1,725 research outputs found

    Differential cognitive impairment for diverse forms of multiple sclerosis

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    BACKGROUND: Cognitive impairment is a common feature in multiple sclerosis (MS) patients and occurs in 60% of all cases. Unfortunately, neurological examination does not always agree with the neuropsychological evaluation in determining the cognitive profile of the patient. On the other hand, psychophysiological techniques such as event-related potentials (ERPs) can help in evaluating cognitive impairment in different pathologies. Behavioural responses and EEG signals were recorded during the experiment in three experimental groups: 1) a relapsing-remitting group (RRMS), 2) a benign multiple sclerosis group (BMS) and 3) a Control group. The paradigm employed was a spatial attention task with central cues (Posner experiment). The main aim was to observe the differences in the performance (behavioural variables) and in the latency and amplitude of the ERP components among these groups. RESULTS: Our data indicate that both MS groups showed poorer task performance (longer reaction times and lower percentage of correct responses), a latency delay for the N1 and P300 component, and a different amplitude for the frontal N1. Moreover, the deficit in the BMS group, indexed by behavioural and pyschophysiological variables, was more pronounced compared to the RRMS group. CONCLUSION: The present results suggest a cognitive impairment in the information processing in all of these patients. Comparing both pathological groups, cognitive impairment was more accentuated in the BMS group compared to the RMSS group. This suggests a silent deterioration of cognitive skills for the BMS that is not usually treated with pharmacological or neuropsychological therapy

    Amino acid dependent formaldehyde metabolism in mammals.

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    Aldehyde dehydrogenase class 3, encoded by ADH5 in humans, catalyzes the glutathione dependent detoxification of formaldehyde. Here we show that ADH5 deficient cells turn over formaldehyde using alternative pathways starting from the reaction of formaldehyde with free amino acids. When mammalian cells are exposed to formaldehyde, the levels of the reaction products of formaldehyde with the amino acids cysteine and histidine - timonacic and spinacine - are increased. These reactions take place spontaneously and the formation of timonacic is reversible. The levels of timonacic are higher in the plasma of Adh5-/- mice relative to controls and they are further increased upon administration of methanol. We conclude that mammals possess pathways of cysteine and histidine dependent formaldehyde metabolism and that timonacic is a formaldehyde reservoir

    Classification methods to identify lesions in skin starting from spectra of diffuse reflectance

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    Con el objetivo de discriminar lesiones benignas y malignas en la piel humana a partir de espectros de reflexión difusa, se han analizado diferentes algoritmos de clasificación usando el software de aprendizaje automático y reconocimiento de patrones WEKA. Además, dada la alta dimensionalidad de la señal espectral, fue empleada una técnica selección de atributos para determinar las variables que aporten la mayor cantidad de información. Se probó la clasificación de la señal usando los algoritmos de máquinas de vectores de soporte, redes neuronales y bosques aleatorios, el desempeño fue evaluado usando el promedio de la k-fold cross-validation tomando en cuenta los porcentajes de instancias clasificadas correctamente, el índice kappa, el área bajo la curva ROC, la sensibilidad, y la especifidad. Finalmente se demuestra que el algoritmo de redes neuronales con los parámetros momentum y learning rate en 0,6 y 0,3 respectivamente, es el que mejor se adapta al problema de reconocimiento de patrones ya que clasifica correctamente al 89,89% de los casos.In order to differentiate between benign and malignant lesions in the human skin using diffuse reflection spectra, different classification algorithms were tested using the WEKA data mining software. In addition, due to the high dimensionality of the spectral signal, an attribute selection technique was applied to determine the variables that contribute with more information. The spectral signal classification was tested using support vector machines, neural networks and random forests, their performance was measured using the k-fold cross-validation percentages of the Kappa statistic, area under the ROC curve, specificity and sensitivity. Finally it is shown that the one layer neural network with 6 neurons and the parameters momentum and learning rate in 0.6 and 0.3 respectively, is best suited to the problem of pattern recognition, achieving correctly classify 89.89% of the cases

    Range expansion and the origin of USA300 north american epidemic methicillin-resistant Staphylococcus aureus

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    The USA300 North American epidemic (USA300-NAE) clone of methicillin-resistant Staphylococcus aureus has caused a wave of severe skin and soft tissue infections in the United States since it emerged in the early 2000s, but its geographic origin is obscure. Here we use the population genomic signatures expected from the serial founder effects of a geographic range expansion to infer the origin of USA300-NAE and identify polymorphisms associated with its spread. Genome sequences from 357 isolates from 22 U.S. states and territories and seven other countries are compared. We observe two significant signatures of range expansion, including decreases in genetic diversity and increases in derived allele frequency with geographic distance from the Pennsylvania region. These signatures account for approximately half of the core nucleotide variation of this clone, occur genome wide, and are robust to heterogeneity in temporal sampling of isolates, human population density, and recombination detection methods. The potential for positive selection of a gyrA fluoroquinolone resistance allele and several intergenic regions, along with a 2.4 times higher recombination rate in a resistant subclade, is noted. These results are the first to show a pattern of genetic variation that is consistent with a range expansion of an epidemic bacterial clone, and they highlight a rarely considered but potentially common mechanism by which genetic drift may profoundly influence bacterial genetic variation. IMPORTANCE The process of geographic spread of an origin population by a series of smaller populations can result in distinctive patterns of genetic variation. We detect these patterns for the first time with an epidemic bacterial clone and use them to uncover the clone’s geographic origin and variants associated with its spread. We study the USA300 clone of methicillin-resistant Staphylococcus aureus, which was first noticed in the early 2000s and subsequently became the leading cause of skin and soft tissue infections in the United States. The eastern United States is the most likely origin of epidemic USA300. Relatively few variants, which include an antibiotic resistance mutation, have persisted during this clone’s spread. Our study suggests that an early chapter in the genetic history of this epidemic bacterial clone was greatly influenced by random subsampling of isolates during the clone’s geographic spread

    Spanish guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia

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    The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies

    Cluster analysis of behavioural and event-related potentials during a contingent negative variation paradigm in remitting-relapsing and benign forms of multiple sclerosis

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    <p>Abstract</p> <p>Background</p> <p>Event-related potentials (ERPs) may be used as a highly sensitive way of detecting subtle degrees of cognitive dysfunction. On the other hand, impairment of cognitive skills is increasingly recognised as a hallmark of patients suffering from multiple sclerosis (MS). We sought to determine the psychophysiological pattern of information processing among MS patients with the relapsing-remitting form of the disease and low physical disability considered as two subtypes: 'typical relapsing-remitting' (RRMS) and 'benign MS' (BMS). Furthermore, we subjected our data to a cluster analysis to determine whether MS patients and healthy controls could be differentiated in terms of their psychophysiological profile.</p> <p>Methods</p> <p>We investigated MS patients with RRMS and BMS subtypes using event-related potentials (ERPs) acquired in the context of a Posner visual-spatial cueing paradigm. Specifically, our study aimed to assess ERP brain activity in response preparation (contingent negative variation -CNV) and stimuli processing in MS patients. Latency and amplitude of different ERP components (P1, eN1, N1, P2, N2, P3 and late negativity -LN) as well as behavioural responses (reaction time -RT; correct responses -CRs; and number of errors) were analyzed and then subjected to cluster analysis.</p> <p>Results</p> <p>Both MS groups showed delayed behavioural responses and enhanced latency for long-latency ERP components (P2, N2, P3) as well as relatively preserved ERP amplitude, but BMS patients obtained more important performance deficits (lower CRs and higher RTs) and abnormalities related to the latency (N1, P3) and amplitude of ERPs (eCNV, eN1, LN). However, RRMS patients also demonstrated abnormally high amplitudes related to the preparation performance period of CNV (cCNV) and post-processing phase (LN). Cluster analyses revealed that RRMS patients appear to make up a relatively homogeneous group with moderate deficits mainly related to ERP latencies, whereas BMS patients appear to make up a rather more heterogeneous group with more severe information processing and attentional deficits.</p> <p>Conclusions</p> <p>Our findings are suggestive of a slowing of information processing for MS patients that may be a consequence of demyelination and axonal degeneration, which also seems to occur in MS patients that show little or no progression in the physical severity of the disease over time.</p

    The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

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    The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected
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