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Zinc Deficiency Exacerbates Loss in Blood-Brain Barrier Integrity Induced by Hyperoxia Measured by Dynamic MRI

2000· article· en· W2026891125 on OpenAlexaff
Michael D. Noseworthy, Tammy Μ. Bray

Bibliographic record

VenueProceedings of The Society for Experimental Biology and Medicine · 2000
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of Guelph
FundersNational Institute of Neurological Disorders and Stroke
KeywordsHyperoxiaBlood–brain barrierMagnetic resonance imagingChemistryEndocrinologyWeanlingInternal medicinePathologyMedicineCentral nervous systemLung

Abstract

fetched live from OpenAlex

Using dynamic Magnetic Resonance Imaging (dMRI), blood-brain barrier (BBB) permeability (k(PSrho)) and tissue interstitial leakage space (v(e)) were evaluated in zinc-deficient (ZnDF) male weanling Wistar rats following 3 days exposure to hyperoxia (85% O2). Temporal monitoring of T1-weighted MR image changes, following a bolus intravenous injection of gadolinium-DTPA, allowed estimation of BBB integrity. Three-day exposure of hyperoxia caused a marginal loss of BBB integrity, reflected in a slight increase in kPSrho and v(e), observed in both the animals fed adequate zinc (ZnAL) and pair-fed controls (ZnPF). However, zinc deficiency resulted in a significant increase in both kPSrho and v(e), indicating a severely disturbed BBB. In addition MR-visible free water was elevated in ZnDF brains following hyperoxia treatment indicating that a loss of BBB integrity may be associated with neuronal edema. The diminished BBB integrity may be free-radical mediated as the ratio of oxidized to reduced glutathione (GSSG:GSH) was significantly elevated.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.319
Teacher spread0.303 · 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

Citations50
Published2000
Admission routes1
Has abstractyes

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Same venueProceedings of The Society for Experimental Biology and MedicineSame topicTrace Elements in HealthFrench-language works237,207