is an aggressive pathogen of pulse crops and a causal agent in root rot disease that negatively impacts Canadian agriculture. This study reports the results of a targeted metabolomics-based profiling of secondary metabolism in an 18-strain panel of cultured axenically in multiple media conditions, in addition to an in planta infection assay involving four strains inoculated on two pea cultivars. Multiple secondary metabolites with known roles as virulence factors were detected which have not been previously associated with , including fungal decalin-containing diterpenoid pyrones (FDDPs), fusaoctaxins, sambutoxin and fusahexin, in addition to confirmation of previously reported secondary metabolites including enniatins, fusarins, chlamydosporols, JM-47 and others.
View Article and Find Full Text PDFBackground: Machine learning-based analysis can accurately detect atrial fibrillation (AF) from photoplethysmograms (PPGs), however the computational requirements for analyzing raw PPG waveforms can be significant. The analysis of PPG-derived peak-to-peak intervals may offer a more feasible solution for smartphone deployment, provided the diagnostic utility is comparable.
Aims: To compare raw PPG waveforms and PPG-derived peak-to-peak intervals as input signals for machine learning detection of AF.
Diadromous fish species are characterised by spawning migrations between freshwater and marine environments, where they traverse through estuaries and close to coasts. This species group has declined substantially over the past decades due to anthropogenic effects such as habitat fragmentation and loss and overfishing. A rising potential threat to their population recovery is the increasing installation of subsea power cables (SPCs) which generate electromagnetic fields (EMF) as they transport energy from offshore wind farms to land.
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