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.     

Murine Cytomegalovirus m02 Gene Family Protects against Natural Killer Cell-Mediated Immune Surveillance

The murine cytomegalovirus m02 gene family encodes putative type I membrane glycoproteins named m02 through m16. A subset of these genes were fused to an epitope tag and cloned into an expression vector. In transfected and murine cytomegalovirus-infected cells, m02, m04, m05, m06, m07, m09, m10, and m12 localized to cytoplasmic structures near the nucleus, whereas m08 and m13 localized to a filamentous structure surrounding the nucleus. Substitution mutants lacking the m02 gene (SMsubm02) or the entire m02 gene family (SMsubm02-16) grew like their wild-type parent in cultured cells. However, whereas SMsubm02 was as pathogenic as the wild-type virus, SMsubm02-16 was markedly less virulent. SMsubm02-16 produced less infectious virus in most organs compared to wild-type virus in BALB/c and C57BL/6J mice, but it replicated to wild-type levels in the organs of immunodeficient gamma(c)/Rag2 mice, lacking multiple cell types including natural killer cells, and in C57BL/6J mice depleted of natural killer cells. These results argue that one or more members of the m02 gene family antagonize natural killer cell-mediated immune surveillance.     

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.     

Plasma Biomarkers Discriminate Clinical Forms of Multiple Sclerosis

Multiple sclerosis, the most common cause of neurological disability in young population after trauma, represents a significant public health burden. Current challenges associated with management of multiple sclerosis (MS) patients stem from the lack of biomarkers that might enable stratification of the different clinical forms of MS and thus prompt treatment for those patients with progressive MS, for whom there is currently no therapy available. In the present work we analyzed a set of thirty different plasma cytokines, chemokines and growth factors present in circulation of 129 MS patients with different clinical forms (relapsing remitting, secondary progressive and primary progressive MS) and 53 healthy controls, across two independent cohorts. The set of plasma analytes was quantified with Luminex xMAP technology and their predictive power regarding clinical outcome was evaluated both individually using ROC curves and in combination using logistic regression analysis. Our results from two independent cohorts of MS patients demonstrate that the divergent clinical and histology-based MS forms are associated with distinct profiles of circulating plasma protein biomarkers, with distinct signatures being composed of chemokines and growth/angiogenic factors. With this work, we propose that an evaluation of a set of 4 circulating biomarkers (HGF, Eotaxin/CCL11, EGF and MIP-1β/CCL4) in MS patients might serve as an effective tool in the diagnosis and more personalized therapeutic targeting of MS patients.