| 1. |
- Algaba, Juan-Carlos, et al.
(författare)
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Broadband Multi-wavelength Properties of M87 during the 2017 Event Horizon Telescope Campaign
- 2021
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Ingår i: Astrophysical Journal Letters. - : American Astronomical Society. - 2041-8213 .- 2041-8205. ; 911:1
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Forskningsöversikt (refereegranskat)abstract
- In 2017, the Event Horizon Telescope (EHT) Collaboration succeeded in capturing the first direct image of the center of the M87 galaxy. The asymmetric ring morphology and size are consistent with theoretical expectations for a weakly accreting supermassive black hole of mass ∼6.5 × 109 M o˙. The EHTC also partnered with several international facilities in space and on the ground, to arrange an extensive, quasi-simultaneous multi-wavelength campaign. This Letter presents the results and analysis of this campaign, as well as the multi-wavelength data as a legacy data repository. We captured M87 in a historically low state, and the core flux dominates over HST-1 at high energies, making it possible to combine core flux constraints with the more spatially precise very long baseline interferometry data. We present the most complete simultaneous multi-wavelength spectrum of the active nucleus to date, and discuss the complexity and caveats of combining data from different spatial scales into one broadband spectrum. We apply two heuristic, isotropic leptonic single-zone models to provide insight into the basic source properties, but conclude that a structured jet is necessary to explain M87's spectrum. We can exclude that the simultaneous γ-ray emission is produced via inverse Compton emission in the same region producing the EHT mm-band emission, and further conclude that the γ-rays can only be produced in the inner jets (inward of HST-1) if there are strongly particle-dominated regions. Direct synchrotron emission from accelerated protons and secondaries cannot yet be excluded.
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| 2. |
- Aartsen, M. G., et al.
(författare)
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Very high-energy gamma-ray follow-up program using neutrino triggers from IceCube
- 2016
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- We describe and report the status of a neutrino-triggered program in IceCube that generates real-time alerts for gamma-ray follow-up observations by atmospheric-Cherenkov telescopes (MAGIC and VERITAS). While IceCube is capable of monitoring the whole sky continuously, high-energy gamma-ray telescopes have restricted fields of view and in general are unlikely to be observing a potential neutrino-flaring source at the time such neutrinos are recorded. The use of neutrino-triggered alerts thus aims at increasing the availability of simultaneous multi-messenger data during potential neutrino flaring activity, which can increase the discovery potential and constrain the phenomenological interpretation of the high-energy emission of selected source classes (e. g. blazars). The requirements of a fast and stable online analysis of potential neutrino signals and its operation are presented, along with first results of the program operating between 14 March 2012 and 31 December 2015.
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| 3. |
- Ahnen, M. L., et al.
(författare)
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Limits to dark matter annihilation cross-section from a combined analysis of MAGIC and Fermi-LAT observations of dwarf satellite galaxies
- 2016
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Ingår i: Journal of Cosmology and Astroparticle Physics. - : IOP Publishing. - 1475-7516. ; :2
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Tidskriftsartikel (refereegranskat)abstract
- We present the first joint analysis of gamma-ray data from the MAGIC Cherenkov telescopes and the Fermi Large Area Telescope (LAT) to search for gamma-ray signals from dark matter annihilation in dwarf satellite galaxies. We combine 158 hours of Segue 1 observations with MAGIC with 6-year observations of 15 dwarf satellite galaxies by the Fermi-LAT. We obtain limits on the annihilation cross-section for dark matter particle masses between 10 GeV and 100 TeV - the widest mass range ever explored by a single gamma-ray analysis. These limits improve on previously published Fermi-LAT and MAGIC results by up to a factor of two at certain masses. Our new inclusive analysis approach is completely generic and can be used to perform a global, sensitivity-optimized dark matter search by combining data from present and future gamma-ray and neutrino detectors.
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| 4. |
- Bonkhoff, Anna K, et al.
(författare)
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The relevance of rich club regions for functional outcome post-stroke is enhanced in women.
- 2023
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Ingår i: Human brain mapping. - : Wiley. - 1097-0193 .- 1065-9471. ; 44:4, s. 1579-1592
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS>2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.
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| 5. |
- Bourached, Anthony, et al.
(författare)
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Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity
- 2023
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Ingår i: BRAIN COMMUNICATIONS. - 2632-1297. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 105-107 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller. Such stroke outcome predictions however could be particularly instrumental in guiding acute clinical and rehabilitation care decisions. We here compared the capacities of classically used linear and novel deep learning algorithms in their prediction of stroke severity. Our analyses relied on a total of 1430 patients assembled from the MRI-Genetics Interface Exploration collaboration and a Massachusetts General Hospital-based study. The outcome of interest was National Institutes of Health Stroke Scale-based stroke severity in the acute phase after ischaemic stroke onset, which we predict by means of MRI-derived lesion location. We automatically derived lesion segmentations from diffusion-weighted clinical MRI scans, performed spatial normalization and included a principal component analysis step, retaining 95% of the variance of the original data. We then repeatedly separated a train, validation and test set to investigate the effects of sample size; we subsampled the train set to 100, 300 and 900 and trained the algorithms to predict the stroke severity score for each sample size with regularized linear regression and an eight-layered neural network. We selected hyperparameters on the validation set. We evaluated model performance based on the explained variance (R2) in the test set. While linear regression performed significantly better for a sample size of 100 patients, deep learning started to significantly outperform linear regression when trained on 900 patients. Average prediction performance improved by similar to 20% when increasing the sample size 9x [maximum for 100 patients: 0.279 +/- 0.005 (R2, 95% confidence interval), 900 patients: 0.337 +/- 0.006]. In summary, for sample sizes of 900 patients, deep learning showed a higher prediction performance than typically employed linear methods. These findings suggest the existence of non-linear relationships between lesion location and stroke severity that can be utilized for an improved prediction performance for larger sample sizes. Bourached et al. contrast linear and deep learning-based algorithms in their prediction performances of stroke severity depending on the training set sample sizes. They find that linear regression outperforms deep learning-based algorithms for smaller training samples comprising lesion location information of 100 patients, while deep learning excels in the case of larger samples (N = 900).
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| 6. |
- Bretzner, Martin, et al.
(författare)
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Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke.
- 2023
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Ingår i: Neurology. - 1526-632X .- 0028-3878. ; 100:8
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Tidskriftsartikel (refereegranskat)abstract
- While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes.We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input.We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes.T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.
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| 7. |
- Brusaferri, Ludovica, et al.
(författare)
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Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset
- 2024
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Ingår i: Brain, Behavior, and Immunity. - 0889-1591 .- 1090-2139. ; 116, s. 259-266
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Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic has exerted a global impact on both physical and mental health, and clinical populations have been disproportionally affected. To date, however, the mechanisms underlying the deleterious effects of the pandemic on pre-existing clinical conditions remain unclear. Here we investigated whether the onset of the pandemic was associated with an increase in brain/blood levels of inflammatory markers and MRI-estimated brain age in patients with chronic low back pain (cLBP), irrespective of their infection history. A retrospective cohort study was conducted on 56 adult participants with cLBP (28 ‘Pre-Pandemic’, 28 ‘Pandemic’) using integrated Positron Emission Tomography/ Magnetic Resonance Imaging (PET/MRI) and the radioligand [11C]PBR28, which binds to the neuroinflammatory marker 18 kDa Translocator Protein (TSPO). Image data were collected between November 2017 and January 2020 (‘Pre-Pandemic’ cLBP) or between August 2020 and May 2022 (‘Pandemic’ cLBP). Compared to the Pre-Pandemic group, the Pandemic patients demonstrated widespread and statistically significant elevations in brain TSPO levels (P =.05, cluster corrected). PET signal elevations in the Pandemic group were also observed when 1) excluding 3 Pandemic subjects with a known history of COVID infection, or 2) using secondary outcome measures (volume of distribution -VT- and VT ratio - DVR) in a smaller subset of participants. Pandemic subjects also exhibited elevated serum levels of inflammatory markers (IL-16; P <.05) and estimated BA (P <.0001), which were positively correlated with [11C]PBR28 SUVR (r's ≥ 0.35; P's < 0.05). The pain interference scores, which were elevated in the Pandemic group (P <.05), were negatively correlated with [11C]PBR28 SUVR in the amygdala (r = −0.46; P<.05). This work suggests that the pandemic outbreak may have been accompanied by neuroinflammation and increased brain age in cLBP patients, as measured by multimodal imaging and serum testing. This study underscores the broad impact of the pandemic on human health, which extends beyond the morbidity solely mediated by the virus itself.
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| 8. |
- Donahue, Manus J, et al.
(författare)
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Consensus statement on current and emerging methods for the diagnosis and evaluation of cerebrovascular disease
- 2018
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Ingår i: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. - 1559-7016. ; 38:9, s. 1391-1417
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Forskningsöversikt (refereegranskat)abstract
- Cerebrovascular disease (CVD) remains a leading cause of death and the leading cause of adult disability in most developed countries. This work summarizes state-of-the-art, and possible future, diagnostic and evaluation approaches in multiple stages of CVD, including (i) visualization of sub-clinical disease processes, (ii) acute stroke theranostics, and (iii) characterization of post-stroke recovery mechanisms. Underlying pathophysiology as it relates to large vessel steno-occlusive disease and the impact of this macrovascular disease on tissue-level viability, hemodynamics (cerebral blood flow, cerebral blood volume, and mean transit time), and metabolism (cerebral metabolic rate of oxygen consumption and pH) are also discussed in the context of emerging neuroimaging protocols with sensitivity to these factors. The overall purpose is to highlight advancements in stroke care and diagnostics and to provide a general overview of emerging research topics that have potential for reducing morbidity in multiple areas of CVD.
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| 9. |
- Frid, Petrea, et al.
(författare)
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Fetal posterior cerebral artery configurations in an ischemic stroke versus an unselected hospital population
- 2022
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Ingår i: Acta Neurologica Scandinavica. - : Hindawi Limited. - 0001-6314 .- 1600-0404. ; 145:3, s. 297-304
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Tidskriftsartikel (refereegranskat)abstract
- Background: Few MRA-based studies have systematically evaluated the prevalence and laterality of a fetal configuration of the posterior cerebral artery (FTP) in ischemic stroke populations versus other populations. This common variant is important in the setting of acute stroke and secondary prevention decisions. Objective: To determine the prevalence and laterality of FTP configurations in MRI-DWI verified acute ischemic stroke patients investigated with MRA, and compare the findings with an unselected hospital population investigated with computed tomography angiography (CTA). We also evaluated the association of FTP with posterior cerebral artery (PCA) territory infarctions. Methods: We reviewed the MRAs of 1407 ischemic stroke patients with acute lesions on MRI-DWI sequences and 546 consecutive CTAs of patients investigated on any indication in a tertiary hospital. The MRA and CTA assessments were made by neuroradiologists blinded to original reports on stroke location and vessel anatomy. Results: The prevalence of any FTP was similar in ischemic stroke patients (31%) and unselected patients (32%). Unilateral FTP was significantly more frequent on the right than on the left side in both groups (15% right vs. 8% left). The presence of FTP ipsilateral to stroke side was not associated with involvement of the PCA territory versus no FTP on the stroke side. Conclusions: FTP is present in approximately 30% of ischemic stroke patients and unselected hospital populations and was detected significantly more frequently on the right versus left side in both groups. PCA territory infarction was not associated with the presence of ipsilateral FTP.
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| 10. |
- Giese, Anne Katrin, et al.
(författare)
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Design and rationale for examining neuroimaging genetics in ischemic stroke : The MRI-GENIE study
- 2017
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Ingår i: Neurology: Genetics. - 2376-7839. ; 3:5
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI-GENetics Interface Exploration (MRI-GENIE) study. Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributedMRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include themanual and automated assessments of established MRI markers. A high-throughputMRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.Conclusions: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
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| 11. |
- Giese, Anne Katrin, et al.
(författare)
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White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype
- 2020
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Ingår i: Neurology. - 0028-3878. ; 95:1, s. 79-88
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveTo examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS).MethodsFor the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool-based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes.ResultsPatients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all p < 0.001). Median WMHv in all patients with AIS was 5.86 cm3 (interquartile range 2.18-14.61 cm3) and differed significantly across CCS subtypes (p < 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all p < 0.001), and diabetes mellitus (p = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes (p < 0.001).ConclusionIn this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.
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| 12. |
- Mayer, Manuel, et al.
(författare)
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Constraints on particle acceleration in SS433/W50 from MAGIC and HESS observations
- 2018
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 612
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Tidskriftsartikel (refereegranskat)abstract
- Context. The large jet kinetic power and non-thermal processes occurring in the microquasar SS 433 make this source a good candidate for a very high-energy (VHE) gamma-ray emitter. Gamma-ray fluxes above the sensitivity limits of current Cherenkov telescopes have been predicted for both the central X-ray binary system and the interaction regions of SS 433 jets with the surrounding W50 nebula. Non-thermal emission at lower energies has been previously reported, indicating that efficient particle acceleration is taking place in the system. Aims. We explore the capability of SS 433 to emit VHE gamma rays during periods in which the expected flux attenuation due to periodic eclipses (P-orb similar to 13.1 days) and precession of the circumstellar disk (P-pre similar to 162 days) periodically covering the central binary system is expected to be at its minimum. The eastern and western SS 433/W50 interaction regions are also examined using the whole data set available. We aim to constrain some theoretical models previously developed for this system with our observations. Methods. We made use of dedicated observations from the Major Atmospheric Gamma Imaging Cherenkov telescopes (MAGIC) and High Energy Spectroscopic System (H.E.S.S.) of SS 433 taken from 2006 to 2011. These observation were combined for the first time and accounted for a total effective observation time of 16.5 h, which were scheduled considering the expected phases of minimum absorption of the putative VHE emission. Gamma-ray attenuation does not affect the jet/medium interaction regions. In this case, the analysis of a larger data set amounting to similar to 40-80 h, depending on the region, was employed. Results. No evidence of VHE gamma-ray emission either from the central binary system or from the eastern/western interaction regions was found. Upper limits were computed for the combined data set. Differential fluxes from the central system are found to be less than or similar to 10(-12)-10(-13) TeV-1 cm(-2) s(-1) in an energy interval ranging from similar to few x 100 GeV to similar to few TeV. Integral flux limits down to similar to 10(-12)-10(-13) ph cm(-2) s(-1) and similar to 10(-13)-10(-14) ph cm(-2) s(-1) are obtained at 300 and 800 GeV, respectively. Our results are used to place constraints on the particle acceleration fraction at the inner jet regions and on the physics of the jet/medium interactions. Conclusions. Our findings suggest that the fraction of the jet kinetic power that is transferred to relativistic protons must be relatively small in SS 433, q(p) <= 2.5 x 10(-5), to explain the lack of TeV and neutrino emission from the central system. At the SS 433/W50 interface, the presence of magnetic fields greater than or similar to 10 mu G is derived assuming a synchrotron origin for the observed X-ray emission. This also implies the presence of high-energy electrons with E-e up to 50 TeV, preventing an efficient production of gamma-ray fluxes in these interaction regions.
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| 13. |
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| 14. |
- Wu, Ona, et al.
(författare)
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Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- 2019
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Ingår i: Stroke. - 1524-4628. ; 50:7, s. 1734-1741
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm3 (0.9-16.6 cm3). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.
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