Neuroinflammation has emerged as a shared molecular mechanism in epilepsy and cognitive impairment, offering new insights into the complex interplay between immune responses and brain function. Evidence reveals involvement of High mobility group box 1 (HMGB1) in blood-brain barrier disruption and correlations with epilepsy severity and drug resistance. While anti-inflammatory treatments show promise, translating these discoveries faces challenges in elucidating mechanisms and developing reliable biomarkers. However, strategically targeting neuroinflammation and HMGB1-mediated inflammation holds therapeutic potential. This review synthesises knowledge on HMGB1 and related biomarkers in epilepsy and cognitive impairment to shape future research and treatments targeting these intricate inflammatory processes.
Down syndrome (DS), is the most common cause of intellectual disability, and is characterized by defective neurogenesis during perinatal development. To identify metabolic aberrations in early neurogenesis, we profiled neurospheres derived from the embryonic brain of Ts1Cje, a mouse model of Down syndrome. High-throughput phenotypic microarray revealed a significant decrease in utilisation of 17 out of 367 substrates and significantly higher utilisation of 6 substrates in the Ts1Cje neurospheres compared to controls. Specifically, Ts1Cje neurospheres were less efficient in the utilisation of glucose-6-phosphate suggesting a dysregulation in the energy-producing pathway. T Cje neurospheres were significantly smaller in diameter than the controls. Subsequent preliminary study on supplementation with 6-phosphogluconic acid, an intermediate of glucose-6-phosphate metabolism, was able to rescue the Ts1Cje neurosphere size. This study confirmed the perturbed pentose phosphate pathway, contributing to defects observed in Ts1Cje neurospheres. We show for the first time that this comprehensive energetic assay platform facilitates the metabolic characterisation of Ts1Cje cells and confirmed their distinguishable metabolic profiles compared to the controls.
A reliable seizure detection or prediction device can potentially reduce the morbidity and mortality associated with epileptic seizures. Previous findings indicating alterations in cardiac activity during seizures suggest the usefulness of cardiac parameters for seizure detection or prediction. This study aims to examine available studies on seizure detection and prediction based on cardiac parameters using non-invasive wearable devices. The Embase, PubMed, and Scopus databases were used to systematically search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Human studies that evaluated seizure detection or prediction based on cardiac parameters collected using wearable devices were included. The QUADAS-2 tool and proposed standards for validation for seizure detection devices were used for quality assessment. Twenty-four articles were identified and included in the analysis. Twenty studies evaluated seizure detection algorithms, and four studies focused on seizure prediction. Most studies used either a wrist-worn or chest-worn device for data acquisition. Among the seizure detection studies, cardiac parameters utilized for the algorithms mainly included heart rate (HR) (n = 11) or a combination of HR and heart rate variability (HRV) (n = 6). HR-based seizure detection studies collectively reported a sensitivity range of 56%-100% and a false alarm rate (FAR) of 0.02-8/h, with most studies performing retrospective validation of the algorithms. Three of the seizure prediction studies retrospectively validated multimodal algorithms, combining cardiac features with other physiological signals. Only one study prospectively validated their seizure prediction algorithm using HRV extracted from ECG data collected from a custom wearable device. These studies have demonstrated the feasibility of using cardiac parameters for seizure detection and prediction with wearable devices, with varying algorithmic performance. Many studies are in the proof-of-principle stage, and evidence for real-time detection or prediction is currently limited. Future studies should prioritize further refinement of the algorithm performance with prospective validation using large-scale longitudinal data. PLAIN LANGUAGE SUMMARY: This systematic review highlights the potential use of wearable devices, like wristbands, for detecting and predicting seizures via the measurement of heart activity. By reviewing 24 articles, it was found that most studies focused on using heart rate and changes in heart rate for seizure detection. There was a lack of studies looking at seizure prediction. The results were promising but most studies were not conducted in real-time. Therefore, more real-time studies are needed to verify the usage of heart activity-related wearable devices to detect seizures and even predict them, which will be beneficial to people with epilepsy.
Aims: The JAK-STAT signalling pathway is one of the key regulators of pro-gliogenesis process during brain development. Down syndrome (DS) individuals, as well as DS mouse models, exhibit an increased number of astrocytes, suggesting an imbalance of neurogenic-to-gliogenic shift attributed to dysregulated JAK-STAT signalling pathway. The gene and protein expression profiles of JAK-STAT pathway members have not been characterised in the DS models. Therefore, we aimed to profile the expression of Jak1, Jak2, Stat1, Stat3 and Stat6 at different stages of brain development in the Ts1Cje mouse model of DS. Methods: Whole brain samples from Ts1Cje and wild-type mice at embryonic day (E)10.5, E15, postnatal day (P)1.5; and embryonic cortex-derived neurospheres were collected for gene and protein expression analysis. Gene expression profiles of three brain regions (cerebral cortex, cerebellum and hippocampus) from Ts1Cje and wild-type mice across four time-points (P1.5, P15, P30 and P84) were also analysed. Results: In the developing mouse brain, none of the Jak/Stat genes were differentially expressed in the Ts1Cje model compared to wild-type mice. However, Western blot analyses indicated that phosphorylated (p)-Jak2, p-Stat3 and p-Stat6 were downregulated in the Ts1Cje model. During the postnatal brain development, Jak/Stat genes showed complex expression patterns, as most of the members were downregulated at different selected time-points. Notably, embryonic cortex-derived neurospheres from Ts1Cje mouse brain expressed lower Stat3 and Stat6 protein compared to the wild-type group. Conclusion: The comprehensive expression profiling of Jak/Stat candidates provides insights on the potential role of the JAK-STAT signalling pathway during abnormal development of the Ts1Cje mouse brains.
Notch signalling pathway is involved in the proliferation of neural progenitor cells (NPCs), to inhibit neuronal cell commitment and to promote glial cell fate. Notch protein is cleaved by gamma-secretase, a multisubunit transmembrane protein complex that releases the Notch intracellular domain (NICD) and subsequently activates the downstream targets. Down syndrome (DS) individuals exhibit an increased number of glial cells (particularly astrocytes), and reduced number of neurons suggesting the involvement of Notch signalling pathway in the neurogenic-to-gliogenic shift in DS brain. Ts1Cje is a DS mouse model that exhibit similar neuropathology to human DS individuals. To date, the spatiotemporal gene expression of the Notch and gamma-secretase genes have not been characterised in Ts1Cje mouse brain. Understanding the expression pattern of Notch and gamma-secretase genes may provide a better understanding of the underlying mechanism that leads to the shift. Gene expression analysis using RT-qPCR was performed on early embryonic and postnatal development of DS brain. In the developing mouse brain, mRNA expression analysis showed that gamma-secretase members (Psen1, Pen-2, Aph-1b, and Ncstn) were not differentially expressed. Notch2 was found to be downregulated in the developing Ts1Cje brain samples. Postnatal gene expression study showed complex expression patterns and Notch1 and Notch2 genes were found to be significantly downregulated in the hippocampus at postnatal day 30. Results from RT-qPCR analysis from E15.5 neurosphere culture showed an increase of expression of Psen1, and Aph-1b but downregulation of Pen-2 and Ncstn genes. Gamma-secretase activity in Ts1Cje E15.5 neurospheres was significantly increased by fivefold. In summary, the association and the role of Notch and gamma-secretase gene expression throughout development with neurogenic-to-gliogenic shift in Ts1Cje remain undefined and warrant further validation.
Ruxolitinib is the first janus kinase 1 (JAK1) and JAK2 inhibitor that was approved by the United States Food and Drug Administration (FDA) agency for the treatment of myeloproliferative neoplasms. The drug targets the JAK/STAT signalling pathway, which is critical in regulating the gliogenesis process during nervous system development. In the study, we assessed the effect of non-maternal toxic dosages of ruxolitinib (0-30 mg/kg/day between E7.5-E20.5) on the brain of the developing mouse embryos. While the pregnant mice did not show any apparent adverse effects, the Gfap protein marker for glial cells and S100β mRNA marker for astrocytes were reduced in the postnatal day (P) 1.5 pups' brains. Gfap expression and Gfap+ cells were also suppressed in the differentiating neurospheres culture treated with ruxolitinib. Compared to the control group, adult mice treated with ruxolitinib prenatally showed no changes in motor coordination, locomotor function, and recognition memory. However, increased explorative behaviour within an open field and improved spatial learning and long-term memory retention were observed in the treated group. We demonstrated transplacental effects of ruxolitinib on astrogenesis, suggesting the potential use of ruxolitinib to revert pathological conditions caused by gliogenic-shift in early brain development such as Down and Noonan syndromes.