TGF- receptor-mediated albumin uptake into astrocytes is involved in neocortical epileptogenesis
Bibliographic record
Abstract
It has long been recognized that insults to the cerebral cortex, such as trauma, ischaemia or infections, may result in the development of epilepsy, one of the most common neurological disorders. Human and animal studies have suggested that perturbations in neurovascular integrity and breakdown of the blood-brain barrier (BBB) lead to neuronal hypersynchronization and epileptiform activity, but the mechanisms underlying these processes are not known. In this study, we reveal a novel mechanism for epileptogenesis in the injured brain. We used focal neocortical, long-lasting BBB disruption or direct exposure to serum albumin in rats (51 and 13 animals, respectively, and 26 controls) as well as albumin exposure in brain slices in vitro. Most treated slices (72%, n = 189) displayed hypersynchronous propagating epileptiform field potentials when examined 5-49 days after treatment, but only 14% (n = 71) of control slices showed similar responses. We demonstrate that direct brain exposure to serum albumin is associated with albumin uptake into astrocytes, which is mediated by transforming growth factor beta receptors (TGF-betaRs). This uptake is followed by down regulation of inward-rectifying potassium (Kir 4.1) channels in astrocytes, resulting in reduced buffering of extracellular potassium. This, in turn, leads to activity-dependent increased accumulation of extracellular potassium, resulting in facilitated N-methyl-d-aspartate-receptor-mediated neuronal hyperexcitability and eventually epileptiform activity. Blocking TGF-betaR in vivo reduces the likelihood of epileptogenesis in albumin-exposed brains to 29.3% (n = 41 slices, P < 0.05). We propose that the above-described cascade of events following common brain insults leads to brain dysfunction and eventually epilepsy and suggest TGF-betaRs as a possible therapeutic target.
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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) | 0.000 | 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 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".