Physiology - Journal Articles

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    Investigation of the gut microbiome, bile acid composition and host immunoinflammatory response in a model of azoxymethane-induced colon cancer at discrete timepoints
    (Springer Nature, 2022-11-23) Keane, Jonathan M.; Walsh, Calum J.; Cronin, P.; Baker, Kevin J.; Melgar, Silvia; Cotter, Paul D.; Joyce, Susan A.; Gahan, Cormac G. M.; Houston, Aileen M.; Hyland, Niall P.; Science Foundation Ireland
    Background: Distinct sets of microbes contribute to colorectal cancer (CRC) initiation and progression. Some occur due to the evolving intestinal environment but may not contribute to disease. In contrast, others may play an important role at particular times during the tumorigenic process. Here, we describe changes in the microbiota and host over the course of azoxymethane (AOM)-induced tumorigenesis. Methods: Mice were administered AOM or PBS and were euthanised 8, 12, 24 and 48 weeks later. Samples were analysed using 16S rRNA gene sequencing, UPLC-MS and qRT-PCR. Results: The microbiota and bile acid profile showed distinct changes at each timepoint. The inflammatory response became apparent at weeks 12 and 24. Moreover, significant correlations between individual taxa, cytokines and bile acids were detected. One co-abundance group (CAG) differed significantly between PBS- and AOM-treated mice at week 24. Correlation analysis also revealed significant associations between CAGs, bile acids and the bile acid transporter, ASBT. Aberrant crypt foci and adenomas were first detectable at weeks 24 and 48, respectively. Conclusion: The observed changes precede host hyperplastic transformation and may represent early therapeutic targets for the prevention or management of CRC at specific timepoints in the tumorigenic process.
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    Development of novel therapeutics for all individuals with CF (the future goes on)
    (Elsevier B.V., 2022-10-30) Amaral, Margarida D.; Harrison, Patrick T.; Science Foundation Ireland; Horizon 2020; Fundação para a Ciência e a Tecnologia; Ministério da Ciência, Tecnologia e Ensino Superior; Cystic Fibrosis Trust; Cystic Fibrosis Foundation
    Despite the major advances and successes in finding and establishing new treatments that tackle the basic defect in Cystic Fibrosis (CF), there is still an unmet need to bring these potentially curative therapies to all individuals with CF. Here, we review aspects of what is still missing to treat all individuals with CF by such approaches. On the one hand, we discuss novel holistic (high-throughput) approaches to elucidate mechanistic defects caused by distinct classes of mutations to identify novel drug targets. On the other hand, we examine therapeutic approaches to correct the gene in its own environment, i.e., in the genome.
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    Impact of cancer cachexia on respiratory muscle function and the therapeutic potential of exercise
    (John Wiley & Sons, Inc., 2022-10-17) Murphy, Ben T.; Mackrill, John J.; O'Halloran, Ken D.
    Cancer cachexia is defined as a multi-factorial syndrome characterised by an ongoing loss of skeletal muscle mass and progressive functional impairment, estimated to affect 50–80% of patients and responsible for 20% of cancer deaths. Elevations in the morbidity and mortality rates of cachectic cancer patients has been linked to respiratory failure due to atrophy and dysfunction of the ventilatory muscles. Despite this, there is a distinct scarcity of research investigating the structural and functional condition of the respiratory musculature in cancer, with the majority of studies exclusively focussing on limb muscle. Treatment strategies are largely ineffective in mitigating the cachectic state. It is now widely accepted that an efficacious intervention will likely combine elements of pharmacology, nutrition, and exercise. However, of these approaches, exercise has received comparatively little attention. Therefore, it is unlikely to be implemented optimally, whether in isolation or combination. In consideration of these limitations, the current review describes the mechanistic basis of cancer cachexia, and subsequently explores the available respiratory- and exercise-focussed literature within this context. The molecular basis of cachexia is thoroughly reviewed. The pivotal role of inflammatory mediators is described. Unravelling the mechanisms of exercise-induced support of muscle via antioxidant and anti-inflammatory effects in addition to promoting efficient energy metabolism via increased mitochondrial biogenesis, mitochondrial function, and muscle glucose uptake provide avenues for interventional studies. Currently available pre-clinical mouse models including novel transgenic animals provide a platform for the development of multi-modal therapeutic strategies to protect respiratory muscles in people with cancer.
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    A framework for AI-assisted detection of Patent Ductus Arteriosus from neonatal phonocardiogram
    (MDPI, 2021-02-05) Gómez-Quintana, Sergi; Schwarz, Christoph E.; Shelevytsky, Ihor; Shelevytska, Victoriya; Semenova, Oksana; Factor, Andreea; Popovici, Emanuel; Temko, Andriy; Science Foundation Ireland; Deutsche Forschungsgemeinschaft; Wellcome Trust; Grand Challenges Canada
    The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.
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    A method for AI assisted human interpretation of neonatal EEG
    (Springer Nature Switzerland AG, 2022-06-29) Gómez-Quintana, Sergi; O'Shea, Alison; Factor, Andreea; Popovici, Emanuel; Temko, Andriy; Science Foundation Ireland
    The study proposes a novel method to empower healthcare professionals to interact and leverage AI decision support in an intuitive manner using auditory senses. The methodâ s suitability is assessed through acoustic detection of the presence of neonatal seizures in electroencephalography (EEG). Neurophysiologists use EEG recordings to identify seizures visually. However, neurophysiological expertise is expensive and not available 24/7, even in tertiary hospitals. Other neonatal and pediatric medical professionals (nurses, doctors, etc.) can make erroneous interpretations of highly complex EEG signals. While artificial intelligence (AI) has been widely used to provide objective decision support for EEG analysis, AI decisions are not always explainable. This work developed a solution to combine AI algorithms with a human-centric intuitive EEG interpretation method. Specifically, EEG is converted to sound using an AI-driven attention mechanism. The perceptual characteristics of seizure events can be heard using this method, and an hour of EEG can be analysed in five seconds. A survey that has been conducted among targeted end-users on a publicly available dataset has demonstrated that not only does it drastically reduce the burden of reviewing the EEG data, but also the obtained accuracy is on par with experienced neurophysiologists trained to interpret neonatal EEG. It is also shown that the proposed communion of a medical professional and AI outperforms AI alone by empowering the human with little or no experience to leverage AI attention mechanisms to enhance the perceptual characteristics of seizure events.