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- Akhi, Ramin, et al.
(author)
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Cross-reactive saliva IgA antibodies to oxidized LDL and periodontal pathogens in humans.
- 2017
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In: Journal of Clinical Periodontology. - : Wiley. - 0303-6979 .- 1600-051X. ; 44:7, s. 682-691
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Journal article (peer-reviewed)abstract
- AIM: Oxidized low-density lipoproteins (oxLDL) are formed as a result of lipid peroxidation and are highly immunogenic and proatherogenic. In this study, saliva antibodies binding to oxLDL, Porphyromonas gingivalis (Pg) and Aggregatibacter actinomycetemcomitans (Aa) were characterized and their cross-reactivity was evaluated.MATERIALS AND METHODS: Resting and stimulated saliva samples were collected from 36 healthy adults (mean age 26 years). Saliva IgA, IgG and IgM autoantibody levels to copper oxidized LDL (CuOx-LDL) and malondialdehyde acetaldehyde-modified LDL (MAA-LDL) were determined with chemiluminescence immunoassay.RESULTS: Saliva IgA and IgG antibodies binding to MAA-LDL and CuOx-LDL were detected in all samples and they were associated with the saliva levels of IgA and IgG to P. gingivalis and A. actinomycetemcomitans. Competitive immunoassay showed that saliva antibodies to MAA-LDL cross-reacted specifically with P. gingivalis. The autoantibody levels to oxLDL in saliva were not associated with the autoantibody levels to oxLDL in plasma or with saliva apolipoprotein B 100 levels.CONCLUSIONS: Saliva contains IgA and IgG binding to oxLDL, which showed cross-reactive properties with the periodontal pathogens Porphyromonas gingivalis (P.g). The data suggest that secretory IgA to P.g may participate in immune reactions involved in LDL oxidation through molecular mimicry.
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| 2. |
- Hyvärinen, Kati, et al.
(author)
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A machine-learning method for biobank-scale genetic prediction of blood group antigens
- 2024
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In: PLoS Computational Biology. - 1553-734X. ; 20:3
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Journal article (peer-reviewed)abstract
- A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational methods for determining antigens from genomic data. We describe here a classification method for determining RBC antigens from genotyping array data. Random forest models for 39 RBC antigens in 14 blood group systems and for human platelet antigen (HPA)-1 were trained and tested using genotype and RBC antigen and HPA-1 typing data available for 1,192 blood donors in the Finnish Blood Service Biobank. The algorithm and models were further evaluated using a validation cohort of 111,667 Danish blood donors. In the Finnish test data set, the median (interquartile range [IQR]) balanced accuracy for 39 models was 99.9 (98.9-100)%. We were able to replicate 34 out of 39 Finnish models in the Danish cohort and the median (IQR) balanced accuracy for classifications was 97.1 (90.1-99.4)%. When applying models trained with the Danish cohort, the median (IQR) balanced accuracy for the 40 Danish models in the Danish test data set was 99.3 (95.1-99.8)%. The RBC antigen and HPA-1 prediction models demonstrated high overall accuracies suitable for probabilistic determination of blood groups and HPA-1 at biobank- scale. Furthermore, population-specific training cohort increased the accuracies of the models. This stand-alone and freely available method is applicable for research and screening for antigen-negative blood donors.
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| 3. |
- Maaninka, Katariina, et al.
(author)
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OxLDL sensitizes platelets for increased formation of extracellular vesicles capable of finetuning macrophage gene expression
- 2023
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In: European Journal of Cell Biology. - : Elsevier. - 0171-9335 .- 1618-1298. ; 102:2
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Journal article (peer-reviewed)abstract
- Platelet extracellular vesicles (PEVs) generated upon platelet activation may play a role in inflammatory pathologies such as atherosclerosis. Oxidized low-density lipoprotein (oxLDL), a well-known contributor to atherogenesis, activates platelets and presensitizes them for activation by other agonists. We studied the effect of oxLDL on the secretion, composition, and inflammatory functions of PEVs using contemporary EV analytics. Platelets were activated by co-stimulation with thrombin (T) and collagen (C) ± oxLDL and characterized by high-resolution flow cytometry, nanoparticle tracking analysis, proximity extension assay, western blot, and electron microscopy. The effect of PEVs on macrophage differentiation and functionality was examined by analyzing macrophage surface markers, cytokine secretion, and transcriptome. OxLDL upregulated TC-induced formation of CD61+, P-selectin+ and phosphatidylserine+ PEVs. Blocking the scavenger receptor CD36 significantly suppressed the oxLDL+TC-induced PEV formation, and HDL caused a slight but detectable suppression. The inflammatory protein cargo differed between the PEVs from stimulated and unstimulated platelets. Both oxLDL+TC- and TC-induced PEVs enhanced macrophage HLA-DR and CD86 expression and decreased CD11c expression as well as secretion of several cytokines. Pathways related to cell cycle and regulation of gene expression, and immune system signaling were overrepresented in the differentially expressed genes between TC PEV -treated vs. control macrophages and oxLDL+TC PEV -treated vs. control macrophages, respectively. In conclusion, we speculate that oxLDL and activated platelets contribute to proatherogenic processes by increasing the number of PEVs that provide an adhesive and procoagulant surface, contain inflammatory mediators, and subtly finetune the macrophage gene expression.
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