Blooms of the dinoflagellate Karenia mikimotoi have cause great financial losses to the marine aquaculture industry. However, the toxicity mechanism of this species is still not fully known. In this study, we evaluated the short-term effects of K. mi...
The northeastern Arabian Sea (NEAS) experiences convective mixing during winter, but this mixing does not reach up to the silicicline, resulting in the limited supply of silicate (Si) compared to nitrate (N) and phosphate (P) to the mixed layer (ML) ...
A pilot-scale bioprocess was developed for the production of karlotoxin-enriched extracts of the marine algal dinoflagellate Karlodinium veneficum. A bubble column and a flat-panel photobioreactors (80-281 L) were used for comparative assessment of g...
The aim of this study was to develop a loop-mediated isothermal amplification (LAMP) combined with a chromatographic lateral flow dipstick (LFD) assay to rapidly and specifically detect the Karlodinium veneficum ITS gene. Four groups of LAMP primers ...
Takayama spp. are phototrophic dinoflagellates belonging to the family Kareniaceae and have caused fish kills in several countries. Understanding their trophic mode and interactions with co-occurring phytoplankton species are critical steps in compre...
The entrapment and death of the ciliate Mesodinium rubrum in the mucus threads in cultures with Dinophysis is described and quantified. Feeding experiments with different concentrations and predator-prey ratios of Dinophysis acuta, Dinophysis acumina...
Inshore and offshore waters of the Gulf of Maine (USA) have spring/summer harmful algal blooms (HABs) of the toxic dinoflagellate , which is responsible for paralytic shellfish poisoning (PSP) in humans. The calanoid copepod co-occurs with during t...
Mechanosensing, the transduction of extracellular mechanical stimuli into intracellular biochemical signals, is a fundamental property of living cells. However, endowing synthetic materials with mechanosensing capabilities comparable to biological le...
Harmful algal blooms (HABs) are challenging to recognize because of their striped and uneven biomass distributions. To address this issue, a refined deep-learning algorithm termed HAB-Ne was developed for the recognition of HABs in GF-1 Wide Field of...
In this study, explainable machine learning techniques are applied to predict the toxicity of mussels in the Gulf of Trieste (Adriatic Sea) caused by harmful algal blooms. By analysing a newly created 28-year dataset containing records of toxic phyto...