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Record W2169454814 · doi:10.5539/ijb.v6n2p42

Antimicrobial Action of Epidermal Mucus Extract of Clarias gariepinus (Burchell, 1822) Juveniles-Fed Ginger Inclusion in Diet

2014· article· en· W2169454814 on OpenAlexvenueno aff
A. A. Nwabueze

Bibliographic record

VenueInternational Journal of Biology · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
Fundersnot available
KeywordsClarias gariepinusMucusAntimicrobialBiologyMicrobiologyPathogenic bacteriaFood scienceBacteriaFish <Actinopterygii>EcologyFishery

Abstract

fetched live from OpenAlex

The antimicrobial activity of epidermal mucus extract of C. gariepinus juveniles-fed ginger inclusion in diet was investigated and compared with the activity of epidermal mucus extract of C. gariepinus juveniles (control) without ginger in diet. This study demonstrates the antimicrobial role of ginger in improving protection of fish against bacterial infection as shown by the higher zones of inhibition observed for epidermal mucus extract of fish-fed ginger in diet as compared with control. Zones of inhibition for epidermal mucus of treatment fish were 30.7 mm, 29.8 mm, 26.3 mm and 19.3 mm for Bacillus, Escherichia, Staphylococcus and Streptococcus species respectively. Though these values were not significantly (P > 0.05) higher than those obtained for the control fish with zones of inhibition of 25 mm, 11.2 mm, 9.0 mm and 7.3 mm for Bacillus, Escherichia, Staphylococcus and Streptococcus species respectively, the higher values recorded for the treatment fish shows that ginger inclusion in fish diet had an antibiotic effect against isolates of bacteria in fish samples from cultured ponds. The addition of ginger in C. gariepinus diet is encouraged as its action is indicative of the potentials of ginger in preventing emergence of resistant bacteria and improving the antimicrobial role of fish mucus and therefore the quality of C. gariepinus.

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)0.000
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 score0.192
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.016
GPT teacher head0.289
Teacher spread0.272 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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