RNA Sequencing Demonstrates Ex Vivo Neocortical Transcriptomic Changes Induced by Epileptiform Activity in Male and Female Mice

\ua9 2024 Vaughan et al. Seizures are generally associated with epilepsy but may also be a symptom of many other neurological conditions. A hallmark of a seizure is the intensity of the local neuronal activation, which can drive large-scale gene transcription changes. Such changes in the transcriptional profile likely alter neuronal function, thereby contributing to the pathological process. Therefore, there is a strong clinical imperative to characterize how gene expression is changed by seizure activity. To this end, we developed a simplified ex vivo technique for studying sei-zure-induced transcriptional changes. We compared the RNA sequencing profile in mouse neocor-tical tissue with up to 3 h of epileptiform activity induced by 4-aminopyridine (4AP) relative to control brain slices not exposed to the drug. We identified over 100 genes with significantly altered expression after 4AP treatment, including multiple genes involved in MAPK, TNF, and neuroinflammatory signaling pathways, all of which have been linked to epilepsy previously. Notably, the patterns in male and female brain slices were almost identical. Various immediate early genes were among those showing the largest upregulation. The set of down-regulated genes included ones that might be expected either to increase or to decrease neuronal excitability. In summary, we found the seizure-induced transcriptional profile complex, but the changes aligned well with an analysis of published epilepsy-associated genes. We discuss how simple models may provide new angles for investigating seizure-induced transcriptional changes

A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

Evaluation of an eHealth intervention aiming to promote healthy food habits from infancy -the Norwegian randomized controlled trial Early Food for Future Health

Confirmatory factor analysis for the Child Eating Behavior Questionnaire; factor loadings for all items and Cronbach alpha scores for each factor structure. (PDF 210 kb