Search bioRxiv⌕ Search

Biology subjects

Vasilyev, V.

Publications and source records attributed to Vasilyev, V..

2 recordsLinked to original sources

Preclinical testing of RRx-001 in mouse models of experimental endometriosis reveals promising therapeutic impacts

Endometriosis is a chronic inflammatory condition characterised by the presence of ectopic endometrial-like tissue (lesions), reduced fertility and chronic pain. Impacting both the health and psycho-social functioning of millions of women worldwide, there is an urgent need for innovative non-hormonal, non-invasive treatments for the disorder. Both peritoneal and lesion-resident macrophages have been strongly implicated in the pathogenesis of endometriosis; key roles include promotion of lesion growth, neuroangiogenesis and nerve sensitization. With such a central role in the disease, macrophages represent a novel therapeutic target. In the current preclinical study, we sought to repurpose the macrophage targeting anti-cancer drug RRx-001 for the treatment of endometriosis. We utilised mouse models of induced endometriosis to demonstrate that RRx-001 induces regression of endometriosis lesions and attenuates pain-like behaviours, without negatively impacting fertility. Targeted depletion of peritoneal cavity macrophages significantly impairs lesion reduction, demonstrating their critical role in mediating the anti-endometriosis impact of RRx-001. Using single nuclei multiomics, we identified a modification of macrophage subpopulations in the peritoneal cavity, specifically reduced acquisition of a pro-disease phenotype and an accumulation of a pro-resolving phenotype. These observations signify the potential of RRx-001 as a novel therapeutic for endometriosis management.

immunology↗

TimeTeller: a tool to probe the circadian clock as a multigene dynamical system

AO_SCPLOWBSTRACTC_SCPLOWRecent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of diseases including cancer and heart diseases. Therefore, there is a need for tools to measure the functional state of the molecular circadian clock and its downstream targets in patients. Moreover, the clock is a multi-dimensional stochastic oscillator and there are few tools for analysing it as a system. In this paper we consider the methodology behind Time-Teller, a machine learning tool that analyses the clock as a system and aims to estimate circadian clock function from a single transcriptome by modelling the multi-dimensional state of the clock. We demonstrate its potential for clock systems assessment by applying it to mouse, baboon and human microarray and RNA-seq data and show how to visualise and quantify the global structure of the clock, quantitatively stratify individual transcriptomic samples by clock dysfunction and globally compare clocks across individuals, conditions and tissues thus highlighting its potential relevance for advancing circadian medicine.

systems biology↗