What neuroscientific studies tell us about inhibition of return

An inhibitory aftermath of orienting, inhibition of return (IOR), has intrigued scholars since its discovery about 40 years ago. Since then, the phenomenon has been subjected to a wide range of neuroscientific methods and the results of these are reviewed in this paper. These include direct manipulations of brain structures (which occur naturally in brain damage and disease or experimentally as in TMS and lesion studies) and measurements of brain activity (in humans using EEG and fMRI and in animals using single unit recording). A variety of less direct methods (e.g., computational modeling, developmental studies, etc.) have also been used. The findings from this wide range of methods support the critical role of subcortical and cortical oculomotor pathways in the generation and nature of IOR

Sublethal exposure to copper supresses the ability to acclimate to hypoxia in a model fish species

This is the final version. Available on open access from Elsevier via the DOI in this recordHypoxia is one of the major threats to biodiversity in aquatic systems. The association of hypoxia with nutrient-rich effluent input into aquatic systems results in scenarios where hypoxic waters could be contaminated with a wide range of chemicals, including metals. Despite this, little is known about the ability of fish to respond to hypoxia when exposures occur in the presence of environmental toxicants. We address this knowledge gap by investigating the effects of exposures to different levels of oxygen in the presence or absence of copper using the three-spined sticklebacks (Gasterosteus aculeatus) model. Fish were exposed to different air saturations (AS; 100%, 75% and 50%) in combination with copper (20 μg/L) over a 4 day period. The critical oxygen level (Pcrit), an indicator of acute hypoxia tolerance, was 54.64 ± 2.51% AS under control conditions, and 36.21 ± 2.14% when fish were chronically exposed to hypoxia (50% AS) for 4 days, revealing the ability of fish to acclimate to low oxygen conditions. Importantly, the additional exposure to copper (20 μg/L) prevented this improvement in Pcrit, impairing hypoxia acclimation. In addition, an increase in ventilation rate was observed for combined copper and hypoxia exposure, compared to the single stressors or the controls. Interestingly, in the groups exposed to copper, a large increase in variation in the measured Pcrit was observed between individuals, both under normoxic and hypoxic conditions. This variation, if observed in wild populations, may lead to selection for a tolerant phenotype and alterations in the gene pool of the populations, with consequences for their sustainability. Our findings provide strong evidence that copper reduces the capacity of fish to respond to hypoxia by preventing acclimation and will inform predictions of the consequences of global increases of hypoxia in water systems affected by other pollutants worldwide.University of ExeterCentre for Environment Fisheries and Aquaculture Science (Cefas)Biotechnology and Biological Sciences Research Council (BBSRC)ONICYT-FONDECY

Correction: How Long Is Too Long in Contemporary Peer Review? Perspectives from Authors Publishing in Conservation Biology Journals.

<p>Correction: How Long Is Too Long in Contemporary Peer Review? Perspectives from Authors Publishing in Conservation Biology Journals</p

Machine learning algorithms for the prediction of EUROP classification grade and carcass weight, using 3-dimensional measurements of beef carcasses

Introduction: Mechanical grading can be used to objectively classify beef carcasses. Despite its many benefits, it is scarcely used within the beef industry, often due to infrastructure and equipment costs. As technology progresses, systems become more physically compact, and data storage and processing methods are becoming more advanced. Purpose-built imaging systems can calculate 3-dimensional measurements of beef carcasses, which can be used for objective grading.Methods: This study explored the use of machine learning techniques (random forests and artificial neural networks) and their ability to predict carcass conformation class, fat class and cold carcass weight, using both 3-dimensional measurements (widths, lengths, and volumes) of beef carcasses, extracted using imaging technology, and fixed effects (kill date, breed type and sex). Cold carcass weight was also included as a fixed effect for prediction of conformation and fat classes.Results: Including the dimensional measurements improved prediction accuracies across traits and techniques compared to that of results from models built excluding the 3D measurements. Model validation of random forests resulted in moderate-high accuracies for cold carcass weight (R2 = 0.72), conformation class (71% correctly classified), and fat class (55% correctly classified). Similar accuracies were seen for the validation of the artificial neural networks, which resulted in high accuracies for cold carcass weight (R2 = 0.68) and conformation class (71%), and moderate for fat class (57%).Discussion: This study demonstrates the potential for 3D imaging technology requiring limited infrastructure, along with machine learning techniques, to predict key carcass traits in the beef industry

Machine learning algorithms for the prediction of EUROP classification grade and carcass weight, using 3-dimensional measurements of beef carcasses

Introduction: Mechanical grading can be used to objectively classify beef carcasses. Despite its many benefits, it is scarcely used within the beef industry, often due to infrastructure and equipment costs. As technology progresses, systems become more physically compact, and data storage and processing methods are becoming more advanced. Purpose-built imaging systems can calculate 3-dimensional measurements of beef carcasses, which can be used for objective grading.Methods: This study explored the use of machine learning techniques (random forests and artificial neural networks) and their ability to predict carcass conformation class, fat class and cold carcass weight, using both 3-dimensional measurements (widths, lengths, and volumes) of beef carcasses, extracted using imaging technology, and fixed effects (kill date, breed type and sex). Cold carcass weight was also included as a fixed effect for prediction of conformation and fat classes.Results: Including the dimensional measurements improved prediction accuracies across traits and techniques compared to that of results from models built excluding the 3D measurements. Model validation of random forests resulted in moderate-high accuracies for cold carcass weight (R2 = 0.72), conformation class (71% correctly classified), and fat class (55% correctly classified). Similar accuracies were seen for the validation of the artificial neural networks, which resulted in high accuracies for cold carcass weight (R2 = 0.68) and conformation class (71%), and moderate for fat class (57%).Discussion: This study demonstrates the potential for 3D imaging technology requiring limited infrastructure, along with machine learning techniques, to predict key carcass traits in the beef industry

The influence of perfusion solution on renal graft viability assessment

BACKGROUND: Kidneys from donors after cardiac or circulatory death are exposed to extended periods of both warm ischemia and intra-arterial cooling before organ recovery. Marshall’s hypertonic citrate (HOC) and Bretschneider’s histidine-tryptophan-ketoglutarate (HTK) preservation solutions are cheap, low viscosity preservation solutions used clinically for organ flushing. The aim of the present study was to evaluate the effects of these two solutions both on parameters used in clinical practice to assess organ viability prior to transplantation and histological evidence of ischemic injury after reperfusion. METHODS: Rodent kidneys were exposed to post-mortem warm ischemia, extended intra-arterial cooling (IAC) (up to 2 h) with preservation solution and reperfusion with either Krebs-Hensleit or whole blood in a transplant model. Control kidneys were either reperfused directly after retrieval or stored in 0.9% saline. Biochemical, immunological and histological parameters were assessed using glutathione-S-transferase (GST) enzymatic assays, polymerase chain reaction and mitochondrial electron microscopy respectively. Vascular function was assessed by supplementing the Krebs-Hensleit perfusion solution with phenylephrine to stimulate smooth muscle contraction followed by acetylcholine to trigger endothelial dependent relaxation. RESULTS: When compared with kidneys reperfused directly post mortem, 2 h of IAC significantly reduced smooth muscle contractile function, endothelial function and upregulated vascular cellular adhesion molecule type 1 (VCAM-1) independent of the preservation solution. However, GST release, vascular resistance, weight gain and histological mitochondrial injury were dependent on the preservation solution used. CONCLUSIONS: We conclude that initial machine perfusion viability tests, including ischemic vascular resistance and GST, are dependent on the perfusion solution used during in situ cooling. HTK-perfused kidneys will be heavier, have higher GST readings and yet reduced mitochondrial ischemic injury when compared with HOC-perfused kidneys. Clinicians should be aware of this when deciding which kidneys to transplant or discard