Selection of the conodont Idiognathodus simulator (Ellison) as the event marker for the base of the global Gzhelian Stage (Upper Pennsylvanian, Carboniferous)

Studies carried out for more than 10 years by the Task Group to establish GSSPs at the base of the Moscovian–Kasimovian and Kasimovian–Gzhelian boundaries have resulted in the proposal that the level at which the conodont species Idiognathodus simulator (Ellison, 1941) first appears be selected to mark the base of the Gzhelian Stage. This expands this eastern European chronostratigraphic unit to a global scale.I. simulator (sensu Barrick et al., 2008) has been identified so far in Midcontinent and eastern North America, the Moscow and Donets basins and southern Urals of eastern Europe, and in south-central China. Correlation of this level based on this species and other conodont species can be reinforced in some areas by ammonoid and fusulinid data.     

Recording of elapsed time and temporal information about biological events using Cas9

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A novel approach for the identification of pointer years

In the context of extreme event ecology, identification of pointer years has become a central aspect of tree-ring research. However, the variety of methods employed for pointer year detection since the introduction of the concept in 1979 impedes a direct comparison among studies. Moreover, most commonly used methods partly rely on arbitrarily selected thresholds, resulting in a potentially inconsistent application of those means. To overcome these discrepancies, we here introduce the “standardized growth change” method SGC, which relies on probability density functions of standardized year-to-year ring width differences and internationally accepted significance levels. To evaluate the performance of SGC, it is applied to 1000 pseudo-populations with known properties as well as to an existing Scots pine tree ring data set and compare the results derived from SGC to the four most frequently applied pointer year detection methods. Our comparative evaluation indicates SGC to supersede the other considered methods. In particular, it identified all artificially introduced pointer years in the pseudo-populations, whereas the other methods missed between 3 and 96 percent of known events. A detailed evaluation of misclassifications by the other approaches points out method-specific weaknesses. Finally, we provide technical aspects and recommendations for the application of SGC in a broader context.     

Prognostic implications of changes in cardiac troponin I levels in patients with non-ST elevation acute coronary syndrome

Abstract

Objective: Information is limited on the prognostic implications of cardiac troponin I (cTnI) changes during the first days of non-ST elevation acute coronary syndrome (NSTE-ACS).

Methods: High-sensitivity cTnI levels were measured at study inclusion and after 48?h in 1615 conservatively managed NSTE-ACS patients from the Global Use of Strategies To Open Occluded Coronary Arteries (GUSTO) IV trial.

Results: Patients with moderately increased cTnI levels and without a relevant decrease over time had a significantly raised mortality at 30 days and 1 year. No relevant associations between cTnI changes and recurrent myocardial infarction were seen.

Conclusion: The cTnI change is predictive for subsequent mortality in selected conservatively managed NSTE-ACS patients.     

Multivariate frailty models for two types of recurrent events with a dependent terminal event: Application to breast cancer data

Individuals may experience more than one type of recurrent event and a terminal event during the life course of a disease. Follow‐up may be interrupted for several reasons, including the end of a study, or patients lost to follow‐up, which are noninformative censoring events. Death could also stop the follow‐up, hence, it is considered as a dependent terminal event. We propose a multivariate frailty model that jointly analyzes two types of recurrent events with a dependent terminal event. Two estimation methods are proposed: a semiparametrical approach using penalized likelihood estimation where baseline hazard functions are approximated by M‐splines, and another one with piecewise constant baseline hazard functions. Finally, we derived martingale residuals to check the goodness‐of‐fit. We illustrate our proposals with a real dataset on breast cancer. The main objective was to model the dependency between the two types of recurrent events (locoregional and metastatic) and the terminal event (death) after a breast cancer.