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Record W3016626278 · doi:10.1021/acs.analchem.0c00570

Toward the Rational Design of Universal Dual Polarity Matrix for MALDI Mass Spectrometry

2020· article· en· W3016626278 on OpenAlexaff
Penghsuan Huang, Chun‐Ying Huang, Tachun Lin, Li‐En Lin, Ethan Yang, Chuping Lee, Cheng‐Chih Hsu, Pi‐Tai Chou

Bibliographic record

VenueAnalytical Chemistry · 2020
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversité de Montréal
FundersMinistry of Science and Technology
KeywordsChemistryMass spectrometryProtonationMatrix-assisted laser desorption/ionizationAnthranilic acidDeprotonationBiomoleculeMatrix (chemical analysis)Polarity (international relations)Proton affinityDesorptionAnalytical Chemistry (journal)Combinatorial chemistryChromatographyIonPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A series of novel anthranilic acid derivatives I–IV, of which COOH-NH2 (I) and COOH-NHMe (IV) are endowed with acid and base bifunctionality, were designed and synthesized for matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applications in dual polarity molecular imaging of biological samples, particularly for lipids. The heat of protonation, deprotonation, and proton transfer reaction as well as the capability of analyzing biomolecules in both positive and negative ion modes for I–IV were systematically investigated under standard 355 nm laser excitation. The results indicate correlation between dual polarity and acid–base property. Further, COOH-NHMe (IV) showed a unique performance and was successfully applied as the matrix for MALDI-TOF mass spectrometry imaging (MSI) for studying the mouse brain. Our results demonstrate the superiority of COOH-NHMe (IV) in detecting more lipid and protein species compared to commercially available matrices. Moreover, MALDI-TOF MSI results were obtained for lipid distributions, making COOH-NHMe (IV) a potential next generation universal matrix.

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 categoriesInsufficient payload (model declined to judge)
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 score0.939
Threshold uncertainty score0.995

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.038
GPT teacher head0.284
Teacher spread0.246 · 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.

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

Citations33
Published2020
Admission routes1
Has abstractyes

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