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.

Local moderate magnetically induced hyperthermia using an implant formed in situ in a mouse tumor model.

Purpose: We investigate a new heat delivery technique for the local treatment of solid tumors. The technique involves injecting a formulation that solidifies to form an implant in situ. This implant entraps superparamagnetic iron oxide nanoparticles (SPIONs) embedded in silica microbeads for magnetically induced moderate hyperthermia. Particle entrapment prevents phagocytosis and distant migration of SPIONs. The implant can be repeatedly heated by magnetic induction. Methods: We evaluated heating and treatment efficacies by means of thermometry and survival studies in nude mice carrying subcutaneous human colocarcinomas. At day 1, we injected the formulation into the tumor. At day 2, a single 20-min hyperthermia treatment was delivered by 141-kHz magnetic induction using field strengths of 9 to 12 mT under thermometry. Results: SPIONs embedded in silica microbeads were effectively confined within the implant at the injection site. Heat-induced necro-apoptosis was assessed by histology on day 3. On average, 12 mT resulted in tumor temperature of 47.8 degrees C, and over 70% tumor necrosis that correlated to the heat dose (AUC = 282 degrees C.min). In contrast, a 9-mT field strength induced tumoral temperature of 40 degrees C (AUC = 131 degrees C.min) without morphologically identifiable necrosis. Survival after treatment with 10.5 or 12 mT fields was significantly improved compared to non-implanted and implanted controls. Median survival times were 27 and 37 days versus 12 and 21 days respectively. Conclusion: Five of eleven mice (45%) of the 12 mT group survived one year without any tumor recurrence, holding promise for tumor therapy using magnetically induced moderate hyperthermia through injectable implants.

Fungi, bacteria and soil pH: the oxalate-carbonate pathway as a model for metabolic interaction

The oxalatecarbonate pathway involves the oxidation of calcium oxalate to low-magnesium calcite and represents a potential long-term terrestrial sink for atmospheric CO2. In this pathway, bacterial oxalate degradation is associated with a strong local alkalinization and subsequent carbonate precipitation. In order to test whether this process occurs in soil, the role of bacteria, fungi and calcium oxalate amendments was studied using microcosms. In a model system with sterile soil amended with laboratory cultures of oxalotrophic bacteria and fungi, the addition of calcium oxalate induced a distinct pH shift and led to the final precipitation of calcite. However, the simultaneous presence of bacteria and fungi was essential to drive this pH shift. Growth of both oxalotrophic bacteria and fungi was confirmed by qPCR on the frc (oxalotrophic bacteria) and 16S rRNA genes, and the quantification of ergosterol (active fungal biomass) respectively. The experiment was replicated in microcosms with non-sterilized soil. In this case, the bacterial and fungal contribution to oxalate degradation was evaluated by treatments with specific biocides (cycloheximide and bronopol). Results showed that the autochthonous microflora oxidized calcium oxalate and induced a significant soil alkalinization. Moreover, data confirmed the results from the model soil showing that bacteria are essentially responsible for the pH shift, but require the presence of fungi for their oxalotrophic activity. The combined results highlight that the interaction between bacteria and fungi is essential to drive metabolic processes in complex environments such as soil.

Predicting trabecular bone microdamage initiation and accumulation using a non-linear perfect damage model

Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions

Online estimation of respiratory mechanics in non-invasive pressure support ventilation: a bench model study.

An online algorithm for determining respiratory mechanics in patients using non-invasive ventilation (NIV) in pressure support mode was developed and embedded in a ventilator system. Based on multiple linear regression (MLR) of respiratory data, the algorithm was tested on a patient bench model under conditions with and without leak and simulating a variety of mechanics. Bland-Altman analysis indicates reliable measures of compliance across the clinical range of interest (± 11-18% limits of agreement). Resistance measures showed large quantitative errors (30-50%), however, it was still possible to qualitatively distinguish between normal and obstructive resistances. This outcome provides clinically significant information for ventilator titration and patient management.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Transcriptional and functional profiles of voltage-gated Na(+) channels in injured and non-injured DRG neurons in the SNI model of neuropathic pain.

Changes in expression and function of voltage-gated sodium channels (VGSC) in dorsal root ganglion (DRG) neurons may play a major role in the genesis of peripheral hyperexcitability that occurs in neuropathic pain. We present here the first description of changes induced by spared nerve injury (SNI) to Na(v)1 mRNA levels and tetrodotoxin-sensitive and -resistant (TTX-S/TTX-R) Na(+) currents in injured and adjacent non-injured small DRG neurons. VGSC transcripts were down-regulated in injured neurons except for Na(v)1.3, which increased, while they were either unchanged or increased in non-injured neurons. TTX-R current densities were reduced in injured neurons and the voltage dependence of steady-state inactivation for TTX-R was positively shifted in injured and non-injured neurons. TTX-S current densities were not affected by SNI, while the rate of recovery from inactivation was accelerated in injured neurons. Our results describe altered neuronal electrogenesis following SNI that is likely induced by a complex regulation of VGSCs.

A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

A novel mucosal orthotopic murine model of human papillomavirus-associated genital cancers.

Cervical cancer results from infection with high-risk type human papillomaviruses (HPV). Therapeutic vaccines aiming at controlling existing genital HPV infections and associated lesions are usually tested in mice with HPV-expressing tumor cells subcutaneously implanted into their flank. However, effective vaccine-induced regression of these ectopic tumors strongly contrasts with the poor clinical results of these vaccines produced in patients with HPV-associated genital neoplasia. To assess HPV therapeutic vaccines in a more relevant setting, we have, here, established an orthotopic mouse model where tumors in the genital mucosa (GM) develop after an intravaginal instillation of HPV16 E6/E7-expressing tumor cells transduced with a luciferase-encoding lentiviral vector for in vivo imaging of tumor growth. Tumor take was 80-90% after nonoxynol-9 induced damage of the epithelium. Tumors remained localized in the genital tract, and histological analysis showed that most tumors grew within the squamous epithelium of the vaginal wall. Those tumors induced (i) E7-specific CD8 T cells restricted to the GM and draining lymph nodes, in agreement with their mucosal location and (ii) high Foxp3+ CD4+ infiltrates, similarly to those found in natural non-regressing HPV lesions. This novel genital HPV-tumor model by requiring GM homing of vaccine-induced immune responses able to overcome local immuno-suppression may be more representative of the situation occurring in patients upon therapeutic vaccination.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Inhibition of the Kit Ligand/c-Kit Axis Attenuates Metastasis in a Mouse Model Mimicking Local Breast Cancer Relapse after Radiotherapy.

PURPOSE: Local breast cancer relapse after breast-saving surgery and radiotherapy is associated with increased risk of distant metastasis formation. The mechanisms involved remain largely elusive. We used the well-characterized 4T1 syngeneic, orthotopic breast cancer model to identify novel mechanisms of postradiation metastasis. EXPERIMENTAL DESIGN: 4T1 cells were injected in 20 Gy preirradiated mammary tissue to mimic postradiation relapses, or in nonirradiated mammary tissue, as control, of immunocompetent BALB/c mice. Molecular, biochemical, cellular, histologic analyses, adoptive cell transfer, genetic, and pharmacologic interventions were carried out. RESULTS: Tumors growing in preirradiated mammary tissue had reduced angiogenesis and were more hypoxic, invasive, and metastatic to lung and lymph nodes compared with control tumors. Increased metastasis involved the mobilization of CD11b(+)c-Kit(+)Ly6G(high)Ly6C(low)(Gr1(+)) myeloid cells through the HIF1-dependent expression of Kit ligand (KitL) by hypoxic tumor cells. KitL-mobilized myeloid cells homed to primary tumors and premetastatic lungs, to give rise to CD11b(+)c-Kit(-) cells. Pharmacologic inhibition of HIF1, silencing of KitL expression in tumor cells, and inhibition of c-Kit with an anti-c-Kit-blocking antibody or with a tyrosine kinase inhibitor prevented the mobilization of CD11b(+)c-Kit(+) cells and attenuated metastasis. C-Kit inhibition was also effective in reducing mobilization of CD11b(+)c-Kit(+) cells and inhibiting lung metastasis after irradiation of established tumors. CONCLUSIONS: Our work defines KitL/c-Kit as a previously unidentified axis critically involved in promoting metastasis of 4T1 tumors growing in preirradiated mammary tissue. Pharmacologic inhibition of this axis represents a potential therapeutic strategy to prevent metastasis in breast cancer patients with local relapses after radiotherapy. Clin Cancer Res; 18(16); 4365-74. ©2012 AACR.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Systemic exposure to tobramycin after local antibiotic treatment with calcium sulphate as carrier material.

INTRODUCTION: Osteoset(®) T is a calcium sulphate void filler containing 4% tobramycin sulphate, used to treat bone and soft tissue infections. Despite systemic exposure to the antibiotic, there are no pharmacokinetic studies in humans published so far. Based on the observations made in our patients, a model predicting tobramycin serum levels and evaluating their toxicity potential is presented. METHODS: Following implantation of Osteoset(®) T, tobramycin serum concentrations were monitored systematically. A pharmacokinetic analysis was performed using a non-linear mixed effects model based on a one compartment model with first-degree absorption. RESULTS: Data from 12 patients treated between October 2006 and March 2008 were analysed. Concentration profiles were consistent with the first-order slow release and single-compartment kinetics, whilst showing important variability. Predicted tobramycin serum concentrations depended clearly on both implanted drug amount and renal function. DISCUSSION AND CONCLUSION: Despite the popularity of aminoglycosides for local antibiotic therapy, pharmacokinetic data for this indication are scarce, and not available for calcium sulphate as carrier material. Systemic exposure to tobramycin after implantation of Osteoset(®) T appears reassuring regarding toxicity potential, except in case of markedly impaired renal function. We recommend in adapting the dosage to the estimated creatinine clearance rather than solely to the patient's weight.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.