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Record W1988034742 · doi:10.1039/b212797k

Studies of cisplatin and hemoglobin interactions using nanospray mass spectrometry and liquid chromatography with inductively-coupled plasma mass spectrometry

2003· article· en· W1988034742 on OpenAlexafffund
Rupasri Mandal, Christine Teixeira, Xing‐Fang Li

Bibliographic record

VenueThe Analyst · 2003
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryMass spectrometryChromatographyCisplatinTandem mass spectrometryHemoglobinInductively coupled plasma mass spectrometryHigh-performance liquid chromatographyLiquid chromatography–mass spectrometryElectrospray ionizationBiochemistry

Abstract

fetched live from OpenAlex

Interactions of cisplatin with hemoglobin (Hb) were studied using both nanoelectrospray mass spectrometry (nanoESI-MS) and a combination of size exclusion high performance liquid chromatography with inductively coupled plasma mass spectrometry (HPLC-ICPMS). Size exclusion HPLC separation of free and protein-bound cisplatin followed by simultaneous monitoring of 195Pt and 57Fe demonstrated the presence of Hb-bound Pt complexes. Nanospray quadrupole time-of-flight mass spectrometry studies of the Hb-cisplatin complexes further demonstrated the specific binding of cisplatin to the alpha-chain, heme-alpha, beta-chain, and heme-beta units of hemoglobin. Accurate mass measurements and tandem mass spectrometry information confirmed the Hb-cisplatin complexes. The formation of Hb-cisplatin complexes was observed at the sub-microM to microM concentration levels of cisplatin, which are relevant to clinical levels. These findings and the techniques developed for cisplatin-Hb interaction studies are useful for understanding of drug-protein interactions.

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 score0.034
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.284
Teacher spread0.262 · 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

Citations31
Published2003
Admission routes2
Has abstractyes

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