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Record W3201116188 · doi:10.1242/dmm.049077

A mouse model of hypoplastic left heart syndrome demonstrating left heart hypoplasia and retrograde aortic arch flow

2021· article· en· W3201116188 on OpenAlexafffund
Anum Rahman, Taylor DeYoung, Lindsay S. Cahill, Yohan Yee, Sarah K. Debebe, Owen Botelho, Mike Seed, Rajiv Chaturvedi, John G. Sled

Bibliographic record

VenueDisease Models & Mechanisms · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsMemorial University of NewfoundlandHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsHypoplastic left heart syndromeHypoplasiaAortic archCardiologyMedicineFetusPenetranceInternal medicineHeart diseaseAnatomyAortaPhenotypeBiologyPregnancy

Abstract

fetched live from OpenAlex

In hypoplastic left heart syndrome (HLHS), the mechanisms leading to left heart hypoplasia and their associated fetal abnormalities are largely unknown. Current animal models have limited utility in resolving these questions as they either do not fully reproduce the cardiac phenotype, do not survive to term and/or have very low disease penetrance. Here, we report the development of a surgically induced mouse model of HLHS that overcomes these limitations. Briefly, we microinjected the fetal left atrium of embryonic day (E)14.5 mice with an embolizing agent under high-frequency ultrasound guidance, which partially blocks blood flow into the left heart and induces hypoplasia. At term (E18.5), all positively embolized mice exhibit retrograde aortic arch flow, non-apex-forming left ventricles and hypoplastic ascending aortas. We thus report the development of the first mouse model of isolated HLHS with a fully penetrant cardiac phenotype and survival to term. Our method allows for the interrogation of previously intractable questions, such as determining the mechanisms of cardiac hypoplasia and fetal abnormalities observed in HLHS, as well as testing of mechanism-based therapies, which are urgently lacking.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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 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

Citations26
Published2021
Admission routes2
Has abstractyes

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