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Preemptive Effects of Administration of Tualang Honey on Inflammatory Responses in Adult Male Rats

2017· article· en· W2589086420 on OpenAlexvenueno aff
Che Aishah Nazariah Ismail, Che Maraina Che Hussin, Mahaneem Mohamed, Che Badariah Abd Aziz

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsnot available
FundersUniversiti Sains Malaysia
KeywordsPrednisoloneMedicineAnalysis of varianceInflammationMonocyteEdemaPharmacologyInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Background: Honey was reported to reduce pain and inflammation from burn wound. To date, no study has compared between the effects of Tualang honey and prednisolone on inflammatory responses in rats. This study has examined the effects of Tualang honey and prednisolone on inflammatory pain and its associated inflammatory responses secondary to formalin injection.Methods: Twenty-one Sprague-Dawley male rats were randomised into control, Tualang honey (1.2 g/kg) or prednisolone (10 mg/kg)groups. Formalin test was conducted and the rats were sacrificed at four-hours post-formalin injection. Serum was collected for measurement of leukocytecounts and interleukins level. All data were analysed using one-way ANOVA with post-hoc Scheffe’s or Dunnet’s C test. Significance level was taken as less than 0.05.Results: Tualang honey and prednisolone groups had significantly reduced pain behaviour and paw edema compared to control group. Tualang honey group demonstrated a significant increase in blood neutrophil count while prednisolone group had significant reduction in blood lymphocyte and monocyte counts compared to control group. Only interleukin-6 level was significantly reduced in honey group. Both interleukin-6 and -8 levels were significantly reduced in prednisolone group.Conclusions: Tualang honey is comparable to prednisolone in modulating the inflammatory pain responses in rats; however, with regards to local and systemic inflammatory responses, it has differential effects compared to prednisolone.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.113

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.316
Teacher spread0.282 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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