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Record W3043000716 · doi:10.1530/rep-20-0233

Membrane trafficking directed by VAMP2 and syntaxin 3 in uterine epithelial cells

2020· article· en· W3043000716 on OpenAlexaff
Sadaf N. Kalam, Louise Cole, Laura A. Lindsay, Christopher R. Murphy

Bibliographic record

VenueReproduction · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsInstitute of Infection and Immunity
FundersAustralian Research CouncilUniversity of Sydney
KeywordsCell biologySyntaxinExocytosisSyntaxin 3BiologyCytoplasmMicrotubuleCytochalasin DCytoskeletonSecretionChemistryBiochemistryCell

Abstract

fetched live from OpenAlex

Luminal uterine epithelial cells (UEC) have a surge in vesicular activity during early uterine receptivity. It has been predicted these vesicles exit the UEC via exocytosis resulting in secretion and membrane trafficking. The present study investigated the changes in SNARE proteins VAMP2 (v-SNARE) and syntaxin 3 (t-SNARE) localisation and abundance in UECs during early pregnancy in the rat. We found VAMP2 and syntaxin 3 are significantly higher on day 5.5 compared to day 1 of pregnancy. On day 5.5, VAMP2 is perinuclear and syntaxin 3 is concentrated in the apical cytoplasm compared to a cytoplasmic localisation on day 1. This change in localisation and abundance show VAMP2 and syntaxin 3 are involved in vesicular movement and membrane trafficking in UECs during early pregnancy. This study also investigated the influence of cytoskeletal disruption of microtubules and actin filaments on VAMP2 and syntaxin 3 in UECs grown in vitro, since microtubules and actin influence vesicle trafficking. As expected, this study found disruption to microtubules with colchicine and actin with cytochalasin D impacted VAMP2 and syntaxin 3 localisation. These results suggest VAMP2 and syntaxin 3 are involved in the timely trafficking of vesicular membranes to the apical surface in UECs during early pregnancy, as are of microtubules and actin.

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 score0.087
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.211
Teacher spread0.202 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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