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.     

A procedure for estimating the surface potential of charged or neutral membranes with 8-anilino-1-naphthalenesulphonate probe. Adequacy of the Gouy-Chapman model

Using the fluorescent anion 8-anilino-1-naphthalenesulphonate (ANS) for determining the membrane surface potential necessitates that the intrinsic affinity constant K_i for the ANS sites be known. Two methods are presented which do not rely on a determination of K_i at high ionic strength. They are respectively applied to neutral membranes (egg phosphatidylcholine liposomes) and highly charged natural ones (horse bean microsomes and liposomes from their phospholipids). The value of K_i appears to be insensitive to the level of occupancy of the sites, the KCl concentration and the pH in large ranges. Furthermore, the classical Gouy-Chapman model seems to describe correctly the whole set of data, provided apparent mean molecular areas larger than the published crystallographic ones are admitted.     

Partial purification of the maturation-promoting factor MPF from unfertilized eggs of Xenopus laevis

A 200-fold purification of the maturation-promoting factor or MPF from unfertilized eggs of Xenopus laevis is reported for the first time. Purification was achieved by three successive column chromatographies on hydroxyapatite, trisacryl blue and L-arginine-agarose. The presence of MPF was assessed by the usual maturation criteria after injections of test material into immature stage VI unstimulated X. laevis oocytes: the precocious appearance of the maturation spot (within 45-120 min), the germinal vesicle breakdown, the presence of the first polar body and the second metaphase spindle. Purification was monitored by the decrease of the minimal amount of protein injected in a constant volume (50 nl) required to induce 50% frequency of germinal vesicle breakdown. This amount decreased from 500 ng in the crude extract to 2.5 ng in the 200-fold purified material. Analysis by SDS-PAGE of the crude extract showed about 40 Coomassie-blue-stained polypeptides with molecular masses ranging from 300 kDa to 20 kDa, whereas in the 200-fold purified MPF only 5 stained polypeptides were revealed, with molecular masses of 62, 53, 49, 39 and 37 kDa. In vitro phosphorylations for the detection of kinase activities for endogenous and exogenous substrates were monitored by analysis of autoradiograms of SDS-PAGE, after treatment of fractions with [gamma-32P]ATP. Only inactive fractions eluted from columns ahead of MPF, and fractions containing MPF activity were tested. Phosphorylation of numerous stained polypeptides was demonstrated in the crude MPF extract and exogenous substrates such as phosvitin, casein and histone type II-AS were also strongly phosphorylated. In the MPF fraction, purified on hydroxyapatite, a polypeptide of 53 kDa was more highly and specifically phosphorylated and the presence of kinase activities was observed for the above three exogenous substrates. In the 100-fold and 200-fold purified MPF, phosphorylation of endogenous substrates could not be shown and kinase activities for the above three substrates were drastically decreased as compared with the crude and purified MPF obtained after hydroxyapatite column chromatography. However, neither endogenous phosphorylations nor kinase activities with the above exogenous substrates could be shown in inactive fractions eluted ahead of MPF at the different purification steps. Some characteristics of the purified material are also described in this paper.     

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.