| 1. |
- Kehoe, Laura, et al.
(författare)
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Make EU trade with Brazil sustainable
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Ayoglu, Burcu, et al.
(författare)
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Anoctamin 2 identified as an autoimmune target in multiple sclerosis
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences of the USA. - 0027-8424 .- 1091-6490. ; 113:8, s. 2188-2193
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system and also is regarded as an autoimmune condition. However, the antigenic targets of the autoimmune response in MS have not yet been deciphered. In an effort to mine the autoantibody repertoire within MS, we profiled 2,169 plasma samples from MS cases and population-based controls using bead arrays built with 384 human protein fragments selected from an initial screening with 11,520 antigens. Our data revealed prominently increased autoantibody reactivity against the chloride-channel protein anoctamin 2 (ANO2) in MS cases compared with controls. This finding was corroborated in independent assays with alternative protein constructs and by epitope mapping with peptides covering the identified region of ANO2. Additionally, we found a strong interaction between the presence of ANO2 autoantibodies and the HLA complex MS-associated DRB1*15 allele, reinforcing a potential role for ANO2 autoreactivity in MS etiopathogenesis. Furthermore, immunofluorescence analysis in human MS brain tissue showed ANO2 expression as small cellular aggregates near and inside MS lesions. Thus this study represents one of the largest efforts to characterize the autoantibody repertoire within MS. The findings presented here demonstrate that an ANO2 autoimmune subphenotype may exist in MS and lay the groundwork for further studies focusing on the pathogenic role of ANO2 autoantibodies in MS.
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| 3. |
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| 4. |
- Bedri, Sahl Khalid, et al.
(författare)
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Plasma protein profiling reveals candidate biomarkers for multiple sclerosis treatment
- 2019
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 14:5
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sclerosis (MS) treatment options have improved significantly over the past decades, but the consequences of MS can still be devastating and the needs for monitoring treatment surveillance are considerable. In the current study we used affinity proteomics technology to identify potential biomarkers which could ultimately be used to as facilitate treatment decisions. We profiled the intra-individual changes in the levels of 59 target proteins using an antibody suspension bead array in serial plasma samples from 44 MS patients during treatment with natalizumab followed by fingolimod. Nine proteins showed decreasing plasma levels during natalizumab treatment, with PEBP1 and RTN3 displaying the most significant changes. Protein levels remained stable during fingolimod treatment for both proteins. The decreasing PEBP1 levels during natalizumab treatment could be validated using ELISA and replicated in an independent cohort. These results support the use of this technology as a high throughput method of identifying potentially useful biomarkers of MS treatment.
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| 5. |
- Bronge, Mattias, et al.
(författare)
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Identification of four novel T cell autoantigens and personal autoreactive profiles in multiple sclerosis
- 2022
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Ingår i: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 8:17
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS), in which pathological T cells, likely autoimmune, play a key role. Despite its central importance, the autoantigen repertoire remains largely uncharacterized. Using a novel in vitro antigen delivery method combined with the Human Protein Atlas library, we screened for T cell autoreactivity against 63 CNS-expressed proteins. We identified four previously unreported autoantigens in MS: fatty acid-binding protein 7, prokineticin-2, reticulon-3, and synaptosomal-associated protein 91, which were verified to induce interferon-gamma responses in MS in two cohorts. Autoreactive profiles were heterogeneous, and reactivity to several autoantigens was MS-selective. Autoreactive T cells were predominantly CD4(+) and human leukocyte antigen-DR restricted. Mouse immunization induced antigen-specific responses and CNS leukocyte infiltration. This represents one of the largest systematic efforts to date in the search for MS autoantigens, demonstrates the heterogeneity of autoreactive profiles, and highlights promising targets for future diagnostic tools and immunomodulatory therapies in MS.
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| 6. |
- Dersjö, Tomas, et al.
(författare)
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A directional surrogate model tailored for efficient reliability based design optimization
- 2012
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Reliability based design optimization (RBDO) aims at minimizing an objective while constraining the failure probability of structural components. Due to the iterative nature of both the minimization and the failure probability validation, there is considerable computational effort associated with it. In this paper, a computationally inexpensive approach for RBDO is presented. The key contribution is the directional surrogate model and its associated advantages; a sound balance between accuracy and computational cost, including the possibility to fit model coefficients based on an optimal experiment design, high fidelity modeling of representative structural responses, treatment of multiple constraints without added computational cost, and straightforward sequential linear programming implementation. The directional surrogate model is of power type with nonlinear behaviour only in the gradient direction, thus balancing accuracy and computational cost. Moreover, information from prior iterations are used in every iteration in a weighted least squares optimization. When benchmarked against existing approaches from the literature using a well known reference problem, it is shown to be highly efficient. It also shows promising stability and convergence rate for additional challenging problems to which it has been applied.
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| 7. |
- Dersjö, Tomas, et al.
(författare)
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Efficient design of experiments for structural optimization using significance screening
- 2012
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Ingår i: Structural and multidisciplinary optimization (Print). - : Springer Science and Business Media LLC. - 1615-147X .- 1615-1488. ; 45:2, s. 185-196
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Tidskriftsartikel (refereegranskat)abstract
- When performing structural optimization of large scale engineering problems, the choice of experiment design is important. However, classical experiment designs are developed to deal with undesired but inevitable scatter and are thus not ideal for sampling of deterministic computational responses. In this paper, a novel screening and design of computer experiments algorithm is presented. It is based on the concept of orthogonal design variable significances and is applicable for problems where design variables do not simultaneously have a significant influence on any of the constraints. The algorithm presented uses significance orthogonality to combine several one-factor-at-a-time experiments in one several-factors-at-a-time experiment. The procedure results in a reduced experiment design matrix. In the reduced experiment design, each variable is varied exactly once but several variables may be varied simultaneously, if their significances with respect to the constraints are orthogonal. Moreover, a measure of influence, as well as an influence significance threshold, is defined. In applications, the value of the threshold is left up to the engineer. To assist in this choice, a relation between model simplification, expressed in terms of the significance threshold, and computational cost is established in a screening. The relation between efficiency and loss of accuracy for the proposed approach is discussed and demonstrated. For two solid mechanics type problems studied herein, the necessary number of simulations could be reduced by 25% and 64%, respectively, with negligible losses in accuracy.
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| 8. |
- Dersjö, Tomas, 1981-
(författare)
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Methods for reliability based design optimization of structural components
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cost and quality are key properties of a product, possibly even the two most important. Onedefinition of quality is fitness for purpose. Load-bearing products, i.e. structural components,loose their fitness for purpose if they fail. Thus, the ability to withstand failure is a fundamentalmeasure of quality for structural components. Reliability based design optimization(RBDO) is an approach for development of structural components which aims to minimizethe cost while constraining the probability of failure. However, the computational effort ofan RBDO applied to large-scale engineering problems has prohibited it from employment inindustrial applications. This thesis presents methods for computationally efficient RBDO.A review of the work presented on RBDO algorithms reveals that three constituentsof an RBDO algorithm has rendered significant attention; i ) the solution strategy for andnumerical treatment of the probabilistic constraints, ii ) the surrogate model, and iii) theexperiment design. A surrogate model is ”a model of a model”, i.e. a computationally cheapapproximation of a physics-based but computationally expensive computer model. It is fittedto responses from the physics-motivated model obtained via a thought-through combinationof experiments called an experiment design.In Paper A, the general algorithm for RBDO employed in this work, including the sequentialapproximation procedure used to treat the probabilistic constraints, is laid out. A singleconstraint approximation point (CAP) is used to save computational effort with acceptablelosses in accuracy. The approach is used to optimize a truck component and incorporatesthe effect that production related design variables like machining and shot peening have onfatigue life.The focus in Paper B is on experiment design. An algorithm employed to construct anovel experiment design for problems with multiple constraints is presented. It is based onan initial screening and uses the specific problem structure to combine one-factor-at-a-timeexperiments to a several-factors-at-a-time experiment design which reduces computationaleffort.In Paper C, a surrogate model tailored for RBDO is introduced. It is motivated by appliedsolid mechanics considerations and the use of the first order reliability method to evaluate theprobabilistic constraint. An optimal CAP is furthermore deduced from the surrogate model.In Paper D, the paradigm to use sets of experiments rather than one experiment at atime is challenged. A new procedure called experiments on demand (EoD) is presented. TheEoD procedure utilizes the core of RBDO to quantify the demand for new experiments andaugments it by a D-optimality criterion for added robustness and numerical stability.
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| 9. |
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| 10. |
- Dersjö, Tomas, et al.
(författare)
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Reliability Based Design Optimization Using a Single Constraint Approximation Point
- 2011
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Ingår i: Journal of mechanical design (1990). - : ASME International. - 1050-0472 .- 1528-9001. ; 133:3, s. 031006-
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Tidskriftsartikel (refereegranskat)abstract
- The computational effort for reliability based design optimization (RBDO) is no longer prohibitive even for detailed studies of mechanical integrity. The sequential approximation RBDO formulation and the use of surrogate models have greatly reduced the amount of computations necessary. In RBDO, the surrogate models need to be most accurate in the proximity of the most probable point. Thus, for multiply constrained problems, such as fatigue design problems, where each finite element (FE)-model node constitutes a constraint, the computational effort may still be considerable if separate experiments are used to fit each constraint surrogate model. This paper presents an RBDO algorithm that uses a single constraint approximation point (CAP) as a starting point for the experiments utilized to establish all surrogate models, thus reducing the computational effort to that of a single constraint problem. Examples of different complexities from solid mechanics applications are used to present the accuracy and versatility of the proposed method. In the studied examples, the ratio of the computational effort (in terms of FE-solver calls) between a conventional method and the single CAP algorithm was approximately equal to the number of constraints and the introduced error was small. Furthermore, the CAP-based RBDO is shown to be capable of handling over 10,000 constraints and even an intermittent remeshing. Also, the benefit of considering other objectives than volume (mass) is shown through a cost optimization of a truck component. In the optimization, fatigue-specific procedures, such as shot peening and machining to reduce surface roughness, are included in the cost as well as in the constraints.
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