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Living under natural conditions of ocean acidification entails energy expenditure and oxidative stress in a mussel species

2024· article· en· W4396785508 on OpenAlexaff
Silvia Giorgia Signorini, Marco Munari, Lorenzo Federico, Fiorenza Farè, Manuela Fontana, Donatella Caruso, Rosa Freitas, Sofia Paciello, Ilaria D'Aniello, María Cristina Gambi, Camilla Della Torre

Bibliographic record

VenueMarine Pollution Bulletin · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsUniversité de Montréal
FundersCentro de Estudos Ambientais e Marinhos, Universidade de AveiroUniversità degli Studi di PadovaUniversità degli Studi di MilanoMissouri Press Association
KeywordsMusselOcean acidificationNatural (archaeology)Environmental scienceOxidative stressEnergy expenditureOceanographyEcologyFisheryBiologySeawaterGeology

Abstract

fetched live from OpenAlex

vents system of Castello Aragonese at Ischia Island (Mediterranean Sea). Individuals of M. galloprovincialis were sampled in three sites along the pH gradient (8.10, 7.7 and up to <7.4). Untargeted metabolomics and biochemical endpoints related to energetic metabolism, oxidative stress/damage, neurotoxicity and immune defense were analyzed. Corrosion of the valves occurred at low pH. A separation of the metabolome was observed along the pH gradient. Metabolites belonging to amino acids, nucleosides, lipids and organic osmolytes were significantly reduced in the organisms from the most acidified sites. The content of reactive oxygen species and the activity of glutathione peroxidase were reduced in organisms from the acidified sites compared to ambient pH, and no oxidative damage was induced. Overall results suggested the presence of an energy cost underpinning long-term survival in acidified conditions for this species.

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 categoriesInsufficient 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 score0.387
Threshold uncertainty score0.997

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)0.0040.000

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 head0.009
GPT teacher head0.217
Teacher spread0.209 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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