Prepubertal male rats with high rates of germ-cell apoptosis present exacerbated rates of germ-cell apoptosis after serotonin depletion.

Male germ-cell apoptosis occurs naturally and can be increased by exposure to drugs and toxic chemicals. Individuals may have different rates of apoptosis and are likely to also exhibit differential sensitivity to outside influences. Previously, we reported that p-chloroamphetamine (pCA), a substance that inhibits serotonin synthesis, induced germ-cell apoptosis in prepubertal male rats. Here, we identified prepubertal rats with naturally high or low rates of germ-cell apoptosis and evaluated gene expression in both groups. Bax and Shbg mRNA levels were higher in rats with high rates of germ-cell apoptosis. Rats were then treated with pCA and the neuro-hormonal response and gene expression were evaluated. Treatment with pCA induced a reduction in serotonin concentrations but levels of sex hormones and gonadotrophins were not changed. Rats with initially high rates of germ-cell apoptosis had even higher rates of germ-cell apoptosis after treatment with pCA. In rats with high rates of germ-cell apoptosis Bax mRNA expression remained high after treatment with pCA. On the basis of category, an inverse relationship between mRNA expression of Bax and Bcl2, Bax and AR and Bax and Hsd3b2 was found. Here we provide evidence that innate levels of germ-cell apoptosis could be explained by the level of mRNA expression of genes involved with apoptosis and spermatogenesis.

Use of multivariate statistics to identify unreliable data obtained using CASA.

In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.