Back

Connexin 40 deficiency alters the temporal profile of postictal oxygen dynamics following focal seizures.

Welsh, D. G.; Farrell, J. S.; Teskey, G. C.; Zechariah, A.

2026-09-28 neuroscience
10.64898/2026.09.21.750745 bioRxiv
Show abstract

Epilepsy is increasingly recognized as a disorder involving both neuronal and vascular dysfunction. While connexin signaling has been implicated in epileptogenesis, the contribution of vascular connexins to seizure associated cerebrovascular pathology remains poorly understood. Connexin40 (Cx40) is an endothelial gap junction protein that plays a crucial role in vascular communication and blood-flow regulation. Seizures induce dynamic changes in cerebral perfusion and oxygenation, including prolonged postictal hypoperfusion/hypoxia. To determine whether Cx40 influences postictal hypoxia following focal seizures, we examined seizure characteristics and postictal oxygen dynamics in Cx40 knockout (Cx40-/-) mice using an established focal hippocampal seizure model. Electrically kindled seizures were elicited in wild-type and Cx40-/- mice, and local hippocampal tissue oxygenation was continuously monitored before and after seizure induction. Seizure duration did not differ between genotypes, indicating comparable seizure severity. Interestingly, Cx40 deletion altered the temporal pattern of postictal oxygen recovery, producing greater early hypoxia and a delayed secondary rebound in pO2 despite similar peak oxygen levels and overall hypoxic burden. These findings demonstrate that loss of Cx40 selectively alters the temporal profile of postictal oxygen dynamics without affecting seizure duration. Taken together, the results suggest that endothelial gap junctional communication contributes to postictal vascular recovery and identify Cx40 as a potential modulator of seizure associated neurovascular dysfunction.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.