Recombinant Human TNF <i>α</i> Induces Concentration-Dependent and Reversible Alterations in the Electrophysiological Properties of Axons in Mammalian Spinal Cord
Bibliographic record
Abstract
Increased expression of the proinflammatory cytokine tumor necrosis factor-alpha (TNFalpha) and its soluble receptors is evident within the central nervous system (CNS) following traumatic brain injury and spinal cord injury. TNFalpha is integral to the acute inflammatory cascade that follows neurotrauma and has been shown to have both beneficial and detrimental properties. We examined the effects of varying concentrations (1-5000 ng/mL) of recombinant human TNFalpha (rhTNFalpha) on select electrophysiological properties of excised guinea pig spinal cord tissue. Pulsed electrical stimuli (0.33 Hz) were delivered to strips of isolated ventral white matter in a double sucrose gap chamber. Recordings were made of the compound action potential (CAP) and membrane potential before, during, and after bathing the tissue with rhTNFalpha for 30 min. Increasing concentrations of rhTNFalpha yielded progressively greater reductions in amplitude of the CAP that were temporally associated with depolarization of the resting compound membrane potential. These effects were largely reversed on washout of rhTNFalpha and were not present when heat-denatured rhTNFalpha was introduced. The results provide evidence that elevated concentrations of TNFalpha induce reversible depolarization of the compound membrane potential and reduction in CAP amplitude, sometimes to the point of extinction of the CAP, suggestive of impaired axonal conduction. These observations point to a new mechanism of immune-mediated central conduction deficit. Cytokine-induced alterations in membrane properties and axonal conduction may contribute to neurological deficits following CNS injury by compounding trauma-induced myelinopathy and axonopathy.
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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".