A Comprehensive Expression Profile of tRNA-Derived Fragments in Papillary Thyroid Cancer
Bibliographic record
Abstract
Objective: In recent years, the incidence of thyroid cancer has been increasing. Papillary thyroid cancer (PTC) is the most common type of malignant thyroid tumor, accounting for approximately 85% of thyroid cancer cases. Although the genetic background of PTC has been studied extensively, relatively little is known about the role of small non-coding RNA (sncRNA) in this disease. tRNA-derived fragments (tRFs) represent a newly discovered class of sncRNAs that exist in many species and play a role in many biological processes. Methods: In this study, we used RNA sequencing to analyse the expression of tRFs in fresh frozen specimens from PTC tissues and normal tissues adjacent to the tumors. Through this analysis, we identified 49 unique tRFs and transfer RNA halves and then performed quantitative PCR to determine the expression levels of these molecules and to make bioinformatic predictions. Conclusion: In this report, we provide a comprehensive catalog of tRFs in PTC and assess the abnormal expression of these fragments. These preliminary findings can be used as the basis for further research regarding the functional role of tRFs in patients with PTC.
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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".