Predictive Simulation and Functional Insights of Serotonin Transporter: Ligand Interactions Explored through Database Analysis
Bibliographic record
Abstract
By regulating serotonin levels and exerting an influence on mood, cognition, and a variety of physiological processes, the serotonin reuptake transporter (SERT) plays a critical role. Palmitoylation is a post-translational modification that allows for the regulation of protein kinetics and trafficking. SERT is a target for palmitoylation. Reducing the expression of SERT through the use of small interference RNA (SERT-siRNA) has been demonstrated to have antidepressant properties and to modify important markers of antidepressant action. These markers include the expression and function of 5-HT1A-autoreceptors, the levels of extracellular serotonin, neurogenesis, and the expression of genes related to plasticity. SERT expression on platelet membranes is downregulated when plasma serotonin levels are elevated, which limits the amount of serotonin that platelets can take in.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".