Methods for unsupervised contribution analysis of raw EEM data in water monitoring. Contaminant identification and quantification.

Fluorescence EEM spectra provide the "fingerprint" of water contamination and is a very efficient way to access the quality of water bodies. These multivariate datasets correspond to complex mixtures and are very rich in information. Graphical approaches have been used for decades to characterize and quantify different contamination sources. It is very important to resolve mixed signals in raw EEM spectra in terms of signal sources and respective composition profiles - signal sources allow the identification of contamination type, while concentration profiles quantify the respective contribution inside the mixtures. In order to be able to use robust modeling algorithms, the first task is to accurately estimate the number of contributions that are present. We demonstrate the ability of Singular value Decomposition (SVD) in accessing this information content in raw EEM datasets. To decompose raw EEM information, several algorithms are tested: PARAFAC, MCR-ALS and ICA. In this work we suggest a systematic unsupervised algorithm to process raw EEM spectra of water samples.

Evaluating Skin Sensitization Via Soft and Hard Multivariate Modeling.

Allergic contact dermatitis is the most frequent manifestation of immunotoxicity in humans with a prevalence rate of 15% to 20% over general population. Skin sensitization is a complex end point that was for a long time being evaluated using animal testing. Great efforts have been made to completely substitute the use of animals and replace them by integrating data from in vitro and in chemico assays with in silico calculated parameters. However, it remains undefined how to make the best use of the cumulative data in such a way that information gain is maximized and accomplished with the fewest number of tests possible. In this work, 3 skin sensitization prediction models were considered: one to discriminate sensitizers from non-sensitizers, considering a 2-level scale; one according to the GHS, considering a 3-level scale; and the other to categorize potency in a 6-level scale, according to available human data. We used a data set of known human skin allergens for which in vitro, in chemico, and in silico descriptors where available to build classifiers based on soft and hard multivariate modeling. Model building, optimization, and refinement resulted in 100% accuracy in distinguishing between sensitizers and non-sensitizers. The same model was able to perform the characterization, in 3 and 6 levels, respectively, with 98.8 and 97.5% accuracy. Combining data from in vitro and in chemico tests with in silico descriptors is relatively simple to implement and some predictors are fitting the adverse outcome pathway for skin sensitization.

Effects of a high energy density diet in the "corpus cavernosum" of mice.

Erectile dysfunction is a common condition that affects men over age 40. It is highly related to obesity. The corpus cavernosum is the most important structure involved in erection. The aim of this study was to evaluate the structure of the corpus cavernosum of mice fed with a high energy density diet (HED). At 3 months of age, male C57BL/6 mice were fed with a HED diet (50% lipids) or standard chow (SC) diet (10% lipids) for 14 weeks. Afterwards, the animals were euthanized and the corpus cavernosum was analyzed through stereology. Statistical significance was calculated by the student's t-test (p < 0.05). The group fed with HED diet showed higher values of body weight, blood pressure and higher rates of cholesterol, triglycerides, and glucose from the second week to the end of the experiment. The HED group showed a significant increase in the connective tissue (15%) and a decrease in smooth muscle fibers (41%). The testosterone concentration in the HED group was 63% lower than in SC animals. Animals fed with a HED presented reduced testosterone serum levels and morphological changes on the corpus cavernosum, which may be related to erectile dysfunction.

Improving discrimination in the grading of rat mammary tumors using two-dimensional mapping of histopathological observations.

This work aims at characterizing rat mammary tumors induced by 7,12-dimethylbenz(a)anthracene (DMBA) and the respective malignancy potential, commonly graded with histopathology features grouped by intensity levels. Tumors were described over fourteen multiple ranged microscopic parameters and a comprehensive characterization of the histological patterns and their relation with tumor grade was carried out by principal component analysis (PCA). The number of histological patterns present on a tumor tends to correlate with malignant features. High grade tumors are characterized by the presence of several structural patterns, with cribriform prevalence and necrosis. The cribriform pattern correlates with grading, i.e., tumors having a higher predominance of the cribriform pattern are likely to be more malignant. The findings may represent a benchmark for similar characterization studies in other models.

Is standard multivariate analysis sufficient in clinical and epidemiological studies?

Clinical tests and epidemiological studies often produce large amounts of data, being multivariate in nature. The respective analysis is, in most cases, of importance comparable to the clinical and sampling tasks. Simple, easily interpretable techniques from chemometrics provide most of the ingredients to carry out this analysis. We have selected available data from different sources pertaining to cancer diagnosis and incidence: (1) cytological diagnosis of breast cancer, (2) classification of breast tissues through parameters obtained from impedance spectra and (3) distribution of new cancer cases in the United States. Hierarchical cluster analysis (HCA) is needed especially in cases where there is no a priori identification of classes, suggesting a structure of the data based on clusters. These clusters or the classes, are then further detailed and rationalized by principal component analysis (PCA). Partial least squares (PLS) and linear discriminant analysis (LDA) provide further insight into the systems. An additional step for understanding the data set is the removal of less characteristic data (NR) using a density-based approach, so as to make it more clearly defined. Results clearly reveal that breast cytology diagnosis relies on variables conveying mostly the same type of information, being thus interchangeable in nature. In the study on tissue characterization by electrical measurements, the distribution of the different types of tissues can be easily constructed. Finally, the distribution of new cancer cases possesses clear, easily unravelled, geographical patterns.

6-Meth-oxyisobenzofuran-1(3H)-one.

In the title compound, C(9)H(8)O(3), the mol-ecular skeleton is almost planar [r.m.s. deviation = 0.016 (2) Å]. Weak inter-molecular C-H⋯O and C-H⋯π inter-actions consolidate the crystal packing, with the mol-ecules stacking in the [101] direction.

Collagen I and III and metalloproteinase gene and protein expression in prostate cancer in relation to Gleason score.

PURPOSE: To evaluate if the expression of metalloproteinase, collagen I and III are related to Gleason score, preoperative PSA and pathological stage in prostate cancer. MATERIALS AND METHODS: Our study group included radical prostatectomy specimens of 33 patients with prostatic adenocarcinoma who underwent surgery from 2001 to 2009. Patients were divided into 3 groups: Gleason score=6 (13 patients), Gleason score=7 (10 patients), Gleason score ≥ 8 (10 patients). The control group included prostates of patients submitted to cystoprostatectomy and benign prostatic tissues adjacent to the cancer area. Specific areas of tissues were selected under microscope and further processed for collagen I and III analysis by real time PCR. In addition, 10 deparaffined sections of each group were used to evaluate collagen I, III and metalloproteinase immune expression. The results were correlated with Gleason score, preoperative PSA and pathological stage. RESULTS: We found significant difference in both collagen I and III gene expression between benign and tumoral areas in the prostate samples from Gleason score=6 (collagen I=0.4 ± 0.2 vs 5 ± 2.4, p < 0.05; collagen III=0.2 ± 0.06 vs 0.7 ± 0.1, p < 0.05) and Gleason score ≥ 8 (collagen I=8 ± 3.4 vs 1.4 ± 0.8, p < 0.07; collagen III=1.8 ± 0.5 vs 0.6 ± 0.1, p < 0.05). There was no correlation of collagen expression with Gleason score, preoperative PSA or pathological stage. There was a positive correlation between metalloproteinase expression and Gleason score (r(2)=0.47). CONCLUSIONS: The positive correlation between metalloproteinase expression and Gleason score suggests that metalloproteinase could be a promising factor to improve Gleason score evaluation. Its expression and regulation do not seem to be related with collagen degradation.

Collagen I and III and metalloproteinase gene and protein expression in prostate cancer in relation to Gleason score

PURPOSE: To evaluate if the expression of metalloproteinase, collagen I and III are related to Gleason score, preoperative PSA and pathological stage in prostate cancer. MATERIALS AND METHODS: Our study group included radical prostatectomy specimens of 33 patients with prostatic adenocarcinoma who underwent surgery from 2001 to 2009. Patients were divided into 3 groups: Gleason score=6 (13 patients), Gleason score=7 (10 patients), Gleason score>8 (10 patients). The control group included prostates of patients submitted to cystoprostatectomy and benign prostatic tissues adjacent to the cancer area. Specific areas of tissues were selected under microscope and further processed for collagen I and III analysis by real time PCR. In addition, 10 deparaffined sections of each group were used to evaluate collagen I, III and metalloproteinase immune expression. The results were correlated with Gleason score, preoperative PSA and pathological stage. RESULTS: We found significant difference in both collagen I and III gene expression between benign and tumoral areas in the prostate samples from Gleason score=6 (collagen I=0.4±0.2 vs 5±2.4, p<0.05; collagen III=0.2±0.06 vs 0.7±0.1, p<0.05) and Gleason score>8 (collagen I=8±3.4 vs 1.4±0.8, p<0.07; collagen III=1.8±0.5 vs 0.6±0.1, p<0.05). There was no correlation of collagen expression with Gleason score, preoperative PSA or pathological stage. There was a positive correlation between metalloproteinase expression and Gleason score (r²=0.47). CONCLUSIONS: The positive correlation between metalloproteinase expression and Gleason score suggests that metalloproteinase could be a promising factor to improve Gleason score evaluation. Its expression and regulation do not seem to be related with collagen degradation.

5-Meth-oxy-2-benzofuran-1(3H)-one.

In the title compound, C9H8O3, the mol-ecular skeleton is almost planar, with an r.m.s. deviation of 0.010 (2) Å. In the crystal, weak C-H⋯O hydrogen bonds connect the mol-ecules into a two-dimensional network parallel to the ac plane.

Carcinóide em divertículo de Meckel: apresentaçäo de caso e revisäo da literatura / Carcinoid of Meckel's diverticulum: report of a case and review of the literature

E apresentado um caso de tumor carcinóide em divertículo de Meckel, em paciente masculino de 56 anos. O paciente foi submetido à colecistectomia. Quando da revisäo da cavidade, encontrou-se um divertículo de intestino delgado a aproximadamente 60 cm da válvula íleo-cecal. O divertículo foi ressecado. Ao exame anatomopatológico, foi diagnosticado tumor carcinóide em divertículo de Meckel