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Record W2059504747 · doi:10.2298/abs1203953d

Seasonal changes in oxidative stress biomarkers of the snail Viviparus acerosus from the Velika Morava River, Serbia

2012· article· en· W2059504747 on OpenAlexaff
Svetlana G. Despotović, Branka Perendija, Jelena P. Gavrić, Slavica Borković-Mitić, Momír Paunović, Slađan Pavlović, Zorica S. Saičić

Bibliographic record

VenueArchives of Biological Sciences · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsGlutathione reductaseGlutathioneCatalaseGlutathione peroxidaseOxidative stressSuperoxide dismutaseBiologyAntioxidantBiomonitoringEnzymeEcologyBiochemistry

Abstract

fetched live from OpenAlex

The river snail (Viviparus acerosus) from the Velika Morava River, Serbia was chosen in our study in order to determine seasonal changes in oxidative stress biomarkers between July (summer) and September (autumn). The activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), glutathione reductase (GR) and the phase II biotransformation enzyme glutathione-S-transferase (GST), as well as the concentration of total glutathione (GSH), were examined in the whole body of the river snails. The obtained results show significantly higher activities of CAT, GSH-Px, GR and biotransformation phase II enzyme GST in September compared to July, while the GSH concentration was lower. There was no general trend in the seasonal changes in the activity of SOD. The presented data show that animals in their natural environment are exposed to constant fluctuations of environmental conditions that could cause antioxidants to exhibit seasonal variations. This fact should be considered as an important variable in the interpretation of results in biomonitoring studies.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
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 studies0.0000.009
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.251
Teacher spread0.219 · 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 designObservational
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

Citations8
Published2012
Admission routes1
Has abstractyes

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