Star Formation in Dwarf Galaxies

We explore mechanisms for the regulation of star formation in dwarf galaxies. We concentrate primarily on a sample in the Virgo cluster, which has HI and blue total photometry, for which we collected H$\alpha$ data at the Wise Observatory. We find that dwarf galaxies do not show the tight correlation of the surface brightness of H$\alpha$ (a star formation indicator) with the HI surface density, or with the ratio of this density to a dynamical timescale, as found for large disk or starburst galaxies. On the other hand, we find the strongest correlation to be with the average blue surface brightness, indicating the presence of a mechanism regulating the star formation by the older (up to 1 Gyr) stellar population if present, or by the stellar population already formed in the present burst.Comment: 15 pages (LATEX aasms4 style) and three postscript figures, accepted for publication in the Astrophysical Journa

Journal Club: comparison of symptomatic and asymptomatic persons with Alzheimer disease neuropathology.

Advances in neuroimaging, biomarkers, and clinical data have led to the hypothesis that the pathologic process of Alzheimer dementia begins decades prior to functional decline and diagnosis.1–3 High-profile clinical trial results have shown that biomarker changes can be made via pharmacologic intervention; however, the timing of this intervention has likely been too late to impact the cascade of neurodegenerative changes.4,5 In “Comparison of symptomatic and asymptomatic persons with Alzheimer disease neuropathology” by Monsell et al.,6 neuropathologic and clinical data were used to determine the risk of developing clinically significant cognitive impairment. This work represents a significant contribution because it examines a large cohort of autopsy data, which includes patients with Alzheimer dementia neuropathology who were clinically normal or diagnosed with mild cognitive impairment and Alzheimer-type dementia. The authors report a 3-fold increase in the risk of cognitive symptoms in association with quantifiable increases in neurofibrillary tangle pathology. Additionally, several other factors including APOE gene status, history of depression, and age impacted the clinical presentation. The ultimate goal of this investigation and similar studies is to facilitate the early and accurate identification of those at risk of developing Alzheimer dementia, such that potentially disease-modifying therapies may be considered

A Review of Dementia with Lewy Bodies' Impact, Diagnostic Criteria and Treatment

Dementia with Lewy bodies is one of the most common causes of dementia. It is not as common as Alzheimer's disease; the general public's awareness of the disease is poor in comparison. Its effects on caregivers and patients alike are not well known to the general population. There are currently no FDA-approved medications specifically for the treatment of DLB. Many of the medications that are approved for Alzheimer's disease are widely used in the treatment of DLB with varying degrees of success. Treatment of DLB is life long and requires a dedicated team of physicians and caregivers to minimize the degree of morbidity and mortality experienced by the patients suffering from the disease as it progresses

Tau Imaging in Alzheimer's Disease Diagnosis and Clinical Trials

In vivo imaging of the tau protein has the potential to aid in quantitative diagnosis of Alzheimer's disease, corroborate or dispute the amyloid hypothesis, and demonstrate biomarker engagement in clinical drug trials. A host of tau positron emission tomography agents have been designed, validated, and tested in humans. Several agents have characteristics approaching the ideal imaging tracer with some limitations, primarily regarding off-target binding. Dozens of clinical trials evaluating imaging techniques and several pharmaceutical trials have begun to integrate tau imaging into their protocols

Radar and optical leonids

International audienceWe present joint optical-radar observations of meteors collected near the peak of the leonid activity in 2002. We show four examples of joint detections with a large, phased array L-band radar and with intensified video cameras. The general characteristic of the radar-detected optical meteors is that they show the radar detection below the termination of the optical meteor. Therefore, at least some radar events associated with meteor activity are neither head echoes nor trail echoes, but probably indicate the formation of "charged clouds" after the visual meteor is extinguished

VEGAS: A VST Early-type GAlaxy Survey. III. Mapping the galaxy structure, interactions and intragroup light in the NGC 5018 group

Most of the galaxies in the Universe at present day are in groups, which are key to understanding the galaxy evolution. In this work we present a new deep mosaic of 1.2 x 1.0 square degrees of the group of galaxies centered on NGC 5018, acquired at the ESO VLT Survey Telescope. We use u, g, r images to analyse the structure of the group members and to estimate the intra-group light. Taking advantage of the deep and multiband photometry and of the large field of view of the VST telescope, we studied the structure of the galaxy members and the faint features into the intra-group space and we give an estimate of the intragroup diffuse light in the NGC 5018 group of galaxies. We found that ~ 41% of the total g-band luminosity of the group is in the form of intragroup light (IGL). The IGL has a (g - r) color consistent with those of other galaxies in the group, indicating that the stripping leading to the formation of IGL is ongoing. From the study of this group we can infer that there are at least two different interactions involving the group members: one between NGC 5018 and NGC 5022, which generates the tails and ring-like structures detected in the light, and another between NGC 5022 and MCG-03-34-013 that have produced the HI tail. A minor merging event also happened in the formation history of NGC 5018 that have perturbed the inner structure of this galaxy.Comment: 21 pages, 15 figures. Accepted for publication in Ap

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease prediction tasks requires models capable of representing, at the same time, individual features as well as data associations between subjects from potentially large populations. Graphs provide a natural framework for such tasks, yet previous graph-based approaches focus on pairwise similarities without modelling the subjects' individual characteristics and features. On the other hand, relying solely on subject-specific imaging feature vectors fails to model the interaction and similarity between subjects, which can reduce performance. In this paper, we introduce the novel concept of Graph Convolutional Networks (GCN) for brain analysis in populations, combining imaging and non-imaging data. We represent populations as a sparse graph where its vertices are associated with image-based feature vectors and the edges encode phenotypic information. This structure was used to train a GCN model on partially labelled graphs, aiming to infer the classes of unlabelled nodes from the node features and pairwise associations between subjects. We demonstrate the potential of the method on the challenging ADNI and ABIDE databases, as a proof of concept of the benefit from integrating contextual information in classification tasks. This has a clear impact on the quality of the predictions, leading to 69.5% accuracy for ABIDE (outperforming the current state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion, significantly outperforming standard linear classifiers where only individual features are considered.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Stromgren Photometry from z=0 to z~1. The Method

We use rest-frame Stromgren photometry to observe clusters of galaxies in a self-consistent manner from z=0 to z=0.8. Stromgren photometry of galaxies is an efficient compromise between standard broad-band photometry and spectroscopy, in the sense that it is more sensitive to subtle variations in spectral energy distributions than the former, yet much less time-consuming than the latter. Principal Component Analysis (PCA) is used to extract maximum information from the Stromgren data. By calibrating the Principal Components using well-studied galaxies (and stellar population models), we develop a purely empirical method to detect, and subsequently classify, cluster galaxies at all redshifts smaller than 0.8. Interlopers are discarded with unprecedented efficiency (up to 100%). The first Principal Component essentially reproduces the Hubble Sequence, and can thus be used to determine the global star formation history of cluster members. The (PC2, PC3) plane allows us to identify Seyfert galaxies (and distinguish them from starbursts) based on photometric colors alone. In the case of E/S0 galaxies with known redshift, we are able to resolve the age-dust- metallicity degeneracy, albeit at the accuracy limit of our present observations. This technique will allow us to probe galaxy clusters well beyond their cores and to fainter magnitudes than spectroscopy can achieve. We are able to directly compare these data over the entire redshift range without a priori assumptions because our observations do not require k-corrections. The compilation of such data for different cluster types over a wide redshift range is likely to set important constraints on the evolution of galaxies and on the clustering process.Comment: 35 pages, 18 figures, accepted by ApJ