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Record W2619911589 · doi:10.1080/17518253.2017.1330904

Gold nanoparticle-enhanced luminol/ferricyanide chemiluminescence system for aristolochic acid-I detection in medicinal plants and slimming products

2017· article· en· W2619911589 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGreen Chemistry Letters and Reviews · 2017
Typearticle
Languageen
FieldMedicine
TopicNephrotoxicity and Medicinal Plants
Canadian institutionsUniversité Laval
FundersZagazig UniversityKing Saud UniversityUniversité Laval
KeywordsChemistryLuminolChemiluminescenceAristolochic acidDetection limitChromatographyFerricyanideColloidal goldNanoparticleBiochemistryNanotechnology

Abstract

fetched live from OpenAlex

Aristolochic acid-I (AA-I) is commonly present as a natural product in medicinal plants such as Asarum and Radix aristolochiae. The misuse of some slimming products and dietary, supplements containing AA-I as a regulator has been reported to cause cancer, acute hepatitis and renal failure. Hence, quality control and quantification of AA-I in these products at a trace level are significantly necessary. In this approach, a simple and accurate sequential injection analysis (SIA) chemiluminescence (CL) detection method was employed for AA-I determination. Gold nanoparticles were used to enhance the CL signal of luminol-ferricyanide-AA-I reaction. The results showed that the proposed method displayed linear relationship of 10–20,000 ng mL−1, (r = 0.9992) with 10 and 3 ng mL−1 as the minimum quantification and detection limits, respectively. The possible interferences such as some common metals, additives and related pharmacological action compounds were tested. The recorded SIA-CL results were statistically assessed and compared to those obtained from other published methods.

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.

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)0.001
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 score0.043
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.027
GPT teacher head0.268
Teacher spread0.241 · 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