A microelectrochemical biosensor for real-time in vivo monitoring of brain extracellular choline
Bibliographic record
Abstract
A first generation Pt-based polymer enzyme composite biosensor developed for real-time neurochemical monitoring was characterised in vivo for sensitive and selective detection of choline. Confirmation that the sensor responds to changes in extracellular choline was achieved using local perfusion of choline which resulted in an increase in current, and the acetylcholinesterase inhibitor neostigmine which produced a decrease. Interference by electroactive species was tested using systemic administration of sodium ascorbate which produced a rapid increase in extracellular levels before gradually returning towards baseline over several hours. There was no overall change in the response of the biosensor during the same period of monitoring. Oxygen interference was examined using pharmacological agents known to change tissue oxygenation. Chloral hydrate produced an immediate increase in O2 before gradually returning to baseline levels over 3 h. The biosensor signal displayed an initial brief decrease before increasing to a maximum after 1 h and returning to baseline within 2 h. L-NAME caused a decrease in O2 before returning to baseline levels after ca. 1.5 h. In contrast, the biosensor current increased over the same time period before slowly returning to baseline levels over several hours. Such differences in time course and direction suggest that changes in tissue O2 levels do not affect the ability of the sensor to monitor choline reliably. Although it was found to rapidly respond to behavioural activation, examination of baseline in vivo data suggests a stable viable signal for at least 14 days after implantation. Using in vitro calibration data the basal extracellular concentration of choline was estimated to be 6.3 μM.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".