MétaCan
Menu
Back to cohort

Computational Analysis of Isoform‐Specific Signal Regulation by CEACAM1—A Cell Adhesion Molecule Expressed in PC12 Cells

2002· article· en· W2031311188 on OpenAlexaff
Björn Öbrink, Hiroki Sawa, Inka Scheffrahn, Bernhard B. Singer, Kristmundur Sigmundsson, Ulla Sundberg, Robert Heymann, Nicole Beauchemin, Gehzi Weng, Prahlad T. Ram, Ravi Iyengar

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2002
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsMcGill University
FundersNational Institute of General Medical Sciences
KeywordsGene isoformCell adhesion moleculeCell biologyChemistryCell adhesionSIGNAL (programming language)CellBiologyBiochemistryComputer scienceGene

Abstract

fetched live from OpenAlex

CEACAM1 is a signal-regulating, homophilic cell adhesion receptor system expressed in epithelia, vessel endothelia, and leukocytes. Here, we demonstrate that CEACAM1 is expressed also in PC12 cells, both as the common transmembrane isoforms, CEACAM1-L and CEACAM1-S, and as a novel, secreted, differentially spliced isoform. CEACAM1 can have both positive and negative effects on cell signaling. In an attempt to explain this dual behavior, we have initiated computational analysis of the signal-regulating effects of CEACAM1. This suggests that CEACAM1 can exert its signal-regulating activities by discriminating between binding of Src kinases and SHP phosphatases, respectively. Major factors that regulate this discrimination are the expression levels and expression ratios of transmembrane CEACAM1-L and CEACAM1-S, the concentration of secreted CEACAM1, and homophilic binding of CEACAM1 presented by neighboring cells.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.334
Teacher spread0.247 · 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 designSimulation or modeling
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

Citations30
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicCell Adhesion Molecules ResearchFrench-language works237,207