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The impact of hypoxia on blood-brain, blood-CSF, and CSF-brain barriers

2021· review· en· W3181806888 on OpenAlexafffund
Jeff F. Dunn, Albert M. Isaacs

Bibliographic record

VenueJournal of Applied Physiology · 2021
Typereview
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersAlberta HealthNational Institute of Biomedical Imaging and BioengineeringCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsHypoxia (environmental)Blood–brain barrierCerebrospinal fluidInflammationCentral nervous systemMedicineMultiple sclerosisPathophysiologyPathologyCerebral edemaBrain damageBiologyImmunologyInternal medicineChemistryOxygen

Abstract

fetched live from OpenAlex

The blood-brain barrier (BBB), blood-cerebrospinal fluid (CSF) barrier (BCSFB), and CSF-brain barriers (CSFBB) are highly regulated barriers in the central nervous system comprising complex multicellular structures that separate nerves and glia from blood and CSF, respectively. Barrier damage has been implicated in the pathophysiology of diverse hypoxia-related neurological conditions, including stroke, multiple sclerosis, hydrocephalus, and high-altitude cerebral edema. Much is known about the damage to the BBB in response to hypoxia, but much less is known about the BCSFB and CSFBB. Yet, it is known that these other barriers are implicated in damage after hypoxia or inflammation. In the 1950s, it was shown that the rate of radionucleated human serum albumin passage from plasma to CSF was five times higher during hypoxic than normoxic conditions in dogs, due to BCSFB disruption. Severe hypoxia due to administration of the bacterial toxin lipopolysaccharide is associated with disruption of the CSFBB. This review discusses the anatomy of the BBB, BCSFB, and CSFBB and the impact of hypoxia and associated inflammation on the regulation of those barriers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.320
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes2
Has abstractyes

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