We define the coarse Ricci curvature of metric spaces in terms of how much small balls are closer (in Wasserstein transportation distance) than their centers are. This definition naturally extends to ...any Markov chain on a metric space. For a Riemannian manifold this gives back, after scaling, the value of Ricci curvature of a tangent vector. Examples of positively curved spaces for this definition include the discrete cube and discrete versions of the Ornstein–Uhlenbeck process. Moreover this generalization is consistent with the Bakry–Émery Ricci curvature for Brownian motion with a drift on a Riemannian manifold.
Positive Ricci curvature is shown to imply a spectral gap, a Lévy–Gromov–like Gaussian concentration theorem and a kind of modified logarithmic Sobolev inequality. The bounds obtained are sharp in a variety of examples.
We provide explicit nonasymptotic estimates for the rate of convergence of empirical means of Markov chains, together with a Gaussian or exponential control on the deviations of empirical means. ...These estimates hold under a "positive curvature" assumption expressing a kind of metric ergodicity, which generalizes the Ricci curvature from differential geometry and, on finite graphs, amounts to contraction under path coupling.
The link between immediate hypersensitivity reactions (HSR) following the first cetuximab infusion and the IgE sensitization against anti-galactose-α-1,3-galactose (α-Gal) is now well-established. An ...automated Fluoroenzyme-Immunoassay (FEIA) is available and may facilitate the screening of patients with anti-α-Gal IgE before treatment.
This study aimed to evaluate its performances as compared to a previously validated anti-cetuximab IgE ELISA, using 185 samples from two previously studied cohorts.
Despite 21.1% of discrepancies between the two techniques, FEIA discriminated better positive patients and similarly negative ones with a ≥ 0.525 kU
/L threshold. Sensitivity was 87.5% for both tests, specificity was better for FEIA (96.3% vs ELISA: 82.1%). FEIA had a higher positive likelihood ratio (23.9 vs ELISA: 4.89) and a similar negative likelihood ratio (0.13 vs ELISA: 0.15). In our population, the risk of severe HSR following a positive test was higher with FEIA (56.7% vs ELISA: 19.6%) and similar following a negative test (0.7% vs ELISA: 0.8%).
Although the predictive value of the IgE screening before cetuximab infusion remains discussed, this automated commercial test can identify high-risk patients and is suitable for routine use in laboratories. It could help avoiding cetuximab-induced HSR by a systematic anti-α-Gal IgE screening before treatment.
Objective
Intravenous immunoglobulin (IVIG) represents a therapeutic alternative in antineutrophil cytoplasmic antibody–associated vasculitides (AAV), but its efficacy has been evaluated in only 2 ...small prospective trials. The aim of this study was to evaluate the efficacy and safety of IVIG in patients with AAV.
Methods
We conducted a nationwide retrospective study of patients who received IVIG as immunomodulatory therapy for AAV.
Results
A total of 92 patients (mean age 51 years) presenting with either granulomatosis with polyangiitis (Wegener's) (68%), eosinophilic granulomatosis with polyangiitis (Churg‐Strauss) (22%), or microscopic polyangiitis (10%) received at least 1 course of IVIG. Antineutrophil cytoplasmic antibodies were present in 72% during the flare that required IVIG, as determined by immunofluorescence assay. IVIG was initiated because of relapsing disease in 83% of cases. IVIG was given for a median of 6 months (range 1–156 months) and in combination with corticosteroids in 21% of the patients or with other immunosuppressive agents in 77%. Efficacy of IVIG was assessed in the entire population and in a subset of 34 patients with unmodified background therapy. Remission rates at 6 months were 56% in the entire population and 58% in the unmodified background therapy group. Refractory disease and treatment failure at 6 months were observed in 7% and 18% in the whole population and 3% and 21% in the unmodified background therapy group, respectively. Adverse events (AEs) occurred in 33%, including serious AEs in 12% and AEs leading to discontinuation of IVIG in 7%.
Conclusion
This large study shows the clinical benefit of IVIG as adjunctive therapy, with an acceptable tolerance profile, and thus supports its use in AAV patients with refractory or relapsing disease.
Abstract Objective To report on the effectiveness of cyclophosphamide (CYC) to treat glucocorticoid (GC)-dependent giant-cell arteritis (GCA) and/or severe GC-related side effects. Methods Fifteen ...patients with GCA and treated with CYC were retrieved from the computerized patient-record system. Glucocorticoid dependence was defined as a prednisone dose of >20 mg/day for 6 months or >10 mg/day for 1 year in order not to relapse. Response to CYC was defined as improved clinical and biological findings. Remission was defined as a sustained absence (>12 months) of active signs of vasculitis at a daily GC dose of <7.5 mg. A literature review searched PubMed for all patients diagnosed with GCA and who received CYC. Results Our 15 patients responded to monthly pulses of CYC, and all experienced a GC-sparing effect, including five patients who discontinued GC long term. At a median follow-up of 43 (range: 14–75) months after CYC, nine (53%) patients were still in remission and six (40%) had relapsed at 6 (3–36) months after the last CYC infusion. Twelve (80%) patients experienced side effects, leading to discontinuation of CYC in two (13%). A literature review retrieved 88 patients who received CYC: 66 for GC-dependent disease, 53 for GC toxicity, and 14 for severe organ involvement. Their median follow-up time was 24 (4–60) months. Among the 88 patients, 74 (84%) were responsive to CYC and 17 (19%) relapsed, although all were receiving a maintenance therapy with immunosuppressive agents (such as methotrexate). Twenty-nine (33%) patients experienced side effects and 11 (12.5%) discontinued treatment. Conclusion Cyclophosphamide is an interesting option for GCA patients with GC-dependent disease or with severe GC-related side effects, especially when conventional immunosuppressive agents have failed.
We present a canonical way to turn any smooth parametric family of probability distributions on an arbitrary search space X into a continuous-time black-box optimization method on X, the ...information-geometric optimization (IGO) method. Invariance as a major design principle keeps the number of arbitrary choices to a minimum. The resulting IGO flow is the flow of an ordinary differential equation conducting the natural gradient ascent of an adaptive, time-dependent transformation of the objective function. It makes no particular assumptions on the objective function to be optimized. The IGO method produces explicit IGO algorithms through time discretization. It naturally recovers versions of known algorithms and offers a systematic way to derive new ones. In continuous search spaces, IGO algorithms take a form related to natural evolution strategies (NES). The cross-entropy method is recovered in a particular case with a large time step, and can be extended into a smoothed, parametrization-independent maximum likelihood update (IGO-ML). When applied to the family of Gaussian distributions on R^d, the IGO framework recovers a version of the well-known CMA-ES algorithm and of xNES. For the family of Bernoulli distributions on {0, 1}^d, we recover the seminal PBIL algorithm and cGA. For the distributions of restricted Boltzmann machines, we naturally obtain a novel algorithm for discrete optimization on {0, 1}^d. All these algorithms are natural instances of, and unified under, the single information-geometric optimization framework. The IGO method achieves, thanks to its intrinsic formulation, maximal invariance properties: invariance under reparametrization of the search space X, under a change of parameters of the probability distribution, and under increasing transformation of the function to be optimized. The latter is achieved through an adaptive, quantile-based formulation of the objective. Theoretical considerations strongly suggest that IGO algorithms are essentially characterized by a minimal change of the distribution over time. Therefore they have minimal loss in diversity through the course of optimization, provided the initial diversity is high. First experiments using restricted Boltzmann machines confirm this insight. As a simple consequence, IGO seems to provide, from information theory, an elegant way to simultaneously explore several valleys of a fitness landscape in a single run.
We describe four algorithms for neural network training, each adapted to different scalability constraints. These algorithms are mathematically principled and invariant under a number of ...transformations in data and network representation, from which performance is thus independent. These algorithms are obtained from the setting of differential geometry, and are based on either the natural gradient using the Fisher information matrix, or on Hessian methods, scaled down in a specific way to allow for scalability while keeping some of their key mathematical properties.
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