Though intensive genetic selection has led to extraordinary advances in growth rate and feed efficiency in production of meat-type chickens, endocrine processes controlling these traits are still poorly understood. The anterior pituitary gland is a central component of the neuroendocrine system and plays a key role in regulating important physiological processes that directly impact broiler production efficiency, though how differences in pituitary gland function contribute to various growth and body composition phenotypes is not fully understood. Global anterior pituitary gene expression was evaluated on post-hatch weeks 1, 3, 5, and 7 in male broiler chickens selected for high (HG) or low (LG) growth. Differentially expressed genes (DEGs) were analyzed with gene ontology categorization, self-organizing maps, gene interaction network determination, and upstream regulator identification to uncover novel pituitary genes and pathways contributing to differences in growth and body composition. A total of 263 genes were differentially expressed between HG and LG anterior pituitary glands (P ≤ 0.05 for genetic line-by-age interaction or main effect of line; ≥1.6-fold difference between lines), including genes encoding four anterior pituitary hormones. Genes involved in signal transduction, transcriptional regulation, and vesicle-mediated transport were differentially expressed and are predicted to influence expression and secretion of pituitary hormones. DEGs involved in immune regulation provide evidence that inflammation and response to cellular stressors may compromise pituitary function in LG birds, affecting their ability to adequately produce pituitary hormones. Many DEGs were also predicted to function in processes that regulate organ morphology and angiogenesis, suggesting pituitary gland structure differs between the divergently selected lines. The large number of DEGs within the anterior pituitary gland of birds selected for high or low body weight highlights the importance of this gland in regulating economically important traits such as growth and body composition in broiler chickens. Intracellular signaling, transcriptional regulation, and membrane trafficking are important cellular processes contributing to proper hormone production and secretion. The data also suggest that pituitary function is intimately tied to structure, and organization of the gland could influence hypothalamic and systemic metabolic inputs and delivery of hormones regulating growth and metabolism into peripheral circulation.

In the teachers’ training schools of Reunion Island and Mayotte, we have been training primary pre-service teachers in programming for the past three years. Most trainees have not learned programming before during their school and university curriculum. As a result, this subject is new to them and they find themselves in the situation of their own pupils. This is why we asked them, during their learning, to produce a “feelings” notebook in which they explain their successes, their failures and what it brings to them for understanding their own pupils. We held two types of studies of these documents: quantitative and qualitative. The analysis shows that if on the whole, the group of trainees have globally identified the key aspects of a learning situation, it is not the case for each trainee.

The Reunion Island teachers training school has decided to set up an ePortfolio platform to validate the “C2i2e” certificate for trainees. This certificate confirms their competencies in technology enhanced learning and digital education. Trainers and trainees of the school have been using this platform for the past three years. Here, we study their activities to understand the real use of the platform that has been done. To analyze their behavior, we look at the traces they left on the platform. These traces show that, while all trainees go on the platform to get the certificate very few of them do it for their own goals and when they do it, it is usually for sharing documents. For their part, only a few trainers of the school work with the platform. When they do it, it is to make documents available to their trainees or to collect their students’ work.

Learning Analytics (LA) can be data driven: the process is oriented essentially by data and not according to a theoretical background. In this case, results can be, sometimes, not exploitable. This is the reason why some LA processes are theory driven: based on A Priori Knowledge (APK), on a theoretical background. Here, we investigate the relationship between APK and LA. We propose a “2-level framework” that considers LA as a level 2 learning process and includes five components: stakeholders, goals, data, technical approaches and feedbacks. Based on this framework, a sample of LA related works is analyzed to exhibit how such works relate LA with APK. We show that most of the time the APK used for LA is the learning theory sustaining the student’s learning. However, it can be otherwise and, according to the goal of LA, it is sometimes fruitful to use another theory.

Decades of intensive genetic selection in the domestic chicken (Gallus gallus domesticus) have enabled the remarkable rapid growth of today’s broiler (meat-type) chickens. However, this enhanced growth rate was accompanied by several unfavorable traits (i.e., increased visceral fatness, leg weakness, and disorders of metabolism and reproduction). The present descriptive analysis of the abdominal fat transcriptome aimed to identify functional genes and biological pathways that likely contribute to an extreme difference in visceral fatness of divergently selected broiler chickens.

As pointed out by previous reviews, the endocrine pancreas of the chicken (and of birds in general) displays several peculiarities by comparison with the feature observed in mammals (these basics are summarized in the introduction). This chapter, mostly focused on glucagon and insulin, summarizes current knowledge about the structure-activity of these hormones and the components or steps through which they exert their control: secretion, receptors, signaling, control of gene expressions and major biological effects. During evolution, birds developed several specific features more particularly for glucagon gene expression, insulin gene structure, insulin secretion, insulin receptor signaling in muscle and adipose tissues. Insulin is required to sustain an active anabolism during fed status. Fat chickens exhibit low glycemia (in contrast to hyperglycemia as found in obese mammals) and changes in their plasma glucose-insulin relationship. Many steps involved in insulin action still appear either unknown or missing in chickens and birds in general. Future progress in the field should permit further improvements in poultry production. This review also further supports the large interest of chicken as an experimental model for comparative endocrinology and physiology, mostly in the field of diabetes and obesity.

In mammals, insulin-sensitive GLUTs, including GLUT4, are recruited to the plasma membrane of adipose and muscle tissues in response to insulin. The GLUT4 gene is absent from the chicken genome, and no functional insulin-sensitive GLUTs have been characterized in chicken tissues to date. A nucleotide sequence is predicted to encode a chicken GLUT12 ortholog and, interestingly, GLUT12 has been described to act as an insulin-sensitive GLUT in mammals. It encodes a 596 amino acid protein exhibiting 71% identity with human GLUT12. First, we present the results of a phylogenetic study showing the stability of this gene during evolution of vertebrates. Second, tissue distribution of chicken SLC2A12 mRNA was characterized by RT-PCR. It was predominantly expressed in skeletal muscle and heart. Protein distribution was analysed by Western blotting using an anti-human GLUT12 antibody directed against a highly conserved region (87% of identity). An immuno-reactive band of the expected size (75kDa) was detected in the same tissues. Third a physiological characterization was performed: SLC2A12 mRNA levels were significantly lowered in fed chickens subjected to insulin immuno-neutralization. Finally, recruitment of immuno-reactive GLUT12 to the muscle plasma membrane was increased following 1h of intraperitoneal insulin administration (compared to a control fasted state). Thus insulin administration elicited membrane GLUT12 recruitment. In conclusion, these results suggest that the facilitative glucose transporter protein GLUT12 could act in chicken muscle as an insulin-sensitive transporter that is qualitatively similar to GLUT4 in mammals.

Genetic selection for enhanced growth rate in meat-type chickens (Gallus domesticus) is usually accompanied by excessive adiposity, which has negative impacts on both feed efficiency and carcass quality. Enhanced visceral fatness and several unique features of avian metabolism (i.e., fasting hyperglycemia and insulin insensitivity) mimic overt symptoms of obesity and related metabolic disorders in humans. Elucidation of the genetic and endocrine factors that contribute to excessive visceral fatness in chickens could also advance our understanding of human metabolic diseases. Here, RNA sequencing was used to examine differential gene expression in abdominal fat of genetically fat and lean chickens, which exhibit a 2.8-fold divergence in visceral fatness at 7 wk. Ingenuity Pathway Analysis revealed that many of 1687 differentially expressed genes are associated with hemostasis, endocrine function and metabolic syndrome in mammals. Among the highest expressed genes in abdominal fat, across both genotypes, were 25 differentially expressed genes associated with de novo synthesis and metabolism of lipids. Over-expression of numerous adipogenic and lipogenic genes in the FL chickens suggests that in situ lipogenesis in chickens could make a more substantial contribution to expansion of visceral fat mass than previously recognized. Distinguishing features of the abdominal fat transcriptome in lean chickens were high abundance of multiple hemostatic and vasoactive factors, transporters, and ectopic expression of several hormones/receptors, which could control local vasomotor tone and proteolytic processing of adipokines, hemostatic factors and novel endocrine factors. Over-expression of several thrombogenic genes in abdominal fat of lean chickens is quite opposite to the pro-thrombotic state found in obese humans. Clearly, divergent genetic selection for an extreme (2.5-2.8-fold) difference in visceral fatness provokes a number of novel regulatory responses that govern growth and metabolism of visceral fat in this unique avian model of juvenile-onset obesity and glucose-insulin imbalance.

We study the traces left by various groups of students on a CSCW platform at Reunion Island University. By observing the functionalities used and the size of the groups we note that, most of the time, the platform is not used for collaborative work. Furthermore, according to the academic programs, use can be very different from one program to the other. At the time the MOOCs are developing, those results could pose problem.

This descriptive study of the abdominal fat transcriptome takes advantage of two experimental lines of meat-type chickens (Gallus domesticus), which were selected over seven generations for a large difference in abdominal (visceral) fatness. At the age of selection (9 wk), the fat line (FL) and lean line (LL) chickens exhibit a 2.5-fold difference in abdominal fat weight, while their feed intake and body weight are similar. These unique avian models were originally created to unravel genetic and endocrine regulation of adiposity and lipogenesis in meat-type chickens. The Del-Mar 14K Chicken Integrated Systems microarray was used for a time-course analysis of gene expression in abdominal fat of FL and LL chickens during juvenile development (1–11 weeks of age).

Background: For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F-2 intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome.Results: Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.Conclusions: The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.

Facilitated transport of glucose into cells is mediated by a family of facilitative-diffusion glucose transporter (GLUT) proteins. In mammals, mostly in adipose and muscle tissues, some GLUTs, called ‘insulin-sensitive GLUTs’, are recruited at the plasma membrane in response to insulin. Facilitative-diffusion glucose transporter-4 is the best characterized (Bryant et al., 2002). So far, no functional ‘insulin-sensitive GLUTs’ has been characterized in chicken tissues. This species exhibits some peculiarities for glucose metabolism: a high glycaemia despite the presence of insulin circulating at ‘normal’ concentrations, and a low sensitivity to exogenous insulin, reminiscent of mammalian type-2 diabetes.

In this paper we propose one possible way to preprocess data according to Activity theory. Such an approach is particularly interesting in Educational Data Mining.

BACKGROUND:Domestic broiler chickens rapidly accumulate adipose tissue due to intensive genetic selection for rapid growth and are naturally hyperglycemic and insulin resistant, making them an attractive addition to the suite of rodent models used for studies of obesity and type 2 diabetes in humans. Furthermore, chicken adipose tissue is considered as poorly sensitive to insulin and lipolysis is under glucagon control. Excessive fat accumulation is also an economic and environmental concern for the broiler industry due to the loss of feed efficiency and excessive nitrogen wasting, as well as a negative trait for consumers who are increasingly conscious of dietary fat intake. Understanding the control of avian adipose tissue metabolism would both enhance the utility of chicken as a model organism for human obesity and insulin resistance and highlight new approaches to reduce fat deposition in commercial chickens.RESULTS:We combined transcriptomics and metabolomics to characterize the response of chicken adipose tissue to two energy manipulations, fasting and insulin deprivation in the fed state. Sixteen to 17 day-old commercial broiler chickens (ISA915) were fed ad libitum, fasted for five hours, or fed but deprived of insulin by injections of anti-insulin serum. Pair-wise contrasts of expression data identified a total of 2016 genes that were differentially expressed after correction for multiple testing, with the vast majority of differences due to fasting (1780 genes). Gene Ontology and KEGG pathway analyses indicated that a short term fast impacted expression of genes in a broad selection of pathways related to metabolism, signaling and adipogenesis. The effects of insulin neutralization largely overlapped with the response to fasting, but with more modest effects on adipose tissue metabolism. Tissue metabolomics indicated unique effects of insulin on amino acid metabolism.CONCLUSIONS:Collectively, these data provide a foundation for further study into the molecular basis for adipose expansion in commercial poultry and identify potential pathways through which fat accretion may be attenuated in the future through genetic selection or management practices. They also highlight chicken as a useful model organism in which to study the dynamic relationship between food intake, metabolism, and adipose tissue biology.

The role of insulin in chicken adipose tissue appears weak or questionable. In a first study, proximal and distal components of the insulin signaling cascade were characterized in abdominal adipose tissue of fasted or fed chickens for the first time. Similar measurements were performed on epididymal adipose tissue from fasted or fed rats for comparison. Tyrosine phosphorylation of IR beta subunit, IRS-1 and Shc and phosphorylation of downstream components (Akt and MAPK ERK1/2) were significantly reduced as expected by fasting in rat, but not in chicken. Phosphorylation of MAPK P38 was increased by fasting in chicken but not in rat. Phosphorylation of AMPK was not affected in the conditions investigated in either species. Whatever the nutritional state, the protein levels of IR and IRS-1 were lower in chicken than in rat, whereas those of Shc, Akt, AMPK, MAPK ERK2 and MAPK P38 were similar in both species. In fed state, PI3K activity was higher in chicken than in rat. Insulin sensitivity of insulin cascade was further investigated in chicken adipose tissue following in vivo insulin neutralization for 1 or 5h in fed chickens. Insulin privation did not alter early insulin signaling steps (IRβ, IRS-1 and Shc) or downstream elements (Akt, P70S6K, S6 ribosomal protein, AMPK, MAPK ERK2 and MAPK P38). Finally, phosphorylation of the transcription factor Creb was increased by 2-fold by 5h fasting or 5h insulin privation, most likely in response to an increase in plasma glucagon levels. Thus, insulin signaling is markedly different in chicken abdominal adipose tissue from that operating in mammals making chicken an interesting model of insulin resistance or refractoriness.

Background The domestic chicken is an attractive, but underutilized, animal model for studies of adipose tissue biology, metabolism and obesity: 1.) like humans, chickens rely on liver rather than adipose tissue for the majority of de novo lipogenesis; 2.) quantitative trait loci (QTLs) linked to fatness in chickens contain genes implicated in human susceptibility to obesity and diabetes; 3.) chickens are naturally hyperglycemic and insulin resistant; and 4.) a broad selection of genetic models exhibiting a range of fatness are available. To date, however, little is known about regulation of adipose metabolism in this model organism.

Chickens mimic an insulin-resistance state by exhibiting several peculiarities with regard to plasma glucose level and its control by insulin. To gain insight into the role of insulin in the control of chicken transcriptome, liver and leg muscle transcriptomes were compared in fed controls and “diabetic” chickens, at 5 h after insulin immuno-neutralization, using 20.7K-chicken oligo-microarrays. At a level of false discovery rate <0.01, 1,573 and 1,225 signals were significantly modified by insulin privation in liver and muscle, respectively. Microarray data agreed reasonably well with qRT-PCR and some protein level measurements. Differentially expressed mRNAs with human ID were classified using Biorag analysis and Ingenuity Pathway Analysis. Multiple metabolic pathways, structural proteins, transporters and proteins of intracellular trafficking, major signaling pathways, and elements of the transcriptional control machinery were largely represented in both tissues. At least 42 mRNAs have already been associated with diabetes, insulin resistance, obesity, energy expenditure, or identified as sensors of metabolism in mice or humans. The contribution of the pathways presently identified to chicken physiology (particularly those not yet related to insulin) needs to be evaluated in future studies. Other challenges include the characterization of “unknown” mRNAs and the identification of the steps or networks, which disturbed tissue transcriptome so extensively, quickly after the turning off of the insulin signal. In conclusion, pleiotropic effects of insulin in chickens are further evidenced; major pathways controlled by insulin in mammals have been conserved despite the presence of unique features of insulin signaling in chicken muscle.

: The purpose of this paper is to show that data mining tools can help refine the understanding of what happens on a platform of collaborative work. For this, we compare a multimodal analysis of traces with an analysis of these same traces performed by data mining tools. The second analysis confirms the results of the first one on some points but also gives more information and reveals some “dysfunctions” in the use of the platform. So, it seems interesting to use such tools to allow a formative evaluation of the training devices

The purpose of this study was to characterize the adipose transcriptome in experimental chickens divergently selected over many generations for a 3- to 4-fold difference in abdominal fatness at the same body weight and feed intake. Our time-course transcriptional analysis of abdominal fat in juvenile fat (FL) and lean (LL) chickens revealed 354 differentially expressed (DE) genes as a main effect of genotype and 254 DE genes in the genotype by age interaction. The LL chickens showed higher expression of a large number of genes involved in hemostasis (F2, F9, FGA, PLG, A2M, PROC, CFB, SERPINA4, SERPIND1 and SERPINE1), retinol metabolism/action (BCMO1, RARRES2, RBP4, RBP7, RDH1, NOL7), thyroid hormone metabolism (DIO1 and DIO3) and angiogenesis (ANG and ANPTL3). Several genes involved in lipogenesis were expressed at higher levels in FL adipose tissue after 5 weeks of age [THRSPA, TAS1R1, SCD1, PPARG, and IKBA and visfatin (NAMPT)]. Apparently, genetically fat chickens exhibit many of the same co-morbidities as obese humans (i.e., insulin resistance, diabetes and cardiovascular disease), presumably caused by dysregulation of endocrine/adipokine signaling and energy expenditure across multiple tissues. This work was supported the USDA-IFAFS Animal Genome Program (Grant 00-52100-9614).