scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless, challenges arise from prevalent sequencing dropout events and noise effects, impacting subsequent analyses. Here, we introduce a novel algorithm, Single-cell Gene Importance Ranking (scGIR), which utilizes a single-cell gene correlation network to evaluate gene importance. The algorithm transforms single-cell sequencing data into a robust gene correlation network through statistical independence, with correlation edges weighted by gene expression levels. We then constructed a random walk model on the resulting weighted gene correlation network to rank the importance of genes. Our analysis of gene importance using PageRank algorithm across nine authentic scRNA-seq datasets indicates that scGIR can effectively surmount technical noise, enabling the identification of cell types and inference of developmental trajectories. We demonstrated that the edges of gene correlation, weighted by expression, play a critical role in enhancing the algorithm's performance. Our findings emphasize that scGIR outperforms in enhancing the clustering of cell subtypes, reverse identifying differentially expressed marker genes, and uncovering genes with potential differential importance. Overall, we proposed a promising method capable of extracting more information from single-cell RNA sequencing datasets, potentially shedding new lights on cellular processes and disease mechanisms.

Nonlinear analysis and recognition of epileptic EEG signals in different stages.

It is a hot problem in epilepsy research to detect and predict seizures by EEG signals. Clinically, it is generally observed that there are only sudden abnormal signals during the ictal stage, but there is no significant difference in the EEG signal between the interictal and preictal stages. To solve the problem that preictal signals are difficult to recognize clinically, and then effectively improve the recognition efficiency of epileptic seizures, so, in this paper, some nonlinear methods are comprehensively used to extract the hidden information in the EEG signals in different stages, namely, phase space reconstruction (PSR), Poincaré section (PS), synchroextracting transform (SET), and machine learning for EEG signal analysis. First, PSR based on C-C method is used, and the results show that there are different diffuse attractor trajectories of the signals in different stages. Second, the confidence ellipse (CE) is constructed by using the scatter diagram of the corresponding trajectory on PS, and the aspect ratio and area of the ellipse are calculated. The results show that there is an interesting transitional phenomenon in preictal stage. To recognize ictal and preictal signals, time-frequency (TF) spectrums, which are processed by SET, are fed into the convolutional neural network (CNN) classifier. The accuracy of recognizing ictal and preictal signals reaches 99.7% and 93.7%, respectively. To summarize, our results based on nonlinear method provide new research ideas for seizure detection and prediction.NEW & NOTEWORTHY Our results based on nonlinear method have better practical significance and clinical application value and improved the prediction efficiency of epileptic EEG signals effectively. This work provides direct insight into the application of these biomarkers for seizure detection and prediction.

Dexmedetomidine Inhibits Paraventricular Corticotropin-releasing Hormone Neurons that Attenuate Acute Stress-induced Anxiety-like Behavior in Mice.

BACKGROUND: Dexmedetomidine has repeatedly shown to improve anxiety, but the precise neural mechanisms underlying this effect remain incompletely understood. This study aims to explore the role of corticotropin-releasing hormone-producing hypothalamic paraventricular nucleus (CRHPVN) neurons in mediating the anxiolytic effects of dexmedetomidine. METHODS: A social defeat stress mouse model was used to evaluate the anxiolytic effects induced by dexmedetomidine through the elevated plus maze, open-field test, and measurement of serum stress hormone levels. In vivo Ca2+ signal fiber photometry and ex vivo patch-clamp recordings were used to determine the excitability of CRHPVN neurons and investigate the specific mechanism involved. CRHPVN neuron modulation was achieved through chemogenetic activation or inhibition. RESULTS: Compared with saline, dexmedetomidine (40 µg/kg) alleviated anxiety-like behaviors. Additionally, dexmedetomidine reduced CRHPVN neuronal excitability. Chemogenetic activation of CRHPVN neurons decreased the time spent in the open arms of the elevated plus maze and in the central area of the open-field test. Conversely, chemogenetic inhibition of CRHPVN neurons had the opposite effect. Moreover, the suppressive impact of dexmedetomidine on CRHPVN neurons was attenuated by the α2-receptor antagonist yohimbine. CONCLUSIONS: The results indicate that the anxiety-like effects of dexmedetomidine are mediated via α2-adrenergic receptor-triggered inhibition of CRHPVN neuronal excitability in the hypothalamus.

Autophagy impairment is involved in midazolam-induced lipid droplet accumulation and consequent phagocytosis decrease in BV2 cells.

An increasing number of experimental and clinical observation suggest that the use of anaesthetics is closely associated with postoperative central nervous system (CNS) complications, such as delirium and cognitive dysfunction. Brain energy rescue is an emerging therapeutic strategy for central nervous system disease (CNSDs). However, the effect of anaesthetics on nerve cell energy utilisation, especially microglia, and its potential effects on cell function still unclear. Elucidating the effects of anaesthetics on lipid droplets, which are specific lipid storage organs, and phagocytosis of microglia is crucial to discover a new therapeutic concept for postoperative CNS complications. Here, we studied the effects of the commonly used anaesthetic midazolam on lipid droplets and phagocytosis in immortalised microglial BV2 cells. Lipid droplets were assessed by flow cytometry and triglyceride quantification. The phagocytosis of BV2 cells was evaluated by detecting their phagocytosis by latex beads. Additionally, the autophagy of BV2 cells was evaluated by western blot and observation under microscopy. Our results showed that midazolam caused lipid droplet accumulation and reduced phagocytosis in BV2 cells, and inhibition of lipid droplet accumulation partially restored phagocytosis. Furthermore, midazolam blocks autophagic degradation by increasing phosphorylated TFEB in BV2 cells, inhibition of midazolam-increased phosphorylated TFEB might contribute to the improvement of autophagic flux by rapamycin. Moreover, promoting autophagy reverse the lipid droplet accumulation and phagocytosis decrease. This study suggests autophagy is a target for attenuating lipid droplet accumulation, normal degradation of lipid droplets is important for maintaining microglia phagocytosis and attenuating the side effects of midazolam on the CNS.

Long-lasting postoperative analgesia with local anesthetic-loaded hydrogels prevent tumor recurrence via enhancing CD8+T cell infiltration.

Postoperative pain (POP) can promote tumor recurrence and reduce the cancer patient's quality of life. However, POP management has always been separated from tumor treatment in clinical practice, and traditional postoperative analgesia using opioids is still unsatisfactory for patients, which is not conducive to tumor treatment. Here, ropivacaine, a popular amide-type LA, was introduced into a Pluronic F127 hydrogel. Postoperative analgesia with ropivacaine-loaded hydrogels reduced the incidence of high-dose ropivacaine-induced convulsions and prolonged pain relief for more than 16 h. More interestingly, ropivacaine-loaded hydrogel was found to upregulate major histocompatibility complex class I (MHC-I) in tumor cells by impairing autophagy. Therefore, a hydrogel co-dopped with ropivacaine and TLR7 agonist imiquimod (PFRM) was rationally synthesized. After postoperative analgesia with PFRM, imiquimod primes tumor-specific CD8+T cells through promoting DCs maturation, and ropivacaine facilitates tumor cells recognition by primed CD8+T cells through upregulating MHC-I. Consequently, postoperative analgesia with PFRM maximumly increases CD8+T cells infiltration into residual tumor tissue and prevents tumor recurrence. Overall, this study for the first time provides an LA-based approach for simultaneous long-lasting postoperative analgesia and prevention of tumor recurrence.

Ropivacaine-loaded hydrogels for prolonged relief of chemotherapy-induced peripheral neuropathic pain and potentiated chemotherapy.

Chemotherapy can cause severe pain for patients, but there are currently no satisfactory methods of pain relief. Enhancing the efficacy of chemotherapy to reduce the side effects of high-dose chemotherapeutic drugs remains a major challenge. Moreover, the treatment of chemotherapy-induced peripheral neuropathic pain (CIPNP) is separate from chemotherapy in the clinical setting, causing inconvenience to cancer patients. In view of the many obstacles mentioned above, we developed a strategy to incorporate local anesthetic (LA) into a cisplatin-loaded PF127 hydrogel for painless potentiated chemotherapy. We found that multiple administrations of cisplatin-loaded PF127 hydrogels (PFC) evoked severe CIPNP, which correlated with increased pERK-positive neurons in the dorsal root ganglion (DRG). However, incorporating ropivacaine into the PFC relieved PFC-induced CIPNP for more than ten hours and decreased the number of pERK-positive neurons in the DRG. Moreover, incorporating ropivacaine into the PFC for chemotherapy is found to upregulate major histocompatibility complex class I (MHC-I) expression in tumor cells and promote the infiltration of cytotoxic T lymphocytes (CD8+ T cells) in tumors, thereby potentiating chemotherapy efficacy. This study proposes that LA can be used as an immunemodulator to enhance the effectiveness of chemotherapy, providing new ideas for painless cancer treatment.

Highly specific neutrophil-mediated delivery of albumin nanoparticles to ectopic lesion for endometriosis therapy.

Endometriosis is an estrogen-dependent chronic inflammatory disease. Hormonal and surgical treatments are the most commonly used clinical therapies, but they have many sides effects or are traumatic to the body. Therefore, specific drugs for endometriosis treatment are urgently needed to develop. In this study, we identified two features of endometriosis, namely the continuous recruitment of neutrophils into the ectopic lesions and the higher uptake of glucose by ectopic cells. For the above features, we designed a glucose oxidase-loaded bovine serum albumin nanoparticle (BSA-GOx-NPs) that is inexpensive and facilitates large-scale production. After injection, BSA-GOx-NPs were high specifically delivered to ectopic lesions in a neutrophil-dependent manner. Furthermore, BSA-GOx-NPs deplete glucose and induce apoptosis in the ectopic lesions. Whereupon BSA-GOx-NPs produced excellent anti-endometriosis effects when administrated in both acute and chronic inflammatory phases. These results reveal for the first time that the neutrophil hitchhiking strategy is effective in chronic inflammatory disease and provide a non-hormonal and easy-to-achieve approach for endometriosis treatment.

Enhanced fiber-coupling efficiency via high-order partially coherent flat-topped beams for free-space optical communications.

The fiber-coupling efficiency of signal beams is crucial in free space optical (FSO) communications. Herein, we derived an analytical expression for the fiber-coupling efficiency of partially coherent flat-topped beams propagating through atmospheric turbulence based on the cross-spectral density function. Our numerical calculation results showed that the fiber-coupling efficiency of partially coherent flat-topped beams in a turbulent atmosphere could be enhanced by increasing the beam order. Under the same conditions, the fiber-coupling efficiency of the high-order partially coherent flat-topped beams was larger than those connected to the Gaussian and Gaussian Schell-model (GSM) beams. Our results will improve the quality of partially coherent beams used in FSO communications.

Kupffer cell-targeting strategy for the protection of hepatic ischemia/reperfusion injury.

The aim of this study is to evaluate the effect of rare earth upconversion nanoparticles (UCNs) on hepatic ischemia reperfusion injury (IRI) and explore its possible mechanism. Hepatic IRI seriously affects the prognosis of patients undergoing liver surgery. Liver-resident Kupffer cells have been reported to promote IRI. Nanomedicines are known to be effective in the treatment of liver diseases, however, Kupffer cell-targeting nanomedicines for the treatment of IRI are yet to be developed. As potential bioimaging nanomaterials, UCNs have been found to specifically deplete Kupffer cells, but the underlying mechanism is unknown. In this study, we found that UCNs specifically depleted Kupffer cells by pyroptosis, while the co-administration of the caspase-1 inhibitor VX-765 rescued the UCN-induced Kupffer cell pyroptosis in mice. Furthermore, the pre-depletion of Kupffer cells by the UCNs significantly suppressed the release of inflammatory cytokines and effectively improved hepatic IRI. The rescue of the pyroptosis of the Kupffer cells by VX-765 abrogated the protective effect of UCNs on the liver. These results suggest that UCNs are highly promising for the development of Kupffer cell-targeting nanomedicines for intraoperative liver protection.

Enhanced autophagic flux contributes to cardioprotection of remifentanil postconditioning after hypoxia/reoxygenation injury in H9c2 cardiomyocytes.

Remifentanil postconditioning (RPC) has been shown to provide potent cardioprotection against ischemia/reperfusion (I/R) injury, but the underlying mechanism has not been fully elucidated. The current study was designed to investigate whether RPC protects cardiomyocytes against I/R injury through enhancement of autophagic flux. H9c2 cardiomyocytes were exposed to hypoxia/reoxygenation (H/R) to mimic myocardial I/R injury in vitro. Autophagosome formation was evaluated by detecting of light chain 3 (LC3) puncta number and LC3Ⅱ levels using immunofluorescence and western blotting, respectively. Additionally, dual fluorescent staining of LC3 and lysosomal-associated membrane protein 2, a lysosomal marker protein, were used to detect autolysosome formation. Moreover, autophagic flux integrity was tracked using changes in LC3Ⅱ and p62 levels. Lastly, myocardial injury was detected by Hoechst 33342 and propidium iodide staining and MTT assay. The results showed that RPC increased autophagosome formation and promoted autophagosome-lysosome fusion, thereby improving autophagic flux in H9c2 cells. Reversal of these effect by bafilomycin A1 or chloroquine co-administration at reoxygenation onset indicated that RPC improved the impaired autophagic flux following H/R injury. Induction of autophagy was associated with increased cell viability and decreased apoptosis. Autophagy inhibition with bafilomycin A1 or chloroquine and ATG7shRNA significantly abolished RPC-induced cardioprotection. In conclusion, our finding that RPC can protect cardiomyocytes against H/R injury through enhancement of autophagic flux suggests a new mechanism for myocardial protection of opioid postconditioning.

Midazolam Enhances Mutant Huntingtin Protein Accumulation via Impairment of Autophagic Degradation In Vitro.

BACKGROUND/AIMS: Autophagy is a well-known pathway to "clean" the misfolded mutant huntingtin protein (mHtt), which plays a considerable role in polyglutamine diseases. To date, there have been few studies of the choice of anesthetic during surgery in patients with polyglutamine diseases and evaluation of the effects and underlying mechanisms of anesthetics in these patients. METHODS: GFP-Htt (Q74)-PC12 cells, which stably express green fluorescent protein-tagged Htt protein containing 74 glutamine repeating units, were used throughout this study. Cells were treated with 15 µM midazolam and 100 mM trehalose (positive control), and the induction of autophagy and autophagic degradation were assessed by detecting changes in autophagy-related proteins and substrates, and cell viability was assessed using the MTT assay. Overexpression of cathepsin D by plasmid transfection was used to restore midazolam-impaired autophagic degradation. RESULTS: Midazolam increased intracellular mHtt levels in a time- and dose-dependent manner. Additionally, enhancing or blocking autophagic flux by trehalose or chloroquine could decrease or increase midazolam-induced mHtt elevation, respectively. Midazolam induced autophagy in the mTOR-dependent signaling pathway, but autophagic degradation was impaired, with a continuous rise in p62 and LC3 II levels and decrease in cathepsin D. However, overexpression of cathepsin D reversed the effects of midazolam. Midazolam led to a 20% decrease in GFP-Htt (Q74)-PC12 cell viability, which could be abrogated by overexpression of cathepsin D. CONCLUSIONS: Midazolam increased mHtt levels and decreased Htt (Q74)-PC12 cell viability via impairment of autophagic degradation, which could be restored by overexpression of cathepsin D.

Persistency of Enlarged Autolysosomes Underscores Nanoparticle-Induced Autophagy in Hepatocytes.

The diverse biological effects of nanomaterials form the basis for their applications in biomedicine but also cause safety issues. Induction of autophagy is a cellular response after nanoparticles exposure. It may be beneficial in some circumstances, yet autophagy-mediated toxicity raises an alarming concern. Previously, it has been reported that upconversion nanoparticles (UCNs) elicit liver damage, with autophagy contributing most of this toxicity. However, the detailed mechanism is unclear. This study reveals persistent presence of enlarged autolysosomes in hepatocytes after exposure to UCNs and SiO2 nanoparticles both in vitro and in vivo. This phenomenon is due to anomaly in the autophagy termination process named autophagic lysosome reformation (ALR). Phosphatidylinositol 4-phosphate (PI(4)P) relocates onto autolysosome membrane, which is a key event of ALR. PI(4)P is then converted into phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2 ) by phosphatidylinositol-4-phosphate 5-kinase. Clathrin is subsequently recruited by PI(4,5)P2 and leads to tubule budding of ALR. Yet it is observed that PI(4)P cannot be converted in nanoparticle-treated hepatocytes cells. Exogenous supplement of PI(4,5)P2 suppresses the enlarged autolysosomes in vitro. Abolishment of these enlarged autolysosomes by autophagy inhibitor relieves the hepatotoxicity of UCNs in vivo. The results provide evidence for disrupted ALR in nanoparticle-treated hepatocytes, suggesting that the termination of nanoparticle-induced autophagy is of equal importance as the initiation.

Giant Cellular Vacuoles Induced by Rare Earth Oxide Nanoparticles are Abnormally Enlarged Endo/Lysosomes and Promote mTOR-Dependent TFEB Nucleus Translocation.

Many nanomaterials are reported to disrupt lysosomal function and homeostasis, but how cells sense and then respond to nanomaterial-elicited lysosome stress is poorly understood. Nucleus translocation of transcription factor EB (TFEB) plays critical roles in lysosome biogenesis following lysosome stress induced by starvation. The authors previously reported massive cellular vacuolization, along with autophagy induction, in cells treated with rare earth oxide (REO) nanoparticles. Here, the authors identify these giant cellular vacuoles as abnormally enlarged and alkalinized endo/lysosomes whose formation is dependent on macropinocytosis. This vacuolization causes deactivation of mammalian target of rapamycin (mTOR), a TFEB-interacting kinase that resides on the lysosome membrane. Subsequently, TFEB is dephosphorylated at serine 142 and translocated into cell nucleus. This nucleus translocation of TFEB is observed only in vacuolated cells and it is critical for maintaining lysosome homeostasis after REO nanoparticle treatment, as knock-down of TFEB gene significantly compromises lysosome function and enhances cell death in nanoparticle-treated cells. Our results reveal that cellular vacuolization, which is commonly observed in cells treated with REOs and other nanomaterials, represents a condition of profound lysosome stress, and cells sense and respond to this stress by facilitating mTOR-dependent TFEB nucleus translocation in an effort to restore lysosome homeostasis.

Isoprenaline: a potential contributor in sick sinus syndrome--insights from a mathematical model of the rabbit sinoatrial node.

The mechanism of isoprenaline exerting its effects on cardiac pacemaking and driving in sick sinus syndrome is controversial and unresolved. In this paper, mathematical models for rabbit sinoatrial node cells were modified by incorporating equations for the known dose-dependent actions of isoprenaline on various ionic channel currents, the intracellular Ca²âº transient, and i(Na) changes induced by SCN5A gene mutations; the cell models were also incorporated into an intact SAN-atrium model of the rabbit heart that is based on both heterogeneities of the SAN electrophysiology and histological structure. Our results show that, in both central and peripheral cell models, isoprenaline could not only shorten the action potential duration, but also increase the amplitude of action potential. The mutation impaired the SAN pacemaking. Simulated vagal nerve activity amplified the bradycardic effects of the mutation. However, in tissue case, the pacemaker activity may show temporal, spatial, or even spatiotemporal cessation caused by the mutation. Addition of isoprenaline could significantly diminish the bradycardic effect of the mutation and the SAN could restart pacing and driving the surrounding tissue. Positive effects of isoprenaline may primarily be attributable to an increase in i(Na) and i(Ca,T) which were reduced by the mutation.

Local anesthetic delivery systems for the management of postoperative pain.

Postoperative pain (POP) is a major clinical challenge. Local anesthetics (LAs), including amide-type LAs, ester-type LAs, and other potential ion-channel blockers, are emerging as drugs for POP management because of their effectiveness and affordability. However, LAs typically exhibit short durations of action and prolonging the duration by increasing their dosage or concentration may increase the risk of motor block or systemic local anesthetic toxicity. In addition, techniques using LAs, such as intrathecal infusion, require professional operation and are prone to catheter displacement, dislodgement, infection, and nerve damage. With the development of materials science and nanotechnology, various LAs delivery systems have been developed to compensate for these disadvantages. Numerous delivery systems have been designed to continuously release a safe dose in a single administration to ensure minimal systemic toxicity and prolong pain relief. LAs delivery systems can also be designed to control the duration and intensity of analgesia according to changes in the external trigger conditions, achieve on-demand analgesia, and significantly improve pain relief and patient satisfaction. In this review, we summarize POP pathways, animal models and methods for POP testing, and highlight LAs delivery systems for POP management. STATEMENT OF SIGNIFICANCE: Postoperative pain (POP) is a major clinical challenge. Local anesthetics (LAs) are emerging as drugs for POP management because of their effectiveness and affordability. However, they exhibit short durations and toxicity. Various LAs delivery systems have been developed to compensate for these disadvantages. They have been designed to continuously release a safe dose in a single administration to ensure minimal toxicity and prolong pain relief. LAs delivery systems can also be designed to control the duration and intensity of analgesia to achieve on-demand analgesia, and significantly improve pain relief and patient satisfaction. In this paper, we summarize POP pathways, animal models, and methods for POP testing and highlight LAs delivery systems for POP management.

In vivo imaging reveals a synchronized correlation among neurotransmitter dynamics during propofol and sevoflurane anesthesia.

General anesthesia is widely applied in clinical practice. However, the precise mechanism of loss of consciousness induced by general anesthetics remains unknown. Here, we measured the dynamics of five neurotransmitters, including γ-aminobutyric acid, glutamate, norepinephrine, acetylcholine, and dopamine, in the medial prefrontal cortex and primary visual cortex of C57BL/6 mice through in vivo fiber photometry and genetically encoded neurotransmitter sensors under anesthesia to reveal the mechanism of general anesthesia from a neurotransmitter perspective. Results revealed that the concentrations of γ-aminobutyric acid, glutamate, norepinephrine, and acetylcholine increased in the cortex during propofol-induced loss of consciousness. Dopamine levels did not change following the hypnotic dose of propofol but increased significantly following surgical doses of propofol anesthesia. Notably, the concentrations of the five neurotransmitters generally decreased during sevoflurane-induced loss of consciousness. Furthermore, the neurotransmitter dynamic networks were not synchronized in the non-anesthesia groups but were highly synchronized in the anesthetic groups. These findings suggest that neurotransmitter dynamic network synchronization may cause anesthetic-induced loss of consciousness.

[A simulation study for the effect of acid concentration and temperture on sick sinus syndrome].

The effective therapeutics for the sinoatrial node (SAN) pacemaker dysfunction induced by SCN5A gene mutation this is still being explored recently. In this study, a two-dimensional experimental model of rabbit SAN-atrial cell system which proposed by Zhang et al., was used as a prototype, the gene mutation was considered, and effects of both the acid concentration and temperature were also introduced. The effects of acid concentration and temperature on sick sinus syndrome (SSS) at the tissue level were investigated by simulation. The results showed that the SAN abnormal pacemaker could be caused by the reduction of I(Na), which is induced by the two mutations of T220I and delF1617. The results also showed that if we properly adjusted the acid concentration and temperature of the system, not only could we increase the relevant currents, but also could we increase I(Na) which reduced by gene mutations, so that the pacemaking behavior of SAN tissue could return to normal state from abnormalities. The above simulation results imply that the abnormal pacemaking of SAN system may closely relate to the gene mutation of ion channel mutations, and the acid concentration and temperature may play a modulatory role. Our study could be useful for clinical medical diagnosis and therapy of cardiac disease.

Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics.

Lots of studies have been carried out on characteristic of epileptic Electroencephalograph (EEG). However, traditional EEG characteristic research methods lack exploration of spatial information. To study the characteristics of epileptic EEG signals from the perspective of the whole brain，this paper proposed combination methods of multi-channel characteristics from time-frequency and spatial domains. This paper was from two aspects: Firstly, signals were converted into 2D Hilbert Spectrum (HS) images which reflected the time-frequency characteristics by Hilbert-Huang Transform (HHT). These images were identified by Convolutional Neural Network (CNN) model whose sensitivity was 99.8%, accuracy was 98.7%, specificity was 97.4%, F1-score was 98.7%, and AUC-ROC was 99.9%. Secondly, the multi-channel signals were converted into brain networks which reflected the spatial characteristics by Symbolic Transfer Entropy (STE) among different channels EEG. And the results show that there are different network properties between ictal and interictal phase and the signals during the ictal enter the synchronization state more quickly, which was verified by Kuramoto model. To summarize, our results show that there was different characteristics among channels for the ictal and interictal phase, which can provide effective physical non-invasive indicators for the identification and prediction of epileptic seizures.

Corrigendum: Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics.

[This corrects the article DOI: 10.3389/fnins.2023.1117340.].

GL-Segnet: Global-Local representation learning net for medical image segmentation.

Medical image segmentation has long been a compelling and fundamental problem in the realm of neuroscience. This is an extremely challenging task due to the intensely interfering irrelevant background information to segment the target. State-of-the-art methods fail to consider simultaneously addressing both long-range and short-range dependencies, and commonly emphasize the semantic information characterization capability while ignoring the geometric detail information implied in the shallow feature maps resulting in the dropping of crucial features. To tackle the above problem, we propose a Global-Local representation learning net for medical image segmentation, namely GL-Segnet. In the Feature encoder, we utilize the Multi-Scale Convolution (MSC) and Multi-Scale Pooling (MSP) modules to encode the global semantic representation information at the shallow level of the network, and multi-scale feature fusion operations are applied to enrich local geometric detail information in a cross-level manner. Beyond that, we adopt a global semantic feature extraction module to perform filtering of irrelevant background information. In Attention-enhancing Decoder, we use the Attention-based feature decoding module to refine the multi-scale fused feature information, which provides effective cues for attention decoding. We exploit the structural similarity between images and the edge gradient information to propose a hybrid loss to improve the segmentation accuracy of the model. Extensive experiments on medical image segmentation from Glas, ISIC, Brain Tumors and SIIM-ACR demonstrated that our GL-Segnet is superior to existing state-of-art methods in subjective visual performance and objective evaluation.