Fluorescence Lifetime Imaging in Stargardt Disease: Potential Marker for Disease Progression.

PURPOSE The purpose of this study was to describe autofluorescence lifetime characteristics in Stargardt disease (STGD) using fluorescence lifetime imaging ophthalmoscopy (FLIO) and to investigate potential prognostic markers for disease activity and progression. METHODS Fluorescence lifetime data of 16 patients with STGD (mean age, 40 years; range, 22-56 years) and 15 age-matched controls were acquired using a fluorescence lifetime imaging ophthalmoscope based on a Heidelberg Engineering Spectralis system. Autofluorescence was excited with a 473-nm laser, and decay times were measured in a short (498-560 nm) and long (560-720 nm) spectral channel. Clinical features, autofluorescence lifetimes and intensity, and corresponding optical coherence tomography images were analyzed. One-year follow-up examination was performed in eight STGD patients. Acquired data were correlated with in vitro measured decay times of all-trans retinal and N-retinylidene-N-retinylethanolamine. RESULTS Patients with STGD displayed characteristic autofluorescence lifetimes within yellow flecks (446 ps) compared with 297 ps in unaffected areas. In 15% of the STGD eyes, some flecks showed very short fluorescence lifetimes (242 ps). Atrophic areas were characterized by long lifetimes (474 ps), with some remaining areas of normal to short lifetimes (322 ps) toward the macular center. CONCLUSIONS Patients with recent disease onset showed flecks with very short autofluorescence lifetimes, which is possible evidence of accumulation of retinoids deriving from the visual cycle. During the study period, many of these flecks changed to longer lifetimes, possibly due to accumulation of lipofuscin. Therefore, FLIO might serve as a useful tool for monitoring of disease progression. (ClinicalTrials.gov number, NCT01981148.).

Insights into the timing of repeated testing after treatment for Chlamydia trachomatis: data and modelling study

The objective of this study was to determine the optimal time interval for a repeated Chlamydia trachomatis (chlamydia) test.

Modelling zero-inflated count data when exposure varies: with an application to tumor counts)

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a modified zero-inflated count data model where the probability of an extra zero is derived from an underlying duration model with Weibull hazard rate. The new model is compared to the standard Poisson model with logit zero inflation in an application to the effect of treatment with thiotepa on the number of new bladder tumors.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.