Antagonism of Synaptic Transmission in vivo: Contributions of Microiontophoresis
Bibliographic record
Abstract
Fundamental to the problems in the study of synaptic transmission in the mammalian central nervous system is the identification of the nature and role of transmitter substances at prescribed loci. Although recently many advances have been made in determining which compounds are endogenous to the central nervous system and which of these and other molecules alter neuronal activity, there can be little doubt that at the present level of our understanding of such brain constituent we are encountering merely a few of the basic materials requisite for the normal functioning of central neurones. Some 60 or 70 substances have now been postulated as candidates for involvement in synaptic processes. Many of the receptors for these and closely related compounds have been characterized pharmacologically through the examination of the effects of agonists and antagonists. One technique which has played a principal role in these neuropharmacological investigations is the method of local drug administration termed microiontophoresis. Although this method is invaluable for helping to answer questions at the molecular and membrane level, under circumscribed conditions its advantages may be exploited for use in experiments oriented toward a more physiological level of investigation. This short account is an attempt to provide a description of some of these conditions and further will describe some of the creative ways in which microiontophoresis has been utilized in vivo to reveal mechanisms by which the central nervous system processes information at the synaptic level.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".