The relationship between glymphatic system, multi-level stress response, and psychological resilience
Bibliographic record
Abstract
Background: Stress promotes affective, neural, endocrine, and immune responses. The glymphatic system, essential for waste clearance and immune homeostasis, protects the brain against adverse neurobiological changes. However, it remains unclear how the glymphatic system changes during acute stress, coordinates with multi-level stress responses, and relates to psychological resilience in humans. Methods: We recruited 84 healthy middle-aged adults (mean age 29.26 ± 2.91, 50 males) without major physical, neurological, or psychological conditions. Glymphatic system function was assessed via the coupling between global blood-oxygen-level-dependent and cerebrospinal fluid signals (gBOLD-CSF coupling) before, immediately after, and 60 min after the Montreal Imaging Stress Task. Mood states, neural responses (BOLD signal changes), acute and awakening cortisol responses, and psychological resilience (Connor-Davidson Resilience Scale) were measured. We compared gBOLD-CSF coupling changes over time using repeated-measures ANOVA, and investigated their associations with affective, neural, endocrine responses, and resilience with linear models and network analysis. Results: gBOLD-CSF coupling was stronger at baseline and after recovery compared to immediately after stress. Changes in gBOLD-CSF coupling were associated with stress-related negative affect and prefrontal neural response. The cortisol response to acute stress was related to gBOLD-CSF coupling response to stress, depending on the level of the cortisol awakening response. The glymphatic system emerged as a central mediator of multi-organ stress response. Finally, post- to pre-stress changes in gBOLD-CSF coupling were associated with psychological resilience. Conclusions: The glymphatic system transiently fluctuates during acute stress, synergizing with affective, neural, and endocrine networks, playing significant roles in stress response and psychological resilience.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".