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Record W2026332221 · doi:10.1073/pnas.0801105105

Neuroprotection via matrix-trophic coupling between cerebral endothelial cells and neurons

2008· article· en· W2026332221 on OpenAlexaff
Shuzhen Guo, Woo Jean Kim, Josephine Lok, Sun-Ryung Lee, Elaine Besancon, Bing‐Hao Luo, Monique F. Stins, Xiaoying Wang, Shoukat Dedhar, Eng H. Lo

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthNational Institute of Neurological Disorders and StrokeAmerican Heart Association
KeywordsNeuroprotectionEndotheliumCell biologyNeuroscienceBiologyOxidative stressNeurotrophic factorsEndocrinologyBiochemistryReceptor

Abstract

fetched live from OpenAlex

The neurovascular unit is an emerging concept that emphasizes homeostatic interactions between endothelium and cerebral parenchyma. Here, we show that cerebral endothelium are not just inert tubes for delivering blood, but they also secrete trophic factors that can be directly neuroprotective. Conditioned media from cerebral endothelial cells broadly protects neurons against oxygen-glucose deprivation, oxidative damage, endoplasmic reticulum stress, hypoxia, and amyloid neurotoxicity. This phenomenon is largely mediated by endothelial-produced brain-derived neurotrophic factor (BDNF) because filtering endothelial-conditioned media with TrkB-Fc eliminates the neuroprotective effect. Endothelial production of BDNF is sustained by beta-1 integrin and integrin-linked kinase (ILK) signaling. Noncytotoxic levels of oxidative stress disrupts ILK signaling and reduces endothelial levels of neuroprotective BDNF. These data suggest that cerebral endothelium provides a critical source of homeostatic support for neurons. Targeting these signals of matrix and trophic coupling between endothelium and neurons may provide new therapeutic opportunities for stroke and other CNS disorders.

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)0.000
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 score0.012
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.287
Teacher spread0.222 · 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

Citations254
Published2008
Admission routes1
Has abstractyes

Explore more

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