Cerebral tissue pO2 response to stimulation is preserved with age in awake mice

Published in final edited form as: Neurosci Lett. 2019 April 23; 699: 160–166. doi:10.1016/j.neulet.2019.02.007.Compromised oxygen supply to cerebral tissue could be an important mechanism contributing to age-related cognition decline. We recently showed in awake mice that resting cerebral tissue pO2 decreases with age, a phenomenon that manifests mainly after middle-age. To extend these findings, here we aimed to study how tissue pO2 response to neuronal stimulation is affected by aging. We used two-photon phosphorescence lifetime microscopy to directly measure the brain tissue pO2 response to whisker stimulation in healthy awake young, middle-aged and old mice. We show that despite a decrease in baseline tissue pO2, the amplitude of the tissue pO2 response to stimulation is well preserved with age. However, the response dynamics are altered towards a slower response with reduced post-stimulus undershoot in older ages, possibly due to stiffer vessel wall among other factors. An estimation of the net oxygen consumption rate using a modified Krogh model suggests that the O2 overshoot during stimulation may be necessary to secure a higher capillary O2 delivery to the tissue proportional to increased CMRO2 to maintain the capillary tissue pO2. It was observed that the coupling between the CMRO2 and capillary O2 delivery is preserved with age.Accepted manuscrip

Wall slip of complex fluids: interfacial friction or slip length?

Using a dynamic Surface Force Apparatus, we demonstrate that the notion of slip length used to describe the boundary flow of simple liquids, is not appropriate for viscoelastic liquids. Rather, the appropriate description lies in the original Navier's partial slip boundary condition, formulated in terms of an interfacial friction coefficient. We establish an exact analytical expression to extract the interfacial friction coefficient from oscillatory drainage forces between a sphere and a plane, suitable for dynamic SFA or Atomic Force Microscopy non-contact measurements. We use this model to investigate the boundary friction of viscoelastic polymer solutions over 5 decades of film thicknesses and one decade in frequency. The proper use of the original Navier's condition describes accurately the complex hydrodynamic force up to scales of tens of micrometers, with a simple "Newtonian-like" friction coefficient, not frequency dependent, and reflecting closely the dynamics of an interfacial depletion layer at the solution/solid interface.Comment: 7 pages, 5 figure

Inférence doublement robuste en présence de données imputées dans les enquêtes

L'imputation est souvent utilisée dans les enquêtes pour traiter la non-réponse partielle. Il est bien connu que traiter les valeurs imputées comme des valeurs observées entraîne une sous-estimation importante de la variance des estimateurs ponctuels. Pour remédier à ce problème, plusieurs méthodes d'estimation de la variance ont été proposées dans la littérature, dont des méthodes adaptées de rééchantillonnage telles que le Bootstrap et le Jackknife. Nous définissons le concept de double-robustesse pour l'estimation ponctuelle et de variance sous l'approche par modèle de non-réponse et l'approche par modèle d'imputation. Nous mettons l'emphase sur l'estimation de la variance à l'aide du Jackknife qui est souvent utilisé dans la pratique. Nous étudions les propriétés de différents estimateurs de la variance à l'aide du Jackknife pour l'imputation par la régression déterministe ainsi qu'aléatoire. Nous nous penchons d'abord sur le cas de l'échantillon aléatoire simple. Les cas de l'échantillonnage stratifié et à probabilités inégales seront aussi étudiés. Une étude de simulation compare plusieurs méthodes d'estimation de variance à l'aide du Jackknife en terme de biais et de stabilité relative quand la fraction de sondage n'est pas négligeable. Finalement, nous établissons la normalité asymptotique des estimateurs imputés pour l'imputation par régression déterministe et aléatoire.Imputation is often used in surveys to treat item nonresponse. It is well known that treating the imputed values as observed values may lead to substantial underestimation of the variance of the point estimators. To overcome the problem, a number of variance estimation methods have been proposed in the literature, including appropriate versions of resampling methods such as the jackknife and the bootstrap. We define the concept of doubly robust point and variance estimation under the so-called nonresponse and imputation model approaches. We focus on jackknife variance estimation, which is widely used in practice. We study the properties of several jackknife variance estimators under both deterministic and random regression imputation. We first consider the case of simple random sampling without replacement. The case of stratified simple random sampling and unequal probability sampling is also considered. A limited simulation study compares various jackknife variance estimators in terms of bias and relative stability when the sampling fraction is not negligible. Finally, the asymptotic normality of imputed estimator is established under both deterministic and random regression imputation

Deep multi-scale architectures for monocular depth estimation

This paper aims at understanding the role of multi-scale information in the estimation of depth from monocular images. More precisely, the paper investigates four different deep CNN architectures, designed to explicitly make use of multi-scale features along the network, and compare them to a state-of-the-art single-scale approach. The paper also shows that involving multi-scale features in depth estimation not only improves the performance in terms of accuracy, but also gives qualitatively better depth maps. Experiments are done on the widely used NYU Depth dataset, on which the proposed method achieves state-of-the-art performance