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Record W4410426077 · doi:10.1016/j.neo.2025.101173

Saturated fat exacerbates mitochondrial dysfunction through remodelling of ATP production and inflammation in Barrett’s oesophagus compared to monounsaturated fat, particularly in contrast to oesophageal adenocarcinoma

2025· article· en· W4410426077 on OpenAlexaff
Kathleen A. J. Mitchelson, Fiona O’Connell, Kieran Wynne, David Matallanas, Jacintha O’Sullivan, Helen M. Roche

Bibliographic record

VenueNeoplasia · 2025
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsTrinity College
FundersBreakthrough Cancer ResearchScience Foundation Ireland
KeywordsBarrett's oesophagusInflammationAdenocarcinomaInternal medicineGastroenterologyMedicinePathologyEndocrinologyCancer

Abstract

fetched live from OpenAlex

Obesity-related oesophageal adenocarcinoma (OAC), arising from Barrett's oesophagus (BO), incidence rates are rising coincident with high-fat diets. However, adipose tissue phenotype drives metabolic characteristics. Prior feeding studies demonstrated that obesogenic diets enriched in saturated fatty acids (SFA) induce a more adverse metabolic and pro-inflammatory adipose phenotype, compared to monounsaturated fatty acids (MUFA) enriched high-fat diets, despite equal obesity. We hypothesise that different fatty acids may alter the progression of BO to OAC, wherein SFA may be more pathogenic compared to MUFA. Proteomic analysis shows that SFA, not MUFA, increases fatty acid metabolism, oncogenic signalling, and mitochondrial respiratory chain to a greater extent in BO but not in OAC cells. Cellular metabolic analysis validated proteomic findings to show mitochondrial dysfunction in BO but showed an increase in glycolysis in OAC following SFA treatment compared to MUFA. Additionally, it showed a decrease in mitochondrial ATP production following treatment of SFA in BO and OAC cells. Reduction of SFA intake may be beneficial as a supplementary treatment approach to manage and/or prevent OAC progression.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.286
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes1
Has abstractyes

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