Prolonged acceptance of skin grafts induced by B cells places regulatory T cells on the histopathology scene

The participation of regulatory T (Treg) cells in B cell-induced T cell tolerance has been claimed in different models. In skin grafts, naive B cells were shown to induce graft tolerance. However, neither the contribution of Treg cells to B cell-induced skin tolerance nor their contribution to the histopathological diagnosis of graft acceptance has been addressed. Here, using male C57BL/6 naive B cells to tolerize female animals, we show that skin graft tolerance is dependent on CD25+ Treg cell activity and independent of B cell-derived IL-10. In fact, B cells from IL-10-deficient mice were able to induce skin graft tolerance while Treg depletion of the host inhibited 100% graft survival. We questioned how Treg cell-mediated tolerance would impact on histopathology. B cell-tolerized skin grafts showed pathological scores as high as a rejected skin from naive, non-tolerized mice due to loss of skin appendages, reduced keratinization and mononuclear cell infiltrate. However, in tolerized mice, 40% of graft infiltrating CD4+ cells were FoxP3+ Treg cells with a high Treg:Teff (effector T cell) ratio (6:1) as compared to non-tolerized mice where Tregs comprise less than 8% of total infiltrating CD4 cells with a Treg:Teff ratio below 1:1. These results render Treg cells an obligatory target for histopathological studies on tissue rejection that may help to diagnose and predict the outcome of a transplanted organ.

Instrumental color and sensory acceptance of soy-based emulsions: a response surface approach

Response Surface Methodology (RSM) was applied to evaluate the chromatic features and sensory acceptance of emulsions that combine Soy Protein (SP) and red Guava Juice (GJ). The parameters analyzed were: instrumental color based on the coordinates a* (redness), b* (yellowness), L* (lightness), C* (chromaticity), h* (hue angle), visual color, acceptance, and appearance. The analyses of the results showed that GJ was responsible for the high measured values of red color, hue angle, chromaticity, acceptance, and visual color, whereas SP was the variable that increased the yellowness intensity of the assays. The redness (R²adj = 74.86%, p < 0.01) and hue angle (R²adj = 80.96%, p < 0.01) were related to the independent variables by linear models, while the sensory data (color and acceptance) could not be modeled due to a high variability. The models of yellowness, lightness, and chromaticity did not present lack of fit but presented adjusted determination coefficients bellow 70%. Notwithstanding, the linear correlations between sensory and instrumental data were not significant (p > 0.05) and low Pearson coefficients were obtained. The results showed that RSM is a useful tool to develop soy-based emulsions and model some chromatic features of guava-based emulsions through RSM.

Influence of strawberry jam color and phenolic compounds on acceptance during storage

The objective of this study was to evaluate the influence of the color and phenolic compounds of strawberry jam on acceptance during storage. Jams were processed, stored for 120 days and evaluated monthly for chromatic characteristics, total phenolic compounds, total anthocyanins (ANT), total ellagic acid (TEA), flavonoids and free ellagic acid (FEA), and sensory acceptance as well. Data were submitted to analysis of variance (ANOVA) and the means were compared by the Least Significant Difference (LSD). Cluster Analysis and Partial Least Square Regression (PLS) were performed to investigate the relationships between instrumental data and acceptance. Contents of ANT, TEA and redness decreased during storage. Other chemical characteristics and sensory acceptance showed a nonlinear behavior. Higher acceptance was observed after 60 days, suggesting a trend of quality improvement followed by decline to the initial levels. The same trend was observed for lightness, non-pigment flavonoids and FEA. According to PLS map, for consumers in cluster 2, acceptance was associated to jams at 60 days and to luminosity, FEA, and non-pigment flavonoids. For cluster 1, a positive association between flavor liking, jam at initial storage, and the contents of TEA and ANT was indicated. Jams at 120 days were positively associated to hue and negatively associated to color liking, for cluster 1. Color and texture were positively correlated to overall liking for cluster 2, whereas for cluster 1, overall acceptance seemed to be more associated to flavor liking. Changes in color and phenolic compounds slightly influenced the acceptance of strawberry jams, but in different ways for consumers clusters.

ABOUT PSYCHOLOGICAL VARIABLES IN APPLICATION SCORING MODELS

The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a) negative dimensions related to money (suffering, inequality and conflict); b) high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c) buyers classified as compulsive; d) individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e) problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.

ANIMAL MODELS FOR THE STUDY OF LEISHMANIASIS IMMUNOLOGY

Leishmaniasis remains a major public health problem worldwide and is classified as Category I by the TDR/WHO, mainly due to the absence of control. Many experimental models like rodents, dogs and monkeys have been developed, each with specific features, in order to characterize the immune response to Leishmania species, but none reproduces the pathology observed in human disease. Conflicting data may arise in part because different parasite strains or species are being examined, different tissue targets (mice footpad, ear, or base of tail) are being infected, and different numbers (“low” 1×102 and “high” 1×106) of metacyclic promastigotes have been inoculated. Recently, new approaches have been proposed to provide more meaningful data regarding the host response and pathogenesis that parallels human disease. The use of sand fly saliva and low numbers of parasites in experimental infections has led to mimic natural transmission and find new molecules and immune mechanisms which should be considered when designing vaccines and control strategies. Moreover, the use of wild rodents as experimental models has been proposed as a good alternative for studying the host-pathogen relationships and for testing candidate vaccines. To date, using natural reservoirs to study Leishmania infection has been challenging because immunologic reagents for use in wild rodents are lacking. This review discusses the principal immunological findings against Leishmania infection in different animal models highlighting the importance of using experimental conditions similar to natural transmission and reservoir species as experimental models to study the immunopathology of the disease.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Acceptance and potential barriers to effective use of diagnostic tests for visceral leishmaniasis in an urban area in Brazil

Abstract: INTRODUCTION: Acceptance of the IT LEISH(r) and direct agglutination test- made in the Laboratório de Pesquisas Clínicas (DAT-LPC) by healthcare professionals and patients suspected of visceral leishmaniasis (VL) in Ribeirão das Neves was evaluated. METHODS: Ninety-two patients and 47 professionals completed three questionnaires. RESULTS: Eighty-eight (96%) patients considered fingertip blood collection a positive test feature, and 86% (37) and 91% of professionals considered the IT LEISH(r) easy to perform and interpret, respectively. All professionals classified the DAT-LPC as simple and easy. CONCLUSIONS: Patients and healthcare professionals in Ribeirão das Neves demonstrated a high degree of acceptance of the IT LEISH(r) and DAT-LPC.

Hormone replacement therapy and the risk of breast cancer: assessment of therapy acceptance in a cohort of previously treated breast cancer patients

INTRODUCTION: In the postmenopausal period, an average of 25% of women will present symptomatic ovarian failure requiring hormonal replacement therapy. Estrogen can relieve vasomotor symptoms. Hormonal replacement therapy is generally not recommended for breast cancer patients due to the potential risk of tumor recurrence. To answer the questions about the safety of hormonal replacement therapy in this subgroup of women, it is necessary to establish the acceptance of treatment. METHODS: Between September 1998 and February 2001, a cohort of 216 breast cancer patients were asked to complete a questionnaire. All patients had completed their treatment and were informed about survival rates after breast cancer and hormonal replacement therapy. RESULTS: Among the 216 patients, 134 (62%) would refuse hormonal replacement therapy. A hundred patients were afraid of relapse (74.6%). Adjuvant tamoxifen therapy was the only statistically significant variable (70.3% versus 29.7% p=0.003). Understanding clinical stage (p= 0.045) and type of medical assistance (private versus public , p=0.033) also seemed to influence the decision. Early stage disease (p= 0.22), type of surgical procedure (radical versus conservative, p=0.67), adjuvant chemotherapy (p=0.082) or marital status (p=0.98 ) were not statistically significant in decision making. Several patients submitted to adjuvant chemotherapy (41.6%) would accept hormonal replacement therapy under medical supervision, as did most of advanced clinical stage patients (58.3%; p=0.022). CONCLUSION: There is a high level of rejection for hormonal replacement therapy among breast cancer patients when current data on tumor cure rates, and potential risks of estrogen use is available. Adverse effects of tamoxifen in the adjuvant setting may be the reason for refusal of hormonal replacement therapy .

Modelling Amazonian forest eddy covariance data: a comparison of big leaf versus sun/shade models for the C-14 tower at Manaus I. Canopy photosynthesis

In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.