Resident immune responses to spinal cord injury: role of astrocytes and microglia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Spinal cord injury can be traumatic or non-traumatic in origin, with the latter rising in incidence and prevalence with the aging demographics of our society. Moreover, as the global population ages, individuals with co-existent degenerative spinal pathology comprise a growing number of traumatic spinal cord injury cases, especially involving the cervical spinal cord. This makes recovery and treatment approaches particularly challenging as age and comorbidities may limit regenerative capacity. For these reasons, it is critical to better understand the complex milieu of spinal cord injury lesion pathobiology and the ensuing inflammatory response. This review discusses microglia-specific purinergic and cytokine signaling pathways, as well as microglial modulation of synaptic stability and plasticity after injury. Further, we evaluate the role of astrocytes in neurotransmission and calcium signaling, as well as their border-forming response to neural lesions. Both the inflammatory and reparative roles of these cells have eluded our complete understanding and remain key therapeutic targets due to their extensive structural and functional roles in the nervous system. Recent advances have shed light on the roles of glia in neurotransmission and reparative injury responses that will change how interventions are directed. Understanding key processes and existing knowledge gaps will allow future research to effectively target these cells and harness their regenerative potential.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it