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Record W2119236645 · doi:10.1177/154405910708600914

Hemoglobin and LPS Act in Synergy to Amplify the Inflammatory Response

2007· article· en· W2119236645 on OpenAlexaff
Charles Bodet, Fatiha Chandad, Daniel Grenier

Bibliographic record

VenueJournal of Dental Research · 2007
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFusobacterium nucleatumHemoglobinPeriodontitisPorphyromonas gingivalisTumor necrosis factor alphaLipopolysaccharideBacteroidaceaeImmunologyChemistryFusobacteriumInterleukin 6InflammationMedicineMicrobiologyBacteroidesInternal medicineBiologyBacteria

Abstract

fetched live from OpenAlex

Vascular disruption and bleeding during periodontitis likely increase the levels of hemoglobin in gingival crevicular fluid. The aim of this study was to investigate the effect of hemoglobin on the inflammatory responses of human macrophages stimulated with lipopolysaccharides (LPS) isolated from periodontopathogens. The production of interleukin-1 beta (IL-1beta), IL-6, IL-8, and tumor necrosis factor alpha (TNF-alpha) by macrophages following challenges with Porphyromonas gingivalis and Fusobacterium nucleatum LPS in the presence or absence of human hemoglobin was analyzed by ELISA. The effect of hemoglobin on LPS-binding to macrophages was evaluated with (3)H-LPS. Hemoglobin and LPS from periodontopathogens acted in synergy to stimulate the production of high levels of IL-1beta, IL-6, IL-8, and TNF-alpha by macrophages. Hemoglobin also enhanced LPS-binding to macrophages. This study suggests that hemoglobin contributes to increases in the levels of pro-inflammatory mediators in periodontal sites by acting in synergy with LPS from periodontopathogens, thus favoring the progression of periodontitis.

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)0.015
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.043
GPT teacher head0.411
Teacher spread0.368 · 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

Citations25
Published2007
Admission routes1
Has abstractyes

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