Translation to Portuguese and Validation of the Douleur Neuropathique 4 Questionnaire

The Douleur Neuropathique 4 (DN4) questionnaire was developed by the French Neuropathic Pain Group and is a simple and objective tool, with the ability to distinguish nociceptive from neuropathic pain. The purpose of this work was to validate the DN4 questionnaire in the Portuguese language in order to allow its use in clinical and research settings. A double-blind, accuracy study was conducted, consisting of translation, back-translation, literal evaluation, semantic equivalence, and communication with the target population. The Portuguese version of the questionnaire was applied in a sample of 101 patients with neuropathic (N = 42) or nociceptive pain (N = 59), ranked according to medical diagnosis. The reproducibility, reliability and validity of the instrument were analyzed, and showed a high diagnostic power for this version of the DN4 questionnaire. The Portuguese version of the DN4 questionnaire presented good validity and reliability, allowing it to identify neuropathic pain and neuropathic characteristics of mixed pain syndromes. Perspective: This article presents the first validated neuropathic pain questionnaire in the Portuguese language and represents a useful tool in the assessment of neuropathic pain both in the clinical setting and in population-based studies. The sensible and quick format of this instrument are key factors that will contribute to its widespread use, permitting a true recognition of patients with neuropathic pain. (C) 2010 by the American Pain Society

Acute hyperglycemia rapidly stimulates VEGF mRNA translation in the kidney. Role of angiotensin type 2 receptor (AT2)

Angiotensin II (Ang II) and vascular endothelial growth factor (VEGF) are important mediators of kidney injury in diabetes. Acute hyperglycemia increased synthesis of intrarenal Ang I and Ang II and resulted in activation of both Ang II receptors, AT1 and AT2, in the kidney. Losartan (specific AT1 antagonist) or PD123319 (specific AT2 antagonist) did not affect hyperglycemia but prevented activation of renal AT1 and AT2, respectively. In murine renal cortex, acute hyperglycemia increased VEGF protein but not mRNA content after 24 h, which suggested translational regulation. Blockade of AT2, but not AT1, prevented increase in VEGF synthesis by inhibiting translation of VEGF mRNA in renal cortex. Acute hyperglycemia increased VEGF expression in wild type but not in AT2 knockout mice. Binding of heterogeneous nuclear ribonucleoprotein K to VEGF mRNA, which stimulates its translation, was prevented by blockade of AT2, but not AT1. The Akt-mTOR-p70(S6K) signaling pathway, involved in the activation of mRNA translation, was activated in hyperglycemic kidneys and was blocked by the AT2 antagonist. Elongation phase is an important step of mRNA translation that is controlled by elongation factor 1A (eEF1A) and 2 (eEF2). Expression of eEF1A and activity of eEF2 was higher in kidney cortex from hyperglycemic mice and only the AT2 antagonist prevented these changes. To assess selectivity of translational control of VEGF expression, we measured expression of fibronectin (FN) and laminin beta 1 (lam beta 1): acute hyperglycemia increased FN expression at both protein and mRNA levels, indicating transcriptional control, and did not affect the expression of lam beta 1. To confirm results obtained with PD123319, we induced hyperglycemia in AT2 knockout mice and found that in the absence of AT2, translational control of VEGF expression by hyperglycemia was abolished. Our data show that acute hyperglycemia stimulates Ang II synthesis in murine kidney cortex, this leads to AT2 activation and stimulation of VEGF mRNA translation, via the Akt-mTOR-p70(S6K) signaling pathway. Our data show that exclusive translational control of protein expression in the kidney by acute hyperglycemia is not a general phenomenon, but do not prove that it is restricted to VEGF. (C) 2010 Elsevier Inc. All rights reserved.

Translation and Cross-Cultural Adaptation of the Brazilian Version of the International Knee Documentation Committee Subjective Knee Form Validity and Reproducibility

Background: The perception of improvement by a patient has assumed a central role in functional evaluation after a variety of knee problems. One of the instruments most used in clinical research is the International Knee Documentation Committee (IKDC) Subjective Knee Form because its psychometric properties are considered to be excellent. Nonetheless, this questionnaire was originally developed for use in the English language. Therefore, to use this questionnaire in the Brazilian population, it is essential to translate and validate it. Purpose: The aim of this study was to translate the IKDC Subjective Knee Form into a Brazilian version and to test its validity and reproducibility. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: The translation of the original IKDC Subjective Knee Form into a Brazilian version was accomplished in accordance with the American Orthopaedic Society for Sports Medicine guidelines and was tested in 32 patients with knee pathologic conditions to develop the first Brazilian version. To test validity and reproducibility, 117 patients with several knee complaints completed the Brazilian IKDC Subjective Knee Form, the Short Form 36 (SF-36), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Lysholm score. From these patients, 85 were retested within a week to achieve reproducibility. The validation was addressed by correlating the Brazilian IKDC Subjective Knee Form to the other outcome measures. The reproducibility was tested by measuring internal consistency, test-retest reliability, and agreement. Results: The Brazilian IKDC Subjective Knee Form was highly related to the physical component summary of the SF-36, the Lysholm score, and the WOMAC, and weakly related to the mental component summary of SF-36 (r=.79, .89, .85, and .51, respectively). The internal consistency was strong, with a Cronbach a value of .928 and .935 in the test and retest assessment, respectively. The test-retest reliability proved to be excellent, with a high value of the intraclass correlation coefficient (.988), as well as the agreement, demonstrated by the low differences between the means of the test and retest, and the short limit of agreement, observed in the Altman-Bland and survival-agreement plots. Conclusion: The results of this study provide evidence that the Brazilian IKDC Subjective Knee Form has psychometric properties similar to the original version. In addition, it was a reliable evaluation instrument for patients with knee-related problems.

Evidences of a Role for Eukaryotic Translation Initiation Factor 5A (eIF5A) in Mouse Embryogenesis and Cell Differentiation

Eukaryotic translation initiation factor 5A (eIF5A) has a unique character: the presence of an unusual amino acid, hypusine, which is formed by post-translational modifications. Even before the identification of hypusination in eIF5A, the correlation between hypusine formation and protein synthesis, shifting cell proliferation rates, had already been observed. Embryogenesis is a complex process in which cellular proliferation and differentiation are intense. In spite of the fact that many studies have described possible functions for eIF5A, its precise role is under investigation, and to date nothing has been reported about its participation in embryonic development. In this study we show that eIF5A is expressed at all mouse embryonic post-implantation stages with increase in eIF5A mRNA and protein expression levels between embryonic days E10.5 and E13.5. Immunohistochemistry revealed the ubiquitous presence of eIF5A in embryonic tissues and organs at E13.5 day. Interestingly, stronger immunoreactivity to eIF5A was observed in the stomodeum, liver, ectoderm, heart, and eye, and the central nervous system; regions which are known to undergo active differentiation at this stage, suggesting a role of eIF5A in differentiation events. Expression analyses of MyoD, a myogenic transcription factor, revealed a significantly higher expression from day E12.5 on, both at the mRNA and the protein levels suggesting a possible correlation to eIF5A. Accordingly, we next evidenced that inhibiting eIF5A hypusination in mouse myoblast C2C12 cells impairs their differentiation into myotubes and decreases MyoD transcript levels. Those results point to a new functional role for eIF5A, relating it to embryogenesis, development, and cell differentiation. J. Cell. Physiol. 225: 500-505, 2010. (C) 2010 Wiley-Liss, Inc.

Insights on eukaryotic translation initiation factor 5A (eIF5A) in the brain and aging

Long-term memory, a persistent form of synaptic plasticity, requires translation of a subset of mRNA present in neuronal dendrites during a short and critical period through a mechanism not yet fully elucidated. Western blotting analysis revealed a high content of eukaryotic translation initiation factor 5A (eIF5A) in the brain of neonatal rats, a period of intense neurogenesis rate, differentiation and synaptic establishment, when compared to adult rats. Immunohistochemistry analysis revealed that eIF5A is present in the whole brain of adult rats showing a variable content among the cells from different areas (e.g. cortex, hippocampus and cerebellum). A high content of eIF5A in the soma and dendrites of Purkinje cells, key neurons in the control of motor long-term memory in the cerebellum, was observed. Detection of high eIF5A content was revealed in dendritic varicosities of Purkinje cells. Evidence is presented herein that a reduction of eIF5A content is associated to brain aging. (C) 2008 Elsevier B.V. All rights reserved.

T3 acutely increases GH mRNA translation rate and GH secretion in hypothyroid rats

Cytoskeleton controls the stability of transcripts, by mechanisms that involve mRNAs and eEF1A attachment to it. Besides, it plays a key role in protein synthesis and secretion, which seems to be impaired in somatotrophs of hypothyroid rats, whose cytoskeleton is disarranged. This study investigated the: eEF1A and GH mRNA binding to cytoskeleton plus GH mRNA translation rate and GH secretion, in sham-operated and thyroidectomized rats treated with T3 or saline, and killed 30 min thereafter. Thyroidectomy reduced: (a) pituitary F-actin content, and eEF1A plus GH mRNA binding to it; (b) GH mRNA recruitment to polysome; and (c) liver IGF-1 mRNA expression, indicating that GH mRNA stability and translation rate, as well as GH secretion were impaired. T3 acutely reversed all these changes, which points toward a nongenomic action of T3 on cytoskeleton rearrangement, which might contribute to the increase on GH mRNA translation rate and GH secretion. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Posttranscriptional regulation of sodium-iodide symporter mRNA expression in the rat thyroid gland by acute iodide administration

Serrano-Nascimento C, Calil-Silveira J, Nunes MT. Posttranscriptional regulation of sodium-iodide symporter mRNA expression in the rat thyroid gland by acute iodide administration. Am J Physiol Cell Physiol 298: C893-C899, 2010. First published January 27, 2010; doi:10.1152/ajpcell.00224.2009.-Iodide is an important regulator of thyroid activity. Its excess elicits the Wolff-Chaikoff effect, characterized by an acute suppression of thyroid hormone synthesis, which has been ascribed to serum TSH reduction or TGF-beta increase and production of iodolipids in the thyroid. These alterations take hours/days to occur, contrasting with the promptness of Wolff-Chaikoff effect. We investigated whether acute iodide administration could trigger events that precede those changes, such as reduction of sodium-iodide symporter (NIS) mRNA abundance and adenylation, and if perchlorate treatment could counteract them. Rats subjected or not to methylmercaptoimidazole treatment (0.03%) received NaI (2,000 mu g/0.5 ml saline) or saline intraperitoneally and were killed 30 min up to 24 h later. Another set of animals was treated with iodide and perchlorate, in equimolar doses. NIS mRNA content was evaluated by Northern blotting and real-time PCR, and NIS mRNA poly(A) tail length by rapid amplification of cDNA ends-poly(A) test (RACE-PAT). We observed that NIS mRNA abundance and poly(A) tail length were significantly reduced in all periods of iodide treatment. Perchlorate reversed these effects, indicating that iodide was the agent that triggered the modifications observed. Since the poly(A) tail length of mRNAs is directly associated with their stability and translation efficiency, we can assume that the rapid decay of NIS mRNA abundance observed was due to a reduction of its stability, a condition in which its translation could be impaired. Our data show for the first time that iodide regulates NIS mRNA expression at posttranscriptional level, providing a new mechanism by which iodide exerts its autoregulatory effect on thyroid.

Involvement of Eukaryotic Translation Initiation Factor 5A (eIF5A) in Skeletal Muscle Stem Cell Differentiation

The eukaryotic translation initiation factor 5A (eIF5A) contains a special amino acid residue named hypusine that is required for its activity, being produced by a post-translational modification using spermidine as substrate. Stem cells from rat skeletal muscles (satellite cells) were submitted to differentiation and an increase of eIF5A gene expression was observed. Higher content of eIF5A protein was found in satellite cells on differentiation in comparison to non-differentiated satellite cells and skeletal muscle. The treatment with NI-guanyl- 1,7-diaminoheptane (GC7), a hypusination inhibitor, reversibly abolished the differentiation process. In association with the differentiation blockage, an increase of glucose consumption and lactate production and a decrease of glucose and palmitic acid oxidation were observed. A reduction in cell proliferation and protein synthesis was also observed. L-Arginine, a spermidine precursor and partial suppressor of muscle dystrophic phenotype, partially abolished the GC7 inhibitory effect on satellite cell differentiation. These results reveal a new physiological role for eIF5A and contribute to elucidate the molecular mechanisms involved in muscle regeneration.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Comparing finite state machine test coverage criteria

To plan testing activities, testers face the challenge of determining a strategy, including a test coverage criterion that offers an acceptable compromise between the available resources and test goals. Known theoretical properties of coverage criteria do not always help and, thus, empirical data are needed. The results of an experimental evaluation of several coverage criteria for finite state machines (FSMs) are presented, namely, state and transition coverage; initialisation fault and transition fault coverage. The first two criteria focus on FSM structure, whereas the other two on potential faults in FSM implementations. The authors elaborate a comparison approach that includes random generation of FSM, construction of an adequate test suite and test minimisation for each criterion to ensure that tests are obtained in a uniform way. The last step uses an improved greedy algorithm.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Structural modeling and mutational analysis of yeast eukaryotic translation initiation factor 5A reveal new critical residues and reinforce its involvement in protein synthesis

Eukaryotic translation initiation factor 5A (eIF5A) is a protein that is highly conserved and essential for cell viability. This factor is the only protein known to contain the unique and essential amino acid residue hypusine. This work focused on the structural and functional characterization of Saccharomyces cerevisiae eIF5A. The tertiary structure of yeast eIF5A was modeled based on the structure of its Leishmania mexicana homologue and this model was used to predict the structural localization of new site-directed and randomly generated mutations. Most of the 40 new mutants exhibited phenotypes that resulted from eIF-5A protein-folding defects. Our data provided evidence that the C-terminal alpha-helix present in yeast eIF5A is an essential structural element, whereas the eIF5A N-terminal 10 amino acid extension not present in archaeal eIF5A homologs, is not. Moreover, the mutants containing substitutions at or in the vicinity of the hypusine modification site displayed nonviable or temperature-sensitive phenotypes and were defective in hypusine modification. Interestingly, two of the temperature-sensitive strains produced stable mutant eIF5A proteins - eIF5A(K56A) and eIF5A(Q22H,L93F)- and showed defects in protein synthesis at the restrictive temperature. Our data revealed important structural features of eIF5A that are required for its vital role in cell viability and underscored an essential function of eIF5A in the translation step of gene expression.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

Multilevel Training of Binary Morphological Operators

The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results.