| 1. |
|
|
| 2. |
|
|
| 3. |
- Bombarda, F., et al.
(författare)
-
Runaway electron beam control
- 2019
-
Ingår i: Plasma Physics and Controlled Fusion. - : IOP Publishing. - 1361-6587 .- 0741-3335. ; 61:1
-
Tidskriftsartikel (refereegranskat)
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Cirnaru, Maria-Daniela, et al.
(författare)
-
Unbiased identification of novel transcription factors in striatal compartmentation and striosome maturation.
- 2021
-
Ingår i: eLife. - 2050-084X. ; 10
-
Tidskriftsartikel (refereegranskat)abstract
- Many diseases are linked to dysregulation of the striatum. Striatal function depends on neuronal compartmentation into striosomes and matrix. Striatal projection neurons are GABAergic medium spiny neurons (MSNs), subtyped by selective expression of receptors, neuropeptides, and other gene families. Neurogenesis of the striosome and matrix occurs in separate waves, but the factors regulating compartmentation and neuronal differentiation are largely unidentified. We performed RNA- and ATAC-seq on sorted striosome and matrix cells at postnatal day 3, using the Nr4a1-EGFP striosome reporter mouse. Focusing on the striosome, we validated the localization and/or role of Irx1, Foxf2, Olig2, and Stat1/2 in the developing striosome and the in vivo enhancer function of a striosome-specific open chromatin region 4.4 Kb downstream of Olig2. These data provide novel tools to dissect and manipulate the networks regulating MSN compartmentation and differentiation, including in human iPSC-derived striatal neurons for disease modeling and drug discovery.
|
|
| 7. |
- Daneshjou, Roxana, et al.
(författare)
-
Working toward precision medicine : Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
- 2017
-
Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1182-1192
-
Tidskriftsartikel (refereegranskat)abstract
- Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
- Fan, Zhirui, et al.
(författare)
-
Nonlinear stiffness optimization with prescribed deformed geometry and loads
- 2022
-
Ingår i: Structural and Multidisciplinary Optimization. - : Springer Science and Business Media LLC. - 1615-147X .- 1615-1488. ; 65:2
-
Tidskriftsartikel (refereegranskat)abstract
- Optimization based on traditional forward motion analysis to ensure a prescribed load distribution on a deformed geometry is challenging, since the load distribution is highly coupled to the deformed geometry, boundary conditions, and the optimized material layout. In contrast to traditional forward motion analysis, the deformed configuration is prescribed in the inverse motion analysis, and the undeformed configuration is the outcome of the analysis. Consequently, the inverse motion analysis is able to define an exact deformed geometry. In the present study, we make use of this key advantage to design structures with both an exact deformed geometry and a prescribed load distribution. The objective in the optimization is to minimize a general function of the nodal displacement vector. To formulate a well-posed optimization problem, the design is regularized using the partial differential equation filter and the sensitivity analysis is based on the adjoint method. The computational model is developed for neo-Hookean hyper-elasticity and the balance equations are discretized using the finite element method. The resulting nonlinear equations are solved using a conventional Newton–Raphson scheme. In the numerical examples, a cantilever beam with an embedded perfect circular shape is first considered. Next, a 2D gasket-like structure is designed, and finally, we consider a 3D structure with contact-like boundary conditions. In these examples, the prescribed deformed geometry is subject to a distributed external force. The examples show that the deformed geometry and load distribution can be exactly prescribed through stiffness optimization based on the inverse motion analysis.
|
|
