LSD Modulates Proteins Involved in Cell Proteostasis, Energy Metabolism and Neuroplasticity in Human Cerebral Organoids
Bibliographic record
Abstract
ABSTRACT Proteomic analysis of human cerebral organoids may reveal how psychedelics regulate biological processes, shedding light on drug-induced changes in the brain. This study elucidates the proteomic alterations induced by lysergic acid diethylamide (LSD) in human cerebral organoids. By employing high-resolution mass spectrometry-based proteomics, we quantitatively analyzed the differential abundance of proteins in cerebral organoids exposed to LSD. Our findings indicate changes in proteostasis, energy metabolism, and neuroplasticity-related pathways. Specifically, LSD exposure led to alterations in protein synthesis, folding, autophagy, and proteasomal degradation, suggesting a complex interplay in the regulation of neural cell function. Additionally, we observed modulation in glycolysis and oxidative phosphorylation, crucial for cellular energy management and synaptic function. In support of the proteomic data, complementary experiments demonstrated LSD’s potential to enhance neurite outgrowth in vitro, confirming its impact on neuroplasticity. Collectively, our results provide a comprehensive insight into the molecular mechanisms through which LSD may affect neuroplasticity and potentially contribute to therapeutic effects for neuropsychiatric disorders.
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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".