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Optically pumped magnetometer magnetoencephalography (OPM-MEG) represents a novel method for recording neural signals in the brain, offering the potential to measure critical neuroimaging characteristics such as effective brain networks. Effective brain networks describe the causal relationships and information flow between brain regions. In constructing effective brain networks using Granger causality, the noise in the multivariate autoregressive model (MVAR) is typically assumed to follow a Gaussian distribution. However, in experimental measurements, the statistical characteristics of noise are difficult to ascertain. In this paper, a Granger causality method based on a cost-reference particle filter (CRPF) is proposed for constructing effective brain networks under unknown noise conditions. Simulation results show that the average estimation errors of the MVAR model coefficients using the CRPF method are reduced by 53.4% and 82.4% compared to the Kalman filter (KF) and maximum correntropy filter (MCF) under Gaussian noise, respectively. The CRPF method reduces the average estimation errors by 88.1% and 85.8% compared to the MCF under alpha-stable distribution noise and the KF method under pink noise conditions, respectively. In an experiment, the CRPF method recoversthe latent characteristics of effective connectivity of benchmark somatosensory stimulation data in rats, human finger movement, and auditory oddball paradigms measured using OPM-MEG, which is in excellent agreement with known physiology. The simulation and experimental results demonstrate the effectiveness of the proposed algorithm and OPM-MEG for measuring effective brain networks. [ABSTRACT FROM AUTHOR]

The spontaneous oscillations within the brain are intimately linked to the hierarchical structures of the cortex, as evidenced by the cross-cortical gradient between parametrized spontaneous oscillations and cortical locations. Despite the significance of both peak frequency and peak time in characterizing these oscillations, limited research has explored the relationship between peak time and cortical locations. And no studies have demonstrated that the cross-cortical gradient can be measured by optically pumped magnetometer-based magnetoencephalography (OPM-MEG). Therefore, the cross-cortical gradient of parameterized spontaneous oscillation was analyzed for oscillations recorded by OPM-MEG using restricted maximum likelihood estimation with a linear mixed-effects model. It was validated that OPM-MEG can measure the cross-cortical gradient of spontaneous oscillations. Furthermore, results demonstrated the difference in the cross-cortical gradient between spontaneous oscillations during eye-opening and eye-closing conditions. The methods and conclusions offer potential to integrate electrophysiological and structural information of the brain, which contributes to the analysis of oscillatory fluctuations across the cortex recorded by OPM-MEG. [ABSTRACT FROM AUTHOR]

Time–frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time–frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time–frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time–frequency spectrum with Superlet transform. Then, the time–frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation. [ABSTRACT FROM AUTHOR]

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience. [ABSTRACT FROM AUTHOR]

In the face of the increasing scale of port video surveillance systems, edge computing is gradually used to improve the real-time processing efficiency of surveillance systems and reduce the load on the cloud with the advantages of distributed computing. In order to improve the security factor of terminal access in the edge computing environment, this paper proposes a decentralized terminal security access authentication system based on blockchain, which realizes the identity registration, revocation and mutual authentication of two interfaces between terminal devices and edge computing through the smart contract technology of blockchain, and establishes a trusted channel for data transmission between terminals and edge nodes. Through the functional test of the system and the security analysis of the system on the Hyperledger Fabric platform, it shows that the system has more security attributes and higher security.

Neural oscillations observed during semantic processing embody the function of brain language processing. Precise parameterization of the differences in these oscillations across various semantics from a time-frequency perspective is pivotal for elucidating the mechanisms of brain language processing. The superlet transform and cluster depth test were used to compute the time-frequency representation of oscillatory difference (ODTFR) between neural activities recorded by optically pumped magnetometer-based magnetoencephalography (OPM-MEG) during processing congruent and incongruent Chinese semantics. Subsequently, ODTFR was parameterized based on the definition of local events. Finally, this study calculated the specific time-frequency values at which oscillation differences occurred in multiple auditory-language-processing regions. It was found that these oscillatory differences appeared in most regions and were mainly concentrated in the beta band. The average peak frequency of these oscillatory differences was 15.7 Hz, and the average peak time was 457 ms. These findings offer a fresh perspective on the neural mechanisms underlying the processing of distinct Chinese semantics and provide references and insights for analyzing language-related brain activities recorded by OPM-MEG.

Introduction: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified., Methods: The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC)., Results: A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy., Conclusion: This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Zhai, Ma, Wu, Cai, Huang, Zhou and Duan.)

Objective: The morbidity of hepatocellular carcinoma (HCC) is increasing annually. The aim of this study is to investigate the molecular mechanisms of upregulated genes in HCC using bioinformatic methods, so as to identify new potential biological markers., Methods: The Gene Expression Omnibus database (GEO database) was mined for HCC datasets, which were screened for hub genes and subjected to (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis. The hub genes were analyzed in terms of Receiver Operating Characteristic (ROC) and methylation levels. Validation of hub genes was completed through basic pathological alterations based on the protein and gene expression level of hub genes. The correlation of genes with immune infiltration in HCC was analyzed based on the database Timer 2.0, and the prognosis as well as survival of hub genes in HCC was analyzed using R studio software. Finally, we performed a gene combination drug analysis on the potential therapeutic targets in HCC., Results: Expression-up-regulated genes were screened via differential analysis, which were mainly enriched in cell cycles and DNA replication pathways. Five hub genes, BRCA1 associated RING domain 1 (BARD1), Mismatch Repair Protein (MSH2), Recombinant H2A Histone Family, Member X (H2AFX), Recombinant H2A Histone Family, Member z (H2AFZ) and Chromosome 18 Open Reading Frame 54 (C18orf54) were identified using a Protein-Protein Interaction Networks (PPI). After a comprehensive analysis of ROC curves and methylation gene mutation sites, C18orf54 was localized followed by basic experiments, so as to verify the C18orf54 upregulated in HCC. Based on the online database Timer 2.0, the immune infiltration of C18orf54 gene in HCC was analyzed, which was found to be negatively correlated with CD4 + T cells and macrophages in HCC, meanwhile a further refinement of the immune checkpoint correlation analysis revealed that C18orf54 was mainly correlated with Hepatitis A virus cellular receptor 2 (HAVCR2), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Cytotoxic T lymphocyte associate protein-4 (CTLA4). The prognosis and survival of patients with HCC expressing C18orf54 were also analyzed, and it was found that such patients had a higher incidence of adjacent liver tissue inflammation, a higher child-Pugh grade score and a higher rate of residual tumor recurrence. Similarly, the prognosis was worse in the subset of patients with C18orf54. Finally, we performed a combined genetic analysis, which suggested that cyclosporine, quercetin, testosterone and calcitriol might be effective in reducing C18orf54 mRNA expression., Conclusion: C18orf54 is involved in the immune infiltration and promotes the poor prognosis of HCC, which could be a candidate biomarker for HCC., Competing Interests: None., (AJTR Copyright © 2023.)