Identification and Characterization of Extrachromosomal Circular DNA in Human Placentas With Fetal Growth Restriction
Bibliographic record
Abstract
Many studies have confirmed that extrachromosomal circular DNAs (eccDNAs/ecDNAs) exist in tumor and normal cells independently of the chromosome and are essential for oncogene plasticity and drug resistance. Studies have confirmed that there are many eccDNAs/ecDNAs in maternal plasma derived from the fetus. Fetal growth restriction (FGR) is a pregnancy-related disease associated with high newborn morbidity and mortality. However, the characteristics and nature of eccDNAs/ecDNAs in FGR are poorly understood. This study aims to deconstruct the properties and potential functions of eccDNAs/ecDNAs in FGR. We performed circle-seq to identify the expression profile of eccDNAs/ecDNAs, analyzed by bioinformatics, and verified by real-time Polymerase Chain Reaction (PCR) combined with southern blot in FGR compared with the normal groups. A total of 45,131 eccDNAs/ecDNAs (including 2,118 unique ones) were identified, which had significantly higher abundance in FRG group than in normal group, and was bimodal in length, peaking at ~146bp and ~340bp, respectively. Gestational age may be one independent factor affecting the production of eccDNAs/ecDNAs, most of which come from genomic regions with high gene density, with a 4~12bp repeat around the junction, and their origin had a certain genetic preference. In addition, some of the host-genes overlapped with non-coding RNAs (ncRNAs) partially or even completely. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that host-genes on the differentially expressed eccDNAs/ecDNAs (DEEECs/DEECs) were mainly enriched in immune-related functions and pathways. The presence of some ecDNAs were verified, and whose variability were consistent with the circle-seq results. We identified and characterized eccDNAs/ecDNAs in placentas with FGR, and elucidated the formation mechanisms and the networks with ncRNAs, which provide a new vision for the screening of new biomarkers and therapeutic targets for FGR.
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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".