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Record W2004080374 · doi:10.1002/jbm.a.32096

Effect of alginate on innate immune activation of macrophages

2008· article· en· W2004080374 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInnate immune systemProinflammatory cytokineLipopolysaccharideMacrophageInflammationImmune systemStimulationCell biologyTumor necrosis factor alphaImmunologyMaterials scienceBiologyBiochemistryNeuroscienceIn vitro

Abstract

fetched live from OpenAlex

Alginate, a natural polysaccharide, has been widely used in tissue engineering and drug delivery, but like other biomaterials, it causes inflammation by unknown mechanisms. We hypothesized that alginate would stimulate innate immune responses through macrophage receptors. In this study, we showed that sodium alginate induced activation of macrophage-like cells (RAW264.7) through the NF-kappaB pathway. Production of proinflammatory cytokines, such as IL-1beta, IL-6, IL-12, and TNF-alpha was time and dose-dependent. Treatment with alginate solution caused responses that closely paralleled stimulation by lipopolysaccharide in timing and magnitude. These data suggest that sodium alginate causes innate immune responses through NF-kappaB activation and likely activates the same pathways as pathogen recognition.

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.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.347
Teacher spread0.318 · 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