Search Results (63)

Pyridoxine-dependent epilepsy (PDE) represents a group of rare developmental and epileptic encephalopathies. The most common PDE is caused by biallelic pathogenic variants in ALDH7A1 (PDE-ALDH7A1; OMIM #266100), which encodes α-aminoadipate semialdehyde (α-AASA) dehydrogenase, a key enzyme in lysine catabolism. Affected individuals present with seizures unresponsive to conventional anticonvulsant medications but responsive to high-dose of pyridoxine (vitamin B6). Adjunctive lysine restriction and arginine supplementation have also shown potential in improving neurodevelopmental outcomes. Given the significant benefit of early intervention, PDE-ALDH7A1 is a strong candidate for newborn screening (NBS). However, traditional biomarkers are biochemically unstable at room temperature (α-AASA and piperideine-6-carboxylate) or lack sufficient specificity (pipecolate), limiting their utility for biomarker-based NBS. The recent identification of two novel and stable biomarkers, 2S,6S-/2S,6R-oxopropylpiperidine-2-carboxylate (2-OPP) and 6-oxo-pipecolate (oxo-PIP), offers renewed potential for biochemical NBS. We evaluated the feasibility of incorporating 2-OPP, oxo-PIP, and pipecolate into routine butylated FIA-MS/MS workflows used for biochemical NBS. A total of 9402 dried blood spots (DBS), including nine confirmed PDE-ALDH7A1 patients and 9393 anonymized controls were analyzed using a single multiplex assay. 2-OPP emerged as the most sensitive biomarker, identifying all PDE-ALDH7A1 patients with 100% sensitivity and a positive predictive value (PPV) of 18.4% using a threshold above the 99.5th percentile. Combining elevated 2-OPP (above the 99.5th percentile) with either pipecolate or oxo-PIP (above the 85.0th percentile) as secondary marker detected within the same multiplex FIA-MS/MS assay further improved the PPVs to 60% and 45%, respectively, while maintaining compatibility with butanol-derivatized method. Notably, increasing the 2-OPP threshold above the 99.89th percentile, in combination with either pipecolate or oxo-PIP above the 85.0th percentile resulted in both 100% sensitivity and 100% PPV. This study supports the strong potential of 2-OPP-based neonatal screening for PDE-ALDH7A1 within existing NBS infrastructures. The ability to multiplex 2-OPP, pipecolate and oxo-PIP within a single assay offers a robust, practical, high-throughput and cost-effective approach. These results support the inclusion of PDE-ALDH7A1 in existing biochemical NBS panels. Further prospective studies in larger cohorts are needed to refine cutoffs and confirm clinical performance. Full article

Epileptic seizure detection and classification from EEG recordings faces significant challenges due to extreme class imbalance. Analysis of the Temple University Hospital Seizure (TUSZ) dataset reveals imbalance ratios of 150:1 between common and rare seizure types, with high temporal heterogeneity (seizure durations of 1–1638 s). We propose a cascaded deep learning architecture with two specialized CNNs: a binary detector followed by a multi-class classifier. This approach decomposes the classification problem, reducing the maximum imbalance from 150:1 to manageable levels (9:1 binary, 5:1 type). The architecture implements a high-confidence filtering mechanism (threshold = 0.9), creating a 99.5% pure dataset for type classification, dynamic class-weighted optimization proportional to inverse class frequencies, and information flow refinement through progressive stages. Loss dynamics analysis reveals that our weighting scheme strategically redistributes optimization attention, reducing variance by 90.7% for majority classes while increasing variance for minority classes, ensuring all seizure types receive proportional learning signals regardless of representation. The binary classifier achieves 99.64% specificity and 98.23% sensitivity (ROC-AUC = 0.995). The type classifier demonstrates >99% accuracy across seven seizure categories with perfect (100%) classification for three seizure types despite minimal representation. Cross-dataset validation on the University of Bonn dataset confirms robust generalization (96.0% accuracy) for binary seizure detection. This framework effectively addresses multi-level imbalance in neurophysiological signal classification with hierarchical class structures. Full article

Tetanus, a severe and life-threatening illness caused by Clostridium tetani, produces symptoms such as muscle spasms, muscle stiffness and seizures caused by the production of tetanus neurotoxin (TeNT). TeNT causes spastic paralysis through the inhibition of neurotransmission in spinal inhibitory interneurons. This is achieved, in part, through pH-triggered membrane insertion of the translocation (HCT) domain, which delivers the catalytic light-chain (LC) domain to the cytosol. While the function of HCT is well defined, the mechanism by which it accomplishes this task is largely unknown. Based on the crystal structure of tetanus neurotoxin, we identified potential polar interactions between arginine 711, tryptophan 715 and aspartate 821 that appear to be evolutionarily conserved across the clostridial neurotoxin family. We show that the disruption of the Asp-Arg pair in a beltless HCT variant (bHCT) results in changes in thermal stability without significant alterations to the overall secondary structure. ANS (1-anilino-8-napthalene sulfonate) binding studies, in conjunction with liposome permeabilization assays, demonstrate that mutations at R711 or D821 trigger interactions with the membrane at higher pH values compared to wildtype bHCT. Interestingly, we show that the introduction of the D821N mutation into LH_NT (LC-HCT only), but not the holotoxin, resulted in the increased cleavage of VAMP 2 in cortical neurons relative to the wildtype protein. This suggests that, as observed for botulinum toxin A, the receptor-binding domain is not necessary for LC translocation but rather helps determine the pH threshold of membrane insertion. The mutation of W715 did not result in detectable changes in the activity of either bHCT or the holotoxin, suggesting that it plays only a minor role in stabilizing the structure of the toxin. We conclude that the protonation of D821 at low pH disrupts interactions with R711 and W715, helping to drive the conformational refolding of HCT needed for membrane insertion and the subsequent translocation of the LC. Full article

Zuranolone (SAGE-217), the first FDA-approved oral neurosteroid (NAS), a positive allosteric modulator (PAM) of γ-aminobutyric acid type A (GABA_A) receptor for postpartum depression approved in 2023, has limitations such as short half-life, low bioavailability, and central inhibitory side effects. To address these, we designed novel C-21 modified derivatives of Zuranolone, identifying the triazolone scaffold as key for enhancing GABA_A activity. Here, we synthesized Zuranolone analogs with diverse triazolone substituents, finding that pyridine-derived modifications improved the activity correlated with LogP. The optimal derivative, S9 (2-(trifluoroethoxy)pyridine-triazolone, LogP 4.61), showed 2.5-fold greater potency (EC₅₀) and efficacy (Emax) than Zuranolone (LogP 4.78) at synaptic/extrasynaptic GABA_A receptors, attributed to stronger binding via molecular docking. In rats, S9 exhibited 5-fold longer plasma T_1/2, 6-fold higher AUC, 3-fold greater brain exposure, and 30% improved bioavailability. It also outperformed Zuranolone in pentylenetetrazole (PTZ)-induced seizure suppression and threshold dose for loss of righting reflex (LORR) in rats. The C21-pyridine-triazolone pharmacophore in S9 enhances receptor activity potency without increasing lipophilicity, optimizing pharmacokinetics and safety, which makes it a promising therapeutic candidate for depression and epilepsy. Full article

Epilepsy is a multifaceted neurological disorder characterized by recurrent seizures and associated with molecular and immune alterations in key brain regions. The GASH/Sal (Genetic Audiogenic Seizure Hamster, Salamanca), a genetic model for audiogenic epilepsy, provides a powerful tool to study seizure mechanisms and resistance in predisposed individuals. This study investigates the proteomic and immune responses triggered by audiogenic kindling in the inferior colliculus, comparing non-responder animals exhibiting reduced seizure severity following repeated stimulation versus GASH/Sal naïve hamsters. To assess auditory pathway functionality, Auditory Brainstem Responses (ABRs) were recorded, revealing reduced neuronal activity in the auditory nerve of non-responders, while central auditory processing remained unaffected. Cytokine profiling demonstrated increased levels of proinflammatory markers, including IL-1 alpha (Interleukin-1 alpha), IL-10 (Interleukin-10), and TGF-beta (Transforming Growth Factor beta), alongside decreased IGF-1 (Insulin-like Growth Factor 1) levels, highlighting systemic inflammation and its interplay with neuroprotection. Building on these findings, a proteomic analysis identified 159 differentially expressed proteins (DEPs). Additionally, bioinformatic approaches, including Gene Set Enrichment Analysis (GSEA) and Weighted Gene Co-expression Network Analysis (WGCNA), revealed disrupted pathways related to metabolic and inflammatory epileptic processes and a module potentially linked to a rise in the threshold of seizures, respectively. Differentially expressed genes, identified through bioinformatic and statistical analyses, were validated by RT-qPCR. This confirmed the upregulation of six genes (Gpc1—Glypican-1; Sdc3—Syndecan-3; Vgf—Nerve Growth Factor Inducible; Cpne5—Copine 5; Agap2—Arf-GAP with GTPase domain, ANK repeat, and PH domain-containing protein 2; and Dpp8—Dipeptidyl Peptidase 8) and the downregulation of two (Ralb—RAS-like proto-oncogene B—and S100b—S100 calcium-binding protein B), aligning with reduced seizure severity. This study may uncover key proteomic and immune mechanisms underlying seizure susceptibility, providing possible novel therapeutic targets for refractory epilepsy. Full article

Background/Objectives: Temporal lobe epilepsy (TLE) often develops following an initial brain injury, where specific triggers lead to epileptogenesis—a process transforming a healthy brain into one prone to spontaneous, recurrent seizures. Although electroencephalography (EEG) remains the primary diagnostic tool for epilepsy, it cannot predict the risk of epilepsy after brain injury. This limitation highlights the need for biomarkers, particularly those measurable in peripheral samples, to assess epilepsy risk. This study investigated urinary metabolites in a rat model of TLE to identify biomarkers that track epileptogenesis progression across the acute, latent, and chronic phases and elucidate the underlying mechanisms. Methods: Status epilepticus (SE) was induced in rats using repeated intraperitoneal injections of lithium chloride–pilocarpine hydrochloride. Urine samples were collected 48 h, 1 week, and 6 weeks after SE induction. Nuclear magnetic resonance spectrometry was used for metabolomic analysis, and statistical evaluations were performed using MetaboAnalyst 6.0. Differences between epileptic and control groups were represented using the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Volcano plot analysis identified key metabolic changes, applying a fold-change threshold of 1.5 and a p-value < 0.05. Results: The acute phase exhibited elevated levels of acetic acid, dihydrothymine, thymol, and trimethylamine, whereas glycolysis and tricarboxylic acid cycle metabolites, including pyruvic and citric acids, were reduced. Both the acute and latent phases showed decreased theobromine, taurine, and allantoin levels, with elevated 1-methylhistidine in the latent phase. The chronic phase exhibited reductions in pimelic acid, tiglylglycine, D-lactose, and xanthurenic acid levels. Conclusions: These findings highlight stage-specific urinary metabolic changes in TLE, suggesting distinct metabolites as biomarkers for epileptogenesis and offering insights into the mechanisms underlying SE progression. Full article

Classification of neurocognitive states from Electroencephalography (EEG) data is complex due to inherent challenges such as noise, non-stationarity, non-linearity, and the high-dimensional and sparse nature of connectivity patterns. Graph-theoretical approaches provide a powerful framework for analysing the latent state dynamics using connectivity measures across spatio-temporal-spectral dimensions. This study applies the graph Koopman embedding kernels (GKKE) method to extract latent neuro-markers of seizures from epileptiform EEG activity. EEG-derived graphs were constructed using correlation and mean phase locking value (mPLV), with adjacency matrices generated via threshold-binarised connectivity. Graph kernels, including Random Walk, Weisfeiler–Lehman (WL), and spectral-decomposition (SD) kernels, were evaluated for latent space feature extraction by approximating Koopman spectral decomposition. The potential of graph Koopman embeddings in identifying latent metastable connectivity structures has been demonstrated with empirical analyses. The robustness of these features was evaluated using classifiers such as Decision Trees, Support Vector Machine (SVM), and Random Forest, on Epilepsy-EEG from the Children’s Hospital Boston’s (CHB)-MIT dataset and cognitive-load-EEG datasets from online repositories. The classification workflow combining mPLV connectivity measure, WL graph Koopman kernel, and Decision Tree (DT) outperformed the alternative combinations, particularly considering the accuracy (91.7%) and F1-score (88.9%), The comparative investigation presented in results section convinces that employing cost-sensitive learning improved the F1-score for the mPLV-WL-DT workflow to 91% compared to 88.9% without cost-sensitive learning. This work advances EEG-based neuro-marker estimation, facilitating reliable assistive tools for prognosis and cognitive training protocols. Full article

Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures. This study proposes a novel closed-loop epilepsy detection system and stimulation control chip. A time-domain detection algorithm based on amplitude, slope, line length, and signal energy characteristics is introduced. A new threshold calculation method is proposed; that is, the threshold is updated by means of the mean and standard deviation of four consecutive eigenvalues through parameter combination. Once a seizure is detected, the system begins to control the stimulation of a two-phase pulse current with an amplitude and frequency of 34 μA and 200 Hz, respectively. The system is physically designed on the basis of the UMC 55 nm process and verified by a field programmable gate array verification board. This research is conducted through innovative algorithms to reduce power consumption and the area of the circuit. It can maintain a high accuracy of more than 90% and perform seizure detection every 64 ms. It is expected to provide a new treatment for patients with epilepsy. Full article

Objectives: This study evaluated the psychometric properties of the ceroid lipofuscinosis type 2 Quality of Life (CLN2 QoL) questionnaire. Methods: Data from children with CLN2 disease aged 3–16 years receiving cerliponase alfa in the BMN 190-201 and BMN 190-202 clinical studies, collected via purposive sampling, were used to assess convergent and divergent validity, internal consistency and reliability. The clinically important difference (CID) was estimated with distribution- and anchor-based methods. Descriptive and inferential statistical analyses were conducted using IBM SPSS. Results: CLN2 QoL data of 22 participants were analysed. Ceiling effects were observed in 22 items (35% threshold); no floor effects were observed. Internal consistency analysis showed good reliability (Cronbach’s alpha and Omega reliability >0.7) for four domains at study completion; only one domain had good reliability at baseline. All domains had good test–retest reliability (correlation >0.5) except Feeding With G-Tube and Seizures. Convergent and divergent correlation analysis showed moderate-strong correlations (>0.4) between PedsQL and CLN2 QoL total scores, between the Pediatric Quality of Life Inventory (PedsQL) total score and most CLN2 QoL domains at baseline, and between CLN2 QoL total score and most PedsQL domains at week 97. Known groups validity showed a significant difference in means for the Behaviour domain (p = 0.05) for reasons that could not be clarified. CID was 6.79–12.94 for domains; total score CID was 6.91 using distribution-based and 6.13–13.05 using anchor-based methods. Conclusions: This study is the first to validate the CLN2 QoL and to estimate the CID of this instrument in CLN2 patients. Our results show good validity and reliability of this tool. Full article

Over the past decade, quetiapine has become one of the most commonly used psychotropic drugs in acute intoxication events worldwide. A structured literature review and analysis were conducted to assess the relationship between the kinetic and dynamic profiles in acute quetiapine intoxication. The correlation between dose and peak serum concentration (c_max) was determined using Pearson’s correlation coefficient. Binary logistic regression was used to evaluate dose and c_max as predictors of the most common clinical events, signs and symptoms. One hundred and thirty-four cases of acute quetiapine ingestion were included in the analysis, with a median ingested dose of 10 g and a median c_max of 4 mg/L. The typical half-life was estimated to be 16.5 h, significantly longer than at therapeutic doses. For the immediate-release formulation, a biphasic disposition could not be excluded. Dose and c_max demonstrated a weak but significant correlation (r = 0.256; N = 63; p = 0.043). Central nervous system depression and tachycardia were the most common clinical signs. Higher doses and concentrations increased the risk of severe intoxication and were good predictors of intubation, tachycardia, hypotension, QT_c prolongation and seizures, but not QRS prolongation, arrhythmia, heart block, hypokalaemia or acidosis. The thresholds for dose and c_max that increased the risk for individual signs and symptoms varied widely. However, doses > 3 g or c_max > 2 mg/L can be considered as alert levels that represent a high risk for severe clinical course of acute quetiapine intoxication. Full article

In animal models of epilepsy, cranial surgery is often required to implant electrodes for electroencephalography (EEG) recording. However, electrode implants can lead to the activation of glial cells and interfere with physiological neuronal activity. In this study, we evaluated the impact of epidural electrode implants in the pilocarpine mouse model of temporal lobe epilepsy. Brain neuroinflammation was assessed 1 and 3 weeks after surgery by cytokines quantification, immunohistochemistry, and western blotting. Moreover, we investigated the effect of pilocarpine, administered two weeks after surgery, on mice mortality rate. The reported results indicate that implanted mice suffer from neuroinflammation, characterized by an early release of pro-inflammatory cytokines, microglia activation, and subsequent astrogliosis, which persists after three weeks. Notably, mice subjected to electrode implants displayed a higher mortality rate following pilocarpine injection 2 weeks after the surgery. Moreover, the analysis of EEGs recorded from implanted mice revealed a high number of single spikes, indicating a possible increased susceptibility to seizures. In conclusion, epidural electrode implant in mice promotes neuroinflammation that could lower the seizure thresholds to pilocarpine and increase the death rate. An improved protocol considering the persistent neuroinflammation induced by electrode implants will address refinement and reduction, two of the 3Rs principles for the ethical use of animals in scientific research. Full article

The discovery of new peptides and their derivatives is an outcome of ongoing efforts to identify a peptide with significant biological activity for effective usage as a possible therapeutic agent. Spinorphin peptides have been documented to exhibit numerous applications and features. In this study, biologically active peptide derivatives based on novel peptide analogues of spinorphin conjugated with 5,5′-dimethyl (Dm) and 5,5′-diphenyl (Ph) hydantoin derivatives have been successfully synthesized and characterized. Scanning electron microscopy (SEM) and spectral methods such as UV-Vis, FT-IR (Fourier Transform Infrared Spectroscopy), CD (Circular Dichroism), and fluorimetry were used to characterize the microstructure of the resulting compounds. The results revealed changes in peptide morphology as a result of the restructuring of the aminoacidic sequences and aromatic bonds, which is related to the formation of intermolecular hydrogen bonds between tyrosyl groups and the hydantoin moiety. Electrochemical and fluorescence approaches were used to determine some physicochemical parameters related to the biological behavior of the compounds. The biological properties of the spinorphin derivatives were evaluated in vivo for anticonvulsant activity against the psychomotor seizures at different doses of the studied peptides. Both spinorphin analog peptides with Ph and Dm groups showed activity against all three phases of the seizure in the intravenous Pentylenetetrazole Seizure (ivPTZ) test. This suggests that hydantoin residues do not play a crucial role in the structure of spinorphin compounds and in determining the potency to raise the seizure threshold. On the other hand, analogs with a phenytoin residue are active against the drug-resistant epilepsy test (6-Hz test). In addition, bioactivity analyses revealed that the new peptide analogues have the potential to be used as antimicrobial and antioxidant compounds. These findings suggest promising avenues for further research that may lead to the development of alternative medicines or applications in various fields beyond epilepsy treatment. Full article

Objectives and Aim: The primary aim of this study was to conduct a comparative analysis of the safety and efficacy of levetiracetam (LEV) and phenobarbital (PB) as first-line treatments for neonatal seizure management. This study was designed to measure and compare the incidence of adverse effects and to determine the discharge and mortality rates associated with the use of these antiseizure medications (ASMs). Through this comparison, this research sought to provide insights to optimise care for neonates experiencing seizures. Materials and Methods: This retrospective cohort study evaluated 104 neonates treated for seizures at Zeynep Kamil Hospital from 2015 to 2020 after excluding those on non-PB/LEV antiseizure medications. Seizures were characterised using electroencephalogram (EEG) and categorised according to aetiology and frequency. Treatment efficacy was gauged by seizure cessation, as confirmed using EEG. Adverse effects and demographic data were recorded. Statistical analyses were conducted using SPSS, employing the Shapiro–Wilk, independent t-test, Mann–Whitney U test, and chi-square test, with a significance threshold of p < 0.05. Results: Overall, 104 neonates treated with first-line ASM were evaluated for efficacy; PB was administered in 68.26% of the cases, while LEV was utilised in 31.74%. The total complete response rate was 40.38%, with no significant difference between the PB and LEV groups (p = 0.309). The incidence rate ratios (IRRs) demonstrated that seizure frequency profoundly influenced treatment effectiveness, with IRRs of 2.09 for rare seizures, 3.25 for frequent seizures, and 4.01 for status epilepticus, indicating a higher treatment response rate with increasing seizure frequency. For second-line treatment, among a subset of 62 patients, PB had a slight, non-significant advantage over LEV, with an odds ratio of 1.09, suggesting a marginally better response to LEV. Adverse events were significantly more frequent in the PB group, affecting 19 of 67 neonates (28.36%), compared to only 2 of 71 neonates (2.82%) in the LEV group (p < 0.001). No significant difference was observed in the discharge rates between the two groups (PB, 67.61%; LEV, 75.76%; p = 0.674). Interestingly, the mortality rate was significantly higher in the LEV group (45.45%) than that in the PB group (22.54%; p = 0.045). Conclusion: This study underscores LEV’s superior safety profile over PB in neonatal seizure management, evidenced by a significantly lower rate of adverse events. PB seems to be more effective in the second-line treatment of neonatal seizures. Despite the lack of significant differences in the discharge rates, the higher mortality rate associated with LEV warrants further investigation. These findings advocate the cautious selection of antiepileptic drugs in neonatal care, with a preference for LEV based on its safety profile. Full article

Hypoglycemia is a particular problem in people with diabetes while it can also occur in other clinical circumstances. Hypoglycemia unawareness describes a condition in which autonomic and neuroglycopenic symptoms of hypoglycemia decrease and hence are hardly perceivable. A failure to recognize hypoglycemia in time can lead to unconsciousness, seizure, and even death. The risk factors include intensive glycemic control, prior episodes of severe hypoglycemia, long duration of diabetes, alcohol consumption, exercise, renal failure, and sepsis. The pathophysiological mechanisms are manifold, but mainly concern altered brain glucose sensing, cerebral adaptations, and an impaired hormonal counterregulation with an attenuated release of glucagon, epinephrine, growth hormone, and other hormones, as well as impaired autonomous and neuroglycopenic symptoms. Physiologically, this counterregulatory response causes blood glucose levels to rise. The impaired hormonal counterregulatory response to recurrent hypoglycemia can lead to a vicious cycle of frequent and poorly recognized hypoglycemic episodes. There is a shift in glycemic threshold to trigger hormonal counterregulation, resulting in hypoglycemia-associated autonomic failure and leading to the clinical syndrome of hypoglycemia unawareness. This clinical syndrome represents a particularly great challenge in diabetes treatment and, thus, prevention of hypoglycemia is crucial in diabetes management. This mini-review provides an overview of hypoglycemia and the associated severe complication of impaired hypoglycemia awareness and its symptoms, pathophysiology, risk factors, consequences, as well as therapeutic strategies. Full article

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images is an alternative to signal inspection, but subtle variations may escape the human eye. Here, we propose a deep learning-based metric of visual complexity to interpret TF images extracted from iEEG data and aim to assess its ability to identify the EZ in the brain. We analyzed interictal iEEG data from 1928 contacts recorded from 20 children with drug-resistant epilepsy who became seizure-free after neurosurgery. We localized each iEEG contact in the MRI, created TF images (1–70 Hz) for each contact, and used a pre-trained VGG16 network to measure their visual complexity by extracting unsupervised activation energy (UAE) from 13 convolutional layers. We identified points of interest in the brain using the UAE values via patient- and layer-specific thresholds (based on extreme value distribution) and using a support vector machine classifier. Results show that contacts inside the seizure onset zone exhibit lower UAE than outside, with larger differences in deep layers (L10, L12, and L13: p < 0.001). Furthermore, the points of interest identified using the support vector machine, localized the EZ with 7 mm accuracy. In conclusion, we presented a pre-surgical computerized tool that facilitates the EZ localization in the patient’s MRI without requiring long-term iEEG inspection. Full article