Unfolded protein response: An essential element of intestinal homeostasis and a potential therapeutic target for inflammatory bowel disease.

Different physiological and pathological situations can produce alterations in the cell's endoplasmic reticulum (ER), leading to a condition known as ER stress, which can trigger an intricate intracellular signal transduction system known as the unfolded protein response (UPR). UPR is primarily tailored to restore proteostasis and ER equilibrium; otherwise, if ER stress persists, it can cause programmed cell death as a cytoprotective mechanism and drive inflammatory processes. Therefore, since intestinal cells strongly rely on UPR for their biological functions and unbalanced UPR has been linked to inflammatory, metabolic, and immune disorders, here we discussed the role of the UPR within the intestinal tract, focusing on the UPR contribution to inflammatory bowel disease development.

The interplay between gut microbiota and the unfolded protein response: Implications for intestinal homeostasis preservation and dysbiosis-related diseases.

The unfolded protein response (UPR) is a complex intracellular signal transduction system that orchestrates the cellular response during Endoplasmic Reticulum (ER) stress conditions to reestablish cellular proteostasis. If, on one side, prolonged ER stress conditions can lead to programmed cell death and autophagy as a cytoprotective mechanism, on the other, unresolved ER stress and improper UPR activation represent a perilous condition able to trigger or exacerbate inflammatory responses. Notably, intestinal and immune cells experience ER stress physiologically due to their high protein secretory rate.

Rosetta stone for the population dynamics of spiking neuron networks.

Populations of spiking neuron models have densities of their microscopic variables (e.g., single-cell membrane potentials) whose evolution fully capture the collective dynamics of biological networks, even outside equilibrium.

A geometrical solution underlies general neural principle for serial ordering.

A general mathematical description of how the brain sequentially encodes knowledge remains elusive. We propose a linear solution for serial learning tasks, based on the concept of mixed selectivity in high-dimensional neural state spaces. In our framework, neural representations of items in a sequence are projected along a "geometric" mental line learned through classical conditioning.