Different Types of Environmental Stressors Could Have Disruptive or Constructive Effects on Vestibular Compensation
Bibliographic record
Abstract
Background and Aim: Stress could play either helpful or harmful roles in vestibular compensation, the process of recovery after vestibular system lesions. Herein, we examined the effect of two stressor types on vestibular compensation: chronic anxiety disorder induced by early maternal separation (MS), and caloric restriction by an intermittent fasting (IF) diet. Methods: Male Wistar rats (n=56) received maternal separation (the MS group), intermittent fasting (IF group), unilateral vestibular deafferentation (UVD group), or a mixture of these interventions (UVD+IF, UVD+MS, and UVD+IF+MS). All the groups were compared with control animals. The animals’ balance, motor coordination, anxiety, locomotor activity, and serum cortisol levels were evaluated by rotarod, open field, and enzyme-linked immunosorbent assay methods, respectively. The data were compared with those of the healthy control (HC) group. Results: The UVD animals did not show a significant change in the time on the rod, except for the IF+UVD group (p=0.04). There was no significant difference between the experimental groups on the open field indices, except for the MS+IF+UVD group which traveled a significantly less total distance (p=0.02). Serum cortisol levels were significantly higher than HCs for all the groups except for the sham saline and IF+UVD group (p<0.05). Conclusion: IF seems to promote compensation after UVD, while MS may disrupt it. However, IF loses its beneficial outcomes if the animal has received another source of stress, i.e. MS.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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 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".