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Record W2026767682 · doi:10.1071/en12078

Effect of pH and environmental ligands on accumulation and toxicity of Ni2+ to Lemna minor

2012· article· en· W2026767682 on OpenAlexaff
Yamini Gopalapillai, Bernard Vigneault, Beverley Hale

Bibliographic record

VenueEnvironmental Chemistry · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of GuelphKellogg's (Canada)Natural Resources Canada
Fundersnot available
KeywordsToxicityEnvironmental chemistryChemistryLemna minorBiotic Ligand ModelMetal toxicityTriethylenetetramineContext (archaeology)Dissolved organic carbonMetalAquatic plantInorganic chemistryBiologyOrganic chemistryEcology

Abstract

fetched live from OpenAlex

Environmental context Predicting metal toxicity is an important tool for effective and efficient risk assessment and regulation of metal pollution in the environment. The present study aims to provide scientific support for the development of a predictive Ni toxicity model for aquatic plants that is particularly applicable to mining-affected natural waters. We show that the effects of pH and natural organic ligands on Ni accumulation and toxicity can be modelled, but further research is required to understand the effects of flotation ligands used in the mining industry. Abstract Effects of water chemistry and metal speciation on metal uptake and toxicity to aquatic plants such as Lemna minor are not fully understood. The present study examined the effect of pH and environmental ligands (dissolved organic carbon (DOC) and mining related flotation ligands diethylenetriamine (DETA), triethylenetetramine (TETA), sodium isopropyl xanthate), on Ni toxicity to L. minor. Exposure and tissue residue toxicity thresholds were assessed to validate the use of a Biotic Ligand Model (BLM) or a Tissue Residue Approach (TRA) as a framework for predicting Ni toxicity. An increase in the activity of H+ non-linearly decreased the toxicity of free Ni ion activity, whereas Ni accumulation kinetics indicated that the mechanism of Ni2+ and H+ interaction was not competitive inhibition as expected by the BLM framework. The effect of DOC on the toxicity of total Ni concentration was relatively small (toxicity decreased by less than a factor of 2) and was explained solely by the complexation of Ni2+ by DOC. Alternatively, the protective effect of flotation ligands (DETA and TETA) was much less than expected based on estimated Ni complexation. Overall, a TRA model was directly applicable in the presence of organic ligands but not to varying pH, whereas a BLM-type model was applicable with changes in pH and DOC but not in the presence of the lesser studied flotation ligands. Such mechanistic information is essential for the development of reliable Ni toxicity models that would aid in risk assessment and regulation of Ni in the environment, particularly in mining-affected regions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.233
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2012
Admission routes1
Has abstractyes

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