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Record W2171064991 · doi:10.1242/jcs.113.19.3499

Physical and genetic interaction of filamin with presenilin in <i>Drosophila</i>

2000· article· en· W2171064991 on OpenAlexaff
Yiquan Guo, Sally X. Zhang, Nicholas S. Sokol, Lynn Cooley, Gabrielle L. Boulianne

Bibliographic record

VenueJournal of Cell Science · 2000
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsFilaminBiologyPresenilinGeneticsRNA splicingAlternative splicingActinDrosophila (subgenus)Drosophila melanogasterPhenotypeCell biologyGeneGene isoformCytoskeletonDiseaseAlzheimer's diseaseRNA

Abstract

fetched live from OpenAlex

Presenilins were first identified as causative factors in early onset, familial Alzheimer's Disease (FAD). They are predicted to encode a highly conserved novel family of eight transmembrane domain proteins with a large hydrophilic loop between TM6 and TM7 that is the site of numerous FAD mutations. Here, we show that the loop region of Drosophila and human presenilins interacts with the C-terminal domain of Drosophila filamin. Furthermore, we show that Drosophila has at least two major filamin forms generated by alternative splicing from a gene that maps to position 89E10-89F4 on chromosome 3. The longest form is enriched in the central nervous system and ovaries, shares 41.7% overall amino acid identity with human filamin (ABP-280) and contains an N-terminal actin-binding domain. The shorter form is broadly expressed and encodes an alternatively spliced form of the protein lacking the actin-binding domain. Finally, we show that presenilin and filamin are expressed in overlapping patterns in Drosophila and that dominant adult phenotypes produced by overexpression of presenilin can be suppressed by overexpression of filamin in the same tissue. Taken together, these results suggest that presenilin and filamin functionally interact during development.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.112

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 head0.014
GPT teacher head0.303
Teacher spread0.289 · 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 designObservational
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

Citations36
Published2000
Admission routes1
Has abstractyes

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