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Record W3084991736 · doi:10.15252/embj.2019103420

Re‐equilibration of imbalanced NAD metabolism ameliorates the impact of telomere dysfunction

2020· article· en· W3084991736 on OpenAlexaff
Chongkui Sun, Kun Wang, Amanda J. Stock, Yi Gong, Tyler G. Demarest, Beimeng Yang, Neelam Giri, Lea Harrington, Blanche P. Alter, Sharon A. Savage, Vilhelm A. Bohr, Yie Liu

Bibliographic record

VenueThe EMBO Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCalcium signaling and nucleotide metabolism
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersDivision of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institute on Aging
KeywordsLibrary scienceGerontologyMedicineFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Short telomeres are a principal defining feature of telomere biology disorders, such as dyskeratosis congenita (DC), for which there are no effective treatments. Here, we report that primary fibroblasts from DC patients and late generation telomerase knockout mice display lower nicotinamide adenine dinucleotide (NAD) levels, and an imbalance in the NAD metabolome that includes elevated CD38 NADase and reduced poly(ADP-ribose) polymerase and SIRT1 activities, respectively, affecting many associated biological pathways. Supplementation with the NAD precursor, nicotinamide riboside, and CD38 inhibition improved NAD homeostasis, thereby alleviating telomere damage, defective mitochondrial biosynthesis and clearance, cell growth retardation, and cellular senescence of DC fibroblasts. These findings reveal a direct, underlying role of NAD dysregulation when telomeres are short and underscore its relevance to the pathophysiology and interventions of human telomere-driven diseases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.218

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)0.0000.000

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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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 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

Citations64
Published2020
Admission routes1
Has abstractyes

Explore more

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