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Record W1997044949 · doi:10.1042/bj20101599

<i>Trans</i>-interaction of nephrin and Neph1/Neph3 induces cell adhesion that associates with decreased tyrosine phosphorylation of nephrin

2011· article· en· W1997044949 on OpenAlexafffund
Eija Heikkilä, Mervi Ristola, Marika Havana, Nina Jones, Harry Holthöfer, Sanna Lehtonen

Bibliographic record

VenueBiochemical Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of Guelph
FundersJenny ja Antti Wihurin RahastoBiomedicum Helsinki-säätiöSuomen KulttuurirahastoKidney Foundation of Canada
KeywordsNephrinSlit diaphragmCell biologyTyrosine phosphorylationBiologyPodocytePhosphorylationEndocrinologyKidney

Abstract

fetched live from OpenAlex

Slit diaphragms are specialized junctions between glomerular epithelial cells (podocytes) that are crucial for glomerular ultrafiltration. The Ig superfamily members nephrin and Neph1 are essential components of the slit diaphragm, whereas the role of Neph1 homologue Neph3 in the slit diaphragm is unknown. In the present paper we show that Neph3 homodimerizes and heterodimerizes with nephrin and Neph1. We further investigated whether these interactions play a role in cell adhesion by using mouse L fibroblasts that lack endogenous cell-adhesion activity and found that Neph1 and Neph3 are able to induce cell adhesion alone, whereas nephrin needs to trans-interact with Neph1 or Neph3 in order to promote formation of cell-cell contacts. Tyrosine phosphorylation of nephrin was down-regulated after nephrin trans-interacted with either Neph1 or Neph3 leading to formation of cell-cell contacts. We further found that the expression of Neph3 was increased in nephrin-deficient mouse podocytes. The findings of the present paper show that nephrin and Neph1 or Neph3 trans-interactions promote cell-contact formation, suggesting that they may also function together in slit diaphragm assembly.

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 score0.110
Threshold uncertainty score0.434

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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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

Citations26
Published2011
Admission routes2
Has abstractyes

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