Detecting clear-cuts and decreases in forest vitality using MODIS NDVI time series

This paper examines the potential of MODIS-NDVI time series for detecting clear-cuts in a coniferous forest stand in the south of France. The proposed approach forms part of a survey monitoring the status of forest health and evaluating the forest decline phenomena observed over the last few decades. One of the prerequisites for this survey was that a rapid and easily reproducible method had to be developed that differentiates between forest clear-cuts and changes in forest health induced by environmental factors such as summer droughts. The proposed approach is based on analysis of the breakpoints detected within NDVI time series, using the “Break for Additive Seasonal and Trend” (BFAST) algorithm. To overcome difficulties detecting small areas on the study site, we chose a probabilistic approach based on the use of a conditional inference tree. For model calibration, clear-cut reference data were produced at MODIS resolution (250 m). According to the magnitude of the detected breakpoints, probability classes for the presence of clear-cuts were defined, from greater than 90% to less than 3% probability of a clear-cut. One of the advantages of the probabilistic model is that it allows end users to choose an acceptable level of uncertainty depending on the application. In addition, the use of BFAST allows events to be dated, thus making it possible to perform a retrospective analysis of decreases in forest vitality in the study area

Antiretroviral-naive and -treated HIV-1 patients can harbour more resistant viruses in CSF than in plasma

Objectives The neurological disorders in HIV-1-infected patients remain prevalent. The HIV-1 resistance in plasma and CSF was compared in patients with neurological disorders in a multicentre study. Methods Blood and CSF samples were collected at time of neurological disorders for 244 patients. The viral loads were >50 copies/mL in both compartments and bulk genotypic tests were realized. Results On 244 patients, 89 and 155 were antiretroviral (ARV) naive and ARV treated, respectively. In ARV-naive patients, detection of mutations in CSF and not in plasma were reported for the reverse transcriptase (RT) gene in 2/89 patients (2.2%) and for the protease gene in 1/89 patients (1.1%). In ARV-treated patients, 19/152 (12.5%) patients had HIV-1 mutations only in the CSF for the RT gene and 30/151 (19.8%) for the protease gene. Two mutations appeared statistically more prevalent in the CSF than in plasma: M41L (P = 0.0455) and T215Y (P = 0.0455). Conclusions In most cases, resistance mutations were present and similar in both studied compartments. However, in 3.4% of ARV-naive and 8.8% of ARV-treated patients, the virus was more resistant in CSF than in plasma. These results support the need for genotypic resistance testing when lumbar puncture is performe

Tracking CNS and systemic sources of oxidative stress during the course of chronic neuroinflammation

The functional dynamics and cellular sources of oxidative stress are central to understanding MS pathogenesis but remain elusive, due to the lack of appropriate detection methods. Here we employ NAD(P)H fluorescence lifetime imaging to detect functional NADPH oxidases (NOX enzymes) in vivo to identify inflammatory monocytes, activated microglia, and astrocytes expressing NOX1 as major cellular sources of oxidative stress in the central nervous system of mice affected by experimental autoimmune encephalomyelitis (EAE). This directly affects neuronal function in vivo, indicated by sustained elevated neuronal calcium. The systemic involvement of oxidative stress is mirrored by overactivation of NOX enzymes in peripheral CD11b(+) cells in later phases of both MS and EAE. This effect is antagonized by systemic intake of the NOX inhibitor and anti-oxidant epigallocatechin-3-gallate. Together, this persistent hyper-activation of oxidative enzymes suggests an "oxidative stress memory" both in the periphery and CNS compartments, in chronic neuroinflammation

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

publishedVersio

Global patterns in monthly activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus: a systematic analysis

Background Influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus are the most common viruses associated with acute lower respiratory infections in young children (= 65 years). A global report of the monthly activity of these viruses is needed to inform public health strategies and programmes for their control.Methods In this systematic analysis, we compiled data from a systematic literature review of studies published between Jan 1, 2000, and Dec 31, 2017; online datasets; and unpublished research data. Studies were eligible for inclusion if they reported laboratory-confirmed incidence data of human infection of influenza virus, respiratory syncytial virus, parainfluenza virus, or metapneumovirus, or a combination of these, for at least 12 consecutive months (or 52 weeks equivalent); stable testing practice throughout all years reported; virus results among residents in well-defined geographical locations; and aggregated virus results at least on a monthly basis. Data were extracted through a three-stage process, from which we calculated monthly annual average percentage (AAP) as the relative strength of virus activity. We defined duration of epidemics as the minimum number of months to account for 75% of annual positive samples, with each component month defined as an epidemic month. Furthermore, we modelled monthly AAP of influenza virus and respiratory syncytial virus using site-specific temperature and relative humidity for the prediction of local average epidemic months. We also predicted global epidemic months of influenza virus and respiratory syncytial virus on a 5 degrees by 5 degrees grid. The systematic review in this study is registered with PROSPERO, number CRD42018091628.Findings We initally identified 37 335 eligible studies. Of 21 065 studies remaining after exclusion of duplicates, 1081 full-text articles were assessed for eligibility, of which 185 were identified as eligible. We included 246 sites for influenza virus, 183 sites for respiratory syncytial virus, 83 sites for parainfluenza virus, and 65 sites for metapneumovirus. Influenza virus had clear seasonal epidemics in winter months in most temperate sites but timing of epidemics was more variable and less seasonal with decreasing distance from the equator. Unlike influenza virus, respiratory syncytial virus had clear seasonal epidemics in both temperate and tropical regions, starting in late summer months in the tropics of each hemisphere, reaching most temperate sites in winter months. In most temperate sites, influenza virus epidemics occurred later than respiratory syncytial virus (by 0.3 months [95% CI -0.3 to 0.9]) while no clear temporal order was observed in the tropics. Parainfluenza virus epidemics were found mostly in spring and early summer months in each hemisphere. Metapneumovirus epidemics occurred in late winter and spring in most temperate sites but the timing of epidemics was more diverse in the tropics. Influenza virus epidemics had shorter duration (3.8 months [3.6 to 4.0]) in temperate sites and longer duration (5.2 months [4.9 to 5.5]) in the tropics. Duration of epidemics was similar across all sites for respiratory syncytial virus (4.6 months [4.3 to 4.8]), as it was for metapneumovirus (4.8 months [4.4 to 5.1]). By comparison, parainfluenza virus had longer duration of epidemics (6.3 months [6.0 to 6.7]). Our model had good predictability in the average epidemic months of influenza virus in temperate regions and respiratory syncytial virus in both temperate and tropical regions. Through leave-one-out cross validation, the overall prediction error in the onset of epidemics was within 1 month (influenza virus -0.2 months [-0.6 to 0.1]; respiratory syncytial virus 0.1 months [-0.2 to 0.4]).Interpretation This study is the first to provide global representations of month-by-month activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus. Our model is helpful in predicting the local onset month of influenza virus and respiratory syncytial virus epidemics. The seasonality information has important implications for health services planning, the timing of respiratory syncytial virus passive prophylaxis, and the strategy of influenza virus and future respiratory syncytial virus vaccination. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd