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Record W2161546622 · doi:10.1081/hem-120035914

A Rare 33 bp In‐Frame Deletion (α63–74 or α64–74 or α65–75) in the α1‐Globin Gene Causing α<sup>+</sup>‐Thalassemia: A Second Observation

2004· article· en· W2161546622 on OpenAlexaboutno aff
Gerasimos Dimisianos, Joanne Traeger‐Synodinos, Christina Vrettou, Ioannis Papassotiriou, Emmanuel Kanavakis

Bibliographic record

VenueHemoglobin · 2004
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsGlobinGeneticsMutationGeneBiologyHemoglobinMolecular biologyAlpha globulinThalassemiaAlpha (finance)Frameshift mutationBiochemistryMedicine

Abstract

fetched live from OpenAlex

The most frequent defects resulting in alpha-thalassemia (thal) include large deletions that remove one or both of the duplicated alpha-globin genes on chromosome 16. Less commonly, alpha-thal mutations involve single nucleotide substitutions or micro-deletions, leading either directly to decreased alpha-globin chain synthesis by the affected allele, or indirectly through production of hyperunstable variant alpha-globin chains. Here we describe the characterization of a 33 bp in-frame deletion within the alpha1-globin gene, in a woman with hematological findings consistent with an alpha-thal trait. The amino acids predicted to be missing as a result of the 33 bp deletion are at the end of the E helix and the EF corner of the alpha-globin protein chain, and are not normally involved in the heme contact, although it is presumed that alpha-globin chain folding and hemoglobin (Hb) formation will be disrupted. The observation of inclusion and Heinz bodies indicates the synthesis of some abnormal Hb (or globin chains). An identical mutation has been previously observed in a single case, a Canadian individual of Greek descent, indicating that it is a rare mutation, and probably of the same origin. Possible mechanisms underlying the mutation at the DNA level are discussed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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.

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

Citations7
Published2004
Admission routes1
Has abstractyes

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