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Record W2625307487 · doi:10.1021/acs.jproteome.7b00157

Targeted Metabolic Profiling of Post-Mortem Brain from Infants Who Died from Sudden Infant Death Syndrome

2017· article· en· W2625307487 on OpenAlexaff
Stewart F. Graham, Onur Türkoğlu, Praveen Kumar, Ali Yılmaz, Trent C. Bjorndahl, Rupasri Mandal, David S. Wishart, Ray Bahado‐Singh

Bibliographic record

VenueJournal of Proteome Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of Alberta
FundersNational Institutes of Health
KeywordsSudden infant death syndromeMedicineBiomarkerMetabolomicsPathophysiologyDiseaseBioinformaticsInternal medicinePathologyPediatricsBiologyGenetics

Abstract

fetched live from OpenAlex

Currently little is known about the underlying pathophysiology associated with SIDS, and no objective biomarkers exist for the accurate identification of those at greatest risk of dying from SIDS. Using targeted metabolomics, we aim to profile the medulla oblongata of infants who have died from SIDS ( n = 16) and directly compare their biochemical profile with age matched controls. Combining data acquired using 1 H NMR and targeted DI-LC-MS/MS, we have identified fatty acid oxidation as a pivotal biochemical pathway perturbed in the brains of those infants who have from SIDS ( p = 0.0016). Further we have identified a potential central biomarker with an AUC (95% CI) = 0.933 (0.845–1.000) having high sensitivity (0.933) and specificity (0.875) values for discriminating between control and SIDS brains. This is the first reported study to use targeted metabolomics for the study of PM brain from infants who have died from SIDS. We have identified pathways associated with the disease and central biomarkers for early screening/diagnosis.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.308
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 science0.0010.001
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 head0.047
GPT teacher head0.364
Teacher spread0.316 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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