Editorial: Are Glucocorticoids Good or Bad for Brain Development and Plasticity?
Bibliographic record
Abstract
There is accumulating evidence that increased levels in glucocorticoids (GCs) may have detrimental effects for the brain, especially for specific neurons of the hippocampus, that may lead to memory disorders. The circumstances allowing such increase in circulating levels of GCs are numerous and include genetic factors, environments, gender, and the nature of stressful events. Some individuals exhibit a maintained activation of the hypothalamic-pituitary-adrenal (HPA) axis in response to a rather modest stressful stimulus, whereas others are not affected by the same situation. We do not known exactly why such differences occur between individuals, but the way we perceive and control a particular event is likely to contribute to our degree of stress and the ultimate endocrine outputs. During a lifetime, this may have a great impact on the brain plasticity and neurodegeneration that may be attributable to the presence of high levels of GCs into the hippocampal environment, for example. A famous series of studies performed by Sapolsky and colleagues (1–3) in wild male baboons living undisturbed in their natural habitat in Africa provided the evidence that sustained social stress has determinant impact on the brain. Indeed, the subordinated group of baboons exhibited higher cortisol levels than dominant baboons (1), which was associated with numerous other endocrine changes and exacerbation in the rate of neuron death during normal aging (2, 3). Although the use of the optical fractionator technique questioned the data of cell death and neuron loss in the hippocampus during normal aging (4), disruption of synaptic plasticity, atrophy of dendritic processes, postnatal neurogenesis (especially in the dentate gyrus), and other fine changes clearly occur in the hippocampal formation of socially stressed animals.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.023 | 0.021 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".