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- Arce, P., et al.
(författare)
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Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group
- 2021
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Ingår i: Medical Physics. - : Wiley. - 0094-2405 .- 2473-4209. ; 48:1, s. 19-56
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Tidskriftsartikel (refereegranskat)abstract
- Background: Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. Aims: To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics. Materials and Methods: G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. Results: This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. Discussion: Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics. Conclusion: The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.
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| 3. |
- Ivanchenko, M, et al.
(författare)
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Natural killer cells and type II interferon in Ro/SSA and La/SSB autoantibody-exposed newborns at risk of congenital heart block
- 2021
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 80:2, s. 194-202
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Tidskriftsartikel (refereegranskat)abstract
- Congenital heart block (CHB) with immune cell infiltration develops in the fetus after exposure to maternal Ro/La autoantibodies. CHB-related serology has been extensively studied, but reports on immune-cell profiles of anti-Ro/La-exposed neonates are lacking. In the current study, we characterised circulating immune-cell populations in anti-Ro/La+mothers and newborns, and explored potential downstream effects of skewed neonatal cell populations.MethodsIn total, blood from mothers (n=43) and neonates (n=66) was sampled at birth from anti-Ro/La+ (n=36) and control (n=30) pregnancies with or without rheumatic disease and CHB. Flow cytometry, microarrays and ELISA were used for characterising cells and plasma.ResultsSimilar to non-pregnant systemic lupus erythematosus and Sjögren-patients, anti-Ro/La+mothers had altered B-cell subset frequencies, relative T-cell lymphopenia and lower natural killer (NK)-cell frequencies. Surprisingly, their anti-Ro/La exposed neonates presented higher frequencies of CD56dimCD16hiNK cells (p<0.01), but no other cell frequency differences compared with controls. Type I and II interferon (IFN) gene-signatures were revealed in neonates of anti-Ro/La+ pregnancy, and exposure of fetal cardiomyocytes to type I IFN induced upregulation of several NK-cell chemoattractants and activating ligands. Intracellular flow cytometry revealed IFNγ production by NK cells, CD8+and CD4+T cells in anti-Ro/La exposed neonates. IFNγ was also detectable in their plasma.ConclusionOur study demonstrates an increased frequency of NK cells in anti-Ro/La exposed neonates, footprints of type I and II IFN and an upregulation of ligands activating NK cells in fetal cardiac cells after type I IFN exposure. These novel observations demonstrate innate immune activation in neonates of anti-Ro/La+pregnancy, which could contribute to the risk of CHB.
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| 4. |
- Vedunova, M, et al.
(författare)
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DC vaccines loaded with glioma cells killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a four-gene signature for glioma prognosis
- 2022
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Ingår i: Cell death & disease. - : Springer Science and Business Media LLC. - 2041-4889. ; 13:12, s. 1062-
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Tidskriftsartikel (refereegranskat)abstract
- Gliomas, the most frequent type of primary tumor of the central nervous system in adults, results in significant morbidity and mortality. Despite the development of novel, complex, multidisciplinary, and targeted therapies, glioma therapy has not progressed much over the last decades. Therefore, there is an urgent need to develop novel patient-adjusted immunotherapies that actively stimulate antitumor T cells, generate long-term memory, and result in significant clinical benefits. This work aimed to investigate the efficacy and molecular mechanism of dendritic cell (DC) vaccines loaded with glioma cells undergoing immunogenic cell death (ICD) induced by photosens-based photodynamic therapy (PS-PDT) and to identify reliable prognostic gene signatures for predicting the overall survival of patients. Analysis of the transcriptional program of the ICD-based DC vaccine led to the identification of robust induction of Th17 signature when used as a vaccine. These DCs demonstrate retinoic acid receptor-related orphan receptor-γt dependent efficacy in an orthotopic mouse model. Moreover, comparative analysis of the transcriptome program of the ICD-based DC vaccine with transcriptome data from the TCGA-LGG dataset identified a four-gene signature (CFH, GALNT3, SMC4, VAV3) associated with overall survival of glioma patients. This model was validated on overall survival of CGGA-LGG, TCGA-GBM, and CGGA-GBM datasets to determine whether it has a similar prognostic value. To that end, the sensitivity and specificity of the prognostic model for predicting overall survival were evaluated by calculating the area under the curve of the time-dependent receiver operating characteristic curve. The values of area under the curve for TCGA-LGG, CGGA-LGG, TCGA-GBM, and CGGA-GBM for predicting five-year survival rates were, respectively, 0.75, 0.73, 0.9, and 0.69. These data open attractive prospects for improving glioma therapy by employing ICD and PS-PDT-based DC vaccines to induce Th17 immunity and to use this prognostic model to predict the overall survival of glioma patients.
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| 5. |
- Krysko, O, et al.
(författare)
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Artificial Intelligence Predicts Severity of COVID-19 Based on Correlation of Exaggerated Monocyte Activation, Excessive Organ Damage and Hyperinflammatory Syndrome: A Prospective Clinical Study
- 2021
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Ingår i: Frontiers in immunology. - : Frontiers Media SA. - 1664-3224. ; 12, s. 715072-
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Tidskriftsartikel (refereegranskat)abstract
- Prediction of the severity of COVID-19 at its onset is important for providing adequate and timely management to reduce mortality.ObjectiveTo study the prognostic value of damage parameters and cytokines as predictors of severity of COVID-19 using an extensive immunologic profiling and unbiased artificial intelligence methods.MethodsSixty hospitalized COVID-19 patients (30 moderate and 30 severe) and 17 healthy controls were included in the study. The damage indicators high mobility group box 1 (HMGB1), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine aminotransferase (ALT), extensive biochemical analyses, a panel of 47 cytokines and chemokines were analyzed at weeks 1, 2 and 7 along with clinical complaints and CT scans of the lungs. Unbiased artificial intelligence (AI) methods (logistic regression and Support Vector Machine and Random Forest algorithms) were applied to investigate the contribution of each parameter to prediction of the severity of the disease.ResultsOn admission, the severely ill patients had significantly higher levels of LDH, IL-6, monokine induced by gamma interferon (MIG), D-dimer, fibrinogen, glucose than the patients with moderate disease. The levels of macrophage derived cytokine (MDC) were lower in severely ill patients. Based on artificial intelligence analysis, eight parameters (creatinine, glucose, monocyte number, fibrinogen, MDC, MIG, C-reactive protein (CRP) and IL-6 have been identified that could predict with an accuracy of 83−87% whether the patient will develop severe disease.ConclusionThis study identifies the prognostic factors and provides a methodology for making prediction for COVID-19 patients based on widely accepted biomarkers that can be measured in most conventional clinical laboratories worldwide.
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| 6. |
- Pellegrini, C, et al.
(författare)
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A Meta-Analysis of Brain DNA Methylation Across Sex, Age, and Alzheimer's Disease Points for Accelerated Epigenetic Aging in Neurodegeneration
- 2021
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Ingår i: Frontiers in aging neuroscience. - : Frontiers Media SA. - 1663-4365. ; 13, s. 639428-
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Forskningsöversikt (övrigt vetenskapligt/konstnärligt)abstract
- Alzheimer's disease (AD) is characterized by specific alterations of brain DNA methylation (DNAm) patterns. Age and sex, two major risk factors for AD, are also known to largely affect the epigenetic profiles in brain, but their contribution to AD-associated DNAm changes has been poorly investigated. In this study we considered publicly available DNAm datasets of four brain regions (temporal, frontal, entorhinal cortex, and cerebellum) from healthy adult subjects and AD patients, and performed a meta-analysis to identify sex-, age-, and AD-associated epigenetic profiles. In one of these datasets it was also possible to distinguish 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) profiles. We showed that DNAm differences between males and females tend to be shared between the four brain regions, while aging differently affects cortical regions compared to cerebellum. We found that the proportion of sex-dependent probes whose methylation is modified also during aging is higher than expected, but that differences between males and females tend to be maintained, with only a few probes showing age-by-sex interaction. We did not find significant overlaps between AD- and sex-associated probes, nor disease-by-sex interaction effects. On the contrary, we found that AD-related epigenetic modifications are significantly enriched in probes whose DNAm varies with age and that there is a high concordance between the direction of changes (hyper or hypo-methylation) in aging and AD, supporting accelerated epigenetic aging in the disease. In summary, our results suggest that age-associated DNAm patterns concur to the epigenetic deregulation observed in AD, providing new insights on how advanced age enables neurodegeneration.
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