Fermi Gamma-ray Imaging of a Radio Galaxy

The Fermi Gamma-ray Space Telescope has detected the gamma-ray glow emanating from the giant radio lobes of the radio galaxy Centaurus A. The resolved gamma-ray image shows the lobes clearly separated from the central active source. In contrast to all other active galaxies detected so far in high-energy gamma-rays, the lobe flux constitutes a considerable portion (>1/2) of the total source emission. The gamma-ray emission from the lobes is interpreted as inverse Compton scattered relic radiation from the cosmic microwave background (CMB), with additional contribution at higher energies from the infrared-to-optical extragalactic background light (EBL). These measurements provide gamma-ray constraints on the magnetic field and particle energy content in radio galaxy lobes, and a promising method to probe the cosmic relic photon fields.Comment: 27 pages, includes Supplementary Online Material; corresponding authors: C.C. Cheung, Y. Fukazawa, J. Knodlseder, L. Stawar

Fermi Large Area Telescope observations of PSR J1836+5925

The discovery of the gamma-ray pulsar PSR J1836+5925, powering the formerly unidentified EGRET source 3EG J1835+5918, was one of the early accomplishments of the Fermi Large Area Telescope (LAT). Sitting 25 degrees off the Galactic plane, PSR J1836+5925 is a 173 ms pulsar with a characteristic age of 1.8 million years, a spindown luminosity of 1.1$\times10^{34}$ erg s$^{-1}$, and a large off-peak emission component, making it quite unusual among the known gamma-ray pulsar population. We present an analysis of one year of LAT data, including an updated timing solution, detailed spectral results and a long-term light curve showing no indication of variability. No evidence for a surrounding pulsar wind nebula is seen and the spectral characteristics of the off-peak emission indicate it is likely magnetospheric. Analysis of recent XMM observations of the X-ray counterpart yields a detailed characterization of its spectrum, which, like Geminga, is consistent with that of a neutron star showing evidence for both magnetospheric and thermal emission.Comment: Accepted to Astrophysical Journa

A change in the optical polarization associated with a gamma-ray flare in the blazar 3C 279

It is widely accepted that strong and variable radiation detected over all accessible energy bands in a number of active galaxies arises from a relativistic, Doppler-boosted jet pointing close to our line of sight. The size of the emitting zone and the location of this region relative to the central supermassive black hole are, however, poorly known, with estimates ranging from light-hours to a light-year or more. Here we report the coincidence of a gamma-ray flare with a dramatic change of optical polarization angle. This provides evidence for co-spatiality of optical and gamma-ray emission regions and indicates a highly ordered jet magnetic field. The results also require a non-axisymmetric structure of the emission zone, implying a curved trajectory for the emitting material within the jet, with the dissipation region located at a considerable distance from the black hole, at about 10^5 gravitational radii.Comment: Published in Nature issued on 18 February 2010. Corresponding authors: Masaaki Hayashida and Greg Madejsk

oA novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.</p> <p>Methods</p> <p>Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.</p> <p>Results</p> <p>The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.</p> <p>Conclusion</p> <p>It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.</p

Inflammatory Markers and Poor Outcome after Stroke: A Prospective Cohort Study and Systematic Review of Interleukin-6

In a prospective cohort study of patient outcomes following stroke, William Whiteley and colleagues find that markers of inflammatory response are associated with poor outcomes. However, addition of these markers to existing prognostic models does not improve outcome prediction

Progesterone after previous preterm birth for prevention of neonatal respiratory distress syndrome (PROGRESS): a randomised controlled trial

Background: Neonatal respiratory distress syndrome, as a consequence of preterm birth, is a major cause of early mortality and morbidity during infancy and childhood. Survivors of preterm birth continue to remain at considerable risk of both chronic lung disease and long-term neurological handicap. Progesterone is involved in the maintenance of uterine quiescence through modulation of the calcium-calmodulin-myosin-light-chain-kinase system in smooth muscle cells. The withdrawal of progesterone, either actual or functional is thought to be an antecedent to the onset of labour. While there have been recent reports of progesterone supplementation for women at risk of preterm birth which show promise in this intervention, there is currently insufficient data on clinically important outcomes for both women and infants to enable informed clinical decision-making. The aims of this randomised, double blind, placebo controlled trial are to assess whether the use of vaginal progesterone pessaries in women with a history of previous spontaneous preterm birth will reduce the risk and severity of respiratory distress syndrome, so improving their infant's health, without increasing maternal risks. Methods Design: Multicentred randomised, double blind, placebo-controlled trial. Inclusion Criteria: pregnant women with a live fetus, and a history of prior preterm birth at less than 37 weeks gestation and greater than 20 weeks gestation in the immediately preceding pregnancy, where onset of labour occurred spontaneously, or in association with cervical incompetence, or following preterm prelabour ruptured membranes. Trial Entry & Randomisation: After obtaining written informed consent, eligible women will be randomised between 18 and 23+6 weeks gestation using a central telephone randomisation service. The randomisation schedule prepared by non clinical research staff will use balanced variable blocks, with stratification according to plurality of the pregnancy and centre where planned to give birth. Eligible women will be randomised to either vaginal progesterone or vaginal placebo. Study Medication & Treatment Schedules: Treatment packs will appear identical. Woman, caregivers and research staff will be blinded to treatment allocation. Primary Study Outcome: Neonatal Respiratory Distress Syndrome (defined by incidence and severity). Sample Size: of 984 women to show a 40% reduction in respiratory distress syndrome from 15% to 9% (p = 0.05, 80% power). Discussion: This is a protocol for a randomised trial.Jodie M. Dodd, Caroline A. Crowther, Andrew J. McPhee, Vicki Flenady, and Jeffrey S. Robinso

Cytological diagnostic features of late breast implant seromas. From reactive to anaplastic large cell lymphoma

Late breast implant seroma may be the presentation of a breast implant-associated anaplastic large cell lymphoma (BI-ALCL), which claims for a prompt recognition. However, BI-ALCL diagnosis on fine-needle aspiration (FNA) might be challenging for pathologists lacking experience with peri-implant breast effusions. Sixty-seven late breast implant seromas collected by FNA from 50 patients were evaluated by Papanicolaou smear stain and immunocytochemistry on cell blocks. A diagnostic algorithm based on the cellular composition, cell morphology and percentage of CD30+ cells was developed. Histological evaluation of the corresponding peri-prosthetic capsules was also performed. Most of the effusions (91% of the samples) were classified as reactive and 9% as BI-ALCL. In the BI-ALCL cases, medium-to-large atypical cells expressing CD30 represented more than 70% of the cellularity, whereas in in the reactive effusions CD30+ elements were extremely rare (<5%) and consisted of non-atypical elements. The reactive effusions were categorized into three patterns: i) acute infiltrate with prominent neutrophilic component (33% of the samples); ii) mixed infiltrate characterized by a variable number of neutrophils, lymphocytes and macrophages (30% of the samples); iii) chronic infiltrate composed predominantly of T lymphocytes or macrophages with only sporadic granulocytes (37% of the samples). The inflammatory cytological patterns were consistent with the histology of the corresponding capsules. Our results indicate that cytological analysis of late breast implant effusions, supported by the knowledge of the heterogeneous cytomorphological spectrum of late seromas, is a valuable approach for the early recognition of BI-ALCL

Robust Biomarkers: Methodologically Tracking Causal Processes in Alzheimer’s Measurement

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions