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Record W2590308841 · doi:10.1039/c7ib00002b

Receptor for hyaluronan mediated motility (RHAMM/HMMR) is a novel target for promoting subcutaneous adipogenesis

2017· article· en· W2590308841 on OpenAlexafffund
Sajad Bahrami, Cornelia Tölg, Teresa Peart, Caitlin Symonette, Mandana Veiseh, Joseph Umoh, David W. Holdsworth, James B. McCarthy, Leonard G. Luyt, Mina J. Bissell, Arjang Yazdani, Eva A. Turley

Bibliographic record

VenueIntegrative Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsRobarts Clinical TrialsWestern UniversityVictoria Hospital
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of HealthBreast Cancer Research Foundation
KeywordsAdipogenesisMotilityReceptorCell biologyHyaluronic acidChemistryBiologyEndocrinologyBiochemistryAnatomyMesenchymal stem cell

Abstract

fetched live from OpenAlex

; p < 0.05) and mammary fat pad size (45 ± 11 mg above control background, p = 0.002) in female rats. This effect lasted >5 weeks as detected by micro CT imaging and perilipin 1 mRNA expression. RHAMM expression suppresses while blocking peptides promote expression of PPARγ, C/EBP and their target genes. Blocking RHAMM function by peptide injection or topical application is a novel and minimally invasive method for potentially promoting subcutaneous adipogenesis in lipodystrophic diseases and a complementary tool to subcutaneous fat augmentation techniques.

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 score0.003
Threshold uncertainty score0.011

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)0.0030.001

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 head0.030
GPT teacher head0.335
Teacher spread0.304 · 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

Citations42
Published2017
Admission routes2
Has abstractyes

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