells, macrophages, and myofibroblasts may be affected and the factors they release altered. This study aimed to assess these cell types, cytokines, and growth factors and their relationships to muscle fiber size and number in a rodent collagen-induced arthritis (CIA) model, in order to identify new therapeutic targets.

Targeting Stem Cells in Chronic Inflammatory Diseases.

Mesenchymal stem cell (MSC) dysfunction is a serious complication in ageing and age-related inflammatory diseases such as type 2 diabetes mellitus. Inflammation and oxidative stress-induced cellular senescence alter the immunomodulatory ability of MSCs and hamper their pro-regenerative function, which in turn leads to an increase in disease severity, maladaptive tissue damage and the development of comorbidities. Targeting stem/progenitor cells to restore their function and/or protect them against impairment could thus improve healing outcomes and significantly enhance the quality of life for diabetic patients.

Improved region of interest selection and colocalization analysis in three-dimensional fluorescence microscopy samples using virtual reality.

Although modern fluorescence microscopy produces detailed three-dimensional (3D) datasets, colocalization analysis and region of interest (ROI) selection is most commonly performed two-dimensionally (2D) using maximum intensity projections (MIP). However, these 2D projections exclude much of the available data. Furthermore, 2D ROI selections cannot adequately select complex 3D structures which may inadvertently lead to either the exclusion of relevant or the inclusion of irrelevant data points, consequently affecting the accuracy of the colocalization analysis.