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The pathogenesis of neurodegenerative diseases involves the accumulation of misfolded protein aggregates. These deposits are both directly toxic to neurons, invoking loss of cell connectivity and cell death, and recognized by innate sensors that upon activation release neurotoxic cytokines, chemokines, and various reactive species. This neuroinflammation is propagated through signaling cascades where activated sensors/receptors, adaptors, and effectors associate into multiprotein complexes known as supramolecular organizing centers (SMOCs). This review provides a comprehensive overview of the SMOCs, involved in neuroinflammation and neurotoxicity, such as myddosomes, inflammasomes, and necrosomes, their assembly, and evidence for their involvement in common neurodegenerative diseases. We discuss the multifaceted role of neuroinflammation in the progression of neurodegeneration. Recent progress in the understanding of particular SMOC participation in common neurodegenerative diseases such as Alzheimer’s disease offers novel therapeutic strategies for currently absent disease-modifying treatments. [ABSTRACT FROM AUTHOR]

Urinary tract infections can be severe, sometimes fatal, diseases whose etiological pathogens are predominantly uropathogenic strains of E. coli (UPEC). To investigate the UPEC pathogenesis, several models have already been established with minor or major disadvantages. The aim was to develop a simple, fast, and inexpensive biomimetic in vitro model based on normal porcine urothelial (NPU) cells that are genetically and physiologically similar to human bladder urothelium and to perform basic studies of E. coli pathogenicity. Initially, the model was tested using a set of control E. coli strains and, subsequently, with human E. coli strains isolated either from patients with urinary infections or from the feces of healthy individuals. A drop in viability of NPU cells was used as a measure of the pathogenicity of the individual strain tested. To visualize the subcellular events, transmission and scanning electron microscopy was performed. The strains were tested for the presence of different virulence-associated genes, phylogroup, type of core lipid, O-serotype, and type of lipopolysaccharide and a statistical analysis of possible correlations between strains' characteristics and the effect on the model was performed. Results showed that our model has the discriminatory power to distinguish pathogenic from non-pathogenic E. coli strains, and to identify new, potentially pathogenic strains. [ABSTRACT FROM AUTHOR]