Characterization of global transcription profile of normal and HPV-immortalized keratinocytes and their response to TNF treatment

Background: Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours. Methods: In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-kappa B activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts. Results: We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: KLK7 (kallikrein 7), SOD2 (superoxide dismutase 2), 100P (S100 calcium binding protein P), PI3 (protease inhibitor 3, skin-derived), CSTA (cystatin A), RARRES1 (retinoic acid receptor responder 1), and LXN (latexin). The differential expression of the KLK7 and SOD2 transcripts was confirmed by Northern blot. Moreover, we observed that SOD2 expression correlates with the differential NF-kappa B activation exhibited by TNF-sensitive and TNF-resistant cells. Conclusion: This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.

Cost-effectiveness of Sick Leave Policies for Health Care Workers with Influenza-like Illness, Brazil, 2009

We describe the effect of influenza-like illness (ILI) during the outbreak of pandemic (H1N1) 2009 on health care worker (HCW) absenteeism and compare the effectiveness and cost of 2 sick leave policies for HCWs with suspected influenza. We assessed initial 2-day sick leaves plus reassessment until the HOW was asymptomatic (2-day + reassessment policy), and initial 7-day sick leaves (7-day policy). Sick leaves peaked in August 2009: 3% of the workforce received leave for ILI. Costs during May October reached R$798,051.87 (approximate to US $443,362). The 7-day policy led to a higher monthly rate of sick leave days per 100 HCWs than did the 2-day + reassessment policy (8.72 vs. 3.47 days/100 HCWs; p<0.0001) and resulted in higher costs (US $609 vs. US $1,128 per HCW on leave). ILI affected HCW absenteeism. The 7-day policy was more costly and not more effective in preventing transmission to patients than the 2-day + reassessment policy.

Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease. Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.

Generation and characterization of human insulin-releasing cell lines

Background: The in vitro culture of insulinomas provides an attractive tool to study cell proliferation and insulin synthesis and secretion. However, only a few human beta cell lines have been described, with long-term passage resulting in loss of insulin secretion. Therefore, we set out to establish and characterize human insulin-releasing cell lines. Results: We generated ex-vivo primary cultures from two independent human insulinomas and from a human nesidioblastosis, all of which were cultured up to passage number 20. All cell lines secreted human insulin and C-peptide. These cell lines expressed neuroendocrine and islets markers, confirming the expression profile found in the biopsies. Although all beta cell lineages survived an anchorage independent culture, none of them were able to invade an extracellular matrix substrate. Conclusion: We have established three human insulin-releasing cell lines which maintain antigenic characteristics and insulin secretion profiles of the original tumors. These cell lines represent valuable tools for the study of molecular events underlying beta cell function and dysfunction.

Correlation between MMPs and their inhibitors in breast cancer tumor tissue specimens and in cell lines with different metastatic potential

Background: The metastatic disease rather than the primary tumor itself is responsible for death in most solid tumors, including breast cancer. The role of matrix metalloproteinases ( MMPs), tissue inhibitors of MMPs (TIMPs) and Reversion-inducing cysteine-rich protein with Kazal motifs ( RECK) in the metastatic process has previously been established. However, in all published studies only a limited number of MMPs/MMP inhibitors was analyzed in a limited number of cell lines. Here, we propose a more comprehensive approach by analyzing the expression levels of several MMPs (MMP-2, MMP-9 and MMP-14) and MMP inhibitors (TIMP-1, TIMP-2 and RECK) in different models ( five human breast cancer cell lines, 72 primary breast tumors and 30 adjacent normal tissues). Methods: We analyzed the expression levels of MMP-2, MMP-9 and MMP-14 and their inhibitors (TIMP-1, TIMP-2 and RECK) by quantitative RT-PCR (qRT-PCR) in five human breast cancer cell lines presenting increased invasiveness and metastatic potential, 72 primary breast tumors and 30 adjacent normal tissues. Moreover, the role of cell-extracellular matrix elements interactions in the regulation of expression and activity of MMPs and their inhibitors was analyzed by culturing these cell lines on plastic or on artificial ECM (Matrigel). Results: The results demonstrated that MMPs mRNA expression levels displayed a positive and statistically significant correlation with the transcriptional expression levels of their inhibitors both in the cell line models and in the tumor tissue samples. Furthermore, the expression of all MMP inhibitors was modulated by cell-Matrigel contact only in highly invasive and metastatic cell lines. The enzyme/inhibitor balance at the transcriptional level significantly favors the enzyme which is more evident in tumor than in adjacent non-tumor tissue samples. Conclusion: Our results suggest that the expression of MMPs and their inhibitors, at least at the transcriptional level, might be regulated by common factors and signaling pathways. Therefore, the multi-factorial analysis of these molecules could provide new and independent prognostic information contributing to the determination of more adequate therapy strategies for each patient.`

LATENT RANK CHANGE DETECTION FOR ANALYSIS OF SPLICE-JUNCTION MICROARRAYS WITH NONLINEAR EFFECTS

Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over-or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.

Highly Toxic Microcystis aeruginosa Strain, Isolated from So Paulo-Brazil, Produce Hepatotoxins and Paralytic Shellfish Poison Neurotoxins

While evaluating several laboratory-cultured cyanobacteria strains for the presence of paralytic shellfish poison neurotoxins, the hydrophilic extract of Microcystis aeruginosa strain SPC777-isolated from Billings`s reservoir, So Paulo, Brazil-was found to exhibit lethal neurotoxic effect in mouse bioassay. The in vivo test showed symptoms that unambiguously were those produced by PSP. In order to identify the presence of neurotoxins, cells were lyophilized, and the extracts were analyzed by HPLC-FLD and HPLC-MS. HPLC-FLD analysis revealed four main Gonyautoxins: GTX4(47.6%), GTX2(29.5%), GTX1(21.9%), and GTX3(1.0%). HPLC-MS analysis, on other hand, confirmed both epimers, with positive Zwitterions M(+) 395.9 m/z for GTX3/GTX2 and M(+) 411 m/z for GTX4/GTX1 epimers. The hepatotoxins (Microcystins) were also evaluated by ELISA and HPLC-MS analyses. Positive immunoreaction was observed by ELISA assay. Alongside, the HPLC-MS analyses revealed the presence of [l-ser(7)] MCYST-RR. The N-methyltransferase (NMT) domain of the microcystin synthetase gene mcyA was chosen as the target sequence to detect the presence of the mcy gene cluster. PCR amplification of the NMT domain, using the genomic DNA of the SPC777 strain and the MSF/MSR primer set, resulted in the expected 1,369 bp product. The phylogenetic analyses grouped the NMT sequence with the NMT sequences of other known Microcystis with high bootstrap support. The taxonomical position of M. aeruginosa SPC777 was confirmed by a detailed morphological description and a phylogenetic analysis of 16S rRNA gene sequence. Therefore, co-production of PSP neurotoxins and microcystins by an isolated M. aeruginosa strain is hereby reported for the first time.

Fatty acids decrease catalase activity in human leukaemia cell lines

Fatty acid (FA) may disturb the redox state of the cells not only by an increase in reactive oxygen species (ROS) generation but also due to a reduction in antioxidant enzyme activities. The effect of various FAs (palmitic, stearic, oleic, linoleic, gamma-linolenic and eicosapentaenoic acids (EPAs)) on Jurkat and Raji cells, (human T and B leukaemic cell lines was investigated). The following measurements were carried out: FA composition of the cells, cell proliferation and activities of catalase, glutathione peroxidase (GPx) and superoxide dismutase (SOD). The protective effect of alpha-tocopherol on cell death was also investigated. Each cell line presented a specific FA composition. All the tested ENS reduced catalase activity. The toxic effect of FA was abolished by the pre-incubation with physiological concentrations of alpha-tocopherol. The findings support the proposition that the increase in oxidative stress induced by FA partially occurs due to a reduction in catalase activity. In spite of the decrease in the enzyme activity, catalase protein and mRNA levels were not changed, suggesting a post-translational regulation. Copyright (C) 2007 John Wiley & Sons, Ltd.

Evaluation of biologic occupational risk control practices: Quality indicators development and validation

Background: There is growing demand for the adoption of qualification systems for health care practices. This study is aimed at describing the development and validation of indicators for evaluation of biologic occupational risk control programs. Methods: The study involved 3 stages: (1) setting up a research team, (2) development of indicators, and (3) validation of the indicators by a team of specialists recruited to validate each attribute of the developed indicators. The content validation method was used for the validation, and a psychometric scale was developed for the specialists` assessment. A consensus technique was used, and every attribute that obtained a Content Validity Index of at least 0.75 was approved. Results: Eight indicators were developed for the evaluation of the biologic occupational risk prevention program, with emphasis on accidents caused by sharp instruments and occupational tuberculosis prevention. The indicators included evaluation of the structure, process, and results at the prevention and biologic risk control levels. The majority of indicators achieved a favorable consensus regarding all validated attributes. Conclusion: The developed indicators were considered validated, and the method used for construction and validation proved to be effective.

A numerical model for the description of the nonlinear behaviour of multi-leaf masonry walls

A nonlinear finite element model was developed to simulate the nonlinear response of three-leaf masonry specimens, which were subjected to laboratory tests with the aim of investigating the mechanical behaviour of multiple-leaf stone masonry walls up to failure. The specimens consisted of two external leaves made of stone bricks and mortar joints, and an internal leaf in mortar and stone aggregate. Different loading conditions, typologies of the collar joints, and stone types were taken into account. The constitutive law implemented in the model is characterized by a damage tensor, which allows the damage-induced anisotropy accompanying the cracking process to be described. To follow the post-peak behaviour of the specimens with sufficient accuracy it was necessary to make the damage model non-local, to avoid mesh-dependency effects related to the strain-softening behaviour of the material. Comparisons between the predicted and measured failure loads are quite satisfactory in most of the studied cases. (c) 2007 Elsevier Ltd. All rights reserved.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

APPLICABILITY OF THE NITRITATION/DENITRITATION PROCESS IN THE TREATMENT OF A LANDFILL LEACHATE

The biological nitritation/denitritation process in the removal of organic matter and nitrogen in a landfill leachate was studied using an activated sludge sequencing batch reactor Treatment cycles were formed by an anoxic and an aerobic phases in which the conditions for oxidation of the influent N load and the prevalence of nitrite concentration at the end of aerobic treatment cycles were determined as well as the use of organic matter present in the leachate as a carbon source for denim-firing organisms in the anoxic stage The removal efficiencies of N-NO(2) at the end of the anoxic process (48h) ranged between 14 and 30% indicating low availability of biodegradable organic matter in the leachate As for the accumulation of N-NO(2) at the end of the aerobic phase (48h) of treatment cycles imbalances were not observed while 100% removal efficiencies of N and specific nth-dation rates from 0 095 to 0 158kgN-NH(3)/kgSSV per day were recorded demonstrating the applicability of simplified nitrification in the treatment of effluents with low C/N ratios

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Suitability of relative humidity as an estimator of leaf wetness duration

Leaf wetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates. Because LWD is not widely measured, several methods have been developed to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empirical models use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimate LWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained from Ames, IA (USA), Elora, Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sao Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH >= 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH >= 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH >= 90% model performed best, presenting the highest general fraction of correct estimates (F(C)), between 0.87 and 0.92, and the lowest false alarm ratio (F(AR)), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, even when independent data were used; MAE ranged from 1.23 to 1.89 h, which is very similar to errors obtained with published physical models for LWD estimation. Based on these results, we concluded that, if calibrated locally, LWD can be estimated with acceptable accuracy by RH above a specific threshold, and that the EXT_RH method was unsuitable for estimating LWD at the locations used in this study. (C) 2007 Elsevier B.V. All rights reserved.