A solver combining reduced basis and convergence acceleration with applications to non-linear elasticity

International audienceAn iterative solver is proposed to solve the family of linear equations arising from the numerical computation of non‐linear problems. This solver relies on two quantities coming from previous steps of the computations: the preconditioning matrix is a matrix that has been factorized at an earlier step and previously computed vectors yield a reduced basis. The principle is to define an increment in two sub‐steps. In the first sub‐step, only the projection of the unknown on a reduced subspace is incremented and the projection of the equation on the reduced subspace is satisfied exactly. In the second sub‐step, the full equation is solved approximately with the help of the preconditioner. Last, the convergence of the sequences is accelerated by a well‐known method, the modified minimal polynomial extrapolation. This algorithm assessed by classical benchmarks coming from shell buckling analysis. Finally, its insertion in path following techniques is discussed. This leads to non‐linear solvers with few matrix factorizations and few iterations

Paired box 6 gene delivery preserves beta cells and improves islet transplantation efficacy

Loss of pancreatic beta cells is the central feature of all forms of diabetes. Current therapies fail to halt the declined beta cell mass. Thus, strategies to preserve beta cells are imperatively needed. In this study, we identified paired box 6 (PAX6) as a critical regulator of beta cell survival. Under diabetic conditions, the human beta cell line EndoC-βH1, db/db mouse and human islets displayed dampened insulin and incretin signalings and reduced beta cell survival, which were alleviated by PAX6 overexpression. Adeno-associated virus (AAV)-mediated PAX6 overexpression in beta cells of streptozotocin-induced diabetic mice and db/db mice led to a sustained maintenance of glucose homeostasis. AAV-PAX6 transduction in human islets reduced islet graft loss and improved glycemic control after transplantation into immunodeficient diabetic mice. Our study highlights a previously unappreciated role for PAX6 in beta cell survival and raises the possibility that ex vivo PAX6 gene transfer into islets prior to transplantation might enhance islet graft function and transplantation outcome

Warped Riemannian metrics for location-scale models

The present paper shows that warped Riemannian metrics, a class of Riemannian metrics which play a prominent role in Riemannian geometry, are also of fundamental importance in information geometry. Precisely, the paper features a new theorem, which states that the Rao-Fisher information metric of any location-scale model, defined on a Riemannian manifold, is a warped Riemannian metric, whenever this model is invariant under the action of some Lie group. This theorem is a valuable tool in finding the expression of the Rao-Fisher information metric of location-scale models defined on high-dimensional Riemannian manifolds. Indeed, a warped Riemannian metric is fully determined by only two functions of a single variable, irrespective of the dimension of the underlying Riemannian manifold. Starting from this theorem, several original contributions are made. The expression of the Rao-Fisher information metric of the Riemannian Gaussian model is provided, for the first time in the literature. A generalised definition of the Mahalanobis distance is introduced, which is applicable to any location-scale model defined on a Riemannian manifold. The solution of the geodesic equation is obtained, for any Rao-Fisher information metric defined in terms of warped Riemannian metrics. Finally, using a mixture of analytical and numerical computations, it is shown that the parameter space of the von Mises-Fisher model of $n$-dimensional directional data, when equipped with its Rao-Fisher information metric, becomes a Hadamard manifold, a simply-connected complete Riemannian manifold of negative sectional curvature, for $n = 2,\ldots,8$. Hopefully, in upcoming work, this will be proved for any value of $n$.Comment: first version, before submissio

Gynecomastia during imatinib mesylate treatment for gastrointestinal stromal tumor: a rare adverse event

<p>Abstract</p> <p>Background</p> <p>Imatinib mesylate has been the standard therapeutic treatment for chronic myeloid leukemia, advanced and metastatic gastrointestinal stromal tumor (GIST). It is well tolerated with mild adverse effects. Gynecomastia development during the course of treatment has been rarely reported.</p> <p>Methods</p> <p>Ninety-eight patients with advanced or recurrent GIST were treated with imatinib mesylate. Among the fifty-seven male patients six developed gynecomastia during the treatment. The lesions were confirmed by sonography. Sex hormone levels were determined in six patients with and without the presence of gynecomastia respectively. The patients with gynecomatia were treated with tamoxifene and the sex hormones were assayed before and after tamoxifene treatment.</p> <p>Results</p> <p>In patients with gynecomastia the lump underneath the bilateral nipples was 2.5 to 5 centimeters in diameter. Their serum free testosterone levels ranged between 356.61 and 574.60 ng/dl with a mean ± SD of 408.64 ± 82.06 ng/dl (95% CI 343.03~474.25 ng/dl), which is within the normal range. The level of serum estradiol was 42.89 ± 16.54 pg/ml (95% CI 29.66~56.12 pg/ml). Three patients had higher levels (43.79~71.21 pg/ml) and the others' were within normal range of 27.00~34.91 pg/ml. Six patients without the development of gynecomastia had normal free testosterone. One patient died because of large tumor burden. The sex hormones had no significant changes before and after tamoxifene treatment.(<it>P </it>> 0.05)</p> <p>Conclusions</p> <p>Testosterone levels were not decreased in the six GIST patients with gynecomastia. Three patients had increased serum estradiol level which suggests that imbalance of sex hormones may be the cause of gynecomastia during treatment with imatinib mesylate.</p

Gabapentin for complex regional pain syndrome in Machado-Joseph disease: a case report

<p>Abstract</p> <p>Introduction</p> <p>Chronic pain is a common problem for patients with Machado-Joseph disease. Most of the chronic pain in Machado-Joseph disease has been reported to be of musculoskeletal origin, but now there seems to be different chronic pain in patients with Machado-Joseph disease.</p> <p>Case presentation</p> <p>A 29-year-old man (Han Chinese, Hoklo) with Machado-Joseph disease experienced severe chronic pain in both feet, cutaneous thermal change, thermal hypersensitivity, focal edema, and sweating and had a history of bone fracture. These symptoms were compatible with a diagnosis of complex regional pain syndrome. After common analgesics failed to relieve his pain, gabapentin was added and titrated to 2000 mg/day (500 mg every six hours) in less than two weeks. This relieved 40% of his pain and led to significant clinical improvement.</p> <p>Conclusions</p> <p>The pathophysiology of complex regional pain syndrome includes peripheral and central sensitizations, the latter of which might be associated with the neurodegeneration in Machado-Joseph disease. In this report, we suggest that gabapentin could inhibit central sensitization as an adjunct for complex regional pain syndrome in patients with Machado-Joseph disease.</p

Genome-Wide Association Study Meta-Analysis for Parkinson Disease Motor Subtypes

Objective: To discover genetic determinants of Parkinson disease (PD) motor subtypes, including tremor dominant (TD) and postural instability/gait difficulty (PIGD) forms. Methods: In 3,212 PD cases of European ancestry, we performed a genome-wide association study (GWAS) examining 2 complementary outcome traits derived from the Unified Parkinson's Disease Rating Scale, including dichotomous motor subtype (TD vs PIGD) or a continuous tremor/PIGD score ratio. Logistic or linear regression models were adjusted for sex, age at onset, disease duration, and 5 ancestry principal components, followed by meta-analysis. Results: Among 71 established PD risk variants, we detected multiple suggestive associations with PD motor subtype, including GPNMB (rs199351, psubtype = 0.01, pratio = 0.03), SH3GL2 (rs10756907, psubtype = 0.02, pratio = 0.01), HIP1R (rs10847864, psubtype = 0.02), RIT2 (rs12456492, psubtype = 0.02), and FBRSL1 (rs11610045, psubtype = 0.02). A PD genetic risk score integrating all 71 PD risk variants was also associated with subtype ratio (p = 0.026, ß = -0.04, 95% confidence interval = -0.07-0). Based on top results of our GWAS, we identify a novel suggestive association at the STK32B locus (rs2301857, pratio = 6.6 × 10-7), which harbors an independent risk allele for essential tremor. Conclusions: Multiple PD risk alleles may also modify clinical manifestations to influence PD motor subtype. The discovery of a novel variant at STK32B suggests a possible overlap between genetic risk for essential tremor and tremor-dominant PD

Acute effects of fine particulate air pollution on ST segment height: A longitudinal study

Background The mechanisms for the relationship between particulate air pollution and cardiac disease are not fully understood. Air pollution-induced myocardial ischemia is one of the potentially important mechanisms. Methods We investigate the acute effects and the time course of fine particulate pollution (PM2.5) on myocardium ischemic injury as assessed by ST-segment height in a community-based sample of 106 healthy non-smokers. Twenty-four hour beat-to-beat electrocardiogram (ECG) data were obtained using a high resolution 12-lead Holter ECG system. After visually identifying and removing all the artifacts and arrhythmic beats, we calculated beat-to-beat ST-height from ten leads (inferior leads II, III, and aVF; anterior leads V3 and V4; septal leads V1 and V2; lateral leads I, V5, and V6,). Individual-level 24-hour real-time PM2.5 concentration was obtained by a continuous personal PM2.5 monitor. We then calculated, on a 30-minute basis, the corresponding time-of-the-day specific average exposure to PM2.5 for each participant. Distributed lag models under a linear mixed-effects models framework were used to assess the regression coefficients between 30-minute PM2.5 and ST-height measures from each lead; i.e., one lag indicates a 30-minute separation between the exposure and outcome. Results The mean (SD) age was 56 (7.6) years, with 41% male and 74% white. The mean (SD) PM2.5 exposure was 14 (22) μg/m3. All inferior leads (II, III, and aVF) and two out of three lateral leads (I and V6), showed a significant association between higher PM2.5 levels and higher ST-height. Most of the adverse effects occurred within two hours after PM2.5 exposure. The multivariable adjusted regression coefficients β (95% CI) of the cumulative effect due to a 10 μg/m3 increase in Lag 0-4 PM2.5 on ST-I, II, III, aVF and ST-V6 were 0.29 (0.01-0.56) μV, 0.79 (0.20-1.39) μV, 0.52 (0.01-1.05) μV, 0.65 (0.11-1.19) μV, and 0.58 (0.07-1.09) μV, respectively, with all p < 0.05. Conclusions Increased PM2.5 concentration is associated with immediate increase in ST-segment height in inferior and lateral leads, generally within two hours. Such an acute effect of PM2.5 may contribute to increased potential for regional myocardial ischemic injury among healthy individuals

A Stable Biologically Motivated Learning Mechanism for Visual Feature Extraction to Handle Facial Categorization

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task