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The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the agricultural frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). This study's objective is to assess the effects of forest disturbances on water fluxes and forest structure in a transitional forest site in the Southern Amazon. We used ET and LST products from MODIS and Landsat 8 and GEDI-derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced in croplands/pastures than in forests (differences up to 20% in the dry season), and more pronounced in second-growth and recently burned areas than in logged and intact forests (differences up to 12% in the dry season). Moreover, ET and LST were negatively related, with more consistent relationships across disturbance classes in the dry season (R2: 0.41–0.87) than in the wet season (R2: 0.18–0.49). Forest and cropland or pasture classes showed contrasting relationships in the dry season. Finally, we found that forest structure exhibited stronger relationships with ET and LST in the most disturbed forests (R2: 0.01–0.43) than in the least disturbed forests (R2 < 0.05). Our findings help to elucidate degraded forests functioning under a changing climate and to improve estimates of water and energy fluxes in Amazonian degraded forests.

Objective: IgA vasculitis (IgAV) (formerly Henoch-Schonlein ̈ Purpura, HSP) rarely causes severe skin lesions in children. The purpose of the research was to determine whether severe skin manifestations were associated with a more severe disease course. Methods: Severe cutaneous manifestations were defined as presence of hemorrhagic vesicles, bullae, ulcerations and/or necroses. Data were collected retrospectively from 12 international tertiary university medical centers. Results: A total of 64 patients with the most severe skin changes in IgAV/HSP and median (Q1, Q3) age of 8.08 (5.08, 11.92) years at the disease onset were compared with 596 IgAV/HSP patients without these manfiestations and median (Q1, Q3) age of 6.33 (4.50, 8.92) years. The patients with severe cutaneous manifestations were older in comparison to other patients with IgAV/HSP (p<0.001), they developed nephritis more frequently (40.6% vs. 20.6%, p = 0.001) with worse outcome of renal disease (p = 0.001). This group of patients also had higher frequencies of severe gastrointestinal complications like hematochezia, massive bleeding and/or intussusception (29.3% vs. 14.8%, p<0.001). D-dimer concentrations were significantly higher in these patients (4.60 mg/L vs. 2.72 mg/L, p = 0.003) and they had more frequent need for treatment with systemic glucocorticoids (84.4% vs. 37.2%, p<0.001) in comparison with the control group. Further multivariate analysis showed that severe cutaneous changes were associated with higher risk of developing nephritis [OR=3.1 (95%CI 1.04–9.21), p = 0.042] and severe gastrointestinal complications [OR=3.65 (95%CI 1.08–12.37), p = 0.038]. Conclusion: Patients with IgAV/HSP and severe skin manifestations had a more severe clinical course and more frequently required glucocorticoids compared to classic IgAV/HSP patients.

LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. We show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad uti

Tropical forest degradation (e.g., anthropogenic disturbances such as selective logging and fires) alters forest structure and function and influences the forest's carbon sink. In this study, we explored structure-function relationships across a variety of degradation levels in the southern Brazilian Amazon by 1) investigating how forest structural properties vary as a function of degradation history using airborne lidar data; 2) assessing the effects of degradation on solar-induced chlorophyll fluorescence (SIF) seasonality using TROPOMI data; and 3) quantifying the contribution of structural variables to SIF using multiple regression models with stepwise selection of lidar metrics. Forest degradation history was obtained through Landsat time-series classification. We found that fire, logging, and time since disturbance were major determinants of forest structure, and that forests affected by fires experienced larger variability in leaf area index (LAI), canopy height and vertical structure relative to logged and intact forests. Moreover, only recently burned forests showed significantly depressed SIF during the dry season compared to intact forests. Canopy height and the vertical distribution of foliage were the best predictors of SIF. Unexpectedly, we found that wet-season SIF was higher in active regenerating forests (~ 4 years after fires or logging) compared with intact forests, despite lower LAI. Our findings help to elucidate the mechanisms of carbon accumulation in anthropogenically disturbed tropical forests and indicate that they can capture large amounts of carbon while recovering.

We assessed PET-CT myocardial blood flow (MBF) using N-13 ammonia, brachial flow-mediated dilation, and cardiopulmonary exercise test in five post-discarged MIS-C survivors. None of the patients (median age: 9, range: 7-18 years; 3 females; 2 males) had preexisting pediatric chronic conditions. At the follow-up visit, two patients exhibited severe perfusion defect developed in the left ventricular cavity, suggesting extensive myocardial ischemia (MBF <2.0) and one patient showed persistent mild pericardial effusion. Others two patients demonstrated endothelial dysfunction. Nevertheless, all patients had lower predicted values in the VO2peak, VO2VAT, OUES, and O2 Pulse (range: 35.2%–64.5%; 15.6%–38.2%; 1.0–1.3 L/min; 4–7 ml/beat), respectively. Our d suggested that previously health MIS-C patients had impaired MBF, endothelial dysfunction and lower cardiopulmonary capacity at follow-up analysis. Multidisciplinary further investigations should be conducted to reinforce these findings.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The palm oil industry is one of the major producers of vegetable oil in the tropics. Palm oil is used extensively for the manufacture of a wide variety of products and its production is increasing by around 9% every year, prompted largely by the expanding biofuel markets. The rise in annual demand for biofuels and vegetable oil from importer countries has caused a dramatic increase in the conversion of forests and peatlands into oil palm plantations in Malaysia. This study assessed the area of forests and peatlands converted into oil palm plantations from 1990 to 2018 in the states of Sarawak and Sabah, Malaysia, and estimated the resulting carbon dioxide (CO2) emissions. To do so, we analyzed multitemporal 30-m resolution Landsat-5 and Landsat-8 images using a hybrid method that combined automatic image processing and manual analyses. We found that over the 28-year period, forest cover declined by 12.6% and 16.3%, and the peatland area declined by 20.5% and 19.1% in Sarawak and Sabah, respectively. In 2018, we found that these changes resulted in CO2 emissions of 0.01577 and 0.00086 Gt CO2-C yr−1, as compared to an annual forest CO2 uptake of 0.26464 and 0.15007 Gt CO2-C yr−1, in Sarawak and Sabah, respectively. Our assessment highlights that carbon impacts extend beyond lost standing stocks, and result in substantial direct emissions from the oil palm plantations themselves, with 2018 oil palm plantations in our study area emitting up to 4% of CO2 uptake by remaining forests. Limiting future climate change impacts requires enhanced economic incentives for land uses that neither convert standing forests nor result in substantial CO2 emissions.

© 2019 The Authors. Methods in Ecology and Evolution © 2019 British Ecological Society In forest ecosystems, many functional processes are governed by local canopy gap dynamics, caused by either natural or anthropogenic factors. Quantifying the size and spatial distribution of canopy gaps enables an improved understanding and predictive modelling of multiple environmental phenomena. For instance knowledge of canopy gap dynamics can help us elucidate time-integrated effects of tree mortality, regrowth and succession rates, carbon flux patterns, species heterogeneity and three-dimensional spacing within structurally complex forest ecosystems. Airborne Laser Scanning (ALS) has emerged as a technology that is well-suited for mapping forest canopy gaps in a wide variety of forest ecosystems and across spatial scales. New technological and algorithmic advances, including ALS remote-sensing, coupled with optimized frameworks for data processing and detection of forest canopy gaps, are allowing an enhanced understanding of forest structure and functional processes. This paper introduces ForestGapR, a cutting-edge open source r package for forest gap analysis from canopy height models derived from ALS and other remote sensing sources. The ForestGapR package offers tools to (a) automate forest canopy gap detection, (b) compute a series of gap statistics, including gap-size frequency distributions and spatial distribution, (c) map gap dynamics (when multitemporal ALS data are available) and (d) convert forest canopy gaps detected into raster or vector layers as per user requirements. As case studies, we run ForestGapR on ALS data collected over four different tropical forest regions worldwide. We hope this new package will enable further research towards understanding the distribution, dynamics and role of canopy gaps not only in tropical forests, but in other forest types elsewhere.

The paper describes the assessment and validation process for the MS score to diagnose macrophage activation syndrome in children with systemic juvenile idiopathic arthritis

Previously, we described associations between health-related quality of life (HRQOL) and disease-related factors among childhood onset systemic lupus erythematosus (cSLE) patients. Here we determined the relationship between HRQOL, disease activity and damage in a large prospective international cohort of cSLE. We compared HRQOL, disease activity and disease damage across different continents and examined the relationship between children's and parents' assessments of HRQOL. Patients with cSLE and their parents completed HRQOL measures at enrollment and ≥4 follow-up visits. Physicians assessed disease activity and damage. The multinational cohort ( n = 467) had relatively low disease activity and damage. Patient and parent HRQOL scores were significantly correlated. Asian and European patients had the highest HRQOL, while South and North American patients had lower HRQOL scores. Renal, CNS, skin and musculoskeletal systems exhibited the highest levels of damage. North and South American and Asian patients were more likely to have disease damage and activity scores above median values, compared with Europeans. Asians were more likely to use cyclophosphamide/rituximab. Female gender, high disease activity and damage, non-White ethnicity, and use of cyclophosphamide and/rituximab were related to lower HRQOL. HRQOL domain scores continue to emphasize that SLE has widespread impact on all aspects of children's and parents' lives.