Neuroprotection, Plasticity Manipulation, and Regenerative Strategies to Improve Cardiovascular Function following Spinal Cord Injury
Bibliographic record
Abstract
Damage to the central nervous system, as in the case of spinal cord injury (SCI), results in disrupted supraspinal sympathetic influence and subsequent cardiovascular control impairments. Consequently, people with SCI suffer from disordered basal hemodynamics and devastating fluctuations in blood pressure, as in the case of autonomic dysreflexia (AD), which likely contribute to this population's leading cause of mortality: cardiovascular disease. The development of AD is related, at least in part, to neuroanatomical changes that include disrupted descending supraspinal sympathetic control, changes in propriospinal circuitry, and inappropriate afferent sprouting in the dorsal horn. These anatomical mechanisms may thus be targeted by neural regenerative and protective therapies to improve cardiovascular control and reduce AD. Here, we discuss the relationship between abnormal cardiovascular control and its underlying neuroanatomy. We then review current studies investigating biochemical strategies to reduce the severity of AD through: 1) reducing aberrant calcitonin gene-related peptide immunoreactive afferent sprouting; 2) inhibiting inflammatory processes; and 3) re-establishing descending supraspinal sympathetic control. Finally, we discuss why additional biochemical agents and combinational approaches may be needed to completely ameliorate this condition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".