Gene/Protein Disease Symptom Drug Enzyme Compound
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The voluntary phase of an industry-led national Bovine Viral Diarrhoea (BVD) eradication programme began in Ireland on January 1, 2012 with the goal of progressing to a compulsory programme in 2013. The development and implementation of the programme in 2012 was informed by a review of current and prior eradication programmes elsewhere in Europe and extensive stakeholder consultation. The programme was based on tissue tag testing of newborn calves in participating herds, with the status of the mothers of calves with positive or inconclusive results requiring clarification. Participating herd owners were required to comply with a series of guidelines, including not selling cattle suspected of being persistently infected. For herds compliant with the guidelines, the results from 2012 counted as one of three years of tag testing anticipated in the compulsory phase of the programme. Testing was carried out in laboratories designated for this purpose by the cross-industry BVD Implementation Group that oversees the programme. Results were reported to a central database managed by the Irish Cattle Breeding Federation, and the majority of results were reported to farmers' mobile telephones by SMS message. A detailed review of the programme was conducted, encompassing the period between January 1, 2012 and July 15, 2012, based on results from approximately 500,000 calves. This paper describes the establishment and structure of the programme, and the outcomes of the review, including findings at herd and animal level.
Vet Rec 2014 Jan 18
PMID:Development and review of the voluntary phase of a national BVD eradication programme in Ireland. 2439 63

Simultaneous multi-slice or multi-band (SMS/MB) imaging allows accelerated coverage in magnetic resonance imaging (MRI). Multiple slices are excited and acquired at the same time, and reconstructed using the redundancies in receiver coil arrays, similar to parallel imaging. SMS/MB reconstruction is currently performed with linear reconstruction techniques. Recently, a nonlinear reconstruction method for parallel imaging, Robust Artificial-neural-networks for k-space Interpolation (RAKI) was proposed and shown to improve upon linear methods. This method uses convolutional neural networks (CNN) trained solely on subject-specific calibration data. In this study, we sought to extend RAKI to SMS/MB imaging reconstruction. CNN training was performed on calibration data acquired prior to SMS/MB imaging, in a manner consistent with the existing linear methods. These CNNs were used to reconstruct a time series of functional MRI (fMRI) data. CNN network parameters were optimized using an extensive search of the parameter space. With these optimal parameters, RAKI substantially improves image quality compared to a commonly used linear reconstruction algorithm, especially for high acceleration rates.
Conf Rec Asilomar Conf Signals Syst Comput 2018 Oct
PMID:Accelerated Simultaneous Multi-Slice MRI using Subject-Specific Convolutional Neural Networks. 3189 67