Review of ozone and temperature lidar validations performed within the framework of the Network for the Detection of Stratospheric Change

The use of assimilation tools for satellite validation requires true estimates of the accuracy of the reference data. Since its inception, the Network for Detection of Stratospheric Change (NDSC) has provided systematic lidar measurements of ozone and temperature at several places around the world that are well adapted for satellite validations. Regular exercises have been organised to ensure the data quality at each individual site. These exercises can be separated into three categories: large scale intercomparisons using multiple instruments, including a mobile lidar; using satellite observations as a geographic transfer standards to compare measurements at different sites; and comparative investigations of the analysis software. NDSC is a research network, so each system has its own history, design, and analysis, and has participated differently in validation campaigns. There are still some technological differences that may explain different accuracies. However, the comparison campaigns performed over the last decade have always proved to be very helpful in improving the measurements. To date, more efforts have been devoted to characterising ozone measurements than to temperature observations. The synthesis of the published works shows that the network can potentially be considered as homogeneous within +/-2% between 20-35 km for ozone and +/-1 K between 35-60 km for temperature. Outside this altitude range, larger biases are reported and more efforts are required. In the lower stratosphere, Raman channels seem to improve comparisons but such capabilities were not systematically compared. At the top of the profiles, more investigations on analysis methodologies are still probably needed. SAGE II and GOMOS appear to be excellent tools for future ozone lidar validations but need to be better coordinated and take more advantage of assimilation tools. Also, temperature validations face major difficulties caused by atmospheric tides and therefore require intercomparisons with the mobile systems, at all sites.     

Non-invasive fetal genotyping for maternal alleles with droplet digital PCR: A comparative study of analytical approaches

Objectives

To develop a flexible droplet digital PCR (ddPCR) workflow to perform non-invasive prenatal diagnosis via relative mutation dosage (RMD) for maternal pathogenic variants with a range of inheritance patterns, and to compare the accuracy of multiple analytical approaches.

Methods

Cell free DNA (cfDNA) was tested from 124 archived maternal plasma samples: 88 cases for sickle cell disease and 36 for rare Mendelian conditions. Three analytical methods were compared: sequential probability ratio testing (SPRT), Bayesian and z-score analyses.

Results

The SPRT, Bayesian and z-score analyses performed similarly well with correct prediction rates of 96%, 97% and 98%, respectively. However, there were high rates of inconclusive results for each cohort, particularly for z-score analysis which was 31% overall. Two samples were incorrectly classified by all three analytical methods; a false negative result predicted for a fetus affected with sickle cell disease and a false positive result predicting the presence of an X-linked IDS variant in an unaffected fetus.

Conclusions

ddPCR can be applied to RMD for diverse conditions and inheritance patterns, but all methods carry a small risk of erroneous results. Further evaluation is required both to reduce the rate of inconclusive results and explore discordant results in more detail.