Reflex and Tonic Autonomic Markers for Risk Stratification in Patients With Type 2 Diabetes Surviving Acute Myocardial Infarction

OBJECTIVE Diabetic postinfarction patients are at increased mortality risk compared with nondiabetic postinfarction patients. In a substantial number of these patients, diabetic cardiac neuropathy already preexists at the time of the infarction. In the current study we investigated if markers of autonomic dysfunction can further discriminate diabetic postinfarction patients into low- and high-risk groups. RESEARCH DESIGN AND METHODS We prospectively enrolled 481 patients with type 2 diabetes who survived acute myocardial infarction (MI), were aged ≤80 years, and presented in sinus rhythm. Primary end point was total mortality at 5 years of follow-up. Severe autonomic failure (SAF) was defined as coincidence of abnormal autonomic reflex function (assessed by means of heart rate turbulence) and of abnormal autonomic tonic activity (assessed by means of deceleration capacity of heart rate). Multivariable risk analyses considered SAF and standard risk predictors including history of previous MI, arrhythmia on Holter monitoring, insulin treatment, and impaired left ventricular ejection fraction (LVEF) ≤30%. RESULTS During follow-up, 83 of the 481 patients (17.3%) died. Of these, 24 deaths were sudden cardiac deaths and 21 nonsudden cardiac deaths. SAF identified a high-risk group of 58 patients with a 5-year mortality rate of 64.0% at a sensitivity level of 38.0%. Multivariately, SAF was the strongest predictor of mortality (hazard ratio 4.9 [95% CI 2.4–9.9]), followed by age ≥65 years (3.4 [1.9–5.8]), and LVEF ≤30% (2.6 [1.5–4.4]). CONCLUSIONS Combined abnormalities of autonomic reflex function and autonomic tonic activity identifies diabetic postinfarction patients with very poor prognoses

Benchmarking whole exome sequencing in the German Network for Personalized Medicine

Introduction Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. Methods To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics investigating somatic and germline variants, copy-number alteration (CNA), and different complex biomarkers. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. In addition, all raw data were re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. Results The mean positive percentage agreement (PPA) of somatic variant calling was 76% and positive predictive value (PPV) 89% compared a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88% for all and 97% for clinically relevant variants. CNA calls were concordant for 82% of genomic regions. Calls of homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94%, 93%, and 93% respectively. Variability of CNAs and complex biomarkers did not increase considerably using the central pipeline and was hence attributed to wet-lab differences. Conclusion Continuous optimization of bioinformatic workflows and participating in round robin tests are recommend

Deceleration Runs - a method for risk stratification after myocardial infarction

In der vorliegenden Arbeit wurde eine neue Methode zur Risikostratifizierung nach Myokardinfarkt basierend auf der Dynamik der Herzfrequenz beschrieben. Der Theorie der Symbolischen Dynamik folgend wurde das relative Auftreten von sich kontinuierlich verlängernden Episoden zweier RR-Intervalle gezählt und untersucht, ob sich dieses zur Identifizierung von gefährdeten Patienten eignet. Aus den signifikanten Deleceration Runs (DRs) wurde ein Modell zur Risikostratifizierung entwickelt. Hierfür wurden 1455 Daten von 24h-LZ-EKGs von Patienten nach Myokardinfarkt (MI) verwendet und weitere 946, um das Modell zu validieren. Es fiel auf, dass mit zunehmender Kettenlänge die Häufigkeit der Episoden abnehmen, Kettenlängen von 5 oder mehr fortlaufenden Verlängerungen der RR-Intervalle traten nicht jeden Patienten auf. Alle DRs waren signifikant mit der Mortalität assoziiert und konnten als Risikoparameter genutzt werden (AUC-Werte > 0,5). In den darauf berechneten ROC-Kurven zeigte sich, dass die relative Anzahl von R2-10 invers mit der Gesamtmortalität assoziiert ist. Univariat zeigten sich eine geringe Anzahl an DR2-10 bei Verstorbenen. Mit dem Modell zur Risikostratifizierung, basierend auf den multivariat signifikanten Variablen DR4, DR8 und DR2 der Entwicklungsgruppe, ließen sich Gruppen mit niedrigem, mittlerem und hohem Risiko identifizieren. Auffällig war, dass Patienten mit hohem Risiko allein durch eine verminderte Anzahl an DR4 charakterisiert sind. Nach Anwendung des CART-Modells war die 2-Jahres-Sterberate bezogen auf die Gesamtmortalität in diesen Gruppen 1,8%, 6,1% und 24% in der Entwicklungsgruppe und 1,8%, 4,1% und 21,9% in der Validierungsgruppe. Es zeigte sich somit eine klare Trennung zwischen Hoch-, Mittel- und Niedrigrisiko, sowohl in der Entwicklungs-, als auch in der Validierungsgruppe. Im Hinblick auf die sekundäre Endpunkte kardiale Mortalität und plötzlicher Herztod konnte mit Hilfe des CART-Modells nur in der Validierungsgruppe eine signifikante Trennung zwischen Hoch- und Niedrigrisikopatienten (17,2%, 1,0% bei kardialer Mortalität, 9,4%, 0,8% beim plötzlichen Herztod) errechnet werden, jedoch ähnlich den Sterberaten dieser im Entwicklungskollektiv (17,3% für die Hochrisiko-, 0,8% für die Niedrigrisikogruppe bei kardialer Mortalität, 6,7% für die Hochrisiko-, 0,3% für die Niedrigrisikogruppe beim plötzlichen Herztod). Sowohl in der Entwicklungs- als auch in der Validierungsgruppe war das CART-Modell in seiner Aussage auf die Gesamtmortalität signifikant unabhängig gegenüber den etablierten Standardparameter Alter ≥ 65 Jahre, LVEF ≤ 35%, SDNN ≤ 70 ms, früherer Herzinfarkt und Diabetes mellitus. Zudem zeigte die Hochrisikogruppe des CART-Modells im Vergleich zu den Standardparametern das höchste relative Risiko sowohl für die 2-Jahres-Gesamtmortalität als auch für die sekundären Endpunkte kardiale Mortalität und plötzlicher Herztod. Wegen der geringen Anzahl an Ereignissen bei den sekundären Endpunkten können die Ergebnisse jedoch nur als Trends gewertet werden. Die Arbeit zeigte somit, dass die Berechnung von DRs eine andere bedeutungsvolle Facette der Risikoprädiktion nach einem überlebten Herzinfarkt ist, die auf Langzeit-Dynamiken der Herzfrequenz basiert. Das Ergebnis dieser Arbeit zeigte, dass die Fähigkeit, die Herzfrequenz über fortlaufende Zyklen zu verlangsamen, einen starken prognostischen Wert bei Überlebenden nach MI hat. In weiteren Studien sollte untersucht werden, inwieweit das Modell zur Risikostratifizierung oder die DRs an sich bei anderen Pathologien wie Herzinsuffizienz oder kardiale autonome Neuropathie durch Diabetes prognostisches Potential haben. Zudem ist noch unklar, ob und inwieweit sich die pharmakologische und interventionelle Therapie der Patienten auf die prognostische Aussagekraft des neuen Parameter auswirken.In the present work a new method for risk stratification after myocardial infarction based on the dynamic of the heart rate was described. Following the Theory of the Symbolic Dynamics, the relative occurrence of continuously extending episodes of two RR-intervals was counted and investigated, whether this is suitable for identifying patients at risk. A model for risk stratification was developed out of the significant Deceleration Runs. To this end, 1455 data of 24h-longtime-ecgs from patients after myocardial infarction (MI) were used and another 946 to validate the model. It was noticeable that the frequency of episodes decreases with increasing length of the runs, lengths of 5 or more consecutive extensions of RR intervals did not occur in every patient. All DRs were significantly associated with mortality and could be used as a parameter for risk (AUC-values > 0,5). In the ROC curves calculated on it, it was found that the relative number of R2-10 is inversely associated with all-cause mortality. Univariate showed a low number of DR2-10 in the deceased. The risk stratification model, based on multivariate significant variables DR4, DR8 and DR2 of the development group, identified low, medium and high risk groups. It was noticeable that high-risk patients are characterized solely by a reduced number of DR4. After applying the CART model, the 2-year mortality rate for total mortality in these groups was 1.8%, 6.1% and 24% in the development group and 1.8%, 4,1% and 21,9% respectively in the validation group. Thus it showed a clear separation between high-, medium- and low-risk, both in development, and in the validation group. With regard to the secondary endpoints of cardiac mortality and sudden cardiac death, the CART model showed only a significant separation between high and low risk patients in the validation group (17.2%, 1.0% for cardiac mortality, 9.4%, 0.8% in sudden cardiac death), but similar to the mortality rates in the development collective (17.3% for the high-risk, 0.8% for the low-risk group for cardiac mortality, 6.7% for the high-risk, 0.3% for the low-risk group in sudden cardiac death). In both the development and validation groups, the overall mortality CART model was significantly independent of the established standard parameters age ≥ 65 years, LVEF ≤ 35%, SDNN ≤ 70 ms, previous myocardial infarction, and diabetes mellitus. In addition, the high-risk group of the CART model showed the highest relative risk for both 2-year all-cause mortality and the secondary endpoints cardiac mortality and sudden cardiac death compared to the standard parameters. However, because of the low number of events at the secondary endpoints, the results can only be considered as trends. Thus, the work showed that the calculation of DRs is another significant facet of risk prediction after a survived heart attack based on long-term heart rate dynamics. The result of this work showed that the ability to slow the heart rate over consecutive cycles has a strong prognostic value in survivors after MI. Further studies should examine the extent to which the risk stratification model or the DRs themselves have prognostic potential in other pathologies such as heart failure or cardiac autonomic neuropathy due to diabetes. Moreover, it is still unclear whether and to what extent the pharmacological and interventional treatment of patients affect the prognostic value of the new parameter

¹H and¹³C NMR study of perdeuterated pyrazoles

The1H and13C chemical shifts as well as the1H–2H and2H–13C coupling constants of perdeuterated 3,5-dimethylpyrazole and 3,5-diphenylpyrazole have been measured and the values compared with those of the unlabelled compounds.</jats:p

H-1 and C-13 NMR study of perdeuterated pyrazoles

The ^{1}H and ^{13}C chemical shifts as well as the ^{1}H–^{2}H and ^{2}H–^{13}C coupling constants of perdeuterated 3,5-dimethylpyrazole and 3,5-diphenylpyrazole have been measured and the values compared with those of the unlabelled compounds.Peer reviewe

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

International audienceThe Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents

The DUNE Far Detector Vertical Drift Technology, Technical Design Report

International audienceDUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment