Simulation of surface waves in porous media

We present a novel numerical algorithm for the simulation of seismic wave propagation in porous media, which is particularly suitable for the accurate modelling of surface wave-type phenomena. The differential equations of motion are based on Biot's theory of poro-elasticity and solved with a pseudospectral approach using Fourier and Chebyshev methods to compute the spatial derivatives along the horizontal and vertical directions, respectively. The time solver is a splitting algorithm that accounts for the stiffness of the differential equations. Due to the Chebyshev operator the grid spacing in the vertical direction is non-uniform and characterized by a denser spatial sampling in the vicinity of interfaces, which allows for a numerically stable and accurate evaluation of higher order surface wave modes. We stretch the grid in the vertical direction to increase the minimum grid spacing and reduce the computational cost. The free-surface boundary conditions are implemented with a characteristics approach, where the characteristic variables are evaluated at zero viscosity. The same procedure is used to model seismic wave propagation at the interface between a fluid and porous medium. In this case, each medium is represented by a different grid and the two grids are combined through a domain-decomposition method. This wavefield decomposition method accounts for the discontinuity of variables and is crucial for an accurate interface treatment. We simulate seismic wave propagation with open-pore and sealed-pore boundary conditions and verify the validity and accuracy of the algorithm by comparing the numerical simulations to analytical solutions based on zero viscosity obtained with the Cagniard-de Hoop method. Finally, we illustrate the suitability of our algorithm for more complex models of porous media involving viscous pore fluids and strongly heterogeneous distributions of the elastic and hydraulic material properties.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

External irradiation with or without long-term androgen suppression for prostate cancer with high metastatic risk: 10-year results of an EORTC randomised study.

BACKGROUND: We did a randomised phase 3 trial assessing the benefit of addition of long-term androgen suppression with a luteinising-hormone-releasing hormone (LHRH) agonist to external irradiation in patients with prostate cancer with high metastatic risk. In this report, we present the 10-year results. METHODS: For this open-label randomised trial, eligible patients were younger than 80 years and had newly diagnosed histologically proven T1-2 prostatic adenocarcinoma with WHO histological grade 3 or T3-4 prostatic adenocarcinoma of any histological grade, and a WHO performance status of 0-2. Patients were randomly assigned (1:1) to receive radiotherapy alone or radiotherapy plus immediate androgen suppression. Treatment allocation was open label and used a minimisation algorithm with institution, clinical stage of the disease, results of pelvic-lymph-node dissection, and irradiation fields extension as minimisation factors. Patients were irradiated externally, once a day, 5 days a week, for 7 weeks to a total dose of 50 Gy to the whole pelvis, with an additional 20 Gy to the prostate and seminal vesicles. The LHRH agonist, goserelin acetate (3·6 mg subcutaneously every 4 weeks), was started on the first day of irradiation and continued for 3 years; cyproterone acetate (50 mg orally three times a day) was given for 1 month starting a week before the first goserelin injection. The primary endpoint was clinical disease-free survival. Analysis was by intention to treat. The trial is registered at ClinicalTrials.gov, number NCT00849082. FINDINGS: Between May 22, 1987, and Oct 31, 1995, 415 patients were randomly assigned to treatment groups and were included in the analysis (208 radiotherapy alone, 207 combined treatment). Median follow-up was 9·1 years (IQR 5·1-12·6). 10-year clinical disease-free survival was 22·7% (95% CI 16·3-29·7) in the radiotherapy-alone group and 47·7% (39·0-56·0) in the combined treatment group (hazard ratio [HR] 0·42, 95% CI 0·33-0·55, p<0·0001). 10-year overall survival was 39·8% (95% CI 31·9-47·5) in patients receiving radiotherapy alone and 58·1% (49·2-66·0) in those allocated combined treatment (HR 0·60, 95% CI 0·45-0·80, p=0·0004), and 10-year prostate-cancer mortality was 30·4% (95% CI 23·2-37·5) and 10·3% (5·1-15·4), respectively (HR 0·38, 95% CI 0·24-0·60, p<0·0001). No significant difference in cardiovascular mortality was noted between treatment groups both in patients who had cardiovascular problems at study entry (eight of 53 patients in the combined treatment group had a cardiovascular-related cause of death vs 11 of 63 in the radiotherapy group; p=0·60) and in those who did not (14 of 154 vs six of 145; p=0·25). Two fractures were reported in patients allocated combined treatment. INTERPRETATION: In patients with prostate cancer with high metastatic risk, immediate androgen suppression with an LHRH agonist given during and for 3 years after external irradiation improves 10-year disease-free and overall survival without increasing late cardiovascular toxicity.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Long-term miR-669a therapy alleviates chronic dilated cardiomyopathy in dystrophic mice.

BACKGROUND: Dilated cardiomyopathy (DCM) is a leading cause of chronic morbidity and mortality in muscular dystrophy (MD) patients. Current pharmacological treatments are not yet able to counteract chronic myocardial wastage, thus novel therapies are being intensely explored. MicroRNAs have been implicated as fine regulators of cardiomyopathic progression. Previously, miR-669a downregulation has been linked to the severe DCM progression displayed by Sgcb-null dystrophic mice. However, the impact of long-term overexpression of miR-669a on muscle structure and functionality of the dystrophic heart is yet unknown. METHODS AND RESULTS: Here, we demonstrate that intraventricular delivery of adeno-associated viral (AAV) vectors induces long-term (18 months) miR-669a overexpression and improves survival of Sgcb-null mice. Treated hearts display significant decrease in hypertrophic remodeling, fibrosis, and cardiomyocyte apoptosis. Moreover, miR-669a treatment increases sarcomere organization, reduces ventricular atrial natriuretic peptide (ANP) levels, and ameliorates gene/miRNA profile of DCM markers. Furthermore, long-term miR-669a overexpression significantly reduces adverse remodeling and enhances systolic fractional shortening of the left ventricle in treated dystrophic mice, without significant detrimental consequences on skeletal muscle wastage. CONCLUSIONS: Our findings provide the first evidence of long-term beneficial impact of AAV-mediated miRNA therapy in a transgenic model of severe, chronic MD-associated DCM.

Associations of short-term particle and noise exposures with markers of cardiovascular and respiratory health among highway maintenance workers

BACKGROUND: Highway maintenance workers are constantly and simultaneously exposed to traffic-related particle and noise emissions, and both have been linked to increased cardiovascular morbidity and mortality in population-based epidemiology studies. OBJECTIVES: We aimed to investigate short-term health effects related to particle and noise exposure. METHODS: We monitored 18 maintenance workers, during as many as five 24-hour periods from a total of 50 observation days. We measured their exposure to fine particulate matter (PM2.5), ultrafine particles, noise, and the cardiopulmonary health endpoints: blood pressure, pro-inflammatory and pro-thrombotic markers in the blood, lung function and fractional exhaled nitric oxide (FeNO) measured approximately 15 hours post-work. Heart rate variability was assessed during a sleep period approximately 10 hours post-work. RESULTS: PM2.5 exposure was significantly associated with C-reactive protein and serum amyloid A, and negatively associated with tumor necrosis factor α. None of the particle metrics were significantly associated with von Willebrand factor or tissue factor expression. PM2.5 and work noise were associated with markers of increased heart rate variability, and with increased HF and LF power. Systolic and diastolic blood pressure on the following morning were significantly associated with noise exposure after work, and non-significantly associated with PM2.5. We observed no significant associations between any of the exposures and lung function or FeNO. CONCLUSIONS: Our findings suggest that exposure to particles and noise during highway maintenance work might pose a cardiovascular health risk. Actions to reduce these exposures could lead to better health for this population of workers.

Long-Term Trends of HIV Type 1 Drug Resistance Prevalence among Antiretroviral Treatment-Experienced Patients in Switzerland.

Background. Accurate quantification of the prevalence of human immunodeficiency virus type 1 (HIV-1) drug resistance in patients who are receiving antiretroviral therapy (ART) is difficult, and results from previous studies vary. We attempted to assess the prevalence and dynamics of resistance in a highly representative patient cohort from Switzerland. Methods. On the basis of genotypic resistance test results and clinical data, we grouped patients according to their risk of harboring resistant viruses. Estimates of resistance prevalence were calculated on the basis of either the proportion of individuals with a virologic failure or confirmed drug resistance (lower estimate) or the frequency-weighted average of risk group-specific probabilities for the presence of drug resistance mutations (upper estimate). Results. Lower and upper estimates of drug resistance prevalence in 8064 ART-exposed patients were 50% and 57% in 1999 and 37% and 45% in 2007, respectively. This decrease was driven by 2 mechanisms: loss to follow-up or death of high-risk patients exposed to mono- or dual-nucleoside reverse-transcriptase inhibitor therapy (lower estimates range from 72% to 75%) and continued enrollment of low-risk patients who were taking combination ART containing boosted protease inhibitors or nonnucleoside reverse-transcriptase inhibitors as first-line therapy (lower estimates range from 7% to 12%). A subset of 4184 participants (52%) had 1 study visit per year during 2002-2007. In this subset, lower and upper estimates increased from 45% to 49% and from 52% to 55%, respectively. Yearly increases in prevalence were becoming smaller in later years. Conclusions. Contrary to earlier predictions, in situations of free access to drugs, close monitoring, and rapid introduction of new potent therapies, the emergence of drug-resistant viruses can be minimized at the population level. Moreover, this study demonstrates the necessity of interpreting time trends in the context of evolving cohort populations.

Long-term outcome after cognitive and behavioral regression in nonlesional epilepsy with continuous spike-waves during slow-wave sleep.

PURPOSE: To present the long-term follow-up of 10 adolescents and young adults with documented cognitive and behavioral regression as children due to nonlesional focal, mainly frontal, epilepsy with continuous spike-waves during slow wave sleep (CSWS). METHODS: Past medical and electroencephalography (EEG) data were reviewed and neuropsychological tests exploring main cognitive functions were administered. KEY FINDINGS: After a mean duration of follow-up of 15.6 years (range, 8-23 years), none of the 10 patients had recovered fully, but four regained borderline to normal intelligence and were almost independent. Patients with prolonged global intellectual regression had the worst outcome, whereas those with more specific and short-lived deficits recovered best. The marked behavioral disorders resolved in all but one patient. Executive functions were neither severely nor homogenously affected. Three patients with a frontal syndrome during the active phase (AP) disclosed only mild residual executive and social cognition deficits. The main cognitive gains occurred shortly after the AP, but qualitative improvements continued to occur. Long-term outcome correlated best with duration of CSWS. SIGNIFICANCE: Our findings emphasize that cognitive recovery after cessation of CSWS depends on the severity and duration of the initial regression. None of our patients had major executive and social cognition deficits with preserved intelligence, as reported in adults with early destructive lesions of the frontal lobes. Early recognition of epilepsy with CSWS and rapid introduction of effective therapy are crucial for a best possible outcome.

Segmentation and Clustering of Textual Sequences: a Typological Approach

The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.

Long-term citalopram administration reduces responsiveness of HPA axis in patients with major depression: relationship with S-citalopram concentrations in plasma and cerebrospinal fluid (CSF) and clinical response.

RATIONALE: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a well-documented neurobiological finding in major depression. Moreover, clinically effective therapy with antidepressant drugs may normalize the HPA axis activity. OBJECTIVE: The aim of this study was to test whether citalopram (R/S-CIT) affects the function of the HPA axis in patients with major depression (DSM IV). METHODS: Twenty depressed patients (11 women and 9 men) were challenged with a combined dexamethasone (DEX) suppression and corticotropin-releasing hormone (CRH) stimulation test (DEX/CRH test) following a placebo week and after 2, 4, and 16 weeks of 40 mg/day R/S-CIT treatment. RESULTS: The results show a time-dependent reduction of adrenocorticotrophic hormone (ACTH) and cortisol response during the DEX/CRH test both in treatment responders and nonresponders within 16 weeks. There was a significant relationship between post-DEX baseline cortisol levels (measured before administration of CRH) and severity of depression at pretreatment baseline. Multiple linear regression analyses were performed to identify the impact of psychopathology and hormonal stress responsiveness and R/S-CIT concentrations in plasma and cerebrospinal fluid (CSF). The magnitude of decrease in cortisol responsivity from pretreatment baseline to week 4 on drug [delta-area under the curve (AUC) cortisol] was a significant predictor (p<0.0001) of the degree of symptom improvement following 16 weeks on drug (i.e., decrease in HAM-D21 total score). The model demonstrated that the interaction of CSF S-CIT concentrations and clinical improvement was the most powerful predictor of AUC cortisol responsiveness. CONCLUSION: The present study shows that decreased AUC cortisol was highly associated with S-CIT concentrations in plasma and CSF. Therefore, our data suggest that the CSF or plasma S-CIT concentrations rather than the R/S-CIT dose should be considered as an indicator of the selective serotonergic reuptake inhibitors (SSRIs) effect on HPA axis responsiveness as measured by AUC cortisol response.

Long-term follow-up of high-dose chemotherapy with autologous stem-cell transplantation and response-adapted whole-brain radiotherapy for newly diagnosed primary CNS lymphoma: results of the multicenter Ostdeutsche Studiengruppe Hamato-Onkologie OSHO-53 phase II study

Introduction: We previously reported the results of a phase II study for patients with newly diagnosed primary CNS lymphoma (PCNSL) treated with autologous peripheral blood stem-cell transplantation (aPBSCT) and responseadapted whole brain radiotherapy (WBRT). The purpose of this report is to update the initial results and provide long-term data regarding overall survival, prognostic factors, and the risk of treatment-related neurotoxicity.Methods: A long-term follow-up was conducted on surviving primary central nervous system lymphoma patients having been treated according to the ,,OSHO-53 study", which was initiated by the Ostdeutsche Studiengruppe Hamatologie-Onkologie. Between August 1999 and October 2004 twentythree patients with an average age of 55 and median Karnofsky performance score of 70% were enrolled and received high-dose mthotrexate (HD-MTX) on days 1 and 10. In case of at least a partial remission (PR), high-dose busulfan/ thiotepa (HD-BuTT) followed by aPBSCT was performed. Patients without response to induction or without complete remission (CR) after HD-BuTT received WBRT. All patients (n=8), who are alive in 2011, were contacted and Mini Mental State examination (MMSE) and the EORTC QLQ-C30 were performed.Results: Eight patients are still alive with a median follow-up of 116,9 months (79 - 141, range). One of them suffered from a late relapse eight and a half years after initial diagnosis of PCNSL, another one suffers from a gall bladder carcinoma. Both patients are alive, the one with the relapse of PCNSL has finished rescue therapy and is further observed, the one with gall baldder carcinoma is still under therapy. MMSE and QlQ-C30 showed impressive results in the patients, who were not irradiated. Only one of the irradiated patients is still alive with a clear neurologic deficit but acceptable quality of life.Conclusions: Long-term follow-up of our patients, who were included in the OSHO-53 study show an overall survival of 30 percent. If WBRT can be avoided no long-term neurotoxicity has been observed and the patients benefit from excellent Quality of Life. Induction chemotherapy with two cycles of HD-MTX should be intensified to improve the unsatisfactory OAS of 30 percent.