Functional mimetics of neurotrophins and their receptors
Bibliographic record
Abstract
Neurotrophins regulate cell survival, death, differentiation and growth. Neurotrophins and their receptors have been validated for pathologies including neurodegenerative disorders of the central nervous system and the peripheral nervous system, certain types of cancers, asthma, inflammation and others. Development of neurotrophin-based therapeutics is important due to the limitations of using whole neurotrophins as pharmacological agents. The use of mimicry has proven to be an alternative. Mimetics can be developed through a number of different approaches. To develop receptor-binding agents, we have used anti-receptor antibody mimicry and neurotrophin mimicry. To develop ligand-binding agents, we have used antiligand antibody mimicry and receptor mimicry. High-throughput screening can be incorporated to complement any of these approaches. The end result is small molecule peptidomimetics with properties favourable over proteins. The present review will offer a general overview of these strategies with a few proven examples from our laboratory.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".