150 resultados para color appearance models
Resumo:
Purpose: To phenotype a large 3 generation Swiss family with pattern dystrophy and to report a successful result of treatment with ranibizumab of a subfoveal choroidal neovascularisation (CNV) associated with pattern dystrophy in 1 patient Patients and methods: 4 affected and 3 unaffected patients (3 female 4 male, age range: 19 - 80 years) were assessed with a complete ophthalmologic examination. AF images were taken using Heidelberg Retina Angiograph and the digital color photos, fluorescein angiogragraphy (FFA) using the same TOPCON 501 camera. Electroretinogram (full-field and multifocal) was performed in 1 affected patient. One 48 years old patient developed a subfoveal CNV, which was treated with 2 injections of ranibizumab, at 3 months interval. Blood sample was taken for molecular analysis (screening of the gene RDS). Results: Two patients had a typical fundoscopic appearance of pattern dystrophy with butterfly shaped deposit at the fovea and some peripheral flecks, as shown with AF imaging.. Two others affected patients had a more unusual appearance with some macular atrophy in one or both eyes, surrounded by flecks. The visual acuity ranged from 1.0 to 0.1 according to Snellen EDTRS chart. The patient with subfoveal CNV presented a drop of vision form 1.0 to 0.6 within 10 days prior to the diagnosis and also reported some metamorphopsia. FFA and optical computerized tomography (OCT) confirmed a classic CNV. After the 1st injection her vision improved to 1.0 but persistent metamorphopsia and fluid on OCT motivated a second injection. One month after the second injection the OCT was flat and the patient had no symptoms. The results of RDS screening will be presented at the meeting. Conclusion: We present a family with pattern dystrophy, with some members having an unusual fundus appearance, which was mistaken for an early onset dry AMD. The AF imaging is a useful tool in diagnosing this condition. A CNV associated with pattern dystrophy a rare. This is the first report of a successful treatment of the CNV with anti-VEGF intravitreal injections.
Resumo:
Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.
Resumo:
A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.
Resumo:
BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.
Resumo:
Summary (in English) Computer simulations provide a practical way to address scientific questions that would be otherwise intractable. In evolutionary biology, and in population genetics in particular, the investigation of evolutionary processes frequently involves the implementation of complex models, making simulations a particularly valuable tool in the area. In this thesis work, I explored three questions involving the geographical range expansion of populations, taking advantage of spatially explicit simulations coupled with approximate Bayesian computation. First, the neutral evolutionary history of the human spread around the world was investigated, leading to a surprisingly simple model: A straightforward diffusion process of migrations from east Africa throughout a world map with homogeneous landmasses replicated to very large extent the complex patterns observed in real human populations, suggesting a more continuous (as opposed to structured) view of the distribution of modern human genetic diversity, which may play a better role as a base model for further studies. Second, the postglacial evolution of the European barn owl, with the formation of a remarkable coat-color cline, was inspected with two rounds of simulations: (i) determine the demographic background history and (ii) test the probability of a phenotypic cline, like the one observed in the natural populations, to appear without natural selection. We verified that the modern barn owl population originated from a single Iberian refugium and that they formed their color cline, not due to neutral evolution, but with the necessary participation of selection. The third and last part of this thesis refers to a simulation-only study inspired by the barn owl case above. In this chapter, we showed that selection is, indeed, effective during range expansions and that it leaves a distinguished signature, which can then be used to detect and measure natural selection in range-expanding populations. Résumé (en français) Les simulations fournissent un moyen pratique pour répondre à des questions scientifiques qui seraient inabordable autrement. En génétique des populations, l'étude des processus évolutifs implique souvent la mise en oeuvre de modèles complexes, et les simulations sont un outil particulièrement précieux dans ce domaine. Dans cette thèse, j'ai exploré trois questions en utilisant des simulations spatialement explicites dans un cadre de calculs Bayésiens approximés (approximate Bayesian computation : ABC). Tout d'abord, l'histoire de la colonisation humaine mondiale et de l'évolution de parties neutres du génome a été étudiée grâce à un modèle étonnement simple. Un processus de diffusion des migrants de l'Afrique orientale à travers un monde avec des masses terrestres homogènes a reproduit, dans une très large mesure, les signatures génétiques complexes observées dans les populations humaines réelles. Un tel modèle continu (opposé à un modèle structuré en populations) pourrait être très utile comme modèle de base dans l'étude de génétique humaine à l'avenir. Deuxièmement, l'évolution postglaciaire d'un gradient de couleur chez l'Effraie des clocher (Tyto alba) Européenne, a été examiné avec deux séries de simulations pour : (i) déterminer l'histoire démographique de base et (ii) tester la probabilité qu'un gradient phénotypique, tel qu'observé dans les populations naturelles puisse apparaître sans sélection naturelle. Nous avons montré que la population actuelle des chouettes est sortie d'un unique refuge ibérique et que le gradient de couleur ne peux pas s'être formé de manière neutre (sans l'action de la sélection naturelle). La troisième partie de cette thèse se réfère à une étude par simulations inspirée par l'étude de l'Effraie. Dans ce dernier chapitre, nous avons montré que la sélection est, en effet, aussi efficace dans les cas d'expansion d'aire de distribution et qu'elle laisse une signature unique, qui peut être utilisée pour la détecter et estimer sa force.
Resumo:
Aspergillus lentulus, an Aspergillus fumigatus sibling species, is increasingly reported in corticosteroid-treated patients. Its clinical significance is unknown, but the fact that A. lentulus shows reduced antifungal susceptibility, mainly to voriconazole, is of serious concern. Heterologous expression of cyp51A from A. fumigatus and A. lentulus was performed in Saccharomyces cerevisiae to assess differences in the interaction of Cyp51A with the azole drugs. The absence of endogenous ERG11 was efficiently complemented in S. cerevisiae by the expression of either Aspergillus cyp51A allele. There was a marked difference between azole minimum inhibitory concentration (MIC) values of the clones expressing each Aspergillus spp. cyp51A. Saccharomyces cerevisiae clones expressing A. lentulus alleles showed higher MICs to all of the azoles tested, supporting the hypothesis that the intrinsic azole resistance of A. lentulus could be associated with Cyp51A. Homology models of A. fumigatus and A. lentulus Cyp51A protein based on the crystal structure of Cyp51p from Mycobacterium tuberculosis in complex with fluconazole were almost identical owing to their mutual high sequence identity. Molecular dynamics (MD) was applied to both three-dimensional protein models to refine the homology modelling and to explore possible differences in the Cyp51A-voriconazole interaction. After 20ns of MD modelling, some critical differences were observed in the putative closed form adopted by the protein upon voriconazole binding. A closer study of the A. fumigatus and A. lentulus voriconazole putative binding site in Cyp51A suggested that some major differences in the protein's BC loop could differentially affect the lock-up of voriconazole, which in turn could correlate with their different azole susceptibility profiles.
Resumo:
The investigation of unexplained syncope remains a challenging clinical problem. In the present study we sought to evaluate the diagnostic value of a standardized work-up focusing on non invasive tests in patients with unexplained syncope referred to a syncope clinic, and whether certain combinations of clinical parameters are characteristic of rhythmic and reflex causes of syncope. METHODS AND RESULTS: 317 consecutive patients underwent a standardized work-up including a 12-lead ECG, physical examination, detailed history with screening for syncope-related symptoms using a structured questionnaire followed by carotid sinus massage (CSM), and head-up tilt test. Invasive testings including an electrophysiological study and implantation of a loop recorder were only performed in those with structural heart disease or traumatic syncope. Our work-up identified an etiology in 81% of the patients. Importantly, three quarters of the causes were established non invasively combining head-up tilt test, CSM and hyperventilation testing. Invasive tests yielded an additional 7% of diagnoses. Logistic analysis identified age and number of significant prodromes as the only predictive factors of rhythmic syncope. The same two factors, in addition to the duration of the ECG P-wave, were also predictive of vasovagal and psychogenic syncope. These factors, optimally combined in predictive models, showed a high negative and a modest positive predictive value. CONCLUSION: A standardized work-up focusing on non invasive tests allows to establish more than three quarters of syncope causes. Predictive models based on simple clinical parameters may help to distinguish between rhythmic and other causes of syncope
Resumo:
A new metabolite profiling approach combined with an ultrarapid sample preparation procedure was used to study the temporal and spatial dynamics of the wound-induced accumulation of jasmonic acid (JA) and its oxygenated derivatives in Arabidopsis thaliana. In addition to well known jasmonates, including hydroxyjasmonates (HOJAs), jasmonoyl-isoleucine (JA-Ile), and its 12-hydroxy derivative (12-HOJA-Ile), a new wound-induced dicarboxyjasmonate, 12-carboxyjasmonoyl-l-isoleucine (12-HOOCJA-Ile) was discovered. HOJAs and 12-HOOCJA-Ile were enriched in the midveins of wounded leaves, strongly differentiating them from the other jasmonate metabolites studied. The polarity of these oxylipins at physiological pH correlated with their appearance in midveins. When the time points of accumulation of different jasmonates were determined, JA levels were found to increase within 2-5 min of wounding. Remarkably, these changes occurred throughout the plant and were not restricted to wounded leaves. The speed of the stimulus leading to JA accumulation in leaves distal to a wound is at least 3 cm/min. The data give new insights into the spatial and temporal accumulation of jasmonates and have implications in the understanding of long-distance wound signaling in plants.
Resumo:
Monocytes are central mediators in the development of atherosclerotic plaques. They circulate in blood and eventually migrate into tissue including the vessel wall where they give rise to macrophages and dendritic cells. The existence of monocyte subsets with distinct roles in homeostasis and inflammation suggests specialization of function. These subsets are identified based on expression of the CD14 and CD16 markers. Routinely applicable protocols remain elusive, however. Here, we present an optimized four-color flow cytometry protocol for analysis of human blood monocyte subsets using a specific PE-Cy5-conjugated monoclonal antibody (mAb) to HLA-DR, a PE-Cy7-conjugated mAb to CD14, a FITC-conjugated mAb to CD16, and PE-conjugated mAbs to additional markers relevant to monocyte function. Classical CD14(+)CD16(-) monocytes (here termed "Mo1" subset) expressed high CCR2, CD36, CD64, and CD62L, but low CX(3)CR1, whereas "nonclassical" CD14(lo)CD16(+) monocytes (Mo3) essentially showed the inverse expression pattern. CD14(+)CD16(+) monocytes (Mo2) expressed high HLA-DR, CD36, and CD64. In patients with stable coronary artery disease (n = 13), classical monocytes were decreased, whereas "nonclassical" monocytes were increased 90% compared with healthy subjects with angiographically normal coronary arteries (n = 14). Classical monocytes from CAD patients expressed higher CX(3)CR1 and CCR2 than controls. Thus, stable CAD is associated with expansion of the nonclassical monocyte subset and increased expression of inflammatory markers on monocytes. Flow cytometric analysis of monocyte subsets and marker expression may provide valuable information on vascular inflammation. This may translate into the identification of monocyte subsets as selective therapeutic targets, thus avoiding adverse events associated with indiscriminate monocyte inhibition.
Resumo:
The lymphatic vascular system, the body's second vascular system present in vertebrates, has emerged in recent years as a crucial player in normal and pathological processes. It participates in the maintenance of normal tissue fluid balance, the immune functions of cellular and antigen trafficking and absorption of fatty acids and lipid-soluble vitamins in the gut. Recent scientific discoveries have highlighted the role of lymphatic system in a number of pathologic conditions, including lymphedema, inflammatory diseases, and tumor metastasis. Development of genetically modified animal models, identification of lymphatic endothelial specific markers and regulators coupled with technological advances such as high-resolution imaging and genome-wide approaches have been instrumental in understanding the major steps controlling growth and remodeling of lymphatic vessels. This review highlights the recent insights and developments in the field of lymphatic vascular biology.
Resumo:
Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.
Resumo:
Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.