Biomedical subjects

Sue C Geller

Publications and source records attributed to Sue C Geller.

3 recordsLinked to original sources

PubMed2005

Effect of medetomidine and its antagonism with atipamezole on stress-related hormones, metabolites, physiologic responses, sedation, and mechanical threshold in goats.

OBJECTIVE: To evaluate the effects of medetomidine and its antagonism with atipamezole in goats. STUDY DESIGN: Prospective randomized crossover study with 1 week between treatments. ANIMALS: Six healthy 3-year-old neutered goats (three male and three female) weighing 39.1-90.9 kg (60.0 +/- 18 kg, mean +/- SD). METHODS: Goats were given medetomidine (20 microg kg(-1), IV) followed, 25 minutes later, by either atipamezole (100 microg kg(-1), IV) or saline. Heart and respiratory rate, rectal temperature, indirect blood pressure, and mechanical threshold were measured, and sedation and posture were scored and blood samples obtained to measure epinephrine, norepinephrine, free fatty acids, glucose, and cortisol concentrations at baseline (immediately before medetomidine), 5 and 25 minutes after medetomidine administration, and at 5, 30, 60, and 120 minutes after the administration of antagonist or saline. Parametric and nonparametric tests were used to evaluate data; p < 0.05 was considered significant. RESULTS: Medetomidine decreased body temperature, heart rate, and respiratory rate and increased mean arterial blood pressure, cortisol, and glucose. Recumbency occurred 89 +/- 50 seconds after medetomidine administration. All goats were standing 86 +/- 24 seconds after atipamezole administration whereas all goats administered saline were sedate and recumbent at 2 hours. Tolerance to compression of the withers and metacarpus increased with medetomidine. From 5 to 120 minutes after saline or atipamezole administration, there were differences in body temperature, glucose, and cortisol but none in heart rate or blood pressure. Three of the six goats receiving saline developed bloat; five of six urinated. After atipamezole, four of six goats developed piloerection and all goats were agitated and vocalized. CONCLUSION: At the doses used, atipamezole antagonized the effects of medetomidine on recumbency, sedation, mechanical threshold, and the increase in glucose. Atipamezole increased the rate of return of cortisol toward baseline, and prevented further decline in rectal body temperature. CLINICAL RELEVANCE: Atipamezole may be used to antagonize some, but not all effects of medetomidine.

Adrenergic alpha-Agonists↗

PubMed2003

Evaluation of microchip migration in horses, donkeys, and mules.

OBJECTIVE: To determine whether microchips used for identification migrate after implantation in horses, donkeys, and mules. DESIGN: Prospective study. ANIMALS: 53 horses, donkeys, and mules. PROCEDURE: Twenty horses that had had microchips implanted in the nuchal ligament at a veterinary teaching hospital from 1996 through early 2000 were included (group 1), and the poll-to-withers distance and location of the microchip were determined, measured, and recorded. Additionally, the poll-to-withers distance was measured in 16 horses, 12 donkeys, and 5 mules (group 2), and microchips were implanted in the nuchal ligament on the left side of the neck. Forty-two to 67 days after implantation, the location of the microchip was determined, measured, and recorded. RESULTS: Microchips implanted in the nuchal ligament < or = 4 years previously did not migrate. All microchips were detected with a multimode identification tag reader from the left side of the neck in the midcervical region, and microchips were located at the midpoint between the poll and withers for all 53 horses, donkeys, and mules. CONCLUSIONS AND CLINICAL RELEVANCE: Microchips implanted in the nuchal ligament < or = 4 years earlier did not migrate in horses. Microchips may be useful for identification in horses.

Animal Identification Systems↗

PubMed2003

Transformation and normalization of oligonucleotide microarray data.

MOTIVATION: Most methods of analyzing microarray data or doing power calculations have an underlying assumption of constant variance across all levels of gene expression. The most common transformation, the logarithm, results in data that have constant variance at high levels but not at low levels. Rocke and Durbin showed that data from spotted arrays fit a two-component model and Durbin, Hardin, Hawkins, and Rocke, Huber et al. and Munson provided a transformation that stabilizes the variance as well as symmetrizes and normalizes the error structure. We wish to evaluate the applicability of this transformation to the error structure of GeneChip microarrays. RESULTS: We demonstrate in an example study a simple way to use the two-component model of Rocke and Durbin and the data transformation of Durbin, Hardin, Hawkins and Rocke, Huber et al. and Munson on Affymetrix GeneChip data. In addition we provide a method for normalization of Affymetrix GeneChips simultaneous with the determination of the transformation, producing a data set without chip or slide effects but with constant variance and with symmetric errors. This transformation/normalization process can be thought of as a machine calibration in that it requires a few biologically constant replicates of one sample to determine the constant needed to specify the transformation and normalize. It is hypothesized that this constant needs to be found only once for a given technology in a lab, perhaps with periodic updates. It does not require extensive replication in each study. Furthermore, the variance of the transformed pilot data can be used to do power calculations using standard power analysis programs. AVAILABILITY: SPLUS code for the transformation/normalization for four replicates is available from the first author upon request. A program written in C is available from the last author.

Algorithms↗