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Record W2074457514 · doi:10.1086/432858

The Disruption of <i>Daphnia magna</i> Sodium Metabolism by Humic Substances: Mechanism of Action and Effect of Humic Substance Source

2005· article· en· W2074457514 on OpenAlexaff
Chris N. Glover, Chris M. Wood

Bibliographic record

VenuePhysiological and Biochemical Zoology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDaphnia magnaChemistryHumic acidEnvironmental chemistrySodiumCalciumNatural organic matterMetabolismMembrane permeabilityOrganic matterBiochemistryBiophysicsToxicityMembraneBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Humic substances have important functions in aquatic systems. While these roles are primarily indirect, influencing the physicochemical environment, recent evidence suggests these materials may also have direct biological actions. This study investigated the mechanism by which humic substances perturb sodium metabolism in a freshwater invertebrate, the water flea Daphnia magna. Aldrich humic acid (AHA) stimulated the maximal rate of whole-body sodium influx (Jmax) when experimental pH was 6 and water calcium content was 0.5 mM. This effect persisted at pH 8 and 1 mM calcium but not at pH 8 in the absence of calcium. An indirect action of AHA on apical transporter activity was proposed to explain this effect. At pH 4 AHA promoted a linear sodium uptake kinetic relationship, attributed to altered membrane permeability due to enhanced membrane binding of humic substances at low pH. In contrast, a real-world natural organic matter sample had no consistent action on sodium influx, suggesting that impacts on sodium metabolism may be limited to commercially available humic materials. These findings question the applicability of commercially available humic substances for laboratory investigations and have significant implications for the study of environmental metal toxicity.

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 categoriesnone
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 score0.027
Threshold uncertainty score0.753

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations55
Published2005
Admission routes1
Has abstractyes

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