Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

QSAR Modeling of a Set of Pyrazinoate Esters as Antituberculosis Prodrugs

Tuberculosis is an infection caused mainly by Mycobacterium tuberculosis. A first-line antimycobacterial drug is pyrazinamide (PZA), which acts partially as a prodrug activated by a pyrazinamidase releasing the active agent, pyrazinoic acid (POA). As pyrazinoic acid presents some difficulty to cross the mycobacterial cell wall, and also the pyrazinamide-resistant strains do not express the pyrazinamidase, a set of pyrazinoic acid esters have been evaluated as antimycobacterial agents. In this work, a QSAR approach was applied to a set of forty-three pyrazinoates against M. tuberculosis ATCC 27294, using genetic algorithm function and partial least squares regression (WOLF 5.5 program). The independent variables selected were the Balaban index (I), calculated n-octanol/water partition coefficient (ClogP), van-der-Waals surface area, dipole moment, and stretching-energy contribution. The final QSAR model (N = 32, r(2) = 0.68, q(2) = 0.59, LOF = 0.25, and LSE = 0.19) was fully validated employing leave-N-out cross-validation and y-scrambling techniques. The test set (N = 11) presented an external prediction power of 73%. In conclusion, the QSAR model generated can be used as a valuable tool to optimize the activity of future pyrazinoic acid esters in the designing of new antituberculosis agents.

Identification of protein-coding and intronic noncoding RNAs down-regulated in clear cell renal carcinoma

The clear cell subtype of renal cell carcinoma (RCC) is the most lethal and prevalent cancer of the urinary system. To investigate the molecular changes associated with malignant transformation in clear cell RCC, the gene expression profiles of matched samples of tumor and adjacent non-neoplastic tissue were obtained from six patients. A custom-built cDNA microarray platform was used, comprising 2292 probes that map to exons of genes and 822 probes for noncoding RNAs mapping to intronic regions. Intronic transcription was detected in all normal and neoplastic renal tissues. A subset of 55 transcripts was significantly down-regulated in clear cell RCC relative to the matched nontumor tissue as determined by a combination of two statistical tests and leave-one-out patient cross-validation. Among the down-regulated transcripts, 49 mapped to untranslated or coding exons and 6 were intronic relative to known exons of protein-coding genes. Lower levels of expression of SIN3B, TRIP3, SYNJ2BP and NDE1 (P<0.02), and of intronic transcripts derived from SND1 and ACTN4 loci (P<0.05), were confirmed in clear cell RCC by Real-time RT-PCR. A subset of 25 transcripts was deregulated in additional six nonclear cell RCC samples, pointing to common transcriptional alterations in RCC irrespective of the histological subtype or differentiation state of the tumor. Our results indicate a novel set of tumor suppressor gene candidates, including noncoding intronic RNAs, which may play a significant role in malignant transformations of normal renal cells. (C) 2008 Wiley-Liss, Inc.

Spectral Region Optimization for Raman-Based Optical Biopsy of Inflammatory Lesions

Objective: The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. Background: Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. Methods: Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. Results: Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. Conclusions: The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.

PREDICTION OF FAT-FREE MASS BY BIOELECTRICAL IMPEDANCE ANALYSIS IN OLDER ADULTS FROM DEVELOPING COUNTRIES: A CROSS-VALIDATION STUDY USING THE DEUTERIUM DILUTION METHOD

Objective: Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method. Design and setting: Cross-sectional study of elderly from five developing countries. Methods: Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement. Results: FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht(2)/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R(2), total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r = 0.008 and p = 0.2). Conclusions: This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Total carbon measurement in whole tropical soil sample

Soils are an important component in the biogeochemical cycle of carbon, storing about four times more carbon than biomass plants and nearly three times more than the atmosphere. Moreover, the carbon content is directly related on the capacity of water retention, fertility. among other properties. Thus, soil carbon quantification in field conditions is an important challenge related to carbon cycle and global climatic changes. Nowadays. Laser Induced Breakdown Spectroscopy (LIBS) can be used for qualitative elemental analyses without previous treatment of samples and the results are obtained quickly. New optical technologies made possible the portable LIBS systems and now, the great expectation is the development of methods that make possible quantitative measurements with LIBS. The goal of this work is to calibrate a portable LIBS system to carry out quantitative measures of carbon in whole tropical soil sample. For this, six samples from the Brazilian Cerrado region (Argisoil) were used. Tropical soils have large amounts of iron in their compositions, so the carbon line at 247.86 nm presents strong interference of this element (iron lines at 247.86 and 247.95). For this reason, in this work the carbon line at 193.03 nm was used. Using methods of statistical analysis as a simple linear regression, multivariate linear regression and cross-validation were possible to obtain correlation coefficients higher than 0.91. These results show the great potential of using portable LIBS systems for quantitative carbon measurements in tropical soils. (C) 2008 Elsevier B.V. All rights reserved.

Prevalência de excesso de peso e obesidade e fatores associados, Brasil, 2006

OBJETIVO: Estimar a prevalência de excesso de peso e obesidade e fatores associados. MÉTODOS: Foram analisados dados referentes a indivíduos com idade >18 anos entrevistados pelo sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico (VIGITEL), realizado nas capitais brasileiras e Distrito Federal em 2006. Para 49.395 indivíduos, o índice de massa corporal (IMC) foi utilizado para identificar excesso de peso (IMC 25-30 kg/m²) e obesidade (IMC >30 kg/m²). Prevalência e razões de prevalência foram apresentadas segundo variáveis sociodemográficas, escolaridade e condição de saúde/comorbidades e auto-avaliação da saúde, estratificadas por sexo. Utilizou-se regressão de Poisson para análises brutas e ajustadas por idade. RESULTADOS: A prevalência de excesso de peso foi de 47% para os homens e 39% para as mulheres, e de obesidade, 11% para ambos os sexos. Observou-se associação direta entre excesso de peso e escolaridade entre homens, e associação inversa entre mulheres. Obesidade foi mais freqüente entre os homens que viviam com companheira e não esteve associada com escolaridade ou cor da pele. As prevalências de excesso de peso e obesidade foram mais altas entre mulheres negras e que viviam com companheiro. A presença de diabetes, hipertensão arterial sistêmica e dislipidemias, bem como considerar sua saúde como regular ou ruim, também foram referidas pelos entrevistados com excesso de peso ou obesidade. CONCLUSÕES: Enquanto cerca de um de cada dois entrevistados foram classificados com excesso de peso, obesidade foi referida por um de cada dez entrevistados. Variáveis socioeconômicas e demográficas, bem como morbidades referidas, foram associadas com excesso de peso e obesidade. Esses resultados foram similares àqueles encontrados em outros estudos brasileiros.

Spatial Modeling of a Soil Fertility Index using Visible-Near-Infrared Spectra and Terrain Attributes

Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.

Synthesis of 5-alkynyl-2,2,6-trimethyl-1,3-dioxin-4-ones and 1,4-disubstituted-1,2,3-triazoles

Herein we report an approach to the formation of 5-alkynyl-1,3-dioxin-4-ones using Suzuki-Miyaura cross-coupling reaction of potassium alkynyltrifluoroborate salts with 2,2,6-trimethy1-5-iodo-1,3-dioxin-4-one. The resulting 5-ethynyltrimethylsilyl-1,3-dioxin-4-ones obtained through the Sonogashira reaction were further reacted in a Cu(I)-catalyzed Huisgen azide-alkyne 1,3-dipolar cycloaddition to form functionalized 1,4-disubstituted-1,2,3-triazoles in good yields, using mild conditions and ultrasonic radiation to expedite the reaction. (C) 2011 Elsevier Ltd. All rights reserved.

Quetiapine versus clomipramine in the augmentation of selective serotonin reuptake inhibitors for the treatment of obsessive-compulsive disorder: a randomized, open-label trial

After 12 weeks of selective serotonin reuptake inhibitor (SSRI) monotherapy with inadequate response, 10 patients received clomipramine and 11 received quetiapine as augmentation agents of the SSRI. The primary outcome measure was the difference between initial and final scores of the YaleBrown Obsessive-Compulsive Scale (Y-BOCS), rated in a blinded fashion, and the score of clinical global improvement (CGI-I). Statistical analyses were performed using nonparametric tests to evaluate treatment efficacy and the difference between treatment groups. Percentile plots were constructed with YBOCS scores from the clomipramine and quetiapine groups. Considering response a >= 35% reduction in the initial Y-BOCS score plus a rating of `much improved` or `very much improved` on CGI-I, four of eleven quetiapine patients and one out of ten clomipramine patients were classified as responders. The mean final Y-BOCS score was significantly lower than baseline in the quetiapine augmentation group (P = 0.023), but not in the clomipramine augmentation group (P = 0.503). The difference between groups showed a trend towards significance only at week 4, the mean Y-BOCS score being lower for those receiving quetiapine (P = 0.052). A difference between groups was also observed at week 4 according to percentile plots. These results corroborate previous findings of quetiapine augmentation efficacy in obsessive-compulsive disorder (OCD). Clomipramine augmentation did not produce a significant reduction in Y-BOCS scores. Higher target maximum dosages might have yielded different results.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Drug-resistant tuberculosis in six hospitals in Rio de Janeiro, Brazil

SETTING: Tuberculosis (TB) drug resistance survey in six hospitals in Rio de Janeiro, Brazil. OBJECTIVE: To estimate resistance to at least one drug (DR) and multidrug resistance (MDR) and identify associated factors. DESIGN: One-year cross-sectional survey. Hospitals were included as a convenience sample. RESULTS: Of 595 patients investigated, 156 (26.2%) had previously undergone anti-tuberculosis treatment, 433 (72.8%) were not previously treated and information on the remaining 6 was not available. Overall, DR and MDR rates were high, at respectively 102 (17.1%, 95%CI 14.3-20.5) and 44 (7.4%, 95%CI 5.5-9.9) cases. Among individuals not previously treated, 17 had MDR (3.9%, 95%CI 2.4-6.3) and diagnosis in a TB reference hospital was independently associated with MDR (prevalence ratio [PR] 3.3, 95%CI 1.2-8.7) after multivariate analysis. Among previously treated individuals, 27 had MDR (17.3%, 95%CI 11.7-24.2). MDR-TB was independently associated with diagnosis in a TB reference hospital (PR 3.6, 95%CI 1.5-8.7), male sex (PR 2.3,95%CI 1.2-4.4) and dyspnoea (PR 0.3, 95%CI 0.1-0.7). CONCLUSION: We found high levels of DR- and MDR-TB. Our study design did not permit us to determine the contribution of community versus nosocomial transmission. Further studies are needed to establish this. Nevertheless, hospitals should be recognised as a potential source of transmission of resistant TB strains and urgent measures to avoid nosocomial TB transmission should be taken.

Degenerate Two-Photon Absorption in All-Trans Retinal: Nonlinear Spectrum and Theoretical Calculations

In this work we investigate the degenerate two-photon absorption spectrum of all-trans retinal ill ethanol employing the Z-scan technique with femtosecond pulses, The two-photon absorption (2PA) spectrum presents a monotonous increase as the excitation wavelength approaches the one-photon absorption band and it peak at 790 nm. We attribute the 2PA hand to the mixing of states (1)B(u)+-like and vertical bar S(1)>, which are strongly allowed by one- and two-photon, respectively. We modeled the 2PA spectrum by using the sum-over-states approach and obtained spectroscopic parameters of the electronic transitions to vertical bar S >, vertical bar S(2)> (""(1)Bu(+)""), vertical bar S(3)>, and vertical bar S(4)> singlet-excited states. The results were compared with theoretical predictions of one- and two-photon transition calculations using the response Functions formalism within the density functional theory framework with the aid of the CAM-B3LYP functional.

Cross-cultural adaptation, validation and reliability of the Body Area Scale for Brazilian adolescents

The aim of this study was to translate, validate and verify the reliability of the Body Area Scale (BAS). Participants were 386 teenagers, enrolled in a private school. Translation into Portuguese was conducted. The instrument was evaluated for internal consistency and construct validation analysis. Reproducibility was evaluated using the Wilcoxon test and the coefficient of interclass correlation. The BAS demonstrated good values for internal consistency (0.90 and 0.88) and was able to discriminate boys and girls according to nutritional state (p = 0.020 and p = 0.026, respectively). BAS scores correlated with adolescents' BMI (r = 0.14, p = 0.055; r = 0.23, p = 0.001) and WC (r =0.13, p = 0.083; r = 0.22, 0.002). Reliability was confirmed by the coefficient of inter-class correlation (0.35, p < 0.001; 0.60, p < 0.001) for boys and girls, respectively. The instrument performed well in terms of understanding and time of completion. BAS was successfully translated into Portuguese and presented good validity when applied to adolescents.