EEG power spectra parameterization and adaptive channel selection towards semi-supervised seizure prediction.

BACKGROUND: The seizure prediction algorithms have demonstrated their potential in mitigating epilepsy risks by detecting the pre-ictal state using ongoing electroencephalogram (EEG) signals. However, most of them require high-density EEG, which is burdensome to the patients for daily monitoring. Moreover, prevailing seizure models require extensive training with significant labeled data which is very time-consuming and demanding for the epileptologists. METHOD: To address these challenges, here we propose an adaptive channel selection strategy and a semi-supervised deep learning model respectively to reduce the number of EEG channels and to limit the amount of labeled data required for accurate seizure prediction. Our channel selection module is centered on features from EEG power spectra parameterization that precisely characterize the epileptic activities to identify the seizure-associated channels for each patient. The semi-supervised model integrates generative adversarial networks and bidirectional long short-term memory networks to enhance seizure prediction. RESULTS: Our approach is evaluated on the CHB-MIT and Siena epilepsy datasets. With utilizing only 4 channels, the method demonstrates outstanding performance with an AUC of 93.15% on the CHB-MIT dataset and an AUC of 88.98% on the Siena dataset. Experimental results also demonstrate that our selection approach reduces the model parameters and training time. CONCLUSIONS: Adaptive channel selection coupled with semi-supervised learning can offer the possible bases for a light weight and computationally efficient seizure prediction system, making the daily monitoring practical to improve patients' quality of life.

Study on Thin Lamination of Carbon Fiber Based on Mechanical Broadening.

Carbon fiber has excellent mechanical properties and plays an important role in modern industry. However, due to the complexity of the carbon fiber widening process, the industrial application of carbon fiber is limited. By designing the carbon fiber widening equipment of automaton, the relationship between the widening width of carbon fiber and the process parameters is studied, and the optimum developing process parameters are obtained, to improve the performance of carbon fiber composites to a certain extent. In this study, the widening process of carbon fiber was studied based on the mechanical broadening method. Firstly, an automatic broadening equipment was designed, and the effects of the initial tension, the number of straight rods, the number of convex rods, and the drawing speed on the widened width during the broadening process were discussed. The widening effect was evaluated by SEM imaging and mechanical testing. At the same time, the factors affecting the broadening width and broadening defects during the broadening process were analyzed, and the optimal broadening process parameters were obtained. The results showed that within a specific range, a higher initial tension, a greater number of convex rods, and an appropriate speed resulted in relatively smaller damage to the broadening of carbon fibers. Through the design of automatic broadening, this experiment explores optimal broadening process parameters, provides a reference for the improvement of the carbon fiber broadening process and further promotes large-scale industrial applications of carbon fiber.

Design of Twin Builder-Based Digital Twin Online Monitoring System for Crane Girders.

The crossbeam is frequently subjected to alternating loads during work as an essential load-bearing part of the crane. However, due to the large volume and the limitations of detection technology, it is impossible to realize online monitoring of the mechanical state. The ongoing advancement of ROMing and digital twin technology plays a pivotal role in facilitating the resolution of this particular issue. In this paper, we take the crane beam as the physical entity and combine the Twin Builder reduced-order technology and Deployer digital twin deployment technology to establish a digital twin of the beam. The load recognition model within the twin system exhibits a prediction error rate of ±5%. Furthermore, the accuracy of the ROM surpasses that of conventional machine learning models by a factor of 25. Upon deployment on the web platform, the results are delivered within 0.5 s, representing a substantial improvement as it is merely 1/15 of the time required for traditional 3D displays. The digital twin online monitoring system has the advantages of high accuracy and low requirements for monitoring equipment, which can be widely used in engineering practice to solve the problem that the mechanical state of large parts cannot be accurately monitored online.

The mediating role of HbA1c in the association between elevated low-density lipoprotein cholesterol levels and diabetic peripheral neuropathy in patients with type 2 diabetes mellitus.

BACKGROUND: Increased levels of low-density lipoprotein cholesterol (LDL-C) have been identified as one potential risk factor for diabetic peripheral neuropathy (DPN) in patients. The current study seeks to clarify the link between LDL-C, hyperglycemia, and DPN in patients with type 2 diabetes mellitus (T2DM). METHODS: Here, a total of 120 T2DM individuals were recruited. These volunteers with T2DM were divided into 2 groups, based on the presence or absence of peripheral neuropathy. Additionally, their baseline characteristics were compared. Association among LDL-C and glycosylated hemoglobin (HbA1c) levels and DPN, particularly with respect to specific nerve conduction velocity were analyzed. To identify factors influencing DPN, regression was performed. Furthermore, mediation analysis was employed to evaluate the indirect, direct and total effects of LDL-C on specific nerve conduction velocity, with HbA1c serving as a mediator. RESULTS: Compared to 55 patients without DPN, 65 patients with DPN demonstrated elevated levels of LDL-C and HbA1c. Both LDL-C and HbA1c have been found to be associated with reduced the motor fiber conduction velocities of Ulnar (or the Common peroneal) nerve in diabetic patients. HbA1c is one of the known risk factors for DPN in individuals with T2DM. Further mediation analysis revealed that the effect of LDL-C on the Ulnar (or the Common peroneal) nerve motor fiber conduction velocities are fully mediated by HbA1c in patients with T2DM. CONCLUSIONS: The impact of elevated LDL-C levels upon the Ulnar (or the Common peroneal) nerve motor fiber conduction velocities in patients with T2DM was found to be entirely mediated by increased HbA1c levels.

PDE4DIP contributes to colorectal cancer growth and chemoresistance through modulation of the NF1/RAS signaling axis.

Phosphodiesterase 4D interacting protein (PDE4DIP) is a centrosome/Golgi protein associated with cyclic nucleotide phosphodiesterases. PDE4DIP is commonly mutated in human cancers, and its alteration in mice leads to a predisposition to intestinal cancer. However, the biological function of PDE4DIP in human cancer remains obscure. Here, we report for the first time the oncogenic role of PDE4DIP in colorectal cancer (CRC) growth and adaptive MEK inhibitor (MEKi) resistance. We show that the expression of PDE4DIP is upregulated in CRC tissues and associated with the clinical characteristics and poor prognosis of CRC patients. Knockdown of PDE4DIP impairs the growth of KRAS-mutant CRC cells by inhibiting the core RAS signaling pathway. PDE4DIP plays an essential role in the full activation of oncogenic RAS/ERK signaling by suppressing the expression of the RAS GTPase-activating protein (RasGAP) neurofibromin (NF1). Mechanistically, PDE4DIP promotes the recruitment of PLCγ/PKCε to the Golgi apparatus, leading to constitutive activation of PKCε, which triggers the degradation of NF1. Upregulation of PDE4DIP results in adaptive MEKi resistance in KRAS-mutant CRC by reactivating the RAS/ERK pathway. Our work reveals a novel functional link between PDE4DIP and NF1/RAS signal transduction and suggests that targeting PDE4DIP is a promising therapeutic strategy for KRAS-mutant CRC.

CCF-GNN: A Unified Model Aggregating Appearance, Microenvironment, and Topology for Pathology Image Classification.

Pathology images contain rich information of cell appearance, microenvironment, and topology features for cancer analysis and diagnosis. Among such features, topology becomes increasingly important in analysis for cancer immunotherapy. By analyzing geometric and hierarchically structured cell distribution topology, oncologists can identify densely-packed and cancer-relevant cell communities (CCs) for making decisions. Compared to commonly-used pixel-level Convolution Neural Network (CNN) features and cell-instance-level Graph Neural Network (GNN) features, CC topology features are at a higher level of granularity and geometry. However, topological features have not been well exploited by recent deep learning (DL) methods for pathology image classification due to lack of effective topological descriptors for cell distribution and gathering patterns. In this paper, inspired by clinical practice, we analyze and classify pathology images by comprehensively learning cell appearance, microenvironment, and topology in a fine-to-coarse manner. To describe and exploit topology, we design Cell Community Forest (CCF), a novel graph that represents the hierarchical formulation process of big-sparse CCs from small-dense CCs. Using CCF as a new geometric topological descriptor of tumor cells in pathology images, we propose CCF-GNN, a GNN model that successively aggregates heterogeneous features (e.g., appearance, microenvironment) from cell-instance-level, cell-community-level, into image-level for pathology image classification. Extensive cross-validation experiments show that our method significantly outperforms alternative methods on H&E-stained and immunofluorescence images for disease grading tasks with multiple cancer types. Our proposed CCF-GNN establishes a new topological data analysis (TDA) based method, which facilitates integrating multi-level heterogeneous features of point clouds (e.g., for cells) into a unified DL framework.

Two new alkaloids from a strain of endophytic fungus Aspergillus sp.

19-Hydroxybrevianamide M (1) and 6 R-methoxybrevianamide V (2), two new alkaloids, were isolated from an extract of the endophytic fungus Aspergillus sp. JNU18HC0517J, together with six known analogues (3- 8). Their structures were elucidated by extensive spectroscopic analyses, NMR calculations, and ECD calculations. 6 R-methoxybrevianamide V (2) was the first L-proline indole DKP alkaloid with substitution at C-6 on the proline ring. Furthermore, the cytotoxities and antimicrobial activities of these isolated compounds were also evaluated. Compound 8 exhibited moderate antibacterial activity against Staphylococcus aureus 209 P with a minimal inhibitory concentration (MIC) value of 16 µg/ml.[Figure: see text].

Influence of the Temperature-Dependent Characteristics of CFRP Mechanical Properties on the Critical Axial Force of Drilling Delamination.

Previous studies have often assumed that the mechanical properties of Carbon Fibre Reinforced Plastics (CFRP) remain unchanged during drilling. In fact, due to the increase in drilling temperature, the mechanical properties of the composites change greatly, and this then affects the critical force. In addition, previous studies have often assumed that the failure mode of CFRP drilling was a type I crack failure. In fact, due to the complexity of the CFRP drilling process, the failure modes are often coupled with different failure modes, so type I cracks alone cannot reflect the actual cracking situation. Therefore, a three-dimensional drilling Finite Element Modeling (FEM) was established to analyze the failure modes of CFRP drilling delamination, and the I/III mode was determined; then, a new drilling critical force mechanics model, which considers the temperature dependence of CFRP mechanical properties and the failure modes of CFRP drilling delamination, was established based on the classical drilling critical force mechanics model; the results of the mechanics model were validated by drilling critical force experiments under different temperatures. The effects of the temperature dependence of CFRP mechanical properties on the drilling critical force were investigated and analyzed.

TANGO: A GO-Term Embedding Based Method for Protein Semantic Similarity Prediction.

We aim to quantitatively predict protein semantic similarities (PSS), which is vital to making biological discoveries. Previously, researchers commonly exploited Gene Ontology (GO) graphs (containing standardized hierarchically-organized GO terms for annotating distinct protein attributes) to learn GO term embeddings (vector representations) for quantifying protein attribute similarities and aggregate these embeddings to form protein embeddings for similarity measurement. However, two key properties of GO terms and annotated proteins are not yet well-explored by these learning-based methods: (1) taxonomy relations between GO terms; (2) GO terms' different contributions in describing protein semantics. In this paper, we propose TANGO, a new framework composed of a TAxoNomy-aware embedding module and an aggreGatiOn module. Our Embedding Module encodes taxonomic information into GO term embeddings by incorporating GO term topological distances in the GO graph hierarchy. Hence, distances between GO term embeddings can be used to more accurately measure shared meanings between correlated protein attributes. Our Aggregation Module automatically determines the contributions of GO terms when merging into the target protein embeddings, by mining GO term concept dependency relations in the GO graph and correlations in protein annotations. We conduct extensive experiments on several public datasets. On two PSS metrics, our new method significantly outperforms known methods by a large margin.

A comparative study of vestibular improvement and gastrointestinal effect of betahistine and gastrodin in mice.

Betahistine and gastrodin are the first-line medications for vestibular disorders in clinical practice, nevertheless, their amelioration effects on vestibular dysfunctions still lack direct comparison and their unexpected extra-vestibular effects remain elusive. Recent clinical studies have indicated that both of them may have effects on the gastrointestinal (GI) tract. Therefore, we purposed to systematically compare both vestibular and GI effects induced by betahistine and gastrodin and tried to elucidate the mechanisms underlying their GI effects. Our results showed that betahistine and gastrodin indeed had similar therapeutic effects on vestibular-associated motor dysfunction induced by unilateral labyrinthectomy. However, betahistine reduced total GI motility with gastric hypomotility and colonic hypermotility, whereas gastrodin did not influence total GI motility with only slight colonic hypermotility. In addition, betahistine, at normal dosages, induced a slight injury of gastric mucosa. These GI effects may be due to the different effects of betahistine and gastrodin on substance P and vasoactive intestinal peptide secretion in stomach and/or colon, and agonistic/anatgonistic effects of betahistine on histamine H1 and H3 receptors expressed in GI mucosal cells and H3 receptors distributed on nerves within the myenteric and submucosal plexuses. Furthermore, treatment of betahistine and gastrodin had potential effects on gut microbiota composition, which could lead to changes in host-microbiota homeostasis in turn. These results demonstrate that gastrodin has a consistent improvement effect on vestibular functions compared with betahistine but less effect on GI functions and gut microbiota, suggesting that gastrodin may be more suitable for vestibular disease patients with GI dysfunction.

Targeting the LSD1-G9a-ER Stress Pathway as a Novel Therapeutic Strategy for Esophageal Squamous Cell Carcinoma.

Despite recent advances in the management and treatment of esophageal squamous cell carcinoma (ESCC), the prognosis remains extremely poor, and current nonsurgical treatment options are limited. To identify new therapeutic targets, we screened a curated library of epigenetic compounds using a panel of cancer cell lines and found that coinhibiting the histone demethylase LSD1 and the histone methyltransferase G9a potently suppresses cell growth; similar results were obtained by knocking down both LSD1 and G9a expression. Importantly, we also found that inhibiting LSD1 and G9a significantly decreased tumor growth in a xenograft mouse model with ESCC cell lines. To examine the clinical relevance of these findings, we performed immunohistochemical analyses of microarray profiling data obtained from human esophageal squamous cancer tissues and found that both LSD1 and G9a are upregulated in cancer tissues compared to healthy tissues, and this increased expression was significantly correlated with poor prognosis. Mechanistically, we discovered that inhibiting LSD1 and G9a induces cell death via S-phase arrest and apoptosis, and cotargeting ER stress pathways increased this effect both in vitro and in vivo. Taken together, these findings provide compelling evidence that targeting LSD1, G9a, and ER stress-related pathways may serve as a viable therapeutic strategy for ESCC.

Investigating the Effect of Low-Temperature Drilling Process on the Mechanical Behavior of CFRP.

Previous research has found that lower temperature drilling is helpful to improve the hole quality of carbon fiber reinforced polymer (CFRP). However, the influence of the lower temperature drilling process on the mechanical behavior of composites is yet not fully understood. To examine the influence of the lower temperature drilling process on the mechanical behavior of CFRP, the open hole CFRP specimens used for mechanical tests were obtained with three cases: drilling with -25 °C/uncoated carbide drills/(1000 rpm, 0.02 mm/r), 23 °C/coated carbide drills/(4000 rpm, 0.03 mm/r), and 23 °C/uncoated carbide drills/(1000 rpm, 0.02 mm/r), respectively; corresponding, three groups of open-hole specimens are obtained: specimens drilling at low-temperature with low damage, specimens drilling at room-temperature with low damage and specimens drilling at room-temperature with low damage; the mechanical behavior of the three groups specimens were obtained by static tensile, tensile-tensile fatigue cyclic tests and residual tensile strength test. The results have shown that the mechanical properties of specimens with a low-temperature drilling process is lower than those of the specimen with a normal drilling process due to the better drilling quality. The damage accumulation in specimens was increased with the damage degree of the original hole, the greater the damage degree, the worse the mechanical properties.

Resting-State fMRI Functional Connectivity Strength Predicts Local Activity Change in the Dorsal Cingulate Cortex: A Multi-Target Focused rTMS Study.

Previous resting state functional magnetic resonance imaging (RS-fMRI) studies suggested that repetitive transcranial magnetic stimulation (rTMS) can modulate local activity in distant areas via functional connectivity (FC). A brain region has more than one connection with the superficial cortical areas. The current study proposed a multi-target focused rTMS protocol for indirectly stimulating a deep region, and to investigate 1) whether FC strength between stimulation targets (right middle frontal gyrus [rMFG] and right inferior parietal lobule [rIPL]) and effective region (dorsal anterior cingulate cortex [dACC]) can predict local activity changes of dACC and 2) whether multiple stimulation targets can focus on the dACC via FC. A total of 24 healthy participants received rTMS with two stimulation targets, both showing strong FC with the dACC. There were four rTMS conditions (>1 week apart, 10 Hz, 1800 pulses for each): rMFG-target, rIPL-target, Double-targets (900 pulses for each target), and Sham. The results failed to validate the multi-target focused rTMS hypothesis. But rMFG-target significantly decreased the local activity in the dACC. In addition, stronger dACC-rMFG FC was associated with a greater local activity change in the dACC. Future studies should use stronger FC to focus stimulation effects on the deep region.

Plasma cytokine changes and its clinical significance in intracranial infection secondary to traumatic brain injury.

OBJECTIVE: This study aimed to investigate the plasma cytokine changes and its clinical significance in intracranial infection secondary to traumatic brain injury. METHODS: A total of 60 cases with intracranial infection secondary to traumatic brain injury admitted to our hospital from January 2017 to December 2019 were selected as the research objects, of whom, 24 cases with mild infection, 20 with moderate infection, and 16 with severe infection. Another 60 cases without intracranial infection secondary to traumatic brain injury during the same period were selected as the uninfected group. A comparison of infected and uninfected groups on changes of plasma cytokines (IL-1ß, IL-2, IL-6, IL-8, TNF-α, IFN-γ) and high mobility group-1 protein (HMGB1) were conducted to analyze the correlation between plasma cytokines and disease severity. RESULTS: The data of IL-1ß, IL-2, IL-6, IL-8, TNF-α, IFN-γ and HMGB1 levels in both groups on day 1, day 3 and day 5 after the surgery were obtained. The results indicated that for infected group, the differences were significant among these 3 days (P<0.05), and the data on day 5 were all higher than that on day 1 and day 3 (P<0.05). While for uninfected group, there was no significant difference among those 3 days (P>0.05). The differences in different severity of infection on day 5 showed statistically significance (P<0.05), and it was positively correlated with the severity (P<0.05). CONCLUSION: The cytokines content in intracranial infection secondary to traumatic brain injury increased significantly, which was closely related to the severity of the infection. These factors can be used as monitoring indicators for diagnosis of intracranial infection and assessment ofthe severity.

Influence of Assembly Gap Size on the Structure and Properties of SUS301L Stainless Steel Laser Welded Lap Joint.

The microstructure and properties of laser welding lap joints with different assembly gap sizes are experimentally investigated. The laser weld joint is composed of γ-austenite and δ-ferrite, and the strip ferrite phase is mainly distributed at the austenite grain boundary. The weld metal presents the austenitic-ferritic (AF) solidification mode. When there is a gap between the two plates, a triangular region composed of similar equiaxed crystals can be found, and the size of the cellular crystals in this region decreases significantly. When the assembly gap size increases from 0.1 mm to 0.4 mm, the weld penetration state of the joint changes from full penetration to semi-penetration, and the surface collapse increases. The excessive size of the gap leads to a decrease in the tensile-shear force and fatigue strength of laser welded joints. In order to ensure that the surface morphology and properties of the welded joint meet the quality standard and requirement, the assembly gap should be less than 0.1mm.

Emerging Role of Microglia-Mediated Neuroinflammation in Epilepsy after Subarachnoid Hemorrhage.

Epilepsy is a common and serious complication of subarachnoid hemorrhage (SAH), giving rise to increased morbidity and mortality. It's difficult to identify patients at high risk of epilepsy and the application of anti-epileptic drugs (AEDs) following SAH is a controversial topic. Therefore, it's pressingly needed to gain a better understanding of the risk factors, underlying mechanisms and the optimization of therapeutic strategies for epilepsy after SAH. Neuroinflammation, characterized by microglial activation and the release of inflammatory cytokines, has drawn growing attention due to its influence on patients with epilepsy after SAH. In this review, we discuss the risk factors for epilepsy after SAH and emphasize the critical role of microglia. Then we discuss how various molecules arising from pathophysiological changes after SAH activate specific receptors such as TLR4, NLRP3, RAGE, P2X7R and initiate the downstream inflammatory pathways. Additionally, we focus on the significant responses implicated in epilepsy including neuronal excitotoxicity, the disruption of blood-brain barrier (BBB) and the change of immune responses. As the application of AEDs for seizure prophylaxis after SAH remains controversial, the regulation of neuroinflammation targeting the key pathological molecules could be a promising therapeutic method. While neuroinflammation appears to contribute to epilepsy after SAH, more comprehensive experiments on their relationships are needed.

Nucleus accumbens shell: A potential target for drug-resistant epilepsy with neuropsychiatric disorders.

The nucleus accumbens (NAc) is an important component of the ventral striatum, involving motivational and emotional processes, limbic-motor interfaces. Recently, experimental and clinical data have shown that NAc, particularly NAc shell (NAcs), participates in ictogenesis and epileptogensis in drug-resistant epilepsy (DRE). Therefore, we summarize the existing literature on NAcs and potential role in epilepsy, from the bench to the clinic. Connection abnormalities between NAcs and remainings, degeneration of NAc neurons, and an aberrant distribution of neuroactive substances have been reported in patients with DRE. These changes may be underlying the pathophysiological mechanism of the involvement of NAcs in DRE. Furthermore, alterations in NAcs may also be involved in neuropsychiatric disorders in patients with DRE. These observational studies demonstrate the multiple properties of NAcs and the complex relationship between the limbic system and DRE with neuropsychiatric disorders. NAcs can be a potential target for DBS and stereotactic lesioning to manage DRE with neuropsychiatric disorders. Future studies are warranted to further clarify the role of NAcs in epilepsy.