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Record W2613829040 · doi:10.3324/haematol.2016.155671

Extracellular glycine is necessary for optimal hemoglobinization of erythroid cells

2017· article· en· W2613829040 on OpenAlexafffund
Daniel Garcia‐Santos, Matthias Schranzhofer, Richard Bergeron, Alex D. Sheftel, Prem Ponka

Bibliographic record

VenueHaematologica · 2017
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsImpactMcGill UniversitySpartan Bioscience (Canada)Jewish General HospitalUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health Research
KeywordsGlycineHemeBiochemistryChemistryHemoglobinExtracellularAmino acidBiologyEnzyme

Abstract

fetched live from OpenAlex

Vertebrate heme synthesis requires three substrates: succinyl-CoA, which regenerates in the tricarboxylic acid cycle, iron and glycine. For each heme molecule synthesized, one atom of iron and eight molecules of glycine are needed. Inadequate delivery of iron to immature erythroid cells leads to a decreased production of heme, but virtually nothing is known about the consequence of an insufficient supply of extracellular glycine on the process of hemoglobinization. To address this issue, we exploited mice in which the gene encoding glycine transporter 1 (GlyT1) was disrupted. Primary erythroid cells isolated from fetal livers of GlyT1 knockout (GlyT1−/−) and GlyT1-haplodeficient (GlyT1+/−) embryos had decreased cellular uptake of [2−14C]glycine and heme synthesis as revealed by a considerable decrease in [2-14C]glycine and 59Fe incorporation into heme. Since GlyT1−/− mice die during the first postnatal day, we analyzed blood parameters of newborn pups and found that GlyT1−/− animals develop hypochromic microcytic anemia. Our finding that Glyt1-deficiency causes decreased heme synthesis in erythroblasts is unexpected, since glycine is a non-essential amino acid. It also suggests that GlyT1 represents a limiting step in heme and, consequently, hemoglobin production.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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

Citations34
Published2017
Admission routes2
Has abstractyes

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