| 1. |
- Bonvicini, Gillian
(author)
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Harnessing the molecular Trojan horse : Evaluating properties of preclinical Aβ immunoPET radioligands for optimized brain delivery via the transferrin receptor
- 2023
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Doctoral thesis (other academic/artistic)abstract
- With high specificity and selectivity to targets, antibodies are prime candidates for positron emission tomography (PET) radioligands. They do not passively cross the blood-brain barrier which has hindered their development for imaging intrabrain targets, like amyloid-β (Aβ) in Alzheimer’s disease. The molecular Trojan horse strategy with antibodies that bind to both the transferrin receptor (TfR) and an intrabrain target improves brain delivery of therapeutic antibodies. However, therapeutic antibodies are typically dosed substantially higher than antibody-based PET (immunoPET) radioligands.This thesis evaluated the effects of affinity, valency, and dose on the brain delivery of preclinical Aβ immunoPET radioligands via the TfR.Paper I investigated whether immunoPET with TfR-mediated brain delivery could image Aβ with similar sensitivity in rats as it has in mice. To our knowledge, this was the first time TfR-hijacking to deliver a radioligand to image Aβ was successfully demonstrated in rats; suggesting this strategy could eventually be translated to clinics.Affinity to TfR influences therapeutic delivery to the brain. In Paper II, we compared four Biacore setups and one on-cell assay for determining apparent affinities to the TfR. Absolute affinity determination was challenging since several assay conditions impacted the kinetic parameters. A directional TfR capture in Biacore may be optimal since it determined kinetic parameters while mimicking in vivo receptor conditions. Papers I and III investigated how antibody affinity affects brain delivery at tracer doses and indicated that stronger TfR affinity yielded higher brain delivery. The antibodies in Paper III lacked effector function. The resulting pharmacokinetic profiles in Aβ pathology-presenting mice indicated this may have improved target accumulation of the immunoPET radioligand.In Paper IV, we screened a novel library of monovalent and bivalent affinity variants of the anti-mouse TfR antibody, 8D3. A pair of monovalent and bivalent antibodies with an apparent affinity of 10 nM was identified and evaluated in vivo. Monovalent binding yielded higher brain uptake at a tracer dose but whether bivalent binding steered the antibody towards lysosomal degradation was unclear.In conclusion, monovalency, high affinity binding, and ablated effector function are likely beneficial properties for TfR-mediated brain delivery of an immunoPET radioligand at a tracer dose.
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| 2. |
- Feng, Louis, et al.
(author)
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Anisotropic Noise Samples
- 2008
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In: IEEE Transactions on Visualization and Computer Graphics. - 1077-2626 .- 1941-0506. ; 14:2, s. 342-354
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Journal article (peer-reviewed)abstract
- We present a practical approach to generate stochastic anisotropic samples with Poisson-disk characteristic over a two-dimensional domain. In contrast to isotropic samples, we understand anisotropic samples as non-overlapping ellipses whose size and density match a given anisotropic metric. Anisotropic noise samples are useful for many visualization and graphics applications. The spot samples can be used as input for texture generation, e.g., line integral convolution (LIC), but can also be used directly for visualization. The definition of the spot samples using a metric tensor makes them especially suitable for the visualization of tensor fields that can be translated into a metric. Our work combines ideas from sampling theory and mesh generation. To generate these samples with the desired properties we construct a first set of non-overlapping ellipses whose distribution closely matches the underlying metric. This set of samples is used as input for a generalized anisotropic Lloyd relaxation to distribute noise samples more evenly. Instead of computing the Voronoi tessellation explicitly, we introduce a discrete approach which combines the Voronoi cell and centroid computation in one step. Our method supports automatic packing of the elliptical samples, resulting in textures similar to those generated by anisotropic reaction-diffusion methods. We use Fourier analysis tools for quality measurement of uniformly distributed samples. The resulting samples have nice sampling properties, for example, they satisfy a blue noise property where low frequencies in the power spectrum are reduced to a minimum.
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| 3. |
- Feng, Louis, et al.
(author)
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Dense Glyph Sampling for Visualization
- 2008
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In: Visualization and Processing of Tensor Fields: Advances and Perspectives. - Berlin, Heidelberg : Springer. - 9783540883777 - 9783540883784 ; , s. 177-193
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Book chapter (peer-reviewed)abstract
- We present a simple and efficient approach to generate a dense set of anisotropic, spatially varying glyphs over a two-dimensional domain. Such glyph samples are useful for many visualization and graphics applications. The glyphs are embedded in a set of nonoverlapping ellipses whose size and density match a given anisotropic metric. An additional parameter controls the arrangement of the ellipses on lines, which can be favorable for some applications, for example, vector fields and distracting for others. To generate samples with the desired properties, we combine ideas from sampling theory and mesh generation. We start with constructing a first set of nonoverlapping ellipses whose distribution closely matches the underlying metric. This set of samples is used as input for a generalized anisotropic Lloyd relaxation to distribute samples more evenly.
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| 4. |
- Hotz, Ingrid, et al.
(author)
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Physically Based Methods for Tensor Field Visualization
- 2004
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Conference paper (peer-reviewed)abstract
- The physical interpretation of mathematical features of tensor fields is highly application-specific. Existing visualization methods for tensor fields only cover a fraction of the broad application areas. We present a visualization method tailored specifically to the class of tensor field exhibiting properties similar to stress and strain tensors, which are commonly encountered in geomechanics. Our technique is a global method that represents the physical meaning of these tensor fields with their central features: regions of compression or expansion. The method is based on two steps: first, we define a positive definite metric, with the same topological structure as the tensor field; second, we visualize the resulting metric. The eigenvector fields are represented using a texture-based approach resembling line integral convolution (LIC) methods. The eigenvalues of the metric are encoded in free parameters of the texture definition. Our method supports an intuitive distinction between positive and negative eigenvalues. We have applied our method to synthetic and some standard data sets, and "real" data from earth science and mechanical engineering application.
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| 5. |
- Hotz, Ingrid, et al.
(author)
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Tensor Field Visualization Using a Metric Interpretation
- 2006
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In: Visualization and Image Processing of Tensor Fields. - Berlin, Heidelberg : Springer. - 9783540250326 - 9783540312727 ; , s. 269-281
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Book chapter (peer-reviewed)abstract
- This chapter introduces a visualization method specifically tailored to the class of tensor fields with properties similar to stress and strain tensors. Such tensor fields play an important role in many application areas such as structure mechanics or solid state physics. The presented technique is a global method that represents the physical meaning of these tensor fields with their central features: regions of compression or expansion. The method consists of two steps: first, the tensor field is interpreted as a distortion of a flat metric with the same topological structure; second, the resulting metric is visualized using a texture-based approach. The method supports an intuitive distinction between positive and negative eigenvalues.
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| 6. |
- Hotz, Ingrid, et al.
(author)
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Tensor-fields Visualization using a Fabric like Texture on Arbitrary two-dimensional Surfaces
- 2009
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In: Mathematical Foundations of Scientific Visualization. - Berlin, Heidelberg : Springer. - 9783540250760 - 9783540499268 ; , s. 139-155
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Book chapter (peer-reviewed)abstract
- We present a visualization method that for three-dimensional tensor fields based on the idea of a stretched or compressed piece of fabric used as a “texture” for a two-dimensional surfaces. The texture parameters as the fabric density reflect the physical properties of the tensor field. This method is especially appropriate for the visualization of stress and strain tensor fields that play an important role in many application areas including mechanics and solid state physics. To allow an investigation of a three-dimensional field we use a scalar field that defines a one-parameter family of iso-surfaces controlled by their iso-value. This scalar-field can be a “connected” scalar field, for example, pressure or an additional scalar field representing some symmetry or inherent structure of the dataset. Texture generation consists basically of three steps. The first is the transformation of the tensor field into a positive definite metric. The second step is the generation of an input for the final texture generation using line integral convolution (LIC). This input image consists of “bubbles” whose shape and density are controlled by the eigenvalues of the tensor field. This spot image incorporates the entire information content defined by the three eigenvalue fields. Convolving this input texture in direction of the eigenvector fields provides a continuous representation. This method supports an intuitive distinction between positive and negative eigenvalues and supports the additional visualization of a connected scalar field.
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| 7. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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