MétaCan
Menu
Back to cohort
Record W2083855046 · doi:10.1002/tox.20368

Impact of degradation products of sulfamethoxazole on mammalian cultured cells

2008· article· en· W2083855046 on OpenAlexaff
Viviane Yargeau, Jennifer Caitlin Huot, Angela Rodayan, Léonie Rouleau, Ranjan Roy, Richard L. Leask

Bibliographic record

VenueEnvironmental Toxicology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsMontreal Heart InstituteMcGill University
Fundersnot available
KeywordsDegradation (telecommunications)ChemistrySulfamethoxazoleSulfanilamideBiodegradationToxicityMicrobial biodegradationEnvironmental chemistryNuclear chemistryFood scienceMicroorganismBacteriaBiochemistryAntibioticsOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Sulfamethoxazole (SMX) is a widely used antibiotic which has been detected in surface water samples in the ng/L range and also detected in drinking water samples. To limit the environmental impact, ozonation treatment of waste streams has been proposed. However, the degradation products created by ozonation as well as their toxicity have not been reported. In this study, we investigated the degradation products of SMX formed during ozonation and the effects of these products on mammalian cultured cells. In addition to alcohols and nitrates, sulfanilamide was identified as the larger molecular weight compound of the degradation products detected. Cells exposed to the degradation products of SMX maintained their polyhedral geometry longer than the control cells. Proliferation of the cells exposed to the degradation products was not negatively affected when compared with the control cells. The results of this study show that bioactive degradation products can be formed by ozonation of SMX.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.288
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental ToxicologySame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207