MicroRNAs in type 1 diabetes: new research progress and potential directions
Bibliographic record
Abstract
MicroRNAs (miRNAs) are a class of noncoding single-stranded RNA molecules encoded by endogenous genes of about 22 nucleotides, which are involved in post-transcriptional gene expression regulation in animals and plants. Type 1 diabetes (T1D) is an autoimmune disease that is clinically silent until the majority of β cells are destroyed, and a large number of studies have shown that miRNAs are involved in the pathological mechanism of T1D. In this review, we searched the related research in recent years and summarized the important roles of miRNAs in T1D diagnosis and treatment. Furthermore, we summarized the current understanding of miRNA-mediated regulation mechanisms of gene expression in the T1D pathogenesis as well as related signaling pathways with a focus on the important roles of miRNAs and their antagonists in T1D pathogenesis, and brought insight into the potential therapeutic value of miRNAs for T1D patients. In view of the important roles of miRNAs in T1D pathology, disordered miRNAs may be important diagnostic markers and therapeutic targets for patients with T1D.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".