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Record W4396830514 · doi:10.3171/2024.2.spine23757

Safety of mapping the motor networks in the spinal cord using penetrating microelectrodes in Yucatan minipigs

2024· article· en· W4396830514 on OpenAlexaff
Soroush Mirkiani, Carly L. O’Sullivan, David A. Roszko, Pouria Faridi, David S Hu, Dirk G. Everaert, Amirali Toossi, Ryan Kang, Tongzhou Fang, Neil Tyreman, Ashley N Dalrymple, Kevin Robinson, Richard R. E. Uwiera, Hamid Shah, Richard Fox, Peter E. Konrad, Vivian K. Mushahwar

Bibliographic record

VenueJournal of Neurosurgery Spine · 2024
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of TorontoWomen and Children’s Health Research InstituteUniversity of Alberta
Fundersnot available
KeywordsSpinal cordMicroelectrodeSpinal cord injuryComputer scienceNeurosciencePsychologyPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: The goal of this study was to assess the safety of mapping spinal cord locomotor networks using penetrating stimulation microelectrodes in Yucatan minipigs (YMPs) as a clinically translational animal model. METHODS: Eleven YMPs were trained to walk up and down a straight line. Motion capture was performed, and electromyographic (EMG) activity of hindlimb muscles was recorded during overground walking. The YMPs underwent a laminectomy and durotomy to expose the lumbar spinal cord. Using an ultrasound-guided stereotaxic frame, microelectrodes were inserted into the spinal cord in 8 animals. Pial cuts were made to prevent tissue dimpling before microelectrode insertion. Different locations within the lumbar enlargement were electrically stimulated to map the locomotor networks. The remaining 3 YMPs served as sham controls, receiving the laminectomy, durotomy, and pial cuts but not microelectrode insertion. The Porcine Thoracic Injury Behavioral Scale (PTIBS) and hindlimb reflex assessment results were recorded for 4 weeks postoperatively. Overground gait kinematics and hindlimb EMG activity were recorded again at weeks 3 and 4 postoperatively and compared with preoperative measures. The animals were euthanized at the end of week 4, and the lumbar spinal cords were extracted and preserved for immunohistochemical analysis. RESULTS: All YMPs showed transient deficits in hindlimb function postoperatively. Except for 1 YMP in the experimental group, all animals regained normal ambulation and balance (PTIBS score 10) at the end of weeks 3 and 4. One animal in the experimental group showed gait and balance deficits by week 4 (PTIBS score 4). This animal was excluded from the kinematics and EMG analyses. Overground gait kinematic measures and EMG activity showed no significant (p > 0.05) differences between preoperative and postoperative values, and between the experimental and sham groups. Less than 5% of electrode tracks were visible in the tissue analysis of the animals in the experimental group. There was no statistically significant difference in damage caused by pial cuts between the experimental and sham groups. Tissue damage due to the pial cuts was more frequently observed in immunohistochemical analyses than microelectrode tracks. CONCLUSIONS: These findings suggest that mapping spinal locomotor networks in porcine models can be performed safely, without lasting damage to the spinal cord.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.097
GPT teacher head0.376
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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