Biology subjects

O'Brien, F.

Publications and source records attributed to O'Brien, F..

5 recordsLinked to original sources

bioRxiv2025

Mechanically activated bone cell derived extracellular vesicles regulate angiogenesis in a manner that is dependent on the stage of lineage commitment

Bone regeneration requires a finely tuned interplay between osteogenesis and angiogenesis. While current treatments such as auto/allografts, provide support, they often fail to promote adequate vascularisation necessary for complete repair. Extracellular vesicles (EVs), as mediators of intercellular communication, have emerged as promising acellular nanotechnologies for tissue regeneration due to their bioactive cargo and low immunogenicity. Mechanical stimulation, a known enhancer of bone cell function, can modulate EV cargo and potentially improve regenerative efficacy. In this study, we investigated how mechanical stimulation, and the stage of mesenchymal lineage commitment influence the angiogenic potential of secretomes and EVs derived from mesenchymal stromal/stem cells, osteoblasts, and osteocytes. Our findings reveal that both cell mechanical stimulation and their differentiation stage significantly modulate the angiogenic properties of the resulting EVs. Among the tested conditions, mechanically-stimulated osteocyte-derived EVs demonstrate superior angiogenesis, promoting endothelial cell migration, tube formation, and CD31 expression. These effects were further validated in a pre-clinical ex ovo chick chorioallantoic membrane assay, where robust neovascularisation was observed. This work highlights the critical role of both mechanical cues and cell differentiation stage in regulating the angiogenic capacity of EVs and proposes mechanically activated osteocyte-derived EVs as a novel pro-angiogenic nanotherapeutic for bone repair.

bioengineering↗

bioRxiv2021

Systemic application of the TRPV4 antagonist GSK2193874 induces tail vasodilation in a mouse model of thermoregulation

In humans the skin is a primary thermoregulatory organ, with vasodilation leading to rapid body cooling, whereas in Rodentia the tail performs an analogous function. Many thermodetection mechanisms are likely to be involved including transient receptor potential vanilloid-type 4 (TRPV4), a widely distributed ion channel with both mechanical and thermosensitive properties. Previous studies have shown that TRPV4 can act as a vasodilator by local action in blood vessels, and in this study, we investigated whether TRPV4 activity effects mus muscularis tail vascular tone and thermoregulation. We measured tail blood flow by pressure plethysmography in lightly sedated mus muscularis (CD1 strain) at a range of ambient temperatures, with and without intraperitoneal administration of the blood brain barrier crossing TRPV4 antagonist GSK2193874. We also measured heart rate and blood pressure with and without GSK2193874. As expected for a thermoregulatory organ, we found that tail blood flow increased with temperature. However, unexpectedly we found that the TRPV4 antagonist GSK2193874 increased tail blood flow at all temperatures, and we observed changes in heart rate variability. Since TRPV4 activation stimulates the relaxation of peripheral resistance arteries (vasodilation) that would increase tail blood flow, these data suggest that increases in tail blood flow resulting from the TRPV4 antagonist may arise from a site other than the blood vessels themselves, perhaps in central cardiovascular control centres such as the hypothalamus.

physiology↗

bioRxiv2020

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks

Development of automated analysis tools for "single ion channel" recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1 sample point every 100microsecond). In an experimental context, such data are labelled with human supervision, and whilst this is feasible for simple experimental analysis, it is infeasible to generate the enormous datasets that would be necessary for a big data approach using hand crafting. In this work we aimed to develop methods to generate simulated ion channel data that is free from assumptions and prior knowledge of noise and underlying hidden Markov models. We successfully leverage generative adversarial networks (GANs) to build an end-to-end pipeline for generating an unlimited amount of labelled training data from a small annotated ion channel "seed" record, and this needs no prior knowledge of theoretical dynamical ion channel properties. Our method utilises 2D CNNs to maintain the synchronised temporal relationship between the raw and idealised record. We demonstrate the applicability of the method with 5 different data sources and show authenticity with t-SNE and UMAP projection comparisons between real and synthetic data. The model would be easily extendable to other time series data requiring parallel labelling, such as labelled ECG signals or raw nanopore sequencing data.

physiology↗

bioRxiv2020

Pro-inflammatory cytokines drive deregulation of potassium channel expression in primary synovial fibroblasts

The synovium secretes synovial fluid, but is also richly innervated with nociceptors and acts as a gateway between avascular joint tissues and the circulatory system. Resident fibroblast-like synoviocytes (FLS) calcium-activated potassium channels (KCa) change in activity in arthritis models and this correlates with FLS activation. ObjectiveTo investigate this activation in an in vitro model of inflammatory arthritis; 72hr treatment with cytokines TNF and IL1{beta}. MethodsFLS cells were isolated from rat synovial membranes. We analysed global changes in FLS mRNA by RNA-sequencing and then focused on FLS ion channels genes and corresponding FLS electrophysiological phenotype, finally modelling data with Ingenuity Pathway Analysis (IPA) and MATLAB. ResultsIPA showed significant activation of inflammatory, osteoarthritic and calcium signalling canonical pathways by cytokines, and we identified ~200 channel gene transcripts. The large KCa (BK) channel consists of the pore forming Kcnma1 together with {beta}-subunits. Following cytokine treatment, a significant increase in Kcnma1 RNA abundance was detected by qPCR and changes in several ion channels were detected by RNA-sequencing, including a loss of BK channel {beta}-subunit expression Kcnmb1/2 and increase in Kcnmb3. In electrophysiological experiments, there was a decrease in overall current density at 20mV without change in chord conductance at this potential. ConclusionTNF and IL1{beta} treatment of FLS in vitro recapitulated several common features of inflammatory arthritis at the transcriptomic level, including increase in Kcnma1 and Kcnmb3 gene expression.

bioinformatics↗

bioRxiv2019

Deep-Channel: A Deep Convolution and Recurrent Neural Network for Detection of Single Molecule Events

Single-molecule research such as patch-clamp recording delivers unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysis is event detection, so called "idealisation", where noisy raw data are turned into discrete records of protein movement. To date there have been practical limitations in patch-clamp data idealisation; high quality idealisation is typically laborious and becomes infeasible and subjective with complex biological data containing many distinct native single ion channel proteins gating simultaneously. Here we show a deep learning model based on convolutional neural networks and long short-term memory architecture can automatically idealise complex single molecule activity more accurately and faster than traditional methods. There are no parameters to set; baseline, channel amplitude or numbers of channels for example. We believe this approach could revolutionise the unsupervised automatic detection of single-molecule transition events in the future.

physiology↗