14 research outputs found

    Bovine pericardium retail preserved in glutaraldehyde and used as a vascular patch

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>In this study we evaluated the performance of bovine pericardium preserved in glutaraldehyde used as a vascular patch.</p> <p>Methods</p> <p>Fourteen young pigs, six females and eight males, weighting 10.3 - 18.4 kg were used in our study. We implanted three remnants in each pig, two in the abdominal aorta and one was juxtaposed to the peritoneum. The smooth face (SF) and rough face (RF) of each remnant were implanted turned to the vessel inner portion and one remnant was juxtaposed to the peritoneum. The animals were sacrificed in 4.5 - 8 months after surgery (75 - 109 kg). The remnants were assessed for aorta wall, fibroses formation in inner apposition and calcification related to the face turned to the vessel inner portion.</p> <p>Results</p> <p>The rough face showed a lower dilatation level compared to the face implanted in adjacent aorta. There was no difference between intensity and/or incidence of graft calcification when the superficies were compared. The bovine pericardium preserved in glutaraldehyde did not show alterations in its structure when implanted with different faces turned to the inner portion of vessel.</p> <p>Conclusion</p> <p>When turned to the inner portion of the vessel, the rough face of the remnant presented a lower dilatation in relation to the adjacent aorta and a better quality of endothelium layer and did not show a difference between intensity and/or incidence of graft calcification.</p

    Neural network modelling of the influence of channelopathies on reflex visual attention

    No full text
    This paper introduces a model of Emergent Visual Attention in presence of calcium channelopathy (EVAC). By modelling channelopathy, EVAC constitutes an effort towards identifying the possible causes of autism. The network structure embodies the dual pathways model of cortical processing of visual input, with reflex attention as an emergent property of neural interactions. EVAC extends existing work by introducing attention shift in a larger-scale network and applying a phenomenological model of channelopathy. In presence of a distractor, the channelopathic network’s rate of failure to shift attention is lower than the control network’s, but overall, the control network exhibits a lower classification error rate. The simulation results also show differences in task-relative reaction times between control and channelopathic networks. The attention shift timings inferred from the model are consistent with studies of attention shift in autistic children
    corecore