| Affiliations: | Michael E. DeBakey Institute Undergraduate Research Program |
| Project Leader: | Chesley Johnson cmjcmj25@tamu.edu Biology |
| Faculty Mentor: | Christopher Quick, Ph.D. |
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Meeting Times:
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Summer 2017: TBD |
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Team Size:
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3 (Team Full) |
| Open Spots: | 0 |
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Special Opportunities:
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This project is well-developed, and a manuscript is in preparation for submission to the American Journal of Physiology. Team members will have an opportunity to continue this project in the Fall, and those making a scientific contribution will earn co-authorship. |
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Team Needs:
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We are looking for team members with different strengths that can advance the project. We are particularly seeking a team member with a strong writing skills, a member with an interest in mathematical modeling, and a team member who is interested in synthesizing information from diverse journal articles. Students will be expected to register for 3 ch of research (VTPP 291/491 or BMEN 291/491). |
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Description:
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Nutrients absorbed into the interstitial space from the intestinal lumen can be transported either by intestinal capillaries to the liver or by the mesenteric lymphatics to the great veins of the neck. Several factors can alter the fraction of nutrients that are transported by mesenteric lymphatics, including abnormal liver function. Experimental approaches employed to elucidate the mechanisms governing the relative flow through these two parallel pathways are limited, because critical parameters are difficult to measure and cannot be controlled independently. Conventional mathematical modeling approaches are also limited, because the numerical solution of the systems of equations are sensitive to assumed parameter values and must employ advanced computational techniques. Therefore, the purpose of the present work is to develop a simple algebraic formula that predicts the fraction of nutrients that is transported by the mesenteric lymphatic vessels. This model will not only allow for the prediction of nutrient transport, but will also serve as a novel tool in characterizing critical parameter values in clinically relevant disease states. |