Search Results (29)

Background. Sturge–Weber syndrome (SWS) is a rare non-hereditary neurovascular disorder characterized by capillary–venous malformations on the face, ocular vascular anomalies, and leptomeningeal capillary–venous malformations. Patients with SWS often experience cerebral perfusion impairment, increasing their risk for stroke-like episodes, seizures, and motor and cognitive impairments. Methods. We report the case of a 2-year-old boy diagnosed with SWS who developed a stroke-like episode following dye laser therapy under deep sedation. Results. Despite initial diagnostic challenges and persistent seizures, appropriate management led to full neurological recovery. Conclusions. This case highlights the importance of considering stroke-like episodes in children with SWS after stressful events such as medical procedures. Full article

Background: Absence epilepsy is a non-convulsive form of genetic generalized epilepsy characterized by spontaneous bilateral spike-and-wave discharges (SWDs) in EEG. In contrast to grand-mal epilepsy, absence epilepsy without greatly expressed motor and interictal EEG abnormalities is difficult to detect, especially at the early stages. The WAG/Rij rat strain is a well-validated animal model of childhood absence epilepsy. At the early, preclinical stage, precursors or immature SWDs appear. Then, with age, immature discharges gradually turn into mature ones and mature SWDs prevail at the clinical stage. Mature SWDs, with an amplitude several times higher than the background EEG, can be easily distinguished visually. However, the amplitude of immature discharges is significantly lower than that of mature SWDs and is comparable to the amplitude of sleep spindles. Therefore, it is quite a difficult problem to distinguish immature discharges from sleep spindles. The task is further complicated by the fact that absence seizures mainly appear in a state of drowsiness and slow-wave (non-REM) sleep, when a lot of sleep spindles occur. The purpose of the present study was to develop a diagnostic method that allows us to precisely distinguish immature forms of epileptic seizures from background EEG and sleep spindles. Methods: The idea of analyzing wave-train electrical activity is to investigate the wavelet spectrum, find local peculiarities in this spectrum, and estimate generalized time-frequency peculiarities of the signal in terms of the found local peculiarities. Results: The criteria for diagnosis of the immature form of epileptic discharges and sleep spindles have been developed based on the analysis of wave-train activity with the construction of AUC diagrams (area under the curve diagrams). Conclusions: The method of wave-train analysis with the construction of AUC diagrams can be used for extracting the diagnostic features necessary for the diagnosis of absence epilepsy at the early stages of the disease in people with a genetic predisposition. Full article

Introduction: Traumatic brain injuries (TBIs) are conditions affecting brain function caused by blunt or penetrating forces to the head. Symptoms may include confusion, impaired consciousness, coma, seizures, and focal or sensory neurological motor injuries. Objective: This study evaluated sex hormone profiles and their predictive role in returning consciousness after severe traumatic brain injury. Materials and Methods: We included 120 patients with TBIs and collected comprehensive information about each patient, including the cause of the trauma, age, gender, Glasgow Coma Scale (GCS) score, Injury Severity Score (ISS), and neuroradiological imaging data. The ISS was used to assess the severity of the trauma. At the same time, the lowest GCS score was recorded either before sedation and intubation in the emergency room or by emergency medical services personnel. For female participants, samples were collected during the luteal phase of the menstrual cycle (days 18 to 23). Results: The mean age of male patients was 33.40 years, ranging from 23 to 45 years, while female patients had an average age of 34.25 years, ranging from 25 to 48 years. The primary cause of injury for both genders was motor vehicle accidents. In male patients, testosterone levels were significantly higher in those classified as responsive (RC) compared to those non-responsive (NRC), with levels of 2.56 ± 0.47 ng/mL versus 0.81 ± 0.41 ng/mL (p = 0.003). A cut-off point of 1.885 ng/mL for testosterone levels in males was established, achieving a sensitivity and specificity of 86.7% and 86.7%, respectively. In female patients, progesterone levels were elevated in those who regained consciousness, measuring 1.80 ± 0.31 ng/mL compared to 0.62 ± 0.31 ng/mL (p = 0.012). A cut-off point of 1.335 ng/mL for progesterone levels in females was determined, with a sensitivity and specificity of 93.3% and 86.7%, respectively. Conclusions: We can conclude that sex hormone levels in the acute phase of TBIs can vary between males and females. Notably, serum testosterone levels in males and progesterone levels in females with TBIs are significant prognostic factors for assessing the likelihood of regaining consciousness after such injuries. These findings underscore the importance of considering sex hormone profiles in TBI recovery prognosis. Full article

In the medical field, there are several very different movement disorders, such as tremors, Parkinson’s disease, or Huntington’s disease. A wide range of motor and non-motor symptoms characterizes them. It is evident that in the modern era, the use of smart wrist devices, such as smartwatches, wristbands, and smart bracelets is spreading among all categories of people. This diffusion is justified by the limited costs, ease of use, and less invasiveness (and consequently greater acceptability) than other types of sensors used for health status monitoring. This systematic review aims to synthesize research studies using smart wrist devices for a specific class of movement disorders. Following PRISMA-S guidelines, 130 studies were selected and analyzed. For each selected study, information is provided relating to the smartwatch/wristband/bracelet model used (whether it is commercial or not), the number of end-users involved in the experimentation stage, and finally the characteristics of the benchmark dataset possibly used for testing. Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. It turned out that most of the studies have been published in the last ten years, showing a growing interest in the scientific community. The selected articles mainly investigate the relationship between smart wrist devices and Parkinson’s disease. Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington’s Disease, ataxia, or Tourette Syndrome. However, the results of this review highlight the difficulties still present in the use of the smartwatch/wristband/bracelet for the identified categories of movement disorders, despite the advantages these technologies could bring in the dissemination of low-cost solutions usable directly within living environments and without the need for caregivers or medical personnel. Full article

Background: Evaluating the differential impact of vagus nerve stimulation (VNS) therapy across various seizure types, our study explores its efficacy specifically in patients with categorized minor and major seizures. Methods: We conducted a retrospective cohort study involving 76 patients with pharmacoresistant epilepsy treated at the University Emergency Hospital of Bucharest between 2021 and 2024. Seizures were classified as ‘minor’ (including focal-aware and non-motor/absence seizures) and ‘major’ (including focal to bilateral tonic-clonic and generalized motor seizures), based on modified International League Against Epilepsy (ILAE) criteria. This classification allowed us to assess the response to VNS therapy, defined by a 50% or greater reduction in seizure frequency at the 12-month follow-up. Results: Our findings reveal that major seizures respond more favorably to VNS therapy, significantly reducing both frequency and intensity. In contrast, minor seizures showed a less pronounced response in frequency reduction but noted improvements in neurocognitive functions, suggesting a nuanced benefit of VNS in these cases. Conclusion: The study underscores the importance of seizure type in determining the efficacy of VNS therapy, advocating for personalized treatment approaches based on seizure classification. This approach could potentially enhance clinical outcomes by tailoring VNS settings to specific seizure types, improving overall management strategies in pharmacoresistant epilepsy. Full article

The hypothalamic–pituitary–adrenal axis is known to be involved in the pathogenesis of epilepsy and psychiatric disorders. Epileptic seizures (ESs) and psychogenic non-epileptic seizures (PNESs) are frequently differentially misdiagnosed. This study aimed to evaluate changes in serum cortisol and prolactin levels after ESs and PNESs as possible differential diagnostic biomarkers. Patients over 18 years with ESs (n = 29) and PNESs with motor manifestations (n = 45), captured on video-EEG monitoring, were included. Serum cortisol and prolactin levels as well as hemograms were assessed in blood samples taken at admission, during the first hour after the seizure, and after 6, 12, and 24 h. Cortisol and prolactine response were evident in the ES group (but not the PNES group) as an acute significant increase within the first hour after seizure. The occurrence of seizures in patients with ESs and PNESs demonstrated different circadian patterns. ROC analysis confirmed the accuracy of discrimination between paroxysmal events based on cortisol response: the AUC equals 0.865, with a prediction accuracy at the cutoff point of 376.5 nmol/L 0.811 (sensitivity 86.7%, specificity 72.4%). Thus, assessments of acute serum cortisol response to a paroxysmal event may be regarded as a simple, fast, and minimally invasive laboratory test contributing to differential diagnosis of ESs and PNESs. Full article

Mutations of the SCN1A gene, which encodes the voltage-dependent Na⁺ channel’s α subunit, are associated with diverse epileptic syndromes ranging in severity, even intra-family, from febrile seizures to epileptic encephalopathy. The underlying cause of this variability is unknown, suggesting the involvement of additional factors. The aim of our study was to describe the properties of mutated channels and investigate genetic causes for clinical syndromes’ variability in the family of five SCN1A gene p.Arg1596Cys mutation carriers. The analysis of additional genetic factors influencing SCN1A-associated phenotypes was conducted through exome sequencing (WES). To assess the impact of mutations, we used patch clamp analysis of mutated channels expressed in HEK cells and in vivo neural excitability studies (NESs). In cells expressing the mutant channel, sodium currents were reduced. NESs indicated increased excitability of peripheral motor neurons in mutation carriers. WES showed the absence of non-SCA1 pathogenic variants that could be causative of disease in the family. Variants of uncertain significance in three genes, as potential modifiers of the most severe phenotype, were identified. The p.Arg1596Cys substitution inhibits channel function, affecting steady-state inactivation kinetics. Its clinical manifestations involve not only epileptic symptoms but also increased excitability of peripheral motor fibers. The role of Nav1.1 in excitatory neurons cannot be ruled out as a significant factor of the clinical phenotype. Full article

Background: Only a few studies have focused on hemiplegic migraine (HM) in children despite its early age of onset. The aim of this review is to describe the peculiar characteristics of pediatric HM. Methods: This is a narrative review based on 14 studies on pediatric HM selected from 262 papers. Results: Different from HM in adults, pediatric HM affects both genders equally. Early transient neurological symptoms (prolonged aphasia during a febrile episode, isolated seizures, transient hemiparesis, and prolonged clumsiness after minor head trauma) can precede HM long before its onset. The prevalence of non-motor auras among children is lower than it is in adults. Pediatric sporadic HM patients have longer and more severe attacks compared to familial cases, especially during the initial years after disease onset, while familial HM cases tend to have the disease for longer. During follow-up, the frequency, intensity, and duration of HM attacks often decrease. The outcome is favorable in most patients; however, neurological conditions and comorbidities can be associated. Conclusion: Further studies are needed to better define the clinical phenotype and the natural history of pediatric HM and to refine genotype–phenotype correlations in order to improve the knowledge on HM physiopathology, diagnosis, and outcome. Full article

Early bag-mask ventilation (BMV) administered to non-breathing neonates at birth in the presence of birth asphyxia (interruption of placental blood flow) has reduced neonatal mortality by up to 50% in low- and middle-income countries. The neurodevelopmental outcome of neonates receiving BMV remains unknown. Using the Malawi Developmental Assessment Tool (MDAT), infants who received BMV at birth were assessed at 6 months, evaluating gross motor, fine motor, language and social skills. A healthy cohort with no birth complications was assessed with the same tool for comparison. Mean age-adjusted MDAT z-scores were not significantly different between the groups. The number of children having developmental delay defined as a z-score ≤ −2 was significantly higher in the resuscitated cohort for the fine motor and language domain and overall MDAT z-score. The prevalence of clinical seizures post discharge was significantly higher in the resuscitated group and was associated with neurodevelopmental delay. Infants with developmental delay or seizures were more likely to have a 5 min Apgar < 7 and a longer duration of BMV. Most children receiving BMV at birth are developing normally at 6 months. Still, there are some children with impaired development among resuscitated children, representing a subgroup of children who may have suffered more severe asphyxia. Full article

During an emergency rescue operation, rescuers have to deal with many different health complications like cardiovascular, respiratory, neurological, psychiatric, etc. The identification process of the common health complications in rescue events is not very difficult or time-consuming because the health vital symptoms or primary observations are enough to identify, but it is quite difficult with some complications related to neurology e.g., schizophrenia, epilepsy with non-motor seizures, or retrograde amnesia because they cannot be identified with the trend of health vital data. The symptoms have a wide spectrum and are often non-distinguishable from other types of complications. Further, waiting for results from medical tests like MRI and ECG is time-consuming and not suitable for emergency cases where a quick treatment path is an obvious necessity after the diagnosis. In this paper, we present a novel solution for overcoming these challenges by employing artificial intelligence (AI) models in the diagnostic procedure of neurological complications in rescue situations. The novelty lies in the procedure of generating input features from raw rescue data used in AI models, as the data are not like traditional clinical data collected from hospital repositories. Rather, the data were gathered directly from more than 200,000 rescue cases and required natural language processing techniques to extract meaningful information. A step-by-step analysis of developing multiple AI models that can facilitate the fast identification of neurological complications, in general, is presented in this paper. Advanced data analytics are used to analyze the complete record of 273,183 rescue events in a duration of almost 10 years, including rescuers’ analysis of the complications and their diagnostic methods. To develop the detection model, seven different machine learning algorithms-Support Vector Machine (SVM), Random Forest (RF), K-nearest neighbor (KNN), Extreme Gradient Boosting (XGB), Logistic Regression (LR), Naive Bayes (NB) and Artificial Neural Network (ANN) were used. Observing the model’s performance, we conclude that the neural network and extreme gradient boosting show the best performance in terms of selected evaluation criteria. To utilize this result in practical scenarios, the paper also depicts the possibility of embedding such machine learning models in hardware like FPGA. The goal is to achieve fast detection results, which is a primary requirement in any rescue mission. An inference time analysis of the selected ML models and VTA AI accelerator of Apache-TVM machine learning compiler used for the FPGA is also presented in this research. Full article

Gliomas are infiltrative primary brain tumors that often invade functional cortical and subcortical regions, and they mandate individualized brain mapping strategies to avoid postoperative neurological deficits. It is well known that maximal safe resection significantly improves survival, while postoperative deficits minimize the benefits associated with aggressive resections and diminish patients’ quality of life. Although non-invasive imaging tools serve as useful adjuncts, intraoperative stimulation mapping (ISM) is the gold standard for identifying functional cortical and subcortical regions and minimizing morbidity during these challenging resections. Current mapping methods rely on the use of low-frequency and high-frequency stimulation, delivered with monopolar or bipolar probes either directly to the cortical surface or to the subcortical white matter structures. Stimulation effects can be monitored through patient responses during awake mapping procedures and/or with motor-evoked and somatosensory-evoked potentials in patients who are asleep. Depending on the patient’s preoperative status and tumor location and size, neurosurgeons may choose to employ these mapping methods during awake or asleep craniotomies, both of which have their own benefits and challenges. Regardless of which method is used, the goal of intraoperative stimulation is to identify areas of non-functional tissue that can be safely removed to facilitate an approach trajectory to the equator, or center, of the tumor. Recent technological advances have improved ISM’s utility in identifying subcortical structures and minimized the seizure risk associated with cortical stimulation. In this review, we summarize the salient technical aspects of which neurosurgeons should be aware in order to implement intraoperative stimulation mapping effectively and safely during glioma surgery. Full article

Prader–Willi syndrome (PWS) is a complex genetic disorder with three PWS molecular genetic classes and presents as severe hypotonia, failure to thrive, hypogonadism/hypogenitalism and developmental delay during infancy. Hyperphagia, obesity, learning and behavioral problems, short stature with growth and other hormone deficiencies are identified during childhood. Those with the larger 15q11-q13 Type I deletion with the absence of four non-imprinted genes (NIPA1, NIPA2, CYFIP1, TUBGCP5) from the 15q11.2 BP1-BP2 region are more severely affected compared with those with PWS having a smaller Type II deletion. NIPA1 and NIPA2 genes encode magnesium and cation transporters, supporting brain and muscle development and function, glucose and insulin metabolism and neurobehavioral outcomes. Lower magnesium levels are reported in those with Type I deletions. The CYFIP1 gene encodes a protein associated with fragile X syndrome. The TUBGCP5 gene is associated with attention-deficit hyperactivity disorder (ADHD) and compulsions, more commonly seen in PWS with the Type I deletion. When the 15q11.2 BP1-BP2 region alone is deleted, neurodevelopment, motor, learning and behavioral problems including seizures, ADHD, obsessive-compulsive disorder (OCD) and autism may occur with other clinical findings recognized as Burnside–Butler syndrome. The genes in the 15q11.2 BP1-BP2 region may contribute to more clinical involvement and comorbidities in those with PWS and Type I deletions. Full article

Coronavirus disease 2019 (COVID-19) is frequently accompanied by neurological manifestations such as headache, delirium, and epileptic seizures, whereas ageusia and anosmia may appear before respiratory symptoms. Among the various neurological COVID-19-related comorbidities, Parkinson’s disease (PD) has gained increasing attention. Some cases of PD disease have been linked to COVID-19, and both motor and non-motor symptoms in Parkinson’s disease patients frequently worsen following SARS-CoV-2 infection. Although it is still unclear whether PD increases the susceptibility to SARS-CoV-2 infection or whether COVID-19 increases the risk of or unmasks future cases of PD, emerging evidence sheds more light on the molecular mechanisms underlying the relationship between these two diseases. Among them, angiotensin-converting enzyme 2 (ACE2), a significant component of the renin-angiotensin system (RAS), seems to play a pivotal role. ACE2 is required for the entry of SARS-CoV-2 to the human host cells, and ACE2 dysregulation is implicated in the severity of COVID-19-related acute respiratory distress syndrome (ARDS). ACE2 imbalance is implicated in core shared pathophysiological mechanisms between PD and COVID-19, including aberrant inflammatory responses, oxidative stress, mitochondrial dysfunction, and immune dysregulation. ACE2 may also be implicated in alpha-synuclein-induced dopaminergic degeneration, gut–brain axis dysregulation, blood–brain axis disruption, autonomic dysfunction, depression, anxiety, and hyposmia, which are key features of PD. Full article

SPTAN1 spectrinopathies refer to a group of rare, inherited diseases associated with damage to non-erythrocytic α-II spectrin (α-II). They are linked to a range of mild to severe neuropathologies of the central and peripheral nervous systems, such as early infantile epileptic encephalopathy type 5, cerebellar ataxia, inherited peripheral neuropathy, and spastic paraplegia. Modeling human SPTAN1 encephalopathies in laboratory animals has been challenging partially because no haploinsufficiency-related phenotypes unfold in heterozygous Spna2 deficient mice nor stable transgenic lines of mice mimicking missense human SPTAN1 mutations have been created to date. Here, we assess the motor and memory performance of a dominant-negative murine Spna2 (SPTAN1) variant carrying a spontaneous point mutation replacing an arginine 1098 in the repeat 10th of α-II with the glutamine (R1098Q). By comparing groups of heterozygous R1098Q mice at different ages, we find evidence for progressive ataxia, and age-related deterioration of motor performance and muscle strength. We also document stress-induced, long-lasting seizure episodes of R1098Q mice and their poor performance in novel object recognition memory tests. Overall, we propose that the complexity of neuropathology-related phenotypes presented by the R1098Q mice recapitulates a number of symptoms observed in human patients carrying SPTAN1 mutations affecting α-II scaffold stability. This makes the R1098Q mice a valuable animal model for preclinical research. Full article

Epilepsy is a debilitating neurological condition characterized by intermittent paroxysmal states called fits or seizures. Especially, the major motor seizures of a convulsive nature, such as tonic–clonic seizures, can cause aggravating consequences. Timely alerting for these convulsive epileptic states can therefore prevent numerous complications, during, or following the fit. Based on our previous research, a non-contact method using automated video camera observation and optical flow analysis underwent field trials in clinical settings. Here, we propose a novel adaptive learning paradigm for optimization of the seizure detection algorithm in each individual application. The main objective of the study was to minimize the false detection rate while avoiding undetected seizures. The system continuously updated detection parameters retrospectively using the data from the generated alerts. The system can be used under supervision or, alternatively, through autonomous validation of the alerts. In the latter case, the system achieved self-adaptive, unsupervised learning functionality. The method showed improvement of the detector performance due to the learning algorithm. This functionality provided a personalized seizure alerting device that adapted to the specific patient and environment. The system can operate in a fully automated mode, still allowing human observer to monitor and override the decision process while the algorithm provides suggestions as an expert system. Full article