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Record W2041035765 · doi:10.1074/jbc.m111.306522

Pannexin1 Drives Multicellular Aggregate Compaction via a Signaling Cascade That Remodels the Actin Cytoskeleton

2012· article· en· W2041035765 on OpenAlexafffund
Brian A. Bao, Charles Pin‐Kuang Lai, Christian C. Naus, Jeffrey R. Morgan

Bibliographic record

VenueJournal of Biological Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health Research
KeywordsActinActin cytoskeletonCytoskeletonCell biologyCascadeMulticellular organismAggregate (composite)CompactionChemistryBiophysicsBiologyGeologyMaterials scienceGeotechnical engineeringNanotechnologyBiochemistryCell

Abstract

fetched live from OpenAlex

Pannexin 1 (Panx1) is a novel gap junction protein shown to have tumor-suppressive properties. To model its in vivo role in the intratumor biomechanical environment, we investigated whether Panx1 channels modulate the dynamic assembly of multicellular C6 glioma aggregates. Treatment with carbenoxolone and probenecid, which directly and specifically block Panx1 channels, respectively, showed that Panx1 is involved in accelerating aggregate assembly. Experiments further showed that exogenous ATP can reverse the inhibitive effects of carbenoxolone and that aggregate compaction is sensitive to the purinergic antagonist suramin. With a close examination of the F-actin microfilament network, these findings show that Panx1 channels act as conduits for ATP release that stimulate the P(2)X(7) purinergic receptor pathway, in turn up-regulating actomyosin function. Using a unique three-dimensional scaffold-free method to quantify multicellular interactions, this study shows that Panx1 is intimately involved in regulating intercellular biomechanical interactions pivotal in the progression of cancer.

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)0.001
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 score0.031
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.035
GPT teacher head0.269
Teacher spread0.234 · 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

Citations61
Published2012
Admission routes2
Has abstractyes

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