Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

Graded Meshes In Bio-thermal Problems With Transmission-line Modeling Method.

In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

Molecular Genetic Variability Of Commercial And Wild Accessions Of Passion Fruit (passiflora Spp.) Targeting Ex Situ Conservation And Breeding.

Passiflora species are distributed throughout Latin America, and Brazil and Colombia serve as the centers of diversity for this genus. We performed cross-species amplification to evaluate 109 microsatellite loci in 14 Passiflora species and estimated the diversity and genetic structure of Passiflora cincinnata, Passiflora setaceae and Passiflora edulis. A total of 127 accessions, including 85 accessions of P. edulis, a commercial species, and 42 accessions of 13 wild species, were examined. The cross-species amplification was effective for obtaining microsatellite loci (average cross-amplification of 70%). The average number of alleles per locus (five) was relatively low, and the average diversity ranged from 0.52 in P. cincinnata to 0.32 in P. setacea. The Bayesian analyses indicated that the P. cincinnata and P. setacea accessions were distributed into two groups, and the P. edulis accessions were distributed into five groups. Private alleles were identified, and suggestions for core collections are presented. Further collections are necessary, and the information generated may be useful for breeding and conservation.

Genetic Diversity Of Giardia Duodenalis: Multilocus Genotyping Reveals Zoonotic Potential Between Clinical And Environmental Sources In A Metropolitan Region Of Brazil.

Giardia duodenalis is a flagellate protozoan that parasitizes humans and several other mammals. Protozoan contamination has been regularly documented at important environmental sites, although most of these studies were performed at the species level. There is a lack of studies that correlate environmental contamination and clinical infections in the same region. The aim of this study is to evaluate the genetic diversity of a set of clinical and environmental samples and to use the obtained data to characterize the genetic profile of the distribution of G. duodenalis and the potential for zoonotic transmission in a metropolitan region of Brazil. The genetic assemblages and subtypes of G. duodenalis isolates obtained from hospitals, a veterinary clinic, a day-care center and important environmental sites were determined via multilocus sequence-based genotyping using three unlinked gene loci. Cysts of Giardia were detected at all of the environmental sites. Mixed assemblages were detected in 25% of the total samples, and an elevated number of haplotypes was identified. The main haplotypes were shared among the groups, and new subtypes were identified at all loci. Ten multilocus genotypes were identified: 7 for assemblage A and 3 for assemblage B. There is persistent G. duodenalis contamination at important environmental sites in the city. The identified mixed assemblages likely represent mixed infections, suggesting high endemicity of Giardia in these hosts. Most Giardia isolates obtained in this study displayed zoonotic potential. The high degree of genetic diversity in the isolates obtained from both clinical and environmental samples suggests that multiple sources of infection are likely responsible for the detected contamination events. The finding that many multilocus genotypes (MLGs) and haplotypes are shared by different groups suggests that these sources of infection may be related and indicates that there is a notable risk of human infection caused by Giardia in this region.

Polymorphisms Of Cell Cycle Control Genes Influence The Development Of Sporadic Medullary Thyroid Carcinoma.

The role of key cell cycle regulation genes such as, CDKN1B, CDKN2A, CDKN2B, and CDKN2C in sporadic medullary thyroid carcinoma (s-MTC) is still largely unknown. In order to evaluate the influence of inherited polymorphisms of these genes on the pathogenesis of s-MTC, we used TaqMan SNP genotyping to examine 45 s-MTC patients carefully matched with 98 controls. A multivariate logistic regression analysis demonstrated that CDKN1B and CDKN2A genes were related to s-MTC susceptibility. The rs2066827*GT+GG CDKN1B genotype was more frequent in s-MTC patients (62.22%) than in controls (40.21%), increasing the susceptibility to s-MTC (OR=2.47; 95% CI=1.048-5.833; P=0.038). By contrast, the rs11515*CG+GG of CDKN2A gene was more frequent in the controls (32.65%) than in patients (15.56%), reducing the risk for s-MTC (OR=0.174; 95% CI=0.048-0.627; P=0.0075). A stepwise regression analysis indicated that two genotypes together could explain 11% of the total s-MTC risk. In addition, a relationship was found between disease progression and the presence of alterations in the CDKN1A (rs1801270), CDKN2C (rs12885), and CDKN2B (rs1063192) genes. WT rs1801270 CDKN1A patients presented extrathyroidal tumor extension more frequently (92%) than polymorphic CDKN1A rs1801270 patients (50%; P=0.0376). Patients with the WT CDKN2C gene (rs12885) presented larger tumors (2.9±1.8 cm) than polymorphic patients (1.5±0.7 cm; P=0.0324). On the other hand, patients with the polymorphic CDKN2B gene (rs1063192) presented distant metastases (36.3%; P=0.0261). In summary, we demonstrated that CDKN1B and CDKN2A genes are associated with susceptibility, whereas the inherited genetic profile of CDKN1A, CDKN2B, and CDKN2C is associated with aggressive features of tumors. This study suggests that profiling cell cycle genes may help define the risk and characterize s-MTC aggressiveness.

Variability Modeling Of Rainfall, Deforestation, And Incidence Of American Tegumentary Leishmaniasis In Orán, Argentina, 1985-2007.

American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

Enhanced Glucose-induced Intracellular Signaling Promotes Insulin Hypersecretion: Pancreatic Beta-cell Functional Adaptations In A Model Of Genetic Obesity And Prediabetes.

Obesity is associated with insulin resistance and is known to be a risk factor for type-2 diabetes. In obese individuals, pancreatic beta-cells try to compensate for the increased insulin demand in order to maintain euglycemia. Most studies have reported that this adaptation is due to morphological changes. However, the involvement of beta-cell functional adaptations in this process needs to be clarified. For this purpose, we evaluated different key steps in the glucose-stimulated insulin secretion (GSIS) in intact islets from female ob/ob obese mice and lean controls. Obese mice showed increased body weight, insulin resistance, hyperinsulinemia, glucose intolerance and fed hyperglycemia. Islets from ob/ob mice exhibited increased glucose-induced mitochondrial activity, reflected by enhanced NAD(P)H production and mitochondrial membrane potential hyperpolarization. Perforated patch-clamp examination of beta-cells within intact islets revealed several alterations in the electrical activity such as increased firing frequency and higher sensitivity to low glucose concentrations. A higher intracellular Ca(2+) mobilization in response to glucose was also found in ob/ob islets. Additionally, they displayed a change in the oscillatory pattern and Ca(2+) signals at low glucose levels. Capacitance experiments in intact islets revealed increased exocytosis in individual ob/ob beta-cells. All these up-regulated processes led to increased GSIS. In contrast, we found a lack of beta-cell Ca(2+) signal coupling, which could be a manifestation of early defects that lead to beta-cell malfunction in the progression to diabetes. These findings indicate that beta-cell functional adaptations are an important process in the compensatory response to obesity.

In Vivo Evaluation Of The Genetic Toxicity Of Rubus Niveus Thunb. (rosaceae) Extract And Initial Screening Of Its Potential Chemoprevention Against Doxorubicin-induced Dna Damage.

Rubus niveus Thunb. plant belongs to Rosaceae family and have been used traditionally to treat wounds, burns, inflammation, dysentery, diarrhea and for curing excessive bleeding during menstrual cycle. The present study was undertaken to investigate the in vivo genotoxicity of Rubus niveus aerial parts extract and its possible chemoprotection on doxorubicin (DXR)-induced DNA damage. In parallel, the main phytochemicals constituents in the extract were determined. The animals were exposed to the extract for 24 and 48h, and the doses selected were 500, 1000 and 2000mg/kg b.w. administered by gavage alone or prior to DXR (30mg/kg b.w.) administered by intraperitoneal injection. The endpoints analyzed were DNA damage in bone marrow and peripheral blood cells assessed by the alkaline alkaline (pH>13) comet assay and bone marrow micronucleus test. The results of chemical analysis of the extract showed the presence of tormentic acid, stigmasterol, quercitinglucoronide (miquelianin) and niga-ichigoside F1 as main compounds. Both cytogenetic endpoints analyzed showed that there were no statistically significant differences (p>0.05) between the negative control and the treated groups with the two higher doses of Rubus niveus extract alone, demonstrating absence of genotoxic and mutagenic effects. Aneugenic/clastogenic effect was observed only at 2000mg/kg dose. On the other hand, in the both assays and all tested doses were observed a significant reduction of DNA damage and chromosomal aberrations in all groups co-treated with DXR and extract compared to those which received only DXR. These results indicate that Rubus niveus aerial parts extract did not revealed any genotoxic effect, but presented some aneugenic/clastogenic effect at higher dose; and suggest that it could be a potential adjuvant against development of second malignant neoplasms caused by the cancer chemotherapic DXR.

Investigation Of Genetic Factors Underlying Typical Orofacial Clefts: Mutational Screening And Copy Number Variation.

Typical orofacial clefts (OFCs) comprise cleft lip, cleft palate and cleft lip and palate. The complex etiology has been postulated to involve chromosome rearrangements, gene mutations and environmental factors. A group of genes including IRF6, FOXE1, GLI2, MSX2, SKI, SATB2, MSX1 and FGF has been implicated in the etiology of OFCs. Recently, the role of the copy number variations (CNVs) has been studied in genetic defects and diseases. CNVs act by modifying gene expression, disrupting gene sequence or altering gene dosage. The aims of this study were to screen the above-mentioned genes and to investigate CNVs in patients with OFCs. The sample was composed of 23 unrelated individuals who were grouped according to phenotype (associated with other anomalies or isolated) and familial recurrence. New sequence variants in GLI2, MSX1 and FGF8 were detected in patients, but not in their parents, as well as in 200 control chromosomes, indicating that these were rare variants. CNV screening identified new genes that can influence OFC pathogenesis, particularly highlighting TCEB3 and KIF7, that could be further analyzed. The findings of the present study suggest that the mechanism underlying CNV associated with sequence variants may play a role in the etiology of OFC.

Comparing Near-infrared Conventional Diffuse Reflectance Spectroscopy And Hyperspectral Imaging For Determination Of The Bulk Properties Of Solid Samples By Multivariate Regression: Determination Of Mooney Viscosity And Plasticity Indices Of Natural Rubber.

Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

Modeling The Effects Of Temperature And Ph On The Resistance Of Alicyclobacillus Acidoterrestris In Conventional Heat-treated Fruit Beverages Through A Meta-analysis Approach.

In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D* values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The zT (temperature change needed to cause one log reduction in D-values) estimated by the meta-analysis model were compared to those ('observed' zT values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

Utilização da discriminação grafica de Fisher para indicação dos dermatoglifos como referencial de potencialidade de atletas de basquetebol

Universidade Estadual de Campinas. Faculdade de Educação Física

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.