A Bayesian Solution to the Behrens-Fisher problem

A simple solution to the Behrens–Fisher problem based on Bayes factors is presented, and its relation with the Behrens–Fisher distribution is explored. The construction of the Bayes factor is based on a simple hierarchical model, and has a closed form based on the densities of general Behrens–Fisher distributions. Simple asymptotic approximations of the Bayes factor, which are functions of the Kullback–Leibler divergence between normal distributions, are given, and it is also proved to be consistent. Some examples and comparisons are also presented.Open access funding provided by Universidad de Málaga/CBUA

A bayesian approach for one-way ANOVA under unequal variances

In this report a Bayesian solution to the problem of testing the equality of the means of k independent normal populations with unknown and arbitrary variances is provided. An important issue in the solution of this problem is the determination of groups with equal means, often solved by multiple comparisons, which can lead to results that are difficult to interpret. In order to avoid this drawback, we propose to treat all possible alternatives existing in the alternative hypothesis by considering the set of all possible configurations of the set of k means. This idea is closely related to the statistical pro-blem of cluster analysis. This allows us to reformulate the testing problem in terms of model selection. A hierarchical model is proposed to compute the Bayes factor of all models, as well as the posterior probability of all the possible configurations. Some illustrative examples of the goodness of the proposed solution are presented.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

An FPGA Kalman-MPPT implementation adapted in SST-based dual active bridge converters for DC microgrids systems

The design of digital hardware controllers for the integration of renewable energy sources in DC microgrids is a research topic of interest. In this paper, a Kalman filter-based maximum power point tracking algorithm is implemented in an FPGA and adapted in a dual active bridge (DAB) converter topology for DC microgrids. This approach uses the Hardware/Software (HW/SW) co-design paradigm in combination with a pipelined piecewise polynomial approximation design of the Kalman-maximum power point tracking (MPPT) algorithm instead of traditional lookup table (LUT)-based methods. Experimental results reveal a good integration of the Kalman-MPPT design with the DAB-based converter, particularly during irradiation and temperature variations due to changes in weather conditions, as well as a good balanced hardware design in complexity and area-time performance compared to other state-of-art FPGA designs

Metformin-induced preferential killing of breast cancer initiating CD44+CD24−/low cells is sufficient to overcome primary resistance to trastuzumab in HER2+ human breast cancer xenografts

Trastuzumab-refractory breast cancer stem cells (CSCs) could explain the high rate of primary resistance to single-agent trastuzumab in HER2 gene-amplified breast cancer patients. The identification of agents with strong selective toxicity for trastuzumab-resistant breast CSCs may have tremendous relevance for how HER2+ breast cancer patients should be treated. Using the human breast cancer cell line JIMT-1, which was established from the pleural metastasis of a patient who was clinically resistant to trastuzumab ab initio, we examined whether preferential killing of the putative CD44+CD24 −/low breast CSC population might be sufficient to overcome primary resistance to trastuzumab in vivo. Because recent studies have shown that the anti-diabetic biguanide metformin can exert antitumor effects by targeted killing of CSC-like cells, we explored whether metformin's ability to preferentially kill breast cancer initiating CD44+CD24 −/low cells may have the potential to sensitize JIMT-1 xenograft mouse models to trastuzumab. Upon isolation for breast cancer initiating CD44+CD24 −/low cells by employing magnetic activated cell sorting, we observed the kinetics of metformin-induced killing drastically varied among CSC and non-CSC subpopulations. Metformin's cell killing effect increased dramatically by more than 10-fold in CD44+CD24 −/low breast CSC cells compared to non-CD44+CD24 −/low immunophenotypes. While seven-weeks treatment length with trastuzumab likewise failed to reduce tumor growth of JIMT-1 xenografts, systemic treatment with metformin as single agent resulted in a significant two-fold reduction in tumor volume. When trastuzumab was combined with concurrent metformin, tumor volume decreased sharply by more than four-fold. Given that metformin-induced preferential killing of breast cancer initiating CD44+CD24 −/low subpopulations is sufficient to overcome in vivo primary resistance to trastuzumab, the incorporation of metformin into trastuzumab-based regimens may provide a valuable strategy for treatment of HER2+ breast cancer patients

Stratification of cancer and diabetes based on circulating levels of formate and glucose

Background: Serum and urine metabolites have been investigated for their use as cancer biomarkers. The specificity of candidate metabolites can be limited by the impact of other disorders on metabolite levels. In particular, the increasing incidence of obesity could become a significant confounding factor. Methods: Here we developed a multinomial classifier for the stratification of cancer, obesity and healthy phenotypes based on circulating glucose and formate levels. We quantified the classifier performance from the retrospective analysis of samples from breast cancer, lung cancer, obese individuals and healthy controls. Results: We discovered that circulating formate levels are significantly lower in breast and lung cancer patients than in healthy controls. However, the performance of a cancer classifier based on formate levels alone is limited because obese patients also have low serum formate levels. By introducing a multinomial classifier based on circulating glucose and formate levels, we were able to improve the classifier performance, reaching a true positive rate of 79% with a false positive rate of 8%. Conclusions: Circulating formate is reduced in HER2+ breast cancer, non-small cell lung cancer and highly obese patients relative to healthy controls. Further studies are required to determine the relevance of these observations in other cancer types and diseases