Blob formation and acceleration in the solar wind: role of converging flows and viscosity

The effect of viscosity and of converging flows on the formation of blobs in the slow solar wind is analysed by means of resistive MHD simulations. The regions above coronal streamers where blobs are formed (Sheeley et al., 1997) are simulated using a model previously proposed by Einaudi et al. (1999). The result of our investigation is twofold. First, we demonstrate a new mechanism for enhanced momentum transfer between a forming blob and the fast solar wind surrounding it. The effect is caused by the longer range of the electric field caused by the tearing instability forming the blob. The electric field reaches into the fast solar wind and interacts with it, causing a viscous drag that is global in nature rather than local across fluid layers as it is the case in normal uncharged fluids (like water). Second, the presence of a magnetic cusp at the tip of a coronal helmet streamer causes a converging of the flows on the two sides of the streamer and a direct push of the forming island by the fast solar wind, resulting in a more efficient momentum exchange

Resistive magnetohydrodynamic reconnection : resolving long-term, chaotic dynamics

We acknowledge financial support from the EC FP7/2007-2013 Grant Agreement SWIFF (No. 263340) and from project GOA/2009/009 (KU Leuven). This research has been funded by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (IAP P7/08 CHARM). Part of the simulations used the infrastructure of the VSC-Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government-Department EWI. Another part of the simulations was done at the former Danish Center for Scientific Computing at Copenhagen University which is now part of DeIC Danish e-Infrastructure Cooperation.In this paper, we address the long-term evolution of an idealised double current system entering reconnection regimes where chaotic behavior plays a prominent role. Our aim is to quantify the energetics in high magnetic Reynolds number evolutions, enriched by secondary tearing events, multiple magnetic island coalescence, and compressive versus resistive heating scenarios. Our study will pay particular attention to the required numerical resolutions achievable by modern (grid-adaptive) computations, and comment on the challenge associated with resolving chaotic island formation and interaction. We will use shock-capturing, conservative, grid-adaptive simulations for investigating trends dominated by both physical (resistivity) and numerical (resolution) parameters, and confront them with (visco-)resistive magnetohydrodynamic simulations performed with very different, but equally widely used discretization schemes. This will allow us to comment on the obtained evolutions in a manner irrespective of the adopted discretization strategy. Our findings demonstrate that all schemes used (finite volume based shock-capturing, high order finite differences, and particle in cell-like methods) qualitatively agree on the various evolutionary stages, and that resistivity values of order 0.001 already can lead to chaotic island appearance. However, none of the methods exploited demonstrates convergence in the strong sense in these chaotic regimes. At the same time, nonperturbed tests for showing convergence over long time scales in ideal to resistive regimes are provided as well, where all methods are shown to agree. Both the advantages and disadvantages of specific discretizations as applied to this challenging problem are discussed.Publisher PDFPeer reviewe

Lipoxin A4 and interleukin-8 levels in cystic fibrosis sputum after antibiotherapy

AbstractAntibiotics are largely prescribed for cystic fibrosis (CF) respiratory exacerbations. Effects of antibiotics on the inflammatory profile of the patients have been shown but remain controversial. Lipoxin A4 (LXA4) is a lipid mediator, reported to play a central role in resolving airway inflammation. The aim of the study was to investigate the consequences of antibiotherapy on LXA4 and IL-8 levels in CF patients' airways.MethodsEighteen CF patients (7 females, median age 20, range 8 to 47 years) consecutively admitted at the CF center of Montpellier for antibiotics during pulmonary exacerbation, were enrolled. Before and after antibiotics, all patients underwent spirometry (FEV1 and FVC), bacterial cultures and cell counts in sputa. IL-8 and LXA4 concentrations were determined in sputum samples by the median of immunometric assays.ResultsAs previously reported, after antibiotics therapy, FEV1 and FVC significantly improved. While neutrophil cell counts and IL-8 levels decreased, the LXA4 levels significantly increased after antibiotics therapy and were inversely correlated with IL-8 levels.In conclusion, we reported a correlation between antibiotics treatments and inflammatory markers in CF sputum. Our data provide evidences for a novel effect of antibiotics increasing the concentration of the anti-inflammatory lipid mediator LXA4

PRIMAGE project : predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours

Artificial intelligence, radiomics and other horizons in body composition assessment

This paper offers a brief overview of common non-invasive techniques for body composition assessment methods, and of the way images extracted by these methods can be processed with artificial intelligence (AI) and radiomic analysis. These new techniques are becoming more and more appealing in the field of health care, thanks to their ability to treat and process a huge amount of data, suggest new correlations between extracted imaging biomarkers and traits of several diseases as well as lead to the possibility to realise an increasingly personalized medicine. The idea is to suggest the use of AI applications and radiomic analysis to search for features that may be extracted from medical images [computed tomography (CT) and magnetic resonance imaging (MRI)], and that may turn out to be good predictors of metabolic disorder diseases and cancer. This could lead to patient-specific treatments and management of several diseases linked with excessive body fat

Pharmacogenetics and metabolism from science to implementation in clinical practice: the example of dihydropyrimidine dehydrogenase.

BACKGROUND: Fluoropyrimidines are widely used in the treatment of solid tumors and remain the backbone of many combination chemotherapy regimens. Despite their clinical benefit, they are associated with frequent gastrointestinal and hematological toxicities, which often lead to treatment discontinuation. Fluoropyrimidines undergo complex anabolic and catabolic biotransformation. Enzymes involved in this pathway include dihydropyrimidine dehydrogenase (DPD), which breaks down 5-FU and its prodrugs. Candidate gene approaches have demonstrated associations between 5-FU treatment outcomes and germline polymorphisms in DPD. The aim of this review is to report and discuss the latest results on fluoropyrimidine pharmacogenetics. METHODS: Literature from PubMed databases and bibliography from retrieved publications have been analyzed according to terms such DPD, DPYD, fluoropyrimdines, polymorphisms, toxicity, pharmacogenetics. RESULTS: To date, many sequence variations have been identified within DPYD gene, although the majority of these have no functional consequences on enzymatic activity. Nowadays, there is a general agreement on the clinical significance of the importance of DPD deficiency in patients who suffer from severe, life-threatening drug toxicity although preemptive testing is not applied to all patients. CONCLUSION: Considering the published literature, clinicians are strongly encouraged to consider testing for DPD poor metabolizer variants as a rational pre-treatment screening for patients candidate to a fluoropyrimidine-based regimens, in order to prevent toxicities and personalise treatments

Critical focus on mechanisms of resistance and toxicity of m-TOR inhibitors in pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (pNETs) are rare neoplasms representing less than 2% of all pancreatic malignancies. The PI3K-AKT-mTOR pathway is often deregulated in pNETs and seems to play a key role in tumorigenesis. Everolimus, an inhibitor of the mTOR pathway, has demonstrated efficacy in the treatment of pNETs. Nevertheless de novo or acquired drug resistance is responsible for disease progression and represents a major obstacle to overcome by clinicians. Blocking the PI3K/AKT/mTOR pathway may cover the supposed main mechanisms of resistance to everolimus. Therefore, BEZ-235, a potent oral dual PI3K/mTOR inhibitor was investigated in clinical trials. Globally more than 250 patients with different types of solid tumors were treated. Two studies were conducted in pNETs with BEZ-235 as single agent. The former was a phase 2 trial conducted in pNETs resistant to everolimus while the latter a randomized trial comparing everolimus and BEZ-235. Unfortunately, both the studies disappointed the expectations and were prematurely halted mainly due to severe toxicity. On this basis we reviewed m-TOR inhibitors in pNETs, focusing on their mechanisms of resistance and toxicity