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Record W1989100502 · doi:10.1177/154405910608500503

Osteopontin and Mucosal Protection

2006· review· en· W1989100502 on OpenAlexaff
Jaro Sodek, A. Paes Batista Da Silva, Ron Zohar

Bibliographic record

VenueJournal of Dental Research · 2006
Typereview
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOsteopontinImmune systemWound healingInflammationBiologyImmunologyRespiratory tractCell biologyRespiratory systemAnatomy

Abstract

fetched live from OpenAlex

Protection of mucosal tissues of the oral cavity, intestines, respiratory tract, and urogenital tract from the constant challenge of pathogens is achieved by the combined barrier function of the lining epithelia and specialized immune cells. Recent studies have indicated that osteopontin (OPN) has a pivotal role in the development of immune responses and in the tissue destruction and the subsequent repair processes associated with inflammatory diseases. While expression of OPN is increased in immune cells--including neutrophils, macrophages, T- and B-lymphocytes--and in epithelial, endothelial, and fibroblastic cells of inflamed tissues, deciphering the specific functions of OPN has been difficult. In part, this is due to the broad range of biological activities of OPN that are mediated by multiple receptors which recognize several signaling motifs whose activities are influenced by post-translational modifications and proteolytic processing of OPN. Understanding the role of OPN in mucosal inflammation is further complicated by its contributions to the barrier function of the lining epithelia and the complexity of the specialized mucosal immune system. In an attempt to provide some insights into the involvement of OPN in mucosal diseases, this review summarizes current knowledge of the biological activities of OPN involved in the development of inflammatory responses and in wound healing, and indicates how these activities may affect the protection of mucosal tissues.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.277
GPT teacher head0.507
Teacher spread0.230 · 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 designOther design
Domainnot available
GenreReview

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

Citations81
Published2006
Admission routes1
Has abstractyes

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