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Record W2583820511 · doi:10.1093/ofid/ofw172.44

Evaluation of the Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry for the Identification of Cystic Fibrosis Pathogens

2016· article· en· W2583820511 on OpenAlexaff
Nancy Nashid, Yvonne Yau

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnterobacteriaceae and Cronobacter Research
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineMass spectrometryCystic fibrosisIdentification (biology)Time-of-flight mass spectrometryPathogenic organismChromatographyIonizationMicrobiologyInternal medicineBiologyPhysicsChemistry

Abstract

fetched live from OpenAlex

Background. Accurate and timely identification of organisms recovered from respiratory specimens of cystic fibrosis (CF) patients is crucial for effective management. Identification of nonfermenting Gram-negative bacilli (NFGNB) from respiratory cultures of CF patients is challenging; traditional biochemical tests, APINE, 16S rRNA sequencing, or a combination of these methods are used for identification of these organisms. Few studies have validated the use of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of NFGNB in CF patients. Methods. Two hundred forty NFGNB were isolated from respiratory specimens of CF patients at the Hospital For Sick Children between January 2013 and June 2015. Frozen isolates were subcultured onto 5% sheep blood agar before analysis was performed using the Burker Microflex LT MS system and interpreted with the Biotyper software (version 3.1). Reference identification was by partial 16S rRNA gene amplification and sequencing. Organisms identified were as follows: Achromobacter (64), Burkholderia (Burkholderia cepacia complex [BCC] [34], Burkholderia multivorans [37], and Burkholderia gladioli [8]), Chryseobacterium (16), Cupriavidus (8), Inquilinus (18), Pseudomonas (15), and Sphingobacterium (8) species. Others were as follows: Acinetobacter (5), Bordetella (3), Comamonas (1), Delftia (1), Elizabethkingia (5), Moraxella (1), Neisseria (2), Pandoraea (4), Pantoea (1), Ralstonia (4), and Stenotrophomonas (5). Results. The MALDI-TOF MS correctly identified 100% of the NFGNB isolates to genus level. All isolates of B gladioli, Inquilinus limosus, Pseudomonas aeruginosa, Ralstonia species, Stenotrophomonas maltophilia, and Sphingobacterium species were also correctly identified to species level. Although MALDI-TOF MS provided identification to species level for some of the Achromobacter, Chryseobacterium, Elizabethkingia, and Pandoraea isolates, the accuracy of these identifications cannot be confirmed due to limitations of partial 16S rRNA sequencing. The MALDI-TOF MS accurately identified B multivorans but cannot reliably provide genomovar typing of other BCC. Conclusion. The MALDI-TOF MS accurately identified NFGNB, which are challenging to identify by conventional methods from CF respiratory specimens to the genus level. Further molecular characterization is still required to appropriately speciate certain genera. Disclosures. All authors: No reported disclosures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.297
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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
Published2016
Admission routes1
Has abstractyes

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