A defense of backwards in time causation models in quantum mechanics

This paper offers a defense of backwards in time causation models in quantum mechanics. Particular attention is given to Cramer's transactional account, which is shown to have the threefold virtue of solving the Bell problem, explaining the complex conjugate aspect of the quantum mechanical formalism, and explaining various quantum mysteries such as Schrodinger's cat. The question is therefore asked, why has this model not received more attention from physicists and philosophers? One objection given by physicists in assessing Cramer's theory was that it is not testable. This paper seeks to answer this concern by utilizing an argument that backwards causation models entail a fork theory of causal direction. From the backwards causation model together with the fork theory one can deduce empirical predictions. Finally, the objection that this strategy is questionable because of its appeal to philosophy is deflected.

Risk Estimates of Dengue in Travelers to Dengue Endemic Areas Using Mathematical Models

Dengue has emerged as a frequent problem in international travelers. The risk depends on destination, duration, and season of travel. However, data to quantify the true risk for travelers to acquire dengue are lacking. We used mathematical models to estimate the risk of nonimmune persons to acquire dengue when traveling to Singapore. From the force of infection, we calculated the risk of dengue dependent on duration of stay and season of arrival. Our data highlight that the risk for nonimmune travelers to acquire dengue in Singapore is substantial but varies greatly with seasons and epidemic cycles. For instance, for a traveler who stays in Singapore for 1 week during the high dengue season in 2005, the risk of acquiring dengue was 0.17%, but it was only 0.00423% during the low season in a nonepidemic year such as 2002. Risk estimates based on mathematical modeling will help the travel medicine provider give better evidence-based advice for travelers to dengue endemic countries.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

Systemic lupus erythematosus exhibits a dynamic and continuum spectrum of effector/regulatory T cells

Objective: The identification of regulatory T cells (Treg cells) as CD4(+)CD25(high) cells may be upset by the increased frequency of activated effector T cells (Teff cells) in inflammatory diseases such as systemic lupus erythematosus (SLE). This study aimed to evaluate the frequency of T-cell subsets according to the expression of CD25 and CD127 in active (A-SLE) and inactive SLE (I-SLE). Methods: Peripheral blood mononuclear cells (PBMCs) from 26 A-SLE patients (SLE Disease Activity Index (SLEDAI) = 10.17 +/- 3.7), 31 I-SLE patients (SLEDAI = 0), and 26 healthy controls (HC) were analysed by multicolour flow. cytometry. Results: CD25(high) cell frequency was increased in A-SLE (5.2 +/- 5.7%) compared to I-SLE (3.4 +/- 3.4%) and HC (1.73 +/- 0.8%) (p < 0.01). However, the percentage of FoxP3(+) cells in the CD25(high) subset was decreased in A-SLE (24.6 +/- 16.4%) compared to I-SLE (33.7 +/- 16) and HC (45 +/- 25.1%) (p < 0.01). This was partly due to the increased frequency of Teff cells (CD25(high)CD127(+)FoxP3(empty set)) in A-SLE (10.7 +/- 7.3%) compared to I-SLE (8.5 +/- 6.5) and HC (6.1 +/- 1.8%) (p = 0.02). Hence the frequency of Treg cells (CD25(+/high)CD127(low/empty set)FoxP3(+)) was equivalent in A-SLE (1.4 +/- 0.8%), I-SLE (1.37 +/- 1.0%), and HC (1.13 +/- 0.59%) (p = 0.42). A-SLE presented an increased frequency of CD25(+)CD127(+)FoxP3(+) and CD25(empty set)FoxP3(+)CD127(low/empty set) T cells, which may represent intermediate phenotypes between Treg and Teff cells. Conclusions: The present study has provided data supporting normal Treg cell frequency in A-SLE and I-SLE as well as increased frequency of Teff cells in A-SLE. This scenario reflects a Treg/Teff ratio imbalance that may favour the inflammatory phenotype of the disease. In addition, the increased frequency of T cells with putative intermediate phenotypes may be compatible with a highly dynamic immune system in SLE.

Predictive models for diagnosis of pleural effusions secondary to tuberculosis or cancer

Background and objective: Tuberculosis (TB) and cancer are two of the main causes of pleural effusions which frequently share similar clinical features and pleural fluid profiles. This study aimed to identify diagnostic models based on clinical and laboratory variables to differentiate tuberculous from malignant pleural effusions. Methods: A retrospective study of 403 patients (200 with TB; 203 with cancer) was undertaken. Univariate analysis was used to select the clinical variables relevant to the models composition. Variables beta coefficients were used to define a numerical score which presented a practical use. The performances of the most efficient models were tested in a sample of pleural exudates (64 new cases). Results: Two models are proposed for the diagnosis of effusions associated with each disease. For TB: (i) adenosine deaminase (ADA), globulins and the absence of malignant cells in the pleural fluid; and (ii) ADA, globulins and fluid appearance. For cancer: (i) patient age, fluid appearance, macrophage percentage and presence of atypical cells in the pleural fluid; and (ii) as for (i) excluding atypical cells. Application of the models to the 64 pleural effusions showed accuracy higher than 85% for all models. Conclusions: The proposed models were effective in suggesting pleural tuberculosis or cancer.