| 1. |
- Colomb-Delsuc, Mathieu, et al.
(author)
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Assessment of the percentage of full recombinant adeno-associated virus particles in a gene therapy drug using CryoTEM
- 2022
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17:6
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Journal article (peer-reviewed)abstract
- In spite of continuous development of gene therapy vectors with thousands of drug candidates in clinical drug trials there are only a small number approved on the market today stressing the need to have characterization methods to assist in the validation of the drug development process. The level of packaging of the vector capsids appears to play a critical role in immunogenicity, hence an objective quantitative method assessing the content of particles containing a genome is an essential quality measurement. As transmission electron microscopy (TEM) allows direct visualization of the particles present in a specimen, it naturally seems as the most intuitive method of choice for characterizing recombinant adeno-associated virus (rAAV) particle packaging. Negative stain TEM (nsTEM) is an established characterization method for analysing the packaging of viral vectors. It has however shown limitations in terms of reliability. To overcome this drawback, we propose an analytical method based on CryoTEM that unambiguously and robustly determines the percentage of filled particles in an rAAV sample. In addition, we show that at a fixed number of vector particles the portion of filled particles correlates well with the potency of the drug. The method has been validated according to the ICH Q2 (R1) guidelines and the components investigated during the validation are presented in this study. The reliability of nsTEM as a method for the assessment of filled particles is also investigated along with a discussion about the origin of the observed variability of this method.
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| 3. |
- Kylberg, Gustaf, et al.
(author)
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Local Intensity and PCA Based Detection of Virus Particle Candidates in Transmission Electron Microscopy Images
- 2009
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In: Proc. 6th International Symposium on Image and Signal Processing and Analysis. - Piscataway, NJ : IEEE. - 9789531841351 ; , s. 426-431
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Conference paper (peer-reviewed)abstract
- We present a general method using local intensity informationand PCA to detect objects characterized onlyby that they differ from their surroundings. We apply ourmethod to the problem of automatically detecting virus particlecandidates in transmission electron microscopy images.Viruses have very different shapes and sizes, manyspecies are spherical whereas others are highly pleomorphic.To detect any kind of virus particles in electron microscopyimages it is therefore necessary to use a methodnot restricted to detection of a specific shape. The methodproposed here uses only one input parameter, the approximatevirus thickness, which is a conserved feature withina virus species. It is capable to detect virus particles ofvery varying shapes. Results on images with highly texturedbackground of several different virus species are presented.
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| 4. |
- Ryner, Martin, et al.
(author)
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Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
- 2023
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In: Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. - : Neural Information Processing Systems Foundation.
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Conference paper (peer-reviewed)abstract
- This paper presents a framework for computing the Gromov-Wasserstein problem between two sets of points in low dimensional spaces, where the discrepancy is the squared Euclidean norm. The Gromov-Wasserstein problem is a generalization of the optimal transport problem that finds the assignment between two sets preserving pairwise distances as much as possible. This can be used to quantify the similarity between two formations or shapes, a common problem in AI and machine learning. The problem can be formulated as a Quadratic Assignment Problem (QAP), which is in general computationally intractable even for small problems. Our framework addresses this challenge by reformulating the QAP as an optimization problem with a low-dimensional domain, leveraging the fact that the problem can be expressed as a concave quadratic optimization problem with low rank. The method scales well with the number of points, and it can be used to find the global solution for large-scale problems with thousands of points. We compare the computational complexity of our approach with state-of-the-art methods on synthetic problems and apply it to a near-symmetrical problem which is of particular interest in computational biology.
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| 5. |
- Ryner, Martin, et al.
(author)
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Identification and classification of human cytomegalovirus capsids in textured electron micrographs using deformed template matching
- 2006
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In: Virology Journal. - : Springer Science and Business Media LLC. - 1743-422X. ; 3
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Journal article (peer-reviewed)abstract
- Background: Characterization of the structural morphology of virus particles in electron micrographs is a complex task, but desirable in connection with investigation of the maturation process and detection of changes in viral particle morphology in response to the effect of a mutation or antiviral drugs being applied. Therefore, we have here developed a procedure for describing and classifying virus particle forms in electron micrographs, based on determination of the invariant characteristics of the projection of a given virus structure. The template for the virus particle is created on the basis of information obtained from a small training set of electron micrographs and is then employed to classify and quantify similar structures of interest in an unlimited number of electron micrographs by a process of correlation. Results: Practical application of the method is demonstrated by the ability to locate three diverse classes of virus particles in transmission electron micrographs of fibroblasts infected with human cytomegalovirus. These results show that fast screening of the total number of viral structures at different stages of maturation in a large set of electron micrographs, a task that is otherwise both time-consuming and tedious for the expert, can be accomplished rapidly and reliably with our automated procedure. Using linear deformation analysis, this novel algorithm described here can handle capsid variations such as ellipticity and furthermore allows evaluation of properties such as the size and orientation of a virus particle. Conclusion: Our methodological procedure represents a promising objective tool for comparative studies of the intracellular assembly processes of virus particles using electron microscopy in combination with our digitized image analysis tool. An automated method for sorting and classifying virus particles at different stages of maturation will enable us to quantify virus production in all stages of the virus maturation process, not only count the number of infectious particles released from un infected cell.
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| 7. |
- Sintorn, Ida-Maria, 1976-, et al.
(author)
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Facilitating Ultrastructural Pathology through Automated Imaging and Analysis
- 2019
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In: Journal of Pathology Informatics. - : Elsevier. - 2229-5089 .- 2153-3539. ; 10:1, s. 38-39
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Journal article (other academic/artistic)abstract
- Transmission electron microscopy (TEM) is an important diagnostic tool for analyzing human tissue at the nm scale. It is the only option, or gold standard, for diagnosing several disorders e.g. cilia and renal diseases, rare cancers etc. However, conventional TEM microscopes are highly manual, technically complex and a special environment is required to house the bulky and sensitive machines. Interpretation of information is subjective, time consuming, and relies on a high level of expertise which, unfortunately, is rare for this specialty within pathology. Here, we present methods and results from an ongoing project with the goal to develop a smart and easy to use platform for ultrastructural pathologic diagnoses. The platform is based on the recently developed MiniTEM instrument, a highly automated table-top TEM. In the project we develop image analysis methods for guided as well as fully automated search and analysis of structures of interest. In addition we enrich MiniTEM with an integrated database for convenient image handling and traceability. These points are identified by user representatives as crucial for creating a cost-effective diagnostic platform. We will show strategies and results for using image analysis and machine learning for automated search for objects/regions of interest at low magnification as well as combining multiple object instances acquired at high magnification to enhance nm details necessary for correct diagnosis. This will be exemplified for diagnosing primary cilia dyskinesia and renal disorders. The automation in imaging and analysis within the platform is a big step towards digital ultrapathology.
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