Changes in Regional Brain Glucose Metabolism Measured With Positron Emission Tomography After Paroxetine Treatment of Major Depression
Bibliographic record
Abstract
OBJECTIVE: Depression is commonly associated with frontal hypometabolic activity accompanied by hypermetabolism in certain limbic regions. It is unclear whether successful antidepressant treatments reverse these abnormalities or create new resting levels of metabolism. The aim of the present study was to assess the effects of successful paroxetine treatment on regional glucose metabolism in patients with major depression. METHOD: Positron emission tomography with [(18)F]fluorodeoxyglucose was performed on 13 male patients before and after 6 weeks of paroxetine therapy. Resting state scans were also acquired under similar conditions in 24 healthy male subjects for comparison. RESULTS: After successful paroxetine therapy, increased glucose metabolism occurred in dorsolateral, ventrolateral, and medial aspects of the prefrontal cortex (left greater than right), parietal cortex, and dorsal anterior cingulate. Areas of decreased metabolism were noted in both anterior and posterior insular regions (left) as well as right hippocampal and parahippocampal regions. In comparison to metabolism levels in a group of healthy volunteers, the increase in prefrontal metabolic activity represented a normalization of previously reduced metabolic activity, whereas the reduction in pregenual anterior cingulate activity represented a decrease from previously elevated metabolic levels. CONCLUSIONS: These results provide further support for a dysfunction in cortical-limbic circuitry in depression, which is at least partly reversed after successful paroxetine treatment.
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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".