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Record W4413327930 · doi:10.1016/j.lwt.2025.118361

Sensitive and visual detection for Atlantic salmon in processed foods using PCR-CRISPR/Cas12a system

2025· article· en· W4413327930 on OpenAlexafffund
Chao Ji, Peili Wang, Yihan He, Marti Z. Hua, Sentao Liu, Yue Shi, Henry K. Rotich, Changzhong Li, Liangjuan Zhao, Wenjie Zheng, Xiaonan Lu

Bibliographic record

VenueLWT · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill University
FundersTianjin Science and Technology ProgramTianjin Normal UniversityMcGill University
KeywordsCRISPRFisheryComputational biologyBiologyComputer scienceGeneticsGene

Abstract

fetched live from OpenAlex

In this study, a sensitive and visual PCR-based CRISPR/Cas12a detection method was established to identify Atlantic salmon ingredients in processed foods. A guide RNA (gRNA) was designed based on the mitochondrial genome of Atlantic salmon, with an efficient target site identified within the ATP synthase F0 subunit 6 (ATP6) gene. Specificity test against 9 other species commonly associated with Atlantic salmon adulteration revealed no evidence of cross-reactivity. The developed assay exhibited an absolute detection limit of 0.5 pg and a relative sensitivity of 0.1%. The results were visually interpretable under UV light without the need for complex instrumentation. The reliability of this assay was further confirmed through Sanger sequencing during the authentication of commercial products, highlighting its practical applicability. The PCR-CRISPR/Cas12a assay developed in this study provides a promising tool for specific and sensitive authentication of high-value seafood 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.

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)0.000
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 score0.189
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.007
GPT teacher head0.309
Teacher spread0.302 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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