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Record W2806817698 · doi:10.3389/fphar.2018.00666

Molecular Markers Associated With Chemical Analysis: A Powerful Tool for Quality Control Assessment of Copalchi Medicinal Plant Complex

2018· article· en· W2806817698 on OpenAlexfundno aff
Sol Cristians, Robert Bye, Jorge Nieto‐Sotelo

Bibliographic record

VenueFrontiers in Pharmacology · 2018
Typearticle
Languageen
FieldChemistry
TopicHeavy Metals in Plants
Canadian institutionsnot available
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoComisión Nacional de Áreas Naturales ProtegidasConsejo Nacional de Ciencia y Tecnología, GuatemalaConsejo Nacional de Ciencia y TecnologíaCommission for Environmental Cooperation
KeywordsQuality (philosophy)Computational biologyMedicineBiologyBiotechnologyTraditional medicinePhysics

Abstract

fetched live from OpenAlex

The copalchi complex, Hintonia latiflora, H. standleyana and Exostema caribaeum, is widely used in Mexico for treating diabetes and gastrointestinal disorders. The first therapeutic use for H. latiflora bark was registered in the “Florentine Codex” in the 16th century. The latest pharmacological and phytochemical studies revealed that the infusion of the leaves have hypoglycemic, antihyperglycemic and gastroprotective activities. For these reasons the monograph of the main copalchi species, H. latiflora, was recently added to the Mexican Herbal Pharmacopoeia. Nevertheless, quality control parameters are focused to the bark but not to the leaves. Moreover, information about other Rubiaceae species is needed. The main goal of this study was to generate molecular and chemical markers for quality control of the copalchi complex raw material. In addition, the resolution of the taxonomical ambiguity between H. latiflora and H. standleyana, as well as the testing of the molecular and chemical markers in different geographical batches, were aims of this study. The molecular markers and chemical profiles of the leaf infusions were generated considering three different populations for H. latiflora and separate individuals of the three species (HL, n=10; HS, n=3; EC, n=4). The molecular markers matK, rbcL, trnH-psbA, rpl32-trnL and ITS2 were tested for their discriminating capabilities. Chemical profiles of the leaf infusions were obtained by means of HPLC analyses using chlorogenic acid and 4-phenylcoumarins as chemical markers. The concatenated sequence of the molecular markers trnH-psbA, rpl32-trnL and ITS2 clearly distinguished the three taxa, clarifying the taxonomical ambiguity of the Hintonia genus. Additionally, the chemical profiles allowed the unequivocal identification of each species supporting the molecular results; the geographical origin of the samples did not modify neither the chemical profiles nor the concatenated sequence of H. latiflora, suggesting that it is a robust identity test. The complementary use of molecular and chemical markers will assure the quality of plant material used in traditional medicine for therapeutic purposes, and should be valuable new information for the National Health authorities as a part of the Mexican Herbal Pharmacopoeia.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.350
Teacher spread0.331 · 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 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

Citations13
Published2018
Admission routes1
Has abstractyes

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