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Record W4210817227 · doi:10.1002/alz.050909

Serum oxylipins indicate subcortical ischemic vascular disease in patients with clinical stroke

2021· article· en· W4210817227 on OpenAlexaffabout
Di Yu, Ameer Y. Taha, Theresa L. Pedersen, Joel Ramirez, Maged Goubran, Miracle Ozzoude, Fuqiang Gao, Leanne K. Casaubon, Robert Bartha, Sean Symons, Donna Kwan, Dar Dowlatshahi, Ayman Hassan, Jennifer Mandzia, Demetrios J. Sahlas, Gustavo Saposnik, Stephen R. Arnott, Brian Tan, Krista L. Lanctôt, Mario Masellis, Sandra E. Black, Richard H. Swartz, Walter Swardfager

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsToronto Dementia Research AllianceRobarts Clinical TrialsMcMaster UniversityHealth Sciences CentreThunder Bay Regional Health Sciences CentreBaycrest HospitalUniversity of OttawaToronto Rehabilitation InstituteSunnybrook Health Science CentreHeart and Stroke FoundationUniversity of TorontoWestern University
Fundersnot available
KeywordsOxylipinHyperintensityEpoxide hydrolase 2EtiologyMedicineStroke (engine)Internal medicinePolyunsaturated fatty acidPathologyWhite matterLinoleic acidCardiologyGastroenterologyChemistryFatty acidMagnetic resonance imagingBiochemistryRadiology

Abstract

fetched live from OpenAlex

Abstract Background Subcortical ischemic vascular disease (SIVD) is the most common vascular pathology found in patients with late onset dementia. The soluble epoxide hydrolase (sEH) enzyme inactivates anti‐inflammatory and vasoactive cytochrome p450 derived polyunsaturated fatty acid epoxides by converting them into cytotoxic dihydroxy (diol) oxylipin species. Previously, we found that the ratios of linoleic acid (LA) diols to epoxides were associated with more white matter hyperintensity (WMH) in patients with transient ischemic attack; however, it remains univestigated if these oxylipins can identify SIVD in patients with ischemic stroke of heterogenous cerebrovascular pathologies such as large vessel occlusion and lacunar infarcts. Method The study cohort comprises patients from the Ontario Neurodegenerative Disease Research Initiative, who has clinical stroke of either large or small vessel etiology (according to TOAST criteria). 4 LA oxylipins (12,13‐dihydroxyoctadecamonoenoic acid (12,13‐DiHOME), 12,13‐epoxyoctadecenoic acid (12,13‐EpOME), 9,10‐DiHOME, 9,10‐EpOME) were extracted from blood and quantified with a targeted ultrahigh pressure liquid chromatography mass spectrometry (UPLC‐MS/MS) WMH and perivascular spaces (PVS) were quantified from structural MRI scans using a personalized semi‐automatic processing pipeline (Lesion Explorer). The associations between oxylipins and small vessel disease markers were examined using linear regression models. Result In 80 stroke patients (n=50 large vessel disease and n=30 lacunar infarcts), the ratio of 12,13‐DiHOME to its epoxide sEH substrate 12,13‐EpOME was higher among patients with small vessel etiology (F1,79 = 4.55, p = 0.036). In linear regression models controlling for age, sex, APOE, waist hip ratio, diabetes, and hyperlipidemia, the same ratio, and the ratio of 9,10‐DiHOME/9,10‐EpOME were positively associated with volume of deep (β = 0.338, p = 0.004; β = 0.288, p = 0.012, respectively) and periventricular (β = 0.316, p = 0.003; β = 0.400, p < 0.001, respectively) WMH. The same ratios were associated with higher volumes of perivascular spaces in the white matter (β = 0.293, p = 0.013; β = 0.276, p = 0.016, respectively) but not in the basal ganglia (β = 0.145, p = 0.212; β = 0.086, p = 0.450, respectively). Conclusion Oxylipins derived from sEH activity may contribute to cerebral small vessel disease and to stroke of small vessel etiology.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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 designObservational
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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