Estudio longitudinal del peso e índice de masa corporal tras el trasplante renal durante 5 años de evolución.

INTRODUCTION: Gain weight after transplantation is relatively common, also tends to be multifactorial and can be influenced by glucocorticoids and immunosuppressive medications, delayed graft function and cause serious health complications. OBJECTIVES: Assess changes in weight, degree of obesity and body mass index as well as the effect of immunosuppressive treatment over these 5 years after kidney transplantation. METHODS: The samples were 119 kidney transplant recipients, 70 men and 49 women, that attended the query post for five years. All patients were measured Pretransplant and post (from 1st year to the 5th year) weight, height and body mass index calculated by the formula weight/size2 relating it to immunosuppressive treatment taking. RESULTS: There is a considerable increase of body mass index, weight and degree of obesity in the first year after transplantation to increase more slowly in the next four years. The type of immunosuppressive treatment influence the weight and degree of obesity that occurs in this period of time. CONCLUSIONS: A high prevalence there are overweight and obesity after the transplant especially during the first year. A year patients earn an average of 6.6 kg in weight and an average of 2.5 kg/m2 in their BMI. During treatment should minimize doses of steroids and include dietary treatment and adequate physical exercise

Desarrollo de un cuadro de mando para una gran compañía

Una importante empresa, Indra, vino a nosotros para que desarrollaramos un cuadro de mando operativo para una de sus secciones.

The relationship between monocarboxylate transporters 1 and 4 expression in skeletal muscle and endurance performance in athletes

The purpose of this study was to examine the relationship between skeletal muscle monocarboxylate transporters 1 and 4 (MCT1 and MCT4) expression, skeletal muscle oxidative capacity and endurance performance in trained cyclists. Ten well-trained cyclists (mean +/- SD; age 24.4 +/- 2.8 years, body mass 73.2 +/- 8.3 kg, VO(2max) 58 +/- 7 ml kg(-1) min(-1)) completed three endurance performance tasks [incremental exercise test to exhaustion, 2 and 10 min time trial (TT)]. In addition, a muscle biopsy sample from the vastus lateralis muscle was analysed for MCT1 and MCT4 expression levels together with the activity of citrate synthase (CS) and 3-hydroxyacyl-CoA dehydrogenase (HAD). There was a tendency for VO(2max) and peak power output obtained in the incremental exercise test to be correlated with MCT1 (r = -0.71 to -0.74; P < 0.06), but not MCT4. The average power output (P (average)) in the 2 min TT was significantly correlated with MCT4 (r = -0.74; P < 0.05) and HAD (r = -0.92; P < 0.01). The P (average) in the 10 min TT was only correlated with CS activity (r = 0.68; P < 0.05). These results indicate the relationship between MCT1 and MCT4 as well as cycle TT performance may be influenced by the length and intensity of the task.

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Running versus strength-based warm-up : acute effects on isometric knee extension function

This study investigated the influence of two warm-up protocols on neural and contractile parameters of knee extensors. A series of neuromuscular tests including voluntary and electrically evoked contractions were performed before and after running- (R (WU); slow running, athletic drills, and sprints) and strength-based (S (WU); bilateral 90 degrees back squats, Olympic lifting movements and reactivity exercises) warm ups (duration ~40 min) in ten-trained subjects. The estimated overall mechanical work was comparable between protocols. Maximal voluntary contraction torque (+15.6%; P < 0.01 and +10.9%; P < 0.05) and muscle activation (+10.9 and +12.9%; P < 0.05) increased to the same extent after R (WU) and S (WU), respectively. Both protocols caused a significant shortening of time to contract (-12.8 and -11.8% after R (WU) and S (WU); P < 0.05), while the other twitch parameters did not change significantly. Running- and strength-based warm ups induce similar increase in knee extensors force-generating capacity by improving the muscle activation. Both protocols have similar effects on M-wave and isometric twitch characteristics.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

El lenguaje de la interrogación: una gramática formal para la recuperación de la información

El conocimiento del lenguaje de interrogación es una herramienta imprescindible para la recuperación de información. En este artículo se ofrece una gramática formal (sintaxis y semántica) para ese tipo de lenguaje. Esta gramática nos permite, por un lado, conocer el lenguaje de interrogación desde un plano sistemático y conceptual y, por otro lado, nos permite obtener ciertos beneficios prácticos de tipo sintáctico y de tipo semántico relacionados con los procesos de recuperación de información.

Vulnerabilities of fingerprint reader to fake fingerprints attacks

The purpose of this research is to assess the vulnerabilities of a high resolution fingerprint sensor when confronted with fake fingerprints. The study has not been focused on the decision outcome of the biometric device, but essentially on the scores obtained following the comparison between a query (genuine or fake) and a template using an AFIS system. To do this, fake fingerprints of 12 subjects have been produced with and without their cooperation. These fake fingerprints have been used alongside with real fingers. The study led to three major observations: First, genuine fingerprints produced scores higher than fake fingers (translating a closer proximity) and this tendency is observed considering each subject separately. Second, scores are however not sufficient as a single measure to differentiate these samples (fake from genuine) given the variation due to the donors themselves. That explains why fingerprint readers without vitality detection can be fooled. Third, production methods and subjects greatly influence the scores obtained for fake fingerprints.

Fructose and glucose co-ingestion during prolonged exercise increases lactate and glucose fluxes and oxidation compared with an equimolar intake of glucose

BACKGROUND: When fructose is ingested together with glucose (GLUFRU) during exercise, plasma lactate and exogenous carbohydrate oxidation rates are higher than with glucose alone. OBJECTIVE: The objective was to investigate to what extent GLUFRU increased lactate kinetics and oxidation rate and gluconeogenesis from lactate (GNG(L)) and from fructose (GNG(F)). DESIGN: Seven endurance-trained men performed 120 min of exercise at approximately 60% VOmax (maximal oxygen consumption) while ingesting 1.2 g glucose/min + 0.8 g of either glucose or fructose/min (GLUFRU). In 2 trials, the effects of glucose and GLUFRU on lactate and glucose kinetics were investigated with glucose and lactate tracers. In a third trial, labeled fructose was added to GLUFRU to assess fructose disposal. RESULTS: In GLUFRU, lactate appearance (120 +/- 6 mumol . kg(1) . min(1)), lactate disappearance (121 +/- 7 mumol . kg(1) . min(1)), and oxidation (127 +/- 12 mumol . kg(1) . min(1)) rates increased significantly (P < 0.001) in comparison with glucose alone (94 +/- 16, 95 +/- 16, and 97 +/- 16 mumol . kg(1) . min(1), respectively). GNG(L) was negligible in both conditions. In GLUFRU, GNG(F) and exogenous fructose oxidation increased with time and leveled off at 18.8 +/- 3.7 and 38 +/- 4 mumol . kg(1) . min(1), respectively, at 100 min. Plasma glucose appearance rate was significantly higher (P < 0.01) in GLUFRU (91 +/- 6 mumol . kg(1) . min(1)) than in glucose alone (82 +/- 9 mumol . kg(1) . min(1)). Carbohydrate oxidation rate was higher (P < 0.05) in GLUFRU. CONCLUSIONS: Fructose increased total carbohydrate oxidation, lactate production and oxidation, and GNG(F). Fructose oxidation was explained equally by fructose-derived lactate and glucose oxidation, most likely in skeletal and cardiac muscle. This trial was registered at clinicaltrials.gov as NCT01128647.

Documents : Dating a document

The determination of the age of a document is a very frequent query, however it is also one of the most challenging and controversial areas of questioned document examination. Several approaches were defined to address this problem. The first is based on the introduction date of raw constituents (like paper or ink) on the market. The second approach is based on the aging of documents, which is unfortunately not only influenced by passing time, but also by storage conditions and document composition. The third approach considers the relative age of documents and aims at reconstructing their chronology. The three approaches are equally complex to develop and encounter quantity of problems which are not negligible. This article aims to expose the potential applications and limitations of current ink dating methods. Method development and validation and the interpretation of evidence prove to be essential criteria for the dating of documents.

CATMA: a complete Arabidopsis GST database.

The Complete Arabidopsis Transcriptome Micro Array (CATMA) database contains gene sequence tag (GST) and gene model sequences for over 70% of the predicted genes in the Arabidopsis thaliana genome as well as primer sequences for GST amplification and a wide range of supplementary information. All CATMA GST sequences are specific to the gene for which they were designed, and all gene models were predicted from a complete reannotation of the genome using uniform parameters. The database is searchable by sequence name, sequence homology or direct SQL query, and is available through the CATMA website at http://www.catma.org/.

Mynodbcsv: Lightweight Zero-Config Database Solution for Handling Very Large CSV Files.

Volumes of data used in science and industry are growing rapidly. When researchers face the challenge of analyzing them, their format is often the first obstacle. Lack of standardized ways of exploring different data layouts requires an effort each time to solve the problem from scratch. Possibility to access data in a rich, uniform manner, e.g. using Structured Query Language (SQL) would offer expressiveness and user-friendliness. Comma-separated values (CSV) are one of the most common data storage formats. Despite its simplicity, with growing file size handling it becomes non-trivial. Importing CSVs into existing databases is time-consuming and troublesome, or even impossible if its horizontal dimension reaches thousands of columns. Most databases are optimized for handling large number of rows rather than columns, therefore, performance for datasets with non-typical layouts is often unacceptable. Other challenges include schema creation, updates and repeated data imports. To address the above-mentioned problems, I present a system for accessing very large CSV-based datasets by means of SQL. It's characterized by: "no copy" approach - data stay mostly in the CSV files; "zero configuration" - no need to specify database schema; written in C++, with boost [1], SQLite [2] and Qt [3], doesn't require installation and has very small size; query rewriting, dynamic creation of indices for appropriate columns and static data retrieval directly from CSV files ensure efficient plan execution; effortless support for millions of columns; due to per-value typing, using mixed text/numbers data is easy; very simple network protocol provides efficient interface for MATLAB and reduces implementation time for other languages. The software is available as freeware along with educational videos on its website [4]. It doesn't need any prerequisites to run, as all of the libraries are included in the distribution package. I test it against existing database solutions using a battery of benchmarks and discuss the results.

Vulnerabilities of Fingerprint Reader to Fake Fingerprint Attacks

The purpose of this research is to assess the vulnerabilities of a high resolution fingerprint sensor when confronted with fake fingerprints. The study has not been focused on the decision outcome of the biometric device, but essentially on the scores obtained following the comparison between a query (genuine or fake) and a template using an AFIS system. To do this, fake fingerprints of 12 subjects have been produced with and without their cooperation. These fake fingerprints have been used alongside with real fingers. The study led to three major observations: First, genuine fingerprints produced scores higher than fake fingers (translating a closer proximity) and this tendency is observed considering each subject separately. Second, scores are however not sufficient as a single measure to differentiate these samples (fake from genuine) given the variation due to the donors themselves. That explains why fingerprint readers without vitality detection can be fooled. Third, production methods and subjects greatly influence the scores obtained for fake fingerprints.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.