PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancerpatients

In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1,MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.

QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.

Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

Seroprevalence and risk factors associated with Chlamydophila abortus infection in dairy goats in the Northeast of Brazil

Few data are available on the prevalence and risk factors of Chlamydophila abortus infection in goats in Brazil. A cross-sectional study was carried out to determine the flock-level prevalence of C. abortus infection in goats from the semiarid region of the Paraíba State, Northeast region of Brazil, as well as to identify risk factors associated with the infection. Flocks were randomly selected and a pre-established number of female goats > 12 mo old were sampled in each of these flocks. A total of 975 serum samples from 110 flocks were collected, and structured questionnaire focusing on risk factors for C. abortus infection was given to each farmer at the time of blood collection. For the serological diagnosis the complement fixation test (CFT) using C. abortus S26/3 strain as antigen was performed. The flock-level factors for C. abortus prevalence were tested using multivariate logistic regression model. Fifty-five flocks out of 110 presented at least one seropositive animal with an overall prevalence of 50.0% (95%; CI: 40.3%, 59.7%). Ninety-one out of 975 dairy goats examined were seropositive with titers >32, resulting in a frequency of 9.3%. Lend buck for breeding (odds ratio = 2.35; 95% CI: 1.04-5.33) and history of abortions (odds ratio = 3.06; 95% CI: 1.37-6.80) were associated with increased flock prevalence.

Treatment of patients with Schistosomiasis mansoni: a double blind clinical trial comparing praziquantel with oxamniquine

A double-blind clinical trial involving 120 patients with chronic schistosomiasis was carried out to compare the tolerability and efficacy of praziquantel and oxamniquine. The patients were randomly allocated into two groups. One was treated with praziquantel, 55 mg/kg of body weight CBWT), and the other one with oxamniquine, 15mg/kg bwt, administered in a single oral dose. The diagnosis and the parasitological follow-up was based on stool examinations by quantitative Kato-Katz method and on rectal biopsies. Side-effects — mainly dizziness, sleepness, abdominal distress, headache, nausea and diarrhea — were observed in 87% of the cases. Their incidence, intensity and duration were similar for both drugs but abdominal pain was significantly more frequent after praziquantel intake and severe dizziness was more commonly reported after oxamniquine. A significant increase of alanine-aminotransferase and y-glutamyltransferase was found with the latter drug and of total bilirubin with the former one. A total of 48 patients treated with praziquantel and 46 with oxamniquine completed with negative findings the required three post-treatment parasitological controls — three slides of each stool sample on the first, third and sixth month. The achieved cure rates were 79.2% and 84.8%, respectively, a difference without statistical significance. The non-cured cases showed a mean reduction in the number of eggs per gram of feces of 93.5% after praziquantel and of 84.1% after oxamniquine. This diference also was not significant. Five patients retreated with praziquantel were cured but only one out of three treated a second time with oxamniquine. These findings show that both drugs — despite their different chemical structures, pharmacological properties and mechanisms-of-action — induce similar side-effects as well as a comparable therapeutical efficacy, in agreement with the results reported from analogous investigations.

Hepatitis G virus / GB virus C in Brazil. Preliminary report

Hepatitis G virus/ GB virus C is a novel flavivirus recently detected in hepatitis non A-E cases. In this study, the presence of this virus in chronic non-B, non-C hepatitis patients was evaluated using GBV-C specific PCR and this virus was detected in one out of thirteen patients. This patient has presented a severe liver failure, has lived for a long time in the Western Amazon basin and no other cause for this clinical picture was reported. The impact of the discovery of this new agent is still under evaluation throughout the world. The study of the prevalence of this virus among chronic hepatitis patients and healthy individuals (as blood donors) will furnish subside to evaluate its real pathogenicity.

Childhood astrovirus-associated diarrhea in the ambulatory setting in a Public Hospital in Cordoba city, Argentina

Human astroviruses have been increasingly identified as important agents of diarrheal disease in children. However, the disease burden of astrovirus infection is still incompletely assessed. This paper reports results on the epidemiological and clinical characteristics of astrovirus-associated diarrhea, as well as the impact of astrovirus infection on the ambulatory setting at a Public Hospital in Córdoba city, Argentina. From February 2001 through January 2002, 97 randomly selected outpatient visits for diarrhea among children < 36 months old were enrolled. A single specimen of stool from each child was collected and tested for astrovirus antigen by enzyme immunoassay. Astroviruses were detected in 12.37% of the diarrheal episodes. All the positive cases occurred in children 4 to 18 months, but the highest rate was in children aged 4 to 6 months (23.80%). The clinical symptoms of astrovirus associated-diarrhea were fever 41.66%, vomiting 25.00% and dehydration 8.33%; overall 16.66% required hospitalization. Astrovirus was identified through the year and no seasonally pattern was detected (cool semester 15.21% versus warm semester 9.80% p > 0.05). According to our estimation about one out of seventy-four children in this cohort would be assisted annually for an astroviral-diarrheal episode in the Public Hospital and one out of eight diarrheal cases could be attributed to astrovirus infection. Astrovirus is a common symptomatic infection in pediatric outpatient visits in the public hospital in the study area, contributing 12.37% of the overall morbidity from diarrhea.

Nocardial infections: report of 22 cases

Twenty-two cases of nocardial infections were diagnosed in our city between 1977- 1998. All patients whose clinical specimens showed Nocardia spp. at Gram stain, which were further confirmed by culture, were selected to be included in the study. Data from patients who were cured were compared with those from patients who died by statistical tests using EPIINFO version 6.04 software. Six isolates were identified as Nocardia asteroides complex, one as Nocardia asteroides sensu stricto and other as Nocardia brasiliensis. We had 17 cases of lung nocardiosis, being one out of them also a systemic disease. Other four cases of systemic nocardiosis were diagnosed: nocardial brain abscesses (one); nocardiosis of the jejunum (one); multiple cutaneous abscesses (one); and a case of infective nocardial endocarditis of prosthetic aortic valve. One patient had a mycetoma by N. brasiliensis. Fifteen (68.2%) out of 22 patients were immunosuppressed, being most (93.3%) by high-doses corticotherapy. Mortality by nocardial infection was 41%; mortality of systemic nocardiosis was 60%. Nocardiosis has a bad prognosis in immunosuppressed patients and also in non-immunosuppressed patients if the diagnosis is delayed. We propose that the delay in diagnosis should be examined in larger series to document its influence in the prognosis of the disease.

Hepatitis C virus and human T-lymphotropic virus coinfection: epidemiological, clinical, laboratory and histopathological features

Twenty-four hepatitis C virus patients coinfected with human T-lymphotropic virus type 1 were compared with six coinfected with HTLV-2 and 55 with HCV alone, regarding clinical, epidemiological, laboratory and histopathological data. Fischer's discriminant analysis was applied to define functions capable of differentiating between the study groups (HCV, HCV/HTLV-1 and HCV/HTLV-2). The discriminant accuracy was evaluated by cross-validation. Alcohol consumption, use of intravenous drugs or inhaled cocaine and sexual partnership with intravenous drug users were more frequent in the HCV/HTLV-2 group, whereas patients in the HCV group more often reported abdominal pain or a sexual partner with hepatitis. Coinfected patients presented higher platelet counts, but aminotransferase and gamma-glutamyl transpeptidase levels were higher among HCV-infected subjects. No significant difference between the groups was seen regarding liver histopathological findings. Through discriminant analysis, classification functions were defined, including sex, age group, intravenous drug use and sexual partner with hepatitis. Cross-validation revealed high discriminant accuracy for the HCV group.

Helminths of introduced house sparrows (Passer domesticus) in Brazil: does population age affect parasite richness?

Species introductions have altered host and parasite diversity throughout the world. In the case of introduced hosts, population age appears to be a good predictor of parasite richness. Habitat alteration is another variable that may impact host-parasite interactions by affecting the availability of intermediate hosts. The house sparrow (Passer domesticus (Linnaeus, 1758)) is a good model to test these predictions. It was introduced in several parts of the world and can be found across rural-urban gradients. A total of 160 house sparrows from Porto Alegre, state of Rio Grande do Sul, Brazil, were necropsied. Thirty house sparrows (19 %) were parasitized with at least one out of five helminth species (Digenea: Tamerlania inopina Freitas, 1951 and Eumegacetes sp.; Eucestoda: Choanotaenia passerina (Fuhrmann, 1907) Fuhrmann, 1932; Nematoda: Dispharynx nasuta (Rudolphi, 1819) Stiles & Hassall, 1920 and Cardiofilaria pavlovskyi Strom, 1937). Overall, there was no difference in prevalence and intensity of infection of any parasite species, parasite richness and community diversity between adult males and females and adults and juveniles. The number of infected sparrows among seasons, the richness of helminths and the abundance of species were also similar between rural and urban landscapes. Only the prevalence of C. passerina varied seasonally (p=0.0007). A decrease in the number of parasite species from the original range of P. domesticus (13) to its port of entrance in Brazil, the city of Rio de Janeiro (nine), to Porto Alegre (five) is compatible with the hypothesis that host population age is a good predictor of parasite richness.