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In this work, polypropylene (PP) and PP/poly(ethylene-co-octene) (PP/POE) blend replica surfaces with densely arranged nanowires are fabricated using a molding process. Morphology analysis shows that the nanowires on these replica surfaces have sharp tips and high aspect ratios. The droplet impact behaviors on the surfaces of the PP/POE blend replicas and PP replicas are investigated before and after freezing at -20 °C for 4 h. The height of the nanowires on the PP/POE blend replica surfaces is higher than that on the PP surface before and after freezing. The static wettability and droplet impact tests on the surfaces of PP/POE blend replicas and PP replica show that adding POE into the PP matrix can significantly increase the toughness of the nanowires on the PP/POE blend replica surfaces during the droplet impact at low temperatures. These investigations are favorable to broaden the practical applications of superhydrophobic surfaces in some severe environments.
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Many industrial processes can be described by distributed parameter systems (DPSs) governed by partial differential equations (PDEs). In this research, a spatiotemporal network is proposed for DPS modeling without any process knowledge. Since traditional linear modeling methods may not work well for nonlinear DPSs, the proposed method considers the nonlinear space-time separation, which is transformed into a Lagrange dual optimization problem under the orthogonal constraint. The optimization problem can be solved by the proposed neural network with good structural interpretability. The spatial construction method is employed to derive the continuous spatial basis functions (SBFs) based on the discrete spatial features. The nonlinear temporal model is derived by the Gaussian process regression (GPR). Benefiting from spatial construction and GPR, the proposed method enables spatially continuous modeling and provides a reliable output range under the given confidence level. Experiments on a catalytic reaction process and a battery thermal process demonstrate the effectiveness and superiority of the proposed method.
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Backgrounds: In order to detect early gastric cancer (EGC), this research sought to assess the diagnostic utility of magnifying endoscopy (ME) as well as the significance of mucin phenotype and microvessel features. Methods: 402 individuals with an EGC diagnosis underwent endoscopic submucosal dissection (ESD) at the Department of ME between 2012 and 2020. After adjusting for image distortion, high-magnification endoscopic pictures were taken and examined to find microvessels in the area of interest. The microvessel density was measured as counts per square millimeter (counts/mm2) after segmentation, and the vascular bed's size was computed as a percentage of the area of interest. To identify certain properties of the microvessels, such as end-points, crossing points, branching sites, and connection points, further processing was done using skeletonized pixels. Results: According to the research, undifferentiated tumors often lacked the MS pattern and showed an oval and tubular microsurface (MS) pattern, but differentiated EGC tumors usually lacked the MS pattern and presented a corkscrew MV pattern. Submucosal invasion was shown to be more strongly associated with the destructive MS pattern in differentiated tumors as opposed to undifferentiated tumors. While lesions with a corkscrew MV pattern and an antrum or body MS pattern revealed greater MUC5AC expression, lesions with a loop MV pattern indicated higher MUC2 expression. Furthermore, CD10 expression was higher in lesions with a papillary pattern and an antrum or body MS pattern. Conclusion: These results imply that evaluating mucin phenotype and microvessel features in conjunction with magnifying endoscopy (ME) may be a useful diagnostic strategy for early gastric cancer (EGC) detection. Nevertheless, further investigation is required to confirm these findings and identify the best course of action for EGC diagnosis.
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Epilepsy is a severe central nervous system disorder characterized by an imbalance between neuronal excitation and inhibition, resulting in heightened neuronal excitability, particularly within the hippocampus. About one-third of individuals with epilepsy experience difficult-to-manage seizures, known as refractory epilepsy. Epilepsy is closely linked to inflammatory immune response, with elevated levels of inflammatory mediators observed in individuals with this condition. This inflammation of the brain can lead to seizures of various types and is further exacerbated by the release of inflammatory factors, which heighten the excitability of peripheral neurons and worsen the progression of epilepsy. Pyroptosis is an inflammatory programmed cell death which has been shown to be involved in the pathological process of epilepsy. Inflammatory factors released during pyroptosis increase neuronal excitability and promote abnormal discharge in epilepsy, increasing susceptibility to epilepsy. This article provides an overview of the current knowledge on cell pyroptosis and its potential mechanisms, including both canonical and noncanonical pathways. Additionally, we discuss the potential mechanisms of pyroptosis occurrence in epilepsy and the potential therapeutic drugs targeting pyroptosis as a treatment strategy. In summary, this review highlights the promising potential of pyroptosis as a target for developing innovative therapies for epilepsy.
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Epilepsia , Piroptosis , Humanos , Epilepsia/metabolismo , Epilepsia/inmunología , Animales , Neuronas/metabolismo , Neuronas/patologíaRESUMEN
BACKGROUND: Epilepsy is a chronic disabling disease poorly controlled by available antiseizure medications. Oridonin, a bioactive alkaloid with anti-inflammatory properties and neuroprotective effects, can inhibit the increased excitability of neurons caused by glutamate accumulation at the cellular level. However, whether oridonin affects neuronal excitability and whether it has antiepileptic potential has not been reported in animal models or clinical studies. METHOD: Pentylenetetrazol was injected into mice to create a model of chronic epilepsy. Seizure severity was assessed using the Racine scale, and the duration and latency of seizures were observed. Abnormal neuronal discharge was detected using electroencephalography, and neuronal excitability was assessed using calcium imaging. Damage to hippocampal neurons was evaluated using Hematoxylin-Eosin and Nissl staining. The expression of the NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome and other pyroptosis-related proteins was determined using western blotting and immunofluorescence. A neuronal pyroptosis model was established using the supernatant of BV2 cells treated with lipopolysaccharide and adenosine triphosphate to stimulate hippocampal neurons. RESULTS: Oridonin (1 and 5 mg/kg) reduced neuronal damage, increased the latency of seizures, and shortened the duration of fully kindled seizures in chronic epilepsy model mice. Oridonin decreased abnormal discharge during epileptic episodes and suppressed increased neuronal excitability. In vitro experiments showed that oridonin alleviated pyroptosis in hippocampal HT22 neurons. CONCLUSION: Oridonin exerts neuroprotective effects by inhibiting pyroptosis through the NLRP3/caspase-1 pathway in chronic epilepsy model mice. It also reduces pyroptosis in hippocampal neurons in vitro, suggesting its potential as a therapy for epilepsy.
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Anticonvulsivantes , Modelos Animales de Enfermedad , Diterpenos de Tipo Kaurano , Epilepsia , Hipocampo , Proteína con Dominio Pirina 3 de la Familia NLR , Neuronas , Fármacos Neuroprotectores , Piroptosis , Animales , Diterpenos de Tipo Kaurano/farmacología , Diterpenos de Tipo Kaurano/uso terapéutico , Proteína con Dominio Pirina 3 de la Familia NLR/metabolismo , Fármacos Neuroprotectores/farmacología , Fármacos Neuroprotectores/uso terapéutico , Epilepsia/tratamiento farmacológico , Piroptosis/efectos de los fármacos , Ratones , Anticonvulsivantes/farmacología , Anticonvulsivantes/uso terapéutico , Masculino , Hipocampo/efectos de los fármacos , Hipocampo/metabolismo , Hipocampo/patología , Neuronas/efectos de los fármacos , Neuronas/patología , Neuronas/metabolismo , Pentilenotetrazol , Ratones Endogámicos C57BL , Inflamasomas/metabolismo , Inflamasomas/efectos de los fármacos , Línea Celular , Convulsiones/tratamiento farmacológicoRESUMEN
BACKGROUND: Interleukin-1 receptor-associated kinase 4 (IRAK4) plays an important role in immune modulation in various central nervous system disorders. However, IRAK4 has not been reported in epilepsy models in animal and clinical studies, nor has its involvement in regulating pyroptosis in epilepsy. METHOD: First, we performed transcriptome sequencing, quantitative real-time polymerase chain reaction, and western blot analysis on the hippocampal tissues of refractory epilepsy patients to measure the mRNA and protein levels of IRAK4 and pyroptosis-related proteins. Second, we successfully established a pentylenetetrazol (PTZ)-induced seizure mouse model. We conducted behavioral tests, electroencephalography, virus injection, and molecular biology experiments to investigate the role of IRAK4 in seizure activity regulation. RESULTS: IRAK4 is upregulated in the hippocampus of epilepsy patients and PTZ-induced seizure model mice. IRAK4 expression is observed in the hilar neurons of PTZ-induced mice. Knocking down IRAK4 in PTZ-induced mice downregulated pyroptosis-related protein expression and alleviated seizure activity. Overexpressing IRAK4 in naive mice upregulated pyroptosis-related protein expression and increased PTZ-induced abnormal neuronal discharges. IRAK4 and NF-κB were found to bind to each other in patient hippocampal tissue samples. Pyrrolidine dithiocarbamate reversed the pyroptosis-related protein expression increase caused by PTZ. PF-06650833 alleviated seizure activity and inhibited pyroptosis in PTZ-induced seizure mice. CONCLUSION: IRAK4 plays a key role in the pathological process of epilepsy, and its potential mechanism may be related to pyroptosis mediated by the NF-κB/NLRP3 signaling pathway. PF-06650833 has potential as a therapeutic agent for alleviating epilepsy.
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Epilepsia , Hipocampo , Quinasas Asociadas a Receptores de Interleucina-1 , FN-kappa B , Proteína con Dominio Pirina 3 de la Familia NLR , Neuronas , Piroptosis , Convulsiones , Transducción de Señal , Animales , Quinasas Asociadas a Receptores de Interleucina-1/metabolismo , Quinasas Asociadas a Receptores de Interleucina-1/genética , Hipocampo/metabolismo , Hipocampo/efectos de los fármacos , Proteína con Dominio Pirina 3 de la Familia NLR/metabolismo , Piroptosis/efectos de los fármacos , Piroptosis/fisiología , Ratones , Transducción de Señal/efectos de los fármacos , Transducción de Señal/fisiología , Humanos , FN-kappa B/metabolismo , Masculino , Convulsiones/metabolismo , Convulsiones/inducido químicamente , Neuronas/metabolismo , Neuronas/efectos de los fármacos , Epilepsia/metabolismo , Epilepsia/inducido químicamente , Femenino , Ratones Endogámicos C57BL , Adulto , Pentilenotetrazol/toxicidad , Adulto Joven , Adolescente , NiñoRESUMEN
PURPOSE: Epilepsy is a debilitating disease that can lead to series of social and psychological issues, impairing the quality of life of people with epilepsy (PWE). This survey aimed to investigate the awareness, attitudes, and first-aid knowledge of epilepsy in university students METHOD: This cross-sectional study was conducted in Henan Province, China between January 1 and April 30, 2022. Students majored in education, medicine, science and engineering from 8 universities attended the study. The survey questionnaire comprised 28 questions covering 4 sections: demographic characteristics, awareness of epilepsy, attitudes toward PWE and knowledge of first aid for seizures. RESULTS: A total of 2376 university students completed the questionnaire. 94.7% heard of epilepsy. In the first aid knowledge section, individual question was correctly answered by at least 50% students, 9.3% students correctly answered all questions. Attitude toward PWE was independently (R2 =0.108, F=73.227, p < 0.001) associated with both awareness of epilepsy (B=0.411, p < 0.001) and first aid knowledge of epilepsy (B=0.047, p = 0.001). Among the three majors, medical students had more positive attitudes toward PWE than students majored in education, science and engineering (p < 0.05). However, medical students performed worse among the groups when answering the first aid knowledge questions. CONCLUSION: This survey showed that university students in Central China had a good awareness of epilepsy. For medical students, improvements are necessary for the awareness of the first aid knowledge for seizure.
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Epilepsia , Primeros Auxilios , Humanos , Estudios Transversales , Universidades , Calidad de Vida , Conocimientos, Actitudes y Práctica en Salud , Epilepsia/terapia , Epilepsia/psicología , Convulsiones , Estudiantes/psicología , Encuestas y Cuestionarios , ChinaRESUMEN
BACKGROUND: This study aimed to construct prediction models for the recognizing of anxiety disorders (AD) in patients with epilepsy (PWEs) by combining clinical features with quantitative electroencephalogram (qEEG) features and using machine learning (ML). METHODS: Nineteen clinical features and 20-min resting-state EEG were collected from 71 PWEs comorbid with AD and another 60 PWEs without AD who met the inclusion-exclusion criteria of this study. The EEG were preprocessed and 684 Phase Locking Value (PLV) and 76 Lempel-Ziv Complexity (LZC) features on four bands were extracted. The Fisher score method was used to rank all the derived features. We constructed four models for recognizing AD in PWEs, whether PWEs based on different combinations of features using eXtreme gradient boosting (XGboost) and evaluated these models using the five-fold cross-validation method. RESULTS: The prediction model constructed by combining the clinical, PLV, and LZC features showed the best performance, with an accuracy of 96.18%, precision of 94.29%, sensitivity of 98.33%, F1-score of 96.06%, and Area Under the Curve (AUC) of 0.96. The Fisher score ranking results displayed that the top ten features were depression, educational attainment, α_P3LZC, α_T6-PzPLV, α_F7LZC, ß_Fp2-O1PLV, θ_T4-CzPLV, θ_F7-PzPLV, α_Fp2LZC, and θ_T4-PzPLV. CONCLUSIONS: The model, constructed by combining the clinical and qEEG features PLV and LZC, efficiently identified the presence of AD comorbidity in PWEs and might have the potential to complement the clinical diagnosis. Our findings suggest that LZC features in the α band and PLV features in Fp2-O1 may be potential biomarkers for diagnosing AD in PWEs.
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Ansiedad , Epilepsia , Humanos , Ansiedad/diagnóstico , Ansiedad/epidemiología , Trastornos de Ansiedad/diagnóstico , Trastornos de Ansiedad/epidemiología , Comorbilidad , Epilepsia/diagnóstico , Epilepsia/epidemiología , Electroencefalografía , Aprendizaje AutomáticoRESUMEN
OBJECTIVE: Anxiety disorders (AD) are critical factors that significantly (about one-fifth) impact the quality of life (QoL) in patients with epilepsy (PWE). Objective diagnostic methods have contributed to the identification of PWE susceptible to AD. This study aimed to identify AD in PWE by constructing a diagnostic model based on the phase locking value (PLV) and Lempel-Ziv Complexity (LZC) features of the electroencephalogram (EEG). METHODS: EEG data from 131 patients with epilepsy (PWE) were enrolled in this study. Patients were divided into two groups, anxiety disorder (AD, nâ¯=â¯61) and non-anxiety disorder (NAD, nâ¯=â¯70), according to the Hamilton Rating Scale for Anxiety (HAM-A). Support vector machine (SVM) and K-Nearest-Neighbor(KNN) algorithms were used to construct three models - the PLVEEG, LZCEEG, and PLVEEGâ¯+â¯LZCEEG feature models. Finally, the area under the receiver operating characteristic curve (AUC) and statistical analyses were performed to evaluate the model performance. RESULTS: The efficiency of the KNN-based PLCEEGâ¯+â¯LZCEEG feature model was the best, and the accuracy, precision, recall, F1-score, and AUC of the model after five-fold cross-validations scores were 87.89â¯%, 82.27â¯%, 98.33â¯%, 88.95â¯%, and 0.89, respectively. When the model efficiency was optimal, 29 EEG features were suggested. Further analysis of these features indicated 22 EEG features that were significantly different between the two groups, including 50â¯% features of the alpha (α)-band. CONCLUSIONS: The PLVEEGâ¯+â¯LZCEEG model features can identify AD in PWE. The PLVEEG and LZCEEG characteristics of the α-band may further be explored as potential biomarkers for AD in PWE.
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Epilepsia , Calidad de Vida , Humanos , Epilepsia/diagnóstico , Ansiedad/diagnóstico , Trastornos de Ansiedad , Electroencefalografía/métodosRESUMEN
Our previous studies have discovered that long non-coding RNA (lncRNA) MALAT1 and its target microRNA-125b-5p (miR-125b-5p) are implicated in neurological diseases via regulating neuroinflammation and neuronal injury. This study aimed to further explore the relationship between lncRNA MALAT1 and miR-125b-5p, as well as their effect on microglial activation, neuroinflammation, and neural apoptosis in spinal cord injury (SCI). Primary microglia from Sprague Dawley rats were stimulated with lipopolysaccharide (LPS). Then, microglia were transfected with lncRNA MALAT1 overexpression or knock-down adenovirus-associated virus with or without miR-125b-5p mimic. The culture medium of microglia was incubated with primary neurons. SCI rats were established for in vivo validation. LncRNA MALAT1 expression was reduced by LPS treatment in a dose-dependent manner. LncRNA MALAT1 overexpression suppressed the microglial M1 polarization (decreased iNOS but increased ARG1), neuroinflammation (declined PTGS2, TNF-α, IL-1ß, and IL-6), and microglia-induced neural apoptosis (lower TUNEL positive cells and C-caspase3 but higher BCL2) under LPS treatment; its knock-down displayed the opposite trend. Moreover, lncRNA MALAT1 directly bound to and negatively regulated miR-125b-5p. MiR-125b-5p mimic promoted microglial M1 polarization, neuroinflammation, and microglia-induced neural apoptosis following LPS treatment; also, it could attenuate the effect of lncRNA MALAT1. Further in vivo study displayed that lncRNA MALAT1 overexpression elevated the Basso-Beattie-Bresnahan motor function score and improved neural injury. Also, in vivo validation indicated a similar effect of lncRNA MALAT1 on microglial polarization and neuroinflammation as in vitro. LncRNA MALAT1 improves SCI recovery via miR-125b-5p mediated microglial M1 polarization, neuroinflammation, and neural apoptosis.
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MicroARNs , ARN Largo no Codificante , Traumatismos de la Médula Espinal , Ratas , Animales , MicroARNs/genética , ARN Largo no Codificante/genética , Microglía/metabolismo , Enfermedades Neuroinflamatorias , Ratas Sprague-Dawley , Lipopolisacáridos/farmacología , Inflamación/metabolismo , Traumatismos de la Médula Espinal/metabolismo , Apoptosis , Médula Espinal/metabolismoRESUMEN
INTRODUCTION: Diabetes is a worldwide chronic disease. The incidence rate of this disease is high, and it is a common disease in clinics. At present, the incidence rate of diabetes patients is increasing year by year due to the increasing work pressure, the accelerated pace of life, the change of diet, the reduction of labor, and the acceleration of aging. EVIDENCE ACQUISITION: The computer retrieves four databases to obtain random controlled trials on the influence of resistance exercise and aerobic exercise on type 2 diabetes. After a rigorous literature quality evaluation, data analysis was performed using RevMan 5.3 software. EVIDENCE SYNTHESIS: Ten studies were ultimately included in this meta-analysis. 10 studies reported the HbA
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Diabetes Mellitus Tipo 2 , Entrenamiento de Fuerza , Humanos , Diabetes Mellitus Tipo 2/terapia , Ejercicio Físico , Terapia por Ejercicio/métodos , DietaRESUMEN
A strategy is proposed herein for preparing a flexible switching piezoresistive pressure sensor, which has a bridge-like structure and inverted micropyramids (IMPs) on its lower conductive substrate. The sensor substrates were prepared by injection compression molding (an industrial manufacturing process) using thermoplastic polyurethane (TPU; an industrial grade polymer). The designed bridge-like structure enables the sensor to obtain a pressure threshold. The flexibility of upper and lower TPU substrates allows them to contact quickly when pressed, and so the sensor exhibits a fast response (as short as 2 ms) and can respond to both static force and dynamic force (up to 50 Hz frequency), which are prominent for the sensor made from TPU. The sensor exhibits less bending-sensitive performance, which is attributed to the conformality of the upper and lower substrates and lower strain on the lower substrate with the IMP under bending. The sensor can amplify signal response at the monitoring limit (the relative resistance change is up to 46%). It can achieve a higher sensitivity in different low-pressure ranges by changing the gap of the bridge-like structure. Moreover, the sensor can obviously and steadily respond to an additional very low pressure under preloading and exhibits good durability performance. As the sensor has a pressure threshold similar to the human pain perception process, a pain-perception-mimetic glove that can identify the external mechanical stimuli but reduces the interference of finger bending is prepared, displaying potential applications of the flexible switching sensor in intelligent wearable protectors.
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Coronavirus disease-2019 (COVID-19) first emerged in late 2019 and has since spread worldwide. More than 600 million people have been diagnosed with COVID-19, and over 6 million have died. Vaccination against COVID-19 is one of the best ways to protect humans. Epilepsy is a common disease, and there are approximately 10 million patients with epilepsy (PWE) in China. However, China has listed "uncontrolled epilepsy" as a contraindication for COVID-19 vaccination, which makes many PWE reluctant to get COVID-19 vaccination, greatly affecting the health of these patients in the COVID-19 epidemic. However, recent clinical practice has shown that although a small percentage of PWE may experience an increased frequency of seizures after COVID-19 vaccination, the benefits of COVID-19 vaccination for PWE far outweigh the risks, suggesting that COVID-19 vaccination is safe and recommended for PWE. Nonetheless, vaccination strategies vary for different PWE, and this consensus provides specific recommendations for PWE to be vaccinated against COVID-19.
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COVID-19 , Epilepsia , Humanos , COVID-19/prevención & control , Vacunas contra la COVID-19/efectos adversos , Consenso , Pueblos del Este de Asia , Epilepsia/complicaciones , Epilepsia/epidemiología , VacunaciónRESUMEN
Objective: To investigate the value of 18F-FDG positron emission tomography/computed tomography (PET/CT) two time point imaging for the identification of the potential epileptogenic zone (EZ) in temporal lobe epilepsy (TLE). Methods: Fifty-two patients with TLE were prospectively enrolled in the 18F-FDG PET/CT two time point imaging study. The early imaging was obtained approximately 40 min (43.44 ± 18.04 min) after 18F-FDG injection, and the delayed imaging was obtained about 2 to 3 h (160.46 ± 28.70 min) after the injection. Visual and semi-quantitative analysis of 18F-FDG uptake were performed at the two time points in EZ and contralateral symmetrical region. The mean standardized uptake value (SUVmean) of EZ and contralateral symmetrical region was calculated to determine the asymmetry index (AI) of the early and delayed images, as well as in the MRI positive and negative patient groups. Results: Semi-quantitative analysis demonstrated that AI of the early and delayed 18F-FDG PET/CT images was 13.47 ± 6.10 and 16.43 ± 6.66, respectively. The ΔAI was 2.95 ± 3.05 in 52 TLE patients between the two time points. The AI of the EZ was significantly elevated in delayed images compared to the early images (p < 0.001). The AI of delayed imaging was also significantly elevated compared to the early imaging in both MRI positive (ΔAI = 2.81 ± 2.54, p < 0.001) and MRI negative (ΔAI = 3.21 ± 3.91, p < 0.003) groups, and more pronounced in MRI negative group. Visual analysis also showed that the delayed imaging appeared to be superior to the early imaging for identification of potential EZ. Conclusion: Delayed 18F-FDG PET imaging provided significantly better than the early imaging in the identification of potential EZ, which can be valuable during epilepsy pre-surgical evaluation in patients with TLE.
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BACKGROUND: Anti-metabotropic glutamate receptor 5 (mGluR5) encephalitis is a rare and under-recognized autoimmune encephalitis. This study is conducted to characterize its clinical and neuroimaging features. METHODS: Twenty-nine patients with anti-mGluR5 encephalitis (15 new cases identified in this study and 14 previously reported cases) were included in this study and their clinical features were characterized. Brain MRI volumetric analysis using FreeSurfer software was performed in 9 new patients and compared with 25 healthy controls at both early (≤6 months of onset) and chronic (>1 year of onset) disease stages. RESULTS: The common clinical manifestations of anti-mGluR5 encephalitis included cognitive deficits (n = 21, 72.4%), behavioral and mood disturbances (n = 20, 69%), seizures (n = 16, 55.2%), and sleep disorder (n = 13, 44.8%). Tumors were observed in 7 patients. Brain MRI T2/FLAIR signal hyperintensities were observed predominantly in mesiotemporal and subcortical regions in 75.9% patients. MRI volumetric analysis demonstrated significant amygdala enlargement in both early and chronic disease stages compared to healthy controls (P < 0.001). Twenty-six patients had complete or partial recovery, one remained stable, one died and one was lost to follow-up. CONCLUSION: Our findings demonstrated that cognitive impairment, behavioral disturbance, seizures, and sleep disorder are the prominent clinical manifestations of anti-mGluR5 encephalitis. Most patients showed a good prognosis with full recovery, even in the paraneoplastic disease variants. The amygdala enlargement in the early and chronic disease stages is a distinct MRI feature, which exploratively offer a valuable perspective for the study of the disease processes.
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Encefalitis , Trastornos del Sueño-Vigilia , Humanos , Imagen por Resonancia Magnética , Neuroimagen , Encefalitis/diagnóstico por imagen , Convulsiones , Encéfalo/diagnóstico por imagenRESUMEN
Recent years have witnessed a significant advancement in brain imaging techniques that offer a non-invasive approach to mapping the structure and function of the brain. Concurrently, generative artificial intelligence (AI) has experienced substantial growth, involving using existing data to create new content with a similar underlying pattern to real-world data. The integration of these two domains, generative AI in neuroimaging, presents a promising avenue for exploring various fields of brain imaging and brain network computing, particularly in the areas of extracting spatiotemporal brain features and reconstructing the topological connectivity of brain networks. Therefore, this study reviewed the advanced models, tasks, challenges, and prospects of brain imaging and brain network computing techniques and intends to provide a comprehensive picture of current generative AI techniques in brain imaging. This review is focused on novel methodological approaches and applications of related new methods. It discussed fundamental theories and algorithms of four classic generative models and provided a systematic survey and categorization of tasks, including co-registration, super-resolution, enhancement, classification, segmentation, cross-modality, brain network analysis, and brain decoding. This paper also highlighted the challenges and future directions of the latest work with the expectation that future research can be beneficial.
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Fault detection for distributed parameter systems (DPSs) generally requires the complete model information to be known so far. However, for numerous industrial applications, it is common that accurate first-principles physical models are extremely difficult to obtain. Hence, the applicability of traditional model-based methods is being restricted. To pave the way, an adaptive neural network (AdNN) is constructed to simultaneously estimate the state variable and the unknown nonlinearity for a class of partially known nonlinear DPSs. Moreover, considering that full-state measurement is unrealistic in applications, the proposed adaptive neural observer is based on a reduced-order model, which also increases the computation efficiency. Then, the residual generation and evaluation are conducted using the output estimation error of the proposed adaptive neural observer. Bearing the effects of the neglected fast dynamics in mind, a data-driven threshold generation scheme is proposed. Extensive experimental results are presented and analyzed to validate the effectiveness of the proposed method.
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Development of new non-addictive analgesics requires advanced strategies to differentiate human pluripotent stem cells (hPSCs) into relevant cell types. Following principles of developmental biology and translational applicability, here we developed an efficient stepwise differentiation method for peptidergic and non-peptidergic nociceptors. By modulating specific cell signaling pathways, hPSCs were first converted into SOX10+ neural crest, followed by differentiation into sensory neurons. Detailed characterization, including ultrastructural analysis, confirmed that the hPSC-derived nociceptors displayed cellular and molecular features comparable to native dorsal root ganglion (DRG) neurons, and expressed high-threshold primary sensory neuron markers, transcription factors, neuropeptides, and over 150 ion channels and receptors relevant for pain research and axonal growth/regeneration studies (e.g., TRPV1, NAV1.7, NAV1.8, TAC1, CALCA, GAP43, DPYSL2, NMNAT2). Moreover, after confirming robust functional activities and differential response to noxious stimuli and specific drugs, a robotic cell culture system was employed to produce large quantities of human sensory neurons, which can be used to develop nociceptor-selective analgesics.
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Neuronas , Células Madre Pluripotentes , Humanos , Neuronas/metabolismo , Nociceptores , Diferenciación Celular , Transducción de Señal , Ganglios Espinales/metabolismo , Células Receptoras SensorialesRESUMEN
AIM: To analyze whether the Lempel-Ziv Complexity (LZC) in quantitative electroencephalogram differs between the temporal lobe epilepsy (TLE) patients with or without cognitive impairment (CI) and explore the diagnostic value of LZC for identifying CI in TLE patients. METHODS: Twenty-two clinical features and 20-min EEG recordings were collected from 48 TLE patients with CI and 27 cognitively normal (CON) TLE patients. Seventy-six LZC features were calculated for 19 leads in four frequency bands (alpha, beta, delta, and theta). The clinical and LZC features were compared between the two groups. A support vector machine (SVM) was subsequently constructed using the leave-one-out method of cross-validation for LZC features with statistical differences. RESULTS: Regarding the clinical features, the level of education (p < .001), hippocampal atrophy and sclerosis (p = .029), and depression (p = .037) were statistically different between the two groups. For the LZC features, there were statistically significant differences in the alpha (Fp1, Fz, Cz, Pz, C3, C4, T3, T4, T5, T6, F3, F4, F7, F8, O1, and O2), beta (Fp2), and theta (F7) oscillations. The mean LZC in the alpha band was higher in the TLE-CI group than that in the CON group, and there were no differences in the remaining bands. The SVM model showed 74.51% accuracy, 79.63% sensitivity, 84.30% F1 score, 68.75% specificity, and .85 area under the curve scores. CONCLUSIONS: The LZC in the alpha band might have the potential to be used as a biomarker for the diagnosis of TLE combined with CI. The TLE-CI group, on the other hand, exhibited a higher degree of complexity in alpha oscillations, which were widespread and occurred in all brain regions.
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Disfunción Cognitiva , Epilepsia del Lóbulo Temporal , Humanos , Epilepsia del Lóbulo Temporal/diagnóstico , Electroencefalografía/métodos , Encéfalo , Disfunción Cognitiva/diagnóstico , Disfunción Cognitiva/etiologíaRESUMEN
Sodium channel inhibitors used as local anesthetics, antiarrhythmics, or antiepileptics typically have the property of use-dependent inhibition, whereby inhibition is enhanced by repetitive channel activation. For targeting pain, Nav1.8 channels are an attractive target because they are prominent in primary pain-sensing neurons, with little or no expression in most other kinds of neurons, and a number of Nav1.8-targeted compounds have been developed. We examined the characteristics of Nav1.8 inhibition by one of the most potent Nav1.8 inhibitors so far described, A-887826, and found that when studied with physiologic resting potentials and physiologic temperatures, inhibition had strong "reverse use dependence", whereby inhibition was relieved by repetitive short depolarizations. This effect was much stronger with A-887826 than with A-803467, another Nav1.8 inhibitor. The use-dependent relief from inhibition was seen in both human Nav1.8 channels studied in a cell line and in native Nav1.8 channels in mouse dorsal root ganglion (DRG) neurons. In native Nav1.8 channels, substantial relief of inhibition occurred during repetitive stimulation by action potential waveforms at 5 Hz, suggesting that the phenomenon is likely important under physiologic conditions. SIGNIFICANCE STATEMENT: Nav1.8 sodium channels are expressed in primary pain-sensing neurons and are a prime current target for new drugs for pain. This work shows that one of the most potent Nav1.8 inhibitors, A-887826, has the unusual property that inhibition is relieved by repeated short depolarizations. This "reverse use dependence" may reduce inhibition during physiological firing and should be selected against in drug development.