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Record W2256937149 · doi:10.1586/14737140.2016.1121106

New investigations into the stability of Mesna using LC-MS/MS and NMR

2015· article· en· W2256937149 on OpenAlexfundno aff
Dahlia Salman, Julian Swinden, Jean‐Marie Péron, Stephen Barton, Shereen Nabhani‐Gebara

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsnot available
FundersBaxter Healthcare CorporationInternational Society of Oncology Pharmacy Practitioners
KeywordsMesnaIfosfamideChromatographyMass spectrometryMedicineLiquid chromatography–mass spectrometryChemistryCisplatinSurgeryChemotherapy

Abstract

fetched live from OpenAlex

INTRODUCTION: It is important for sarcoma patients to receive the correct dose of Mesna as an adjuvant with ifosfamide to reduce the risk of hemorrhagic cystitis. This paper describes a study conducted to evaluate the physicochemical stability of Mesna for injection formulation over 14 days. METHODS: Mesna samples (n = 4, 20 mg/ml) were incubated in glass vials at 37 + 0.5ºC. Mesna concentrations were determined by liquid chromatography-mass spectrometry (LC-MS/MS), and nuclear magnetic resonance spectroscopy (NMR) was used to detect degradation products. Evaporative losses and pH were also monitored. RESULTS: Our results differed from those published in existing literature. Both LC-MS/MS and NMR indicated that Mesna was unstable. The mean percentage decrease in Mesna concentration was 40% by day 14 of the analysis. The presence of Mesna's dimer Dimesna was detected on day 0 and its concentration increased over time. Dimesna was the only by-product identified. CONCLUSION: Both LC-MS/MS and NMR analyses confirmed the instability of Mesna and its conversion into Dimesna.

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)0.001
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 score0.095
Threshold uncertainty score0.417

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 head0.082
GPT teacher head0.375
Teacher spread0.293 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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