Concordia University

About: Concordia University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Context (language use) & Control theory. The organization has 13565 authors who have published 31084 publications receiving 783525 citations. The organization is also known as: Sir George Williams University & Loyola College, Montreal.

Erythropoietin treatment elevates haemoglobin concentration by increasing red cell volume and depressing plasma volume

Abstract: Erythropoietin (Epo) has been suggested to affect plasma volume, and would thereby possess a mechanism apart from erythropoiesis to increase arterial oxygen content. This, and potential underlying mechanisms, were tested in eight healthy subjects receiving 5000 IU recombinant human Epo (rHuEpo) for 15 weeks at a dose frequency aimed to increase and maintain haematocrit at approximately 50%. Red blood cell volume was increased from 2933 ± 402 ml before rHuEpo treatment to 3210 ± 356 (P < 0.01), 3117 ± 554 (P < 0.05), and 3172 ± 561 ml (P < 0.01) after 5, 11 and 13 weeks, respectively. This was accompanied by a decrease in plasma volume from 3645 ± 538 ml before rHuEpo treatment to 3267 ± 333 (P < 0.01), 3119 ± 499 (P < 0.05), and 3323 ± 521 ml (P < 0.01) after 5, 11 and 13 weeks, respectively. Concomitantly, plasma renin activity and aldosterone concentration were reduced. This maintained blood volume relatively unchanged, with a slight transient decrease at week 11, such that blood volume was 6578 ± 839 ml before rHuEpo treatment, and 6477 ± 573 (NS), 6236 ± 908 (P < 0.05), and 6495 ± 935 ml (NS), after 5, 11 and 13 weeks of treatment. We conclude that Epo treatment in healthy humans induces an elevation in haemoglobin concentration by two mechanisms: (i) an increase in red cell volume; and (ii) a decrease in plasma volume, which is probably mediated by a downregulation of the rennin–angiotensin–aldosterone axis. Since the relative contribution of plasma volume changes to the increments in arterial oxygen content was between 37.9 and 53.9% during the study period, this mechanism seems as important for increasing arterial oxygen content as the well-known erythropoietic effect of Epo.

Modeling Bridge Deterioration Using Case-Based Reasoning

Abstract: Current bridge deterioration models used in bridge management systems are not successful in capturing the effects of bridge condition history on future condition, in performing what if analyses for...

Author Correction: A compendium of geochemical information from the Saanich Inlet water column

Abstract: In Table 3 of this Data Descriptor the units of Mean_N2O and Mean_CH4 are incorrectly stated as "Nanomolar (μM)". This should instead read "Nanomolar (nM)".

Developing Practical Neural Network Applications Using Back-Propagation

Abstract: In the past few years, neural networks have emerged as a problem-solving technique with capabilities suited to many civil engineering problems. Among the various neural network paradigms available, back-propagation is by far the most utilized for its relatively simple mathematical proofs and good generalization capabilities. Despite its capabilities, back-propagation suffers from several problems that hinder the development of practical neural network applications. These include slow training, ill-defined knowledge representation and problem structuring, and nonguided design of an optimal network configuration for adequate generalization. This paper represents an effort to guide the process of developing practical neural network applications using back-propagation. The paper starts with a brief description of back-propagation mathematics. Some of the heuristics and techniques used to overcome back-propagation problems, particularly lack of generalization, are identified and outlined, along with areas of potential improvements to the paradigm. An application development methodology is proposed utilizing the identified heuristics and techniques. The methodology provides a structured framework for designing and implementing practical neural network applications with less effort.