Complex platelet phenotyping: integrative assessment of platelet activity in haemostasis and thrombosis

For my dissertation, I researched the complex mechanisms underlying thrombosis. Using the flow chamber model (a perfusion model that simulates thrombosis formation in a blood vessel), I measured thrombus formation in flowing blood by examining various vessel wall components and markers for platelet activation and blood clotting over time (kinetics). In healthy people, individual differences in the parameters for thrombus formation were discovered that could be partially explained by variations in and among genes. By measuring the kinetics of thrombus and fibrin formation, a new stimulation mechanism of the intrinsic coagulation pathway through tissue factor was discovered. In the blood of mice with hyperlipidaemia, thrombus formation was significantly higher, caused in particular by elevated platelet cholesterol

Circulating growth differentiation factor-15 correlates with myocardial fibrosis in patients with non-ischaemic dilated cardiomyopathy and decreases rapidly after left ventricular assist device support

Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine and is emerging as a biomarker of cardiac remodelling. Left ventricular assist devices (LVADs) provide unloading of the left ventricle, resulting in partial reverse remodelling. Our aim was to study GDF-15 in patients with a non-ischaemic dilated cardiomyopathy (DCM) during LVAD support. We analysed circulating GDF-15 in 30 patients before and 1, 3, and 6 months after LVAD implantation and before heart transplantation or explantation. In addition, mRNA and protein expression of GDF-15 were evaluated in myocardial tissue obtained prior to and after LVAD support. Circulating GDF-15 was significantly higher before LVAD implantation as compared with healthy controls (P 0.001). After 1 month of mechanical support, GDF-15 levels were significantly decreased compared with pre-implantation levels (P 0.001) and remained stable thereafter. Circulating GDF-15 was significantly correlated with kidney function and the severity of myocardial fibrosis. Interestingly, GDF-15 mRNA and protein expression in the myocardium were hardly detectable. High circulating levels of GDF-15 in patients with end-stage non-ischaemic DCM correlate with myocardial fibrosis and kidney function and decline strongly after 1 month of mechanical unloading, remaining stable thereafter. However, cardiac mRNA and protein expression of GDF-15 are very low, suggesting that the heart is not an important source of GDF-15 production in these patients

MicroRNA Expression in Myocardial Tissue and Plasma of Patients with End-Stage Heart Failure during LVAD Support : Comparison of Continuous and Pulsatile Devices

Aim Pulsatile flow left ventricular assist devices (pf-LVADs) are being replaced by continuous flow LVADs (cf-LVADs) in patients with end-stage heart failure (HF). MicroRNAs (miRs) play an important role in the onset and progression of HF. Our aim was to analyze cardiac miR expression patterns associated with each type of device, to analyze differences in the regulation of the induced cardiac changes. Methods and Results Twenty-six miRs were selected (based on micro-array data and literature studies) and validated in myocardial tissue before and after pf- (n = 17) and cf-LVAD (n = 17) support. Of these, 5 miRs displayed a similar expression pattern among the devices (miR-129*, miR-146a, miR-155, miR-221, miR-222), whereas others only changed significantly during pf-LVAD (miR-let-7i, miR-21, miR-378, miR-378*) or cf-LVAD support (miR-137). In addition, 4 miRs were investigated in plasma of cf-LVAD supported patients (n = 18) and healthy controls (n = 10). Circulating miR-21 decreased at 1, 3, and 6 months after LVAD implantation. MiR-146a, miR-221 and miR-222 showed a fluctuating time pattern post-LVAD. Conclusion Our data show a different miR expression pattern after LVAD support, suggesting that differentially expressed miRs are partially responsible for the cardiac morphological and functional changes observed after support. However, the miR expression patterns do not seem to significantly differ between pf- and cf-LVAD implying that most cardiac changes or clinical outcomes specific to each device do not relate to differences in miR expression levels

Changes in plasma miR expression after continuous flow LVAD (cf-LVAD) implantation.

<p>Expression of circulating miR-21 (<i>a</i>), miR-146a (<i>b</i>), miR-221 (<i>c</i>) en miR-222 (<i>d</i>) during cf-LVAD support prior to and 1,3, and 6 months after implantation and before HTx (n = 18 patients) and controls (n = 10). In miR-222, no reliable duplicates on controls could be measured (<i>d</i>). The asterisk (*) represents p<0.05.</p

Baseline demographics of the patients supported with a pulsatile flow LVAD (pf-LVAD) and continuous flow LVAD (cf-LVAD) (validation).

<p>HF, heart failure; CVA, cerebrovascular accident; TIA, transient ischemic attack; NYHA, New York Heart Association; DCM, dilated cardiomyopathy; CRTD, cardiac resynchronization therapy defibrillator; ICD, implantable cardioverter defibrillator.</p><p>^aCategorical data are presented as number (%), continuous data as mean±SEM or median (IQR), respectively.</p><p>^bFamilial DCM is defined if the patient has one or more family members diagnosed with idiopathic DCM or has a first-degree relative with an unexplained sudden death under the age of 35 years.</p><p>^cDays of LVAD support are based on patients who already underwent HTx.</p><p>Baseline demographics of the patients supported with a pulsatile flow LVAD (pf-LVAD) and continuous flow LVAD (cf-LVAD) (validation).</p

Similar changes in miR expression in pulsatile flow (pf-LVAD) and continuous flow LVAD (cf-LVAD).

<p>The alteration in miR-expression in myocardial tissue of both pf-LVAD (n = 17) and cf-LVAD (n = 17) patients. miR-129* (<i>a</i>) and miR-146a (<i>b</i>) are up-regulated in post-LVAD in comparison to pre-LVAD, whereas miR- 155 (<i>c</i>), miR-221 (<i>d</i>) and miR-222 (<i>e</i>) are down-regulated in both devices. The asterisk (*) represents p<0.05.</p

Validation of Aura-OMI QA4ECV NO₂ climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

International audienceThe QA4ECV version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDR) from the satellite sensor OMI are validated, using NDACC zenith scattered light DOAS (ZSL-DOAS) and Multi Axis-DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCD have a small bias of ~ 0.2 Pmolec cm-2 (5–10 %) and a dispersion of 0.2 to 1 Pmolec cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few Pmolec cm-2 up to −10 Pmolec cm-2 (−40 %) in one extreme high-pollution case. QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec cm-2), a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite and ground-based data exceed by far the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and to the difference in vertical smoothing and a priori profile assumptions

Validation of Aura-OMI QA4ECV NO2 Climate Data Records with ground-based DOAS networks: role of measurement and comparison uncertainties

International audienceThe QA4ECV version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDR) from the satellite sensor OMI are validated, using NDACC zenith scattered light DOAS (ZSL-DOAS) and Multi Axis-DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCD have a small bias of ~ 0.2 Pmolec cm-2 (5–10 %) and a dispersion of 0.2 to 1 Pmolec cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few Pmolec cm-2 up to −10 Pmolec cm-2 (−40 %) in one extreme high-pollution case. QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec cm-2), a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite and ground-based data exceed by far the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and to the difference in vertical smoothing and a priori profile assumptions