Estimation of hexenuronic acids and kappa number in kraft pulps of Eucalyptus globulus by Fourier transform near infrared spectroscopy and multivariate analysis

Fourier transform near infrared (FT-NIR) spectroscopy was evaluated as an analytical too[ for monitoring residual Lignin, kappa number and hexenuronic acids (HexA) content in kraft pulps of Eucalyptus globulus. Sets of pulp samples were prepared under different cooking conditions to obtain a wide range of compound concentrations that were characterised by conventional wet chemistry analytical methods. The sample group was also analysed using FT-NIR spectroscopy in order to establish prediction models for the pulp characteristics. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of PCR or PLS algorithms. Calibration curves were built by using all the spectral data or selected regions. Best calibration models for the quantification of lignin, kappa and HexA were proposed presenting R-2 values of 0.99. Calibration models were used to predict pulp titers of 20 external samples in a validation set. The lignin concentration and kappa number in the range of 1.4-18% and 8-62, respectively, were predicted fairly accurately (standard error of prediction, SEP 1.1% for lignin and 2.9 for kappa). The HexA concentration (range of 5-71 mmol kg(-1) pulp) was more difficult to predict and the SEP was 7.0 mmol kg(-1) pulp in a model of HexA quantified by an ultraviolet (UV) technique and 6.1 mmol kg(-1) pulp in a model of HexA quantified by anion-exchange chromatography (AEC). Even in wet chemical procedures used for HexA determination, there is no good agreement between methods as demonstrated by the UV and AEC methods described in the present work. NIR spectroscopy did provide a rapid estimate of HexA content in kraft pulps prepared in routine cooking experiments.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

Impact of cancer-related symptom synergisms on health-related quality of life and performance status

To identify the impact of multiple symptoms and their co-occurrence on health-related quality of life (HRQOL) dimensions and performance status (PS), 115 outpatients with cancer, who were not receiving active cancer treatment and were recruited from, a university hospital in Sao Paulo, Brazil completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30, the Beck Depression Inventory, and the Brief Pain Inventory. Karnofsky Performance Status scores also were completed. Application of TwoStep Cluster analysis resulted in two distinct patient subgroups based on 113 patient experiences with pain, depression, fatigue, insomnia, constipation, lack of appetite, dyspnea, nausea, vomiting, and diarrhea. One group had multiple and severe symptom subgroup and another had Less symptoms and with lower severity. Multiple and severe symptoms had worse PS, role functioning, and physical, emotional, cognitive, social, and overall HRQOL. Multiple and severe symptom subgroup was also six times as likely as lower severity to have poor role functioning;five times more likely to have poor emotional;four times more likely to have poor PS, physical, and overall HRQOL, and three times as likely to have poor cognitive and social HRQOL, independent of gender, age, level of education, and economic condition. Classification and Regression Tree analyses were undertaken to identify which co-occurring symptoms would best determine reduction in HRQOL and PS. Pain and fatigue were identified as indicators of reduction on physical HRQOL and PS. Fatigue and insomnia were associated with reduction in cognitive; depression and pain in social; and fatigue and constipation in role functioning. Only depression was associated with reduction in overall HRQOL. These data demonstrate that there is a synergic effect among distinct cancer symptoms that result in reduction in HRQOL dimensions and PS.

Mercury Exposure Increases Circulating Net Matrix Metalloproteinase (MMP)-2 and MMP-9 Activities

Mercury (Hg) exposure causes health problems that may result from increased oxidative stress and matrix metalloproteinase (MMP) levels. We investigated whether there is an association between the circulating levels of MMP-2, MMP-9, their endogenous inhibitors (the tissue inhibitors of metalloproteinases; TIMPs) and the circulating Hg levels in 159 subjects environmentally exposed to Hg. Blood and plasma Hg were determined by inductively coupled plasma-mass spectrometry (ICP-MS). MMP and TIMP concentrations were measured in plasma samples by gelatin zymography and ELISA respectively. Thiobarbituric acid-reactive species (TBARS) were measured in plasma to assess oxidative stress. Selenium (Se) levels were determined by ICP-MS because it is an antioxidant. The relations between bioindicators of Hg and the metalloproteinases levels were examined using multivariate regression models. While we found no relation between blood or plasma Hg and MMP-9, plasma Hg levels were negatively associated with TIMP-1 and TIMP-2 levels, and thereby with increasing MMP-9/TIMP-1 and MMP-2/TIMP-2 ratios, thus indicating a positive association between plasma Hg and circulating net MMP-9 and MMP-2 activities. These findings provide a new insight into the possible biological mechanisms of Hg toxicity, particularly in cardiovascular diseases.

Hepatic Steatosis, Obesity, and the Metabolic Syndrome Are Independently and Additively Associated With Increased Systemic Inflammation

Objective-The goal of this study was to assess the independent and collective associations of hepatic steatosis, obesity, and the metabolic syndrome with elevated high-sensitivity C-reactive protein (hs-CRP) levels. Methods and Results-We evaluated 2388 individuals without clinical cardiovascular disease between December 2004 and December 2006. Hepatic steatosis was diagnosed by ultrasound, and the metabolic syndrome was defined using National Heart, Lung, and Blood Institute criteria. The cut point of >= 3 mg/L was used to define high hs-CRP. Multivariate logistic regression was used to assess the independent and collective associations of hepatic steatosis, obesity, and the metabolic syndrome with high hs-CRP. Steatosis was detected in 32% of participants, 23% met criteria for metabolic syndrome, and 17% were obese. After multivariate regression, hepatic steatosis (odds ratio [OR] 2.07; 95% CI 1.68 to 2.56), obesity (OR 3.00; 95% CI 2.39 to 3.80), and the metabolic syndrome (2.39; 95% CI 1.88 to 3.04) were all independently associated with high hs-CRP. Combinations of these factors were associated with an additive increase in the odds of high hs-CRP, with individuals with 1, 2, and 3 factors having ORs for high hs-CRP of 1.92 (1.49 to 2.48), 3.38 (2.50 to 4.57), and 4.53 (3.23 to 6.35), respectively. Conclusion-Hepatic steatosis, obesity, and the metabolic syndrome are independently and additively associated with increased odds of high hs-CRP levels. (Arterioscler Thromb Vasc Biol. 2011; 31: 1927-1932.)

Physical function interfering with pain and symptoms in fibromyalgia patients

Objectives. The aim of this study was to assess the relationship between variables of physical assessment - muscular strength, flexibility and dynamic balance - with pain, pain threshold, and fibromyalgia symptoms (FM). Methods. Our sample consists of 55 women, with age ranging from 30 to 55 years (mean of 46.5, (standard deviation, SD=6.6)), mean body mass index (BMI) of 28.7(3.8) and diagnosed for FM according to the American College of Rheumatology criteria. Pain intensity was measured using a visual analogue scale (VAS) and pain threshold (PT) using Fisher`s dolorimeter. FM symptoms were assessed by the Fibromyalgia Impact Questionnaire (FIQ); flexibility by the third finger to floor test (3FF); the muscular strength index (MSI) by the maximum volunteer isometric contraction at flexion and extension of right knee and elbow using a force transducer, dynamic balance by the time to get up and go (TUG) test and the functional reach test (FRT). Data were analysed using Pearson`s correlation, as well as simple and multivariate regression tests, with significance level of 5%. Results. PT and FIQ were weakly but significantly correlated with the TUG, MSI and 3FF as well as VAS with the TUG and MSI (p<0.05). VAS, PT and FIQ was not correlated with FRT. Simple regression suggests that, alone, TUG, FR, MSI and 3FF are low predictors of VAS, PT and FIQ. For the VAS, the best predictive model includes TUG and MSI, explaining 12.6% of pain. variability. For TP and total symptoms, as obtained by the FIQ, most predictive model includes 3FF and MSI, which respectively respond by 30% and 21% of the variability. Conclusion. Muscular strength, flexibility and balance are associated with pain, pain threshold, and symptoms in FM patients.

New body fat prediction equations for severely obese patients

Background & aims: Severe obesity imposes physical limitations to body composition assessment. Our aim was to compare body fat (BF) estimations of severely obese patients obtained by bioelectrical impedance (BIA) and air displacement plethysmography (ADP) for development of new equations for BF prediction. Methods: Severely obese subjects (83 female/36 mate, mean age = 41.6 +/- 11.6 years) had BF estimated by BIA and ADP. The agreement of the data was evaluated using Bland-Altman`s graphic and concordance correlation coefficient (CCC). A multivariate regression analysis was performed to develop and validate new predictive equations. Results: BF estimations from BIA (64.8 +/- 15 kg) and ADP (65.6 +/- 16.4 kg) did not differ (p > 0.05, with good accuracy, precision, and CCC), but the Bland- Altman graphic showed a wide Limit of agreement (- 10.4; 8.8). The standard BIA equation overestimated BF in women (-1.3 kg) and underestimated BF in men (5.6 kg; p < 0.05). Two BF new predictive equations were generated after BIA measurement, which predicted BF with higher accuracy, precision, CCC, and limits of agreement than the standard BIA equation. Conclusions: Standard BIA equations were inadequate for estimating BF in severely obese patients. Equations developed especially for this population provide more accurate BF assessment. (C) 2008 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Prevalence and correlates of alcoholism in community-dwelling elderly living in Sao Paulo, Brazil

Objectives To assess the prevalence of alcoholism in elderly living in the city of Sao Paulo (Brazil) and investigate associated risk factors. Methods A total of 1,563 individuals aged 60 years or older, of both genders of three districts of different socioeconomic classes (high, medium and low) in the city of Sao Paulo (Brazil) were interviewed. The CAGE screening test for alcoholism was applied and a structured interview was used to assess associated sociodemographic and clinical factors. The tests Mini Mental State Examination, Fuld Object Memory Evaluation, The Informant Questionnaire on Cognitive Decline in the Elderly and Bayer-Activities of Daily Living Scale were used for cognitive and functional assessment. Results Prevalence of alcoholism was 9.1%. Multivariate regression analysis showed that alcoholism was associated with male gender, `mulatto` ethnicity, smoking, and cognitive and functional impairment. In addition, the younger the individual and the lower the schooling level, the higher the risk for alcoholism. Conclusions The results obtained in this study show that alcoholism is highly frequent in the community-dwelling elderly living in Sao Paulo, and that it is associated with socio-demographic and clinical risk factors similar to those reported in the literature. This suggests that alcoholism in the elderly of a developing country shares the same basic characteristics seen in developed countries. These findings suggest that it is essential for health services and professional to be prepared to meet this demand that will significantly grow in the next years, especially in developing countries, where the rates of population aging are higher than those of developed countries. Copyright (C) 2009 John Wiley & Sons, Ltd.

Brain structure and symptom dimension relationships in obsessive-compulsive disorder: A voxel-based morphometry study

Background: Obsessive-compulsive disorder (OCD) is a clinically heterogenous disorder characterized by temporally stable symptom dimensions. Past inconsistent results from structural neuroimaging studies of OCD may have resulted from the effects of these specific symptom dimensions as well as other socio-demographic and clinical variables upon gray matter (GM) volume. Methods: GM volume was measured in 25 adult OCD patients and 20 adult healthy controls using voxel-based morphometry (VBM), controlling for age and total brain GM volume. Univariate and multivariate regression analyses were carried out between regions of GM difference and age, age of onset, medication load, OCD severity, depression severity, and separate symptom dimension scores. Results: Significant GM volumetric differences in OCD patients relative to controls were found in dorsal cortical regions, including bilateral BA6, BA46, BA9 and right BA8 (controls > patients), and bilateral midbrain (patients > controls). Stepwise regression analyses revealed highly significant relationships between greater total OCD symptom severity and smaller GM volumes in dorsal cortical regions and larger GM volumes in bilateral midbrain. Greater age was independently associated with smaller GM volumes in right BA6, left BA9, left BA46 and larger GM volumes in right midbrain. Greater washing symptom severity was independently associated with smaller GM volume in right BA6, while there was a trend association between greater hoarding symptom severity and lower GM volume in left BA6. Limitations: The sample was relatively small to examine the relationship between symptom scores and GM volumes. Multiple patients were taking medication and had comorbid disorders. Conclusions: These analyses suggest dorsal prefrontal cortical and bilateral midbrain GM abnormalities in OCD that appear to be primarily driven by the effects of total OCD symptom severity. The results regarding the relationship between GM volumes and symptom dimension scores require examination in larger samples. (C) 2008 Elsevier B.V. All rights reserved.

Oral mucositis in acute lymphoblastic leukaemia: analysis of 169 paediatric patients

Chemotherapy-induced oral mucositis is a frequent therapeutic challenge in cancer patients. The purpose of this retrospective study was to estimate the prevalence and risk factors of oral mucositis in 169 acute lymphoblastic leukaemia (ALL) patients treated according to different chemotherapeutic trials at the Darcy Vargas Children`s Hospital from 1994 to 2005. Demographic data, clinical history, chemotherapeutic treatment and patients` follow-up were recorded. The association of oral mucositis with age, gender, leucocyte counts at diagnosis and treatment was assessed by the chi-squared test and multivariate regression analysis. Seventy-seven ALL patients (46%) developed oral mucositis during the treatment. Patient age (P = 0.33), gender (P = 0.08) and leucocyte counts at diagnosis (P = 0.34) showed no correlation with the occurrence of oral mucositis. Multivariate regression analysis showed a significant risk for oral mucositis (P = 0.009) for ALL patients treated according to the ALL-BFM-95 protocol. These results strongly suggest the greater stomatotoxic effect of the ALL-BFM-95 trial when compared with Brazilian trials. We concluded that chemotherapy-induced oral mucositis should be systematically analysed prospectively in specialized centres for ALL treatment to establish the degree of toxicity of chemotherapeutic drugs and to improve the quality of life of patients based on more effective therapeutic and prophylactic approaches for prevention of its occurrence. Oral Diseases (2008) 14, 761-766

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

WOOD DENSITY VARIATION AND TREE RING DEMARCATION IN Gmelina arborea TREES USING X-RAY DENSITOMETRY

Due to its relationship with other properties, wood density is the main wood quality parameter. Modern, accurate methods - such as X-ray densitometry - are applied to determine the spatial distribution of density in wood sections and to evaluate wood quality. The objectives of this study were to determinate the influence of growing conditions on wood density variation and tree ring demarcation of gmelina trees from fast growing plantations in Costa Rica. The wood density was determined by X-ray densitometry method. Wood samples were cut from gmelina trees and were exposed to low X-rays. The radiographic films were developed and scanned using a 256 gray scale with 1000 dpi resolution and the wood density was determined by CRAD and CERD software. The results showed tree-ring boundaries were distinctly delimited in trees growing in site with rainfall lower than 25 10 mm/year. It was demonstrated that tree age, climatic conditions and management of plantation affects wood density and its variability. The specific effect of variables on wood density was quantified by for multiple regression method. It was determined that tree year explained 25.8% of the total variation of density and 19.9% were caused by climatic condition where the tree growing. Wood density was less affected by the intensity of forest management with 5.9% of total variation.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.