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Record W2025104203 · doi:10.1073/pnas.98.3.986

Mouse model of congenital polycythemia: Homologous replacement of murine gene by mutant human erythropoietin receptor gene

2001· article· en· W2025104203 on OpenAlexaff
Vladimír Divoký, Zhiyong Liu, Thomas M. Ryan, Jaroslav F. Prchal, Tim M. Townes, Josef T. Prchal

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2001
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsMcGill University
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsErythropoietin receptorErythropoiesisBiologyErythropoietinMutantGeneAlleleGene knockoutMutationGeneticsInternal medicineMedicine

Abstract

fetched live from OpenAlex

Mutations causing truncations of the cytoplasmic domain of the human erythropoietin receptor (EPOR) result in a dominantly inherited disorder-primary familial congenital polycythemia. This disorder is characterized by increased numbers of erythrocytes (polycythemia) and by in vitro hypersensitivity of erythroid precursors to erythropoietin. The consequences of EPOR truncation in nonerythroid tissues are unknown. We replaced the murine EPOR gene with a wild-type human EPOR gene and a mutant human EPOR gene that we initially identified in a patient with polycythemia. This mutation leads to an EPOR truncated after the first tyrosine residue of the intracellular domain. Mice heterozygous for this mutant allele and a wild-type human EPOR allele mimicked the human disorder. Interestingly, mice that were homozygous for the mutant human allele were severely polycythemic but viable. Our results provide a model for functional studies of EPOR-triggered signaling pathways in erythropoiesis. These animals can now be used to investigate the molecular pathophysiology of this gain-of-function EPOR mutation in erythroid tissue and in those nonerythroid tissues that express EPOR.

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)0.001
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 score0.020
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.041
GPT teacher head0.310
Teacher spread0.269 · 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

Citations56
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicMyeloproliferative Neoplasms: Diagnosis and TreatmentFrench-language works237,207