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Abstract Background COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. Methods A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. Results The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p

META-R (multi-environment trial analysis in R) is a suite of R scripts linked by a graphical user interface (GUI) designed in Java language. The objective of META-R is to accurately analyze multi-environment plant breeding trials (METs) by fitting mixed and fixed linear models from experimental designs such as the randomized complete block design (RCBD) and the alpha-lattice/lattice designs. META-R simultaneously estimates the best linear and unbiased estimators (BLUEs) and the best linear and unbiased predictors (BLUPs). Additionally, it computes the variance-covariance parameters, as well as some statistical and genetic parameters such as the least significant difference (LSD) at 5% significance, the coefficient of variation in percentage (CV), the genetic variance, and the broad-sense heritability. These parameters are very important in the selection of top performing genotypes in plant breeding. META-R also computes the phenotypic and genetic correlations among environments and between traits, as well as their statistical significance. The genetic correlations between environments or traits can be visualized in a biplot graph or a tree diagram (dendrogram). Genetic correlations are very important for identifying environments with similar behavior or making indirect selection and identifying the most highly associated traits. META-R performs multi-environment analyses by using the residual maximum likelihood (REML) method; these analyses can be done by environment, across environments by grouping factors (stress conditions, nitrogen content, etc.) and across environments; the analyses across environments can be done with a pre-defined degree of heritability.

Genebanks hold comprehensive collections of wild species, wild relatives, and landraces that are useful for genetic improvement. Here, the authors report the genotype of nearly 80,000 wheat accessions using DArTseq technology to show the less explored genetic diversity.

“Sparse testing” refers to reduced multi-environment breeding trials in which not all genotypes of interest are grown in each environment. Using genomic-enabled prediction and a model embracing genotype × environment interaction (GE), the non-observed genotype-in-environment combinations can be predicted. Consequently, the overall costs can be reduced and the testing capacities can be increased. The accuracy of predicting the unobserved data depends on different factors including (1) how many genotypes overlap between environments, (2) in how many environments each genotype is grown, and (3) which prediction method is used. In this research, we studied the predictive ability obtained when using a fixed number of plots and different sparse testing designs. The considered designs included the extreme cases of (1) no overlap of genotypes between environments, and (2) complete overlap of the genotypes between environments. In the latter case, the prediction set fully consists of genotypes that have not been tested at all. Moreover, we gradually go from one extreme to the other considering (3) intermediates between the two previous cases with varying numbers of different or non-overlapping (NO)/overlapping (O) genotypes. The empirical study is built upon two different maize hybrid data sets consisting of different genotypes crossed to two different testers (T1 and T2) and each data set was analyzed separately. For each set, phenotypic records on yield from three different environments are available. Three different prediction models were implemented, two main effects models (M1 and M2), and a model (M3) including GE. The results showed that the genome-based model including GE (M3) captured more phenotypic variation than the models that did not include this component. Also, M3 provided higher prediction accuracy than models M1 and M2 for the different allocation scenarios. Reducing the size of the calibration sets decreased the prediction accuracy under all allocation designs with M3 being the less affected model; however, using the genome-enabled models (i.e., M2 and M3) the predictive ability is recovered when more genotypes are tested across environments. Our results indicate that a substantial part of the testing resources can be saved when using genome-based models including GE for optimizing sparse testing designs.

Personal assistance for people with intellectual disabilities can contribute to the application of the new paradigms of self-determination and social inclusion and to an improvement in the quality of life. Through a literature review and analysis with professional experts, experts from experience and potential users, a brief model of personal assistance was developed to be executed by community agents with professional supervision. The model considers activities in the usual spaces of people and their families, with support for the use of community formal and informal resources and the reinforcement of social support networks that continue operating once the intervention ends. With duration of 9 months, the model is developed through a 3-stage process: 1) engagement and formulation of an individualized plan, 2) implementation of the plan, and 3) participants’ learning reinforcement and transfer to support networks. The feasibility of the model in Latin American countries and the need for studies to evaluate its implementation are discussed.

Abstract Background Patisiran, an RNA interference therapeutic, has demonstrated robust reduction of wild-type and mutant transthyretin protein and was able to improve polyneuropathy and quality of life following 18 months of treatment in patients with hereditary transthyretin-mediated (hATTR) amyloidosis. In this 24-month Phase II open-label extension study, we evaluated the effects of patisiran treatment (0.3 mg/kg intravenously every 3 weeks) on safety, serum transthyretin levels, and clinical parameters. Efficacy assessments included modified Neuropathy Impairment Score +7 (mNIS+7) and multiple disease-relevant measures. Cardiac assessments were performed in a pre-specified cardiac subgroup. Results Twenty-seven patients entered this study, including 12 (44%) with ambulation difficulties due to their neuropathy and 11 (41%) who met criteria for the cardiac subgroup. During treatment, the majority of adverse events were mild/moderate in severity; there were no drug-related adverse events leading to treatment discontinuation. The most common drug-related adverse events were flushing and infusion-related reactions (22% each). Patisiran resulted in rapid, robust (~ 82%), and sustained reduction of mean transthyretin levels over 24 months. A mean 6.95-point decrease (improvement) in mNIS+7 from baseline was observed at 24 months. Patisiran’s impact on mNIS+7 was irrespective of concomitant tafamidis or diflunisal use, sex, or age. Clinical assessments of motor function, autonomic symptoms, disease stage, and quality of life remained stable over 24 months. No significant changes were observed for echocardiographic measures or cardiac biomarkers in the cardiac subgroup. Exploratory analyses demonstrated improvements in nerve-fiber density with corresponding reductions in amyloid burden observed in skin biopsies over 24 months. Conclusions Long-term treatment with patisiran had an acceptable safety profile and was associated with halting/improvement of polyneuropathy progression in patients with hATTR amyloidosis. Trial registration The study was registered at ClinicalTrials.gov (identifier: NCT01961921 ) on October 14, 2013.

Objetivos: El objetivo de este trabajo es determinar la proporción de ansiedad en estudiantes españoles de medicina durante la pandemia de COVID-19. Metodología: 31 estudiantes del grado de medicina de una universidad española contestaron un cuestionario on-line en abril del 2020. La escala GAD-7 se utilizó para evaluar sintomatología ansiosa autorreportada, y se utilizaron los puntos de corte para clasificarlos en ansiedad probable. Resultados: El 64,5% de la muestra presentó ansiedad, siendo más prevalente entre mujeres y los más jóvenes. Conclusiones: La prevalencia de ansiedad en la muestra analizada sugiere la necesidad de evaluar sintomatología ansiosa entre los estudiantes de medicina durante la pandemia de COVID-19 y establecer programas de apoyo psicológico adecuados. Estudios epidemiológicos futuros con muestras amplias y representativas se hacen necesarios para hacer un seguimiento de la salud mental de este colectivo.

Information transfer at synapses occurs when vesicles fuse with the plasma membrane to release neurotransmitters, which then bind to receptors at the postsynaptic membrane. The process of neurotransmitter release varies dramatically between different synapses, but little is known about how this heterogeneity emerges. The development of super-resolution microscopy has revealed that synaptic proteins are precisely organised within and between the two parts of the synapse and that this precise spatiotemporal organisation fine-tunes neurotransmission. However, it remains unclear if variability in release probability could be attributed to the nanoscale organisation of one or several proteins of the release machinery. To begin to address this question, we have developed a pipeline for correlative functional and super-resolution microscopy, taking advantage of recent technological advancements enabling multicolour imaging. Here we demonstrate the combination of live imaging of SypHy-RGECO, a unique dual reporter that simultaneously measures presynaptic calcium influx and neurotransmitter release, with post hoc immunolabelling and multicolour single molecule localisation microscopy, to investigate the structure-function relationship at individual presynaptic boutons.

Abstract Sparse testing in genome‐enabled prediction in plant breeding can be emulated throughout different line allocations where some lines are observed in all environments (overlap) and others are observed in only one environment (nonoverlap). We studied three general cases of the composition of the sparse testing allocation design for genome‐enabled prediction of wheat (Triticum aestivum L.) breeding: (a) completely nonoverlapping wheat lines in environments, (b) completely overlapping wheat lines in all environments, and (c) a proportion of nonoverlapping/overlapping wheat lines allocated in the environments. We also studied several cases in which the size of the testing population was systematically decreased. The study used three extensive wheat data sets (W1, W2, and W3). Three different genome‐enabled prediction models (M1–M3) were used to study the effect of the sparse testing in terms of the genomic prediction accuracy. Model M1 included only main effects of environments and lines; M2 included main effects of environments, lines, and genomic effects; whereas the remaining model (M3) also incorporated the genomic × environment interaction (GE). The results show that the GE component of the genome‐based model M3 captures a larger genetic variability than the main genomic effects term from models M1 and M2. In addition, model M3 provides higher prediction accuracy than models M1 and M2 for the same allocation designs (different combinations of nonoverlapping/overlapping lines in environments and training set sizes). Overlapped sets of 30–50 lines in all the environments provided stable genomic‐enabled prediction accuracy. Reducing the size of the testing populations under all allocation designs decreases the prediction accuracy, which recovers when more lines are tested in all environments. Model M3 offers the possibility of maintaining the prediction accuracy throughout both extreme situations of all nonoverlapping lines and all overlapping lines.

Prensa periódica, intelectuales y mundialización:"momentos globales" en la esfera pública de Buenos Aires (1870-1940).

Magalí Andrea Devés. Guillermo Facio Hebequer. Entre el campo artístico y la cultura de izquierdas, Buenos Aires, Prometeo, 2020, 306 páginas

Current climate change models predict an increased frequency and intensity of drought for much of the developing world within the next 30 years. These events will negatively affect maize yields, potentially leading to economic and social instability in many smallholder farming communities. Knowledge about the genetic resources available for traits related to drought tolerance has great importance in developing breeding program strategies. The aim of this research was to study a maize landrace introgression panel to identify chromosomal regions associated with a drought tolerance index. For that, we performed Genome-Wide Association Study (GWAS) on 1326 landrace progenies developed by the CIMMYT Genetic Resources Program, originating from 20 landraces populations collected in arid regions. Phenotypic data were obtained from early testcross trials conducted in three sites and two contrasting irrigation environments, full irrigation (well-watered) and reduced irrigation (drought). The populations were genotyped using the DArTSeq® platform, and a final set of 5,695 SNPs markers was used. The genotypic values were estimated using spatial adjustment in a two-stage analysis. First, we performed the individual analysis for each site/irrigation treatment combination. The best linear unbiased estimates (BLUEs) were used to calculate the Harmonic Mean of Relative Performance (HMRP) as a drought tolerance index for each testcross. The second stage was a joint analysis, which was performed using the HMRP to obtain the best linear unbiased predictions (BLUPs) of the index for each genotype. Then, GWAS was performed to determine the marker-index associations and the marker-Grain Yield (GY) associations for the two irrigation treatments. We detected two significant markers associated with the drought-tolerance index, four associated with GY in drought condition, and other four associated with GY in irrigated conditions each. Although each of these markers explained less than 0.1% of the phenotypic variation for the index and GY, we found two genes likely related to the plant response to drought stress. For these markers, alleles from landraces provide a slightly higher yield under drought conditions. Our results indicate that the positive diversity delivered by landraces are still present on the backcrosses and this is a potential breeding strategy for improving maize for drought tolerance and for trait introgression bringing new superior allelic diversity from landraces to breeding populations.

Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear unbiased predictor (GBLUP or GB) kernel, and the Gaussian kernel (GK). In general, these kernels have been used with two statistical models: single-environment and genomic × environment (GE) models. Recently near infrared spectroscopy (NIR) has been used as an inexpensive and non-destructive high-throughput phenotyping method for predicting unobserved line performance in plant breeding trials. In this study, we used a non-linear arc-cosine kernel (AK) that emulates deep learning artificial neural networks. We compared AK prediction accuracy with the prediction accuracy of GB and GK kernel methods in four genomic data sets, one of which also includes pedigree and NIR information. Results show that for all four data sets, AK and GK kernels achieved higher prediction accuracy than the linear GB kernel for the single-environment and GE multi-environment models. In addition, AK achieved similar or slightly higher prediction accuracy than the GK kernel. For all data sets, the GE model achieved higher prediction accuracy than the single-environment model. For the data set that includes pedigree, markers and NIR, results show that the NIR wavelength alone achieved lower prediction accuracy than the genomic information alone; however, the pedigree plus NIR information achieved only slightly lower prediction accuracy than the marker plus the NIR high-throughput data.

The dna is the fundamental basis of genetic information, just as bits are for computers. Whenever computers are used to represent genetic data, the computational encoding must be efficient to allow the representation of processes driving the inheritance and variability. This is especially important across simulations in view of the increasing complexity and dimensions brought by genomics. This paper introduces a new binary representation of genetic information. Algorithms as bitwise operations that mimic the inheritance of a wide range of polymorphisms are also presented. Different kinds and mixtures of polymorphisms are discussed and exemplified. Proposed algorithms and data structures were implemented in C++ programming language and is available to end users in the R package “isqg” which is available at the R repository (cran). Supplementary data are available online.

El presente artículo busca analizar las representaciones que el semanario socialista La Vanguardia elaboró sobre los diarios de mayor tirada de la ciudad de Buenos Aires en el cambio del siglo XIX al XX. En este período, los redactores del órgano central de prensa del Partido Socialista manifestaron una creciente ansiedad en torno al singular protagonismo social y político que adquirían diarios como La Prensa, La Nación y El Diario. En sus esfuerzos por dar inteligibilidad al fenómeno de la llamada “prensa burguesa”, La Vanguardia ofreció imágenes sobre el funcionamiento interno y sobre el perfil de sus periodistas y lectores, así como de sus formas de intervención política y sus representaciones sobre la sociedad argentina finisecular.

Resumen: La cirugía cardiovascular es la especialidad médica que se ocupa de la prevención, diagnóstico y tratamiento quirúrgico de los trastornos y enfermedades del sistema cardiocirculatorio. Los continuos y rápidos avances en el diagnóstico y tratamiento de las enfermedades cardiovasculares justifican la necesidad de llevar a cabo una actualización de los principales aspectos definitorios y organizativos de la especialidad, relacionados con la profesión (de la práctica, calidad asistencial), con el programa docente de la especialidad, la formación continuada de los cirujanos, los procesos de acreditación desde la Sociedad Española de Cirugía Torácica-Cardiovascular, entre otros.Este documento, elaborado por expertos de la cirugía cardiovascular, representa la opinión de la Sociedad Española de Cirugía Torácica-Cardiovascular y actualiza los principales aspectos de la especialidad en nuestro país. Abstract: Cardiovascular surgery is the medical specialty that deals with the prevention, diagnosis, and surgical treatment of disorders and diseases of the circulatory system. The continuous and rapid advances in the diagnosis and treatment of cardiovascular diseases justify the need to update the main, defining, and organisational aspects of the specialty, related to the profession (its practice, quality care), aspects on the teaching program of the specialty, the continuing education program of the surgeons, the processes of accreditation from the Spanish Society of Thoracic-Cardiovascular Surgery, etc.This document, prepared by experts in cardiovascular surgery, represents the opinion of the Spanish Society of Thoracic-Cardiovascular surgery and updates the main aspects of the specialty in our country. Palabras clave: Cirugía cardiovascular, Cirugía cardíaca, Cirugía torácica, Cirugía vascular, Recomendaciones, Keywords: Cardiovascular surgery, Cardiac surgery, Thoracic surgery, Vascular surgery, Recommendations

Genome–environment Associations (GEA) or Environmental Genome-Wide Association scans (EnvGWAS) have been poorly applied for studying the genomics of adaptive traits in bread wheat landraces (Triticum aestivum L.). We analyzed 990 landraces and seven climatic variables (mean temperature, maximum temperature, precipitation, precipitation seasonality, heat index of mean temperature, heat index of maximum temperature, and drought index) in GEA using the FarmCPU approach with GAPIT. Historical temperature and precipitation values were obtained as monthly averages from 1970 to 2000. Based on 26,064 high-quality SNP loci, landraces were classified into ten subpopulations exhibiting high genetic differentiation. The GEA identified 59 SNPs and nearly 89 protein-encoding genes involved in the response processes to abiotic stress. Genes related to biosynthesis and signaling are mainly mediated by auxins, abscisic acid (ABA), ethylene (ET), salicylic acid (SA), and jasmonates (JA), which are known to operate together in modulation responses to heat stress and drought in plants. In addition, we identified some proteins associated with the response and tolerance to stress by high temperatures, water deficit, and cell wall functions. The results provide candidate regions for selection aimed to improve drought and heat tolerance in bread wheat and provide insights into the genetic mechanisms involved in adaptation to extreme environments.

Smallholder farmers who grow maize landraces face important challenges to preserve their seed biodiversity from one season to another. This study was carried out in the central highlands of Mexico to compare the effectiveness of two seed storage practices—specifically, polypropylene woven bags (farmers’ conventional practice) vs. hermetic containers—for minimizing seed losses and maintaining germination. Four Mexican landraces were stored for three and six months. Data on moisture content and kernel damage were collected at the beginning and the end of the storage period. Pest-free samples collected were also analyzed for seed germination. Moisture content was below 13% overall and was not significantly affected by storage technology or storage time. Samples from the polypropylene woven bags suffered significant damage from Sitophilus zeamais and Prostephanus truncatus, with the percentages of insect damage and weight loss reaching 61.4% and 23.4%, respectively. Losses were minimal in seed stored in hermetic containers, with a maximum insect damage of 4.1% and weight loss of 2.2%. Overall, the germination rate of samples stored in these airtight containers was greater than 90%. This study provides additional evidence on the effectiveness of hermetic containers at maintaining Mexican landraces’ seed quantity and quality during storage in smallholder conditions in central Mexico.

Multimodal image integration (MMII) is a promising tool to help delineate the epileptogenic zone (EZ) in patients with medically intractable focal epilepsies undergoing presurgical evaluation. We report here the detailed methodology of MMII and an overview of the utility of MMII at the Cleveland Clinic Epilepsy Center from 2014 to 2018, exemplified by illustrative cases. The image integration was performed using the Curry platform (Compumedics Neuroscan™, Charlotte, NC, USA), including all available diagnostic modalities such as Magnetic resonance imaging (MRI), Positron Emission Tomography (PET), single-photon emission computed tomography (SPECT) and Magnetoencephalography (MEG), with additional capability of trajectory planning for intracranial EEG (ICEEG), particularly stereo-EEG (SEEG), as well as surgical resection planning. In the 5-year time span, 467 patients underwent MMII; of them, 98 patients (21%) had a history of prior neurosurgery and recurring seizures. Of the 467 patients, 425 patients underwent ICEEG implantation with further CT co-registration to identify the electrode locations. A total of 351 patients eventually underwent surgery after MMII, including 197 patients (56%) with non-lesional MRI and 223 patients (64%) with extra-temporal lobe epilepsy. Among 269 patients with 1-year post-operative follow up, 134 patients (50%) had remained completely seizure-free. The most common histopathological finding is focal cortical dysplasia. Our study illustrates the usefulness of MMII to enhance SEEG electrode trajectory planning, assist non-invasive/invasive data interpretation, plan resection strategy, and re-evaluate surgical failures. Information presented by MMII is essential to the understanding of the anatomo-functional-electro-clinical correlations in individual cases, which leads to the ultimate success of presurgical evaluation of patients with medically intractable focal epilepsies.

This manuscript presents findings from the first dichotomous data pooling analysis on clinical trials (CT) regarding the effectiveness of binding potassium. The results emanated from pairwise and network meta-analyses aiming evaluation of response to commercial potassium-binding polymers, that is, to achieve and maintain normal serum potassium (n = 1,722), and the association between this response and an optimal dosing of renin-angiotensin-aldosterone system inhibitors (RAASi) needing individuals affected by heart failure (HF) or resistant hypertension, who may be consuming other hyperkalemia-inducing drugs (HKID) (e.g., β-blockers, heparin, etc.), and frequently are affected by chronic kidney disease (CKD) (n = 1,044): According to the surface under the cumulative ranking area (SUCRA), sodium zirconium cyclosilicate (SZC) (SUCRA >0.78), patiromer (SUCRA >0.58) and sodium polystyrene sulfonate (SPS) (SUCRA 5.1 mEq/L), and, when normokalemia is achieved, patiromer 16.8–25.2 g/day (SUCRA = 0.94) and patiromer 8.4–16.8 g/day (SUCRA = 0.41) can allow to increase the dose of spironolactone up to 50 mg/day in subjects affected by heart failure (HF) or with resistant hypertension needing treatment with other RAASi. The potential of zirconium cyclosilicate should be explored further, as no data exists to assess properly its capacity to optimize dosing of RAASi, contrarily as it occurs with patiromer. More research is also necessary to discern between benefits of binding potassium among all type of hyperkalemic patients, for example, patients with DM who may need treatment for proteinuria, patients with early hypertension, etc.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020185614, CRD42020185558, CRD42020191430.

To enable a scalable sparse testing genomic selection (GS) strategy at preliminary yield trials in the CIMMYT maize breeding program, optimal approaches to incorporate genotype by environment interaction (GEI) in genomic prediction models are explored. Two cross-validation schemes were evaluated: CV1, predicting the genetic merit of new bi-parental populations that have been evaluated in some environments and not others, and CV2, predicting the genetic merit of half of a bi-parental population that has been phenotyped in some environments and not others using the coefficient of determination (CDmean) to determine optimized subsets of a full-sib family to be evaluated in each environment. We report similar prediction accuracies in CV1 and CV2, however, CV2 has an intuitive appeal in that all bi-parental populations have representation across environments, allowing efficient use of information across environments. It is also ideal for building robust historical data because all individuals of a full-sib family have phenotypic data, albeit in different environments. Results show that grouping of environments according to similar growing/management conditions improved prediction accuracy and reduced computational requirements, providing a scalable, parsimonious approach to multi-environmental trials and GS in early testing stages. We further demonstrate that complementing the full-sib calibration set with optimized historical data results in improved prediction accuracy for the cross-validation schemes.

In maize, doubled haploid (DH) line production capacity of large-sized maize breeding programs often exceeds the capacity to phenotypically evaluate the complete set of testcross candidates in multi-location trials. The ability to partially select DH lines based on genotypic data while maintaining or improving genetic gains for key traits using phenotypic selection can result in significant resource savings. The present study aimed to evaluate genomic selection (GS) prediction scenarios for grain yield and agronomic traits of one of the tropical maize breeding pipelines of CIMMYT in eastern Africa, based on multi-year empirical data for designing a GS-based strategy at the early stages of the pipeline. We used field data from 3,068 tropical maize DH lines genotyped using rAmpSeq markers and evaluated as test crosses in well-watered (WW) and water-stress (WS) environments in Kenya from 2017 to 2019. Three prediction schemes were compared: (1) 1 year of performance data to predict a second year; (2) 2 years of pooled data to predict performance in the third year, and (3) using individual or pooled data plus converting a certain proportion of individuals from the testing set (TST) to the training set (TRN) to predict the next year's data. Employing five-fold cross-validation, the mean prediction accuracies for grain yield (GY) varied from 0.19 to 0.29 under WW and 0.22 to 0.31 under WS, when the 1-year datasets were used training set to predict a second year's data as a testing set. The mean prediction accuracies increased to 0.32 under WW and 0.31 under WS when the 2-year datasets were used as a training set to predict the third-year data set. In a forward prediction scenario, good predictive abilities (0.53 to 0.71) were found when the training set consisted of the previous year's breeding data and converting 30% of the next year's data from the testing set to the training set. The prediction accuracy for anthesis date and plant height across WW and WS environments obtained using 1-year data and integrating 10, 30, 50, 70, and 90% of the TST set to TRN set was much higher than those trained in individual years. We demonstrate that by increasing the TRN set to include genotypic and phenotypic data from the previous year and combining only 10–30% of the lines from the year of testing, the predicting accuracy can be increased, which in turn could be used to replace the first stage of field-based screening partially, thus saving significant costs associated with the testcross formation and multi-location testcross evaluation.

El hábito de crecimiento de los trigos harineros (primavera e invierno) está determinado primordialmente por el proceso de vernalización, regulado por los genes Vrn. Algunos estudios sugieren la implicación de otros genes en la diferenciación de dicha característica. Por ello, se tiene por objetivo la identificación genómica de regiones con una posible relación funcional al hábito de crecimiento. Se realizó un estudio de asociación del genoma completo (GWAS) con dos enfoques de análisis: a) FarmCPU (Unificación de Probabilidad Circulante de Modelo fijo y aleatorio) y b) BLINK (Información Bayesiana y Desequilibrio de ligamiento Anidado Iterativamente) implementados en el paquete GAPIT de R. Se utilizaron datos de 25 681 loci de polimorfismo de un solo nucleótido (SNP’s) de 7 757 colectas de T. aestivum del banco de germoplasma del CIMMYT clasificadas en cuanto a su hábito de crecimiento. Se identificaron 593 marcadores SNP’s con una alta asociación al hábito de crecimiento (p < 0.01). Pero solo 70 marcadores formaban bloques de asociación (BA) en 11 cromosomas. Como se esperaba, se identificó un BA cercano al gen Vrn1 en el cromosoma 5A. Adicionalmente se identificaron 20 regiones genómicas (BA) con asociación al hábito de crecimiento, en las que se detectó la presencia de proteínas de respuesta al estrés implicadas en procesos de aclimatación y des-aclimatación. Los resultados sugieren la participación de nuevos genes en la determinación del hábito de crecimiento en Triticum aestivum y su potencial predictivo en colectas no clasificadas.

Perfusion patterns observed in Subtraction Ictal SPECT Co-registered to MRI (SISCOM) assist in focus localization and surgical planning for patients with medically intractable focal epilepsy. While the localizing value of SISCOM has been widely investigated, its relationship to the underlying electrophysiology has not been extensively studied and is therefore not well understood. In the present study, we set to investigate this relationship in a cohort of 70 consecutive patients who underwent ictal and interictal SPECT studies and subsequent stereo-electroencephalography (SEEG) monitoring for localization of the epileptogenic focus and surgical intervention. Seizures recorded during SEEG evaluation (SEEG seizures) were matched to semiologically-similar seizures during the preoperative ictal SPECT evaluation (SPECT seizures) by comparing the semiological changes in the course of each seizure. The spectral changes of the ictal SEEG with respect to interictal ones over 7 traditional frequency bands (0.1 to 150Hz) were analyzed at each SEEG site. Neurovascular (SEEG/SPECT) relations were assessed by comparing the estimated spectral power density changes of the SEEG at each site with the perfusion changes (SISCOM z-scores) estimated from the acquired SISCOM map at that site. Across patients, a significant correlation (p

El objetivo del presente dossier es reunir un conjunto de artículos originales sobre la historia de la prensa periódica en la Argentina. En un contexto de renovación a nivel global de estos estudios, se han venido desarrollando en los últimos años investigaciones que proponen nuevas perspectivas para analizar las inflexiones locales del ciclo histórico del periodismo escrito. Antes que un campo o sub campo especializado como en otras latitudes, nuestra historiografía ofrece en esta materia una gama muy heterogénea de trabajos que abordan momentos y objetos diferentes, y ponen en práctica herramientas metodológicas y diálogos disciplinares muy diversos. Una de las zonas que ha mostrado mayor dinamismo en los últimos tiempos es la que pone el foco en el papel social, político y cultural de los diarios porteños de fines del siglo XIX y principios del siglo XX. De la mano de estas investigaciones, el denominado proceso de modernización periodística producido en estas décadas –que hizo de los diarios de Buenos Aires los más dinámicos y pujantes del continente– ha comenzado a volverse inteligible a partir de ritmos y contornos propios, por fuera de los marcos de una clásica conceptualización organizada en torno a la rígida oposición entre una prensa política facciosa decimonónica y una prensa comercial y moderna propia del siglo XX. Siguiendo esta orientación, los trabajos que componen el dossier abordan en un registro monográfico aspectos nodales de este complejo proceso, tales como el flujo internacional de noticias, los procesos de profesionalización periodística, las dinámicas de ampliación y fragmentación de los públicos, las formas de intervención política de los grandes matutinos y el nuevo status de la prensa militante en la era de la industrialización periodística.

En este artículo analizamos la presencia de noticias policiales en La Protesta y La Vanguardia, principales periódicos del anarquismo y socialismo de la ciudad de Buenos Aires en la primera década del siglo XX. Dos hipótesis estructuran nuestro trabajo. La primera postula que La Protesta y La Vanguardia mostraron un alto grado de permeabilidad al proceso de modernización que atravesó el periodismo en este período. En tal sentido, nos detenemos en la incorporación de innovaciones estructurales y estilísticas que realizaron ambos periódicos, en un contexto de emergencia y expansión de un público lector de carácter masivo. La segunda hipótesis plantea que la inclusión de las noticias policiales en La Protesta y La Vanguardia no fue fijada, necesariamente, bajo parámetros doctrinarios y que respondió, en cambio, a una búsqueda por establecer un vínculo más directo y cotidiano con las inquietudes con las que la desordenada vida urbana de la Buenos Aires del novecientos amenazaba a sus lectores.

Inherited bone marrow failure syndromes (IBMFSs) are a group of congenital rare diseases characterized by bone marrow failure, congenital anomalies, high genetic heterogeneity, and predisposition to cancer. Appropriate treatment and cancer surveillance ideally depend on the identification of the mutated gene. A next-generation sequencing (NGS) panel of genes could be 1 initial genetic screening test to be carried out in a comprehensive study of IBMFSs, allowing molecular detection in affected patients. We designed 2 NGS panels of IBMFS genes: version 1 included 129 genes and version 2 involved 145 genes. The cohort included a total of 204 patients with suspected IBMFSs without molecular diagnosis. Capture-based targeted sequencing covered > 99% of the target regions of 145 genes, with more than 20 independent reads. No differences were seen between the 2 versions of the panel. The NGS tool allowed a total of 91 patients to be diagnosed, with an overall molecular diagnostic rate of 44%. Among the 167 patients with classified IBMFSs, 81 patients (48%) were diagnosed. Unclassified IBMFSs involved a total of 37 patients, of whom 9 patients (24%) were diagnosed. The preexisting diagnosis of 6 clinically classified patients (6%) was amended, implying a change of therapy for some of them. Our NGS IBMFS gene panel assay is a useful tool in the molecular diagnosis of IBMFSs and a reasonable option as the first tier genetic test in these disorders.

Aim of study: Commercially, chicken meat has a similar positioning to turkey meat, as both are healthy and low-fat meats. For this reason, we proposed analysing consumer behaviour with respect to each of these meats based on market segmentation. Area of study: Spain. Material and methods: We carried out a telephone survey with an error of ± 4.0% at a confidence level of 95.5%, using the food-related lifestyle (FRL) instrument as part of the questionnaire. The statistical analysis techniques employed were different depending on the objective pursued: univariate, bivariate and multivariate analysis. Main results: Five segments were obtained: “Manager cook” (24.5%), “Healthy cook” (20.8%), “Concerned with food, but not cooks” (22%), “Total detachment” (11.9%) and “Rational shopper with little interest in cuisine” (20.8%). Notwithstanding the similar positioning of chicken and turkey meats, there are significant differences in purchasing and consumption habits between FRL segments. Specifically, there were significant differences in the frequency of purchase, the usual shopping location, purchasing criteria and preparation methods. Research highlights: Knowing the profile of these segments allows us to adapt the marketing mix (product, place, price and promotion) to each one. This is very useful for the companies due to the wide demand they face. First, they can choose the FRL segments to target and, second, they can define an appropriate marketing strategy according to these segments. In this way, market segmentation strategy based on food-related lifestyles may ensure companies a greater likelihood of success in the market.

Background: Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome-Corona Virus 2 has generated significant impact on global health worldwide. COVID-19 can cause pneumonia and organ injury. Chronic kidney disease (CKD) has been associated with increased mortality in previous epidemics, but there is a paucity of data regarding actual risks for non-dialysis CKD patients with COVID-19.Methods: Multicenter, observational cohort study including 136 non-dialysis CKD patients and 136 age- and sex-matched controls that required hospitalization due to COVID-19. Patients with end-stage renal disease, a kidney transplant or without registered baseline glomerular filtration rate prior to COVID-19 infection were excluded. CKD and acute kidney injury (AKI) were defined according to KDIGO criteria.Results: CKD patients had higher white blood cell count and D-dimer and lower lymphocyte percentage. No differences were found regarding symptoms on admission. CKD was associated with higher rate of AKI (61 vs. 24.3%) and mortality (40.4 vs. 24.3%). Patients with AKI had the highest hazard for death (AKI/non-CKD HR:7.04, 95% CI:2.87–17.29; AKI/CKD HR:5.25, 95% CI: 2.29–12.02), followed by CKD subjects without AKI (HR:3.39, 95% CI:1.36–8.46). CKD status did not condition ICU admission or length of in-hospital stay.Conclusions: CKD patients that require hospitalization due to COVID-19 are exposed to higher risk of death and AKI.

Abstract Objective The anticonvulsant hypothesis posits that ECT’s mechanism of action is related to enhancement of endogenous anticonvulsant brain mechanisms. Results of prior studies investigating the role of the inhibitory neurotransmitter gamma‐aminobutyric acid (“GABA+”, GABA and coedited macromolecules) in the pathophysiology and treatment of depression remain inconclusive. The aim of our study was to investigate treatment‐responsive changes of GABA+ in subjects with a depressive episode receiving electroconvulsive therapy (ECT). Methods In total, 41 depressed subjects (DEP) and 35 healthy controls (HC) were recruited at two independent sites in Norway and the USA. MEGA‐PRESS was used for investigation of GABA+ in the anterior cingulate cortex. We assessed longitudinal and cross‐sectional differences between DEP and HC, as well as the relationship between GABA+ change and change in depression severity and number of ECTs. We also assessed longitudinal differences in cognitive performance and GABA+ levels. Results Depressive episode did not show a difference in GABA+ relative to HC (t71 = −0.36, p = .72) or in longitudinal analysis (t36 = 0.97, p = .34). Remitters and nonremitters did not show longitudinal (t36 = 1.12, p = .27) or cross‐sectional differences in GABA+. GABA+ levels were not related to changes in antidepressant response (t35 = 1.12, p = .27) or treatment number (t36 = 0.05, p = .96). An association between cognitive performance and GABA+ levels was found in DEP that completed cognitive effortful testing (t18 = 2.4, p = .03). Conclusion Our results failed to support GABA as a marker for depression and abnormal mood state and provide no support for the anticonvulsant hypothesis of ECT. ECT‐induced change in GABA concentrations may be related to change in cognitive function.

Pyrolysis techniques provide an interesting way of recycling plastic wastes (PW) by transforming them into liquid fuels with high calorific values. Catalysts are employed in PW pyrolysis in order to favor cracking reactions; in that regard, cheap and abundant natural resources are being investigated as potential catalyst precursors. This article explores the pyrolysis of low-density polyethylene (LDPE) in a semibatch reactor under a reduced pressure of 300 torr and temperatures in the range of 370 °C–430 °C. Three different solid materials, an activated carbon (AC1), a commercial Fluid cracking catalyst (FCC) and an aluminum- pillared clay (Al-PILC), were tested as catalysts for the pyrolysis process. Thermogravimetric analyzes were previously performed to select the most catalytically active materials. AC1 displayed very low catalytic activity while FCC and Al-PILC displayed high activity and conversion to liquid products. Hydrocarbons ranging from C5 to C28 were identified in the liquid products as well as significant changes in their composition when FCC and Al-PILC catalyst were used. Differences in the catalytic activity of the 3 solid materials are ascribed mainly to differences in their acid properties.

Defining mode of action is vital for both developing new drugs and predicting potential resistance mechanisms. Sensitivity of African trypanosomes to pentamidine and melarsoprol is predominantly mediated by aquaglyceroporin 2 (TbAQP2), a channel associated with water/glycerol transport. TbAQP2 is expressed at the flagellar pocket membrane and chimerisation with TbAQP3 renders parasites resistant to both drugs. Two models for how TbAQP2 mediates pentamidine sensitivity have emerged; that TbAQP2 mediates pentamidine translocation across the plasma membrane or via binding to TbAQP2, with subsequent endocytosis and presumably transport across the endosomal/lysosomal membrane, but as trafficking and regulation of TbAQPs is uncharacterised this remains unresolved. We demonstrate that TbAQP2 is organised as a high order complex, is ubiquitylated and is transported to the lysosome. Unexpectedly, mutation of potential ubiquitin conjugation sites, i.e. cytoplasmic-oriented lysine residues, reduced folding and tetramerization efficiency and triggered ER retention. Moreover, TbAQP2/TbAQP3 chimerisation, as observed in pentamidine-resistant parasites, also leads to impaired oligomerisation, mislocalisation and increased turnover. These data suggest that TbAQP2 stability is highly sensitive to mutation and that instability contributes towards the emergence of drug resistance.

Data Envelopment Analysis (DEA) is a relative measure of efficiency applied to a set of decision units and is being used more and more frequently in the supermarket sector. Nonetheless, given how strongly the sector’s financials depend on demand, companies need to combine this measurement with trade area information to best manage corporate efficiency. In this paper, the proposal consists of integrating DEA with a clearly articulated, structural typology so that supermarkets, based on their particular characteristics, can determine which variables are most critical for improving their efficiency. This methodology has been validated in the case of one of Spain’s five largest supermarket chains. A principal component analysis and a classification analysis were carried out on a series of internal management variables from 61 locations for which DEA had been used to calculate efficiency and to which multiple trade area variables were added using GIS. Some of them are related to the loyalty scheme membership programme. These latter variables described the implantation of the loyalty scheme member programme and were revealed as key elements for the efficiency of the supermarket. This methodology provides marketing profiles that are more adapted to local circumstances, thus allowing companies to set better internal benchmarking objectives.

Abstract Background Acute intermittent porphyria (AIP) is a low-penetrant genetic metabolic disease caused by a deficiency of hydroxymethylbilane synthase (HMBS) in the haem biosynthesis. Manifest AIP (MAIP) is considered when carriers develop typical acute neurovisceral attacks with elevation of porphyrin precursors, while the absence of attacks is referred to as latent AIP (LAIP). Attacks are often triggered by drugs, endocrine factors, fasting or stress. Although AIP penetrance is traditionally considered to be around 10–20%, it has been estimated to be below 1% in general population studies and a higher figure has been found in specific AIP populations. Genetic susceptibility factors underlying penetrance are still unknown. Drug-metabolizing cytochrome P450 enzymes (CYP) are polymorphic haem-dependent proteins which play a role in haem demand, so they might modulate the occurrence of AIP attacks. Our aim was to determine the prevalence and penetrance of AIP in our population and analyse the main hepatic CYP genes to assess their association with acute attacks. For this, CYP2C9*2, *3; CYP2C19*2; CYP2D6*4, *5; CYP3A4*1B and CYP3A5*3 defective alleles were genotyped in fifty AIP carriers from the Region of Murcia, a Spanish population with a high frequency of the HMBS founder mutation c.669_698del30. Results AIP penetrance was 52%, and prevalence was estimated as 17.7 cases/million inhabitants. The frequency of defective CYP2D6 alleles was 3.5 times higher in LAIP than in MAIP. MAIP was less frequent among CYP2D6*4 and *5 carriers (p

RESUMEN El seudohipoparatiroidismo 1b se caracteriza por resistencia aislada a la parathormona, en ausencia de las manifestaciones típicas de la osteodisfrofia hereditaria de Albright; debido a alteraciones epigenéticas del locus GNAS. Puede presentarse de forma esporádica, o heredado de manera autosómico dominante por vía materna. Se presenta paciente masculino de 31 años, con antecedentes de tumores óseos y calcificaciones cerebrales diagnosticados a los 14 años; que se consulta por presentar mareo intenso, rigidez del cuello y la boca, dificultad para hablar y tragar, desorientación y trastornos de percepción; con fenotipo y somatometría normales, y signos de tetania latente (Chvostek y Trouseau positivos). Los estudios realizados mostraron: hipocalcemia, hiperfosfatemia, aumento de niveles de parathormona y múltiples calcificaciones en cerebro y cerebelo. Con tales hallazgos se emite el diagnóstico de seudohipoparatiroidismo 1b, el cual se confirma mediante pruebas moleculares con alteración en el patrón de metilación en el locus GNAS. No presentó alteraciones en el estudio de secuenciación de los 13 exones codificantes del GNAS. Se concluyó como un caso esporádico ante la ausencia de historia familiar de hipocalcemia, combinado con amplia pérdida de metilación del gen GNAS y la no evidencia de deleciones. Se presenta el primer reporte de esta enfermedad en Cuba con estudio molecular.

Reseña de Francisco de Luis Martín, Historia del deporte obrero en España (de los orígenes al final de la guerra civil), Salamanca: Universidad de Salamanca, 2019, 371 pgs.

Background. The present research is an exploratory study on clinical teaching and competency-based education in the discursive practices of the fifth-level students of the Occupational Therapy program at the University of Chile Purpose. Describe and analyze the assessment made by students regarding the clinical teachings they receive in their professional practices. Methods. This work, from the theoretical and methodological points of view, assumes the critical analysis of the discourse, specifically, of the discursive practices that arise from the professional practices carried out by the students of the first innovated cohort, in 2017, of occupational oherapy in the clinical fields. It is based in a file body, which the students complete according to three periods during the academic year. Therefore, an analysis of the discursive practices is followed, which transcends the pure act of numerical and qualitative scores, to acquire all its subjective dimension as recognition of a multiplicity of meanings, which value and challenge the conditions of its own formative course. Results. Data and valuations are presented, where the scores mark repeatedly a positive evaluation of the teaching practice. For example, compliance with the agreements and established deadlines (84%); a respectful treatment with the student is maintained (77.8%); the necessary time is used to support and supervise the practice (92.9%); it is encouraged and generates spaces for the discussion of topics related to professional practice; the student is encouraged to work as a team (86.9%); among other things. Likewise, the students identify a series of topics, such as autonomy / autonomous work; feedback; teamwork; facilitation of teaching work, and, critical points in the teaching-learning process, such as participation; the administrative work of the teacher of practice and the lack of spaces for discussion. However, the different learning contexts in the different clinical fields are valued in a relevant way: conditions are facilitated to participate in various activities such as team meetings, home visits, instances of group and individual intervention, all of a practical nature; training focused on student learning, the issue of decision making and

Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle the selection problem based on genomic selection (GS) in single- and multi-trait settings. We proposed and tested three univariate loss functions (Kullback-Leibler, KL; Continuous Ranked Probability Score, CRPS; Linear-Linear loss, LinLin) and their corresponding multivariate generalizations (Kullback-Leibler, KL; Energy Score, EnergyS; and the Multivariate Asymmetric Loss Function, MALF). We derived and expressed all the loss functions in terms of heritability and tested them on a real wheat dataset for one cycle of selection and in a simulated selection program. The performance of each univariate loss function was compared with the standard method of selection (Std) that does not use loss functions. We compared the performance in terms of the selection response and the decrease in the population’s genetic variance during recurrent breeding cycles. Results suggest that it is possible to obtain better performance in a long-term breeding program using the single-trait scheme by selecting 30% of the best individuals in each cycle but not by selecting 10% of the best individuals. For the multi-trait approach, results show that the population mean for all traits under consideration had positive gains, even though two of the traits were negatively correlated. The corresponding population variances were not statistically different from the different loss function during the 10th selection cycle. Using the loss function should be a useful criterion when selecting the candidates for selection for the next breeding cycle.

One of the major issues in plant breeding is the occurrence of genotype × environment (GE) interaction. Several models have been created to understand this phenomenon and explore it. In the genomic era, several models were employed to improve selection by using markers and account for GE interaction simultaneously. Some of these models use special genetic covariance matrices. In addition, the scale of multi-environment trials is getting larger, and this increases the computational challenges. In this context, we propose an R package that, in general, allows building GE genomic covariance matrices and fitting linear mixed models, in particular, to a few genomic GE models. Here we propose two functions: one to prepare the genomic kernels accounting for the genomic GE and another to perform genomic prediction using a Bayesian linear mixed model. A specific treatment is given for sparse covariance matrices, in particular, to block diagonal matrices that are present in some GE models in order to decrease the computational demand. In empirical comparisons with Bayesian Genomic Linear Regression (BGLR), accuracies and the mean squared error were similar; however, the computational time was up to five times lower than when using the classic approach. Bayesian Genomic Genotype × Environment Interaction (BGGE) is a fast, efficient option for creating genomic GE kernels and making genomic predictions.

Cognitive impairment is a feature of many psychiatric diseases. Here the authors aimed to identify multimodal neuromarkers that can be used to quantify and predict cognitive performance in individuals with schizophrenia using three different features of MRI and three independent cohorts.

Given the importance of competition in the retail sector, this research builds on spatial interaction theory to develop the competition index (CI). For this, geographic information systems (GIS) and the analytic hierarchy process (AHP) were used. AHP results reveal that key factors to assess competitors relate to location and branding. The proposed method was tested by evaluating 45 supermarkets in the city of Castellón (Spain). Using this method, sales targets can be adapted to each outlet’s individual circumstances.

Abstract Background Modern agriculture uses hyperspectral cameras with hundreds of reflectance data at discrete narrow bands measured in several environments. Recently, Montesinos-López et al. (Plant Methods 13(4):1–23, 2017a. https://doi.org/10.1186/s13007-016-0154-2; Plant Methods 13(62):1–29, 2017b. https://doi.org/10.1186/s13007-017-0212-4) proposed using functional regression analysis (as functional data analyses) to help reduce the dimensionality of the bands and thus decrease the computational cost. The purpose of this paper is to discuss the advantages and disadvantages that functional regression analysis offers when analyzing hyperspectral image data. We provide a brief review of functional regression analysis and examples that illustrate the methodology. We highlight critical elements of model specification: (i) type and number of basis functions, (ii) the degree of the polynomial, and (iii) the methods used to estimate regression coefficients. We also show how functional data analyses can be integrated into Bayesian models. Finally, we include an in-depth discussion of the challenges and opportunities presented by functional regression analysis. Results We used seven model-methods, one with the conventional model (M1), three methods using the B-splines model (M2, M4, and M6) and three methods using the Fourier basis model (M3, M5, and M7). The data set we used comprises 976 wheat lines under irrigated environments with 250 wavelengths. Under a Bayesian Ridge Regression (BRR), we compared the prediction accuracy of the model-methods proposed under different numbers of basis functions, and compared the implementation time (in seconds) of the seven proposed model-methods for different numbers of basis. Our results as well as previously analyzed data (Montesinos-López et al. 2017a, 2017b) support that around 23 basis functions are enough. Concerning the degree of the polynomial in the context of B-splines, degree 3 approximates most of the curves very well. Two satisfactory types of basis are the Fourier basis for period curves and the B-splines model for non-periodic curves. Under nine different basis, the seven method-models showed similar prediction accuracy. Regarding implementation time, results show that the lower the number of basis, the lower the implementation time required. Methods M2, M3, M6 and M7 were around 3.4 times faster than methods M1, M4 and M5. Conclusions In this study, we promote the use of functional regression modeling for analyzing high-throughput phenotypic data and indicate the advantages and disadvantages of its implementation. In addition, many key elements that are needed to understand and implement this statistical technique appropriately are provided using a real data set. We provide details for implementing Bayesian functional regression using the developed genomic functional regression (GFR) package. In summary, we believe this paper is a good guide for breeders and scientists interested in using functional regression models for implementing prediction models when their data are curves.

Treatment of medically intractable focal epilepsy (MIFE) by surgical resection of the epileptogenic zone (EZ) is often effective provided the EZ can be reliably identified. Even with the use of invasive recordings, the clinical differentiation between the EZ and normal brain areas can be quite challenging, mainly in patients without MRI detectable lesions. Consequently, despite relatively large brain regions being removed, surgical success rates barely reach 60–65%. Such variable and unfavorable outcomes associated with high morbidity rates are often caused by imprecise and/or inaccurate EZ localization. We developed a localization algorithm that uses network-based data analytics to process invasive EEG recordings. This network algorithm analyzes the centrality signatures of every contact electrode within the recording network and characterizes contacts into susceptible EZ based on the centrality trends over time. The algorithm was tested in a retrospective study that included 42 patients from four epilepsy centers. Our algorithm had higher agreement with EZ regions identified by clinicians for patients with successful surgical outcomes and less agreement for patients with failed outcomes. These findings suggest that network analytics and a network systems perspective of epilepsy may be useful in assisting clinicians in more accurately localizing the EZ. Epilepsy is a disease that results in abnormal firing patterns in parts of the brain that comprise the epileptogenic network, known as the epileptogenic zone (EZ). Current methods to localize the EZ for surgical treatment often require observations of hundreds of thousands of EEG data points measured from many electrodes implanted in a patient’s brain. In this paper, we used network science to show that EZ regions may exhibit specific network signatures before, during, and after seizure events. Our algorithm computes the likelihood of each electrode being in the EZ and tends to agree more with clinicians during successful resections and less during failed surgeries. These results suggest that a networked analysis approach to EZ localization may be valuable in a clinical setting.

The textile industry is characterized by the economic activity whose objective is the production of fibres, yarns, fabrics, clothing and textile goods for home and decoration, as well as technical and industrial purposes. Within manufacturing, the Textile is one of the oldest and most complex sectors which includes a large number of sub-sectors covering the entire production cycle, from raw materials and intermediate products, to the production of final products. Textile industry activities present different subdivisions,each with its own traits. The length of the textile process and the variety of its technicalprocesses lead to the coexistence of different sub-sectors in regards to their business structure and integration. The textile industry is developing expert systems applicationsto increase production, improve quality and reduce costs. The analysis of textile designs or structures includes the use of mathematical models to simulate the behavior of the textile structures (yarns, fabrics and knitting). The Finite Element Method (FEM) has largely facilitated the prediction of the behavior of that textile structure under mechanical loads. For classification problems Artificial Neural Networks (ANNs) have proved to be a very effective tool as a quick and accurate solution. The Case-Based Reasoning (CBR) method proposed in this study complements the results of the finite element simulation, mathematical modeling and neural networks methods.