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Record W4411673291 · doi:10.1038/s41586-025-09282-7

Addendum: Unravelling cysteine-deficiency-associated rapid weight loss

2025· article· en· W4411673291 on OpenAlexaff
Alan Varghese, Ivan Gusarov, Begoña Gamallo-Lana, Daria Dolgonos, Yatin Mankan, Ilya Shamovsky, Mydia Phan, Rebecca Jones, Maria Gomez-Jenkins, Eileen White, Rui Wang, Drew R. Jones, Thales Papagiannakopoulos, Michael E. Pacold, Adam C. Mar, Dan R. Littman, Evgeny Nudler

Bibliographic record

VenueNature · 2025
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsYork University
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical Sciences
KeywordsAddendumCysteineChemistryBiochemistryPhysiologyBiologyEnzymePhilosophy

Abstract

fetched live from OpenAlex

A study by Lee et al. (Lee, A.H. et al. Cysteine depletion triggers adipose tissue thermogenesis and weight loss. Nat. Metab. https://doi.org/10.1038/s42255-025-01297-8 (2025)) similarly reports a 30% weight loss upon cysteine restriction in a Cse knockout mouse model. Like our findings, they observe depletion of CoA and GSH, strong induction of FGF21, comparable changes in adipose tissue and increased lipid utilization.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.168
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1680.066

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 head0.010
GPT teacher head0.302
Teacher spread0.292 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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