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biotic ligand model.
The linear correlation between Cd2+ toxicity and pH clearly indicates that there is possible proton competition at the biotic ligand.
The development of mechanistic surface complexation models for bacteria provides an opportunity to develop advanced biotic ligand models which are similar to traditional biotic ligand models but which incorporate the mechanistic approach of surface complexation modeling to quantify metal adsorption.
Traditional biotic ligand models were the first attempts to relate metal bioavailability, as manifested by metal toxicity, to the concentration of adsorbed metal on organisms, using a single generic 'biotic' ligand as the lone metal binding site on the organism.
The proper application of biotic ligand models to predict metal toxicity depends on accurate prediction of metal binding to sites on natural organic matter (NOM) which compete with the 'biotic' ligand for available metal.
These changes in toxicity can be attributed to the Biotic Ligand Model (BLM) rather than to metal speciation.
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For instance, cations (e.g. Ca2+ and Mg2+) compete with other free metal ions (Mn+) for biotic ligands, such as gill membranes, thereby reducing their uptake [2, 5, 6].
The levels of toxic trace metals (Pb, Cd, Cu, Zn) in the waters are low (Table 1), and should not affect the test organisms or compete with the added Cu for humic or biotic ligands.
The chemical equilibrium sub-model incorporates metal-biotic ligand interactions to compute metal accumulation at the site of action (e.g., the gill of a fish) as a function of water quality.
RNA structures possess the ability to respond to biotic signals, including molecular ligands, and abiotic signals, such as temperature, regulating diverse cellular tasks such as transcriptional regulation and protein synthesis.
A GPCR system in diatoms involving GABA or other extracellular or intracellular ligands may function similarly in protecting the cells against abiotic and biotic stressors such as temperature or salinity changes.
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