Human breast tumor slices: A model for identification of vitamin D regulated genes in the tumor microenvironment

While many studies have addressed the direct effects of 1 alpha,25(OH)(2)D(3) on breast cancer (BC) cells, stromal-epithelial interactions, which are important for the tumor development, have been largely ignored. In addition, high concentrations of the hormone, which cannot be attained in vivo, have been used. Our aim was to establish a more physiological breast cancer model, represented by BC tissue slices, which maintain epithelial-mesenchymal interactions, cultured with a relatively low 1 alpha,25(OH)(2)D(3) concentration, in order to evaluate the vitamin D pathway. Freshly excised human BC samples were sliced and cultured in complete culture media containing vehicle, 0.5 nM or 100 nM 1 alpha,25(OH)(2)D(3) for 24 h. BC slices remained viable for at least 24 h, as evaluated by preserved tissue morphology in hematoxylin and eosin (HE) stained sections and bromodeoxyuridine (BrdU) incorporation by 10% of tumor cells. VDR mRNA expression was detected in all samples and CYP24A1 mRNA expression was induced by 1 alpha,25(OH)(2)D(3) in both concentrations (but mainly with 100 nM). Our results indicate that the vitamin D signaling pathway is functional in BC slices, a model which preserves stromal-epithelial interactions and mimics in vivo conditions. (C) 2010 Elsevier Ltd. All rights reserved.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

An optimization model for antibiotic use

There is a positive correlation between the intensity of use of a given antibiotic and the prevalence of resistant strains. The more you treat, more patients infected with resistant strains appears and, as a consequence, the higher the mortality due to the infection and the longer the hospitalization time. In contrast, the less you treat, the higher the mortality rates and the longer the hospitalization time of patients infected with sensitive strains that could be successfully treated. The hypothesis proposed in this paper is an attempt to solve such a conflict: there must be an optimum treatment intensity that minimizes both the additional mortality and hospitalization time due to the infection by both sensitive and resistant bacteria strains. In order to test this hypothesis we applied a simple mathematical model that allowed us to estimate the optimum proportion of patients to be treated in order to minimize the total number of deaths and hospitalization time due to the infection in a hospital setting. (C) 2007 Elsevier Inc. All rights reserved.

Diagnostic model based on Raman spectra of normal, hyperplasia and prostate adenocarcinoma tissues in vitro

This study evaluated the use of Raman spectroscopy to identify the spectral differences between normal (N), benign hyperplasia (BPH) and adenocarcinoma (CaP) in fragments of prostate biopsies in vitro with the aim of developing a spectral diagnostic model for tissue classification. A dispersive Raman spectrometer was used with 830 nm wavelength and 80 mW excitation. Following Raman data collection and tissue histopathology (48 fragments diagnosed as N, 43 as BPH and 14 as CaP), two diagnostic models were developed in order to extract diagnostic information: the first using PCA and Mahalanobis analysis techniques and the second one a simplified biochemical model based on spectral features of cholesterol, collagen, smooth muscle cell and adipocyte. Spectral differences between N, BPH and CaP tissues, were observed mainly in the Raman bands associated with proteins, lipids, nucleic and amino acids. The PCA diagnostic model showed a sensitivity and specificity of 100%, which indicates the ability of PCA and Mahalanobis distance techniques to classify tissue changes in vitro. Also, it was found that the relative amount of collagen decreased while the amount of cholesterol and adipocyte increased with severity of the disease. Smooth muscle cell increased in BPH tissue. These characteristics were used for diagnostic purposes.

Capnography reflects ventilation/perfusion distribution in a model of acute lung injury

Background Changes in the shape of the capnogram may reflect changes in lung physiology. We studied the effect of different ventilation/perfusion ratios (V/Q) induced by positive end-expiratory pressures (PEEP) and lung recruitment on phase III slope (S(III)) of volumetric capnograms. Methods Seven lung-lavaged pigs received volume control ventilation at tidal volumes of 6 ml/kg. After a lung recruitment maneuver, open-lung PEEP (OL-PEEP) was defined at 2 cmH(2)O above the PEEP at the onset of lung collapse as identified by the maximum respiratory compliance during a decremental PEEP trial. Thereafter, six distinct PEEP levels either at OL-PEEP, 4 cmH(2)O above or below this level were applied in a random order, either with or without a prior lung recruitment maneuver. Ventilation-perfusion distribution (using multiple inert gas elimination technique), hemodynamics, blood gases and volumetric capnography data were recorded at the end of each condition (minute 40). Results S(III) showed the lowest value whenever lung recruitment and OL-PEEP were jointly applied and was associated with the lowest dispersion of ventilation and perfusion (Disp(R-E)), the lowest ratio of alveolar dead space to alveolar tidal volume (VD(alv)/VT(alv)) and the lowest difference between arterial and end-tidal pCO(2) (Pa-ETCO(2)). Spearman`s rank correlations between S(III) and Disp(R-E) showed a =0.85 with 95% CI for (Fisher`s Z-transformation) of 0.74-0.91, P < 0.0001. Conclusion In this experimental model of lung injury, changes in the phase III slope of the capnograms were directly correlated with the degree of ventilation/perfusion dispersion.

A general hazard model for lifetime data in the presence of cure rate

Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

Estimation of R(0) from the initial phase of an outbreak of a vector-borne infection

The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0) > 1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.