Progress in front propagation research

We review the progress in the field of front propagation in recent years. We survey many physical, biophysical and cross-disciplinary applications, including reduced-variable models of combustion flames, Reid's paradox of rapid forest range expansions, the European colonization of North America during the 19th century, the Neolithic transition in Europe from 13 000 to 5000 years ago, the description of subsistence boundaries, the formation of cultural boundaries, the spread of genetic mutations, theory and experiments on virus infections, models of cancer tumors, etc. Recent theoretical advances are unified in a single framework, encompassing very diverse systems such as those with biased random walks, distributed delays, sequential reaction and dispersion, cohabitation models, age structure and systems with several interacting species. Directions for future progress are outlined

The role of integrins in glioma biology and anti-glioma therapies.

The tumor environment is critical for tumor maintenance and progression. Integrins are a large family of cell surface receptors mediating the interaction of tumor cells with their microenvironment and play important roles in glioma biology, including migration, invasion, angiogenesis and tumor stem cell anchorage. Here, we review preclinical and clinical data on integrin inhibition in malignant gliomas. Various pharmacological approaches to the modulation of integrin signaling have been explored including antibodies and peptide-based agents. Cilengitide, a cyclic RGD-mimetic peptide of αvβ3 and αvβ5 integrins is in advanced clinical development in glioblastoma. Cilengitide had only limited activity as a single agent in glioblastoma, but, when added to standard radiochemotherapy, appeared to prolong progression-free and overall survival in patients with newly diagnosed glioblastomas and methylation of the promoter of the O⁶ methylguanine methyltransferase (MGMT) gene. MGMT gene promoter methylation in turn predicts benefit from alkylating chemotherapy. A phase III randomized clinical trial in conjunction with standard radiochemotherapy in newly diagnosed glioblastoma patients with MGMT gene promoter methylation has recently completed accrual (EORTC 26071-22072). A companion trial explores a dose-escalated regimen of cilengitide added to radiotherapy plus temozolomide in patients without MGMT gene promoter methylation. Promising results in these trials would probably result in a broader interest in integrins as targets for glioma therapy and hopefully the development of a broader panel of anti-integrin agents.

Progress in front propagation research

We review the progress in the field of front propagation in recent years. We survey many physical, biophysical and cross-disciplinary applications, including reduced-variable models of combustion flames, Reid's paradox of rapid forest range expansions, the European colonization of North America during the 19th century, the Neolithic transition in Europe from 13 000 to 5000 years ago, the description of subsistence boundaries, the formation of cultural boundaries, the spread of genetic mutations, theory and experiments on virus infections, models of cancer tumors, etc. Recent theoretical advances are unified in a single framework, encompassing very diverse systems such as those with biased random walks, distributed delays, sequential reaction and dispersion, cohabitation models, age structure and systems with several interacting species. Directions for future progress are outlined

Functional connectivity of reward processing in the brain

Controversial results have been reported concerning the neural mechanisms involved in the processing of rewards and punishments. On the one hand, there is evidence suggesting that monetary gains and losses activate a similar fronto-subcortical network. On the other hand, results of recent studies imply that reward and punishment may engage distinct neural mechanisms. Using functional magnetic resonance imaging (fMRI) we investigated both regional and interregional functional connectivity patterns while participants performed a gambling task featuring unexpectedly high monetary gains and losses. Classical univariate statistical analysis showed that monetary gains and losses activated a similar fronto-striatallimbic network, in which main activation peaks were observed bilaterally in the ventral striatum. Functional connectivity analysis showed similar responses for gain and loss conditions in the insular cortex, the amygdala, and the hippocampus that correlated with the activity observed in the seed region ventral striatum, with the connectivity to the amygdala appearing more pronounced after losses. Larger functional connectivity was found to the medial orbitofrontal cortex for negative outcomes. The fact that different functional patterns were obtained with both analyses suggests that the brain activations observed in the classical univariate approach identifi es the involvement of different functional networks in the current task. These results stress the importance of studying functional connectivity in addition to standard fMRI analysis in reward-related studies.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Time in e-Learning Research: A Qualitative Review of the Empirical Consideration of Time in Research into e-Learning

Peer-reviewed

Temporal issues in e-learning research: A literature review

Peer-reviewed

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood.

When a bloodstream infection (BSI) is suspected, most of the laboratory results-biochemical and haematologic-are available within the first hours after hospital admission of the patient. This is not the case for diagnostic microbiology, which generally takes a longer time because blood culture, which is to date the reference standard for the documentation of the BSI microbial agents, relies on bacterial or fungal growth. The microbial diagnosis of BSI directly from blood has been proposed to speed the determination of the etiological agent but was limited by the very low number of circulating microbes during these paucibacterial infections. Thanks to recent advances in molecular biology, including the improvement of nucleic acid extraction and amplification, several PCR-based methods for the diagnosis of BSI directly from whole blood have emerged. In the present review, we discuss the advantages and limitations of these new molecular approaches, which at best complement the culture-based diagnosis of BSI.

Longitudinal study of informed consent in innovative therapy research: experience and provisional recommendations from a multicenter trial of intracerebral grafting.

BACKGROUND: There is an urgent need to assess and improve the consent process in clinical trials of innovative therapies for neurodegenerative disorders. METHODS: We performed a longitudinal study of the consent of Huntington's disease patients during the Multicenter Fetal Cell Intracerebral Grafting Trial in Huntington's Disease (MIG-HD) in France and Belgium. Patients and their proxies completed a consent questionnaire at inclusion, before signing the consent form and after one year of follow-up, before randomization and transplantation. The questionnaire explored understanding of the protocol, satisfaction with the information delivered, reasons for participating in the trial and expectations regarding the transplant. Forty-six Huntington's disease patients and 27 proxies completed the questionnaire at inclusion, and 27 Huntington's disease patients and 16 proxies one year later. RESULTS: The comprehension score was high and similar for Huntington's disease patients and proxies at inclusion (72.6% vs 77.8%; P > 0.1) but only decreased in HD patients after one year. The information satisfaction score was high (73.5% vs 66.5%; P > 0.1) and correlated with understanding in both patients and proxies. The motivation and expectation profiles were similar in patients and proxies and remained unchanged after one year. CONCLUSIONS: Cognitively impaired patients with Huntington's disease were capable of consenting to participation in this trial. This consent procedure has presumably strengthened their understanding and should be proposed before signing the consent form in future gene or cell therapy trials for neurodegenerative disorders. Because of the potential cognitive decline, proxies should be designated as provisional surrogate decision-makers, even in competent patients.

Visualizing the spatiotemporal dynamics of DNA damage in budding yeast.

Fluorescence microscopy has enabled the analysis of both the spatial distribution of DNA damage and its dynamics during the DNA damage response (DDR). Three microscopic techniques can be used to study the spatiotemporal dynamics of DNA damage. In the first part we describe how we determine the position of DNA double-strand breaks (DSBs) relative to the nuclear envelope. The second part describes how to quantify the co-localization of DNA DSBs with nuclear pore clusters, or other nuclear subcompartments. The final protocols describe methods for the quantification of locus mobility over time.