Artificial Gait In Complete Spinal Cord Injured Subjects: How To Assess Clinical Performance.

Objective Adapt the 6 minutes walking test (6MWT) to artificial gait in complete spinal cord injured (SCI) patients aided by neuromuscular electrical stimulation. Method Nine male individuals with paraplegia (AIS A) participated in this study. Lesion levels varied between T4 and T12 and time post injured from 4 to 13 years. Patients performed 6MWT 1 and 6MWT 2. They used neuromuscular electrical stimulation, and were aided by a walker. The differences between two 6MWT were assessed by using a paired t test. Multiple r-squared was also calculated. Results The 6MWT 1 and 6MWT 2 were not statistically different for heart rate, distance, mean speed and blood pressure. Multiple r-squared (r2 = 0.96) explained 96% of the variation in the distance walked. Conclusion The use of 6MWT in artificial gait towards assessing exercise walking capacity is reproducible and easy to apply. It can be used to assess SCI artificial gait clinical performance.

Classificação e padronização dos tomates cv. Carmem e Débora dentro da CEAGESP - SP

The creation of the Brazilian Program for the Modernization of the Horticulture by the Secretariat of Agriculture and Supplying of the State of São Paulo at CEAGESP, determined the standardization of fruit and vegetables in the follow aspects: degree of coloration, format, calibers, defects and packing. Therefore, the main goal of this research is to correlate the classification given by the Brazilian Program with the one used by the wholesalers at CEAGESP, verifying if the established norms are being fulfilled for cultivar Carmen and Debora (SAKATA SEED). The results showed, that for cultivar Carmem, for the averages of the observed values it does not move away from the norms created by the Program for sizes small and medium. However, for the case of cultivar Debora, the results showed differences between the adopted classifications. The tomatoes were devaluated, because had been commercialized below of the standardization indicated for the Brazilian Program.

Basquetebol masculino paulista : apropriação das caracteristicas do esporte profissional na estrutura organizacional das categorias de base

Universidade Estadual de Campinas . Faculdade de Educação Física

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Clustering Of Water Bodies In Unpolluted And Polluted Environments Based On Escherichia Coli Phylogroup Abundance Using A Simple Interaction Database.

Different types of water bodies, including lakes, streams, and coastal marine waters, are often susceptible to fecal contamination from a range of point and nonpoint sources, and have been evaluated using fecal indicator microorganisms. The most commonly used fecal indicator is Escherichia coli, but traditional cultivation methods do not allow discrimination of the source of pollution. The use of triplex PCR offers an approach that is fast and inexpensive, and here enabled the identification of phylogroups. The phylogenetic distribution of E. coli subgroups isolated from water samples revealed higher frequencies of subgroups A1 and B23 in rivers impacted by human pollution sources, while subgroups D1 and D2 were associated with pristine sites, and subgroup B1 with domesticated animal sources, suggesting their use as a first screening for pollution source identification. A simple classification is also proposed based on phylogenetic subgroup distribution using the w-clique metric, enabling differentiation of polluted and unpolluted sites.

Didanosine-loaded Chitosan Microspheres Optimized By Surface-response Methodology: A Modified Maximum Likelihood Classification" Approach Formulation For Reverse Transcriptase Inhibitors."

Didanosine-loaded chitosan microspheres were developed applying a surface-response methodology and using a modified Maximum Likelihood Classification. The operational conditions were optimized with the aim of maintaining the active form of didanosine (ddI), which is sensitive to acid pH, and to develop a modified and mucoadhesive formulation. The loading of the drug within the chitosan microspheres was carried out by ionotropic gelation technique with sodium tripolyphosphate (TPP) as cross-linking agent and magnesium hydroxide (Mg(OH)2) to assure the stability of ddI. The optimization conditions were set using a surface-response methodology and applying the Maximum Likelihood Classification, where the initial chitosan concentration, TPP and ddI concentration were set as the independent variables. The maximum ddI-loaded in microspheres (i.e. 1433mg of ddI/g chitosan), was obtained with 2% (w/v) chitosan and 10% TPP. The microspheres depicted an average diameter of 11.42μm and ddI was gradually released during 2h in simulated enteric fluid.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Ssr-based Genetic Diversity And Structure Of Garlic Accessions From Brazil.

Garlic is a spice and a medicinal plant; hence, there is an increasing interest in 'developing' new varieties with different culinary properties or with high content of nutraceutical compounds. Phenotypic traits and dominant molecular markers are predominantly used to evaluate the genetic diversity of garlic clones. However, 24 SSR markers (codominant) specific for garlic are available in the literature, fostering germplasm researches. In this study, we genotyped 130 garlic accessions from Brazil and abroad using 17 polymorphic SSR markers to assess the genetic diversity and structure. This is the first attempt to evaluate a large set of accessions maintained by Brazilian institutions. A high level of redundancy was detected in the collection (50 % of the accessions represented eight haplotypes). However, non-redundant accessions presented high genetic diversity. We detected on average five alleles per locus, Shannon index of 1.2, HO of 0.5, and HE of 0.6. A core collection was set with 17 accessions, covering 100 % of the alleles with minimum redundancy. Overall FST and D values indicate a strong genetic structure within accessions. Two major groups identified by both model-based (Bayesian approach) and hierarchical clustering (UPGMA dendrogram) techniques were coherent with the classification of accessions according to maturity time (growth cycle): early-late and midseason accessions. Assessing genetic diversity and structure of garlic collections is the first step towards an efficient management and conservation of accessions in genebanks, as well as to advance future genetic studies and improvement of garlic worldwide.

Diagnosis, Treatment, And Follow-up Of Medullary Thyroid Carcinoma: Recommendations By The Thyroid Department Of The Brazilian Society Of Endocrinology And Metabolism.

Medullary thyroid carcinoma (MTC) originates in the thyroid parafollicular cells and represents 3-4% of the malignant neoplasms that affect this gland. Approximately 25% of these cases are hereditary due to activating mutations in the REarranged during Transfection (RET) proto-oncogene. The course of MTC is indolent, and survival rates depend on the tumor stage at diagnosis. The present article describes clinical evidence-based guidelines for the diagnosis, treatment, and follow-up of MTC. The aim of the consensus described herein, which was elaborated by Brazilian experts and sponsored by the Thyroid Department of the Brazilian Society of Endocrinology and Metabolism, was to discuss the diagnosis, treatment, and follow-up of individuals with MTC in accordance with the latest evidence reported in the literature. After clinical questions were elaborated, the available literature was initially surveyed for evidence in the MedLine-PubMed database, followed by the Embase and Scientific Electronic Library Online/Latin American and Caribbean Health Science Literature (SciELO/Lilacs) databases. The strength of evidence was assessed according to the Oxford classification of evidence levels, which is based on study design, and the best evidence available for each question was selected. Eleven questions corresponded to MTC diagnosis, 8 corresponded to its surgical treatment, and 13 corresponded to follow-up, for a total of 32 recommendations. The present article discusses the clinical and molecular diagnosis, initial surgical treatment, and postoperative management of MTC, as well as the therapeutic options for metastatic disease. MTC should be suspected in individuals who present with thyroid nodules and family histories of MTC, associations with pheochromocytoma and hyperparathyroidism, and/or typical phenotypic characteristics such as ganglioneuromatosis and Marfanoid habitus. Fine-needle nodule aspiration, serum calcitonin measurements, and anatomical-pathological examinations are useful for diagnostic confirmation. Surgery represents the only curative therapeutic strategy. The therapeutic options for metastatic disease remain limited and are restricted to disease control. Judicious postoperative assessments that focus on the identification of residual or recurrent disease are of paramount importance when defining the follow-up and later therapeutic management strategies.

[the New Classification Of Breast Cancers: Finding The Luminal A].

To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.

On The Consistency Of Monte Carlo Track Structure Dna Damage Simulations.

Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies. The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV-220 keV were superimposed on a geometric DNA model composed of 2.7 × 10(6) nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy ETH. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands. Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when ETH ≈ 10.79 eV, but deviate significantly for higher ETH values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors' show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared. MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.

The Robson Ten-group Classification System For Appraising Deliveries At A Tertiary Referral Hospital In Brazil.

To evaluate the distribution of women according to the Robson 10-group classification system (RTGCS) and the occurrence of severe maternal morbidity (SMM) by mode of delivery at a tertiary referral hospital. A retrospective cross-sectional study was conducted of all women admitted to the Women's Hospital at the University of Campinas (Campinas, Brazil) for delivery between January 2009 and July 2013. Women were grouped according to RTGCS. Mode of delivery and SMM (defined as need for admission to the intensive care unit) were assessed. Among 12 771 women, 5957 (46.6%) delivered by cesarean. Overall, 3594 (28.1%) women were in group 1 (nulliparous, single pregnancy, cephalic, term, spontaneous labor), 2328 (18.2%) in group 5 (≥1 previous cesarean, single pregnancy, cephalic, term), and 2112 (16.5%) in group 3 (multiparous excluding previous cesarean, single pregnancy, cephalic, term, spontaneous labor). Group 5 contributed the most cesarean deliveries (1626 [27.3%]), followed by group 2 (nulliparous, single pregnancy, cephalic, term, induced labor or cesarean before labor; 1049 [17.6%]). SMM was more common among women undergoing cesarean delivery than among those delivering vaginally in groups 1-5. The RTGCS allowed the identification of groups with the highest frequency of cesarean delivery and an assessment of SMM. This should be considered in related health policies.

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.