MétaCan
Menu
Back to cohort
Record W2120669459 · doi:10.1128/iai.00491-06

Interleukin-10 Inhibits Gram-Negative-Microbe-Specific Human Receptor Activator of NF-κB Ligand-Positive CD4 <sup>+</sup> -Th1-Cell- Associated Alveolar Bone Loss In Vivo

2006· article· en· W2120669459 on OpenAlexfundno aff
Xiaoxia Zhang, Yen-Tung A. Teng

Bibliographic record

VenueInfection and Immunity · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial ResearchCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of Rochester
KeywordsBiologyIn vivoActivator (genetics)ReceptorLigand (biochemistry)MicrobiologyCytokineImmunologyMolecular biologyBiochemistry

Abstract

fetched live from OpenAlex

To study anti-inflammatory cytokine effects on RANKL+-T-cell-mediated osteoclastogenesis in vivo, we injected human interleukin-10 (hIL-10) into pathogen-infected HuPBL-NOD/SCID mice. The results show significantly decreased RANKL+ Th1-associated alveolar bone loss and coexpression of human gamma interferon (hIFN-gamma) and human macrophage colony-stimulating factor, but not hIL-4, in RANKL+ Th cells compatible with those from successfully treated aggressive periodontitis subjects. Thus, there are critical cytokine interactions linking hIFN-gamma+ Th1 cells to RANKL-RANK/OPG signaling for periodontal osteoclastogenesis in vivo.

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 score0.036
Threshold uncertainty score0.986

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 head0.006
GPT teacher head0.224
Teacher spread0.217 · 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

Citations49
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueInfection and ImmunitySame topicBone Metabolism and DiseasesFrench-language works237,207