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Record W2698514805 · doi:10.15302/j-fase-2017157

Molecular authentication of the traditional Chinese medicine Tongren Dahuoluo Wan and its alternative formulation

2017· article· en· W2698514805 on OpenAlexfundno aff
Jikun Wang, Jing Du, Meng Cao, Yao Lu, Suhua Xie, Jia-Fu Chen, Xingbo Zhao

Bibliographic record

VenueFrontiers of Agricultural Science and Engineering · 2017
Typearticle
Languageen
FieldMedicine
TopicTraditional Chinese Medicine Analysis
Canadian institutionsnot available
FundersWageningen University and ResearchInstitute of GeneticsNational Natural Science Foundation of China
KeywordsAuthentication (law)Traditional medicineTraditional Chinese medicineChinese traditional medicineMedicineComputer scienceAlternative medicineComputer security

Abstract

fetched live from OpenAlex

Tongren Dahuoluo Wan has been a popular traditional Chinese medicine in international pharmaceutical markets for hundreds of years. Leopard bone powder is the key element in its formulation. However, the leopard has been listed for wildlife conservation, which limits the use of the leopard bone supplies. Therefore, an alternative formulation which substitutes leopard bone with zokor bone in the formula of Tongren Dahuoluo Wan is now manufactured. To develop a simple and reliable molecular method for authenticating the two patent medicines, mitochondrial nucleotide polymorphic sites of 12S rRNA, COI and Cytb genes were screened in leopard and zokor bones, and nine pairs of species-specific primers were verified for discriminating the two species. For the patent medicine authentication, we set up a molecular diagnostic assay to resolve the difficulties of low concentration of target DNAs and presence of PCR-inhibitory substances in this complex medicine, and successfully confirmed leopard or zokor content using the nine pairs of species-specific primers. We recommend a common technical strategy for authentication of species origins in traditional Chinese medicine, and discuss the experimental solutions for technical problems of molecular diagnostic assays.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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 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
Published2017
Admission routes1
Has abstractyes

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