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Cristina Lanzas

Researcher at North Carolina State University

Publications -  73
Citations -  1452

Cristina Lanzas is an academic researcher from North Carolina State University. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 20, co-authored 65 publications receiving 1249 citations. Previous affiliations of Cristina Lanzas include National Institute for Mathematical and Biological Synthesis & North Carolina State University College of Veterinary Medicine.

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A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants

TL;DR: In this paper, a modified version of the Cornell Net Carbohydrate and Protein System (CNCPS) was used to predict the digestibility of ruminant diets for appropriate levels and types of dietary carbohydrates.
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Epidemiological model for Clostridium difficile transmission in healthcare settings.

TL;DR: It is suggested that transmission within the ward alone from patients with CDI cannot sustain new C. difficile colonizations and therefore that the admission of colonized patients plays an important role in sustaining transmission in the ward.
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Shifts in the Gut Metabolome and Clostridium difficile Transcriptome throughout Colonization and Infection in a Mouse Model.

TL;DR: The gut environment after antibiotics and during the initial stages of C. difficile colonization and infection is defined and amino acids, in particular, proline and branched-chain amino acids and carbohydrates decrease in abundance over time and that C.difficile gene expression is consistent with their utilization in vivo.
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Development and evaluation of empirical equations to predict feed passage rate in cattle

TL;DR: In this paper, a random coefficients model that used each study effect as a random variable was used to select statistically significant input variables to predict rate of passage for all classes of dairy and beef cattle.
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Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

TL;DR: Real-time location system is used to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen.