Revista complutense de educación

Resumen basado en el de la publicaciónEl discurso es una herramienta clave para la comprensión y la mejora de la calidad educativa. En el artículo el autor ofrece un nuevo modelo psicopedagógico que permite analizar la potencia formativa del discurso a través de cinco dimensiones interdependientes: instructiva, afectiva, motivadora, social y ética. Se trata de favorecer la elaboración de un discurso coherente y armónico que estimule, a un tiempo, el desarrollo cognitivo-intelectual y socio-afectivo de los alumnos. A partir del original modelo ofrecido se establecen sendas tipologías del profesorado y del alumnado que sirven igualmente de referencia para la mejora de la calidad educativa.ES

Epidemiological trends in notified influenza cases in Australia’s Northern Territory, 2007-2016

Background: The Northern Territory (NT) of Australia has a mix of climates, sparsely distributed population and a large proportion of the populace are Indigenous Australians, and influenza is known to have a disproportionate impact upon this group. Understanding the epidemiology of influenza in this region would inform public health strategies. Objectives: To assess if there are consistent patterns in characteristics of influenza outbreaks in the NT. Methods: Laboratory confirmed influenza cases in the NT are notified to the NT Centre for Disease Control. We conducted analyses on notified cases from 2007-2016 to determine incidence rates (by age group, Indigenous status and area), seasonality of cases and spatial distribution of influenza types. Notified cases were linked to laboratory datasets to update information on influenza type or subtype. Results: The disparity in Indigenous and non-Indigenous notification rates varied by age group, with rate ratios for Indigenous versus non-Indigenous ranging from 1.58 (95% CI:1.39, 1.80) for ages 15-24 to 5.56 (95% CI: 4.71, 6.57) for ages 55-64. The disparity between Indigenous and non-Indigenous notification rates appeared higher in the Central Australia region. Indigenous versus non-Indigenous hospitalisation and mortality rate ratios were 6.51 (95% CI: 5.91, 7.18) and 5.46 (95% CI: 2.40, 12.71) respectively. Inter-seasonal peaks during February and March occurred in 2011, 2013 and 2014, and were due to influenza activity in the tropical north of the NT. Conclusions: Our results highlight the importance of influenza vaccination across all age groups for Indigenous Australians. An early vaccination campaign targeted against outbreaks in February-March would be best focused on the tropical north

Performance of deployable assay for detection of influenza A/H1N1 2009 according to specimen type and viral RNA extraction method.

<p>POCT  =  point of care test.</p

Deployable molecular microbiology laboratory.

<p>Deployable molecular biology equipment used during the exercise. The layout corresponds to the two modules; left table – static field hospital used for real time PCR assays, right table – field portable. Only the hand-held magnetic bead extraction device from the field portable module was used in an attempt to detect influenza A by PCR assay during the military exercise.</p

NoV outbreak settings in Australia and New Zealand between January 2013 and June 2014.

<p>NoV outbreak settings in Australia and New Zealand between January 2013 and June 2014.</p

A Multi-Site Study of Norovirus Molecular Epidemiology in Australia and New Zealand, 2013-2014

<div><p>Background</p><p>Norovirus (NoV) is the major cause of acute gastroenteritis across all age groups. In particular, variants of genogroup II, genotype 4 (GII.4) have been associated with epidemics globally, occurring approximately every three years. The pandemic GII.4 variant, Sydney 2012, was first reported in early 2012 and soon became the predominant circulating NoV strain globally. Despite its broad impact, both clinically and economically, our understanding of the fundamental diversity and mechanisms by which new NoV strains emerge remains limited. In this study, we describe the molecular epidemiological trends of NoV-associated acute gastroenteritis in Australia and New Zealand between January 2013 and June 2014.</p><p>Methodology</p><p>Overall, 647 NoV-positive clinical faecal samples from 409 outbreaks and 238 unlinked cases of acute gastroenteritis were examined by RT-PCR and sequencing. Phylogenetic analysis was then performed to identify NoV capsid genotypes and to establish the temporal dominance of circulating pandemic GII.4 variants. Recombinant viruses were also identified based on analysis of the ORF1/2 overlapping region.</p><p>Findings</p><p>Peaks in NoV activity were observed, however the timing of these epidemics varied between different regions. Overall, GII.4 NoVs were the dominant cause of both outbreaks and cases of NoV-associated acute gastroenteritis (63.1%, n = 408/647), with Sydney 2012 being the most common GII.4 variant identified (98.8%, n = 403/408). Of the 409 reported NoV outbreaks, aged-care facilities were the most common setting in both Western Australia (87%, n = 20/23) and New Zealand (58.1%, n = 200/344) while most of the NoV outbreaks were reported from hospitals (38%, n = 16/42) in New South Wales, Australia. An analysis of a subset of non-GII.4 viruses from all locations (125/239) showed the majority (56.8%, n = 71/125) were inter-genotype recombinants. These recombinants were surprisingly diverse and could be classified into 18 distinct recombinant types, with GII.P16/GII.13 (24% of recombinants) the most common.</p><p>Conclusion</p><p>This study revealed that following its emergence in 2012, GII.4 Sydney 2012 variant continued to be the predominant cause of NoV-associated acute gastroenteritis in Australia and New Zealand between 2013 and 2014.</p></div

Summary of NoV genotypes identified in Australia and New Zealand during 2013–2014.

<p>Summary of NoV genotypes identified in Australia and New Zealand during 2013–2014.</p

NoV wildtypes (non-GII.4) and intergenotypic recombinants identified in this study.

<p>NoV wildtypes (non-GII.4) and intergenotypic recombinants identified in this study.</p

Phylogenetic analysis of NoV GII partial capsid nucleotide (nt) sequences from Australia and New Zealand.

<p>Neighbour-Joining phylogeny of sequences of the 5’ end of ORF2 was generated. NoV GII sequences (266-bp, nt position 5101–5366 with reference to Lordsdale virus, GenBank accession number X86557) are shown. Global NoV reference sequences (n = 78) genotype were obtained from GenBank and are labelled with the GenBank accession number in black. The detailed reference strain information and collection year are tabulated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0145254#pone.0145254.s004" target="_blank">S1 Table</a>. Representative NoV sequences used for the phylogenetic analysis (n = 156) are labelled with red (New Zealand), blue (NSW Australia) and green (WA Australia), in the format of: Sample ID/Collection month and year/Country. Each NoV-associated outbreak is indicated with a black solid circle. The phylogeny was generated using programs within MEGA 5, with bootstrap values of ≥75 indicated as a percentage of 1000 replicates. The distance scale represents the number of nucleotide substitutions per site. AU—Australia; NZ—New Zealand.</p

Monthly proportion of NoV genotypes identified in Australia and New Zealand between January 2013 and June 2014.

<p>The prevalence of NoV capsid genotypes and specific GII.4 variants within the 634 NoV-positive samples were compared for NSW and WA, Australia (panel A and B, respectively) and New Zealand (panel C). Samples with unknown GI or GII capsid genotypes as well as mixed GI and GII infection are excluded in this analysis (n = 13). The percentage of each NoV capsid genotype (Y-axis) is plotted by month (X-axis). Different genotypes and GII.4 variants are labelled according to the legends provided and plotted from the top down with increasing prevalence so the most predominant genotype is at the base of the graph.</p