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Record W4406606816 · doi:10.1016/j.microc.2025.112827

Electrochemical determination of Penicillin G in biological matrix based on the carbon paste electrode modified with a molecular imprinted polymer

2025· article· en· W4406606816 on OpenAlexafffund
Babak Tavana, Carlos A. Ramírez, Aicheng Chen

Bibliographic record

VenueMicrochemical Journal · 2025
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsElectrochemistryPolymerElectrodeMaterials scienceMatrix (chemical analysis)Carbon fibersPenicillinMolecularly imprinted polymerChemical engineeringChemistryComposite materialOrganic chemistryCatalysisComposite numberPhysical chemistrySelectivityAntibiotics

Abstract

fetched live from OpenAlex

• Design of an electrochemical sensor based on MIP for PNCG in biological matrices. • The developed MIP for PNCG works selectively with an acceptable LOD in blood plasma. • The analytical method has been validated based on the bioanalytical validation guidance. • The developed MIP-CPE sensor is highly reliable, cost-effective, durable, and rapid. • The sensor can replace chromatographic methods for testing pharmaceutical compounds. An accurate and sensitive electrochemical sensor was developed based on a carbon paste electrode modified with a molecularly imprinted polymer (CPE-MIP) for the determination of Penicillin G (PNCG). A suitable MIP for PNCG was synthesized and characterized using spectroscopic and electrochemical methods. The electrochemical behavior of PNCG was investigated, and the composition, extraction efficiency, and electrochemical parameters of the electrode were thoroughly assessed. The developed CPE-MIP sensor was tested in human blood plasma, demonstrating reproducibility, repeatability, stability, selectivity, minimal matrix effects, and satisfactory recovery. Two dynamic linear ranges were observed: 5.0 × 10 −8 –1.0 × 10 −6 M and 1.0 × 10 −6 –1.0 × 10 −4 M, with a limit of detection (LOD) of 3.8 × 10 −8 M. The results demonstrate that the developed CPE-MIP sensor is highly reliable, cost-effective, rapid, environmentally friendly, and selective for PNCG determination.

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 score0.102
Threshold uncertainty score0.822

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 science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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

Citations5
Published2025
Admission routes2
Has abstractyes

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