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- Cossarizza, A., et al.
(författare)
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Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)
- 2019
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Ingår i: European Journal of Immunology. - : Wiley. - 0014-2980 .- 1521-4141. ; 49:10, s. 1457-1973
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Tidskriftsartikel (refereegranskat)abstract
- These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.
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- Pantazis, N, et al.
(författare)
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Determining the likely place of HIV acquisition for migrants in Europe combining subject-specific information and biomarkers data
- 2019
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Ingår i: Statistical methods in medical research. - : SAGE Publications. - 1477-0334 .- 0962-2802. ; 28:7, s. 1979-1997
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Tidskriftsartikel (refereegranskat)abstract
- In most HIV-positive individuals, infection time is only known to lie between the time an individual started being at risk for HIV and diagnosis time. However, a more accurate estimate of infection time is very important in certain cases. For example, one of the objectives of the Advancing Migrant Access to Health Services in Europe (aMASE) study was to determine if HIV-positive migrants, diagnosed in Europe, were infected pre- or post-migration. We propose a method to derive subject-specific estimates of unknown infection times using information from HIV biomarkers’ measurements, demographic, clinical, and behavioral data. We assume that CD4 cell count (CD4) and HIV-RNA viral load trends after HIV infection follow a bivariate linear mixed model. Using post-diagnosis CD4 and viral load measurements and applying the Bayes’ rule, we derived the posterior distribution of the HIV infection time, whereas the prior distribution was informed by AIDS status at diagnosis and behavioral data. Parameters of the CD4–viral load and time-to-AIDS models were estimated using data from a large study of individuals with known HIV infection times (CASCADE). Simulations showed substantial predictive ability (e.g. 84% of the infections were correctly classified as pre- or post-migration). Application to the aMASE study ( n = 2009) showed that 47% of African migrants and 67% to 72% of migrants from other regions were most likely infected post-migration. Applying a Bayesian method based on bivariate modeling of CD4 and viral load, and subject-specific information, we found that the majority of HIV-positive migrants in aMASE were most likely infected after their migration to Europe.
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| 9. |
- Hartmann, S., et al.
(författare)
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Can single-cell and spatial omics unravel the pathophysiology of pre-eclampsia?
- 2023
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Ingår i: Journal of Reproductive Immunology. - : Elsevier. - 0165-0378 .- 1872-7603. ; 159
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Tidskriftsartikel (refereegranskat)abstract
- Pre-eclampsia is a leading cause of maternal and fetal morbidity and mortality. Characterised by the onset of hypertension and proteinuria in the second half of pregnancy, it can lead to maternal end-organ injury such as cerebral ischemia and oedema, pulmonary oedema and renal failure, and potentially fatal outcomes for both mother and fetus. The causes of the different maternal end-organ phenotypes of pre-eclampsia and why some women develop pre-eclampsia condition early in pregnancy have yet to be elucidated. Omics methods include proteomics, genomics, metabolomics, transcriptomics. These omics techniques, previously mostly used on bulk tissue and individually, are increasingly available at a single cellular level and can be combined with each other. Multi-omics techniques on a single-cell or spatial level provide us with a powerful tool to understand the pathophysiology of pre-eclampsia. This review will explore the status of omics methods and how they can and could contribute to understanding the pathophysiology of pre-eclampsia.
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| 10. |
- Hastie, R., et al.
(författare)
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Associations Between Soluble fms-Like Tyrosine Kinase-1 and Placental Growth Factor and Disease Severity Among Women With Preterm Eclampsia and Preeclampsia
- 2022
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Ingår i: Journal of the American Heart Association (JAHA). - : Ovid Technologies (Wolters Kluwer Health). - 2047-9980. ; 11:16
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Tidskriftsartikel (refereegranskat)abstract
- Background The angiogenic factors soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) are postulated to be pathogenic disease drivers of preeclampsia. If true, then circulating levels should become more deranged with increasing disease severity. Methods and Results We investigated the association between circulating sFlt-1 and PlGF levels and severe adverse maternal outcomes among 348 women with preeclampsia. Compared with 125 women with preeclampsia without severe features, 25 women with preeclampsia and any of hemolysis, elevated liver enzymes, low platelet count syndrome, disseminated intravascular coagulation, or severe renal involvement had sFlt-1 levels that were 2.63-fold higher (95% CI, 1.81-3.82), sFlt-1/PlGF levels that were 10.07-fold higher (95% CI, 5.36-18.91) and PlGF levels that were 74% lower (adjusted fold change, 0.26 [95% CI, 0.18-0.39]). Compared with 125 women with preeclampsia without severe features, 37 with eclampsia had sFlt-1 levels that were 2-fold higher (2.02 [95% CI, 1.32-3.09]), sFlt-1/PIGF levels that were 4.71-fold higher (95% CI, 2.30-9.66) and PIGF levels that were 63% lower (0.43-fold change [95% CI, 0.27-0.68]). Compared with those without severe features, preeclampsia with severe hypertension (n=146) was also associated with altered angiogenic levels (sFlt-1, 1.71-fold change [95% CI, 1.39-2.11]; sFlt/PlGF, 2.91 [95% CI, 2.04-4.15]; PlGF, 0.59 [95%CI 0.47-0.74]). We also found that sFlt-1 and PlGF levels were altered by the number of maternal complications experienced. Conclusions Further angiogenic imbalance among women with preeclampsia is likely a pathogenic disease driver responsible for the life-threatening maternal complications.
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- Kapun, Martin, et al.
(författare)
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Drosophila Evolution over Space and Time (DEST) : A New Population Genomics Resource
- 2021
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Ingår i: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 38:12, s. 5782-5805
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Tidskriftsartikel (refereegranskat)abstract
- Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.
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