Altered in vivo early neurogenesis traits in patients with depression: Evidence from neuron-derived extracellular vesicles and electroconvulsive therapy
Bibliographic record
Abstract
BACKGROUND: The neurogenesis hypothesis is a promising candidate etiologic hypothesis for depression, and it is associated with electroconvulsive therapy (ECT). However, human in vivo molecular-level evidence is lacking. OBJECTIVE: We used neuron-derived extracellular vesicles (NDEVs) as a "window to the neurons" to explore the in vivo neurogenesis status associated with ECT in patients with treatment-resistant depression (TRD). METHODS: In this study, we enrolled 40 patients with TRD and 35 healthy controls (HCs). We isolated NDEVs from the plasma of each participant to test the levels of doublecortin (DCX), a marker of neurogenesis, and cluster of differentiation (CD) 81, a marker of EVs. We also assessed the plasma levels of brain-derived neurotrophic factor (BDNF), a protein that is known to be associated with ECT and neuroplastic processes. RESULTS: Our findings indicated that both the levels of DCX in NDEVs and BDNF in plasma were significantly lower in TRD patients compared to HCs at baseline, but increased following ECTs. Conversely, levels of CD81 in NDEVs were found higher in TRD patients at baseline, but did not change after the ECT treatments. Exploratory analyses revealed that lower levels of BDNF in plasma and DCX in NDEVs, along with higher CD81 levels in NDEVs, were associated with more severe depressive symptoms and reduced cognitive function at baseline. Furthermore, higher baseline CD81 concentrations in NDEVs were correlated with greater decreases in depression symptoms. CONCLUSIONS: We first present human in vivo evidence of early neurogenesis using DCX through NDEVs: decreased in TRD patients, increased after ECTs.
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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".