Unveiling autophagy and aging through time-resolved imaging of lysosomal polarity with a delayed fluorescent emitter.

Detecting the lysosomal microenvironmental changes like viscosity, pH, and polarity during their dynamic interorganelle interactions remains an intriguing area that facilitates the elucidation of cellular homeostasis. The subtle variation of physiological conditions can be assessed by deciphering the lysosomal microenvironments during lysosome-organelle interactions, closely related to autophagic pathways leading to various cellular disorders. Herein, we shed light on the dynamic lysosomal polarity in live cells and a multicellular model organism, (), through time-resolved imaging employing a thermally activated delayed fluorescent probe, DC-Lyso.

Microfluidics based bioimaging with cost-efficient fabrication of multi-level micrometer-sized trenches.

Microfluidic devices, through their vast applicability as tools for miniaturized experimental setups, have become indispensable for cutting edge research and diagnostics. However, the high operational cost and the requirement of sophisticated equipment and clean room facility for the fabrication of these devices make their use unfeasible for many research laboratories in resource limited settings. Therefore, with the aim of increasing accessibility, in this article, we report a novel, cost-effective micro-fabrication technique for fabricating multi-layer microfluidic devices using only common wet-lab facilities, thereby significantly lowering the cost.

Persistent Correlation in Cellular Noise Determines Longevity of Viral Infections.

The slowly decaying viral dynamics, even after 2-3 weeks from diagnosis, is one of the characteristics of COVID-19 infection that is still unexplored in theoretical and experimental studies. This long-lived characteristic of viral infections in the framework of inherent variations or noise present at the cellular level is often overlooked. Therefore, in this work, we aim to understand the effect of these variations by proposing a stochastic non-Markovian model that not only captures the coupled dynamics between the immune cells and the virus but also enables the study of the effect of fluctuations.

A near analytic solution of a stochastic immune response model considering variability in virus and T-cell dynamics.

Biological processes at the cellular level are stochastic in nature, and the immune response system is no different. Therefore, models that attempt to explain this system need to also incorporate noise or fluctuations that can account for the observed variability. In this work, a stochastic model of the immune response system is presented in terms of the dynamics of T cells and virus particles.