Differentiating loss of consciousness causes through artificial intelligence-enabled decoding of functional connectivity.

Differential diagnosis of acute loss of consciousness (LOC) is crucial due to the need for different therapeutic strategies despite similar clinical presentations among etiologies such as nonconvulsive status epilepticus, metabolic encephalopathy, and benzodiazepine intoxication. While altered functional connectivity (FC) plays a pivotal role in the pathophysiology of LOC, there has been a lack of efforts to develop differential diagnosis artificial intelligence (AI) models that feature the distinctive FC change patterns specific to each LOC cause. Three approaches were applied for extracting features for the AI models: three-dimensional FC adjacency matrices, vectorized FC values, and graph theoretical measurements. Deep learning using convolutional neural networks (CNN) and various machine learning algorithms were implemented to compare classification accuracy using electroencephalography (EEG) data with different epoch sizes. The CNN model using FC adjacency matrices achieved the highest accuracy with an AUC of 0.905, with 20-s epoch data being optimal for classifying the different LOC causes. The high accuracy of the CNN model was maintained in a prospective cohort. Key distinguishing features among the LOC causes were found in the delta and theta brain wave bands. This research advances the understanding of LOC's underlying mechanisms and shows promise for enhancing diagnosis and treatment selection. Moreover, the AI models can provide accurate LOC differentiation with a relatively small amount of EEG data in 20-s epochs, which may be clinically useful.

Grapefruit-Inspired Polymeric Capsule with Hierarchical Microstructure: Advanced Nanomaterial Carrier Platform for Energy Storage, Drug Delivery, Catalysis, and Environmental Applications.

Efficient support materials are crucial for maximizing the efficacy of nanomaterials in various applications such as energy storage, drug delivery, catalysis, and environmental remediation. However, traditional supports often hinder nanomaterial performance due to their high weight ratio and limited manageability, leading to issues like tube blocking and secondary pollution. To address this, a novel grapefruit-inspired polymeric capsule (GPC) as a promising carrier platform is introduced. The millimeter-scale GPC features a hydrophilic shell and an internal hierarchical microstructure with 80% void volume, providing ample space for encapsulating diverse nanomaterials including metals, polymers, metal-organic frameworks, and silica. Through liquid-phase bottom-up methods, it is successfully loaded Fe2O3, SiO2, polyacrylic acid, and Prussian blue nanomaterials onto the GPC, achieving high mass ratio (1776, 488, 898, and 634 wt.%, respectively). The GPC shell prevents nanomaterial leakage and the influx of suspended solids, while its internal framework enhances structural stability and mass transfer rates. With long-term storage stability, high carrying capacity, and versatile applicability, the GPC significantly enhances the field applicability of nanomaterials.

Enhanced functional connectivity in the reward circuitry in healthy adults with weekend catch-up sleep.

We aimed to identify structural and functional changes in healthy adults with catch-up sleep (CUS), we applied seed-based functional connectivity (FC) analysis using resting-state functional magnetic resonance imaging (MRI). We hypothesized that deficits in reward processing could be a fundamental mechanism underlying the motivation of taking CUS. Then, 55 healthy adults voluntarily (34 with CUS and 21 without CUS) participated in this study. Voxel-based morphometry was performed to explore region of gray matter volume (GMV) difference between CUS and non-CUS groups. Between-group comparison of FC was then carried out using resting-state functional MRI analysis seeding at the region of volume difference. Moreover, the region of volume difference and the strength of FC were correlated with scores of questionnaires for reward-seeking behavior and clinical variables. CUS group had a higher reward-seeking tendency, and increased GMV in the bilateral nucleus accumbens and right superior frontal gyrus relative to non-CUS group. FC analysis seeding at the bilateral accumbens revealed increases of FC in the bilateral medial prefrontal cortex in CUS group compared to non-CUS group. The questionnaire scores reflecting the reward-seeking tendency were correlated with the FC strength between bilateral accumbens and medial prefrontal cortex. Our results indicate that CUS is associated with reward-seeking tendency and increased GMV and FC in regions responsible for reward network. Our findings suggest that enhanced reward network could be the crucial mechanism underlying taking CUS and might be implicated in the detrimental effects of circadian misalignment.

Augmented ocular vestibular-evoked myogenic potentials in postural orthostatic tachycardia syndrome.

PURPOSE: To delineate the association between otolith function and changes in mean orthostatic blood pressure (BP) and heart rate (HR) in patients with postural orthostatic tachycardia syndrome (POTS). METHODS: Forty-nine patients with POTS were prospectively recruited. We analyzed the results of ocular vestibular-evoked myogenic potentials (oVEMPs) and cervical vestibular-evoked myogenic potentials (cVEMPs), as well as head-up tilt table tests using a Finometer. The oVEMP and cVEMP responses were obtained using tapping stimuli and 110 dB tone-burst sounds, respectively. We measured maximal changes in 5-s averaged systolic BP (SBP), diastolic BP (DBP), and heart rate (HR) within 15 s and during 10 min after tilting. We compared the results with those of 20 age- and sex-matched healthy participants. RESULTS: The n1-p1 amplitude of oVEMPs was larger in patients with POTS than in healthy participants (p = 0.001), whereas the n1 latency (p = 0.280) and interaural difference (p = 0.199) did not differ between the two. The n1-p1 amplitude was a positive predictor for POTS (odds ratio 1.07, 95% confidence interval 1.01-1.13, p = 0.025). Body weight (p = 0.007) and n1-p1 amplitude of oVEMP (p = 0.019) were positive predictors for ΔSBP15s in POTS, whereas aging was a negative predictor (p = 0.005). These findings were not observed in healthy participants. CONCLUSIONS: Augmented utricular inputs may be associated with a relative predominance of sympathetic over vagal control of BP and HR, especially for an early response during orthostasis in patients with POTS. Overt sympathoexcitation due to exaggerated utricular input and lack of readaptation may be associated with the pathomechanism of POTS.

Live isolation of naïve ESCs via distinct glucose metabolism and stored glycogen.

Naïve and primed pluripotent stem cells recapitulate the peri- and post-implantation development, respectively. Thus, investigation of distinct traits between each pluripotent stem cell type would shed light on early embryonic processes. Herein, by screening a fluorescent probe library, we found that intracellular glycogen led to specific reactivity to CDg4, a glycogen fluorescence sensor, in both human and mouse naïve embryonic stem cells (ESCs). The requirement of constant inhibition of Gsk3ß as well as high oxidative phosphorylation (OxPHOS) in naïve compared to primed ESCs was closely associated to high level of intracellular glycogen in naïve ESCs. Both capacity of OxPHOS and stored glycogen, rescued naïve ESCs by transient inhibition of glycolysis, which selectively eliminated primed ESCs. Additionally, naïve ESCs with active OxPHOS were enriched from a mixture with primed ESCs by high reactivity to ATP-Red1, a mitochondrial ATP fluorescence probe. These results indicate the active OxPHOS and high intracellular glycogen as a novel "biomarker" delineating metabolic remodeling during the transition of naïve pluripotency.

Multi-Domain Convolutional Neural Networks for Lower-Limb Motor Imagery Using Dry vs. Wet Electrodes.

Motor imagery (MI) brain-computer interfaces (BCIs) have been used for a wide variety of applications due to their intuitive matching between the user's intentions and the performance of tasks. Applying dry electroencephalography (EEG) electrodes to MI BCI applications can resolve many constraints and achieve practicality. In this study, we propose a multi-domain convolutional neural networks (MD-CNN) model that learns subject-specific and electrode-dependent EEG features using a multi-domain structure to improve the classification accuracy of dry electrode MI BCIs. The proposed MD-CNN model is composed of learning layers for three domain representations (time, spatial, and phase). We first evaluated the proposed MD-CNN model using a public dataset to confirm 78.96% classification accuracy for multi-class classification (chance level accuracy: 30%). After that, 10 healthy subjects participated and performed three classes of MI tasks related to lower-limb movement (gait, sitting down, and resting) over two sessions (dry and wet electrodes). Consequently, the proposed MD-CNN model achieved the highest classification accuracy (dry: 58.44%; wet: 58.66%; chance level accuracy: 43.33%) with a three-class classifier and the lowest difference in accuracy between the two electrode types (0.22%, d = 0.0292) compared with the conventional classifiers (FBCSP, EEGNet, ShallowConvNet, and DeepConvNet) that used only a single domain. We expect that the proposed MD-CNN model could be applied for developing robust MI BCI systems with dry electrodes.

Role of MEK partner-1 in cancer stemness through MEK/ERK pathway in cancerous neural stem cells, expressing EGFRviii.

BACKGROUND: Glioma stem cells (GSCs) are a major cause of the frequent relapse observed in glioma, due to their high drug resistance and their differentiation potential. Therefore, understanding the molecular mechanisms governing the 'cancer stemness' of GSCs will be particularly important for improving the prognosis of glioma patients. METHODS: We previously established cancerous neural stem cells (CNSCs) from immortalized human neural stem cells (F3 cells), using the H-Ras oncogene. In this study, we utilized the EGFRviii mutation, which frequently occurs in brain cancers, to establish another CNSC line (F3.EGFRviii), and characterized its stemness under spheroid culture. RESULTS: The F3.EGFRviii cell line was highly tumorigenic in vitro and showed high ERK1/2 activity as well as expression of a variety of genes associated with cancer stemness, such as SOX2 and NANOG, under spheroid culture conditions. Through meta-analysis, PCR super-array, and subsequent biochemical assays, the induction of MEK partner-1 (MP1, encoded by the LAMTOR3 gene) was shown to play an important role in maintaining ERK1/2 activity during the acquisition of cancer stemness under spheroid culture conditions. High expression of this gene was also closely associated with poor prognosis in brain cancer. CONCLUSION: These data suggest that MP1 contributes to cancer stemness in EGFRviii-expressing glioma cells by driving ERK activity.

Sexual experiences among multicultural adolescents in Korea: evidence from the Korean Youth's Risk Behavior Survey.

Several studies have examined adolescent sexual behaviors by family immigration status, but most of these failed to account for heterogeneity within youths' multicultural backgrounds. To fill this gap in the literature, this paper draws data from the 2011 to 2022 rounds of the Korean Youth's Risk Behavior Survey (N = 769,160) and compares the likelihood of sexual intercourse across four groups of adolescents. Results from logistic regression indicate that the odds of having sexual contact increased 2.8 times for youths with a non-Korean father and Korean mother, compared with those from families with two Korean parents. When both father and mother are foreign-born, the odds of being sexually active increased 4.7 times. In both cases, the discrepancies might be primarily associated with the foreign fathers' lack of socioeconomic resources. Therefore, the father's role deserves more examination, and sex education in schools should be tailored to reflect multicultural adolescents' needs.

Crosstalk between Signaling Pathways and Energy Metabolism in Pluripotency.

The sequential change from totipotency to multipotency occurs during early mammalian embryo development. However, due to the lack of cellular models to recapitulate the distinct potency of stem cells at each stage, their molecular and cellular characteristics remain ambiguous. The establishment of isogenic naïve and primed pluripotent stem cells to represent the pluripotency in the inner cell mass of the pre-implantation blastocyst and in the epiblast from the post-implantation embryo allows the understanding of the distinctive characteristics of two different states of pluripotent stem cells. This review discusses the prominent disparities between naïve and primed pluripotency, including signaling pathways, metabolism, and epigenetic status, ultimately facilitating a comprehensive understanding of their significance during early mammalian embryonic development.

Developing a device for simultaneously investigating pivoting neuromuscular control and muscle properties toward a multi-axis rehabilitation.

Understanding the pivoting neuromuscular control of the lower limb and its associated muscle properties is critical for developing diagnostic and rehabilitation tools. However, to the best of our knowledge, a device that can evaluate these factors simultaneously remains lacking. To address this gap, a device that can investigate pivoting neuromuscular control and associated muscle properties was developed in this study. The proposed device consisted of a pivoting mechanism and height-adjustable chair with a brace interface. The device can control a footplate at various speeds to facilitate pivoting stretching and quantify neuromuscular control. Time-synchronized ultrasonographic images can be acquired simultaneously to quantify muscle properties during both active and passive pivoting movements. The muscle displacement, fascicle length/displacement, pennation angle, pivoting stiffness, and pivoting instability were investigated using the proposed device. Further, the feasibility of the device was demonstrated through a cross-sectional study with healthy subjects. The proposed device successfully quantified changes in muscle displacement during passive and active pivoting movements, pivoting stiffness during passive movements, and neuromuscular control during active movements. Therefore, the proposed device is expected to be used as a research and therapeutic tool for improving pivoting neuromuscular control and muscle functions and investigating the underlying mechanisms associated between muscle properties and joint movement in the transverse plane.

Multi-Task Heterogeneous Ensemble Learning-Based Cross-Subject EEG Classification Under Stroke Patients.

Robot-assisted motor training is applied for neurorehabilitation in stroke patients, using motor imagery (MI) as a representative paradigm of brain-computer interfaces to offer real-life assistance to individuals facing movement challenges. However, the effectiveness of training with MI may vary depending on the location of the stroke lesion, which should be considered. This paper introduces a multi-task electroencephalogram-based heterogeneous ensemble learning (MEEG-HEL) specifically designed for cross-subject training. In the proposed framework, common spatial patterns were used for feature extraction, and the features according to stroke lesions are shared and selected through sequential forward floating selection. The heterogeneous ensembles were used as classifiers. Nine patients with chronic ischemic stroke participated, engaging in MI and motor execution (ME) paradigms involving finger tapping. The classification criteria for the multi-task were established in two ways, taking into account the characteristics of stroke patients. In the cross-subject session, the first involved a direction recognition task for two-handed classification, achieving a performance of 0.7419 (±0.0811) in MI and 0.7061 (±0.1270) in ME. The second task focused on motor assessment for lesion location, resulting in a performance of 0.7457 (±0.1317) in MI and 0.6791 (±0.1253) in ME. Comparing the specific-subject session, except for ME on the motor assessment task, performance on both tasks was significantly higher than the cross-subject session. Furthermore, classification performance was similar to or statistically higher in cross-subject sessions compared to baseline models. The proposed MEEG-HEL holds promise in improving the practicality of neurorehabilitation in clinical settings and facilitating the detection of lesions.

Four-hour-delayed 3D-FLAIR MRIs in patients with acute unilateral peripheral vestibulopathy.

OBJECTIVE: Conventionally, MRI aids in differentiating acute unilateral peripheral vestibulopathy/vestibular neuritis (AUPV/VN) from mimickers. Meanwhile, the diagnostic utility of MRIs dedicated to the inner ear remains to be elucidated for diagnosing AUPV/VN. METHODS: We prospectively recruited 53 patients with AUPV/VN (mean age ± SD = 60 ± 15 years, 29 men). Initial MRIs were performed with a standard protocol, and an additional axial 3D-fluid-attenuated inversion recovery (3D-FLAIR) sequence was obtained 4 h after intravenous injection of gadoterate meglumine. Abnormal enhancement was defined as a signal intensity that exceeded the mean + 2SD value on the healthy side. The findings of neurotologic evaluation and MRIs were compared. RESULTS: Overall, the inter-rater agreement for gadolinium enhancement was 0.886 (Cohen's kappa coefficient). Enhancement was observed in 26 patients (49%), most frequently in the vestibule (n = 20), followed by the anterior (n = 12), horizontal (HC, n = 8), posterior canal (n = 5), and superior (n = 3) and inferior (n = 1) vestibular nerves. In multivariable logistic regression analysis, the enhancement was associated with decreased HC gain in video head-impulse tests (p = 0.036), increased interaural difference in ocular vestibular-evoked myogenic potentials (p = 0.001), and a longer onset-to-MRI time span (p = 0.024). The sensitivity and specificity were 92.3% and 81.5%, respectively, with an area under the curve of 0.90 for predicting gadolinium enhancement. INTERPRETATION: Robust gadolinium enhancement was observed on 4-hour-delayed 3D-FLAIR images in nearly half of the patients with AUPV/VN, with a good correlation with the results of neurotologic evaluation. The positivity may be determined by the extent of vestibular deficit, timing of imaging acquisition, and possibly by the underlying etiology causing AUPV/VN. MRIs may aid in delineating the involved structures in AUPV/VN.

Improving inter-session performance via relevant session-transfer for multi-session motor imagery classification.

Motor imagery (MI)-based brain-computer interfaces (BCIs) using electroencephalography (EEG) have found practical applications in external device control. However, the non-stationary nature of EEG signals remains to obstruct BCI performance across multiple sessions, even for the same user. In this study, we aim to address the impact of non-stationarity, also known as inter-session variability, on multi-session MI classification performance by introducing a novel approach, the relevant session-transfer (RST) method. Leveraging the cosine similarity as a benchmark, the RST method transfers relevant EEG data from the previous session to the current one. The effectiveness of the proposed RST method was investigated through performance comparisons with the self-calibrating method, which uses only the data from the current session, and the whole-session transfer method, which utilizes data from all prior sessions. We validated the effectiveness of these methods using two datasets: a large MI public dataset (Shu Dataset) and our own dataset of gait-related MI, which includes both healthy participants and individuals with spinal cord injuries. Our experimental results revealed that the proposed RST method leads to a 2.29 % improvement (p < 0.001) in the Shu Dataset and up to a 6.37 % improvement in our dataset when compared to the self-calibrating method. Moreover, our method surpassed the performance of the recent highest-performing method that utilized the Shu Dataset, providing further support for the efficacy of the RST method in improving multi-session MI classification performance. Consequently, our findings confirm that the proposed RST method can improve classification performance across multiple sessions in practical MI-BCIs.

Ocular vestibular-evoked myogenic potential assists in differentiation of multiple system atrophy from Parkinson's disease.

Vestibular-evoked myogenic potentials (VEMPs) can help assess otolithic neural pathway in the brainstem that may also participate in cardiovascular autonomic function. Parkinson's disease (PD) is associated with altered VEMP responses; however, the association between VEMP abnormalities and multiple system atrophy (MSA) remains unknown. Therefore, we compared the extent of otolith dysfunction using ocular (oVEMP) and cervical VEMP (cVEMP) between MSA and PD. We analyzed the clinical features and VEMP and head-up tilt table test (HUT) findings using the Finometer in 24 patients with MSA and 52 with de-novo PD, who had undergone neurotologic evaluation in a referral-based university hospital in South Korea from January 2021 to March 2023. MSA was associated with bilateral oVEMP abnormality (odds ratio [95% confidence interval] = 9.19 [1.77-47.76], p=0.008). n1-p1 amplitude was negatively correlated with Unified Multiple System Atrophy Rating Scale I-II scores in patients with MSA (r=-0.571, p=0.033), whereas it did not correlate with Movement Disorder Society-Unified Parkinson's Disease Rating Scale-III scores in patients with PD (r=-0.051, p=0.687). n1 latency was negatively correlated with maximum changes in systolic blood pressure within 15 s during HUT in patients with PD (r=-0.335, p=0.040) but not in those with MSA (r=0.277, p=0.299). In conclusion, bilaterally abnormal oVEMP responses may indicate the extent of brainstem dysfunction in MSA. oVEMP reflects the integrity of otolith-autonomic interplay, reliably assists in differentiating between MSA and PD, and helps infer clinical decline.

Transition Substitution of Desired Bases in Human Pluripotent Stem Cells with Base Editors: A Step-by-Step Guide.

The recent advances in human pluripotent stem cells (hPSCs) enable to precisely edit the desired bases in hPSCs to be used for the establishment of isogenic disease models and autologous ex vivo cell therapy. The knock-in approach based on the homologous directed repair with Cas9 endonuclease, causing DNA double-strand breaks (DSBs), produces not only insertion and deletion (indel) mutations but also deleterious large deletions. On the contrary, due to the lack of Cas9 endonuclease activity, base editors (BEs) such as adenine base editor (ABE) and cytosine base editor (CBE) allow precise base substitution by conjugated deaminase activity, free from DSB formation. Despite the limitation of BEs in transition substitution, precise base editing by BEs with no massive off-targets is suggested to be a prospective alternative in hPSCs for clinical applications. Considering the unique cellular characteristics of hPSCs, a few points should be considered. Herein, we describe an updated and optimized protocol for base editing in hPSCs. We also describe an improved methodology for CBE-based C to T substitutions, which are generally lower than A to G substitutions in hPSCs.

Classification of deep vein thrombosis stages using convolutional neural network of electromyogram with vibrotactile stimulation toward developing an early diagnostic tool: A preliminary study on a pig model.

Deep vein thrombosis (DVT) can lead to life-threatening disorders; however, it can only be recognized after its symptom appear. This study proposed a novel method that can detect the early stage of DVT using electromyography (EMG) signals with vibration stimuli using the convolutional neural networks (CNN) algorithm. The feasibility of the method was tested with eight legs before and after the surgical induction of DVT at nine-time points. Furthermore, perfusion pressure (PP), intracompartmental pressure (IP), and shear elastic modulus (SEM) of the tibialis anterior were also collected. In the proposed method, principal component analysis (PCA) and CNN were used to analyze the EMG data and classify it before and after the DVT stages. The cross-validation was performed in two strategies. One is for each leg and the other is the leave-one-leg-out (LOLO), test without any predicted information, for considering the practical diagnostic tool. The results showed that PCA-CNN can classify before and after DVT stages with an average accuracy of 100% (each leg) and 68.4±20.5% (LOLO). Moreover, all-time points (before induction of DVT and eight-time points after DVT) were classified with an average accuracy of 72.0±11.9% which is substantially higher accuracy than the chance levels (11% for 9-class classification). Based on the experimental results in the pig model, the proposed CNN-based method can classify the before- and after-DVT stages with high accuracy. The experimental results can provide a basis for further developing an early diagnostic tool for DVT using only EMG signals with vibration stimuli.

Clinical Features and Neurotologic Findings in Patients With Acute Unilateral Peripheral Vestibulopathy Associated With Antiganglioside Antibody.

BACKGROUND AND OBJECTIVES: Anecdotal studies have reported the presence of antiganglioside antibodies in acute unilateral peripheral vestibulopathy (AUPV). This study aimed to determine the prevalence, clinical characteristics, and neurotologic findings of AUPV associated with antiganglioside antibodies. METHODS: Serum antigangliosides were measured in consecutive patients with AUPV according to the Bárány Society criteria during the acute and recovery phases in a referral-based university hospital in South Korea from September 2019 to January 2023. Clinical characteristics and neurotologic findings were compared between those with and without antiganglioside antibodies. The results of video-oculography, video head impulse and bithermal caloric tests, and other neurotologic evaluations including ocular and cervical vestibular-evoked myogenic potentials and subjective visual vertical were compared between the 2. MRIs dedicated to the inner ear were also conducted when considered necessary. RESULTS: One hundred five patients (mean age ± SD = 60 ± 13 years, 57 male) were included for analyses. During the acute phase, 12 patients (12/105, 11%) were tested positive for serum antiganglioside antibodies, including anti-GQ1b immunoglobulin (Ig) G (n = 5) or IgM (n = 4), anti-GM1 IgM (n = 3), and anti-GD1a IgG (n = 1, including 1 patient with a positive anti-GQ1b antibody). Patients with antiganglioside antibodies showed lesser intensity of spontaneous nystagmus (median [interquartile range] = 1.8 [1.2-2.1] vs 3.4 [1.5-9.5], p = 0.003) and a lesser degree of canal paresis (30 [17-47] vs 58 [34-79], p = 0.028) and gain asymmetry of the vestibulo-ocular reflex for the horizontal semicircular canal during head impulse tests (0.07 [-0.04 to 0.61] vs 0.36 [0.18-0.47], p = 0.032) than those without antibodies. Negative conversion of antibodies and vestibular recovery were observed in most patients (6/8, 75%). Among 30 patients with AUPV with 4-hour delayed 3D fluid-attenuated inversion recovery dedicated to the inner ear, gadolinium enhancement was observed in 18 (18/30, 60%), either in the vestibule (n = 9), semicircular canal (n = 6), or vestibular nerve (n = 5). The positivity rates based on specific antibodies could not be determined due to limited sample sizes. DISCUSSION: The association between antiganglioside antibodies and AUPV suggests an immune-mediated mechanism in acute vestibular failure and extends the clinical spectrum of antiganglioside antibody syndrome.

Differentiating changes in movement-related EEG response induced by transcranial direct current stimulation using convolutional neural network.

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that can modulate neuronal excitability and induce brain plasticity. Although tDCS has been studied with various methods, more research is needed on the movement-related electroencephalography (EEG) changes induced by tDCS. Moreover, it is necessary to investigate whether these changes can be distinguished through a convolutional neural network (CNN)-based classifier. In this study, we measured the EEG during the voluntary foot-tapping task of participants who received tDCS or sham stimulation and evaluated the classification performance. As a result, significantly higher classification accuracy was shown using the ß band (88.7±9.4%), which is more related to motor function, than in the other bands (71.4±10.6% for δ band, 64.1±13.4% for θ band, and 65.7±10.9% for α band). Consequently, EEG changes during the voluntary foot-tapping task induced by tDCS appeared large in the ß band, implying that it is effective in classifying whether tDCS was given or not, and plays an important role in identifying the effect of tDCS.

Venous congestion affects neuromuscular changes in pigs in terms of muscle electrical activity and muscle stiffness.

Early detection of venous congestion (VC)-related diseases such as deep vein thrombosis (DVT) is important to prevent irreversible or serious pathological conditions. However, the current way of diagnosing DVT is only possible after recognizing advanced DVT symptoms such as swelling, pain, and tightness in affected extremities, which may be due to the lack of information on neuromechanical changes following VC. Thus, the goal of this study was to investigate acute neuromechanical changes in muscle electrical activity and muscle stiffness when VC was induced. The eight pigs were selected and the change of muscle stiffness from the acceleration and muscle activity in terms of integral electromyography (IEMG) was investigated in three VC stages. Consequently, we discovered a significant increase in the change in muscle stiffness and IEMG from the baseline to the VC stages (p < 0.05). Our results and approach can enable early detection of pathological conditions associated with VC, which can be a basis for further developing early diagnostic tools for detecting VC-related diseases.

Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis.

We compared neural activities and network properties between the antihistamine-induced seizures (AIS) and seizure-free groups, with the hypothesis that patients with AIS might have inherently increased neural activities and network properties that are easily synchronized. Resting-state electroencephalography (EEG) data were collected from 27 AIS patients and 30 healthy adults who had never had a seizure. Power spectral density analysis was used to compare neural activities in each localized region. Functional connectivity (FC) was measured using coherence, and graph theoretical analyses were performed to compare network properties between the groups. Machine learning algorithms were applied using measurements found to be different between the groups in the EEG analyses as input features. Compared with the seizure-free group, the AIS group showed a higher spectral power in the entire regions of the delta, theta, and beta bands, as well as in the frontal areas of the alpha band. The AIS group had a higher overall FC strength, as well as a shorter characteristic path length in the theta band and higher global efficiency, local efficiency, and clustering coefficient in the beta band than the seizure-free group. The Support Vector Machine, k-Nearest Neighbor, and Random Forest models distinguished the AIS group from the seizure-free group with a high accuracy of more than 99%. The AIS group had seizure susceptibility considering both regional neural activities and functional network properties. Our findings provide insights into the underlying pathophysiological mechanisms of AIS and may be useful for the differential diagnosis of new-onset seizures in the clinical setting.