Didactique de la géographie et formation initiale des enseignants spécialistes : conception et première évaluation du nouveau dispositif de formation initiale des enseignants de géographie du Secondaire supérieur à la HEP Vaud

Geography as a school subject is specifically thought for and by the schools. The contents of the school subject, nowadays, do not reflect the concerns and the evolution of the discipline as such. Nevertheless, official curricula set school objectives that address issues affecting the world and people's lives. These issues are coherent with the ones addressed by geography as a social science, that is to say the study of how people and their environment interact and how societies are interconnected through space. On an every day basis, Geography as a school subject is most of the time reduced to accumulating knowledge outside any given context. This knowledge may even be partially untrue or old and the related activities focus on low cognitive tensions. These practices do not contribute to the learners' understanding of the world because it does not allow them to build a geographical competence, which they. will need as future citizens in order to make responsible choices when they are confronted to questions related to how the locations of human and physical features are influenced by each other and how they interact across space. The central part of the text relies on the ideas and the processes discussed in the publications, which constitute the published file; it is divided into two parts. The first part (chapter 4) presents a didactic approach, which gives meaningful insights into Geography as a school subject and shows a brief account of the theoretical background that supports it. This socio-constructivist approach relies on the main following features: a priming stage (élément déclencheur), which presents geographical knowledge as an issue to be explored, discussed or solved; the issue is given to learners;. the planning of the teaching-learning sequence in small units launched by the main issue in the priming stage ; the interconnections of geographical knowledge with integrative concepts ; the synthetic stage or reporting stage where final concepts and knowledge are put together in order to be learned. Such an approach allows learners to re-invest the knowledge they have built themselves. This knowledge is organised by geographical integrative concepts, which represent true thinking operative tools and with which key issues in the geographical thinking are associated. The second part of the text (chapter 5) displays the didactic principles that governed the conception of the new initial training course for the future upper secondary school teachers at the HEP Vaud. The ambition of this course is to prepare future teachers to plan and realize the teaching of geography that provides pupils with the tools to understand better how people and their environment interact and how societies are interconnected through space. One of the tools for the teachers is the conceptual framework, whose most salient interest is to be relevant at every stage of the preparation and planning of the teaching, including the necessary epistemological reflection that should always be present. The synthesis of the text starts with a short account of the first evaluation of the new course. Various reflections on the future concerns and issues, that the didactics and methodology of Geography will be confronted with, constitute the synthesis.

The region of mouse mammary tumor virus DNA containing the long terminal repeat includes a long coding sequence and signals for hormonally regulated transcription.

Starting from a biologically active recombinant DNA clone of exogenous unintegrated GR mouse mammary tumor virus, we have generated three subclones of PstI fragments of 1.45, 1.1, and 2.0 kb in the plasmid vector PBR322. The nucleotide sequence has been determined for the clone of 1.45 kb which includes almost the complete region of the long terminal repeat (LTR) plus an adjacent stretch of unique sequence DNA. A short region of the 2.0 kb clone, containing the beginning of the LTR, has also been sequenced. Starting with the A of an initiation codon outside the LTR, we detected an open reading frame of 960 nucleotides, potentially coding for a protein of 320 amino acids (36K). Two hundred nucleotides downstream from the termination codon, and approximately 25 nucleotides upstream from the presumptive initiation site of viral RNA synthesis, we found a promoter-like sequence. The sequence AGTAAA was detected approximately 15-20 nucleotides upstream from the 3' end of virion RNA and probably serves as a polyadenylation signal. The 1.45 kb PstI fragment has been transfected into Ltk- cells together with a plasmid containing the thymidine kinase gene of herpes simplex virus. The virus-specific RNA synthesis detected in a Tk+ cell clone was strongly stimulated by the addition of dexamethasone.

Usefulness of double locus sequence typing (DLST) for regional and international epidemiological surveillance of methicilin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of nosocomial infections worldwide. To differentiate reliably among S. aureus isolates, we recently developed double locus sequence typing (DLST) based on the analysis of partial sequences of clfB and spa genes. In the present study, we evaluated the usefulness of DLST for epidemiological investigations of MRSA by routinely typing 1242 strains isolated in Western Switzerland. Additionally, particular local and international collections were typed by pulsed field gel electrophoresis (PFGE) and DLST to check the compatibility of DLST with the results obtained by PFGE, and for international comparisons. Using DLST, we identified the major MRSA clones of Western Switzerland, and demonstrated the close relationship between local and international clones. The congruence of 88% between the major PFGE and DLST clones indicated that our results obtained by DLST were compatible with earlier results obtained by PFGE. DLST could thus easily be incorporated in a routine surveillance procedure. In addition, the unambiguous definition of DLST types makes this method more suitable than PFGE for long-term epidemiological surveillance. Finally, the comparison of the results obtained by DLST, multilocus sequence typing, PFGE, Staphylococcal cassette chromosome mec typing and the detection of Panton-Valentine leukocidin genes indicated that no typing scheme should be used on its own. It is only the combination of data from different methods that gives the best chance of describing precisely the epidemiology and phylogeny of MRSA.

Three-dimensional sequence stratigraphy and subtle stratigraphic traps associated with systems tracts: West Cameron region, offshore Louisiana, Gulf of Mexico

Three-dimensional sequence stratigraphy is a potent exploration and development tool for the discovery of subtle stratigraphic traps. Reservoir morphology, heterogeneity and subtle stratigraphic trapping mechanisms can be better understood through systematic horizontal identification of sedimentary facies of systems tracts provided by three-dimensional attribute maps used as an important complement to the sequential analysis on the two-dimensional seismic lines and the well log data. On new prospects as well as on already-producing fields, the additional input of sequential analysis on three-dimensional data enables the identification, location and precise delimitation of new potentially productive zones. The first part of this paper presents four typical horizontal seismic facies assigned to the successive systems tracts of a third- or fourth-order sequence deposited in inner to outer neritic conditions on a elastic shelf. The construction of this synthetic representative sequence is based on the observed reproducibility of the horizontal seismic facies response to cyclic eustatic events on more than 35 sequences registered in the Gulf coast Plio-Pleistocene and Late Miocene, offshore Louisiana in the West Cameron region of the Gulf of Mexico. The second part shows how three-dimensional sequence stratigraphy can contribute in localizing and understanding sedimentary facies associated with productive zones. A case study in the early Middle Miocene Cibicides opima sands shows multiple stacked gas accumulations in the top slope fan, prograding wedge and basal transgressive systems tract of the third-order sequence between SB15.5 and SB 13.8 Ma.

Bridging the Gap: establishing the necessary infrastructure and knowledge for teaching and research in neuroscience in Africa.

Advances in neuroscience research over the last few decades have increased our understanding of how individual neurons acquire their specific properties and assemble into complex circuits, and how these circuits are affected in disease. One of the important motives driving neuroscience research is the development of new scientific techniques and interdisciplinary cooperation. Compared to developed countries, many countries on the African continent are confronted with poor facilities, lack of funding or career development programs for neuroscientists, all of which deter young scientists from taking up neuroscience as a career choice. This article highlights some steps that are being taken to promote neuroscience education and research in Africa.

Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Plastinated Ethmoidal Region : II. The Preparation and Use of Radio-Opaque Artery Casts in Clinical Teaching.

In endoscopic sinus surgery, knowledge of the course of the internal ethmoida and orbital arteries is crucial.The maxillary and the internal carotid arteries of cadavers were injected with radio-opaque , red colorede silicone. The ethmoidal regions were perpared and plastinated using the standard S10 technique. On some specimens, the ophtalmic and ethmoidal arteries were dissected prior to plastination. The plastinated specimens of the ethmoidal blocks were successfullyintroduced into clinical teaching of sinus anatomy and surgery as an aid to study vaascularization an dits relationship to surgical procedures. Among the advantages of this method are the long-lasting preservation of dissected tissue, visualization of arteries during endoscopic and radiological examinations, and invaluable teachjing and training resources for endoscopic sinus surgery.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

Islands of euchromatin-like sequence and expressed polymorphic sequences within the short arm of human chromosome 21

The goals of the human genome project did not include sequencing of the heterochromatic regions. We describe here an initial sequence of 1.1 Mb of the short arm of human chromosome 21 (HSA21p), estimated to be 10% of 21p. This region contains extensive euchromatic-like sequence and includes on average one transcript every 100 kb. These transcripts show multiple inter- and intrachromosomal copies, and extensive copy number and sequence variability. The sequencing of the "heterochromatic" regions of the human genome is likely to reveal many additional functional elements and provide important evolutionary information.

A comparison of random sequence reads versus 16S rDNA sequences for estimating the biodiversity of a metagenomic library

The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10,010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.

Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

Prediction of enzyme function by combining sequence similarity and protein interactions

Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature

Background: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. Results: Our group has previously reported the development of OSIRIS, a system aimed at the retrieval of literature about allelic variants of genes http://ibi.imim.es/osirisform.html. Here we describe the development of a new version of OSIRIS (OSIRISv1.2, http://ibi.imim.es/OSIRISv1.2.html webcite) which incorporates a new entity recognition module and is built on top of a local mirror of the MEDLINE collection and HgenetInfoDB: a database that collects data on human gene sequence variations. The new entity recognition module is based on a pattern-based search algorithm for the identification of variation terms in the texts and their mapping to dbSNP identifiers. The performance of OSIRISv1.2 was evaluated on a manually annotated corpus, resulting in 99% precision, 82% recall, and an F-score of 0.89. As an example, the application of the system for collecting literature citations for the allelic variants of genes related to the diseases intracranial aneurysm and breast cancer is presented. Conclusion: OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and therefore is suitable for collecting current knowledge on gene sequence variations and supporting the functional annotation of variation databases. The application of OSIRISv1.2 in combination with controlled vocabularies like MeSH provides a way to identify associations of biomedical interest, such as those that relate SNPs with diseases.