Identification of disease-specific genes related to immune infiltration in nonalcoholic steatohepatitis using machine learning algorithms.

To identify disease signature genes associated with immune infiltration in nonalcoholic steatohepatitis (NASH), we downloaded 2 publicly available gene expression profiles, GSE164760 and GSE37031, from the gene expression omnibus database. These profiles represent human NASH and control samples and were used for differential genes (DEGs) expression screening. Two machine learning methods, the Least Absolute Shrinkage and Selection Operator regression model and Support Vector Machine Recursive Feature Elimination, were used to identify candidate disease signature genes. The CIBERSORT deconvolution algorithm was employed to analyze the infiltration of 22 immune cell types in NASH. Additionally, we constructed a NASH cell model using HepG2 cells treated with oleic acid and free fatty acids. The construction of the cell model was verified using oil red O staining, and Western blotting was used to detect the protein expression of the disease signature genes in both control and model groups. As a result, a total of 262 DEGs were identified. These DEGs were primarily associated with metal ion transmembrane transporter activity, sodium ion transmembrane transporter protein activity, calcium ion, and neuroactive ligand-receptor interactions. FOS, IGFBP2, dual-specificity phosphatase 1 (DUSP1), and IKZF3 were identified as disease signature genes of NASH by the least absolute shrinkage and selection operator and Support Vector Machine Recursive Feature Elimination algorithms for DEGs analysis. The receiver operating characteristic curves showed that FOS, IGFBP2, DUSP1, and IKZF3 had good diagnostic value (area under receiver operating characteristic curve > 0.8). These findings were validated in the GSE89632 dataset and through cellular assays. Immunocyte infiltration analysis revealed that NASH was associated with CD8 T cells, CD4 T cells, follicular helper T cells, resting NK cells, eosinophils, regulatory T cells, and γδ T cells. The FOS, IGFBP2, DUSP1, and IKZF3 genes were specifically associated with follicular helper T cells. Lipid droplet aggregation significantly increased in HepG2 cells treated with oleic acid and free fatty acids, indicating successful construction of the cell model. In this model, the expression of FOS, IGFBP2, and DUSP1 was significantly decreased, while that of IKZF3 was significantly elevated (P < .01, P < .001) compared with the control group. Therefore, FOS, IGFBP2, DUSP1, and IKZF3 can be considered as disease signature genes associated with immune infiltration in NASH.

An EEG Study on [Formula: see text] Phase-Amplitude Coupling-Based Functional Brain Network in Epilepsy Patients.

Epilepsy, a chronic neuropsychiatric brain disorder characterized with recurrent seizures, is closely associated with abnormal neural communications within the brain. Despite that the phase-amplitude coupling (PAC) has been suggested to offer a new way to observe neural interactions during epilepsy, however, few studies pay attention to alterations of the epileptic functional brain network based on PAC, especially on the [Formula: see text] PAC. Therefore, we use scalp electroencephalography (EEG) data of epileptic patients and the [Formula: see text] PAC modulation index (MI) to construct functional brain networks to examine variations of neural interactions during different epileptic phases. Statistically, the findings show that between-channel MI values in the post-ictal period significantly increase compared to that in the pre-ictal period, and the between-channel MI value has a close association with the information of phase and amplitude provided by the channels. Importantly, in both the phase-amplitude and amplitude-phase functional brain networks, the average node degree is remarkably higher in the post-ictal period than that in the pre-ictal period, whereas the characteristic path length in the ictal and post-ictal periods is significantly lower than that in the pre-ictal period. Besides, the average betweenness centrality in the post-ictal period is remarkably higher than that in the ictal period. Interestingly, the positive correlations between within-channel MI values and between-channel MI values can be observed during the pre-ictal, ictal and post-ictal periods. These findings suggest that the [Formula: see text] PAC-based functional brain network may provide a novel perspective to understanding alterations of neural interactions during the epileptic evolution, and may contribute to effectively controlling the spread of epileptic seizures.

Dynamic molecular architecture and substrate recruitment of cullin3-RING E3 ligase CRL3KBTBD2.

Phosphatidylinositol 3-kinase α, a heterodimer of catalytic p110α and one of five regulatory subunits, mediates insulin- and insulin like growth factor-signaling and, frequently, oncogenesis. Cellular levels of the regulatory p85α subunit are tightly controlled by regulated proteasomal degradation. In adipose tissue and growth plates, failure of K48-linked p85α ubiquitination causes diabetes, lipodystrophy and dwarfism in mice, as in humans with SHORT syndrome. Here we elucidated the structures of the key ubiquitin ligase complexes regulating p85α availability. Specificity is provided by the substrate receptor KBTBD2, which recruits p85α to the cullin3-RING E3 ubiquitin ligase (CRL3). CRL3KBTBD2 forms multimers, which disassemble into dimers upon substrate binding (CRL3KBTBD2-p85α) and/or neddylation by the activator NEDD8 (CRL3KBTBD2~N8), leading to p85α ubiquitination and degradation. Deactivation involves dissociation of NEDD8 mediated by the COP9 signalosome and displacement of KBTBD2 by the inhibitor CAND1. The hereby identified structural basis of p85α regulation opens the way to better understanding disturbances of glucose regulation, growth and cancer.

MGFKD: A semi-supervised multi-source domain adaptation algorithm for cross-subject EEG emotion recognition.

Currently, most models rarely consider the negative transfer problem in the research field of cross-subject EEG emotion recognition. To solve this problem, this paper proposes a semi-supervised domain adaptive algorithm based on few labeled samples of target subject, which called multi-domain geodesic flow kernel dynamic distribution alignment (MGFKD). It consists of three modules: 1) GFK common feature extractor: projects the feature distribution of source and target subjects to the Grassmann manifold space, and obtains the latent common features of the two feature distributions through GFK method. 2) Source domain selector: obtains pseudo-labels of the target subject through weak classifier, finds "golden source subjects" by using few known labels of target subjects. 3) Label corrector: uses a dynamic distribution balance strategy to correct the pseudo-labels of the target subject. We conducted comparison experiments on the SEED and SEED-IV datasets, and the results show that MGFKD outperforms unsupervised and semi-supervised domain adaptation algorithms, achieving an average accuracy of 87.51±7.68% and 68.79±8.25% on the SEED and SEED-IV datasets with only one labeled sample per video for target subject. Especially when the number of source domains is set as 6 and the number of known labels is set as 5, the accuracy increase to 90.20±7.57% and 69.99±7.38%, respectively. The above results prove that our proposed algorithm can efficiently and quickly improve the cross-subject EEG emotion classification performance. Since it only need a small number of labeled samples of new subjects, making it has strong application value in future EEG-based emotion recognition applications.

Correlations between root phosphorus acquisition and foliar phosphorus allocation reveal how grazing promotes plant phosphorus utilization.

Overgrazing and phosphorus (P) deficiency are two major factors limiting the sustainable development of grassland ecosystems. Exploring plant P utilization and acquisition strategies under grazing can provide a solid basis for determining a reasonable grazing intensity. Both foliar P allocation and root P acquisition are crucial mechanisms for plants to adapt to environmental P availability; however, their changing characteristics and correlation under grazing remain unknown. Here, we investigated foliar P fractions, root P-acquisition traits and gene expression, as well as rhizosphere and bulk soil properties of two dominant plant species, Leymus chinensis (a rhizomatous grass) and Stipa grandis (a bunchgrass), in a field grazing intensity gradient site in Inner Mongolia. Grazing induced different degrees of compensatory growth in the two dominant plant species, increased rhizosphere P availability, and alleviated plant P limitation. Under grazing, the foliar metabolite P of L. chinensis increased, whereas the nucleic acid P of S. grandis increased. Increased P fractions in L. chinensis were positively correlated with increased root exudates and rapid inorganic P absorption. For S. grandis, increased foliar P fractions were positively correlated with more fine roots, more root exudates, and up-regulated expression of genes involved in defense and P metabolism. Overall, efficient root P mobilization and uptake traits, as well as increases in leaf metabolic activity-related P fractions, supported plant compensatory growth under grazing, a process that differed between tiller types. The highest plant productivity and leaf metabolic activity-related P concentrations under medium grazing intensity clarify the underlying basis for sustainable livestock production.

First-principles study of the discharge electrochemical and catalytic performance of the sulfur cathode host Fe0.875M0.125S2 (M = Ti, V).

Lithium-sulfur batteries (LSBs) are one of the most promising energy storage devices with high energy density. However, their application and commercialization are hampered by the slow Li-S redox chemistry. Fe0.875M0.125S2 (M = Ti, V), as the sulfur cathode host, enhances the Li-S redox chemistry. FeS2 with Pa3̄ is transformed into Li2FeS2 with P3̄m1 after discharge. The structure changes and physicochemical properties during Fe0.875M0.125S2 discharge process are further investigated to screen out the sulfur cathode host materials with the best comprehensive properties. The discharge structure of Fe0.875M0.125S2 is verified by the thermodynamic stability of Li-deficient phases, voltage and capacity based on Monte Carlo methods. Fe0.875M0.125S2 with Pa3̄ is transformed into Li2Fe0.875M0.125S2 with P3̄m1 after discharge. Using the first-principles calculations, the physicochemical properties of Li2Fe0.875M0.125S2 are systematically investigated, including the formation energy, voltage, theoretical capacity, electrical conductivity, Li+ diffusion, catalytic performance and Li2S oxidation decomposition. The average redox voltage of Li2Fe0.875V0.125S2 is higher than that of Li2Fe0.875Ti0.125S2. Li2Fe0.875M0.125S2 shows metallic properties. Li2Fe0.875V0.125S2 is more beneficial to the reduction reaction of Li2S2 and Li2S oxidation decomposition. Fe0.875V0.125S2 has more potential as the sulfur cathode host than Fe0.875Ti0.125S2 in LSBs. A new strategy for the selection of the sulfur cathode host material for LSBs is provided by this work.

Multilayer network-based channel selection for motor imagery brain-computer interface.

Objective. The number of electrode channels in a motor imagery-based brain-computer interface (MI-BCI) system influences not only its decoding performance, but also its convenience for use in applications. Although many channel selection methods have been proposed in the literature, they are usually based on the univariate features of a single channel. This leads to a loss of the interaction between channels and the exchange of information between networks operating at different frequency bands.Approach. We integrate brain networks containing four frequency bands into a multilayer network framework and propose a multilayer network-based channel selection (MNCS) method for MI-BCI systems. A graph learning-based method is used to estimate the multilayer network from electroencephalogram (EEG) data that are filtered by multiple frequency bands. The multilayer participation coefficient of the multilayer network is then computed to select EEG channels that do not contain redundant information. Furthermore, the common spatial pattern (CSP) method is used to extract effective features. Finally, a support vector machine classifier with a linear kernel is trained to accurately identify MI tasks.Main results. We used three publicly available datasets from the BCI Competition containing data on 12 healthy subjects and one dataset containing data on 15 stroke patients to validate the effectiveness of our proposed method. The results showed that the proposed MNCS method outperforms all channels (85.8% vs. 93.1%, 84.4% vs. 89.0%, 71.7% vs. 79.4%, and 72.7% vs. 84.0%). Moreover, it achieved significantly higher decoding accuracies on MI-BCI systems than state-of-the-art methods (pairedt-tests,p< 0.05).Significance. The experimental results showed that the proposed MNCS method can select appropriate channels to improve the decoding performance as well as the convenience of the application of MI-BCI systems.

Soil phosphorus availability alters the correlations between root phosphorus-uptake rates and net photosynthesis of dominant C3 and C4 species in a typical temperate grassland of Northern China.

Phosphorus (P) fertilization can alleviate a soil P deficiency in grassland ecosystems. Understanding plant functional traits that enhance P uptake can improve grassland management. We measured impacts of P addition on soil chemical and microbial properties, net photosynthetic rate (Pn ) and nonstructural carbohydrate concentrations ([NSC]), and root P-uptake rate (PUR), morphology, anatomy, and exudation of two dominant grass species: Leymus chinensis (C3 ) and Cleistogenes squarrosa (C4 ). For L. chinensis, PUR and Pn showed a nonlinear correlation. Growing more adventitious roots compensated for the decrease in P transport per unit root length, so that it maintained a high PUR. For C. squarrosa, PUR and Pn presented a linear correlation. Increased Pn was associated with modifications in root morphology, which further enhanced its PUR and a greater surplus of photosynthate and significantly stimulated root exudation (proxied by leaf [Mn]), which had a greater impact on rhizosheath micro-environment and microbial PLFAs. Our results present correlations between the PUR and the Pn of L. chinensis and C. squarrosa and reveal that NSC appeared to drive the modifications of root morphology and exudation; they provide more objective basis for more efficient P-input in grasslands to address the urgent problem of P deficiency.

Benzo(a)pyrene regulates chaperone-mediated autophagy via heat shock protein 90.

AIMS: Some studies have shown that the Benzo(a)pyrene (BaP) exposure induced oxidative damage, DNA damage and autophagy, but the molecular mechanism is not clear. Heat shock protein 90 (HSP90) is regarded as an important target in cancer therapy and a key factor in autophagy. Therefore, this study aims to clarify the new mechanism of BaP regulating CMA through HSP90. MAIN METHODS: C57BL mice were fed with BaP at a dose of 25.3 mg/kg. A549 cells were treated with different concerntrations of BaP, and MTT assay was used to observe the effect of BaP on the proliferation of A549 cells. DNA damage was detected by alkaline comet assay. Focus experiment for detection of γ-H2AX by immunofluorescence. The mRNA expression of HSP90, HSC70 and Lamp-2a was detected by qPCR. The protein expressions of HSP90, HSC70 and Lamp-2a were detected by Western blot. Next, we knocked down HSP90 expression by the HSP90 Inhibitor, NVP-AUY 922, exposed or HSP90α shRNA lentivirus transduction in A549 cells. KEY FINDINGS: In these studies, we first found that heat shock protein 90 (HSP90), heat shock cognate 70 (HSC70) and lysosomal-associated membrane protein type 2 receptor (Lamp-2a) expressions of C57BL mice lung tissue and A549 cells exposed to BaP were significant increase, as well as BaP induced DNA double-strand breaks (DSBs) and activated DNA damage responses, as evidenced by comet assay and γ-H2AX foci analysis in A549 cells. Our results demonstrated BaP induced CMA and caused DNA damage. Next, we knocked down HSP90 expression by the HSP90 Inhibitor, NVP-AUY 922, exposed or HSP90α shRNA lentivirus transduction in A549 cells. HSC70 and Lamp-2a expressions of these cells exposed to BaP were not significant increase, which showed that BaP inducted CMA was mediated by HSP90. Further, HSP90α shRNA prevented BaP induced of BaP which suggested BaP regulated CMA and caused DNA damage by HSP90. Our results elucidated a new mechanism of BaP regulated CMA through HSP90. SIGNIFICANCE: BaP regulated CMA through HSP90. HSP90 is involved in the regulation of gene instability induced by DNA damage by BaP, which promotes CMA. Our study also revealed that BaP regulates CMA through HSP90. This study fills the gap of the effect of BaP on autophagy and its mechanism, which will lead to a more comprehensive understanding of the action mechanism of BaP.

Assessing stroke rehabilitation degree based on quantitative EEG index and nonlinear parameters.

The assessment of motor function is critical to the rehabilitation of stroke patients. However, commonly used evaluation methods are based on behavior scoring, which lacks neurological indicators that directly reflect the motor function of the brain. The objective of this study was to investigate whether resting-state EEG indicators could improve stroke rehabilitation evaluation. We recruited 68 participants and recorded their resting-state EEG data. According to Brunnstrom stage, the participants were divided into three groups: severe, moderate, and mild. Ten quantitative electroencephalographic (QEEG) and five non-linear parameters of resting-state EEG were calculated for further analysis. Statistical tests were performed, and the genetic algorithm-support vector machine was used to select the best feature combination for classification. We found the QEEG parameters show significant differences in Delta, Alpha1, Alpha2, DAR, and DTABR (P < 0.05) among the three groups. Regarding nonlinear parameters, ApEn, SampEn, Lz, and C0 showed significant differences (P < 0.05). The optimal feature classification combination accuracy rate reached 85.3%. Our research shows that resting-state EEG indicators could be used for stroke rehabilitation evaluation.

Asymmetric pendrin homodimer reveals its molecular mechanism as anion exchanger.

Pendrin (SLC26A4) is an anion exchanger expressed in the apical membranes of selected epithelia. Pendrin ablation causes Pendred syndrome, a genetic disorder associated with sensorineural hearing loss, hypothyroid goiter, and reduced blood pressure. However its molecular structure has remained unknown, limiting our understanding of the structural basis of transport. Here, we determine the cryo-electron microscopy structures of mouse pendrin with symmetric and asymmetric homodimer conformations. The asymmetric homodimer consists of one inward-facing protomer and the other outward-facing protomer, representing coincident uptake and secretion- a unique state of pendrin as an electroneutral exchanger. The multiple conformations presented here provide an inverted alternate-access mechanism for anion exchange. The structural and functional data presented here disclose the properties of an anion exchange cleft and help understand the importance of disease-associated variants, which will shed light on the pendrin exchange mechanism.

Improving AR-SSVEP Recognition Accuracy Under High Ambient Brightness Through Iterative Learning.

Augmented reality-based brain-computer interface (AR-BCI) system is one of the important ways to promote BCI technology outside of the laboratory due to its portability and mobility, but its performance in real-world scenarios has not been fully studied. In the current study, we first investigated the effect of ambient brightness on AR-BCI performance. 5 different light intensities were set as experimental conditions to simulate typical brightness in real scenes, while the same steady-state visual evoked potentials (SSVEP) stimulus was displayed in the AR glass. The data analysis results showed that SSVEP can be evoked under all 5 light intensities, but the response intensity became weaker when the brightness increased. The recognition accuracies of AR-SSVEP were negatively correlated to light intensity, the highest accuracies were 89.35% with FBCCA and 83.33% with CCA under 0 lux light intensity, while they decreased to 62.53% and 49.24% under 1200 lux. To solve the accuracy loss problem in high ambient brightness, we further designed a SSVEP recognition algorithm with iterative learning capability, named ensemble online adaptive CCA (eOACCA). The main strategy is to provide initial filters for high-intensity data by iteratively learning low-light-intensity AR-SSVEP data. The experimental results showed that the eOACCA algorithm had significant advantages under higher light intensities ( 600 lux). Compared with FBCCA, the accuracy of eOACCA under 1200 lux was increased by 13.91%. In conclusion, the current study contributed to the in-depth understanding of the performance variations of AR-BCI under different lighting conditions, and was helpful in promoting the AR-BCI application in complex lighting environments.

Case Study: Extension of MSW landfill with reinforced earth berm.

This paper reports a case study of an extension design of an existing municipal solid waste (MSW) earth berm in Guangzhou, China. The berm has limited space for extension and was constructed during a rainy season. Due to the space constraint, the extended berm was designed with a steep slope 1.1 horizontal to 1.0 vertical (1.1H:1.0 V). Due to the rainy season, the new extended earth berm was built with a mix of gravel and sandy clay (i.e. Vgravel/Vclay = 50:50). To make the new berm design satisfies the stability requirement, it has been reinforced with geotextile layers within the berm and piles at the toe of the berm. A 2D finite-element analysis has been conducted to demonstrate the rationality of the design. The performance of the new berm was monitored using field sensors, which include the vertical and lateral displacements of the berm, vertical earth pressure of the berm, and tensile strain of the geotextile layers during and after the berm construction. Numerical and field tests results show that the failure surface appears along the interface between the old berm and the horizonal displacements are mainly observed in the new berm. The results of this study proven that a steep slope berm with geotextiles reinforcement can resistant the load from extended MSW landfill, which can provide a guidance for the design and construction of the extension of MSW landfill.

Changes in plant phosphorus demand and supply relationships in response to different grazing intensities affect the soil organic carbon stock of a temperate steppe.

Ongoing climate change and long-term overgrazing are the main causes of grassland degradation worldwide. Phosphorus (P) is typically a limiting nutrient in degraded grassland soils, and its dynamics may play a crucial role in the responses of carbon (C) feedback to grazing. Yet how multiple P processes respond to a multi-level of grazing and its impact on soil organic carbon (SOC), which is critical for sustainable grassland development in the face of climate change, remains inadequately understood. Here, we investigated P dynamics at the ecosystem level in a 7-year-long multi-level grazing field experiment and analyzed their relation to SOC stock. The results showed that, due to the greater P demand for compensatory plant growth, grazing by sheep increased the aboveground plants' P supply (by 70 % at most) while decreasing their relative P limitation. The increase in P in aboveground tissue was associated with changes in plant root-shoot P allocation and P resorption, and the mobilization of moderately labile organic P in soil. Affected by the altered P supply under grazing, corresponding changes to root C stock and soil total P were two major factors impacting SOC. Compensatory growth-induced P demand and P supply processes responded differently to grazing intensity, resulting in differential effects on SOC. Unlike the light and heavy grazing levels, which reduced the SOC stock, moderate grazing was capable of maintaining maximal vegetation biomass, total plant biomass P, and SOC stock, mainly by promoting biologically- and geochemically-driven plant-soil P turnover. Our findings have important implications for addressing future soil C losses and mitigating higher atmospheric CO2 threats, as well as maintaining high productivity in temperate grasslands.

IGFBP­rP1 affects the proliferation, apoptosis and macrophage polarization of endometrial cancer cells by regulating the PI3K/AKT pathway.

Insulin-like growth factor binding protein-related protein 1 (IGFBP-rP1) is a potential tumor suppressor gene in a variety of cancers including colorectal cancer and breast cancer. However, its role and the potential mechanism in endometrial carcinoma (EC) are still unclear. The purpose of this study was to explore the effect of IGFBP-rP1 on EC cell proliferation and apoptosis and its underlying mechanism. Western blot analysis and reverse transcription-quantitative PCR were used to assess protein and gene expression levels of IGFBP-rP1 in EC cells. Overexpression of IGFBP-rP1 and/or AKT serine/threonine kinase was used to analyze their effects on cell proliferation and apoptosis of the EC cells. Co-immunoprecipitation and glutathione S transferase pull-down assays were used to analyze the interaction between IGFBP-rP1 and AKT. The expression of IGFBP-rP1 in EC cells was downregulated. Overexpression of IGFBP-rP1 inhibited the proliferation and induced apoptosis of EC cells, which were abolished by the overexpression of AKT. In addition, IGFBP-rP1 directly interacted with AKT to inhibit PI3K/AKT signaling. Additionally, M0 macrophages were induced by EC cells to differentiate into M2 macrophages, which was reversed by IGFBP-rP1. Overexpression of AKT in EC cells abolished the inhibitory effect of IGFBP-rP1 on M2 polarization. IGFBP-rP1 as an oncogenic factor inhibits M2 polarization of TAMs through PI3K/AKT signaling pathway and may be a potentially valuable target for EC therapy.

A model description of beta oscillations in the external globus pallidus.

The external globus pallidus (GPe), a subcortical nucleus located in the indirect pathway of the basal ganglia, is widely considered to have tight associations with abnormal beta oscillations (13-30 Hz) observed in Parkinson's disease (PD). Despite that many mechanisms have been put forward to explain the emergence of these beta oscillations, however, it is still unclear the functional contributions of the GPe, especially, whether the GPe itself can generate beta oscillations. To investigate the role played by the GPe in producing beta oscillations, we employ a well described firing rate model of the GPe neural population. Through extensive simulations, we find that the transmission delay within the GPe-GPe pathway contributes significantly to inducing beta oscillations, and the impacts of the time constant and connection strength of the GPe-GPe pathway on generating beta oscillations are non-negligible. Moreover, the GPe firing patterns can be significantly modulated by the time constant and connection strength of the GPe-GPe pathway, as well as the transmission delay within the GPe-GPe pathway. Interestingly, both increasing and decreasing the transmission delay can push the GPe firing pattern from beta oscillations to other firing patterns, including oscillation and non-oscillation firing patterns. These findings suggest that if the transmission delays within the GPe are at least 9.8 ms, beta oscillations can be produced originally in the GPe neural population, which also may be the origin of PD-related beta oscillations and should be regarded as a promising target for treatments for PD.

Recognition of single upper limb motor imagery tasks from EEG using multi-branch fusion convolutional neural network.

Motor imagery-based brain-computer interfaces (MI-BCI) have important application values in the field of neurorehabilitation and robot control. At present, MI-BCI mostly use bilateral upper limb motor tasks, but there are relatively few studies on single upper limb MI tasks. In this work, we conducted studies on the recognition of motor imagery EEG signals of the right upper limb and proposed a multi-branch fusion convolutional neural network (MF-CNN) for learning the features of the raw EEG signals as well as the two-dimensional time-frequency maps at the same time. The dataset used in this study contained three types of motor imagery tasks: extending the arm, rotating the wrist, and grasping the object, 25 subjects were included. In the binary classification experiment between the grasping object and the arm-extending tasks, MF-CNN achieved an average classification accuracy of 78.52% and kappa value of 0.57. When all three tasks were used for classification, the accuracy and kappa value were 57.06% and 0.36, respectively. The comparison results showed that the classification performance of MF-CNN is higher than that of single CNN branch algorithms in both binary-class and three-class classification. In conclusion, MF-CNN makes full use of the time-domain and frequency-domain features of EEG, can improve the decoding accuracy of single limb motor imagery tasks, and it contributes to the application of MI-BCI in motor function rehabilitation training after stroke.

Role and mechanism of benzo[a]pyrene in the transformation of chronic obstructive pulmonary disease into lung adenocarcinoma.

OBJECTIVE: This experiment is explores the genes that play a key role, their expression changes and the biological processes in the transformation of chronic obstructive pulmonary disease (COPD) into lung adenocarcinoma (LAC). Meanwhile, identify the effects of Benzo[a]pyrene (BaP) in the conversion of COPD into LAC. METHODS: 1. Differential expression genes of COPD and LAC were screened and analyzed by high-throughput microarray data between the two diseases and their respective control groups. 2. The screened genes were used for routine bioinformatics analysis such as functional analysis, expression verification, protein interaction analysis and functional enrichment. 3. Cigarette smoke extract (CSE) combined with lipopolysaccharide (LPS) was used to establish an in vitro COPD model. 4. MTT assay was used to detect the influence of B(a)P in effect on A549 cell proliferation. CCK-8, Transwell invasion test and scratch test were used to detect the cell proliferation, invasion and migration ability, while qPCR and Western Blot tests were used to observe the cell proliferation, apoptosis and changes in related indicators such as EMT. 5. Experimental method of separately adding agonists (tBHQ) and inhibitors (DIC) of NQO1 was used to confirm the effect of NQO1 on A549 cell proliferation, apoptosis, migration and invasion. 6. To further clarify whether BaP exerted effect on cell proliferation, apoptosis, migration and invasion through NQO1, we knocked down NQO1 gene and then infecting cells with BaP. RESULTS: 1. We screened genes of COPD and LAC using datasets from GSE151052, GSE118370, and GSE140797. After screening, the genes upregulated in COPD and downregulated in LAC were RTKN2, SLC6A4, and HBB, the gene downregulated in COPD and upregulated in LAC was NQO1, the genes downregulated in both COPD and LAC were FPR1, LYVE1 and PKHD1L1. 2. The main signaling pathways in which the target genes were enriched are cell cycle, EMT, PI3K/AKT, and apoptosis. In the data included GEPIA, PKHD1L1, FPR1, LYVE1, RTKN2, HBB, and SLC6A4 were significantly downregulated and NQO1 was upregulated in LAC relative to controls. In addition, there were 46 interaction proteins in the target genes, and the functions they enriched included hydrogen peroxide catabolism, etc. 3. When A549 cell was stimulated with 100 ng/mL LPS+ 10% CSE, the COX-2 expression indicated that COPD model in vitro was successfully established. 4. The optimal dose and action time were screened which were 1 µM and 24 h. Compared to the control group, COPD and BaP group increased cell proliferation and invasion capabilities. On the basis of COPD, adding BaP could further increase the proliferation and migration capabilities. Interestingly, the levels of NQO1 decreased in COPD models, while increased by BaP. 5. tBHQ can increase the proliferation and migration capacity of A549 cells, which is inhibited by the addition of DIC. 6. The enhanced proliferation, migration and invasion of A549 cells by BaP were attenuated after knockdown of NQO1. CONCLUSION: Our study reveals that PKHD1L1, FPR1, LYVE1, RTKN2, HBB, SLC6A4 and NQO1 may play an important role in the conversion of COPD to LAC. High NQO1 expression may increase the proliferation and migration ability of A549 cells, and BaP may promote the EMT state by increasing the expression of NQO1, thereby making the COPD model in vitro expose the tumor characteristics.

Time-estimation process could cause the disappearence of readiness potential.

Generally, the readiness potential (RP) is considered to be the scalp electroencephalography (EEG) activity preceding movement. In our previous study, we found early RP was absent among approximately half of the subjects during instructed action, but we did not identify the mechanism causing the disappearance of the RP. In this study, we investigated whether the time-estimation process could cause the disappearance of the RP. First, we designed experiments consisting of motor execution (ME), motor execution after time estimation (MEATE), and time estimation (TE) tasks, and we collected and preprocessed the EEG data of 16 subjects. Second, we compared the event related potential (ERP) waveform and scalp topography between ME and MEATE tasks. Then, to explore the influence of time-estimation, we analyzed the difference in ERP between MEATE and TE tasks. Finally, we used source imaging to probe the activation of brain regions during the three tasks, and we calculated the average activation amplitude of eight motor related brain regions. We found that the RP occurred in the ME task but not in the MEATE task. We also found that the waveform of the difference in ERP between the MEATE and TE tasks was similar to that of the ME task. The results of source imaging indicated that, compared to the ME task, the activation amplitude of the supplementary motor area (SMA) decreased significantly for the MEATE task. Our results suggested that the time estimation process could cause the disappearance of the RP. This phenomenon might be caused by the counteraction of neural electrical activity related to time estimation and motor preparation in the SMA.

Structural Study of SARS-CoV-2 Antibodies Identifies a Broad-Spectrum Antibody That Neutralizes the Omicron Variant by Disassembling the Spike Trimer.

The continuous emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants poses new challenges in the fight against the coronavirus disease 2019 (COVID-19) pandemic. The newly emerging Omicron strain caused serious immune escape and raised unprecedented concern all over the world. The development of an antibody targeting a conserved and universal epitope is urgently needed. A subset of neutralizing antibodies (NAbs) against COVID-19 from convalescent patients were isolated in our previous study. In this study, we investigated the accommodation of these NAbs to SARS-CoV-2 variants of concern (VOCs), revealing that IgG 553-49 neutralizes pseudovirus of the SARS-CoV-2 Omicron variant. In addition, we determined the cryo-electron microscopy (cryo-EM) structure of the SARS-CoV-2 spike (S) protein complexed with three monoclonal antibodies targeting different epitopes, including 553-49, 553-15, and 553-60. Notably, 553-49 targets a novel conserved epitope and neutralizes the virus by disassembling S trimers. IgG 553-15, an antibody that neutralizes all of the VOCs except Omicron, cross-links two S trimers to form a trimer dimer, demonstrating that 553-15 neutralizes the virus by steric hindrance and virion aggregation. These findings suggest the potential to develop 553-49 and other antibodies targeting this highly conserved epitope as promising therapeutic reagents for COVID-19. IMPORTANCE The emergence of the Omicron strain of SARS-CoV-2 caused higher immune escape, raising unprecedented concerns about the effectiveness of antibody therapies and vaccines. In this study, we identified a SARS-CoV-2 neutralizing antibody, 553-49, which neutralizes all variants by targeting a completely conserved novel epitope. In addition, we revealed that IgG 553-15 neutralizes SARS-CoV-2 by cross-linking virions and that 553-60 functions by blocking receptor binding. Comparison of different receptor binding domain (RBD) epitopes revealed that the 553-49 epitope is hidden in the S trimer and keeps a high degree of conservation during SARS-CoV-2 evolution, making 553-49 a promising therapeutic reagent against the emerging Omicron and future variants of SARS-CoV-2.