Fibulin-3 is necessary to prevent cardiac rupture following myocardial infarction

Published online: 11 September 2023Despite the high prevalence of heart failure in the western world, there are few effective treatments. Fibulin-3 is a protein involved in extracellular matrix (ECM) structural integrity, however its role in the heart is unknown. We have demonstrated, using single cell RNA-seq, that fibulin-3 was highly expressed in quiescent murine cardiac fibroblasts, with expression highest prior to injury and late post-infarct (from ~ day-28 to week-8). In humans, fibulin-3 was upregulated in left ventricular tissue and plasma of heart failure patients. Fibulin-3 knockout (Efemp1-/-) and wildtype mice were subjected to experimental myocardial infarction. Fibulin-3 deletion resulted in significantly higher rate of cardiac rupture days 3-6 post-infarct, indicating a weak and poorly formed scar, with severe ventricular remodelling in surviving mice at day-28 post-infarct. Fibulin-3 knockout mice demonstrated less collagen deposition at day-3 post-infarct, with abnormal collagen fibre-alignment. RNA-seq on day-3 infarct tissue revealed upregulation of ECM degradation and inflammatory genes, but downregulation of ECM assembly/structure/organisation genes in fibulin-3 knockout mice. GSEA pathway analysis showed enrichment of inflammatory pathways and a depletion of ECM organisation pathways. Fibulin-3 originates from cardiac fibroblasts, is upregulated in human heart failure, and is necessary for correct ECM organisation/structural integrity of fibrotic tissue to prevent cardiac rupture post-infarct.Lucy A. Murtha, Sean A. Hardy, Nishani S. Mabotuwana, Mark J. Bigland, Taleah Bailey, Kalyan Raguram, Saifei Liu, Doan T. Ngo, Aaron L. Sverdlov, Tamara Tomin, Ruth Birner, Gruenberger, Robert D. Hume, Siiri E. Iismaa, David T. Humphreys, Ralph Patrick, James J. H. Chong, Randall J. Lee, Richard P. Harvey, Robert M. Graham, Peter P. Rainer and Andrew J. Boyl

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders1, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing3,4,5,6,7,8,9,10,11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders

Inversion domain nucleation in homoepitaxial GaN

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Morphological and structural characteristics of homoepitaxial GaN grown by metalorganic chemical vapour deposition (MOCVD)

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Flight heights obtained from GPS versus altimeters influence estimates of collision risk with offshore wind turbines in Lesser Black-backed Gulls <i>Larus fuscus</i>

The risk posed by offshore wind farms to seabirds through collisions with turbine blades is greatly influenced by species-specific flight behaviour. Bird-borne telemetry devices may provide improved measurement of aspects of bird behaviour, notably individual and behaviour specific flight heights. However, use of data from devices that use the GPS or barometric altimeters in the gathering of flight height data is nevertheless constrained by a current lack of understanding of the error and calibration of these methods. Uncertainty remains regarding the degree to which errors associated with these methods can affect recorded flight heights, which may in turn have a significant influence on estimates of collision risk produced by Collision Risk Models (CRMs), which incorporate flight height distribution as an input. Using GPS/barometric altimeter tagged Lesser Black-backed Gulls Larus fuscus from two breeding colonies in the UK, we examine comparative flight heights produced by these devices, and their associated errors. We present a novel method of calibrating barometric altimeters using behaviour characterised from GPS data and open-source modelled atmospheric pressure. We examine the magnitude of difference between offshore flight heights produced from GPS and altimeters, comparing these measurements across sampling schedules, colonies, and years. We found flight heights produced from altimeter data to be significantly, although not consistently, higher than those produced from GPS data. This relationship was sustained across differing sampling schedules of five minutes and of 10 s, and between study colonies. We found the magnitude of difference between GPS and altimeter derived flight heights to also vary between individuals, potentially related to the robustness of calibration factors used. Collision estimates for theoretical wind farms were consequently significantly higher when using flight height distributions generated from barometric altimeters. Improving confidence in telemetry-obtained flight height distributions, which may then be applied to CRMs, requires sources of errors in these measurements to be identified. Our study improves knowledge of the calibration processes for flight height measurements based on telemetry data, with the aim of increasing confidence in their use in future assessments of collision risk and reducing the uncertainty over predicted mortality associated with wind farms.</p

Investigating avoidance and attraction responses in lesser black-backed gulls Larus fuscus to offshore wind farms

Movements through or use of offshore wind farms by seabirds while commuting or foraging may increase the potential for collision with turbine blades. Collision risk models provide a method for estimating potential impacts of wind farms on seabird populations, but are sensitive to input parameters, including avoidance rates (ARs). Refining understanding of avoidance through the use of high-resolution empirical movement data has the potential to inform assessments of the collision impacts of offshore wind farms on seabird populations. We assessed the movements of GPS-tagged lesser black-backed gulls Larus fuscus from a breeding colony in northwest England to estimate the species' AR and avoidance/attraction index (AAI) to nearby offshore wind farms. To investigate both macro- (0−4 km) and meso-scale (0−200 m) responses to wind turbines, we used calculations of AR and AAI based on simulated vs. observed tracks. We found that birds exhibited an AR of −0.15 (95% CI: −0.44 to 0.06), indicating a degree of attraction within 4 km of the wind farms. However, AAI values varied with distance from wind farm boundaries, with a degree of avoidance displayed between 3 and 4 km, which weakened as distance bands approach wind farm boundaries. Meso-scale avoidance/attraction was assessed with regard to the nearest individual turbine, and flight height relative to the rotor height range (RHR) of the nearest turbine. We found attraction increased below the RHR at distances <70 m, while avoidance increased within the RHR at distances approaching the turbine. We explore how high-resolution tracking data can be used to improve our knowledge of L. fuscus avoidance/attraction behaviour to established wind farms, and so inform assessments of collision impacts