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Record W2025175309 · doi:10.1096/fj.14-265744

Adseverin plays a role in osteoclast differentiation and periodontal disease‐mediated bone loss

2015· article· en· W2025175309 on OpenAlexafffund
Hongwei Jiang, Yongqiang Wang, Ana Viniegra, Corneliu Sima, Christopher A. McCulloch, Michael Glogauer

Bibliographic record

VenueThe FASEB Journal · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Science Foundation of Guangdong Province
KeywordsOsteoclastCell biologyPodosomeBone resorptionActinCytoskeletonForminsGelsolinResorptionChemistryActin remodelingActin cytoskeletonBiologyCellBiochemistryGeneticsEndocrinologyIn vitro

Abstract

fetched live from OpenAlex

Osteoclast differentiation and function are highly dependent on the assembly and turnover of actin filaments, but little is known about the roles of actin binding proteins in these processes. Adseverin (Ads), a member of the gelsolin superfamily of actin capping and severing proteins, regulates actin filament turnover and can regulate the turnover of cortical actin filaments of chromaffin cells during exocytosis. Using a conditional Ads knockout mouse model, we confirmed our previous finding in cultured cells that Ads plays a role in osteoclastogenesis (OCG) and actin cytoskeletal organization in osteoclasts. Here we show that Ads is required for osteoclast formation and that when alveolar bone resorption is experimentally induced in mice, genetic deletion of Ads prevents osteoclast-mediated bone loss. Further, when Ads-null osteoclasts are cultured, they exhibit defective OCG, disorganized podosome-based actin filament superstructures, and decreased bone resorption. Reintroduction of Ads into Ads-null osteoclast precursor cells restored these osteoclast defects. Collectively, these data demonstrate a unique and osteoclast-specific role for Ads in OCG and osteoclast function.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.287

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 head0.211
Teacher spread0.203 · 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 designObservational
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

Citations19
Published2015
Admission routes2
Has abstractyes

Explore more

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