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- Groß, M., et al.
(author)
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Rubella vaccine–induced granulomas are a novel phenotype with incomplete penetrance of genetic defects in cytotoxicity
- 2022
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In: Journal of Allergy and Clinical Immunology. - : Elsevier BV. - 0091-6749 .- 1097-6825. ; 149:1, s. 388-399
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Journal article (peer-reviewed)abstract
- Background: Rubella virus–induced granulomas have been described in patients with various inborn errors of immunity. Most defects impair T-cell immunity, suggesting a critical role of T cells in rubella elimination. However, the molecular mechanism of virus control remains elusive. Objective: This study sought to understand the defective effector mechanism allowing rubella vaccine virus persistence in granulomas. Methods: Starting from an index case with Griscelli syndrome type 2 and rubella skin granulomas, this study combined an international survey with a literature search to identify patients with cytotoxicity defects and granuloma. The investigators performed rubella virus immunohistochemistry and PCR and T-cell migration assays. Results: This study identified 21 patients with various genetically confirmed cytotoxicity defects, who presented with skin and visceral granulomas. Rubella virus was demonstrated in all 12 accessible biopsies. Granuloma onset was typically before 2 years of age and lesions persisted from months to years. Granulomas were particularly frequent in MUNC13-4 and RAB27A deficiency, where 50% of patients at risk were affected. Although these proteins have also been implicated in lymphocyte migration, 3-dimensional migration assays revealed no evidence of impaired migration of patient T cells. Notably, patients showed no evidence of reduced control of concomitantly given measles, mumps, or varicella live-attenuated vaccine or severe infections with other viruses. Conclusions: This study identified lymphocyte cytotoxicity as a key effector mechanism for control of rubella vaccine virus, without evidence for its need in control of live measles, mumps, or varicella vaccines. Rubella vaccine–induced granulomas are a novel phenotype with incomplete penetrance of genetic disorders of cytotoxicity. © 2021 American Academy of Allergy, Asthma & Immunology
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- Maier, O., et al.
(author)
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ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
- 2017
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In: Medical Image Analysis. - : Elsevier BV. - 1361-8415 .- 1361-8423. ; 35, s. 250-269
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Journal article (peer-reviewed)abstract
- Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached this urgent problem of comparability with the Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference. In this paper we propose a common evaluation framework, describe the publicly available datasets, and present the results of the two sub-challenges: Sub-Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES). A total of 16 research groups participated with a wide range of state-of-the-art automatic segmentation algorithms. A thorough analysis of the obtained data enables a critical evaluation of the current state-of-the-art, recommendations for further developments, and the identification of remaining challenges. The segmentation of acute perfusion lesions addressed in SPES was found to be feasible. However, algorithms applied to sub-acute lesion segmentation in SISS still lack accuracy. Overall, no algorithmic characteristic of any method was found to perform superior to the others. Instead, the characteristics of stroke lesion appearances, their evolution, and the observed challenges should be studied in detail. The annotated ISLES image datasets continue to be publicly available through an online evaluation system to serve as an ongoing benchmarking resource (www.isles-challenge.org).
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- Thomas, Ilias, 1987-, et al.
(author)
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Integrative Analysis of Circulating Metabolite Profiles and Magnetic Resonance Imaging Metrics in Patients with Traumatic Brain Injury
- 2020
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In: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 21:4
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Journal article (peer-reviewed)abstract
- Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TBI, relate to structural MRI (sMRI) findings. Serum samples were collected upon admission to the emergency department from patients suffering from acute TBI and metabolites were measured using mass spectrometry-based metabolomics. Most of these patients sustained a mild TBI. In the same patients, sMRIs were taken and volumetric data were extracted (138 metrics). From a pool of 203 eligible screened patients, 96 met the inclusion criteria for this study. Metabolites were summarized as eight clusters and sMRI data were reduced to 15 independent components (ICs). Partial correlation analysis showed that four metabolite clusters had significant associations with specific ICs, reflecting both the grey and white matter brain injury. Multiple machine learning approaches were then applied in order to investigate if circulating metabolites could distinguish between positive and negative sMRI findings. A logistic regression model was developed, comprised of two metabolic predictors (erythronic acid and myo-inositol), which, together with neurofilament light polypeptide (NF-L), discriminated positive and negative sMRI findings with an area under the curve of the receiver-operating characteristic of 0.85 (specificity = 0.89, sensitivity = 0.65). The results of this study show that metabolomic analysis of blood samples upon admission, either alone or in combination with protein biomarkers, can provide valuable information about the impact of TBI on brain structural changes.
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