Biology subjects

Horsley, A.

Publications and source records attributed to Horsley, A..

3 recordsLinked to original sources

bioRxiv2020

Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection

The immune response to SARS-CoV-2 is critical in both controlling primary infection and preventing re-infection. However, there is concern that immune responses following natural infection may not be sustained and that this may predispose to recurrent infection. We analysed the magnitude and phenotype of the SARS-CoV-2 cellular immune response in 100 donors at six months following primary infection and related this to the profile of antibody level against spike, nucleoprotein and RBD over the previous six months. T-cell immune responses to SARS-CoV-2 were present by ELISPOT and/or ICS analysis in all donors and are characterised by predominant CD4+ T cell responses with strong IL-2 cytokine expression. Median T-cell responses were 50% higher in donors who had experienced an initial symptomatic infection indicating that the severity of primary infection establishes a setpoint for cellular immunity that lasts for at least 6 months. The T-cell responses to both spike and nucleoprotein/membrane proteins were strongly correlated with the peak antibody level against each protein. The rate of decline in antibody level varied between individuals and higher levels of nucleoprotein-specific T cells were associated with preservation of NP-specific antibody level although no such correlation was observed in relation to spike-specific responses. In conclusion, our data are reassuring that functional SARS-CoV-2-specific T-cell responses are retained at six months following infection although the magnitude of this response is related to the clinical features of primary infection.

immunology↗

bioRxiv2020

Spectral graph theory efficiently characterises ventilation heterogeneity in lung airway networks.

This paper introduces a linear operator for the purposes of quantifying the spectral properties of transport within resistive trees, such as airflow in lung airway networks. The operator, which we call the Maury matrix, acts only on the terminal nodes of the tree and is equivalent to the adjacency matrix of a complete graph summarising the relationships between all pairs of terminal nodes. We show that the eigenmodes of the Maury operator have a direct physical interpretation as the relaxation, or resistive, modes of the network. We apply these findings to both idealised and image-based models of ventilation in lung airway trees and show that the spectral properties of the Maury matrix characterise the flow asymmetry in these networks more concisely than the Laplacian modes, and that eigenvector centrality in the Maury spectrum is closely related to the phenomenon of ventilation heterogeneity caused by airway narrowing or obstruction. This method has applications in dimensionality reduction in simulations of lung mechanics, as well as for characterisation of models of the airway tree derived from medical images.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2018

Modelling structural determinants of ventilation heterogeneity: a perturbative approach.

We have developed a computational model of gas mixing and ventilation in the human lung represented as a bifurcating network. We have simulated multiple-breath washout (MBW), a clinical test for measuring ventilation heterogeneity (VH) in patients with obstructive lung conditions. By applying airway constrictions inter-regionally, we have predicted the response of MBW indices to obstructions and found that they detect a narrow range of severe constrictions that reduce airway radius to 10%-30% of healthy values. These results help to explain the success of the MBW test to distinguish obstructive lung conditions from healthy controls. Further, we have used a perturbative approach to account for intra-regional airway heterogeneity that avoids modelling each airway individually. We have found, for random airway heterogeneity, that the variance in MBW indices is greater when indices are already elevated due to constrictions. By quantifying this effect, we have shown that variability in lung structure and mechanical properties alone can lead to clinically significant variability in LCI and Scond, but only in cases simulating obstructive lung conditions. This method is a computationally efficient way to probe the lungs sensitivity to structural changes, and to quantify uncertainty in predictions due to random variations in lung mechanical and structural properties.

biophysics↗