Statistical analysis of the induced Basel 2006 earthquake sequence: Introducing a probability-based monitoring approach for Enhanced Geothermal Systems

ISSN:0956-540XISSN:1365-246

The Relationship Between Plasma Flow Doppler Velocities and Magnetic Field Parameters During the Emergence of Active Regions at the Solar Photospheric Level

A statistical study has been carried out of the relationship between plasma flow Doppler velocities and magnetic field parameters during the emergence of active regions at the solar photospheric level with data acquired by the Michelson Doppler Imager (MDI) onboard the Solar and Heliospheric Observatory (SOHO). We have investigated 224 emerging active regions with different spatial scales and positions on the solar disc. The following relationships for the first hours of the emergence of active regions have been analysed: i) of peak negative Doppler velocities with the position of the emerging active regions on the solar disc; ii) of peak plasma upflow and downflow Doppler velocities with the magnetic flux growth rate and magnetic field strength for the active regions emerging near the solar disc centre (the vertical component of plasma flows); iii) of peak positive and negative Doppler velocities with the magnetic flux growth rate and magnetic field strength for the active regions emerging near the limb (the horizontal component of plasma flows); iv) of the magnetic flux growth rate with the density of emerging magnetic flux; v) of the Doppler velocities and magnetic field parameters for the first hours of the appearance of active regions with the total unsigned magnetic flux at the maximum of their development.Comment: 14 pages, 8 figures. The results of article were presented at the ESPM-13 (12-16 September 2011, Rhodes, Greece, Abstract Book p. 102-103, P.4.13, http://astro.academyofathens.gr/espm13/documents/ESPM13_abstract_programme_book.pdf

Clinical data for paediatric research: the Swiss approach : Proceedings of the National Symposium in Bern, Switzerland, Dec 5-6, 2019.

Continuous improvement of health and healthcare system is hampered by inefficient processes of generating new evidence, particularly in the case of rare diseases and paediatrics. Currently, most evidence is generated through specific research projects, which typically require extra encounters with patients, are costly and entail long delays between the recognition of specific needs in healthcare and the generation of necessary evidence to address those needs. The Swiss Personalised Health Network (SPHN) aims to improve the use of data obtained during routine healthcare encounters by harmonizing data across Switzerland and facilitating accessibility for research. The project "Harmonising the collection of health-related data and biospecimens in paediatric hospitals throughout Switzerland (SwissPedData)" was an infrastructure development project funded by the SPHN, which aimed to identify and describe available data on child health in Switzerland and to agree on a standardised core dataset for electronic health records across all paediatric teaching hospitals. Here, we describe the results of a two-day symposium that aimed to summarise what had been achieved in the SwissPedData project, to put it in an international context, and to discuss the next steps for a sustainable future. The target audience included clinicians and researchers who produce and use health-related data on children in Switzerland. The symposium consisted of state-of-the-art lectures from national and international keynote speakers, workshops and plenary discussions. This manuscript summarises the talks and discussions in four sections: (I) a description of the Swiss Personalized Health Network and the results of the SwissPedData project; (II) examples of similar initiatives from other countries; (III) an overview of existing health-related datasets and projects in Switzerland; and (IV) a summary of the lessons learned and future prospective from workshops and plenary discussions. Streamlined processes linking initial collection of information during routine healthcare encounters, standardised recording of this information in electronic health records and fast accessibility for research are essential to accelerate research in child health and make it affordable. Ongoing projects prove that this is feasible in Switzerland and elsewhere. International collaboration is vital to success. The next steps include the implementation of the SwissPedData core dataset in the clinical information systems of Swiss hospitals, the use of this data to address priority research questions, and the acquisition of sustainable funding to support a slim central infrastructure and local support in each hospital. This will lay the foundation for a national paediatric learning health system in Switzerland

Plasma NGAL levels in stable kidney transplant recipients and the risk of allograft loss

BACKGROUND: The object of this study was to investigate the utility of Neutrophil gelatinase-associated lipocalin (NGAL) and Calprotectin (CPT) to predict long-term graft survival in stable kidney transplant recipients (KTR). METHODS: 709 stable outpatient KTR were enrolled >2 months post-transplant. The utility of plasma and urinary NGAL (pNGAL, uNGAL) and plasma and urinary CPT at enrollment to predict death-censored graft loss (GL) was evaluated during a 58-month follow-up. RESULTS: Among biomarkers, pNGAL showed best predictive ability for graft loss and was the only biomarker with an AUC > 0.7 for GL within 5 years. Patients with GL within 5 years (n=49) had a median pNGAL of 304[IQR 235-358] versus 182[IQR 128 -246]ng/ml with surviving grafts (p<0.001). Time-dependent Receiver operating characteristic analyses at 58 months indicated an Area-Under-the-Curve (AUC) for pNGAL of 0.795, serum creatinine (sCr) based estimated glomerular filtration rate (eGFR) CKD EPI had an AUC of 0.866. pNGAL added to a model based on conventional risk factors for GL with death as competing risk (age, transplant age, presence of donor specific antibodies, presence of proteinuria, history of delayed graft function) had a strong independent association with GL (subdistribution Hazard ratio (sHR) for binary log transfomed pNGAL (log2 (pNGAL)) (3.4 95% CI 2.24-5.15), p<0.0001). This association was substantially attenuated when eGFR was added to the model (sHR for log2 (pNGAL) 1.63 95% CI 0.92-2.88, p=0.095). Category-free net reclassification improvement of a risk model including log2(pNGAL) additionally to conventional risk factors and eGFR was 54.3% (95% CI 9.2 to 99.3%) but C-statistic did not improve significantly. CONCLUSIONS: pNGAL was an independent predictor of renal allograft loss in stable KTR from one transplant center but did not show consistent added value when compared to baseline predictors including the conventional marker eGFR. Future studies in larger cohorts are warranted