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Record W4281705204 · doi:10.32920/19857427

Developing the polycystic kidney disease interactome

2022· preprint· en· W4281705204 on OpenAlexaff
Mackenzie Brauer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsToronto Metropolitan UniversityRoyal Military College of CanadaSciencetech (Canada)
Fundersnot available
KeywordsCiliumPKD1Polycystic kidney diseaseEndoplasmic reticulumCell biologyAutosomal dominant polycystic kidney diseaseHEK 293 cellsBiologyIntraflagellar transportInteractomeGeneKidneyGenetics

Abstract

fetched live from OpenAlex

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disease causing numerous renal cysts to form leading to adult renal failure. The PKD-causing genes, polycystic kidney disease-1 and -2 (PKD1 and PKD2), encode for proteins polycystin-1 and -2 (PC1 and PC2). These proteins form a complex through their C-termini at cilia with mutations abolishing their interaction and impairing ciliary localization. We report the first use of proximity-dependent biotinylation for identification (BioID) to characterize the PC1 PC2 C-terminal complex binding partners in HEK 293 cells. We identify high- confidence interacting partners including an enrichment of cilia-related, transporter activity and trafficking genes. We report interesting PC1 interactions including Biogenesis of Lysosome-Related Organelles Complex-1 (BLOC-1) subunits and BLOC-One-Related Complex (BORC) subunits. We also report endoplasmic reticulum (ER)-related proteins that likely contribute to PC2 ER localization and function. Overall, this research hopes to contribute information to how PC1 and PC2 traffic and function at cilia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.003
Science and technology studies0.0010.000
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.014

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 head0.017
GPT teacher head0.282
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes1
Has abstractyes

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