MétaCan
Menu
Back to cohort
Record W2015997966 · doi:10.1039/c3mt00186e

Analysis of the biological response of mouse liver (Mus musculus) exposed to As2O3 based on integrated -omics approaches

2013· article· en· W2015997966 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMetallomics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsnot available
FundersNational Research Council CanadaMinisterio de Economía y Competitividad
KeywordsComputational biologyBiologyOmicsBioinformatics

Abstract

fetched live from OpenAlex

Organic and inorganic mass spectrometries were used to investigate the biochemical response of mice (Mus musculus) to inorganic arsenic exposure using liver as the target organ. The toxicological effects of trivalent inorganic arsenic after oral administration (3 mg kg(-1) body weight and per day) were investigated over a period of 7 days using metallomics, metabonomics and redox proteomics approaches. Size-exclusion chromatography (SEC) with ICP-MS detection was combined with anion exchange chromatography (AEC) to characterize the biological response of the exposed mice. On the other hand, direct infusion mass spectrometry (DI-ESI-QTOF-MS) of polar and lipophilic extracts using positive and negative modes of acquisition (ESI+/ESI-) provided information about time-dependent changes in endogenous metabolites identified by Partial Least Square-Discriminant Analysis (PLS-DA). Finally, the study has been complemented with the evaluation of up/down-regulation of enzymes related to oxidative stress such as superoxide dismutase (SOD), glutathione reductase (GR), catalase (CAT) and peroxidases in connection with metal toxicity issues. The results show that the inorganic arsenic methylation in the liver may reach the saturation point upon chronic exposure to the element. On the other hand, SEC-ICP-MS coupling provided information about metal containing-proteins and metabolites related to arsenic exposure (metallomics) which has been correlated with the changes in the global metabolism (metabonomics), also considering their consequences on the redox status of protein and protein expression (redox proteomics). Our study shows that arsenic causes biochemical pathway alterations, such as energy metabolism (e.g. glycolysis, Krebs cycle), amino acid metabolism, choline metabolism and degradation of membrane phospholipids (apoptosis). This work illustrates the high reliability of the integrated use of organic mass spectrometry for the metabonomic study of biochemical effects induced by As2O3, with inorganic mass spectrometry for metallomic and speciation assessment of arsenic biomethylation in the liver of exposed mice, and redox proteomics to evaluate inhibition of enzymatic activity in different proteins such as superoxide dismutase (SOD), catalase (CAT) and glutathione reductase (GR) caused by this element. In conclusion, the integration of metallomics, metabolomics and redox proteomics results provides a more comprehensive evaluation about the biological response in experiments dealing with exposure to toxic metals.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.043
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.228
Teacher spread0.192 · 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