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Record W4388850922 · doi:10.1111/acel.14041

Age‐related nitration/dysfunction of myogenic stem cell activator HGF

2023· article· en· W4388850922 on OpenAlexaff
Alaa Elgaabari, Nana Imatomi, Hirochika Kido, Takashi Nakashima, Shoko Okuda, Yoshitaka Manabe, Shoko Sawano, Wataru Mizunoya, Ryuki Kaneko, Sakiho Tanaka, Takahiro Maeno, Yuji Matsuyoshi, Miyumi Seki, So Kuwakado, Kahona Zushi, Nasibeh Daneshvar, Mako Nakamura, Takahiro Suzuki, Kenji Sunagawa, Judy E. Anderson, Ronald E. Allen, Ryuichi Tatsumi

Bibliographic record

VenueAging Cell · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Manitoba
FundersJapan Society for the Promotion of ScienceSEI Group CSR FoundationUehara Memorial Foundation
KeywordsHepatocyte growth factorBiologySarcopeniaCell biologyStem cellExtracellularMuscle atrophyNitrationInternal medicineEndocrinologySkeletal muscleReceptorBiochemistryChemistryMedicine

Abstract

fetched live from OpenAlex

Mechanical perturbation triggers activation of resident myogenic stem cells to enter the cell cycle through a cascade of events including hepatocyte growth factor (HGF) release from its extracellular tethering and the subsequent presentation to signaling-receptor c-met. Here, we show that with aging, extracellular HGF undergoes tyrosine-residue (Y) nitration and loses c-met binding, thereby disturbing muscle homeostasis. Biochemical studies demonstrated that nitration/dysfunction is specific to HGF among other major growth factors and is characterized by its locations at Y198 and Y250 in c-met-binding domains. Direct-immunofluorescence microscopy of lower hind limb muscles from three age groups of rat, provided direct in vivo evidence for age-related increases in nitration of ECM-bound HGF, preferentially stained for anti-nitrated Y198 and Y250-HGF mAbs (raised in-house) in fast IIa and IIx myofibers. Overall, findings highlight inhibitory impacts of HGF nitration on myogenic stem cell dynamics, pioneering a cogent discussion for better understanding age-related muscle atrophy and impaired regeneration with fibrosis (including sarcopenia and frailty).

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 score0.008
Threshold uncertainty score0.373

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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