Publications by authors named "Duffy G"

Background: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.

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What little we know about how microbiomes change over the course of host dispersal has been gleaned from simulations or snapshot sampling of microbiomes of hosts undertaking regular, cyclical migrations. These studies suggest that major changes in both microbiome richness and turnover occur in response to long-distance movements, but we do not yet know how rare or sporadic dispersal events for non-migratory organisms might affect the microbiomes of their hosts. Here we directly examine the microbiomes of rafting seaweed, leveraging host genomic analyses, amplicon sequencing, and oceanographic modelling to study the impacts of ecological dispersal of hosts on their microbiomes.

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Therapeutic proteins, the fastest growing class of pharmaceuticals, are subject to rapid proteolytic degradation in vivo, rendering them inactive. Sophisticated drug delivery systems that maintain protein stability, prolong therapeutic effects, and reduce administration frequency are urgently required. Herein, a mechanoresponsive hydrogel is developed contained within a soft robotic drug delivery (SRDD) device.

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Transplantation of donor islets of Langerhans is a potential therapeutic approach for patients with diabetes mellitus; however, its success is limited by islet death and dysfunction during the initial hypoxic conditions at the transplantation site. This highlights the need to support the donor islets in the days post-transplantation until the site is vascularized. It was previously demonstrated that the extracellular matrix (ECM) proteins nidogen-1 (NID1) and decorin (DCN) improve the functionality and survival of the β-cell line, EndoC-βH3, and the viability of human islets post-isolation.

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Introduction: Myalgic encephalomyelitis/ chronic fatigue syndrome (ME/CFS) is a chronic condition which may be characterised by debilitating fatigue, post-exertional malaise, unrefreshing sleep, and cognitive difficulties. ME/CFS has significant negative impact on quality of life for those living with the condition. This may be exacerbated by a lack of knowledge within healthcare regarding the condition.

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Article Synopsis
  • A deep learning pipeline was developed to automatically identify videos of the heart's apical 4-chamber view and assess the severity of mitral regurgitation (MR) using transthoracic echocardiograms.
  • The pipeline was trained and validated on over 58,000 echocardiograms, achieving high accuracy in recognizing color Doppler images and determining MR severity, with AUC values exceeding 0.9 in different test cohorts.
  • The automated model showed strong sensitivity and specificity for detecting clinically significant MR, indicating its potential as an effective tool for echocardiographic evaluation in clinical settings.
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Marine sponges have recently emerged as efficient natural environmental DNA (eDNA) samplers. The ability of sponges to accumulate eDNA provides an exciting opportunity to reconstruct contemporary communities and ecosystems with high temporal and spatial precision. However, the use of historical eDNA, trapped within the vast number of specimens stored in scientific collections, opens up the opportunity to begin to reconstruct the communities and ecosystems of the past.

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Passive samplers are enabling the scaling of environmental DNA (eDNA) biomonitoring in our oceans, by circumventing the time-consuming process of water filtration. Designing a novel passive sampler that does not require extensive sample handling time and can be connected to ocean-going vessels without impeding normal underway activities has potential to rapidly upscale global biomonitoring efforts onboard the world's oceanic fleet. Here, we demonstrate the utility of an artificial sponge sampler connected to the continuous pump underway seawater system as a means to enable oceanic biomonitoring.

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Objectives: To longitudinally characterize disease-relevant CSF and plasma biomarkers in individuals at risk for genetic prion disease up to disease conversion.

Methods: This single-center longitudinal cohort study has followed known carriers of pathogenic variants at risk for prion disease, individuals with a close relative who died of genetic prion disease but who have not undergone predictive genetic testing, and controls. All participants were asymptomatic at first visit and returned roughly annually.

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Our understanding of cardiac remodeling processes due to left ventricular pressure overload derives largely from animal models of aortic banding. However, these studies fail to enable control over both disease progression and reversal, hindering their clinical relevance. Here, we describe a method for progressive and reversible aortic banding based on an implantable expandable actuator that can be finely tuned to modulate aortic banding and debanding in a rat model.

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Host-associated microbial communities are shaped by host migratory movements. These movements can have contrasting impacts on microbiota, and understanding such patterns can provide insight into the ecological processes that contribute to community diversity. Furthermore, long-distance movements to new environments are anticipated to occur with increasing frequency due to host distribution shifts resulting from climate change.

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Article Synopsis
  • Echocardiography is widely used for evaluating heart structure and function, but cardiac magnetic resonance (CMR) imaging offers detailed tissue analysis, including fibrosis and inflammation indicators, which may not be detectable by traditional methods.
  • A study was conducted where a deep learning model was trained on echocardiography videos of patients who had both echocardiograms and CMRs to predict certain CMR measures like wall motion abnormalities and tissue characteristics.
  • The model successfully predicted wall motion abnormalities with high accuracy but struggled with detecting other important tissue characteristics, indicating that such information might not be captured in echocardiography videos and highlighting the continuing importance of CMR for assessing heart tissue.
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Implantable medical devices that can facilitate therapy transport to localized sites are being developed for a number of diverse applications, including the treatment of diseases such as diabetes and cancer, and tissue regeneration after myocardial infraction. These implants can take the form of an encapsulation device which encases therapy in the form of drugs, proteins, cells, and bioactive agents, in semi-permeable membranes. Such implants have shown some success but the nature of these devices pose a barrier to the diffusion of vital factors, which is further exacerbated upon implantation due to the foreign body response (FBR).

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Climate change is altering environmental conditions, with microclimates providing small-scale refuges within otherwise challenging environments. Durvillaea (southern bull kelp; rimurapa) is a genus of large intertidal fucoid algae, and some species harbour diverse invertebrate communities in their holdfasts. We hypothesised that animal-excavated Durvillaea holdfasts provide a thermal refuge for epibiont species, and tested this hypothesis using the exemplar species D.

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Introduction: Neural crest cells (NCCs) are multipotent and are attributed to the combination of complex multimodal gene regulatory mechanisms. Cardiac neural crest (CNC) cells, originating from the dorsal neural tube, are pivotal architects of the cardio-neuro-vascular domain, which orchestrates the embryogenesis of critical cardiac and vascular structures. Remarkably, while the scientific community compiled a comprehensive inventory of neural crest derivatives by the early 1980s, our understanding of the CNC's role in various cardiovascular disease processes still needs to be explored.

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Article Synopsis
  • A deep learning algorithm was developed to analyze transthoracic echocardiograms (TTEs) and identify patients with atrial fibrillation (AF), even in cases where symptoms were not present.
  • The model demonstrated high accuracy in distinguishing between TTEs showing AF and those showing sinus rhythm, achieving an AUC score of 0.96 and effectively predicting paroxysmal AF presence in patients with sinus rhythm at an AUC of 0.74.
  • The algorithm outperformed traditional clinical risk factors and TTE measurements, suggesting its potential for opportunistic AF screening and earlier treatment in patients.
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Polynyas, areas of open water embedded within sea ice, are a key component of ocean-atmosphere interactions that act as hotspots of sea-ice production, bottom-water formation, and primary productivity. The specific drivers of polynya dynamics remain, however, elusive and coupled climate models struggle to replicate Antarctic polynya activity. Here, we leverage a 44-y time series of Antarctic sea ice to elucidate long-term trends.

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Background: With the spread of SARS-CoV-2 impacting upon public health directly and socioeconomically, further information was required to inform policy decisions designed to limit virus spread during the pandemic. This study sought to contribute to serosurveillance work within Northern Ireland to track SARS-CoV-2 progression and guide health strategy.

Methods: Sera/plasma samples from clinical biochemistry laboratories were analysed for anti-SARS-CoV-2 antibodies.

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Importance: Genetic prion disease is a universally fatal and rapidly progressive neurodegenerative disease for which genetically targeted therapies are currently under development. Preclinical proofs of concept indicate that treatment before symptoms will offer outsize benefit. Though early treatment paradigms will be informed by the longitudinal biomarker trajectory of mutation carriers, to date limited cases have been molecularly tracked from the presymptomatic phase through symptomatic onset.

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Advancements in medical imaging and artificial intelligence (AI) have revolutionized the field of cardiac diagnostics, providing accurate and efficient tools for assessing cardiac function. AI diagnostics claims to improve upon the human-to-human variation that is known to be significant. However, when put in practice, for cardiac ultrasound, AI models are being run on images acquired by human sonographers whose quality and consistency may vary.

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Article Synopsis
  • Existing preoperative risk assessments are inadequate at predicting postoperative mortality, but deep-learning analysis of ECGs can highlight hidden risk factors.
  • A deep-learning algorithm was developed using ECG data from nearly 46,000 patients to more accurately forecast postoperative mortality, and its performance was compared to the Revised Cardiac Risk Index (RCRI).
  • In testing, the algorithm achieved an AUC of 0.83, significantly outperforming the RCRI score (AUC of 0.67), indicating its effectiveness across multiple health-care systems.
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Introduction: Only 5% of rare diseases have an approved treatment available, therefore patients often utilise complementary and integrative medicines (CIMs) to help manage their condition. Limited high-quality evidence-based studies are available which support the effectiveness of CIM, as it is difficult to show that an outcome is a direct result of the CIM intervention and not due to bias. Patients and healthcare professionals must weigh up the evidence quality, safety, efficacy, practical logistics, and financial implications of utilising CIM for rare diseases.

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The foreign body response (FBR) to implanted materials culminates in the deposition of a hypo-permeable, collagen rich fibrotic capsule by myofibroblast cells at the implant site. The fibrotic capsule can be deleterious to the function of some medical implants as it can isolate the implant from the host environment. Modulation of fibrotic capsule formation has been achieved using intermittent actuation of drug delivery implants, however the mechanisms underlying this response are not well understood.

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This study describes the hybrid genome assemblies of four Shiga toxin-producing strains isolated from the recto-anal junction of slaughter-age Irish sheep. serotyping and genome analysis determined that each of the strains harbored a Shiga-toxin subtype, a complete locus of enterocyte effacement, and a rare O-island 122.

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In western Canada, decades of oil-and-gas exploration have fragmented boreal landscapes with a dense network of linear forest disturbances (seismic lines). These seismic lines are implicated in the decline in wildlife populations that are adapted to function in unfragmented forest landscapes. In particular, anthropogenic disturbances have led to a decline of woodland caribou populations due to increasing predator access to core caribou habitat.

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