Cycle-based Cluster Variational Method for Direct and Inverse Inference

We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure

Recovery of lung function following a pulmonary exacerbation in patients with cystic fibrosis and the G551D-CFTR mutation treated with ivacaftor

BACKGROUND: Pulmonary exacerbations (PEx) are associated with acute loss of lung function that is often not recovered after treatment. We investigated lung function recovery following PEx for ivacaftor- and placebo-treated subjects. METHODS: Short- and long-term pulmonary function recovery data after PEx were summarized from a placebo-controlled trial in 161 cystic fibrosis patients≥12years old with the G551D-CFTR mutation (NCT00909532). Short-term recovery was measured 2 to 8weeks after treatment, and long-term recovery was determined at the end-of-study, both compared with baseline measured just prior to the PEx. RESULTS: Fewer patients receiving ivacaftor experienced a PEx than patients receiving placebo (33.7% vs. 56.4%; P=0.004) and had a lower adjusted incidence rate of PEx (0.589 vs. 1.382; P<0.001). The proportion of PEx followed by full short-term recovery of percent predicted forced expiratory volume in 1s was similar (ivacaftor vs. placebo, 57.1% vs. 53.7), as was the proportion of patients having long-term recovery (46.4% vs. 47.7%). CONCLUSIONS: Ivacaftor treatment reduces the frequency of PEx but does not improve on the rate of complete lung function recovery after PEx when compared with placebo

Photodynamic and Antibiotic Therapy Impair the Pathogenesis of Enterococcus faecium in a Whole Animal Insect Model

Enterococcus faecium has emerged as one of the most important pathogens in healthcare-associated infections worldwide due to its intrinsic and acquired resistance to many antibiotics, including vancomycin. Antimicrobial photodynamic therapy (aPDT) is an alternative therapeutic platform that is currently under investigation for the control and treatment of infections. PDT is based on the use of photoactive dye molecules, widely known as photosensitizer (PS). PS, upon irradiation with visible light, produces reactive oxygen species that can destroy lipids and proteins causing cell death. We employed Galleria mellonella (the greater wax moth) caterpillar fatally infected with E. faecium to develop an invertebrate host model system that can be used to study the antimicrobial PDT (alone or combined with antibiotics). In the establishment of infection by E. faecium in G. mellonella, we found that the G. mellonella death rate was dependent on the number of bacterial cells injected into the insect hemocoel and all E. faecium strains tested were capable of infecting and killing G. mellonella. Antibiotic treatment with ampicillin, gentamicin or the combination of ampicillin and gentamicin prolonged caterpillar survival infected by E. faecium (P = 0.0003, P = 0.0001 and P = 0.0001, respectively). In the study of antimicrobial PDT, we verified that methylene blue (MB) injected into the insect followed by whole body illumination prolonged the caterpillar survival (P = 0.0192). Interestingly, combination therapy of larvae infected with vancomycin-resistant E. faecium, with antimicrobial PDT followed by vancomycin, significantly prolonged the survival of the caterpillars when compared to either antimicrobial PDT (P = 0.0095) or vancomycin treatment alone (P = 0.0025), suggesting that the aPDT made the vancomycin resistant E. faecium strain more susceptible to vancomycin action. In summary, G. mellonella provides an invertebrate model host to study the antimicrobial PDT and to explore combinatorial aPDT-based treatments

Exploring new physics frontiers through numerical relativity

The demand to obtain answers to highly complex problems within strong-field gravity has been met with significant progress in the numerical solution of Einstein's equations - along with some spectacular results - in various setups. We review techniques for solving Einstein's equations in generic spacetimes, focusing on fully nonlinear evolutions but also on how to benchmark those results with perturbative approaches. The results address problems in high-energy physics, holography, mathematical physics, fundamental physics, astrophysics and cosmology

The Bin Area Method: A Computationally Efficient Technique for Analysis of Ventricular and Atrial Intracardiac Electrograms

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74901/1/j.1540-8159.1990.tb02028.x.pd

A survey on independence-based Markov networks learning

This work reports the most relevant technical aspects in the problem of learning the \emph{Markov network structure} from data. Such problem has become increasingly important in machine learning, and many other application fields of machine learning. Markov networks, together with Bayesian networks, are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. Learning graphical models from data have been extensively applied for the case of Bayesian networks, but for Markov networks learning it is not tractable in practice. However, this situation is changing with time, given the exponential growth of computers capacity, the plethora of available digital data, and the researching on new learning technologies. This work stresses on a technology called independence-based learning, which allows the learning of the independence structure of those networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sampling of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms for learning Markov networks structure, discussing its current limitations, and proposing a series of open problems where future works may produce some advances in the area in terms of quality and efficiency. The paper concludes by opening a discussion about how to develop a general formalism for improving the quality of the structures learned, when data is scarce.Comment: 35 pages, 1 figur

Monitoring of Regulatory T Cell Frequencies and Expression of CTLA-4 on T Cells, before and after DC Vaccination, Can Predict Survival in GBM Patients

PURPOSE: Dendritic cell (DC) vaccines have recently emerged as an innovative therapeutic option for glioblastoma patients. To identify novel surrogates of anti-tumor immune responsiveness, we studied the dynamic expression of activation and inhibitory markers on peripheral blood lymphocyte (PBL) subsets in glioblastoma patients treated with DC vaccination at UCLA. EXPERIMENTAL DESIGN: Pre-treatment and post-treatment PBL from 24 patients enrolled in two Phase I clinical trials of dendritic cell immunotherapy were stained and analyzed using flow cytometry. A univariate Cox proportional hazards model was utilized to investigate the association between continuous immune monitoring variables and survival. Finally, the immune monitoring variables were dichotomized and a recursive partitioning survival tree was built to obtain cut-off values predictive of survival. RESULTS: The change in regulatory T cell (CD3(+)CD4(+)CD25(+)CD127(low)) frequency in PBL was significantly associated with survival (p = 0.0228; hazard ratio = 3.623) after DC vaccination. Furthermore, the dynamic expression of the negative co-stimulatory molecule, CTLA-4, was also significantly associated with survival on CD3(+)CD4(+) T cells (p = 0.0191; hazard ratio = 2.840) and CD3(+)CD8(+) T cells (p = 0.0273; hazard ratio = 2.690), while that of activation markers (CD25, CD69) was not. Finally, a recursive partitioning tree algorithm was utilized to dichotomize the post/pre fold change immune monitoring variables. The resultant cut-off values from these immune monitoring variables could effectively segregate these patients into groups with significantly different overall survival curves. CONCLUSIONS: Our results suggest that monitoring the change in regulatory T cell frequencies and dynamic expression of the negative co-stimulatory molecules on peripheral blood T cells, before and after DC vaccination, may predict survival. The cut-off point generated from these data can be utilized in future prospective immunotherapy trials to further evaluate its predictive validity

An interdisciplinary team communication framework and its application to healthcare 'e-teams' systems design

<p>Abstract</p> <p>Background</p> <p>There are few studies that examine the processes that interdisciplinary teams engage in and how we can design health information systems (HIS) to support those team processes. This was an exploratory study with two purposes: (1) To develop a framework for interdisciplinary team communication based on structures, processes and outcomes that were identified as having occurred during weekly team meetings. (2) To use the framework to guide 'e-teams' HIS design to support interdisciplinary team meeting communication.</p> <p>Methods</p> <p>An ethnographic approach was used to collect data on two interdisciplinary teams. Qualitative content analysis was used to analyze the data according to structures, processes and outcomes.</p> <p>Results</p> <p>We present details for team meta-concepts of structures, processes and outcomes and the concepts and sub concepts within each meta-concept. We also provide an exploratory framework for interdisciplinary team communication and describe how the framework can guide HIS design to support 'e-teams'.</p> <p>Conclusion</p> <p>The structures, processes and outcomes that describe interdisciplinary teams are complex and often occur in a non-linear fashion. Electronic data support, process facilitation and team video conferencing are three HIS tools that can enhance team function.</p

Th17 Cells Are Involved in the Local Control of Tumor Progression in Primary Intraocular Lymphoma

BACKGROUND: Th17 cells play an important role in the pathogenesis of many autoimmune diseases, but despite some reports of their antitumor properties, too little is known about their presence and role in cancers. Specifically, knowledge is sparse about the relation of Th17 to lymphoma microenvironments and, more particularly, to the microenvironment of primary intraocular B-cell lymphoma (PIOL), an aggressive lymphoma with a poor prognosis. METHODS AND PRINCIPAL FINDINGS: In this work, we investigated the presence of Th17 cells and their related cytokines in a syngeneic model of PIOL, a subtype of non-Hodgkin lymphoma. The very small number of lymphocytes trafficking in normal eyes, which represent a low background as compared to tumor-bearing eyes, allows us to develop the present model to characterize the different lymphocyte subsets present when a tumor is developing. IL-21 mRNA was expressed concomitantly with IL-17 mRNA in tumor-bearing eyes and intracellular expression of IL-17A and IL-21 in infiltrating CD4(+) T lymphocytes. Interestingly, IL-17A production by T cells was negatively correlated with tumor burden. We also showed that IL-21 but not IL-17 inhibits tumor cell proliferation in vitro. CONCLUSIONS: These data demonstrate that IL-17A and IL-21-producing CD4(+) T cells, referred as Th17 cells, infiltrate this tumor locally and suggest that Th17-related cytokines may counteract tumor progression via IL-21 production. Thus, Th17 cells or their related cytokines could be considered to be a new therapeutic approach for non-Hodgkin B-cell lymphomas, particularly those with an ocular localization