MétaCan
Menu
Back to cohort
Record W2998521554 · doi:10.1016/j.chmed.2019.12.003

Attenuation of inflammation in streptozotocin-induced diabetic rabbits by Matricaria chamomilla oil: A focus on targeting NF-κB and NLRP3 signaling pathways

2019· article· en· W2998521554 on OpenAlexaff
Saeid Saghahazrati, Seyed Abdulmajid Ayatollahi, Farzad Kobarfard, Bagher Minaii Zang

Bibliographic record

VenueChinese Herbal Medicines · 2019
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsUniversity of Winnipeg
FundersOphthalmic Research Center, Shahid Beheshti University of Medical SciencesShahid Beheshti University of Medical Sciences
KeywordsMatricaria chamomillaStreptozotocinDiabetes mellitusIntraperitoneal injectionSalineMedicineInflammationWestern blotEndocrinologyPharmacologyInternal medicineProinflammatory cytokineChemistryTraditional medicineBiochemistry

Abstract

fetched live from OpenAlex

Objectives: against type 1 diabetes mellitus (T1DM) and its potential mechanisms. Methods: , dissolved in 0.2 mL of normal saline). Different doses of chamomile oil (25, 50 and 100 mg/kg) were orally administrated to STZ induced diabetic rabbits for 21 consecutive days. The expression of pro-inflammatory cytokines was determined using ELISA assay. The expression of NF-κB and NLRP3 was measured using Western blot assay. Results: Compared with normal rabbits, STZ-induced diabetic rabbits exhibited significant increased levels of blood glucose and decreased levels of serum insulin that were reversed using middle and high tested dose of chamomile oil. Likewise, STZ-induced diabetic rabbits showed a significant increased expression of NF-κB and NLRP3 proteins in the pancreas tissue that was reversed by high tested dose of chamomile oil. Conclusion: Collectively, our findings demonstrated that chamomile oil possesses anti-hyperglycemic, and anti-inflammatory activities in STZ-induced diabetic rabbits by targeting inflammatory cytokines and NF-κB and NLRP3 signaling pathways.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.246
Teacher spread0.236 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueChinese Herbal MedicinesSame topicNatural Antidiabetic Agents StudiesFrench-language works237,207