Bounds in Competing Risks Models and the War on Cancer

In 1971 President Nixon declared war on cancer and increased the federal funds allocated to cancer research dramatically. Thirty years later, many have declared this war a failure. Overall cancer statistics confirm this view: age-adjusted mortality in 2000 was essentially unchanged from the early 1970s. At the same time, age-adjusted mortality rates from cardiovascular disease have fallen quite dramatically. Since the causes underlying cancer and cardiovascular disease are likely to be correlated, the decline in mortality rates from cardiovascular disease may be somewhat responsible for the rise in cancer mortality. It is natural to model mortality with more than one cause of death as a competing risks model. Such models are fundamentally unidentified, and it is therefore difficult to get a clear picture of the progress in cancer. This paper derives bounds for aspects of the underlying distributions under a number of different assumptions. Most importantly, we do not assume that the underlying risks are independent, and impose weak parametric assumptions in order to obtain identification. The theoretical contribution of the paper is to provide a framework to estimate competing risk models with interval data and discrete explanatory variables, both of which are common in empirical applications. We use our method to estimate changes in cancer and cardiovascular mortality since 1970. The estimated bounds for the effect of time on the duration until death for either cause are fairly tight and we find that trends in cancer show much larger improvements than previously estimated. For example, we find that time until death from cancer increased by about 10% for white males and 20% for white women.

Nonlinear models with panel data

Panel data play an important role in empirical economics. With panel data one can answer questions about microeconomic dynamic behavior that could not be answered with cross sectional data. Panel data techniques are also useful for analyzing cross sectional data with grouping. This paper discusses some issues related to specification and estimation of nonlinear models using panel data.This paper was supported by the National Science Foundation, the Gregory C. Chow Econometric Research Program at Princeton University, and Danish National Research Foundation (through CAM at the University of Copenhagen).info:eu-repo/semantics/publishedVersio

Non-linear models with panel data

Panel data play an important role in empirical economics. With panel data one can answer questions about microeconomic dynamic behavior that could not be answered with cross sectional data. Panel data techniques are also useful for analyzing cross sectional data with grouping. This paper discusses some issues related to specification estimation of nonlinear models using panel data.

Autoradiographic Characterization and Localization of Quisqualate Binding Sites in Rat Brain Using the Antagonist [ 3 H]6-Cyano-7-Nitroquinoxaline-2,3-Dione: Comparison with ( R,S )-[ 3 H]Α-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid Binding Sites

Using quantitative autoradiography, we have investigated the binding sites for the potent competitive non- N -methyl-D-aspartate (non-NMDA) glutamate receptor antagonist [ 3 H]6-cyano-7-nitro-quinoxaline-2,3-dione ([ 3 H]-CNQX) in rat brain sections. [ 3 H]CNQX binding was regionally distributed, with the highest levels of binding present in hippocampus in the stratum radiatum of CA1, stratum lucidum of CA3, and molecular layer of dentate gyrus. Scatchard analysis of [ 3 H]CNQX binding in the cerebellar molecular layer revealed an apparent single binding site with a K D = 67 ± 9.0 n M and B max = 3.56 ± 0.34 pmol/mg protein. In displacement studies, quisqualate, L-glutamate, and kainate also appeared to bind to a single class of sites. However, ( R,S )- Α -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) displacement of [ 3 H]CNQX binding revealed two binding sites in the cerebellar molecular layer. Binding of [ 3 H]AMPA to quisqualate receptors in the presence of potassium thiocyanate produced curvilinear Scatchard plots. The curves could be resolved into two binding sites with K D1 = 9.0 ± 3.5 n M , B max = 0.15 ± 0.05 pmol/mg protein, K D2 = 278 ± 50 n M , and B max = 1.54 ± 0.20 pmol/mg protein. The heterogeneous anatomical distribution of [ 3 H]CNQX binding sites correlated to the binding of L-[ 3 H]glutamate to quisqualate receptors and to sites labeled with [ 3 H]AMPA. These results suggest that the non-NMDA glutamate receptor antagonist [ 3 H]CNQX binds with equal affinity to two states of quisqualate receptors which have different affinities for the agonist [ 3 H]AMPA.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65634/1/j.1471-4159.1990.tb01925.x.pd

The I-mode confinement regime at ASDEX Upgrade: global propert ies and characterization of strongly intermittent density fluctuations

Properties of the I­mode confinement regime on the ASDEX Upgrade tokamak are summarized. A weak dependence of the power threshold for the L­I transition on the toroidal magnetic field strength is found. During improved confinement, the edge radial electric field well deepens. Stability calculations show that the I­mode pedestal is peeling­ballooning stable. Turbulence investigations reveal strongly intermittent density fluctuations linked to the weakly coherent mode in the confined plasma, which become stronger as the confinement quality increases. Across all investigated structure sizes ( ≈ ⊥ k 5 – 12 cm − 1 , with ⊥ k the perpendicular wavenumber of turbulent density fluctuations), the intermittent turbulence bursts are observed. Comparison with bolometry data shows that they move poloidally toward the X­point and finally end up in the divertor. This might be indicative that they play a role in inhibiting the density profile growth, such that no pedestal is formed in the edge density profile.European Union (EUROfusion 633053)European Union (EUROfusion AWP15­ENR­09/IPP­02

Characterising The Atmospheric Dynamics Of HD209458b-like Hot Jupiters Using AI Driven Image Recognition/Categorisation

In-order to understand the results of recent observations of exoplanets, models have become increasingly complex. Unfortunately this increases both the computational cost and output size of said models. We intend to explore if AI-image-recognition can alleviate this burden. We used DYNAMICO to run a series of HD209458-like models with different orbital-radii. Training data for a number of features of interest was selected from the initial outputs of these models. This was used to train a pair of multi-categorisation convolutional-neural-networks (CNN), which we applied to our outer-atmosphere-equilibrated models. The features detected by our CNNs revealed that our models fall into two regimes: models with a shorter orbital-radii exhibit significant global mixing which shapes the entire atmospheres dynamics. Whereas, models with longer orbital-radii exhibit negligible mixing except at mid-pressures. Here, the initial non-detection of any trained features revealed a surprise: a night-side hot-spot. Analysis suggests that this occurs when rotational influence is sufficiently weak that divergent flows from the day-side to the night-side dominate over rotational-driven transport, such as the equatorial jet. We suggest that image-classification may play an important role in future, computational, atmospheric studies. However special care must be paid to the data feed into the model, from the colourmap, to training the CNN on features with enough breadth and complexity that the CNN can learn to detect them. However, by using preliminary-studies and prior-models, this should be more than achievable for future exascale calculations, allowing for a significant reduction in future workloads and computational resources.Comment: Accepted for publication in Ap

L008 Défaut de différenciation veino-lymphatique embyonnaire par modulation de l’ARN interférence

L’ARN interférence, mécanisme de régulation de l’expression des gènes, est médiée par les siARNs et les microARNs, ARN non-codants de 20 à 22 nucléotides affectant la régulation post-transcriptionnelle d’ARNm cibles avec lesquels ils s’apparient.La RNase DICER est une enzyme centrale de la biosynthèse des siARNs et microARNs. Les souris dont le gène dicer est invalidé ont un phénotype complexe, et meurent très tôt pendant le développement, notamment à cause d’un défaut d’angiogenèse.Afin d’étudier l’ARN interférence au cours de l’angiogenèse embryonnaire, des souris dont le gène dicer est floxé (mutant conditionnel) sont croisées avec des souris exprimant la recombinase Cre, de manière constitutive, sous le contrôle du promoteur du gène tie2, dirigeant ainsi son expression dans les cellules endothéliales (CE) et les cellules hématopiétiques.Nos résultats montrent que l’invalidation de dicer sous le contrôle du promoteur du gène tie2 entraine une mortalité embryonnaire suite à un œdème et des hémorragies au treizième jour du développement (E13,5). L’analyse histologique montre des vaisseaux lymphatiques remplis de sang, suggérant une mauvaise séparation du réseau sanguin et lymphatique. Cette hypothèse est étudiée par marquage des vaisseaux lymphatiques (LYVE-1) et des vaisseaux sanguins (PECAM) sur embryon entier et peaux isolées à différents stades précédant la mort.Ces embryons présentent également un problème de développement du foie, probablement dû à l’activité du promoteur tie2 dans les lignées hématopoiétiques. La mise en culture de ces foies fœtaux à E13,5 révèle une atteinte des précurseurs hématopoétiques.L’étude de ces précurseurs à des stades plus précoces (E8,5) est en cours au laboratoire.Nos résultats démontrent donc un rôle important de l’ARN interférence dans le contrôle épigénétique de l’angiogenèse et de la lymphangiogenèse embryonnaire mais également dans le développement de l’hématopoièse, suggérant son implication dans la différenciation veino-lymphangiogenèse, dont les mécanismes moléculaires seront discutés