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Record W3212570433 · doi:10.3390/foods10112705

Development of Hydrolysis Probe-Based qPCR Assays for Panax ginseng and Panax quinquefolius for Detection of Adulteration in Ginseng Herbal Products

2021· article· en· W3212570433 on OpenAlexaff
Prasad Kesanakurti, Subramanyam Ragupathy, Adam C. Faller, S. Dhivya, Francesco Buongiorno, Isabella Della Noce, Zhengfei Lu, Yanjun Zhang, Steven G. Newmaster

Bibliographic record

VenueFoods · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGinsengRepeatabilityTraditional medicineChemistryConsumer safetyChromatographyMedicineRisk analysis (engineering)

Abstract

fetched live from OpenAlex

Authentication of Panax ginseng and Panax quinquefolius products is important to be able to mitigate instances of adulteration and substitution that exist within the international supply chain of ginseng. To address this issue, species-specific hydrolysis probe qPCR assays were developed and validated for both P. ginseng and P. quinquefolius herbal dietary supplements. Performance of the probe-based assays was evaluated using analytical validation criteria, which included evaluation of: (1) specificity, in selectively identifying the target species; (2) sensitivity, in detecting the lowest amount of the target material; and (3) repeatability and reproducibility of the method in detecting the target species in raw materials on a real-time PCR platform (reliability). The species-specific probes were developed and successfully passed the validation criteria with 100% specificity, 80–120% efficiency and 100% reliability. The methods developed in this study are fit for purpose, rapid, and easy to implement in quality assurance programs; authentication of ginseng herbal supplements is possible, even with extracts where DNA is fragmented and of low quality and quantity.

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 score0.040
Threshold uncertainty score0.356

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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
Published2021
Admission routes1
Has abstractyes

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