The nucleus of solitary tract (NTS) synchronizes sleep-wake-state-dependent cortical activity through the parabrachial nucleus (PB) in rat.

BACKGROUND: The medullary nucleus of solitary tract (NTS) and its afferents of vagus nerve have long been investigated in regulation of cortical activity and sleep promotion. However, the underlying neural circuit by which the NTS regulates electroencephalogram (EEG) and sleep remain unclear. As the NTS has a strong projection to the pontine arousal site, the parabrachial nucleus (PB), we proposed the NTS via the pontine parabrachial nucleus (PB) regulates cortical activity and sleep. METHODS: We bilaterally and directly stimulated the NTS neurons by chemogenetic approach and NTS terminals in the PB by optogenetic approach and examined changes in EEG and sleep in rats. RESULTS: Opto- and chemo-stimulation of the NTS and NTS-PB pathway altered neither sleep amounts nor patterns; however, both stimulations consistently increased EEG delta (0.5-4.0 Hz) EEG power during non-rapid-eye-movement (NREM) sleep and alpha-beta (10-30 Hz) EEG power during wake and REM sleep. CONCLUSION: Our results indicate that the NTS via its projections to the PB synchronizes low frequency EEG during NREM sleep and high frequency EEG during wake and REM sleep. This pathway may serve the neural foundation for the vagus nerve stimulation (VNS) treating cortical disorders.

ESSN: An Efficient Sleep Sequence Network for Automatic Sleep Staging.

By modeling the temporal dependencies of sleep sequence, advanced automatic sleep staging algorithms have achieved satisfactory performance, approaching the level of medical technicians and laying the foundation for clinical assistance. However, existing algorithms cannot adapt well to computing scenarios with limited computing power, such as portable sleep detection and consumer-level sleep disorder screening. In addition, existing algorithms still have the problem of N1 confusion. To address these issues, we propose an efficient sleep sequence network (ESSN) with an ingenious structure to achieve efficient automatic sleep staging at a low computational cost. A novel N1 structure loss is introduced based on the prior knowledge of N1 transition probability to alleviate the N1 stage confusion problem. On the SHHS dataset containing 5,793 subjects, the overall accuracy, macro F1, and Cohen's kappa of ESSN are 88.0%, 81.2%, and 0.831, respectively. When the input length is 200, the parameters and floating-point operations of ESSN are 0.27M and 0.35G, respectively. With a lead in accuracy, ESSN inference is twice as fast as L-SeqSleepNet on the same device. Therefore, our proposed model exhibits solid competitive advantages comparing to other state-of-the-art automatic sleep staging methods.

Association between Body Mass Index and Medication-Overuse Headache among Individuals with Migraine: A Cross-Sectional Study.

INTRODUCTION: Medication-overuse headache (MOH) is a secondary chronic headache disorder that occurs in individuals with a pre-existing primary headache disorder, particularly migraine disorder. Obesity is often combined with chronic daily headaches and is considered a risk factor for the transformation of episodic headaches into chronic headaches. However, the association between obesity and MOH among individuals with migraine has rarely been studied. The present study explored the association between body mass index (BMI) and MOH in people living with migraine. METHODS: This cross-sectional study is a secondary analysis of data from the Survey of Fibromyalgia Comorbidity with Headache study. Migraine and MOH were diagnosed using the criteria of the International Classification of Headache Disorders, 3rd Edition. BMI (kg/m2) is calculated by dividing the weight (kg) by the square of the height (m). Multivariable logistic regression analysis was used to evaluate the association between BMI and MOH. RESULTS: A total of 2,251 individuals with migraine were included, of whom 8.7% (195/2,251) had a concomitant MOH. Multivariable logistic regression analysis, adjusted for age, sex, education level, headache duration, pain intensity, headache family history, chronic migraine, depression, anxiety, insomnia, and fibromyalgia, demonstrated there was an association between BMI (odds ratio [OR], 1.05; 95% confidence interval [CI], 1.01-1.11; p = 0.031) and MOH. The results remained when the BMI was transformed into a category. Compared to individuals with Q2 (18.5 kg/m2 ≤ BMI ≤23.9 kg/m2), those with Q4 (BMI ≥28 kg/m2) had an adjusted OR for MOH of 1.81 (95% CI, 1.04-3.17; p = 0.037). In the subgroup analyses, BMI was associated with MOH among aged more than 50 years (OR, 1.13; 95%, 1.03-1.24), less than high school (OR, 1.08; 95%, 1.01-1.15), without depression (OR, 1.06; 95%, 1.01-1.12), and without anxiety (OR, 1.06; 95%, 1.01-1.12). An association between BMI and MOH was found in a sensitivity analysis that BMI was classified into four categories according to the World Health Organization guidelines. CONCLUSION: In this cross-sectional study, BMI was associated with MOH in Chinese individuals with migraine.

ECGAN-Assisted ResT-Net Based on Fuzziness for OSA Detection.

OBJECTIVE: Growing attention has been paid recently to electrocardiogram (ECG) based obstructive sleep apnea (OSA) detection, with some progresses been made on this topic. However, the lack of data, low data quality, and incomplete data labeling hinder the application of deep learning to OSA detection, which in turn affects the overall generalization capacity of the network. METHODS: To address these issues, we propose the ResT-ECGAN framework. It uses a one-dimensional generative adversarial network (ECGAN) for sample generation, and integrates it into ResT-Net for OSA detection. ECGAN filters the generated ECG signals by incorporating the concept of fuzziness, effectively increasing the amount of high-quality data. ResT-Net not only alleviates the problems caused by deepening the network but also utilizes multi-head attention mechanisms to parallelize sequence processing and extract more valuable OSA detection features by leveraging contextual information. RESULTS: Through extensive experiments, we verify that ECGAN can effectively improve the OSA detection performance of ResT-Net. Using only ResT-Net for detection, the accuracy on the Apnea-ECG and private databases is 0.885 and 0.837, respectively. By adding ECGAN-generated data augmentation, the accuracy is increased to 0.893 and 0.848, respectively. CONCLUSION AND SIGNIFICANCE: Comparing with the state-of-the-art deep learning methods, our method outperforms them in terms of accuracy. This study provides a new approach and solution to improve OSA detection in situations with limited labeled samples.

A Semi-Supervised Multi-Scale Arbitrary Dilated Convolution Neural Network for Pediatric Sleep Staging.

Sleep staging is essential for assessing sleep quality and diagnosing sleep disorders. However, sleep staging is a labor-intensive process, making it arduous to obtain large quantities of high-quality labeled data for automatic sleep staging. Meanwhile, most of the research on automatic sleep staging pays little attention to pediatric sleep staging. To address these challenges, we propose a semi-supervised multi-scale arbitrary dilated convolution neural network (SMADNet) for pediatric sleep staging using the scalogram with a high height-to-width ratio generated by the continuous wavelet transform (CWT) as input. To extract more extended time dimensional feature representations and adapt to scalograms with a high height-to-width ratio in SMADNet, we introduce a multi-scale arbitrary dilation convolution block (MADBlock) based on our proposed arbitrary dilated convolution (ADConv). Finally, we also utilize semi-supervised learning as the training scheme for our network in order to alleviate the reliance on labeled data. Our proposed model has achieved performance comparable to state-of-the-art supervised learning methods with 30% labels. Our model is tested on a private pediatric dataset and achieved 79% accuracy, 72% kappa, and 75% MF1. Therefore, our model demonstrates a powerful feature extraction capability and has achieved performance comparable to state-of-the-art supervised learning methods with a small number of labels.

Pontine parabrachial nucleus-basal forebrain circuitry regulating cortical and hippocampal arousal.

INTRODUCTION: The basal forebrain (BF) and the medial septum (MS) respectively drive neuronal activity of cerebral cortex and hippocampus (HPC) in sleep-wake cycle. Our previous studies of lesions and neuronal circuit tracing have shown that the pontine parabrachial nucleus (PB) projections to the BF and MS may be a key circuit for cortical and HPC arousal. AIMS: This study aims to demonstrate that PB projections to the BF and MS activate the cerebral cortex and HPC. RESULTS: By using chemogenetic stimulation of the BF, the PB-BF and the PB-MS pathway combined with electroencephalogram (EEG) Fast Fourier Transformation (FFT) analysis in rats, we demonstrated that chemogenetic stimulation of the BF or PB neurons projecting to the BF activated the cerebral cortex while chemogenetic stimulation of the MS or PB neurons projecting to the MS activated HPC activity, in sleep and wake state. These stimulations did not significantly alter sleep-wake amounts. CONCLUSIONS: Our results support that PB projections to the BF and MS specifically regulating cortical and HPC activity.

GAC-SleepNet: A dual-structured sleep staging method based on graph structure and Euclidean structure.

Sleep staging is a precondition for the diagnosis and treatment of sleep disorders. However, how to fully exploit the relationship between spatial features of the brain and sleep stages is an important task. Many current classical algorithms only extract the characteristic information of the brain in the Euclidean space without considering other spatial structures. In this study, a sleep staging network named GAC-SleepNet is designed. GAC-SleepNet uses the characteristic information in the dual structure of the graph structure and the Euclidean structure for the classification of sleep stages. In the graph structure, this study uses a graph convolutional neural network to learn the deep features of each sleep stage and converts the features in the topological structure into feature vectors by a multilayer perceptron. In the Euclidean structure, this study uses convolutional neural networks to learn the temporal features of sleep information and combine attention mechanism to portray the connection between different sleep periods and EEG signals, while enhancing the description of global features to avoid local optima. In this study, the performance of the proposed network is evaluated on two public datasets. The experimental results show that the dual spatial structure captures more adequate and comprehensive information about sleep features and shows advancement in terms of different evaluation metrics.

Exploring the cortical habituation in migraine patients based on contingent negative variation.

Introduction: Cognitive dysfunction has frequently been found in patients with migraine. The so-called contingent negative variation (CNV) and EEG power spectral densities may be the best choices to explore the underlining pathophysiology, such as cortical inhibition and habituation. Methods: Thirty migraine patients without aura and healthy controls matched for sex, age, and education were recruited separately for CNV recording. The amplitudes, latencies, and squares of different CNV components, such as oCNV, iCNV, tCNV, and PINV, were selected and analyzed. Behavioral data, such as manual reaction time (RT), were analyzed. We used the Person correlation coefficient R to analyze different ERP components in relation to clinical characteristics. A multiple regression analysis was conducted for the migraine group. Spectral analysis of EEG data from all channels using the fast Fourier transform (FFT). Results: The migraine group had longer A-latency, C-latency, and iCNV-latency than the control group. The migraine group had higher iCNV-amplitude, oCNV-amplitude, and tCNV-amplitude than the control group, especially those located in the occipital area. The iCNV-square, oCNV-square, tCNV-square, or PINV-square in the migraine group was significantly larger than the control group. Different correlations were found between clinical characteristics and ERP components. The delta or theta activity in the migraine group was statistically lower than in the control group. Discussion: Our study has revealed that migraine attacks may influence responsivity, pre-activation, habituation, and cortical inhibition not only on the behavioral level but also on the electrophysiological level. Abnormal changes in cortical habituation and inhibition can be interpreted as CNV components. Additionally, analyses have revealed correlations between CNV components and various factors, including age, the clinical course of the condition, attack frequency, pain intensity, and duration. Thus, repetitive migraine attacks can lead to a reduction in cortical inhibition and subsequent impairment in executive function.

Status of diagnosis and preventative treatment for primary headache disorders: real-world data of unmet needs in China.

BACKGROUND: Headache disorders are widely prevalent and pose a considerable economic burden on individuals and society. Globally, misdiagnosis and inadequate treatment of primary headache disorders remain significant challenges, impeding the effective management of such conditions. Despite advancements in headache management over the last decade, a need for comprehensive evaluations of the status of primary headache disorders in China regarding diagnosis and preventative treatments persists. METHODS: In the present study, we analyzed the established queries in the Survey of Fibromyalgia Comorbidity with Headache (SEARCH), focusing on previous diagnoses and preventative treatment regimens for primary headache disorders. This cross-sectional study encompassed adults diagnosed with primary headache disorders who sought treatment at 23 hospitals across China between September 2020 to May 2021. RESULTS: The study comprised 2,868 participants who were systematically examined. Migraine and tension-type headaches (TTH) constituted a majority of the primary headache disorders, accounting for 74.1% (2,124/2,868) and 23.3% (668/2,868) of the participants, respectively. Medication overuse headache (MOH) affected 8.1% (231/2,868) of individuals with primary headache disorders. Over half of the individuals with primary headache disorders (56.6%, 1,624/2,868) remained undiagnosed. The previously correct diagnosis rates for migraine, TTH, TACs, and MOH were 27.3% (580/2,124), 8.1% (54/668), 23.2% (13/56), and 3.5% (8/231), respectively. The misdiagnosis of "Nervous headache" was found to be the most prevalent among individuals with migraine (9.9%, 211/2,124), TTH (10.0%, 67/668), trigeminal autonomic cephalalgias (TACs) (17.9%, 10/56), and other primary headache disorders (10.0%, 2/20) respectively. Only a minor proportion of individuals with migraine (16.5%, 77/468) and TTH (4.7%, 2/43) had received preventive medication before participating in the study. CONCLUSIONS: While there has been progress made in the rate of correct diagnosis of primary headache disorders in China compared to a decade ago, the prevalence of misdiagnosis and inadequate treatment of primary headaches remains a veritable issue. As such, focused efforts are essential to augment the diagnosis and preventive treatment measures related to primary headache disorders in the future.

The prevalence and clinical features of fibromyalgia in Chinese hospital patients with primary headache: The survey of fibromyalgia comorbid with headache.

OBJECTIVE: The aims were to explore the prevalence and clinical features of fibromyalgia in Chinese hospital patients with primary headache. BACKGROUND: Studies done in non-Chinese populations suggest that around one-third of patients with primary headache have fibromyalgia, but data from mainland China are limited. Investigations into the prevalence and clinical features of fibromyalgia in Chinese patients with primary headache would improve our understanding of these two complex disease areas and help guide future clinical practice. METHODS: This cross-sectional study included adults with primary headache treated at 23 Chinese hospitals from September 2020 to May 2021. Fibromyalgia was diagnosed using the modified 2010 American College of Rheumatology criteria. Mood and insomnia were evaluated employing the Hospital Anxiety and Depression Scale and the Insomnia Severity Index. RESULTS: A total of 2782 participants were analyzed. The fibromyalgia prevalence was 6.0% (166/2782; 95% confidence interval: 5.1%, 6.8%). Compared to primary headache patients without combined fibromyalgia, patients with primary headache combined with fibromyalgia were more likely to be older (47.8 vs. 41.7 years), women (83.7% [139/166] vs. 72.8% [1904/2616]), less educated (65.1% [108/166] vs. 45.2% [1183/2616]), and with longer-duration headache (10.0 vs. 8.0 years). Such patients were more likely to exhibit comorbid depression (34.3% [57/166] vs. 9.9% [260/2616]), anxiety (16.3% [27/166] vs. 2.7% [70/2612]), and insomnia (58.4% [97/166] vs. 17.1% [447/2616]). Fibromyalgia was more prevalent in those with chronic (rather than episodic) migraine (11.1% [46/414] vs. 4.4% [72/1653], p < 0.001) and chronic (rather than episodic) tension-type headache (11.5% [27/235] vs. 4.6% [19/409], p = 0.001). Most fibromyalgia pain was in the shoulders, neck, and upper back. CONCLUSIONS: The prevalence of fibromyalgia in mainland Chinese patients with primary headache was 6.0%. Fibromyalgia was more common in those with chronic rather than episodic headache. The most common sites of fibromyalgia pain were the neck, shoulders, and back.

Insomnia attenuates response inhibition: Evidence from Go/NoGo research.

OBJECTIVE: Varied cognitive dysfunctions including memory, attention, inputs, processing and filtration have been found in insomnia. Meanwhile, evidence from functional neuroimaging have revealed that the abnormal metabolism in prefrontal cortex was associated with probable deficit of executive function. And in our study, we have detected the response inhibition in insomnia patients by Go/NoGo,an Event-related potentials (ERPs) study, in order to explore the impaired executive function, because response inhibition is a hallmark of executive function. METHODS: We used polysomnography (PSG) to record such objective PSG parameters. Go/NoGo was performed in sequence, different ERP components have been analyzed such as latency or amplitude between insomnia group and control group. And we used Person correlation coefficient R to make analysis between different ERP components and gender, duration, education, BMI and sleep characteristics. RESULTS: On the behavioral level, we found a little poor performance insomnia participants. On the electrophysiological level, under Go condition, insomnia participants have prolonged latency and smaller amplitude of N2 or P3. While, under NoGo condition, insomnia participants also have longer latency, but higher amplitude of N2 or P3. another major finding was that different correlation was found between gender,anxiety-depression,duration, education,BMI,sleep characteristics and N2 or P3. DISCUSSION: Our study has revealed that sleep loss may influence the response inhibition ability in insomnia, not only on behavior level, but also on the electrophysiological level. Abnormal changes in inhibition process or inhibition supervision can be represented as N2/P3 components under Go/No-go condition. Additionally, correlation analysis has been found between gender, anxiety-depression, BMI, education, and sleep structure. Thus, sleep loss attenuates response inhibition and impairs executive function in insomnia participants.

Levetiracetam alleviates cognitive decline in Alzheimer's disease animal model by ameliorating the dysfunction of the neuronal network.

Background: Patients with Alzheimer's disease (AD) have a significantly higher risk of seizures than other individuals in an age-matched population, suggesting a close association between epilepsy and AD. We aimed to examine the effects of levetiracetam (LEV)-a drug for treating seizures-on learning and memory and the neuropathological features of AD. Methods: We crossbred APP23 mice with microtubule-associated protein tau (MAPT) transgenic mice to generate APP23/MAPT mice. These mice were treated with different concentrations of LEV in the presence of kainic acid (KA) for 3 months. Results: Low doses of LEV alleviated the effects of KA on memory defects in APP23/MAPT mice. Mechanistic investigations showed that low concentrations of LEV decreased tau phosphorylation by reducing the activities of cyclin-dependent kinase 5 and glycogen synthase kinase 3α/ß, thus rescuing neurons from synaptic dystrophy and apoptosis. Low doses of LEV inhibited the effects of KA (i.e., inducing neuroinflammation and impairing the autophagy of amyloid ß-peptide), thus improving cognitive decline. High concentrations of LEV decreased the production and deposition of amyloid ß-peptide (Aß) by reducing the expression of ß-site APP-cleaving enzyme 1 and presenilin 1. However, high concentrations of LEV also induced neuronal apoptosis, decreased movement ability in mice, and did not alleviate cognitive decline in AD mice. Conclusion: Our results support the hypothesis that aberrant network activity contributes to the synaptic and cognitive deficits in APP23/MAPT mice. A low concentration of LEV may help ameliorate abnormalities of AD; however, a high LEV concentration did not induce similar results.

Exploration of cortical inhibition and habituation in insomnia: Based on CNV and EEG.

OBJECTIVE: Cognitive dysfunction with abnormal cortical inhibition and habituation has frequently been found in patients with insomnia. And the so-called contingent negative variation (CNV) and EEG power spectral density (FFT) may be the best choice to explore the underlining pathophysiology. METHODS: We used polysomnography (PSG) to record such objective PSG parameters. The amplitudes, latencies, areas of different CNV components such as oCNV, iCNV and tCNV, PINV have been selected and analyzed. Behavioral data such as manual reaction time (RT) has been analyzed. Spectral analysis was performed with fast Fourier transformation (FFT) on all channels to make a spectral analyses of EEG datas. RESULTS: The A-latency located in CZ or PZ were statistically longer in insomnia group than control group, the iCNV-latency located in insomnia group were statistically shorter than control group. The iCNV-amplitude located in insomnia group was lower than control group. The oCNV-amplitude or the tCNV-amplitude located in insomnia group was higher than control group. The oCNV-square, tCNV-square, or PINV-square located in insomnia group were significant larger than control group. ß1 or ß2 activity distributed in bilateral hemisphere were significantly increased in insomnia group than control group with different distributions. DISCUSSION: Our study revealed varied attentional and information processing in insomnia patients. Above all, we made a hypothesis with ceiling theory: Frontal lobe play an important role in maintaining cognitive processing, which needs much more energy consumption and leads to decreased fast EEG activity in frontal cortex, which contributes to reduced cortical inhibition, represented as abnormal CNV.

An Overview of EEG-based Machine Learning Methods in Seizure Prediction and Opportunities for Neurologists in this Field.

The unpredictability of epileptic seizures is one of the most problematic aspects of the field of epilepsy. Methods or devices capable of detecting seizures minutes before they occur may help prevent injury or even death and significantly improve the quality of life. Machine learning (ML) is an emerging technology that can markedly enhance algorithm performance by interpreting data. ML has gained increasing attention from medical researchers in recent years. Its epilepsy applications range from the localization of the epileptic region, predicting the medical or surgical outcome of epilepsy, and automated electroencephalography (EEG) analysis to seizure prediction. While ML has good prospects with regard to detecting epileptic seizures via EEG signals, many clinicians are still unfamiliar with this field. This work briefly summarizes the history and recent significant progress made in this field and clarifies the essential components of the automatic seizure detection system using ML methodologies for clinicians. This review also proposes how neurologists can actively contribute to ensure improvements in seizure prediction using EEG-based ML.

The Application of ASSRs, P50, and MMN in the Exploration of Cognitive Dysfunction Involving Inputs and Processing in Insomnia Patients.

Objective cognitive dysfunction has been commonly found in patients with insomnia, such as attention, memory, speed of information processing, and executive functions. Auditory steady-state responses (ASSRs), P50, mismatch negativity (MMN) can meet varied need and estimate such different cognitive dysfunction. Thus, we can examine whether insomnia is associated with different cognitive dysfunction by such multiple event-related potential (ERP) tasks. Methods we used polysomnography (PSG) to record such objective PSG parameters. ASSR, P50, and MMN were performed in sequence, different ERP components have been analyzed such as latency or amplitude between insomnia group and control group. And we chosed person correlation to make correlation analysis between different ERP components and gender, education, and sleep characteristics. Results there is a significant gender difference of ASSR latency found in insomnia group, and the similar result has been found in suppression ratio of amplitudes (S2:S1) for P50. Additionally, a significant correlation between sleep characteristics and ASSR, P50 has been found. Furthermore, there was a significant difference of MMN latency between insomnia and control group, and between sleep characteristics and varied MMN parameters as latency and amplitude. Discussion our results suggested robust electrophysiological abnormalities as ASSR, P50, and MMN in insomnia patients. Such abnormalities included gender difference, education difference, difference in depressive tendency, and difference in sleep parameters. That results revealed varied cognitive dysfunction involving inputs and processing in insomnia patients. And at the same time, we have also explored the neuropsychological mechanisms underlying the cognitive dysfunction with such different ERP tasks.

Compromised Dynamic Cerebral Autoregulation in Patients With Central Disorders of Hypersomnolence.

Objective: We aimed to investigate the dynamic cerebral autoregulation (dCA) in patients with central disorders of hypersomnolence during wakefulness. Methods: Thirty-six patients with central disorders of hypersomnolence were divided into three groups according to polysomnography and multiple sleep latency test results: the idiopathic hypersomnia group (IH), narcolepsy type 1 without rapid-eye-movement sleep behavior disorder group (NT1-RBD), and narcolepsy type 1 with rapid-eye-movement sleep behavior disorder group (NT1 + RBD), with 12 patients in each group. Twelve sex- and age-matched healthy controls were recruited. We assessed the Epworth sleepiness scale (ESS) and dCA of all subjects. dCA was assessed by analyzing the phase difference (PD) using transfer function analysis. The ESS and dCA were analyzed before and after standardized treatment in 24 patients with narcolepsy type 1. Results: The overall PD of the IH, NT1-RBD, and NT1 + RBD groups were lower than that of the control group (P < 0.001). There were no significant differences between the overall PD of the NT1-RBD and NT1 + RBD group (P > 0.05). The ESS scores decreased and the overall PD increased after treatment in 24 patients with narcolepsy type 1 (P < 0.001). Multivariable analysis showed that mean sleep latency in multiple sleep latency test was independently associated with impaired overall PD (P < 0.05). Conclusions: The dCA is impaired in patients with central disorders of hypersomnolence. The impairment of dCA occurs irrespective of NT1-RBD/+RBD. The ESS score and dCA improved in patients with narcolepsy type 1 after medication treatment. The mean sleep latency in multiple sleep latency test was independently associated with impaired dCA. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02752139.

Clinical manifestations and polysomnography-based analysis in nine cases of probable sporadic Creutzfeldt-Jakob disease.

PURPOSE: To summarize the clinical characteristics of patients with sporadic Creutzfeldt-Jakob disease (sCJD), analyze its sleep disorder characteristics using polysomnography (PSG), and compare sleep disturbances with those of fatal familial insomnia (FFI). PATIENTS AND METHODS: We retrospectively reviewed the sleep disturbances; cerebrospinal fluid (CSF) protein 14-3-3 (CSF-14-3-3 protein); prion protein gene, PRNP; magnetic resonance imaging; and electroencephalogram (EEG) of nine sCJD patients RESULTS: Of the nine sCJD patients, six were positive for CSF-14-3-3 protein. In the eight patients who completed diffusion-weighted imaging, seven showed cortical "ribbons sign" and two showed high signal in the basal ganglia. All nine patients had an EEG, which showed an increase in background slow waves; moreover, four showed typical periodic sharp wave complexes. The codon diversity at position 129, 219 of nine patients were MM, EE. Almost all nine patients had sleep disturbances such as insomnia, hypersomnia, and periodic limb movement disorder (PLMD). Five patients completed PSG, which demonstrated severe sleep structure disorder, prolonged total waking time, significantly reduced sleep efficiency, and absent rapid eye movement in some severe patients. CONCLUSION: Sleep disturbances are common in sCJD patients, manifested as insomnia, lethargy, and PLMD. The sCJD patients often demonstrate severe sleep structure disorder through PSG, which is similar to patients with FFI.

Mitochondrial gene COX2 methylation and downregulation is a biomarker of aging in heart mesenchymal stem cells.

The mitochondria have been proven to be involved in processes of aging; however, the mechansims through which mitoepigenetics affect the cytological behaviors of cardiomyocytes during the aging process are not yet fully understood. In the present study, two senescence models were constructed, replicative senescence (RS) and stress­induced premature senescence (SIPS), using human heart mesenchymal stem cells (HMSCs). First, the differences in age­related gene expression levels and telomere length were compared between the HMSCs in the RS and SIPS models by PCR. Subsequently, protein expression and the mitochondrial DNA (mtDNA) methylation status of cytochrome c oxidase subunit II (COX2) was measured by western blot analysis and bisulfite genomic sequencing (BSP). Finally, the value of the DNA methyltransferase (Dnmt) inhibitor, 5­aza­2'­deoxycytidine (AdC), in delaying the senescence of HMSCs was evaluated. It was found that the p16, p27 and p53 mRNA expression levels increased in the senescent cells, whereas p21 mRNA expression did not. It was also found that telomere shortening only occurred in the RS model, but not in the SIPS model. Along with the senescence of HMSCs, COX2 gene methylation increased and its protein expression level significantly decreased. It was demonstrated that AdC inhibited COX2 methylation and downregulated COX2 expression. The addition of exogenous COX2 or the administration of AdC promoted cell proliferation and delayed cell aging. On the whole, the present study demonstrates that COX2 methylation and downregulation are biomarkers of HMSC senescence. Thus, COX2 may have potential for use as a therapeutic target of cardiovascular diseases and this warrants further investigation.

Triphasic waves in electroencephalogram as a possible early marker of carcinomatous meningitis: a case report.

RATIONALE: Carcinomatous meningitis is a rare neurological complication. This condition is difficult to diagnose, and misdiagnosis is common because the clinical manifestations are variable. Cerebrospinal fluid (CSF) cytology is the gold standard for diagnosis. Repeated lumbar puncture is required because of the low positive rate. Our case showed triphasic waves (TWs) in an electroencephalogram (EEG) before cancer cells were detected in cytology. We report this case to demonstrate that TWs in EEG may be a prognostic marker in patients with carcinomatous meningitis. PATIENT CONCERNS: A 76-year-old Chinese male displayed incremental headache, nausea, emesis, and intermittent fever for 2 months. A routine scalp EEG showed mild slow background activity. The CSF analysis demonstrated a slight increase in protein, and the white blood cell count was in the normal range. Cytology did not show any atypical cells. Viral meningitis was considered for the first time. DIAGNOSIS: After admission, a long-term EEG was performed because of his fever and mild abnormalities in the routine EEG. The second EEG showed asymmetric TWs in the frontal brain regions. Lung adenocarcinoma was found after systemic investigation. Finally, the patient was diagnosed with carcinomatous meningitis based on repeated CSF cytology. INTERVENTIONS: The patient received systemic chemotherapy in the Department of Oncology. OUTCOMES: The patient was followed up monthly, and he was lost to follow-up in the sixth month after carcinomatous meningitis was diagnosed. LESSONS: It is difficult to make a diagnosis in the early stage of carcinomatous meningitis because the clinical manifestations lack specificity. Repeated lumbar puncture is time consuming and is painful for the patients. In our case, TWs in EEG were detected before cancer cells were found in cytology. EEG should be performed when carcinomatous meningitis is under consideration.

An elongated tract of polyQ in the carboxyl­terminus of human α1A calcium channel induces cell apoptosis by nuclear translocation.

An aberrant elongated tract of glutamine residues (polyQ) in proteins induces multiple diseases treated in the clinic. In our previous study of progressive myoclonic epilepsy (PME), using whole­exome sequencing, a mutant Cav2.1 protein with an aberrant elongated polyQ tract was identified in PME patients. To investigate the molecular mechanism and cell biology of this aberrant elongated polyQ tract, wild­type Cav2.1 with 13 polyQ repeats (Cav2.1 wt­Q13) and mutant­type Cav2.1 with 26 polyQ repeats (Cav2.1 mt­Q26) were prepared and introduced into human SH­SY5Y neuroblastoma cells. Using a WST­1 assay, it was revealed that Cav2.1 mt­Q26 markedly suppressed the proliferation of the SH­SY5Y cells, a result not observed for the Cav2.1 wt­Q13­transfected cells. It was also revealed that Cav2.1 mt and its truncated molecules suppressed cell proliferation by inducing apoptosis rather than arresting the cell cycle. Further investigations indicated a nuclear translocation phenomenon associated with the Cav2.1 mt molecules. Mechanistically, it was revealed that the Cav2.1 mt molecules activated the Bcl­2/Bax, caspase­3 and poly ADP­ribose polymerase (PARP) apoptotic pathways. The present study may provide new insights for interpreting the pathogenesis of PME and the relationship among polyQ, CACNA1A gene mutations and PME.