Saturation transfer MRI is sensitive to neurochemical changes in the rat brain due to chronic unpredictable mild stress
Bibliographic record
Abstract
Abstract Chemical exchange saturation transfer (CEST) MRI was performed for the evaluation of cerebral metabolic changes in a rat model of depressive-like disease induced by chronic unpredictable mild stress (CUMS). CEST Z-spectra were acquired on a 7 T MRI with two saturation B1 amplitudes (0.5 and 0.75 µT) to measure the magnetization transfer ratio (MTR), CEST and relayed nuclear Overhauser effect (rNOE). Cerebral cortex and hippocampus were examined in two groups of animals: healthy control (n = 10) and stressed (n = 14), the latter of which was exposed to eight weeks of the CUMS protocol. The stressed group Z-spectrum parameters, primarily MTRs, were significantly lower than in controls, at all selected frequency offsets (3.5, 3.0, 2.0, − 3.2, − 3.6 ppm) in the cortex (the largest difference of ~ 3.5% at − 3.6 ppm, p = 0.0005) and the hippocampus (MTRs measured with a B1 = 0.5 µT). The hippocampal rNOE contributions decreased significantly in the stressed brains. Glutamate concentration (assessed using ELISA) and MTR at 3 ppm correlated positively in both brain regions. GABA concentration also correlated positively with CEST contributions in both cerebral areas, while such correlation with MTR was positive in hippocampus, and nonsignificant in cortex. Results indicate that CEST is sensitive to neurometabolic changes following chronic stress exposure.
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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 | 0.000 |
| 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".