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Record W4281776093 · doi:10.17975/sfj-2022-009

Exploring the effect of atrazine exposure on the reproductive capacity of <i>Daphnia magna</i>

2022· article· en· W4281776093 on OpenAlexafffundvenue
Lee Christoff-Johan, Lee Nikko-Johan

Bibliographic record

VenueSTEM Fellowship Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsAtrazineDaphnia magnaDNA fragmentationBiologyFragmentation (computing)OffspringDaphniaToxicologyPesticideApoptosisToxicityEcologyInternal medicineZooplanktonGeneticsProgrammed cell deathPregnancy

Abstract

fetched live from OpenAlex

Atrazine is an herbicide commonly used for weed control in crops and on turf, but environmental contamination with atrazine causes endocrine disruption leading to reproductive defects in humans and freshwater organisms. The molecular and cellular mechanisms causing these reproductive deficiencies remain largely unknown. Thus, the purpose of this study is to explore the reproductive consequence of atrazine exposure at the molecular and cellular level in the freshwater planktonic crustacean, Daphnia magna. Results show that exposure of D. magna to high atrazine concentration of 1000 or 2000 μg/L reduced the number of the first set of offspring born at least 5 days after atrazine exposure. D. magna exposed to these atrazine concentrations exhibited DNA fragmentation, nuclear condensation and fragmentation in the ovaries, and caspase-3 protein activation in both the ovaries and embryos in the brood chamber. No obvious DNA fragmentation, nuclear condensation and fragmentation, or caspase-3 activation was seen in other tissues. These findings suggest that high environmental concentrations of atrazine specifically induce apoptosis in reproductive tissues, which could account for the decline in the number of offspring in D. magna exposed to high concentrations of atrazine.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.273
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.215
Teacher spread0.168 · 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

Citations0
Published2022
Admission routes3
Has abstractyes

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