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The cytoskeleton reduces the diffusional dimensionality of CD36 and promotes its aggregation and signaling

2009· article· en· W2279903905 on OpenAlexaff
Khuloud Jaqaman, Hirotaka Kuwata, Nicolas Touret, William S. Trimble, Gaudenz Danuser, Sergio Grinstein

Bibliographic record

VenueThe FASEB Journal · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of AlbertaHospital for Sick Children
Fundersnot available
KeywordsCytoskeletonReceptorCell biologyChemistryFilaminBiophysicsInternalizationEndocytosisActin cytoskeletonSignal transductionBiologyCellBiochemistry

Abstract

fetched live from OpenAlex

We used single‐molecule imaging and single‐particle tracking to investigate the dynamic behavior of CD36, a receptor that mediates oxidized LDL (oxLDL) uptake by macrophages. Free (unliganded) receptors existed as metastable multimers that split and reformed spontaneously. A subpopulation of receptors ( ≈30%) moved in linear patterns radiating from the nucleus. Unexpectedly, the linear motion was not motor‐driven but reflected instead diffusion within a confined space delimited by trough‐like cytoskeletal structures. These were attributed to microtubule‐induced discontinuities in the cortical actin meshwork. The resulting reduction in diffusional dimensionality increased the probability for receptors to collide and aggregate into multimers. CD36 is activated and undergoes endocytosis when clustered by multivalent ligands like oxLDL. Disruption of the cytoskeletal organization reduced multimer formation and inhibited CD36‐mediated signaling and oxLDL internalization. These observations demonstrate that the cytoskeleton can control signal transduction by dictating the confinement of receptors within regions where their collision frequency is increased.

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 score0.011
Threshold uncertainty score0.394

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 studies0.0010.000
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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