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Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guidelines non-adherence have been proved to be associated with higher mortality. Machine Learning is increasingly being adopted in developing innovative Clinical Decision Support Systems in many areas of medicine, showing a great potential for automatic prediction of diverse patient conditions, as well as assistance in clinical decision making. In this context, this work conducts a narrative review to provide an overview of how specific Machine Learning techniques can be used to improve sepsis management, discussing the main tasks addressed, the most popular methods and techniques, as well as the obtained results, in terms of both intelligent system accuracy and clinical outcomes improvement (AU)

La sepsis representa un problema de salud pública de primer orden y es una de las principales causas de muerte a nivel mundial. El retraso en el inicio del tratamiento, junto con la no adherencia a las guías de práctica clínica se asocian a una mayor mortalidad. El aprendizaje automático o machine learning están siendo empleados en el desarrollo de sistemas de apoyo a la decisión clínica, innovadores en muchas áreas de la medicina, mostrando un gran potencial para la predicción de diversas condiciones del paciente, así como en la asistencia durante el proceso de toma de decisiones médicas. En este sentido, este trabajo lleva a cabo una revisión narrativa para proporcionar una visión general de cómo las técnicas de machine learning pueden ser empleadas para mejorar el manejo de la sepsis, discutiendo las principales tareas que tratan de resolver, los métodos y las técnicas más empleados, así como los resultados obtenidos, tanto en términos de precisión de los sistemas inteligentes, como en la mejora de los resultados clínicos (AU)

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Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guidelines non-adherence have been proved to be associated with higher mortality. Machine Learning is increasingly being adopted in developing innovative Clinical Decision Support Systems in many areas of medicine, showing a great potential for automatic prediction of diverse patient conditions, as well as assistance in clinical decision making. In this context, this work conducts a narrative review to provide an overview of how specific Machine Learning techniques can be used to improve sepsis management, discussing the main tasks addressed, the most popular methods and techniques, as well as the obtained results, in terms of both intelligent system accuracy and clinical outcomes improvement.

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Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guidelines non-adherence have been proved to be associated with higher mortality. Machine Learning is increasingly being adopted in developing innovative Clinical Decision Support Systems in many areas of medicine, showing a great potential for automatic prediction of diverse patient conditions, as well as assistance in clinical decision making. In this context, this work conducts a narrative review to provide an overview of how specific Machine Learning techniques can be used to improve sepsis management, discussing the main tasks addressed, the most popular methods and techniques, as well as the obtained results, in terms of both intelligent system accuracy and clinical outcomes improvement.

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BACKGROUND: Naevoid basal cell carcinoma syndrome (NBCCS) is an autosomal dominant disorder characterized by developmental alterations and multiple basal cell carcinomas. Mutations in PTCH1, which encodes a membrane receptor for Sonic Hedgehog, are associated with the development of the disease. Most of them produce a truncated protein, which is unable to suppress Smoothened protein and continuously activates the downstream pathway. OBJECTIVES: We aimed to characterize 22 unrelated Spanish patients with NBCCS, the largest cohort with Gorlin syndrome reported to date in Spain. METHODS: Genomic analysis of PTCH1 was performed in patients with NBCCS and controls, and mutations were analysed using bioinformatics tools. RESULTS: We report for the first time two young patients, one each with uterus didelphys and ganglioneuroma, within the context of NBCCS. One patient showing a severe phenotype of the disease had developed basal cell carcinomas since childhood. Sanger sequencing of PTCH1 in this cohort identified 17 novel truncating mutations (11 frameshift, five nonsense and one mutation affecting an exon-intron splice site) and two novel missense mutations that were predicted to be pathogenic. The patients showed great clinical variability and inconsistent genotype-phenotype correlation, as seen in relatives carrying similar mutations. CONCLUSIONS: This study contributes to increase the pool of clinical manifestations of NBCCS, as well as increasing the number of pathogenic mutations identified in PTCH1 predisposing to the condition. The inconsistencies found between phenotype and genotype suggest the involvement of other modifying factors, genetic, epigenetic or environmental.

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Protein equalization with dithiothreitol, protein depletion with acetonitrile and the entire proteome were assessed in conjunction with matrix assisted laser desorption ionization time of flight mass spectrometry-based profiling for a fast and effective classification of patients with renal insufficiency. Two case groups were recruited as proof of concept, patients with chronic glomerulonephritis and diabetic nephropathy. Two key tools were used to develop this approach: protein concentration with centrifugal concentrator tubes with 10 KDa cut-off membranes and chemical assisted protein equalization with dithiothreitol or chemical assisted protein depletion with acetonitrile. In-house developed software was used to apply principal component analysis and hierarchical clustering to the profiles obtained. The results suggest that chemical assisted protein equalization with dithiothreitol is a methodology more robust than the other two ones, as the patients were well grouped by principal component analysis or by hierarchical clustering.

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BACKGROUND: The aim of this randomized clinical trial follow-up at three months was to evaluate the effectiveness of an educational intervention with a focus on diet and physical activity (PA) to change the amount of PA, body mass index (BMI) and the waist circumference (WC) in patients with severe mental illness. METHODS: We recruited 332 outpatients with severe mental disorders undergoing treatment with antipsychotic medication from Mental Healthcare Centers of Barcelona. They were randomly assigned to an intervention or a control group. The patients in the intervention group participated in a group PA and diet educational program. The blinded measurements at 0 and 3 months were: the level of PA (IPAQ questionnaire), BMI, WC, blood pressure, dietary habits (PREDIMED questionnaire), quality of life (SF-36 questionnaire) and laboratory parameters (cholesterol, triglycerides, glucose). RESULTS: The average age was 46.7 years and 55% were males. Schizophrenia had been diagnosed in 67.1% of them. At 3 months, the average weekly walking METs rose significantly in the IG 266.05 METs (95%CI: 16.86 to 515.25; P=0.036). The total MET average also rose although not significantly: 191.38 METs (95%CI: 1.38 to 381.38; P=0.086). However, the BMI decreased significantly more in the CG, by 0.26kg/m(2) (95%CI: 0.02 to 0.51; P=0.038), than in the IG. There were no significant differences in the WC. CONCLUSIONS: The short-term results suggest that the intervention increases the level of PA, but does not improve physical or laboratory parameters. TRIAL REGISTRATION: Clinicaltrials.gov NCT01729650 (effectiveness of a physical activity and diet program in patients with psychotic disorder [CAPiCOR]).

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BACKGROUND: Mass spectrometry is one of the most important techniques in the field of proteomics. MALDI-TOF mass spectrometry has become popular during the last decade due to its high speed and sensitivity for detecting proteins and peptides. MALDI-TOF-MS can be also used in combination with Machine Learning techniques and statistical methods for knowledge discovery. Although there are many software libraries and tools that can be combined for these kind of analysis, there is still a need for all-in-one solutions with graphical user-friendly interfaces and avoiding the need of programming skills. RESULTS: Mass-Up, an open software multiplatform application for MALDI-TOF-MS knowledge discovery is herein presented. Mass-Up software allows data preprocessing, as well as subsequent analysis including (i) biomarker discovery, (ii) clustering, (iii) biclustering, (iv) three-dimensional PCA visualization and (v) classification of large sets of spectra data. CONCLUSIONS: Mass-Up brings knowledge discovery within reach of MALDI-TOF-MS researchers. Mass-Up is distributed under license GPLv3 and it is open and free to all users at http://sing.ei.uvigo.es/mass-up.

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This work presents a novel database search engine - MLibrary - designed to assist the user in the detection and identification of androgenic anabolic steroids (AAS) and its metabolites by matrix assisted laser desorption/ionization (MALDI) and mass spectrometry-based strategies. The detection of the AAS in the samples was accomplished by searching (i) the mass spectrometric (MS) spectra against the library developed to identify possible positives and (ii) by comparison of the tandem mass spectrometric (MS/MS) spectra produced after fragmentation of the possible positives with a complete set of spectra that have previously been assigned to the software. The urinary screening for anabolic agents plays a major role in anti-doping laboratories as they represent the most abused drug class in sports. With the help of the MLibrary software application, the use of MALDI techniques for doping control is simplified and the time for evaluation and interpretation of the results is reduced. To do so, the search engine takes as input several MALDI-TOF-MS and MALDI-TOF-MS/MS spectra. It aids the researcher in an automatic mode by identifying possible positives in a single MS analysis and then confirming their presence in tandem MS analysis by comparing the experimental tandem mass spectrometric data with the database. Furthermore, the search engine can, potentially, be further expanded to other compounds in addition to AASs. The applicability of the MLibrary tool is shown through the analysis of spiked urine samples.

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Automatic term annotation from biomedical documents and external information linking are becoming a necessary prerequisite in modern computer-aided medical learning systems. In this context, this paper presents BioAnnote, a flexible and extensible open-source platform for automatically annotating biomedical resources. Apart from other valuable features, the software platform includes (i) a rich client enabling users to annotate multiple documents in a user friendly environment, (ii) an extensible and embeddable annotation meta-server allowing for the annotation of documents with local or remote vocabularies and (iii) a simple client/server protocol which facilitates the use of our meta-server from any other third-party application. In addition, BioAnnote implements a powerful scripting engine able to perform advanced batch annotations.

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BACKGROUND: The cause of spontaneous subarachnoid hemorrhage (SAH) is unknown in 15% of cases; idiopathic SAH has a better prognosis than aneurysmal SAH. When bleeding is confined to the perimesencephalic cisterns, SAH has an especially benign course. METHODS: We retrospectively studied 108 patients admitted for spontaneous non-aneurysmal SAH between 1991 and 2004. We divided patients into two groups according to the bleeding pattern at cranial CT: perimesencephalic pattern (n=60) and aneurysmal pattern (n=48). We included only patients in whom no source of bleeding was detected at angiography; patients with aneurysmal pattern underwent at least two angiographic examinations. Mean follow-up was 5.5years; follow-up consisted of telephone interview in 84.7% of patients. RESULTS: All but one patient with perimesencephalic pattern were classified as grade I or II on the Hunt and Hess scale; the exception was the only patient in this group with a complication (hydrocephalus), who was classified as grade IV. Three-quarters of the patients with aneurysmal pattern were classified as grade I or II on the Hunt and Hess scale; 5 patients presented with hydrocephalus that required drainage and 2 with vasospasms without repercussions. No rebleeding or long-term complications were observed in either group. CONCLUSIONS: Non-aneurysmal SAH with a perimesencephalic pattern of bleeding has a benign course and excellent short-term and long-term prognosis. Patients with non-aneurysmal SAH with an aneurysmal pattern of bleeding have more complications, and the initial clinical situation has a significant impact on their prognosis.

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We report in this work a fast protocol for protein quantification and for peptide mass mapping that rely on (18)O isotopic labeling through the decoupling procedure. It is demonstrated that the purity and source of trypsin do not compromise the labeling degree and efficiency of the decoupled labeling reaction, and that the pH of the labeling reaction is a critical factor to obtain a significant (18)O double labeling. We also show that the same calibration curve can be used for MALDI protein quantification during several days maintaining a reasonable accuracy, thus simplifying the handling of the quantification process. In addition we demonstrate that (18)O isotopic labeling through the decoupling procedure can be successfully used to elaborate peptide mass maps. BSA was successfully quantified using the same calibration curve in different days and plasma from a freshwater fish, Cyprinus carpio, was used to elaborate the peptide mass maps.

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Applied research in both biomedical discovery and translational medicine today often requires the rapid development of fully featured applications containing both advanced and specific functionalities, for real use in practice. In this context, new tools are demanded that allow for efficient generation, deployment and reutilization of such biomedical applications as well as their associated functionalities. In this context this paper presents AIBench, an open-source Java desktop application framework for scientific software development with the goal of providing support to both fundamental and applied research in the domain of translational biomedicine. AIBench incorporates a powerful plug-in engine, a flexible scripting platform and takes advantage of Java annotations, reflection and various design principles in order to make it easy to use, lightweight and non-intrusive. By following a basic input-processing-output life cycle, it is possible to fully develop multiplatform applications using only three types of concepts: operations, data-types and views. The framework automatically provides functionalities that are present in a typical scientific application including user parameter definition, logging facilities, multi-threading execution, experiment repeatability and user interface workflow management, among others. The proposed framework architecture defines a reusable component model which also allows assembling new applications by the reuse of libraries from past projects or third-party software.

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Introducción. Un 15% de hemorragias subaracnoideas (HSA) espontáneas son de causa desconocida, configurando una entidad con características diferentes a las de etiología aneurismática. Analizamos de forma retrospectiva la sintomatología, complicaciones y evolución a largo plazo en 60 pacientes y destacamos el subgrupo de pacientes con un patrón perimesencefálico (PPM) en la tomografía computarizada (TC) por su excelente pronóstico. Métodos. Se obtuvieron datos de 60 pacientes ingresados entre 1992-2000 divididos en tres grupos según neuroimagen: 26 con PPM, 28 con patrón aneurismático (PA) y 6 con TC normal, con estudio arteriográfico completo. El período de seguimiento fue de 6-24 meses. Resultados. De los 26 pacientes con HSA y PPM todos se situaron en grado I-II de la escala de Hunt y Hess, no hubo complicaciones en ninguno de ellos durante el ingreso y a largo plazo 22 (84%) estaban asintomáticos mientras que 4 (16%) referían cefalea. De los 28 pacientes con HSA y PA destacaba Hunt y Hess de I y II en 22 (78%), grado III en 5 (18%) y grado IV en 1 paciente. Uno de ellos resangró con resultado fatal y 2 precisaron drenaje por hidrocefalia. El 68% (19 pacientes) estaban asintomáticos y los demás referían cefalea. Conclusiones. Destacamos la buena evolución a corto y largo plazo de las HSA no aneurismáticas, especialmente en el PPM en el que las complicaciones son excepcionales (AU)

Introduction: Spontaneous subarachnoid hemorrhage (SAH) is idiopathic in 15% of cases. They represent a group whose characteristics are different from those with an aneurysmal etiology. We present a retrospective longterm follow up of 60 patients, analyzing symptomatology, complications and evolution and identify a subgroup of patients with a perimesencephalic pattern (PMP) in computed tomography (CT) for their excellent prognosis. Methods: We collected information on 60 patients admitted to our center between 1992 and 2000 and divided them into three groups, according to neuroimage: 26 had a PMP, 28 showed an aneurysmal pattern (AP), and 6 patients had normal TC, with complete arteriographic study. Length of follow-up was 6-24 months. Results: All of the 26 patients with SAH and PPM pattern were rated grade I-II on the Hunt-Hess scale. None of them had complications during hospital stay and at long term, 22 (84%) were asymptomatic, while 4 (16%) reported cephalea. Out of 28 patients with SAH and AP, 22 were rated Hunt-Hess Scale grade I and II (78%), 5 grade III (18%) and one patient was rated grade IV. Rebleeding caused death in one of them, and two required drainage for hydrocephalia. A total of 68% (19 patients) were asymptomatic and the others complained of cephalea. Conclusions: We stress the good evolution of nonaneurysmal SAH at short and long term, especially those following a PMP with absence of complication (AU)

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INTRODUCTION: Spontaneous subarachnoid hemorrhage (SAH) is idiopathic in 15% of cases. They represent a group whose characteristics are different from those with an aneurysmal etiology. We present a retrospective longterm follow up of 60 patients, analyzing symptomatology, complications and evolution and identify a subgroup of patients with a perimesencephalic pattern (PMP) in computed tomography (CT) for their excellent prognosis. METHODS: We collected information on 60 patients admitted to our center between 1992 and 2000 and divided them into three groups, according to neuroimage: 26 had a PMP, 28 showed an aneurysmal pattern (AP), and 6 patients had normal TC, with complete arteriographic study. Length of follow-up was 6-24 months. RESULTS: All of the 26 patients with SAH and PPM pattern were rated grade I-II on the Hunt-Hess scale. None of them had complications during hospital stay and at long term, 22 (84%) were asymptomatic, while 4 (16%) reported cephalea. Out of 28 patients with SAH and AP, 22 were rated Hunt-Hess Scale grade I and II (78%), 5 grade III (18%) and one patient was rated grade IV. Rebleeding caused death in one of them, and two required drainage for hydrocephalia. A total of 68% (19 patients) were asymptomatic and the others complained of cephalea. CONCLUSIONS: We stress the good evolution of nonaneurysmal SAH at short and long term, especially those following a PMP with absence of complication.

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Entre los efectos adversos de la terapia electroconvulsiva (TEC), las quejas sobre disfunción mnésica son los más frecuentes y relevantes para los pacientes. Tras la TEC, la amnesia anterógrada y retrógrada son más determinantes para la memoria explícita y puede tener un efecto persistente sobre la episódica impersonal. La memoria implícita no suele resultar afectada. Los factores relacionados con más déficit son: TEC bilateral, dosis supraumbral elevada, onda sinusal, 3 tratamientos por semana, alteración cognitiva previa a la TEC y tiempo prolongado en recuperar la orientación tras ésta, agentes anestésicos y edad

One of the most frequent and important complaints made by patients about electroconvulsive therapy (ECT) is memory dysfunction. After ECT, anterograde and retrograde amnesia are more marked for explicit memory, and could have a lasting effect on impersonal episodic memory. Implicit memory is not usually affected. The factors related to severe dysfunction are: bilateral ECT, markedly suprathreshold stimulus, sinus wave, treatment three times per week, cognitive alteration before ECT and prolonged time to recovery of orientation after ECT, anesthetic agents, and age

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Betula pollen is a common cause of pollinosis in localities in NW Spain and between 13% and 60% of individuals who are immunosensitive to pollen grains respond positively to its allergens. It is important in the case of all such people to be able to predict pollen concentrations in advance. We therefore undertook an aerobiological study in the city of Vigo (Pontevedra, Spain) from 1995 to 2001, using a Hirst active-impact pollen trap (VPPS 2000) situated in the city centre. Vigo presents a temperate maritime climate with a mean annual temperature of 14.9 degrees C and 1,412 mm annual total precipitation. This paper analyses two ways of quantifying the prediction of pollen concentration: first by means of a generalized additive regression model with the object of predicting whether the series of interest exceeds a certain threshold; second using a partially linear model to obtain specific prediction values for pollen grains. Both models use a self-explicative part and another formed by exogenous meteorological factors. The models were tested with data from 2001 (year in which the total precipitation registered was almost twice the climatological average overall during the flowering period), which were not used in formulating the models. A highly satisfactory classification and good forecasting results were achieved with the first and second approaches respectively. The estimated line taking into account temperature and a calm S-SW wind, corresponds to the real line recorded during 2001, which gives us an idea of the proposed model's validity.

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In order to survive periods of adverse cold climatic conditions, plant requirements are satisfied by means of physiological adaptations to prevent cells from freezing. Thus, the growth of woody plants in temperate regions slows down and they enter into a physiological state called dormancy. In order to identify the chilling and heat requirements to overcome the dormancy period of Betula in the south of Europe, a comparative study was carried out with aerobiological pollen data of a 7-year (1995-2001) period in Vigo (Spain) and Perugia (Italy). To satisfy chilling requirements, base temperatures of 7 degrees C and 5.75 degrees C showed a lower standard variation coefficient: 3.94% and 2.36% in Perugia and Vigo respectively. In the case of heat accumulation, the sum of mean temperatures in Perugia and the sum of maximum temperatures in Vigo were the parameters that showed a minor coefficient of variation (11.13% and 14.51% respectively).

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