Bibliographic record
Abstract
Major depressive disorder (MDD) is the psychiatric disorder that causes the greatest social and economic damage in the world, being thus a disorder of great interest to the scientific community. A growing body of evidence indicates epigenetic mechanisms as key players in the pathophysiology of depression and the resilience phenotype, in which individuals do not develop depressive symptoms despite exposure to stressors. Circular RNAs (circRNAs) are single-stranded non-coding RNAs molecules with a closed-loop structure formed in a process called backsplicing. These molecules are naturally abundant and stable in the brain and in exosomes, through which they can be detected in various body fluids such as blood and saliva; thus serving as potential biomarkers, both for the development of disorders and the response to pharmacological treatments. Therefore, we sought to use the model of chronic unpredictable mild stress (CUMS) in Wistar rats to investigate the expression profile of circRNAs circSTAG1 and circHIPK2 in hippocampi of animals with depressive-like behavior and resilience phenotype, and the effect of ketamine on their expression.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.807 | 0.602 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".