Faculty Opinions recommendation of Deep brain stimulation of the midbrain locomotor region improves paretic hindlimb function after spinal cord injury in rats.
Bibliographic record
Abstract
In severe spinal cord injuries, the tracts conveying motor commands to the spinal cord are disrupted, resulting in paralysis, but many patients still have small numbers of spared fibers. We have found that excitatory deep brain stimulation (DBS) of the mesencephalic locomotor region (MLR), an important control center for locomotion in the brain, markedly improved hindlimb function in rats with chronic, severe, but incomplete spinal cord injury. The medial medullary reticular formation was essential for this effect. Functional deficits of rats with 20 to 30% spared reticulospinal fibers were comparable to patients able to walk but with strong deficits in strength and speed [for example, individuals with American Spinal Injury Association Impairment Scale (AIS)-D scores]. MLR DBS enabled close to normal locomotion in these rats. In more extensively injured animals, with less than 10% spared reticulospinal fibers, hindlimbs were almost fully paralyzed, comparable to wheelchair-bound patients (for example, AIS-A, B, and C). With MLR DBS, hindlimb function reappeared under gravity-released conditions during swimming. We propose that therapeutic MLR DBS using the brain's own motor command circuits may offer a potential new approach to treat persistent gait disturbances in patients suffering from chronic incomplete spinal cord injury. PMID: 24154600
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.306 | 0.134 |
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".