The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
David F Garwayheath - One of the best experts on this subject based on the ideXlab platform.
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a novel distribution of visual field test points to improve the correlation between Structure Function measurements
Investigative Ophthalmology & Visual Science, 2012Co-Authors: Rin Asaoka, David F Garwayheath, Richard A Russell, Rizwan Malik, David P. CrabbAbstract:PURPOSE: To create a new visual field (VF) test grid centered at the optic disc (disc-centered field [DCF]) and to infer the combination of VF test points (Structure-Function field [SFF]), taken from the DCF and the conventional fovea-centered 24-2 grid (24-2) of standard automated perimetry, which yields the strongest sectorial correlation between Structure-Function measurements of retinal nerve fiber layer (RNFL) thickness and VF sensitivity. METHODS: In 50 eyes with ocular hypertension or open angle glaucoma, the DCF and 24-2 VF were measured with a humphrey field analyzer II (Full Threshold strategy) and RNFL thickness was measured with Stratus optical coherence tomography. test points from the DCF and 24-2 VF Were combined and divided into 12 sectors according to the spatial distribution of the RNFL. A novel VF for Structure-Function studies was established using the following criteria: each sector must contain at least one or two test points (depending on the sector's location), and the combination of test points which yields the strongest Structure-Function correlation is selected. RESULTS: The SFF consisted of 40 test points. The Structure-Function correlation for the SFF was compared with the standard 24-2 VF; a multiple-comparison test for dependent groups was carried out using a percentile bootstrap method, which indicated that the sector correlation coefficients in the SFF were significantly higher than those in the 24-2 VF. CONCLUSIONS: The SFF, with fewer test locations, has a stronger Structure-Function correlation than the 24-2 VF. This improved correlation may help clinicians to better interpret Functional measurements in relation to structural measurements.
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Structure Function relationship in glaucoma past thinking and current concepts
Clinical and Experimental Ophthalmology, 2012Co-Authors: Rizwan Malik, William H. Swanson, David F GarwayheathAbstract:An understanding of the relationship between Functional and structural measures in primary open-angle glaucoma is necessary for both grading the severity of disease and for understanding the natural history of the condition. This article outlines the current evidence for the nature of this relationship and highlights the current mathematical models linking Structure and Function. Large clinical trials demonstrate that both structural and Functional change are apparent in advanced stages of disease, and at an individual level, detectable structural abnormality may precede Functional abnormality in some patients, whereas the converse is true in other patients. Although the exact nature of the ‘Structure–Function’ relationship in primary open-angle glaucoma is still the topic of scientific debate and the subject of continuing research, this article aims to provide the clinician with an understanding of the past concepts and contemporary thinking in relation to the Structure–Function relationship in primary open-angle glaucoma.
Chloe J Stackhouse - One of the best experts on this subject based on the ideXlab platform.
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Functional materials discovery using energy Structure Function maps
Nature, 2017Co-Authors: Angeles Pulido, Linjiang Chen, Tomasz Kaczorowski, Daniel Holden, Marc A Little, Samantha Y Chong, Benjamin J Slater, David P Mcmahon, Baltasar Bonillo, Chloe J StackhouseAbstract:Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their Structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal–organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal Structure prediction and property prediction to build energy–Structure–Function maps that describe the possible Structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the Structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular Structure as the only input. More generally, energy–Structure–Function maps could be used to guide the experimental discovery of materials with any target Function that can be calculated from predicted crystal Structures, such as electronic Structure or mechanical properties. Energy–Structure–Function maps that describe the possible Structures and properties of molecular crystals are developed, and these maps are used to guide the experimental discovery of porous materials with specific Functions. It can be difficult to predict and optimize the Structure and properties of crystalline molecular compounds without resorting to a 'wet' synthesis. Rather than crystallizing according to simple rules, their Structures result from the combination of many weak interactions. Computational calculations and screening can help, but are limited by the computational power available and often rely on prior knowledge and assumptions about the Structure. Here, Graeme Day and colleagues use Structure prediction maps to computationally scan various packings for small molecular crystals, and assign Functions, such as porosity or gas storage capacity, to each plausible Structure found. These energy–Structure–Function maps can guide synthetic work by ruling out seemingly promising Structures that are calculated to have undesirable properties. To validate the method, the authors synthesize a molecule that crystallizes as a porous solid with a record low density for a porous organic compound.
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Functional materials discovery using energy Structure Function maps
Nature, 2017Co-Authors: Angeles Pulido, Linjiang Chen, Tomasz Kaczorowski, Daniel Holden, Marc A Little, Samantha Y Chong, Benjamin J Slater, David P Mcmahon, Baltasar Bonillo, Chloe J StackhouseAbstract:Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their Structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal Structure prediction and property prediction to build energy-Structure-Function maps that describe the possible Structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the Structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular Structure as the only input. More generally, energy-Structure-Function maps could be used to guide the experimental discovery of materials with any target Function that can be calculated from predicted crystal Structures, such as electronic Structure or mechanical properties.
Bart Larsen - One of the best experts on this subject based on the ideXlab platform.
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development of Structure Function coupling in human brain networks during youth
Proceedings of the National Academy of Sciences of the United States of America, 2020Co-Authors: Graham L Baum, Zaixu Cui, David R Roalf, Rastko Ciric, Richard F Betzel, Bart LarsenAbstract:The protracted development of structural and Functional brain connectivity within distributed association networks coincides with improvements in higher-order cognitive processes such as executive Function. However, it remains unclear how white-matter architecture develops during youth to directly support coordinated neural activity. Here, we characterize the development of Structure–Function coupling using diffusion-weighted imaging and n-back Functional MRI data in a sample of 727 individuals (ages 8 to 23 y). We found that spatial variability in Structure–Function coupling aligned with cortical hierarchies of Functional specialization and evolutionary expansion. Furthermore, hierarchy-dependent age effects on Structure–Function coupling localized to transmodal cortex in both cross-sectional data and a subset of participants with longitudinal data (n = 294). Moreover, Structure–Function coupling in rostrolateral prefrontal cortex was associated with executive performance and partially mediated age-related improvements in executive Function. Together, these findings delineate a critical dimension of adolescent brain development, whereby the coupling between structural and Functional connectivity remodels to support Functional specialization and cognition.
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development of Structure Function coupling in human brain networks during youth
bioRxiv, 2019Co-Authors: Graham L Baum, Zaixu Cui, David R Roalf, Rastko Ciric, Richard F Betzel, Bart LarsenAbstract:ABSTRACT The protracted development of structural and Functional brain connectivity within distributed association networks coincides with improvements in higher-order cognitive processes such as working memory. However, it remains unclear how white matter architecture develops during youth to directly support coordinated neural activity. Here, we characterize the development of Structure-Function coupling using diffusion-weighted imaging and n-back fMRI data in a sample of 727 individuals (ages 8-23 years). We found that spatial variability in Structure-Function coupling aligned with cortical hierarchies of Functional specialization and evolutionary expansion. Furthermore, hierarchy-dependent age effects on Structure-Function coupling localized to transmodal cortex in both cross-sectional data and a subset of participants with longitudinal data (n=294). Moreover, Structure-Function coupling in rostrolateral prefrontal cortex was associated with executive performance, and partially mediated age-related improvements in executive Function. Together, these findings delineate a critical dimension of adolescent brain development, whereby the coupling between structural and Functional connectivity remodels to support Functional specialization and cognition.
Hendrik P N Scholl - One of the best experts on this subject based on the ideXlab platform.
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Structure Function correlation of the human central retina
PLOS ONE, 2010Co-Authors: Peter Charbel Issa, Frank G Holz, Hendrik P N Scholl, Eric Troeger, Robert Finger, R WilkeAbstract:Background The impact of retinal pathology detected by high-resolution imaging on vision remains largely unexplored. Therefore, the aim of the study was to achieve high-resolution Structure-Function correlation of the human macula in vivo. Methodology/Principal Findings To obtain high-resolution tomographic and topographic images of the macula spectral-domain optical coherence tomography (SD-OCT) and confocal scanning laser ophthalmoscopy (cSLO), respectively, were used. Functional mapping of the macula was obtained by using fundus-controlled microperimetry. Custom software allowed for co-registration of the fundus mapped microperimetry coordinates with both SD-OCT and cSLO datasets. The method was applied in a cross-sectional observational study of retinal diseases and in a clinical trial investigating the effectiveness of intravitreal ranibizumab in macular telangietasia type 2. There was a significant relationship between outer retinal thickness and retinal sensitivity (p<0.001) and neurodegeneration leaving less than about 50 µm of parafoveal outer retinal thickness completely abolished light sensitivity. In contrast, Functional preservation was found if neurodegeneration spared the photoreceptors, but caused quite extensive disruption of the inner retina. Longitudinal data revealed that small lesions affecting the photoreceptor layer typically precede Functional detection but later cause severe loss of light sensitivity. Ranibizumab was shown to be ineffective to prevent such Functional loss in macular telangietasia type 2. Conclusions/Significance Since there is a general need for efficient monitoring of the effectiveness of therapy in neurodegenerative diseases of the retina and since SD-OCT imaging is becoming more widely available, surrogate endpoints derived from such Structure-Function correlation may become highly relevant in future clinical trials.
Angeles Pulido - One of the best experts on this subject based on the ideXlab platform.
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Functional materials discovery using energy Structure Function maps
Nature, 2017Co-Authors: Angeles Pulido, Linjiang Chen, Tomasz Kaczorowski, Daniel Holden, Marc A Little, Samantha Y Chong, Benjamin J Slater, David P Mcmahon, Baltasar Bonillo, Chloe J StackhouseAbstract:Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their Structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal–organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal Structure prediction and property prediction to build energy–Structure–Function maps that describe the possible Structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the Structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular Structure as the only input. More generally, energy–Structure–Function maps could be used to guide the experimental discovery of materials with any target Function that can be calculated from predicted crystal Structures, such as electronic Structure or mechanical properties. Energy–Structure–Function maps that describe the possible Structures and properties of molecular crystals are developed, and these maps are used to guide the experimental discovery of porous materials with specific Functions. It can be difficult to predict and optimize the Structure and properties of crystalline molecular compounds without resorting to a 'wet' synthesis. Rather than crystallizing according to simple rules, their Structures result from the combination of many weak interactions. Computational calculations and screening can help, but are limited by the computational power available and often rely on prior knowledge and assumptions about the Structure. Here, Graeme Day and colleagues use Structure prediction maps to computationally scan various packings for small molecular crystals, and assign Functions, such as porosity or gas storage capacity, to each plausible Structure found. These energy–Structure–Function maps can guide synthetic work by ruling out seemingly promising Structures that are calculated to have undesirable properties. To validate the method, the authors synthesize a molecule that crystallizes as a porous solid with a record low density for a porous organic compound.
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Functional materials discovery using energy Structure Function maps
Nature, 2017Co-Authors: Angeles Pulido, Linjiang Chen, Tomasz Kaczorowski, Daniel Holden, Marc A Little, Samantha Y Chong, Benjamin J Slater, David P Mcmahon, Baltasar Bonillo, Chloe J StackhouseAbstract:Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their Structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal Structure prediction and property prediction to build energy-Structure-Function maps that describe the possible Structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the Structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular Structure as the only input. More generally, energy-Structure-Function maps could be used to guide the experimental discovery of materials with any target Function that can be calculated from predicted crystal Structures, such as electronic Structure or mechanical properties.
