MétaCan
Menu
← Back to cohort
Record W7133205964 · doi:10.65760/ajoh.v1i2.2

ONE HEALTH EVALUATION OF ANTIMICROBIAL RESIDUES AND RESISTANCE IN ANIMAL-SOURCE FOODS AND THEIR IMPLICATIONS ON NUTRITIONAL STATUS IN SOKOTO STATE, NIGERIA

2025· article· W7133205964 on OpenAlexaboutno aff
Khadijah Abdullahi Bagudu, Usman Zakari, Amina Jiya, Salamatu YUSUF, Ahmad Maryam Muhammad, Ismail Akeem Adesola, Buhari Musa Yusuf

Bibliographic record

VenueAfrican Journal of One Health ISSN · 2025
Typearticle
Language
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAntimicrobialAntibiotic resistanceAntimicrobial stewardshipGrey literatureMultiple drug resistanceDrug resistancePublic health

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) is a major global public health challenge closely linked to antimicrobial use in food-producing animals. In Sokoto State, Nigeria, animal-source foods (ASFs) are essential for nutrition but may also serve as vehicles for antimicrobial residues and resistant organisms, with potential implications for food safety and nutritional well-being. This systematic review synthesized published and grey literature to identify, appraise, and summarize evidence on antimicrobial residues and resistant bacteria in ASFs in Sokoto State. Electronic databases including PubMed, Scopus, Web of Science, African Journals Online, and Google Scholar were searched, complemented by grey literature, for studies published between January 2000 and March 2025. Eligible studies reported antimicrobial residues or antimicrobial resistance in meat, milk, eggs, or other ASFs. Data extraction followed PRISMA 2020 guidelines, and study quality was assessed using the Newcastle–Ottawa Scale and Cochrane RoB 2.0 tool. Due to substantial methodological heterogeneity, findings were synthesized narratively. Forty-five studies (38 peer-reviewed and 7 grey literature) met the inclusion criteria. Tetracyclines and β-lactams were the most frequently detected antimicrobial residues, with concentrations often exceeding Codex Alimentarius–recommended maximum residue limits. Residue prevalence ranged from 18–94% in meat and 22–89% in milk. Antimicrobial-resistant Escherichia coli, Staphylococcus aureus, and Salmonella spp. were commonly isolated, showing high resistance to tetracycline, ampicillin, and cotrimoxazole, with multidrug resistance frequently reported. Overall, the findings indicate widespread antimicrobial contamination and resistance in ASFs in Sokoto State, underscoring the need for strengthened surveillance, regulatory oversight, and antimicrobial stewardship within a One Health framework

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0110.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.354
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAfrican Journal of One Health ISSN→Same topicPharmaceutical and Antibiotic Environmental Impacts→French-language works237,207→