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Record W4392397108 · doi:10.18103/mra.v12i2.5049

Anti-Inflammatory Effect of Extracts of Inonotus obliquus and Microalgae

2024· article· en· W4392397108 on OpenAlex
Sajeev Wagle, Wasitha P. D. W. Thilakarathna, Julie Lee, H.P. Vasantha Rupasinghe

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

VenueMedical Research Archives · 2024
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInonotus obliquusTraditional medicineBiologyBotanyChemistryMicrobiologyMedicine

Abstract

fetched live from OpenAlex

Chaga mushroom (Inonotus obliquus) and marine microalgae are two emerging natural products with many potential physiological health benefits. The aim of this study was to investigate the anti-inflammatory effects of two extracts prepared from Chaga mushroom and microalgae using lipopolysaccharide-stimulated RAW 264.7 murine macrophage cell model. The Chaga mushroom extract dose-dependently reduced the production of proinflammatory biomarkers of interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-α). At a high concentration of 500 µg/L, Chaga mushroom extract significantly suppressed cyclooxygenase-2 levels. Similarly, the extract of microalgae suppressed the secretion of IL-6 and TNF-α by lipopolysaccharide-induced macrophages. Both extracts had no significant impact on the secretion of anti-inflammatory IL-4 production. These results suggest that extracts of Chaga mushroom and microalgae can be used in developing anti-inflammatory natural health products.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.468
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.373
Teacher spread0.349 · 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