Elevated potassium provides an ionic mechanism for deep brain stimulation in the hemiparkinsonian rat
Bibliographic record
Abstract
The mechanism of high-frequency stimulation used in deep brain stimulation (DBS) for Parkinson's disease (PD) has not been completely elucidated. Previously, high-frequency stimulation of the rat entopeduncular nucleus, a basal ganglia output nucleus, elicited an increase in [K(+)](e) to 18 mm, in vitro. In this study, we assessed whether elevated K(+) can elicit DBS-like therapeutic effects in hemiparkinsonian rats by employing the limb-use asymmetry test and the self-adjusting stepping test. We then identified how these effects were meditated with in-vivo and in-vitro electrophysiology. Forelimb akinesia improved in hemiparkinsonian rats undergoing both tests after 20 mm KCl injection into the substantia nigra pars reticulata (SNr) or the subthalamic nucleus. In the SNr, neuronal spiking activity decreased from 38.2 ± 1.2 to 14.6 ± 1.6 Hz and attenuated SNr beta-frequency (12-30 Hz) oscillations after K(+) treatment. These oscillations are commonly associated with akinesia/bradykinesia in patients with PD and animal models of PD. Pressure ejection of 20 mm KCl onto SNr neurons in vitro caused a depolarisation block and sustained quiescence of SNr activity. In conclusion, our data showed that elevated K(+) injection into the hemiparkinsonian rat SNr improved forelimb akinesia, which coincided with a decrease in SNr neuronal spiking activity and desynchronised activity in SNr beta frequency, and subsequently an overall increase in ventral medial thalamic neuronal activity. Moreover, these findings also suggest that elevated K(+) may provide an ionic mechanism that can contribute to the therapeutic effects of DBS for the motor treatment of advanced PD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".