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Record W3186872996 · doi:10.1096/fba.2021-00058

Browning of adipose tissue and increased thermogenesis induced by Methotrexate

2021· article· en· W3186872996 on OpenAlexfundno aff
Narendra Verma, Luce Pèrié, Carmen Corciulo, Philipp Leucht, Bhama Ramkhelawon, Bruce N. Cronstein, Elisabetta Mueller

Bibliographic record

VenueFASEB BioAdvances · 2021
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthNational Center for Advancing Translational SciencesYork University
KeywordsThermogenesisAdipose tissueMethotrexateInflammationRheumatoid arthritisInternal medicineEndocrinologyImmune systemHomeostasisBrown adipose tissueArthritisBiologyMedicineImmunology

Abstract

fetched live from OpenAlex

Methotrexate (MTX) is widely used for the treatment of rheumatoid arthritis due to its well-known anti-inflammatory role in immune cells but its impact on brown and beige adipose tissue biology has not yet been investigated. Here, we present the novel evidence that MTX treatment increases the gene expression of thermogenic genes in brown and beige adipose tissues in a fat cell autonomous manner. Furthermore, we show that treatment of mice with MTX is associated with cold resistance, improved glucose homeostasis, decreased inflammation, and reduced hepatosteatosis in high-fat diet states. Overall, our data provide novel evidence of a role of MTX on thermogenic tissues not previously appreciated.

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 score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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