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- Lazzaroni, Francesca, et al.
(författare)
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Circulating biomarkers in familial cerebral cavernous malformation
- 2024
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 99
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Tidskriftsartikel (refereegranskat)abstract
- Background Cerebral Cavernous Malformation (CCM) is a rare cerebrovascular disease, characterized by the presence of multiple vascular malformations that may result in intracerebral hemorrhages (ICHs), seizure(s), or focal neurological deficits (FND). Familial CCM (fCCM) is due to loss of function mutations in one of the three independent genes KRIT1 (CCM1), Malcavernin (CCM2), or Programmed Cell death 10 (PDCD10/CCM3). The aim of this study was to identify plasma protein biomarkers of fCCM to assess the severity of the disease and predict its progression.Methods Here, we have investigated plasma samples derived from n = 71 symptomatic fCCM patients (40 female/31 male) and n =17 healthy donors (HD) (9 female/8 male) of the Phase 1/2 Treat_CCM trial, using multiplexed protein profiling approaches.Findings Biomarkers as sCD14 (p = 0.00409), LBP (p = 0.02911), CXCL4 (p = 0.038), ICAM-1 (p = 0.02013), ANG2 (p = 0.026), CCL5 (p = 0.00403), THBS1 (p = 0.0043), CRP (p = 0.0092), and HDL (p = 0.027), were significantly different in fCCM compared to HDs. Of note, sENG (p = 0.011), THBS1 (p = 0.011) and CXCL4 (p = 0.011), were correlated to CCM genotype. sROBO4 (p = 0.014), TM (p = 0.026) and CRP (p = 0.040) were able to predict incident adverse clinical events, such as ICH, FND or seizure. GDF-15, FLT3L, CXCL9, FGF-21 and CDCP1, were identified as predictors of the formation of new MRI-detectable lesions over 2-year follow-up. Furthermore, the functional relevance of ang2, thbs1, robo4 and cdcp1 markers was validated by zebrafish pre-clinical model of fCCM.Interpretation Overall, our study identifies a set of biochemical parameters to predict CCM progression, suggesting biological interpretations and potential therapeutic approaches to CCM disease.
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| 3. |
- Menkveld, Albert J., et al.
(författare)
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Nonstandard Errors
- 2024
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Ingår i: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
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Tidskriftsartikel (refereegranskat)abstract
- In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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| 4. |
- Polach, Oldrich, et al.
(författare)
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Validation of simulation models in the context of railway vehicle acceptance
- 2015
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Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 229:6, s. 729-754
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Tidskriftsartikel (refereegranskat)abstract
- The evaluation of a reliable validation method, criteria and limit values suitable for model validation in the context of vehicle acceptance was one of the objectives of the DynoTRAIN project. The presented investigations represent a unique amount of testing, simulations, comparisons with measurements, and validation evaluations. The on-track measurements performed in four European countries included several different vehicles on a test train equipped to simultaneously record track irregularities and rail profiles. The simulations were performed using vehicle models built with the use of different simulation tools by different partners. The comparisons between simulation and measurement results were conducted for over 1000 simulations using a set of the same test sections for all vehicle models. The results were assessed by three different validation approaches: comparing values according to EN 14363; by subjective engineering judgement by project partners; and using so-called validation metrics, i.e. computable measures developed with the aim of increasing objectivity while still maintaining the level of agreement with engineering judgement. The proposed validation method uses the values computed by analogy with EN 14363 and provides validation limits that can be applied to a set of deviations between simulation and measurement values.
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