Investigating TSPO levels in occupation-related posttraumatic stress disorder
Bibliographic record
Abstract
Abstract Microglia are immune brain cells implicated in stress-related mental illnesses including posttraumatic stress disorder (PTSD). Their role in the pathophysiology of PTSD, and on neurobiological systems that regulate stress, is not completely understood. We tested the hypothesis that microglia activation, in fronto-limbic brain regions involved in PTSD, would be elevated in participants with occupation-related PTSD. We also explored the relationship between cortisol and microglia activation. Twenty participants with PTSD and 23 healthy controls (HC) completed positron emission tomography (PET) scanning of the 18-kDa translocator protein (TSPO), a putative biomarker of microglia activation using the probe [18F]FEPPA, and blood samples for measurement of cortisol. [18F]FEPPA VT was non-significantly elevated (6.5–30%) in fronto-limbic regions in PTSD participants. [18F]FEPPA VT was significantly higher in PTSD participants reporting frequent cannabis use compared to PTSD non-users (44%, p = 0.047). Male participants with PTSD (21%, p = 0.094) and a history of early childhood trauma (33%, p = 0.116) had non-significantly higher [18F]FEPPA VT. Average fronto-limbic [18F]FEPPA VT was positively related to cortisol (r = 0.530, p = 0.028) in the PTSD group only. Although we did not find a significant abnormality in TSPO binding in PTSD, findings suggest microglial activation might have occurred in a subgroup who reported frequent cannabis use. The relationship between cortisol and TSPO binding suggests a potential link between hypothalamic–pituitary–adrenal-axis dysregulation and central immune response to trauma which warrants further study.
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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) | 0.002 | 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".