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Record W2111444354 · doi:10.1126/science.1065806

Correction of Sickle Cell Disease in Transgenic Mouse Models by Gene Therapy

2001· article· en· W2111444354 on OpenAlexaff
Robert Pawliuk, Karen A. Westerman, Mary E. Fabry, Emmanuel Payen, Robert Tighe, Eric E. Bouhassira, Seetharama A. Acharya, James Ellis, Irving M. London, Connie J. Eaves, R. Keith Humphries, Yves Beuzard, Ronald L. Nagel, Philippe Leboulch

Bibliographic record

VenueScience · 2001
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsTerry Fox Research InstituteHospital for Sick Children
FundersNational Heart, Lung, and Blood Institute
KeywordsGenetic enhancementHaematopoiesisHemoglobinGeneTransgeneCellBiologyGlobinViral vectorMolecular biologyRed blood cellImmunologyStem cellGeneticsRecombinant DNABiochemistry

Abstract

fetched live from OpenAlex

Sickle cell disease (SCD) is caused by a single point mutation in the human betaA globin gene that results in the formation of an abnormal hemoglobin [HbS (alpha2betaS2)]. We designed a betaA globin gene variant that prevents HbS polymerization and introduced it into a lentiviral vector we optimized for transfer to hematopoietic stem cells and gene expression in the adult red blood cell lineage. Long-term expression (up to 10 months) was achieved, without preselection, in all transplanted mice with erythroid-specific accumulation of the antisickling protein in up to 52% of total hemoglobin and 99% of circulating red blood cells. In two mouse SCD models, Berkeley and SAD, inhibition of red blood cell dehydration and sickling was achieved with correction of hematological parameters, splenomegaly, and prevention of the characteristic urine concentration defect.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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

Citations579
Published2001
Admission routes1
Has abstractyes

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