Association of first-line antidepressants and incident adverse metabolic effects

Clinical Inquiries question: Are first-line antidepressants associated with incident adverse metabolic effects in adults? Evidence-based answer: Selective serotonin reuptake inhibitors (SSRIs) and bupropion statistically significantly increase the risk of incident type 2 diabetes mellitus (T2DM) (strength of recommendation [SOR] B: based on a systematic review and meta-analysis, and a prospective cohort study). Selective serotonin reuptake inhibitors and serotonin-norepinephrine reuptake inhibitors (SNRIs) are associated with weight gain, although there is mixed evidence on both its clinical significance and to what degree depression might be a confounding variable (SOR B: based on 3 prospective cohort studies). Evidence suggests there is an association between the development of metabolic syndrome and SSRIs, but it might be dependent upon the choice of diagnostic criteria and SSRI serum concentration or dose (SOR B: based on 2 retrospective cohort studies). No association between SNRIs, bupropion, and incident hypertension persists after adjustment for demographic characteristics, socioeconomic factors, and comorbidities. No association was observed between SSRIs and incident hypertension (SOR B: based on a retrospective cohort study).Frances K. Wen, PhD; Kimberly Crosby, PharmD; Barbara H. Miller, MD; Michael Rommen, MD; Samuel J. Kirzner, MPH; Toni Hoberecht, MA, MLIS, AHIP; Alyssa Migdalski, MLIS.Dr Wen is Professor, Director of Research, and Behavioral Health Director in the Department of Family and Community Medicine at the University of Oklahoma-Tulsa. Dr Crosby is Associate Professor in the Department of Family and Community Medicine at the University of Oklahoma-Tulsa. Dr Miller is a family physician in Joplin, Mo. Dr Rommen is a family physician in Monroe, La. Mr Kirzner is Double Up Program Manager at Hunger Free Oklahoma in Tulsa. Ms Hoberecht is Technical Services Librarian and Ms Migdalski is Reference and Instruction Librarian in the Schusterman Library at the University of Oklahoma-Tulsa.Includes bibliographical reference

A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast

open20siThe Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.openLagasio, Martina; Parodi, Antonio; Pulvirenti, Luca; Meroni, Agostino N.; Boni, Giorgio; Pierdicca, Nazzareno; Marzano, Frank S.; Luini, Lorenzo; Venuti, Giovanna; Realini, Eugenio; Gatti, Andrea; Tagliaferro, Giulio; Barindelli, Stefano; Monti Guarnieri, Andrea; Goga, Klodiana; Terzo, Olivier; Rucci, Alessio; Passera, Emanuele; Kranzlmueller, Dieter; Rommen, BjornLagasio, Martina; Parodi, Antonio; Pulvirenti, Luca; Meroni, Agostino N.; Boni, Giorgio; Pierdicca, Nazzareno; Marzano, Frank S.; Luini, Lorenzo; Venuti, Giovanna; Realini, Eugenio; Gatti, Andrea; Tagliaferro, Giulio; Barindelli, Stefano; Monti Guarnieri, Andrea; Goga, Klodiana; Terzo, Olivier; Rucci, Alessio; Passera, Emanuele; Kranzlmueller, Dieter; Rommen, Bjor

Comments on “Interference From 24-GHz Automotive Radars to Passive Microwave Earth Remote Sensing Satellites”

In a recent paper, Younis et al. propose an apparently interesting methodology for the computation of the interference received by a spaceborne passive sensor from terrestrial interferences. However, the paper seems to require some clarifications, as some of the conclusions are questionable. This comments paper aims at identifying the most outstanding issues of the publication

BIOMASS LEVEL-2 PRODUCTS - PART II: PROCESSING SCHEMES AND AGB ESTIMATION RESULTS FROM CAMPAIGN DATA

Scheduled for launch in 2023, ESA's seventh Earth Explorer Mission, BIOMASS, will carry the first P-band synthetic aperture radar (SAR) to be flown in space, to gather fully polarimetric acquisitions over forested areas worldwide in interferometric and tomographic modes. This paper presents the algorithms developed to estimate biophysical parameters from BIOMASS measurements and their implementation in the BIOMASS level 2 (L2) prototype processor. The L2 processor will generate global maps of forest Above Ground Biomass (AGB), Forest Height (FH), Forest disturbance (FD). Accurate generation of these products requires the L2 processor to be closely inter-linked with the BIOMASS interferometric processor, in order to produce phase-calibrated interferometric stacks, retrieve sub-canopy terrain topography, and generate a 3D representation of forest structure by use of SAR tomography. AGB estimation results are here shown using BIOMASS-like acquisitions derived from campaign data acquired over six tropical forests in South America and Equatorial Africa

BIOMASS LEVEL-2 PRODUCTS - PART I: RATIONALE AND APPLICATIONS

This paper describes the rationale and development of the estimation techniques for the level-2 data products of the European Space Agency's 7th Earth Explorer BIOMASS mission. BIOMASS is planned for launch in 2023 and will carry the first-ever P-band synthetic aperture radar (SAR) onboard a satellite. It has been designed to produce consistent global maps of the Earth's forests during a nominal five-year lifetime. Fully polarimetric SAR data will be collected and the satellite orbit will be selected for repeat-pass interferometry and tomography in separated mission phases. Mission requirements call for three level-2 data products: above-ground biomass, forest height and forest disturbance. The paper also discusses the expected limitations of the estimation techniques and remaining problems to be addressed

An Exploration Based Cognitive Bias Test for Mice: Effects of Handling Method and Stereotypic Behaviour.

Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training-a major confound in current cognitive bias paradigms