Summary. We present a semiparametric statistical model for the probabilistic index which can be defined as P .Y Y Å /, where Y and Y Å are independent random response variables associated with covariate patterns X and X Å respectively. A link function defines the relationship between the probabilistic index and a linear predictor. Asymptotic normality of the estimators and consistency of the covariance matrix estimator are established through semiparametric theory. The model is illustrated with several examples, and the estimation theory is validated in a simulation study.
Digital PCR is rapidly gaining interest in the field of molecular biology for absolute quantification of nucleic acids. However, the first generation of platforms still needs careful validation and requires a specific methodology for data analysis to distinguish negative from positive signals by defining a threshold value. The currently described methods to assess droplet digital PCR (ddPCR) are based on an underlying assumption that the fluorescent signal of droplets is normally distributed. We show that this normality assumption does not likely hold true for most ddPCR runs, resulting in an erroneous threshold. We suggest a methodology that does not make any assumptions about the distribution of the fluorescence readouts. A threshold is estimated by modelling the extreme values in the negative droplet population using extreme value theory. Furthermore, the method takes shifts in baseline fluorescence between samples into account. An R implementation of our method is available, allowing automated threshold determination for absolute ddPCR quantification using a single fluorescent reporter.
Although microorganisms coexist in the same environment, it is still unclear how their interaction regulates ecosystem functioning. Using a methanotroph as a model microorganism, we determined how methane oxidation responds to heterotroph diversity. Artificial communities comprising of a methanotroph and increasing heterotroph richness, while holding equal starting cell numbers were assembled. We considered methane oxidation rate as a functional response variable. Our results showed a significant increase of methane oxidation with increasing heterotroph richness, suggesting a complex interaction in the cocultures leading to a stimulation of methanotrophic activity. Therefore, not only is the methanotroph diversity directly correlated to methanotrophic activity for some methanotroph groups as shown before, but also the richness of heterotroph interacting partners is relevant to enhance methane oxidation too. In this unprecedented study, we provide direct evidence showing how heterotroph richness exerts a response in methanotrophheterotroph interaction, resulting in increased methanotrophic activity. Our study has broad implications in how methanotroph and heterotroph interact to regulate methane oxidation, and is particularly relevant in methane-driven ecosystems.
Lipoma arborescens is a rare cause of chronic monoarticular arthritis, with only a few cases reported in the literature. It is most commonly seen in the knee, but cases in other joints such as the wrist, shoulder, and elbow have also been described. It is a benign condition, in which the subsynovial tissue is replaced diffusely by mature fat cells. We describe a case involving the knee and discuss the symptoms, diagnosis, and treatment.
TdP can be driven by focal activity as well as by re-entry depending on the duration of the episode. NT episodes are always maintained by re-entry, which can be identified in local unipolar electrograms by shorter interbeat intervals and smaller deflection amplitude.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.