Developmental Patterns of Catechol-O-Methyltransferase in Genetically Different Rat Strains: Enzymatic and Immunochemical Studies

Abstract: Catechol- O -methyltransferase (COMT) activity in the liver and kidneys of adult Fischer-344 (F-344) rats is only half of that in the same organs of Wistar-Furth (W-F) rats. The trait of low COMT activity in these animals is inherited in an autosomal recessive fashion. A comprehensive study of patterns of change in COMT activity during growth and development was performed to determine whether "temporal gene" effects might play a role in the inherited differences in enzyme activity present in adult animals. The COMT activity expressed per mg protein in liver and kidneys of newborn F-344 rats is only 50–60% of that in the same organs of W-F animals. The liver and the kidneys of newborn rats of both strains have COMT activity an order of magnitude higher than those in brain, heart, or blood. In addition, in both strains there are much larger increases in liver and kidney COMT activities during growth and development (5–10 fold) than in blood, brain, or heart (one- to twofold). Immunotitration with antibodies against rat COMT demonstrates that differences in immunoreactive COMT parallel differences in COMT activity, both between strains and within strains during growth and development. However, when the temporal patterns of change in enzyme activities in the liver and the kidneys of the two strains of rat are compared at multiple times during growth and development, no differences in the patterns are present. These results make it unlikely that temporal gene effects can explain the inherited differences in COMT activity in liver and kidneys of F-344 and W-F rats.     

Target cells infected by avian erythroblastosis virus differentiate and become transformed

Transformation in vitro of bone marrow cells by avian erythroblastosis virus (AEV) gives rise to rapidly growing cells of erythroid nature. Target cells of neoplastic transformation by AEV are recruited among the early progenitors of the erythroid lineage, the burst-forming units-erythroid (BFU-E). They express a brain-related antigen at a high level and an immature antigen at a low level. We show that AEV-transformed cells express low levels of the brain antigen and high levels of the immature antigen. Their response to specific factors regulating the erythroid differentiation indicates that they are very sensitive to erythropoietin. Furthermore, cells transformed by a temperature-sensitive mutant of AEV differentiate into hemoglobin-synthesizing cells 4 days after being shifted to the nonpermissive temperature. All these properties are similar to those of late progenitors of the erythroid lineage, the colony-forming units-erythroid (CFU-E). These results indicate that the AEV-transformed cells are blocked in their differentiation at the CFU-E stage.     

Grouped sequential exploitation of food patches in a flock feeder,the feral pigeon

Feral and laboratory flocks of rock doves ($\text{Columba}$$\text{livia}$) show a pattern of grouped sequential exploitation when simultaneously presented with two dispersed, depleting patches of seed. This behavior contrasts with the ideal free distribution pattern shown when patches are small and concentrated. Grouped sequential exploitation consists of two phases: all pigeons first land together and feed at one patch, then leave one by one for the other patch. Departure times of individuals for the second patch are correlated with feeding rate at patch 1, which is in turn correlated with position in the dominance hierarchy. The decision to switch from patch 1 to patch 2 improves individual feeding rates in all cases, but is done slightly later than it should according to optimal foraging theory.     

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.