Decoded Calreticulin-Deficient Embryonic Stem Cell Transcriptome Resolves Latent Cardiophenotype
Bibliographic record
Abstract
Genomic perturbations that challenge normal signaling at the pluripotent stage may trigger unforeseen ontogenic aberrancies. Anticipatory systems biology identification of transcriptome landscapes that underlie latent phenotypes would offer molecular diagnosis before the onset of symptoms. The purpose of this study was to assess the impact of calreticulin-deficient embryonic stem cell transcriptomes on molecular functions and physiological systems. Bioinformatic surveillance of calreticulin-null stem cells, a monogenic insult model, diagnosed a disruption in transcriptome dynamics, which re-prioritized essential cellular functions. Calreticulin-calibrated signaling axes were uncovered, and network-wide cartography of undifferentiated stem cell transcripts suggested cardiac manifestations. Calreticulin-deficient stem cell-derived cardiac cells verified disorganized sarcomerogenesis, mitochondrial paucity, and cytoarchitectural aberrations to validate calreticulin-dependent network forecasts. Furthermore, magnetic resonance imaging and histopathology detected a ventricular septal defect, revealing organogenic manifestation of calreticulin deletion. Thus, bioinformatic deciphering of a primordial calreticulin-deficient transcriptome decoded at the pluripotent stem cell stage a reconfigured multifunctional molecular registry to anticipate predifferentiation susceptibility toward abnormal cardiophenotype.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".