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- Rise, H. H., et al.
(författare)
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Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study
- 2022
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Ingår i: Neuroimage-Clinical. - : Elsevier BV. - 2213-1582. ; 35
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objectives: Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker. Methods: MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient's white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run. Results: rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 x 10(-5)), and longitudinal changes in NfL (t =-2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80-0.83, p = 0.41-0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001). Discussion: In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.
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| 4. |
- Brune, S., et al.
(författare)
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Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis
- 2022
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Ingår i: Multiple Sclerosis Journal. - : SAGE Publications. - 1352-4585 .- 1477-0970. ; 28:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL to predict outcomes in real-world MS cohorts requires further validation. Objective: The aim of the study is to investigate the associations of sNfL concentration, magnetic resonance imaging (MRI) and retinal optical coherence tomography (OCT) markers with disease worsening in a longitudinal European multicentre MS cohort. Methods: MS patients (n = 309) were prospectively enrolled at four centres and re-examined after 2 years (n = 226). NfL concentration was measured by single molecule array assay in serum. The patients' phenotypes were thoroughly characterized with clinical examination, retinal OCT and MRI brain scans. The primary outcome was disease worsening at median 2-year follow-up. Results: Patients with high sNfL concentrations (> 8 pg/mL) at baseline had increased risk of disease worsening at median 2-year follow-up (odds ratio (95% confidence interval) = 2.8 (1.5-5.3), p = 0.001). We found no significant associations of MRI or OCT measures at baseline with risk of disease worsening. Conclusion: Serum NfL concentration was the only factor associated with disease worsening, indicating that sNfL is a useful biomarker in MS that might be relevant in a clinical setting.
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| 5. |
- Johnson, Calvin W., et al.
(författare)
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White paper: From bound states to the continuum
- 2020
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Ingår i: Journal of Physics G: Nuclear and Particle Physics. - : IOP Publishing. - 0954-3899 .- 1361-6471. ; 47:12
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Forskningsöversikt (refereegranskat)abstract
- This white paper reports on the discussions of the 2018 Facility for Rare Isotope Beams Theory Alliance (FRIB-TA) topical program ‘From bound states to the continuum: Connecting bound state calculations with scattering and reaction theory’. One of the biggest and most important frontiers in nuclear theory today is to construct better and stronger bridges between bound state calculations and calculations in the continuum, especially scattering and reaction theory, as well as teasing out the influence of the continuum on states near threshold. This is particularly challenging as many-body structure calculations typically use a bound state basis, while reaction calculations more commonly utilize few-body continuum approaches. The many-body bound state and few-body continuum methods use different language and emphasize different properties. To build better foundations for these bridges, we present an overview of several bound state and continuum methods and, where possible, point to current and possible future connections.
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| 6. |
- Botteghi, N., et al.
(författare)
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Low dimensional state representation learning with reward-shaped priors
- 2020
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728188089 ; , s. 3736-3743
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Konferensbidrag (refereegranskat)abstract
- Reinforcement Learning has been able to solve many complicated robotics tasks without any need for feature engineering in an end-to-end fashion. However, learning the optimal policy directly from the sensory inputs, i.e the observations, often requires processing and storage of a huge amount of data. In the context of robotics, the cost of data from real robotics hardware is usually very high, thus solutions that achieve high sample-efficiency are needed. We propose a method that aims at learning a mapping from the observations into a lower-dimensional state space. This mapping is learned with unsupervised learning using loss functions shaped to incorporate prior knowledge of the environment and the task. Using the samples from the state space, the optimal policy is quickly and efficiently learned. We test the method on several mobile robot navigation tasks in a simulation environment and also on a real robot. A video of our experiments can be found at: https://youtu.be/dgWxmfSv95U.
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| 7. |
- Botteghi, N., et al.
(författare)
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Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces
- 2021
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665417150 ; , s. 190-197
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Konferensbidrag (refereegranskat)abstract
- Reinforcement learning algorithms have proven to be capable of solving complicated robotics tasks in an end-to-end fashion without any need for hand-crafted features or policies. Especially in the context of robotics, in which the cost of real-world data is usually extremely high, Reinforcement Learning solutions achieving high sample efficiency are needed. In this paper, we propose a framework combining the learning of a low-dimensional state representation, from high-dimensional observations coming from the robot's raw sensory readings, with the learning of the optimal policy, given the learned state representation. We evaluate our framework in the context of mobile robot navigation in the case of continuous state and action spaces. Moreover, we study the problem of transferring what learned in the simulated virtual environment to the real robot without further retraining using real-world data in the presence of visual and depth distractors, such as lighting changes and moving obstacles. A video of our experiments can be found at: https://youtu.be/rUdGPKr2Wuo.
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| 8. |
- Botteghi, N., et al.
(författare)
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Reinforcement learning helps slam : Learning to build maps
- 2020
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Ingår i: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. - : International Society for Photogrammetry and Remote Sensing. ; , s. 329-336
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Konferensbidrag (refereegranskat)abstract
- In this research, we investigate the use of Reinforcement Learning (RL) for an effective and robust solution for exploring unknown and indoor environments and reconstructing their maps. We benefit from a Simultaneous Localization and Mapping (SLAM) algorithm for real-time robot localization and mapping. Three different reward functions are compared and tested in different environments with growing complexity. The performances of the three different RL-based path planners are assessed not only on the training environments, but also on an a priori unseen environment to test the generalization properties of the policies. The results indicate that RL-based planners trained to maximize the coverage of the map are able to consistently explore and construct the maps of different indoor environments.
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| 9. |
- Einarsdottir, Sigrun, et al.
(författare)
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Vaccination against tick-borne encephalitis (TBE) after autologous and allogeneic stem cell transplantation
- 2021
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Ingår i: Vaccine. - : Elsevier BV. - 0264-410X .- 1873-2518. ; 39:7, s. 1035-1038
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Our aim was to assess response and side effects of 4 doses of TBE vaccine to patients (pts) after allo- and autologous stem cell transplantation (SCT). PATIENTS: Included were 104 pts with leukaemia, myeloma and lymphoma, median age 61 yrs. METHODS: Vaccine (FSME-Immun (R)) was given at 9, 10, 12, and 21 months post-transplant. Serum samples were obtained before and after vaccinations. Healthy controls (n = 27) received 3 vaccinations. Assessments of TBE specific IgG antibodies were performed by Enzygnost anti-TBE ELISA test (Siemens, Sweden). Results: Antibody levels (>12 U/mL; "seropositivity") were seen in 77% and 80% of pts after allo- and autoSCT; IgG levels; 89 vs 94 U/mL. Ongoing chronic GvHD and immunosuppression (n = 29) was associated with sero-negativity in the last sample (p = 0.007). All controls (n = 27) developed protective antibody levels. Conclusions: TBE vaccination was safe, and 4 doses starting 9 months post-SCT, induced seropositivity in a vast majority of pts. (C) 2021 Elsevier Ltd. All rights reserved.
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