Volatile composition of Red Mencia and Souson cultivars from Rias Baixas and Valdeorras AOC (NW Spain)

Mencía and Sousón are two red Vitis vinifera cultivars grown in two geographic areas from Galicia (NW Spain), Appellation of Origin Controlled Valdeorras and Rías Baixas. Valdeorras AOC is situated in south east Galicia, with Continental climate, slate soil, gentle temperature and rainfall and Rías Baixas AOC is located in the southwest Galicia, near of the sea, with Atlantic climate, siliceous soil, and slightly higher temperature and rainfall than the first one. The aim of this study was to carry out a first approximation to determinate the influence of terroir on volatile composition of these red cultivars grown in Galicia. Grapes of Mencía and Sousón, collected in 2009 vintage, were crushed and the musts volatiles were extracted using Solid Phase Extraction (SPE). The identification and quantification was performed by gas chromatography-mass spectrometry (GC-MS) in free and bound form. The results showed a greater effect of terroir in bound compounds (alcohols, volatile phenols, C13-norisoprenoids and volatile fatty acids) between geographic areas for the two cultivars studied. In free fraction C6-compounds and carbonyl compounds showed variability between geographic areas for the cultivars

The effects of waveform and current direction on the efficacy and test–retest reliability of transcranial magnetic stimulation

[Abstract] The pulse waveform and current direction of transcranial magnetic stimulation (TMS) influence its interactions with the neural substrate; however, their role in the efficacy and reliability of single- and paired-pulse TMS measures is not fully understood. We investigated how pulse waveform and current direction affect the efficacy and test–retest reliability of navigated, single- and paired-pulse TMS measures. 23 healthy adults (aged 18–35 years) completed two identical TMS sessions, assessing resting motor threshold (RMT), motor-evoked potentials (MEPs), cortical silent period (cSP), short- and long-interval intra-cortical inhibition (SICI and LICI), and intracortical facilitation (ICF) using either monophasic posterior–anterior (monoPA; n = 9), monophasic anterior–posterior (monoAP; n = 7), or biphasic (biAP-PA; n = 7) pulses. Averages of each TMS measure were compared across the three groups and intraclass correlation coefficients were calculated to assess test–retest reliability. RMT was the lowest and cSP was the longest with biAP-PA pulses, whereas MEP latency was the shortest with monoPA pulses. SICI and LICI had the largest effect with monoPA pulses, whereas only monoAP and biAP-PA pulses resulted in significant ICF. MEP amplitude was more reliable with either monoPA or monoAP than with biAP-PA pulses. LICI was the most reliable with monoAP pulses, whereas ICF was the most reliable with biAP-PA pulses. Waveform/current direction influenced RMT, MEP latency, cSP, SICI, LICI, and ICF, as well as the reliability of MEP amplitude, LICI, and ICF. These results show the importance of considering TMS pulse parameters for optimizing the efficacy and reliability of TMS neurophysiologic measures

A predictive model and risk factors for case fatality of covid-19

This study aimed to create an individualized analysis model of the risk of intensive care unit (ICU) admission or death for coronavirus disease 2019 (COVID-19) patients as a tool for the rapid clinical management of hospitalized patients in order to achieve a resilience of medical resources. This is an observational, analytical, retrospective cohort study with longitudinal follow-up. Data were collected from the medical records of 3489 patients diagnosed with COVID-19 using RT-qPCR in the period of highest community transmission recorded in Europe to date: February–June 2020. The study was carried out in in two health areas of hospital care in the Madrid region: the central area of the Madrid capital (Hospitales de Madrid del Grupo HM Hospitales (CH-HM), n = 1931) and the metropolitan area of Madrid (Hospital Universitario Príncipe de Asturias (MH-HUPA) n = 1558). By using a regression model, we observed how the different patient variables had unequal importance. Among all the analyzed variables, basal oxygen saturation was found to have the highest relative importance with a value of 20.3%, followed by age (17.7%), lymphocyte/leukocyte ratio (14.4%), CRP value (12.5%), comorbidities (12.5%), and leukocyte count (8.9%). Three levels of risk of ICU/death were established: low-risk level (20%). At the high-risk level, 13% needed ICU admission, 29% died, and 37% had an ICU–death outcome. This predictive model allowed us to individualize the risk for worse outcome for hospitalized patients affected by COVID-19

Enhancing physicians’ radiology diagnostics of COVID-19’s effects on lung health by leveraging artificial intelligence

Introduction: This study aimed to develop an individualized artificial intelligence model to help radiologists assess the severity of COVID-19's effects on patients' lung health.Methods: Data was collected from medical records of 1103 patients diagnosed with COVID-19 using RT- qPCR between March and June 2020, in Hospital Madrid-Group (HM-Group, Spain). By using Convolutional Neural Networks, we determine the effects of COVID-19 in terms of lung area, opacities, and pulmonary air density. We then combine these variables with age and sex in a regression model to assess the severity of these conditions with respect to fatality risk (death or ICU).Results: Our model can predict high effect with an AUC of 0.736. Finally, we compare the performance of the model with respect to six physicians' diagnosis, and test for improvements on physicians' performance when using the prediction algorithm.Discussion: We find that the algorithm outperforms physicians (39.5% less error), and thus, physicians can significantly benefit from the information provided by the algorithm by reducing error by almost 30%

Epidemiology of traumatic spinal cord injury in Galicia, Spain: trends over a 20-year period

[Abstract] Study design: Observational study with prospective and retrospective monitoring. Objective: To describe the epidemiological and demographic characteristics of traumatic spinal cord injury (TSCI), and to analyze its epidemiological changes. Setting: Unidad de Lesionados Medulares, Complejo Hospitalario Universitario A Coruña, in Galicia (Spain). Methods: The study included patients with TSCI who had been hospitalized between January 1995 and December 2014. Relevant data were extracted from the admissions registry and electronic health record. Results: A total of 1195 patients with TSCI were admitted over the specified period of time; 76.4% male and 23.6% female. Mean patient age at injury was 50.20 years. Causes of injury were falls (54.2%), traffic accidents (37%), sports/leisure-related accidents (3.5%) and other traumatic causes (5.3%). Mean patient age increased significantly over time (from 46.40 to 56.54 years), and the number of cases of TSCI related to traffic accidents decreased (from 44.5% to 23.7%), whereas those linked to falls increased (from 46.9% to 65.6%). The most commonly affected neurological level was the cervical level (54.9%), increasing in the case of levels C1–C4 over time, and the most frequent ASIA (American Spinal Injury Association) grade was A (44.3%). The crude annual incidence rate was 2.17/100 000 inhabitants, decreasing significantly over time at an annual percentage rate change of −1.4%. Conclusions: The incidence rate of TSCI tends to decline progressively. Mean patient age has increased over time and cervical levels C1–C4 are currently the most commonly affected ones. These epidemiological changes will eventually result in adjustments in the standard model of care for TSCI

Enhancing physicians’ radiology diagnostics of COVID-19’s effects on lung health by leveraging artificial intelligence

Introduction: This study aimed to develop an individualized artificial intelligence model to help radiologists assess the severity of COVID-19’s effects on patients’ lung health.Methods: Data was collected from medical records of 1103 patients diagnosed with COVID-19 using RT- qPCR between March and June 2020, in Hospital Madrid-Group (HM-Group, Spain). By using Convolutional Neural Networks, we determine the effects of COVID-19 in terms of lung area, opacities, and pulmonary air density. We then combine these variables with age and sex in a regression model to assess the severity of these conditions with respect to fatality risk (death or ICU).Results: Our model can predict high effect with an AUC of 0.736. Finally, we compare the performance of the model with respect to six physicians’ diagnosis, and test for improvements on physicians’ performance when using the prediction algorithm.Discussion: We find that the algorithm outperforms physicians (39.5% less error), and thus, physicians can significantly benefit from the information provided by the algorithm by reducing error by almost 30%

ESTIMULACIÓN MAGNÉTICA TRANSCRANEAL: PRINCIPIOS BÁSICOS Y APLICACIONES EN LA ACTIVIDAD FÍSICA Y EL DEPORTE

<p align="center"> </p><p align="center"><strong>RESUMEN</strong></p> <p class="resumenyabstract" align="justify">La Estimulación Magnética Transcraneal (EMT) es un técnica novedosa que permite estimular la corteza cerebral humana de forma no invasiva, indolora y sin efectos secundarios siempre y cuando se respeten los protocolos de seguridad establecidos. Su utilidad cubre un amplio abanico extendiéndose desde el estudio de las corteza motora hasta los correlatos fisiológicos de las funciones cognitivas, pasando por el tratamiento de determinadas enfermedades neurológicas o por el estudio del tiempo de reacción. En este trabajo, ofrecemos una introducción a las características de la EMT y revisamos sus principales aplicaciones haciendo énfasis en su posible validez como instrumento de investigación aplicado a las Ciencias del Deporte. <br />PALABRAS CLAVE:</p> <p class="tabulado"> </p> <p class="titulo1" align="center"><strong>ABSTRACT</strong></p> <p class="resumenyabstract" align="justify">Transcranial Magnetic Stimulation (TMS) is a novel technique which permits painless stimulation of the cerebral cortex in humans without requiring open access to the brain, and if used following appropriate guidelines, is devoid of important side effects. TMS has been broadly used. It began as a tool for studying motor cortex function, but is now being used to look at cognitive functions, to treat neurological disorders or to study the reaction time. In this article we like to review the technical aspects of TMS and its main applications, and discuss the possibility of using TMS as a research tool to study Sport Sciences. <br />KEY WORDS:</p&gt

An Extension to Philips' Algorithm for Moment Calculation

Abstract. A new reformulation of Philips’ algorithm for the computation of discrete image moments is presented. As Philips’ method, the new reformulation produces the same exact results but in a faster manner. Moment contributions due to the presence of holes in the shape (which are not taken into account, to our knowledge, into any boundary based method for moment calculation including Philips’) are also introduced into the new method