| Literature DB >> 23131178 |
Julia Marchal1, Olène Dorieux, Laurine Haro, Fabienne Aujard, Martine Perret.
Abstract
BACKGROUND: Hematologic and biochemical data are needed to characterize the health status of animal populations over time to determine the habitat quality and captivity conditions. Blood components and the chemical entities that they transport change predominantly with sex and age. The aim of this study was to utilize blood chemistry monitoring to establish the reference levels in a small prosimian primate, the Grey Mouse Lemur (Microcebus murinus).Entities:
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Year: 2012 PMID: 23131178 PMCID: PMC3514280 DOI: 10.1186/1746-6148-8-211
Source DB: PubMed Journal: BMC Vet Res ISSN: 1746-6148 Impact factor: 2.741
Figure 1Means and SEM of mouse lemur body mass (g) was significantly different between (A) sexes (males and females) and (B) seasons (long-day season; short-day season). Statistical significance was considered when p<0.01 (**) and p<0.001 (***).
Blood biochemical markers during the short-day season
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Median, 25%-75% quartiles and range (minimum-maximum) of blood biochemical markers during the short-day season in male and female mouse lemurs.
Blood biochemical markers during the long-day season
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Median, 25%-75% quartiles and range (minimum-maximum) of blood biochemical markers during the long-day season in male and female mouse lemurs.
Figure 2Medians and the 25% and 75% quartiles of blood biochemical markers that were significantly different between seasons (long-day season; short-day season) in Grey Mouse Lemurs.
Figure 3Medians and 25% and 75% quartiles of blood biochemical markers that were significantly different between age groups (young animals: 1 to 3 years old; middle-aged animals: 4 to 5 years old; and old animals: 6 to 10 years old).
Relationship between blood biochemical parameters and body mass
| n=39, r=0.10 | |||
| n=39, r=0.14 | |||
| n=39, r=0.16 | |||
| n=39, r=0.16 |
Sample sizes for each photoperiod: long-day (LD) season and short-day (SD) season and the Pearson correlation coefficient r are given for each regression, as dependent and independent variables. Values were statistically significant if p<0.05 (*). A p<0.01 was indicated by two asterisks (**).
Figure 4Statistical analyses were performed utilizing a Pearson correlation. (A) Simple linear regression between blood urea nitrogen levels and age (n=77, r=0.46, p<0.001). (B) Simple linear regression between creatinine levels and age (n=75, r=0.28, p<0.01). (C) Simple linear regression between total blood globulin concentration and age (n=73, r=0.20, p<0.05), LD: long-day season; SD: short-day season.