Editorial: Insights in epigenomics and epigenetics: 2022
Bibliographic record
Abstract
The top-most viewed original research paper in this "Insights" Research Topic was by Wang and colleagues and was titled "Genetic regulation of newborn telomere length is mediated and modified by DNA methylation" (Wang et al.).This paper came out in October, 2022, and already has over 1,167 views at the time this editorial was written, according to the Frontiers Media site "Loop Research Network" which maps "views," "downloads," "citations," "social buzz," and "demographics" (https://loop.frontiersin.org/).This research paper studied 281 mom-newborn pairs from the ENVIRonmental influence ON early AGEing (ENVIRONAGE) pregnancy cohort comparing DNA 5 mC methylation and telomere (TEL) lengths on genomic DNA isolated from the blood of the mother with that from the babies' umbilical cord.This paper was a tour-de-force of high-dimensional omics analyses.The second-most viewed original research paper was by Lothion-Roy and colleagues and is titled, "Clinical and molecular significance of the RNA m6A methyltransferase complex in prostate cancer" (Lothion-Roy et al.).This paper came out in January, 2023, and already has 1,096 views.N6-methyl adenine (m6A) is the most abundant internal mRNA modification in eukaryotes and regulates processes such as mRNA translation into protein, mRNA alternative splicing, and mRNA stability.The authors studied the levels of key proteins in the m6A pathway in prostate cancer cells and cell lines.Prostate cancer is the most abundant non-cutaneous cancer in men and the authors wanted to determine whether any of the m6A proteins correlate with the type of prostate cancer or the severity and prognosis of the disease.Overall, this is an exciting paper which points to m6A biology as a new avenue for prostate cancer research.The third-most viewed original research paper was by Thumfart and colleagues and was titled "Long-term effects of early postnatal stress on Sertoli cells" (Thumfart et al.).This paper also came out in October, 2022, and has 877 views in this short period of time.This paper studied Sertoli cells from adult male mice, which are tightly associated with germ cells, provide structural support for differentiating sperm, and help form a tight blood-testis barrier.The Sertoli cells are highly glycolytic because they need to provide high levels of lactate to the differentiating sperm as an energy source.The stress applied to the moms and
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.041 | 0.025 |
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 source (direct Gemma or distilled Codex), 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".