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Single-cell reconstruction and mutation enrichment analysis identifies dysregulated cardiomyocyte and endothelial cells in congenital heart disease

2023· review· en· W4387439939 on OpenAlexaff
Richa Tambi, Binte Zehra, Sharon Nandkishore, Shermin Sharafat, Faiza Kader, Nasna Nassir, Nesrin Mohamed, Awab Ahmed, Reem Abdel Hameid, Samah Alasrawi, Martina Brueckner, Wolfgang M. Kuebler, Wendy K. Chung, Alawi Alsheikh‐Ali, Roberto M. Di Donato, Mohammed Uddin, Bakhrom K. Berdiev

Bibliographic record

VenuePhysiological Genomics · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsGenome Canada
FundersNational Heart, Lung, and Blood InstituteMohammed Bin Rashid University of Medicine and Health SciencesNational Institutes of HealthSaudi Heart AssociationAl Jalila Foundation
KeywordsBiologyTranscriptomeGeneticsMYH6Candidate geneMissense mutationHeart diseaseGeneGenetic heterogeneityPhenotypeMYH7Internal medicineGene expressionMedicineGene isoform

Abstract

fetched live from OpenAlex

Congential heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. We present a comprehensive analysis combining genomics and CHD single-cell transcriptome. Our study identifies 90 potential candidate CHD risk genes of which 6 are novel. The risk genes have heterogenous expression suggestive of multiple genes contributing to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.041
GPT teacher head0.303
Teacher spread0.262 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2023
Admission routes1
Has abstractyes

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