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B lymphocytes inhibit human osteoclastogenesis by secretion of TGF?

2000· article· en· W1980205607 on OpenAlexaff
M. Neale Weitzmann, Simone Cenci, Jeff Haug, Christopher Brown, John F. DiPersio, Roberto Pacifici

Bibliographic record

VenueJournal of Cellular Biochemistry · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsUniversity of Calgary
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute on AgingNational Institutes of HealthFoundation for Skin ResearchHospital Research Foundation
KeywordsCell biologyStromal cellOsteoclastSecretionCytokineTransforming growth factorBiologyChemistryImmunologyCancer researchIn vitroEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

The role of B lymphocytes in osteoclast (OC) formation is controversial, because both stimulatory and inhibitory effects of B-lineage cells on osteoclastogenesis and life span have been reported. In this study, we have investigated the effects of mature B cells on human osteoclastogenesis using cultures of peripheral blood stem cells (PBSC), a system that generates functional OCs in the absence of stromal cells. We report that B cells inhibit the formation of OCs and shorten the life span of mature OCs by secreting transforming growth factor beta (TGFbeta), a factor that induces apoptosis in these cells. The antiosteoclastogenic effects of B cells are abolished by addition of anti-TGFbeta antibody to osteoclast cultures and mimicked by treatment of B cell-deprived PBSC cultures with recombinant TGFbeta, thus confirming TGFbeta as the B cell produced antiosteoclastogenic activity. Thus, the ability of B cells to downregulate osteoclastogenesis by secretion of the apoptotic cytokine TGFbeta provides new insights into the ability of immune cells to regulate OC formation under basal and inflammatory conditions.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.206
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 source (direct Gemma or distilled Codex), 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

Citations73
Published2000
Admission routes1
Has abstractyes

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