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La pandemia del Covid-19 resultó ser un hecho sustancial en los cambios y las adaptaciones ejercidas en este sistema dentro de las instituciones educativas. En ese sentido, el presente estudio aborda la cultura escolar en las instituciones educativas públicas durante ese contexto inusual y tiene por objetivo analizar dicha cultura a partir de las percepciones del personal directivo y docente durante la pandemia del Covid-19. La recogida de información se realizó a través de la aplicación de entrevistas semiestructuradas a cinco directores y nueve docentes de cinco escuelas ubicadas en cuatro regiones distintas del Perú. A partir del análisis, se concluye que, en las instituciones educativas públicas, hubo cambios en la organización y el desarrollo de los rituales propios de su identidad. Asimismo, se evidenciaron mitos y metáforas relacionados con la educación a distancia que evidencian ciertas fortalezas, debilidades y oportunidades de mejora que dejó la pandemia del Covid-19 en el contexto educativo.

La autenticación es crucial para la protección de los usuarios y sus datos. Debido a las debilidades que aparecen en las contraseñas alfanuméricas por la acción de los usuarios, se han desarrollado nuevos enfoques como son los basados en autenticación gráfica. Uno de estos sistemas es el Passpoints que se destaca por su seguridad y facilidad de uso. En este artículo se presenta una implementación propia de dicho sistema, resultado de un exhaustivo estudio del sistema en cuestión. Dicho estudio abordó tanto el funcionamiento como la seguridad del sistema Passpoints, identificando sus debilidades y explorando las propuestas existentes para mitigarlas. Para la implementación principal de este sistema, se llevaron a cabo otras implementaciones intermedias esenciales para su desarrollo completo. Para ello se realizó un análisis exhaustivo de los métodos de discretización disponibles con el fin de seleccionar el más efectivo y eficiente para su posterior traducción a código de programación, así como una investigación referente a la adaptación de este sistema a la variedad de resoluciones de pantalla y tamaños de imagen actuales, permitiendo la adaptación de esta implementación a cualquier tipo de dispositivo. Este proceso es fundamental para convertir el sistema en un producto real que pueda ser evaluado por usuarios reales en diferentes medios.

Abstract Background In integrative bioinformatic analyses, it is of great interest to stablish the equivalence between gene or (more in general) feature lists, up to a given level and in terms of their annotations in the Gene Ontology. The aim of this article is to present an equivalence test based on the proportion of GO terms which are declared as enriched in both lists simultaneously. Results On the basis of these data, the dissimilarity between gene lists is measured by means of the Sorensen–Dice index. We present two flavours of the same test: One of them based on the asymptotic normality of the test statistic and the other based on the bootstrap method. Conclusions The accuracy of these tests is studied by means of simulation and their possible interest is illustrated by using them over two real datasets: A collection of gene lists related to cancer and a collection of gene lists related to kidney rejection after transplantation.

El Licenciamiento Institucional es un procedimiento que busca asegurar que las instituciones educativas cumplan con las condiciones básicas de calidad, garantizando que la prestación del servicio educativo sea pertinente con las demandas formativas de la sociedad. Para ello, las instituciones educativas deben implementar diversos cambios en su organización, tanto a nivel curricular como en la forma de trabajo. En ese sentido, el presente trabajo de investigación busca analizar cómo se manifiesta la resistencia al cambio de los docentes de un Instituto de Educación Superior Pedagógico Privado de Lima frente al Proceso de Licenciamiento Institucional. Desde un enfoque cualitativo y utilizando la técnica de la entrevista semiestructurada se ha podido recabar información que permite afirmar, a manera de conclusión, que los actos de resistencia se dan de forma aislada y sutil, puesto que los cambios planteados son productos de una imposición normativa del Ministerio de Educación. Asimismo, se advierte que la resistencia está más relacionada a un aspecto actitudinal de desinterés o desmotivación de participar en los cambios propuestos, aduciendo las informantes un aumento de la carga laboral y un cambio significativo en la práctica docente. Final-mente, se ha podido determinar que para evitar o atenuar cualquier acto de resistencia de la plana docente, es necesario que la institución educativa adopte una estrategia de comunicación que permita que los docentes tomen conocimiento del proceso de licen-ciamiento, promoviendo su participación e involucramiento en la toma de decisiones.

Abstract Background Fatty acids play prominent roles in brain function as they participate in structural, metabolic and signaling processes. The homeostasis of fatty acids and related pathways is known to be impaired in cognitive decline and dementia, but the relationship between these metabolic disturbances and common risk factors, namely the ɛ4 allele of the apolipoprotein E (ApoE-ɛ4) gene and sex, remains elusive. Methods In order to investigate early alterations associated with cognitive decline in the fatty acid-related serum metabolome, we here applied targeted metabolomics analysis on a nested case-control study (N=368), part of a prospective population cohort on dementia. Results When considering the entire study population, circulating levels of free fatty acids, acyl-carnitines and pantothenic acid were found to be increased among those participants who had greater odds of cognitive decline over a 12-year follow-up. Interestingly, stratified analyses indicated that these metabolomic alterations were specific for ApoE-ɛ4 non-carriers and women. Conclusions Altogether, our results highlight that the regulation of fatty acids and related metabolic pathways during ageing and cognitive decline depends on complex inter-relationships between the ApoE-ε4 genotype and sex. A better understanding of the ApoE-ɛ4 and sex dependent modulation of metabolism is essential to elucidate the individual variability in the onset of cognitive decline, which would help develop personalized therapeutic approaches.

El presente estudio tiene como objetivo analizar las tendencias en la oferta formativa de las maestrías en educación en las especialidades de Gestión de la Educación y Currículo en el Perú. Para el estudio documental se revisaron las páginas web de 95 universidades licenciadas en el Perú, en las cuales se halló información sobre la oferta formativa de ambas especialidades en 36 universidades, encontrando 36 programas de Gestión de la Educación en 33 universidades y 3 universidades que ofertan la especialidad de Currículo. Para el análisis de información se utilizaron matrices documentales acordes a las siguientes categorías: ubicación geográfica, duración, plan de estudios, tipos de cursos (teóricos e investigación), entre otros. Entre los resultados más importantes tenemos que las universidades presentan parcialmente información sobre sus programas; solo existen tres programas de la especialidad de Currículo y 36 relacionados con Gestión de la Educación. Los programas son maestrías profesionales y esto se evidencia por la cantidad de cursos relacionados con la especialidad, aunque existe una incidencia en formar investigadores, además de que las habilidades blandas son parte de la formación de los expertos en ambas especialidades.

La Red de Posgrados en Educación en Latinoamérica (REDPEL) creada el 2020, reúne a 15 programas de posgrados (maestrías y doctorados) de las siguientes universidades de la región: Maestría en Educación, mención Gestión de la Educación y mención Currículo (Pontificia Universidad Católica del Perú), Magíster en Educación, mención Currículum y Comunidad Educativa (Universidad de Chile), Maestría en Educación y Maestría en Gestión Educativa

BackgroundDiet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits.ObjectivesThe aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010).DesignWe set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time.ResultsSeveral polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0).ConclusionWe have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits.Clinical Trail Registrationwww.ClinicalTrials.gov, Identifier: NCT03169088.

BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited.ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively.Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests.ConclusionsLaboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible.

Abstract Background Although a few comparison methods based on the biological meaning of gene lists have been developed, the goProfiles approach is one of the few that are being used for that purpose. It consists of projecting lists of genes into predefined levels of the Gene Ontology, in such a way that a multinomial model can be used for estimation and testing. Of particular interest is the fact that it may be used for proving equivalence (in the sense of “enough similarity”) between two lists, instead of proving differences between them, which seems conceptually better suited to the end goal of establishing similarity among gene lists. An equivalence method has been derived that uses a distance–based approach and the confidence interval inclusion principle. Equivalence is declared if the upper limit of a one-sided confidence interval for the distance between two profiles is below a pre-established equivalence limit. Results In this work, this method is extended to establish the equivalence of any number of gene lists. Additionally, an algorithm to obtain the smallest equivalence limit that would allow equivalence between two or more lists to be declared is presented. This algorithm is at the base of an iterative method of graphic visualization to represent the most to least equivalent gene lists. These methods deal adequately with the problem of adjusting for multiple testing. The applicability of these techniques is illustrated in two typical situations: (i) a collection of cancer-related gene lists, suggesting which of them are more reasonable to combine –as claimed by the authors– and (ii) a collection of pathogenesis–based transcript sets, showing which of these are more closely related. The methods developed are available in the goProfiles Bioconductor package. Conclusions The method provides a simple yet powerful and statistically well-grounded way to classify a set of genes or other feature lists by establishing their equivalence at a given equivalence threshold. The classification results can be viewed using standard visualization methods. This may be applied to a variety of problems, from deciding whether a series of datasets generating the lists can be combined to the simplification of groups of lists.

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.

GWAS, immune analyses and biomarker screenings have identified host factors associated with in vivo HIV-1 control. However, there is a gap in the knowledge about the mechanisms that regulate the expression of such host factors. Here, we aimed to assess DNA methylation impact on host genome in natural HIV-1 control. To this end, whole DNA methylome in 70 untreated HIV-1 infected individuals with either high (>50,000 HIV-1-RNA copies/ml, n = 29) or low (

Abstract Background Recent studies in experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis (MS), suggest an involvement of the histone methyltransferase enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) in important processes such as cell adhesion and migration. Methods Here, we aimed to expand these initial observations by investigating the role of EZH2 in MS. mRNA expression levels for EZH2 were measured by real-time PCR in peripheral blood mononuclear cells (PBMC) from 121 MS patients (62 untreated and 59 receiving treatment) and 24 healthy controls. Results EZH2 expression levels were decreased in PBMC from untreated patients compared to that from controls, and treatment significantly upregulated EZH2 expression. Expression of miR-124 was increased in MS patients compared to controls. Blood immunophenotyping revealed EZH2 expression mostly restricted to CD4+ and CD8+ T cells, and circulating EZH2+ CD4+ and CD8+ T cells were decreased in untreated MS patients compared to controls. CD8+ T cells expressing EZH2 exhibited a predominant central memory phenotype, whereas EZH2+ CD4+ T cells were of effector memory nature, and both T cell subsets produced TNF-α. EZH2+ T cells were enriched in the cerebrospinal fluid compartment compared to blood and were found in chronic active lesions from MS patients. EZH2 inhibition and microarray analysis in PBMC was associated with significant downregulation of key T cell adhesion molecules. Conclusion These findings suggest a role of EZH2 in the migration of T cells in MS patients. The observation of TNF-α expression by CD4+ and CD8+ T cells expressing EZH2 warrants additional studies to explore more in depth the pathogenic potential of EZH2+-positive cells in MS.

Abstract The epigenomic landscape of Parkinson's disease (PD) remains unknown. We performed a genomewide DNA methylation and a transcriptome studies in induced pluripotent stem cell (iPSC)‐derived dopaminergic neurons (DAn) generated by cell reprogramming of somatic skin cells from patients with monogenic LRRK2‐associated PD (L2PD) or sporadic PD (sPD), and healthy subjects. We observed extensive DNA methylation changes in PD DAn, and of RNA expression, which were common in L2PD and sPD. No significant methylation differences were present in parental skin cells, undifferentiated iPSCs nor iPSC‐derived neural cultures not‐enriched‐in‐DAn. These findings suggest the presence of molecular defects in PD somatic cells which manifest only upon differentiation into the DAn cells targeted in PD. The methylation profile from PD DAn, but not from controls, resembled that of neural cultures not‐enriched‐in‐DAn indicating a failure to fully acquire the epigenetic identity own to healthy DAn in PD. The PD‐associated hypermethylation was prominent in gene regulatory regions such as enhancers and was related to the RNA and/or protein downregulation of a network of transcription factors relevant to PD (FOXA1, NR3C1, HNF4A, and FOSL2). Using a patient‐specific iPSC‐based DAn model, our study provides the first evidence that epigenetic deregulation is associated with monogenic and sporadic PD.

BACKGROUND: Selection of amino acid substitutions associated with resistance to nucleos(t)ide-analog (NA) therapy in the hepatitis B virus (HBV) reverse transcriptase (RT) and their combination in a single viral genome complicates treatment of chronic HBV infection and may affect the overlapping surface coding region. In this study, the variability of an overlapping polymerase-surface region, critical for NA resistance, is investigated before treatment and under antiviral therapy, with assessment of NA-resistant amino acid changes simultaneously occurring in the same genome (linkage analysis) and their influence on the surface coding region. METHODOLOGY/PRINCIPAL FINDINGS: Serum samples obtained from chronic HBV-infected patients at pre-treatment and during sequential NA treatment with lamivudine, adefovir, and entecavir were analyzed by ultra-deep pyrosequencing (UDPS) using the GS-FLX platform (454 Life Sciences-Roche). The pre-treatment HBV quasispecies was not enriched with NA-resistant substitutions. The frequencies of this type of substitutions at pre-treatment did not predict the frequencies observed during lamivudine treatment. On linkage analysis of the RT region studied, NA-resistant HBV variants (except for rtA181T) were present in combinations of amino acid substitutions that increased in complexity after viral breakthrough to entecavir, at which time the combined variant rtL180M-S202G-M204V-V207I predominated. In the overlapping surface region, NA-resistant substitutions caused selection of stop codons in a significant percentage of sequences both at pre-treatment and during sequential treatment; the rtA181T substitution, related to sW172stop, predominated during treatment with lamivudine and adefovir. A highly conserved RT residue (rtL155), even more conserved than the essential residues in the RT catalytic motif YMDD, was identified in all samples. CONCLUSIONS: UDPS methodology enabled quantification of HBV quasispecies variants, even those harboring complex combinations of amino acid changes. The high percentage of potentially defective genomes, especially in the surface region, suggests effective trans-complementation of these variants.