Biology subjects

O'Brien, K.

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

21 records · Page 2Linked to original sources

bioRxiv2018

DeepQSM - Using Deep Learning to Solve the Dipole Inversion for MRI Susceptibility Mapping

Quantitative susceptibility mapping (QSM) aims to extract the magnetic susceptibility of tissue from magnetic resonance imaging (MRI) phase measurements. The mapping of magnetic susceptibility in vivo has gained broad interest in several fields of science and medicine because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium. Thereby, QSM can also reveal pathological changes of these key components in devastating diseases such as Parkinsons disease, Multiple Sclerosis, or hepatic iron overload. As QSM requires the solution of an ill-posed field-to-source-inversion, current techniques utilize manual optimization of regularization parameters to balance between smoothing, artifacts and quantification accuracy. We trained a fully convolutional deep neural network - DeepQSM - to invert the magnetic dipole kernel convolution. This network is capable of solving the ill-posed field-to-source inversion on real-world in vivo MRI phase data without the need for manual parameter tuning, which proves that this network has generalized the underlying mathematical principle of the dipole inversion. We demonstrate that DeepQSMs susceptibility maps enable identification of deep brain substructures that are not visible in MRI phase data and provide information on their respective magnetic tissue properties. We illustrate DeepQSMs clinical relevance in a patient with multiple sclerosis showing its sensitivity to white matter lesions. In summary, DeepQSM can be used to determine the composition of myelin sheets of nerve fibers in the brain, and to assess quantitative information on iron homeostasis and its dysregulation, and will subsequently contribute to a better understanding of these biological processes in health and disease.

neuroscience↗

bioRxiv2017

A systems approach to the characterization and classification of T-cell responses

Types of T-cell responses are categorized on the basis of a limited number of molecular markers selected using a priori knowledge about T-cell immunobiology. We sought to develop a novel systems-based approach for the creation of an unbiased framework enabling assessment of antigenic-peptide specific T-cell responses in vitro. A meta-analysis of transcriptome data from PBMCs stimulated with a wide range of peptides identified patterns of gene regulation that provided an unbiased classification of types of antigen-specific responses. Further analysis yielded new insight about the molecular processes engaged following antigenic stimulation. This led for instance to the identification of transcription factors not previously studied in the context of T-cell differentiation. Taken together this profiling approach can serve as a basis for the unbiased characterization of antigen-specific responses and as a foundation for the development of novel systems-based immune profiling assays.

genomics↗

bioRxiv2017

Assessing The Efficiency Of Catch-Up Campaigns For Introduction Of Pneumococcal Conjugate Vaccine; A Modelling Study Based On Data From Kilifi, Kenya

BackgroundThe World Health Organisation recommends the use of catch-up campaigns as part of the introduction of pneumococcal conjugate vaccines (PCVs) to accelerate herd protection and hence PCV impact. The value of a catch-up campaign is a trade-off between the costs of vaccinating additional age groups and the benefit of additional direct and indirect protection. There is a paucity of observational data, particularly from low-middle income countries to quantify the optimal breadth of such catch-up campaigns.\n\nMethodsIn Kilifi, Kenya PCV10 was introduced in 2011 using the 3-dose EPI infant schedule and a catch-up campaign in children <5 years old. We fitted a transmission dynamic model to detailed local data including nasopharyngeal carriage and invasive pneumococcal disease (IPD) to infer the marginal impact of the PCV catch-up campaign over hypothetical routine cohort vaccination in that setting, and to estimate the likely impact of alternative campaigns and their dose-efficiency.\n\nResultsWe estimated that, within 10 years of introduction, the catch-up campaign among <5y olds prevents an additional 65 (48 to 84) IPD cases, compared to PCV cohort introduction alone. Vaccination without any catch-up campaign prevented 155 (121 to 193) IPD cases and used 1321 (1058 to 1698) PCV doses per IPD case prevented. In the years after implementation, the PCV programme gradually accrues herd protection and hence its dose-efficiency increases: 10 years after the start of cohort vaccination alone the programme used 910 (732 to 1184) doses per IPD case averted. We estimated that a two-dose catch-up among <1y olds uses an additional 910 (732 to 1184) doses per additional IPD case averted. Furthermore, by extending a single dose catch-up campaign to children 1 to <2y old and subsequently to 2 to <5y olds the campaign uses an additional 412 (296 to 606) and 543 (403 to 763) doses per additional IPD case averted. These results were not sensitive to vaccine coverage, serotype competition, the duration of vaccine protection or the relative protection of infants.\n\nConclusionsWe find that catch-up campaigns are a highly dose-efficient way to accelerate population protection against pneumococcal disease.

epidemiology↗