Testing a phantom eye under various signal-to-noise ratio conditions using eleven different OCT devices

We compared eleven OCT devices in their ability to quantify retinal layer thicknesses under different signal-strength conditions, using a commercially available phantom eye. We analyzed a medium-intensity 50 µm layer in an identical manner for all devices, using the provided log-scale images and a reconstructed linear-scale tissue reflectivity metric. Thickness measurements were highly comparable when the data were analyzed in an identical manner. With optimal signal strength, the thickness of the 50 µm layer was overestimated by a mean of 4.3 µm in the log-scale images and of 2.7 µm in the linear-scale images

Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian Semiarid region, for use in Dynamic Global Vegetation Models.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caating

Spatial distribution of early red lesions is a risk factor for development of vision-threatening diabetic retinopathy

Aims/hypothesis Diabetic retinopathy is characterised by morphological lesions related to disturbances in retinal blood flow. It has previously been shown that the early development of retinal lesions temporal to the fovea may predict the development of treatment-requiring diabetic maculopathy. The aim of this study was to map accurately the area where lesions could predict progression to vision-threatening retinopathy. Methods The predictive value of the location of the earliest red lesions representing haemorrhages and/or microaneurysms was studied by comparing their occurrence in a group of individuals later developing vision-threatening diabetic retinopathy with that in a group matched with respect to diabetes type, age, sex and age of onset of diabetes mellitus who did not develop vision-threatening diabetic retinopathy during a similar observation period. Results The probability of progression to vision-threatening diabetic retinopathy was higher in a circular area temporal to the fovea, and the occurrence of the first lesions in this area was predictive of the development of vision-threatening diabetic retinopathy. The calculated peak value showed that the risk of progression was 39.5% higher than the average. There was no significant difference in the early distribution of lesions in participants later developing diabetic maculopathy or proliferative diabetic retinopathy. Conclusions/interpretation The location of early red lesions in diabetic retinopathy is predictive of whether or not individuals will later develop vision-threatening diabetic retinopathy. This evidence should be incorporated into risk models used to recommend control intervals in screening programmes for diabetic retinopathy

Latin America's Nitrogen Challenge

Latin America (LA) has many social indicators similar to those of highly developed economies but most frequently falls midway between least developed countries and industrialized regions. To move forward, LA must address uncontrolled urbanization, agricultural production, social inequity, and destruction of natural resources. We discuss these interrelated challenges in terms of human impact on the nitrogen (N) cycle. Human activity has caused unprecedented changes to the global N cycle; in the past century; total global fixation of reactive N (Nr) has at least doubled (1). Excess Nr leaked into the environment negatively affects soils, atmosphere, and water resources in temperate zones (1). In addition to N excess from human impact, mining of natural soil N creates N deficits in some regions (2, 3).Fil: Austin, Amy Theresa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Bustamante, M. M. C.. Universidade Do Brasilia; BrasilFil: Nardoto, G. B.. Universidade Do Brasilia; BrasilFil: Mitre, S. K.. Universidade Do Brasilia; BrasilFil: Pérez, T.. Instituto Venezolano de Investigaciones Cientificas; VenezuelaFil: Ometto, J. P. H. B.. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; BrasilFil: Ascarrunz, N. L.. Instituto Boliviano de Investigación Forestal; BoliviaFil: Forti, M. C.. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; BrasilFil: Longo, K.. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; BrasilFil: Gavito, M. E.. Universidad Nacional Autónoma de México; MéxicoFil: Enrich Prast, A.. Universidade Federal do Rio de Janeiro; BrasilFil: Martinelli, L. A.. Universidade de Sao Paulo; Brasi

Relaxation of natural selection in the evolution of the giant lungfish genomes

Nonadaptive hypotheses on the evolution of eukaryotic genome size predict an expansion when the process of purifying selection becomes weak. Accordingly, species with huge genomes, such as lungfish, are expected to show a genome-wide relaxation signature of selection compared with other organisms. However, few studies have empirically tested this prediction using genomic data in a comparative framework. Here, we show that 1) the newly assembled transcriptome of the Australian lungfish, Neoceratodus forsteri, is characterized by an excess of pervasive transcription, or transcriptional leakage, possibly due to suboptimal transcriptional control, and 2) a significant relaxation signature in coding genes in lungfish species compared with other vertebrates. Based on these observations, we propose that the largest known animal genomes evolved in a nearly neutral scenario where genome expansion is less efficiently constraine

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Canopy-scale biophysical controls on transpiration and evaporation in the Amazon Basin

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales