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Record W2152341218 · doi:10.1074/mcp.m111.012302

Proteomics Analyses of Human Optic Nerve Head Astrocytes Following Biomechanical Strain

2011· article· en· W2152341218 on OpenAlexafffund
Ronan Rogers, Moyez Dharsee, Suzanne Ackloo, Jeremy M. Sivak, John G. Flanagan

Bibliographic record

VenueMolecular & Cellular Proteomics · 2011
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsToronto Western HospitalUniversity of WaterlooUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsOptic nerveProteomicsStrain (injury)Tandem mass spectrometryOptic neuropathyBlotChemistryMolecular biologyCell biologyPathologyBiologyMedicineMass spectrometryBiochemistryNeuroscienceAnatomyChromatography

Abstract

fetched live from OpenAlex

We investigate the role of glial cell activation in the human optic nerve caused by raised intraocular pressure, and their potential role in the development of glaucomatous optic neuropathy. To do this we present a proteomics study of the response of cultured, optic nerve head astrocytes to biomechanical strain, the magnitude and mode of strain based on previously published quantitative models. In this case, astrocytes were subjected to 3 and 12% stretches for either 2 h or 24 h. Proteomic methods included nano-liquid chromatography, tandem mass spectrometry, and iTRAQ labeling. Using controls for both stretch and time, a six-plex iTRAQ liquid chromatography- tandem MS (LC/MS/MS) experiment yielded 573 proteins discovered at a 95% confidence limit. The pathways included transforming growth factor β1, tumor necrosis factor, caspase 3, and tumor protein p53, which have all been implicated in the activation of astrocytes and are believed to play a role in the development of glaucomatous optic neuropathy. Confirmation of the iTRAQ analysis was performed by Western blotting of various proteins of interest including ANXA 4, GOLGA2, and αB-Crystallin.

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 categoriesMeta-epidemiology (narrow)
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 score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.308
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 teacher head, not a consensus.

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

Citations70
Published2011
Admission routes2
Has abstractyes

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