A real-time measurement system for gene expression rhythms from deep tissues of freely moving mice under light-dark conditions
Bibliographic record
Abstract
Clock gene expression in most organs of the living body exhibits a diurnal rhythm synchronized with the external 24 h light-dark (LD) cycle via circadian pacemaker suprachiasmatic nucleus (SCN). Disturbances in clock gene expression due to desynchronization of clock gene expression of the external LD cycle are risk factors for developing various diseases. Measuring the in vivo clock genes expression rhythm for a long duration under LD conditions can greatly contribute to understand the pathogenic mechanism of the disease caused by the disturbance of the biological rhythm. However, it is presently difficult to continuously measure gene expression for a long duration under LD conditions. In present study, we succeeded in measuring Period1 ( Per1 ) gene expression under LD conditions using ultraviolet (UV) light with filter cut the visible light range. In addition, we succeeded in measuring the kinetic change of liver Per1 gene expression during the process of desynchronization of behavioral rhythm from the LD cycle by chronic administration of methamphetamine (MAP). In the future, by using this system to measure clock gene expression rhythms of brain tissues such as SCN and peripheral tissues under LD conditions, it could contribute to understand the onset mechanism of diseases induced by the desynchronization mechanism of biological rhythm to the LD cycle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".