Acute Histologic Effects and Thermal Distribution Profile of Disc Biacuplasty Using a Novel Water-Cooled Bipolar Electrode System in an<i>In vivo</i>Porcine Model
Bibliographic record
Abstract
BACKGROUND: Thermal treatment of the lumbar intervertebral disc has been suggested for the treatment of chronic discogenic pain. Disc biacuplasty (D-BAC) is a novel procedure that uses two water-cooled radiofrequency electrodes in a bipolar configuration to heat a large volume of the posterior annulus fibrosus. METHODS: Seven porcine lumbar discs were treated with D-BAC to assess acute effects on the treated tissue in a "worst-case"in vivo model. Intradiscal and peridiscal temperatures were measured during treatment and histologic analysis was used to assess for evidence of acute thermal injury. RESULTS: Temperature monitoring at designated safety zones outside the disc demonstrated maintenance of near-physiologic conditions while temperature in the inner posterior annulus reached 65 degrees C. Histologic sections of treated discs demonstrated no evidence of thermal damage to the dorsal root ganglia or spinal nerve roots when compared with controls. Increased coarseness of the fibrillar matrix and loss of cellular detail were noted in the nucleus pulposus of treated discs. DISCUSSION: Disc biacuplasty, in a porcine model, achieves suitable temperatures to induce thermal transition of collagen and thermoneurolysis while showing no evidence of damage to neural tissue in safety zones surrounding the disc.
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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".