Biology subjects

Brooks, H.

Publications and source records attributed to Brooks, H..

4 recordsLinked to original sources

bioRxiv2024

Targeting DNA-PK is a highly conserved poxvirus innate immune evasion mechanism

The sensing of viral nucleic acid by pattern recognition receptors (PRRs) is essential for initiation of a type-I interferon response against infection. Intracellular DNA sensing PRRs are responsible for initiating innate immune responses to poxviruses and other double-stranded DNA viruses. Poxviruses, in turn, encode an armoury of immunomodulators that inhibit this host defence mechanism. DNA-dependent protein kinase (DNA-PK) is an essential component of the cGAS/STING-dependent viral DNA sensing machinery that leads to the initiation of a type-I interferon response during poxvirus infection. Poxviruses counter this host sensing mechanism using the C4/C10 family of proteins that target DNA-PK, interfering with its ability to bind viral DNA. Although the DNA-PK complex, known also for its role in double strand break repair, is conserved across multiple taxa, its function in innate immunity outside mammals is unexplored. Here we analysed the contribution of DNA-PK to poxvirus DNA sensing in chickens, a species that is evolutionarily distant from mammals, but that is also infected by poxviruses. We found that DNA-PK functions as a DNA sensor in chickens, and this process is countered by C4/C10 family members found in fowlpox virus. This host/pathogen interaction is conserved across a broader range of species than other mechanisms of poxvirus antagonism of innate immune sensing, which may reflect the difficulty of the host in evolving escape mechanisms that interfere with a protein that is essential for maintenance of genomic stability.

immunology↗

bioRxiv2022

Tensor Image Registration Library: Automated Deformable Registration of Stand-Alone Histology Images to Whole-Brain Post-Mortem MRI Data

BackgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to automate the registration of stand-alone histology sections to whole-brain MRI data. MethodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slice photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. ResultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. ConclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies. HighlightsO_LINew software framework for prototyping bespoke image registration pipelines C_LIO_LIAutomated pipeline to register stand-alone histology sections to whole-brain MRI C_LIO_LINovel deformable slice-to-volume registration algorithm C_LIO_LINo strict necessity for serial histological sectioning for MRI-histology registration C_LI

neuroscience↗

bioRxiv2021

Defining 'Destructive fishing': a lack of consensus inhibits effective global policy

The term "destructive fishing" appears in multiple international policy instruments intended to improve outcomes for marine biodiversity, coastal communities and sustainable fisheries. However, the meaning of "destructive fishing" is often vague, limiting effectiveness in policy. Therefore, in this study we systematically reviewed the use of "destructive fishing" in three record types: academic literature, media articles, and policy documents between 1976-2020. A more detailed analysis was performed on sub-sets of these records, considering the extent to which the term is characterised, geographic distribution of use, and specific impacts and practices associated with the term. We found that use of "destructive fishing" relative to the generic term fisheries has increased since the 1990s. Records focused predominantly on fishing practices in South-eastern Asia, followed by Southern Asia and Europe. The term was characterised in detail in only 15% of records. Habitat damage and blast/poison fishing were the most associated ecological impacts and gear/practices, respectively. Bottom trawling and unspecified net fishing were regularly linked to destructive fishing. Importantly, the three record types use the term differently. Academic literature tends to specifically articulate the negative impacts, while media articles focus generally on associated gears/practices. Significant regional variation also exists in how the term is used and what phenomena it is applied to. This study provides evidence and recommendations to inform stakeholders in any future pursuit of a unified definition of "destructive fishing" to support more meaningful implementation of global sustainability goals.

ecology↗

bioRxiv2019

Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain

There is a need to understand the histopathological basis of MRI signal characteristics in complex biological matter. Microstructural imaging holds promise for sensitive and specific indicators of the early stages of human neurodegeneration but requires validation against traditional histological markers before it can be reliably applied in the clinical setting. Validation relies on a precise and preferably automatic method to align MRI and histological images of the same tissue, which poses unique challenges compared to more conventional MRI-to-MRI registration. A customisable open-source platform, Tensor Image Registration Library (TIRL) is presented. Based on TIRL, a fully automated pipeline was implemented to align small stained histological images with dissection photographs of corresponding tissue blocks and coronal brain slices, and further with high-resolution (0.5 mm) whole-brain post-mortem MRI data. The pipeline performed three separate deformable registrations to achieve accurate mapping between whole-brain MRI and small-slide histology coordinates. The robustness and accuracy of the individual registration steps were evaluated using both simulated data and real-life images from 6 different anatomical locations of one post-mortem human brain. The automated registration method demonstrated sub-millimetre accuracy in all steps, robustness against tissue damage, and good reproducibility between experiments. The method also outperformed manual landmark-based slice-to-volume registration, also correcting for curvatures in the slicing plane. Due to the customisability of TIRL, the pipeline can be conveniently adapted for other research needs and is therefore suitable for the large-scale comparison of routinely collected histology and MRI data. HighlightsO_LITIRL: new framework for prototyping bespoke image registration pipelines C_LIO_LIPipeline for automated registration of small-slide histology to whole-brain MRI C_LIO_LISlice-to-volume registration accounting for through-plane deformations C_LIO_LINo need for serial histological sampling C_LI

neuroscience↗