Nanoneuropharmacology: A challenging concept in pharmaceutical investigations for the next decade
Bibliographic record
Abstract
A rapid increase in the incidence of neurodegenerative disorders has been observed with the aging of the population. During the last decade, a large number of pharmacologic compounds with differing brain targets were investigated. Pharmacologic agents developed using classical strategies of pharmacologic development are frequently limited by pharmacodynamics and pharmacokinetics problems, such as low efficacy or lack of selectivity. In addition, many drugs have poor solubility and low bioavailability, and they can be quickly degraded or cleared. Furthermore, the efficacy of different drugs is often limited by dose-dependent side effects. The targeted drug delivery to the central nervous system (CNS), for the diagnosis and treatment of neurodegenerative disorders, is restricted due to the limitations posed by the blood–brain barrier (BBB), the opsonization by plasma proteins in the systemic circulation, and peripheral side effects. Read more...
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".