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Biochemical responses of two Erythrinidae fish to environmental ammonia

2004· article· en· W2117525485 on OpenAlexaff
Gilberto Moraes, V. L. P. Polez, George K. Iwama

Bibliographic record

VenueBrazilian Journal of Biology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsNational Research Council Canada
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsBiologyAmmoniaUreaAmmonium chlorideAmmoniumEnzymeStressorChlorideFish <Actinopterygii>BiochemistryZoologyFisheryChemistry

Abstract

fetched live from OpenAlex

The non-ionized form of ammonia is very toxic to many aquatic species. It is especially important in several aspects of fish biology. A large range of organismal strategies for coping with environmental stressors is usually observed in living organisms. Among those, the responses for managing chemical stressors are well studied. The present work compares biochemical responses of two evolutionarily close species, Hoplias malabaricus and Hoplerythrinus unitaeniatus, exposed to environmental ammonia. Adult fish were submitted to 1.0 mg/L of ammonium chloride for 24 hours, and plasma ammonia and urea levels were determined. The activities of OUC enzymes OCT and ARG, and the accessory enzyme GS, were quantified in liver extract and are expressed below in mumol/min/mg of wet tissue. Increases in OUC enzymes (GS from 1.14 to 2.43, OCT from 0.81 to 1.72, and ARG from 3.15 to 4.23), plasma ammonia (from 0.95 to 1.42 mmol/L), and plasma urea (from 0.82 to 1.53 mmol/L) were observed (p < 0.05) in H. malabaricus exposed to 1 mg/L of ammonia chloride. The GS in H. unitaeniatus increased from 1.43 to 1.84, however the OCT, ARG, and plasma urea from H. unitaeniatus did not change. These data indicate that each species responds differently to the same environmental stressor.

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 score0.134
Threshold uncertainty score0.569

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 studies0.0000.000
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 head0.250
Teacher spread0.242 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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