Transcriptomics and metatranscriptomics in zooplankton: wave of the future?

Abstract Molecular tools have changed the understanding of zooplankton biodiversity, speciation, adaptation, population genetics and global patterns of connectivity. However, the molecular resources needed to capitalize on these advances continue to be limited in comparison with those available for other eukaryotic plankton. This deficiency could be addressed through an Ocean Zooplankton Open 'Omics Project (Ocean ZOOP) that would generate de novo assembled transcriptomes for hundreds of metazoan plankton species. A collection of comparable reference transcriptomes would generate a new framework for ecological and physiological studies. Defining species niches, identifying optimal habitats, assessing adaptive capacity and predicting changes in phenology are just a few examples of how such a resource could transform studies on zooplankton ecology

Coronary angiography enhancement for visualization

High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 ± 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms