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Chimeric antigen receptor (CAR) T-cell therapy is highly effective for treating blood cancers such as B-cell malignancies, however, its effectiveness as an approach to treat solid tumors remains to be further explored. Here, we focused on the development of CAR-T cell therapies targeting tropomyosin-related kinase receptor B (TRKB), a highly expressed protein that is significantly associated with tumor progression, malignancy, and drug resistance in multiple forms of aggressive solid tumors. To achieve this, we screened brain-derived neurotrophic factor (BDNF) and neurotrophin 4 (NTF4) ligand-based CAR-T cells for their efficiency in targeting the TRKB receptor in the context of solid tumors, particularly hepatocellular carcinoma and pancreatic cancer. We demonstrated that TRKB is overexpressed not only in hepatocellular carcinoma and pancreatic carcinoma cell lines but also in cancer stem-like cells (CSCs). Notably, BDNF-CAR T and NTF4-CAR T cells could not only effectively target and kill TRKB-expressing pan-cancer cell lines in a dose-dependent manner but also effectively kill CSCs. We also performed in vivo studies to show that NTF4-CAR T cells have a better potential to inhibit the tumor growth of hepatocellular carcinoma xenografts in mice, compared with BDNF-CAR T cells. Taken together, our findings suggest that CAR-T targeting TRKB may be a promising approach for developing novel therapies to treat solid cancers. [ABSTRACT FROM AUTHOR]

MYB-related transcription factors (TFs) subfamily is a subfamily of MYB TFs, which are mainly involved in plant secondary metabolism, growth and development, and stress response. To explore the function of MYB-related subfamily genes in Rosa chinensis, this study systematically analyzed characters of the MYB-related subfamily members in R. chinensis with bioinformatic analysis using the genomic data of R. chinensis and investigated their expression characteristics using quantitative real-time PCR (qRT-PCR). The results show that 100 MYB-related proteins were identified in R. chinensis. Proteins are mainly found in the nucleus. Chromosome localization revealed that all MYB-related genes are mapped to seven chromosomes and are distributed in clusters. Collinear analysis shows that 13 pairs of MYB-related genes had a collinear relationship, indicating R. chinensis may have evolved its MYB-related subfamily gene through fragment duplication. The analysis of motifs and conserved domains shows that Motif 3 is the most conserved motif. There are numerous ABA and MeJA response elements in MYB-related genes. ABA and MeJA treatments significantly shortened the vase life of R. chinensis, while the flower diameter on day 3 was the largest, suggesting that ABA and MeJA might induce MYB-related gene expression during cut flower senescence. The expression of MYB-related genes is tissue specific, most of which show the highest expression levels in petals. Notably, among six plant growth regulator treatments, ABA treatment significantly increased RcMYB002 expression in R. chinensis, suggesting that RcMYB002 may be a crucial gene for ABA response. This study provides a reference for further research on the function of MYB-related genes in R. chinensis. [ABSTRACT FROM AUTHOR]

Objective: Cardiovascular complications associated with COVID‐19 are being increasingly recognized. They include potential long‐term effects on the heart, although how these complications manifest in patients with stroke who are already vulnerable to cardiovascular issues is lacking. This study addressed this gap by investigating the influence of SARS‐CoV‐2 infection on cardiac hemodynamic changes in inpatients with stroke, thereby providing valuable insights into the management of cardiac complications in this population. Methods: This retrospective cohort study enrolled inpatients with stroke who did or did not experience SARS‐CoV‐2 infection in Shenzhen Second People's Hospital. Clinical information, hemodynamics data, serum myocardial enzyme levels, functional levels, including Barthel index, and Longshi scale assessment (bedridden, domestic, and community) were extracted from clinical records. An independent sample t‐test and the Mann–Whitney U test were used for comparison between groups. Multiple logistic regression analysis was used to identify indicators associated with decline in cardiac function in patients with stroke post‐COVID‐19. Results: Eighty‐three patients with stroke (average age of 66.0 ± 15.5 years) were recruited (42 patients in the study group and 41 in the control group). No significant difference in general characteristics was observed between the groups. The ejection fraction (EF, 56.45 ± 12.46 vs. 47.64 ± 14.76, p = 0.04) was decreased, and the end‐diastolic volume (EDV, 142.74 ± 80.00 vs. 193.34 ± 140.17, p = 0.001) was increased significantly in patients infected with SARS‐CoV‐2 compared with the noninfected participants. SARS‐CoV‐2 infection was an independent risk factor for EF (−10%) decrease (OR: 5.205, 95% CI: 1.621–16.720, p = 0.006). The risk of cardiac function decline among bedridden infected patients was 15.43 times higher than that of uninfected nonbedridden patients (OR: 15.430, 95% CI: 1.402–169.805, p = 0.025). Conclusion: Patients who are bedridden after stroke face a higher potential risk of cardiac hemodynamic impairment following SARS‐CoV‐2 infection, emphasizing the need for meticulous hemodynamic monitoring during treatment and rehabilitation of these patients to prevent any potential cardiovascular complications. Trial Registration: ClinicalTrials.gov identifier: ChiCTR2300071376. [ABSTRACT FROM AUTHOR]

The most common type of non-small cell lung cancer is lung adenocarcinoma (LUAD), which is characterized by high morbidity and poor survival. Up-regulation of SASS6 expression can lead to the progression of various malignant tumors. However, there are no relevant studies on the role of SASS6 in LUAD. SASS6 was highly expressed in most tumors, reflecting a good diagnostic value, and its overexpression in LUAD indicated discouraging overall prognosis. Functional enrichment analysis suggested that SASS6 was associated with cell cycle in LUAD. In addition, patients with high SASS6 expression had worse immune infiltration, but higher TMB and immune checkpoint, and higher sensitivity to multiple targeted drugs such as osimertinib. Cell experiments confirmed that knockdown of SASS6 could inhibit the viability of tumor cells.SASS6 has important value in the diagnosis of cancer. In particular, SASS6 is a crucial factor in the progression of LUAD, and has important clinical value, especially in the diagnosis, prognosis and treatment [ABSTRACT FROM AUTHOR]

Current medical therapies for treating acute myeloid leukemia (AML) remain unmet, and AML patients may benefit from targeted immunotherapy approaches that focus on specific tumor antigens. GRP78, which is upregulated in various malignant tumors such as AML, is partially expressed as cell surface GRP78 (csGRP78) on the cell membrane, making it an ideal target for redirecting T cells, including T-cell engagers. However, considering the conventional approach of using two scFv segments to construct a bispecific T-cell engager (BiTE), we have undertaken the development of a novel BiTE that utilizes a cyclic peptide ligand to specifically target csGRP78, which we refer to as GRP78-CD3/BiTE. We studied the effects of GRP78-CD3/BiTE on treatments for AML in vitro and in vivo and assessed the pharmacokinetics of this engager. Our findings demonstrated that GRP78-CD3/BiTE could not only effectively mediate the cytotoxicity of T cells against csGRP78-expressing AML cells but also specifically eliminate primary AML tumor cells in vitro. Furthermore, GRP78-CD3/BiTE exhibited a longer half-life despite having a lower molecular weight than CD19-CD3/BiTE. In a xenograft mouse model of AML, treatment with GRP78-CD3/BiTE prolonged the survival time of the mice. Our findings demonstrate that GRP78-CD3/BiTE is effective and selective for eliminating csGRP78-expressing AML cells and suggest that this approach to targeted immunotherapy could lead to effective new treatments for AML. [ABSTRACT FROM AUTHOR]

CAR-T cell immunotherapy has achieved remarkable success in malignant B-cell malignancies, but progress in solid tumors is slow, and one of the key reasons is the lack of ideal targets. Cancer-specific extra domain B of fibronectin (EDB-FN) is widely upregulated in solid tumors and expressed at low levels in normal tissues. Many imaging and targeted cancer therapies based on EDB-FN targets have been developed and tested in clinical trials, making EDB-FN an ideal target for immunotherapy. We constructed two EDB-FN-targeted CAR-Ts based on the peptide APT0 and the single-chain antibody CGS2 in a lentiviral infection manner for the first time. Luciferase cytotoxicity assay to assess CAR-T killing of tumor cells. An enzyme-linked immunosorbent assay was used to detect the release of the cytokine IFN-γ. Fluorescence imaging to evaluate the dynamics of CAR-T cell and tumor cell coculture. Knockdown assays were used to validate the target specificity of CAR-T cells. In this research, two CAR-Ts targeting EDB-FN, APT0 CAR-T, and CGS2 CAR-T, were constructed. In vitro, both CAR-T cells produced broad-spectrum killing of multiple EDB-FN-positive solid tumor cell lines and were accompanied by cytokine IFN-γ release. Regarding safety, the two CAR-T cells did not affect T cells' normal growth and proliferation and were not toxic to HEK-293T human embryonic kidney epithelial cells. APT0 CAR-T and CGS2 CAR-T cells are two new CAR-Ts targeting EDB-FN. Both CAR-T cells can successfully identify and specifically kill various EDB-FN-positive solid tumor cells with potential clinical applications. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC), the most common primary liver cancer, prevails mainly in males and has long been attributed to androgens and higher circumstantial levels of interleukin-6 (IL-6) produced by resident hepatic macrophages. Methods: Constitutively hepatocyte-specific histone deacetylase 3 (HDAC3)-deficient (HDAC3LCKO) mice and constitutively hepatocyte-specific HDAC3 knockout and systemic IL-6 simultaneously ablated (HDAC3LCKO& IL-6−/−) mice were used in our study to explore the causes of sex differences in HCC. Additionally, we performed human HCC tissues with an IHC score. Correlation analysis and linear regression plots were constructed to reveal the association between HDAC3 and its candidate genes. To further elucidate that HDAC3 controls the expression of Foxa1/2, we knocked down HDAC3 in HUH7 liver cancer cells. Results: We observed a contrary sex disparity, with an earlier onset and higher incidence of HCC in female mice when HDAC3 was selectively ablated in the liver. Loss of HDAC3 led to constant liver injury and the spontaneous development of HCC. Unlike the significant elevation of IL-6 in male mice at a very early age, female mice exhibit stable IL-6 levels, and IL-6 ablation did not eliminate the sex disparity in hepatocarcinogenesis in HDAC3-deficient mice. Oestrogen often protects the liver when combined with oestrogen receptor alpha (ERα); however, ovariectomy in HDAC3-ablated female mice significantly delayed tumourigenesis. The oestrogen-ERα axis can also play a role in tumour promotion in the absence of Foxa1 and Foxa2 in the receptor complex. Loss of HDAC3 profoundly reduced the expression of both Foxa1 and Foxa2 and impaired the binding between Foxa1/2 and ERα. Furthermore, a more frequent HDAC3 decrease accompanied by the simultaneous Foxa1/2 decline was found in female HCC compared to that in male HCC. Conclusion: In summary, we reported that loss of HDAC3 reduces Foxa1/2 and thus promotes HCC development in females in an oestrogen-dependent manner. [ABSTRACT FROM AUTHOR]

In the era of the digital economy, traditional industries have begun to realize digital transformations. For commercial banks, digital transformation is a trend and a requirement and is the only way to achieve sustainable development. At the same time, at the helm of the enterprise, executives play an essential role in the development of commercial banks. This study explored the relationship between digital bank transformation and bank efficiency, environment, society, and corporate governance (ESG) through empirical analysis, and how executives' innovation awareness and executive technical background affect the relationships between digital bank transformation, bank efficiency, and ESG. This study used the regression method of fixed effects to conduct empirical research on the data of China's A-share listed banks from 2011 to 2021. The research results show that the digital transformation of banks has improved efficiency and promoted the ESG performance of commercial banks. At the same time, executives' innovation consciousness and technical background have played a positive regulatory role in banks' digital transformation to promote bank efficiency and ESG. The main research object of this study was Chinese commercial banks. The bank's digital transformation results were examined and the research was expanded to digital transformation and ESG. At the same time, this study has particular significance for investors who have a financial interest in banks. [ABSTRACT FROM AUTHOR]

Whether in natural scenes or laboratory environments, leaf instance segmentation is still a challenging task in high-throughput plant phenotypic research. Because compared with normal instance objects, leaves have more complex boundaries and severe inter-leaf occlusions. In this paper, we present an effective two-stage method called Bilayer Convolution Mask (BCMask) for high-quality leaf instance segmentation. BCMask consists of three main modules: (1) Bottom-up Path Augmentation (BPA) module is added after Feature Pyramid Network (FPN) in Faster R-CNN. BPA shortens the information path between lower layers and high-level layers, and helps accurate semantical features in lower layers to enhance the entire feature hierarchy; (2) Bilayer Occlusion Module. This module consists of two convolutional layers with a residual structure, which decouples the occluding leaves and the partially occluded target leaf during the mask regression; (3) Mask Refining Module. This module uses an iterative refinement method with adaptive selection to classify pixels, which effectively alleviates the problem of inaccurate leaf boundary segmentation. To validate BCMask, this paper takes the chrysanthemum seedling leaf dataset for experiment, which is collected in the natural environment with complex boundaries and severe occlusions. Two remarkable public datasets CVPPA and Komatsuna under laboratory environments are also added as supplements to validate the robustness of BCMask. The proposed method achieves the 60.42% average precision (AP) score outperforming state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The development of financial technology has promoted the innovation and digital transformation of commercial banks. Through digital transformation, commercial banks can improve bank efficiency and operational capabilities. Through empirical analysis, this study explored the relationship between digital bank transformation and commercial bank operating capabilities and how COVID-19, bank categories, and enterprise life cycles affect the relationship between digital bank transformation and commercial bank operating capabilities. This study selected data from China's commercial banks from 2011 to 2021 and used the regression method of fixed effects to conduct an empirical analysis. The research results show that the digital transformation of banks has improved the operational capabilities of commercial banks. Further analysis showed that the emergence of COVID-19 has negatively affected their relationship. At the same time, compared with rural commercial banks and commercial banks in the recession and phase-out periods, non-rural commercial banks and commercial banks in the growth and maturity stages play a more vital moderating role in the impact of the digital transformation of banks on the financial performance of commercial banks. The main research object of this study is Chinese commercial banks, and this study examines the results of banks' digital transformation and enriches the research on digital transformation. At the same time, this study is helpful to investors who like investment banks and has good practical significance. [ABSTRACT FROM AUTHOR]

The transport of a non-uniform bed load in a river is a complicated process and has enormous implications on the sediment flux and anomalous riverbed evolution. To investigate the transport characteristics of the non-uniform bed load and the related particle interactions, a real-time monitoring system of the bed load transport was developed to determine the instant transport rate and grain composition of the bed load. Doppler Velocimetry was used to synchronously measure the fluctuating velocity in high frequency. A total of 211 cases of flume experiments were conducted, focusing on non-uniform sediment with a bimodal pattern. The experimental results indicate that the random fluctuation of the bed load transport amount closely depends on the flow-intensity fluctuation caused by the turbulence burst near the bed. When the value of the flow-fluctuation peak is bigger than 2.5 σ, the coarse sands tend to incipient motion in high probability but are mostly fine sand transport when the peak is less than 1.5 σ. The transport rate of fine particles remains continuous throughout the process, while that of coarse particles is intermittent because the incipient motion mechanism of bed load sands mainly follows three modes. If the difference in diameter between the coarse and fine particles is large, the transport of coarse particles may undergo supernormal transport because of the effect of the fine particles on the coarse particles. The bed load flux of total, fine, and coarse sand present different trends with changes in the bed material composition, in which the transport rate of coarse sands and total bed load sands presents a humped curve in terms of the mixture ratio, and the optimal corresponding mixture ratio ηc is about 3:7. The optimal mixture ratio is not fixed, and it depends on the grain composition and size differential of bed material. With a proper mixture ratio, the transport rate of a non-uniform bed load is higher than the uniform bed load of related size. These findings might provide valuable support for predicting bed load transport and bed evolution in rivers. [ABSTRACT FROM AUTHOR]

The observation of and research on raindrop size distribution (DSD) is important for mastering and understanding the mutual restriction relationship between cloud dynamics and cloud microphysics in a process of precipitation; it also plays an irreplaceable role in many fields, such as radar meteorology, weather modification, boundary layer land surface processes, aerosols, etc. Using more than 1.7 million minutes of raindrop data observed with 17 laser disdrometers at 17 stations in Anhui Province, China, from 7 August 2009 to 30 April 2020, a DSD training dataset was constructed. Furthermore, the data are fitted to a normalized Gamma function and used to obtain its three parameters, i.e., the normalized intercept Nw, the mass weighted average diameter Dm, and the shape factor μ. Based on the long short-term memory network (LSTM), a DSD Gamma distribution prediction network (DSDnet) was designed. In the process of modeling based on DSDnet, a self-defined loss function (SLF) was proposed in order to improve the DSD prediction by increasing the weight values in the poor fitting regions according to the common mean square error loss function (MLF). By means of the training dataset, a DSDnet-based model was trained to realize the prediction of Nw, Dm, and μ minute-to-minute over the course of 30 min, and then was evaluated by the test dataset according to three indicators, namely, mean relative error (MRE), mean absolute error (MAE), and correlation coefficient (CC). The CC of lgNw, Dm, and μ can reach 0.93403, 0.90934, and 0.89741 for 12-min predictions, and 0.87559, 0.85261, and 0.84564 for 30-min predictions, respectively, which means that the DSD prediction accuracy within 30 min can basically reach the application level. Furthermore, the 12- and 30-min predictions of 3 precipitation processes were taken as examples to fully demonstrate the application effect of model. The prediction effects of Nw and Dm are better than that of μ, and the stratiform precipitation is better than the convective and convective-stratiform mixed cloud precipitation. [ABSTRACT FROM AUTHOR]

We propose HyFRIS-Net to jointly estimate the hybrid reflectance and illumination models, as well as the refined face shape from a single unconstrained face image in a pre-defined texture space. The proposed hybrid reflectance and illumination representation ensure photometric face appearance modeling in both parametric and non-parametric spaces for efficient learning. While forcing the reflectance consistency constraint for the same person and face identity constraint for different persons, our approach recovers an occlusion-free face albedo with disambiguated color from the illumination color. Our network is trained in a self-evolving manner to achieve general applicability on real-world data. We conduct comprehensive qualitative and quantitative evaluations with state-of-the-art methods to demonstrate the advantages of HyFRIS-Net in modeling photo-realistic face albedo, illumination, and shape. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) presents a significant global health challenge owing to its poor prognosis and high mortality rates. Despite its involvement in the initiation and progression of a number of cancer types, the understanding of the precise impact of MIS18 kinetochore protein A (MIS18A) on LUAD remains incomplete. In the present study, the role of MIS18A in LUAD was investigated by analyzing the genomic and clinical data from multiple public datasets. The expression of MIS18A was validated using reverse transcription-quantitative polymerase chain reaction, and in vitro experiments involving small interfering RNA-induced downregulation of MIS18A in lung cancer cells were conducted to further explore its impact. These findings revealed that elevated MIS18A expression in LUAD was associated with advanced clinical features and poor prognosis. Functional analysis also revealed the role of MIS18A in regulating the cell cycle and immune-related pathways. Moreover, MIS18A altered the immune microenvironment in LUAD, influencing its response to immunotherapy and drug sensitivity. The results of the in vitro experiments indicated that suppression of MIS18A expression reduced the proliferative and migratory capacities of LUAD cells. In summary, MIS18A possesses potential as a biomarker and may serve as a possible therapeutic target for LUAD, with significant implications for tumor progression by influencing both cell cycle dynamics and immune infiltration. [ABSTRACT FROM AUTHOR]

Summary: Accurate and reliable model parameters are not only a prerequisite for model‐based estimation but also a significant part of battery operating characteristics. However, the measurement signal inevitably contains noise, which brings great challenges to model identification. This paper focuses on the noise immunity performance of model identification based on two‐swarm cooperative particle swarm optimization. An adaptive dynamic sliding window based on the current rate criterion and the identification results feedback is designed to avoid data redundancy and improve the robustness of model identification. The model parameters are obtained using two‐swarm cooperative particle swarm optimization based on the adaptive dynamic sliding window. The proposed method effectively improves the accuracy and speed of parameter identification through optimization of data fragments and particle update rules. Compared with two existing parameter identification methods, simulation studies illustrate that the average mean square deviation of the proposed method is reduced by at least 35 dB. The proposed method is superior to existing parameter identification methods in noise immunity performance, parameter identification reliability, and state‐of‐charge estimation accuracy. By employing the proposed method, the maximum errors of state‐of‐charge estimation are limited within 1% under experimental verification. The experiment results verify that the proposed method has the potential to extract reliable model features online. [ABSTRACT FROM AUTHOR]

Aim:PYGL has been reported to have carcinogenic effects in a variety of tumors. This study is the first to reveal the relationship between PYGL and the prognosis of glioma. Materials & methods: Analyzing the Chinese Glioma Genome Atlas database, the authors revealed the expression status and prognostic value of PYGL in gliomas and used quantitative real-time PCR to verify PYGL expression again. Subsequently, they used Gene Set Enrichment Analysis to explore the biological pathways that PYGL may participate in. The authors also used the tumor immune estimation resource database to explore the relationship between PYGL and tumor immune cells. Results:PYGL is involved in the malignant progression of glioma. Conclusions:PYGL can be used as a new biomarker and molecular target for evaluating the prognosis and immunotherapy of glioma. [ABSTRACT FROM AUTHOR]

Research has confirmed that extra spindle pole bodies-like 1 (ESPL1), an etiological factor, promotes the malignant progression of cancers. However, the relationship between ESPL1 and glioma has not yet been demonstrated. The purpose of this study was to reveal the potential mechanisms of ESPL1-mediated malignant glioma progression. Gene expression data and detailed clinical information of glioma cases were obtained from multiple public databases. Subsequently, a series of bioinformatics analyses were used to elucidate the effects of ESPL1 on glioma. The results demonstrated that the mRNA and protein levels of ESPL1 in glioma were higher than those in normal brain tissues. In addition, ESPL1 expression was considerably associated with the clinical and pathological features of gliomas, such as World Health Organization grade, histology, and 1p19q co-deletion status. Importantly, ESPL1 reduced the overall survival (OS) of glioma patients and had prognostic value for gliomas. Gene set enrichment analysis (GSEA) indirectly revealed that ESPL1 regulates the activation of cancer-related pathways, such as the cell cycle and base excision repair pathways. In addition, we used the Connectivity Map (CMap) database to screen three molecular drugs that inhibit ESPL1: thioguanosine, antimycin A, and zidovudine. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of ESPL1 in glioma cell lines. This study plays an important role in revealing the etiology of glioma by revealing the function of ESPL1, providing a potential molecular marker for the diagnosis and treatment of glioma, especially low-grade glioma. [ABSTRACT FROM AUTHOR]

Emotional reactions to movies are typically similar between people. However, depressive symptoms decrease synchrony in brain responses. Less is known about the effect of depressive symptoms on intersubject synchrony in conscious stimulus-related processing. In this study, we presented amusing, sad and fearful movie clips to dysphoric individuals (those with elevated depressive symptoms) and control participants to dynamically rate the clips' valences (positive vs. negative). We analysed both the valence ratings' mean values and intersubject correlation (ISC). We used electrodermal activity (EDA) to complement the measurement in a separate session. There were no group differences in either the EDA or mean valence rating values for each movie type. As expected, the valence ratings' ISC was lower in the dysphoric than the control group, specifically for the sad movie clips. In addition, there was a negative relationship between the valence ratings' ISC and depressive symptoms for sad movie clips in the full sample. The results are discussed in the context of the negative attentional bias in depression. The findings extend previous brain activity results of ISC by showing that depressive symptoms also increase variance in conscious ratings of valence of stimuli in a mood-congruent manner. [ABSTRACT FROM AUTHOR]

This article aims to realize the combined application of satellite remote sensing data and Lidar data fusion of atmospheric ozone in the ozone distribution prediction in western China. Firstly, the ozone remote sensing data and Lidar vertical monitoring data detected by ozone monitoring instruments are collected from various provinces in western China; the recurrent neural network (RNN) model based on the gated recurrent unit and the convolutional neural network (CNN) model based on time series are constructed and integrated to obtain the RNN–CNN model for ozone concentration prediction, and the prediction performance is compared with that of the RNN and CNN model. Satellite remote sensing data show that the total ozone concentration in western China has obvious spatial distribution characteristics, and can be elevated with the increase in latitude; the ozone concentration in the north is higher and the ozone concentration in the south is lower in different seasons in western China, and it in autumn and summer is lower than that in spring and winter generally. The hour-by-hour change of ozone concentration shows that the ozone concentration in different seasons reaches a trough around 9–10 o'clock, and reaches a peak around 16–17 o'clock. When the RNN–CNN model is applied to predict the hourly change of ozone concentration within a day, it can achieve the best root-mean-squared error (18.13), mean absolute error (11.64), and index of agreement (0.973). The monitoring results of Lidar data at a certain site are compared and analyzed, and the results show that the fitness is the best between the predicted value of ozone concentration obtained by the RNN–CNN model and the actually measured value. This research provides the possibility for the intelligent prediction of atmospheric ozone concentration distribution and has reliable theoretical value and practical significance. [ABSTRACT FROM AUTHOR]

Summary: Model‐based state of charge (SOC) estimation method depends on the accuracy of the online identified battery model. However, when battery model parameters are identified by conventional recursive least squares (RLS), voltage and current noise will lead to the deviation of parameters and further affect the accuracy of SOC estimation. To analyze the difference influence of voltage and current noise, a simulation is carried out under the same noise variance of both voltage and current. Results indicate that voltage noise is the main cause of parameter deviation. Based on these results, a novel method, the auxiliary model recursive least square (AM‐RLS) which enjoys low computational complexity is proposed to compensate the parameter deviation caused by voltage noise. The AM‐RLS method is further combined with an extended Kalman filter (EKF) to estimate SOC in real time. Both simulation and experimental results show that AM‐RLS can effectively attenuate the parameter deviation and SOC estimation error under noise interference. Compared with RLS, the maximum SOC errors of the proposed method are reduced by 2.6% and 5.86% respectively under two current profiles. [ABSTRACT FROM AUTHOR]

Previous studies have associated visual working memory (VWM) capacity with the use of internal attention. Retrocues, which direct internal attention to a particular object or feature dimension, can improve VWM performance (i.e., retrocue benefit, RCB). However, so far, no study has investigated the relationship between VWM capacity and the magnitudes of RCBs obtained from object-based and dimension-based retrocues. The present study explored individual differences in the magnitudes of object- and dimension-based RCBs and their relationships with VWM capacity. Participants completed a VWM capacity measurement, an object-based cue task, and a dimension-based cue task. We confirmed that both object- and dimension-based retrocues could improve VWM performance. We also found a significant positive correlation between the magnitudes of object- and dimension-based RCB indexes, suggesting a partly overlapping mechanism between the use of object- and dimension-based retrocues. However, our results provided no evidence for a correlation between VWM capacity and the magnitudes of the object- or dimension-based RCBs. Although inadequate attention control is usually assumed to be associated with VWM capacity, the results suggest that the internal attention mechanism for using retrocues in VWM retention is independent of VWM capacity. [ABSTRACT FROM AUTHOR]

To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscillatory brain patterns were determined by permutation correlation analysis between individual time courses of Fourier-ICA components and musical features. We found that (1) three components, including a beta sensorimotor network, a beta auditory network and an alpha medial visual network, were involved in music processing among most healthy subjects; and that (2) one alpha lateral component located in the left angular gyrus was engaged in music perception in most individuals with MDD. The proposed method allowed the statistical group comparison, and we found that: (1) the alpha lateral component was activated more strongly in healthy subjects than in the MDD individuals, and that (2) the derived frequency-dependent networks of musical feature processing seemed to be altered in MDD participants compared to healthy subjects. The proposed pipeline appears to be valuable for studying disrupted brain oscillations in psychiatric disorders during naturalistic paradigms. [ABSTRACT FROM AUTHOR]

Sustained attention encompasses a cascade of fundamental functions. The human ability to implement a sustained attention task is supported by brain networks that dynamically formed and dissolved through oscillatory synchronization. The decrement of vigilance induced by prolonged task engagement affects sustained attention. However, little is known about which stage or combinations are affected by vigilance decrement. Here, we applied an analysis framework composed of weighted phase lag index (wPLI) and tensor component analysis (TCA) to an EEG dataset collected during 80 min sustained attention task to examine the electrophysiological basis of such effect. We aimed to characterize the phase-coupling networks to untangle different phases involved in sustained attention and study how they are modulated by vigilance decrement. We computed the time–frequency domain wPLI from each block and subject and constructed a fourth-order tensor, containing the time, frequency, functional connectivity (FC), and blocks × subjects. This tensor was subjected to the TCA to identify the interacted and low-dimensional components representing the frequency-specific dynamic FC (fdFC). We extracted four types of neuromakers during a sustained attention task, namely the pre-stimulus alpha right-lateralized parieto-occipital FC, the post-stimulus theta fronto-parieto-occipital FC, delta fronto-parieto-occipital FC, and beta right/left sensorimotor FCs. All these fdFCs were impaired by vigilance decrement. These fdFCs, except for the beta left sensorimotor network, were restored by rewards, although the restoration by reward in the beta right sensorimotor network was transient. These findings provide implications for dissociable effects of vigilance decrement on sustained attention by utilizing the tensor-based framework. [ABSTRACT FROM AUTHOR]

Two hypotheses have been proposed to explain the formation manner for visual working memory (VWM) representations during the consolidation process: an all-or-none process hypothesis and a coarse-to-fine process hypothesis. However, neither the all-or-none process hypothesis nor the coarse-to-fine process hypothesis can stipulate clearly how VWM representations are formed during the consolidation process. In the current study, we propose a two-stage process hypothesis to reconcile these hypotheses. The two-stage process hypothesis suggests that the consolidation of coarse information is an all-or-none process in the early consolidation stage, while the consolidation of detailed information is a coarse-to-fine process in the late consolidation stage. By systematically manipulating the encoding time of memory stimuli, we asked participants to memorize one (Experiment 1) or two (Experiment 2) orientations in different encoding time intervals. We found that the memory rate increased linearly as the encoding time increased. More importantly, VWM precision remained constant when the encoding time was short, while the precision increased linearly as the encoding time increased when the encoding time was sufficient. These results supported the two-stage process hypothesis, which reconciles previous conflicting findings in the literature. [ABSTRACT FROM AUTHOR]

The influence of motivation on selective visual attention in states of high vs. low vigilance is poorly understood. To explore the possible differences in the influence of motivation on behavioral performance and neural activity in high and low vigilance levels, we conducted a prolonged 2 h 20 min flanker task and provided monetary rewards during the 20- to 40- and 100- to 120-min intervals of task performance. Both the behavioral and electrophysiological measures were modulated by prolonged task engagement. Moreover, the effect of reward was different in high vs. low vigilance states. The monetary reward increased accuracy and decreased the reaction time (RT) and number of omitted responses in the low but not in the high vigilance state. The fatigue-related decrease in P300 amplitude recovered to its level in the high vigilance state by manipulating motivation, whereas the fatigue-related increase in P300 latency was not modulated by reward. Additionally, the fatigue-related increase in event-related spectral power at 1–4 Hz was sensitive to vigilance decrement and reward. However, the spectral power at 4–8 Hz was only affected by the decrease in vigilance. These electrophysiological measures were not influenced by motivation in the state of high vigilance. Our results suggest that neural processing capacity, but not the timing of processing, is sensitive to motivation. These findings also imply that the fatigue-related impairments in behavioral performance and neural activity underlying selective visual attention only partly recover after manipulating motivation. Furthermore, our results provide evidence for the dissociable neural mechanisms underlying the fatigue-related decrease vs. reward-related increase in attentional resources. [ABSTRACT FROM AUTHOR]

Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier–ICA) to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta–beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing. [ABSTRACT FROM AUTHOR]

Recent continuous task studies, such as narrative speech comprehension, show that fluctuations in brain functional connectivity (FC) are altered and enhanced compared to the resting state. Here, we characterized the fluctuations in FC during comprehension of speech and time-reversed speech conditions. The correlations of Hilbert envelope of source-level EEG data were used to quantify FC between spatially separate brain regions. A symmetric multivariate leakage correction was applied to address the signal leakage issue before calculating FC. The dynamic FC was estimated based on a sliding time window. Then, principal component analysis (PCA) was performed on individually concatenated and temporally concatenated FC matrices to identify FC patterns. We observed that the mode of FC induced by speech comprehension can be characterized with a single principal component. The condition-specific FC demonstrated decreased correlations between frontal and parietal brain regions and increased correlations between frontal and temporal brain regions. The fluctuations of the condition-specific FC characterized by a shorter time demonstrated that dynamic FC also exhibited condition specificity over time. The FC is dynamically reorganized and FC dynamic pattern varies along a single mode of variation during speech comprehension. The proposed analysis framework seems valuable for studying the reorganization of brain networks during continuous task experiments. [ABSTRACT FROM AUTHOR]

Recent studies show that the dynamics of electrophysiological functional connectivity is attracting more and more interest since it is considered as a better representation of functional brain networks than static network analysis. It is believed that the dynamic electrophysiological brain networks with specific frequency modes, transiently form and dissolve to support ongoing cognitive function during continuous task performance. Here, we propose a novel method based on tensor component analysis (TCA), to characterize the spatial, temporal, and spectral signatures of dynamic electrophysiological brain networks in electroencephalography (EEG) data recorded during free music-listening. A three-way tensor containing time-frequency phase-coupling between pairs of parcellated brain regions is constructed. Nonnegative CANDECOMP/PARAFAC (CP) decomposition is then applied to extract three interconnected, low-dimensional descriptions of data including temporal, spectral, and spatial connection factors. Musical features are also extracted from stimuli using acoustic feature extraction. Correlation analysis is then conducted between temporal courses of musical features and TCA components to examine the modulation of brain patterns. We derive several brain networks with distinct spectral modes (described by TCA components) significantly modulated by musical features, including higher-order cognitive, sensorimotor, and auditory networks. The results demonstrate that brain networks during music listening in EEG are well characterized by TCA components, with spatial patterns of oscillatory phase-synchronization in specific spectral modes. The proposed method provides evidence for the time-frequency dynamics of brain networks during free music listening through TCA, which allows us to better understand the reorganization of electrophysiological networks. [ABSTRACT FROM AUTHOR]

Neural Oscillatory Basis of Depression The authors agree with the discusser that it might be better to use nonlinear analysis to discriminate between MDD patients and healthy controls during emotional processing. Dalian University of Technology, Dalian, P. R. China †† Department of Computer Science University of Helsinki, Finland ‡‡ yongjie.zhu@foxmail.com §§ xujing doc@aliyun.com ¶¶ changee99@gmail.com cong@dlut.edu.cn Accepted 19 December 2020 Published Online 4 February 2021 Keywords: Brain network disease; bio-psycho-social model; music therapy; natural stimuli; depression. Specifically, they would like to look at whether the frequency-specific networks of musical feature processing were disrupted in patients with MDD. [Extracted from the article]

Abstract: Acute liver failure (ALF) is associated with high mortality, and a poor understanding of the underlying pathophysiology has resulted in a lack of effective treatments so far. Here, using an amatoxin‐induced rhesus monkey model of ALF, we panoramically revealed the cellular and molecular events that lead to the development of ALF. The challenged monkeys with toxins underwent a typical course of ALF including severe hepatic injury, systemic inflammation and eventual death. Adaptive immune was not noticeably disturbed throughout the progress of ALF. A systematic examination of serum factors and cytokines revealed that IL‐6 increase was the most rapid and drastic. Interestingly, we found that IL‐6 was mainly produced by circulating monocytes. Furthermore, ablation of monocyte‐derived IL‐6 in mice decreased liver injury and systemic inflammation following chemical injection. Our findings reveal a critical role of circulating monocytes in initiating and accelerating ALF, indicating a potential therapeutic target in clinical treatment for ALF. [ABSTRACT FROM AUTHOR]

Estrogen-related receptor α (ERRα) is a member of the superfamily controlling energy homeostasis; however, its precise role in regulating antiviral innate immunity remains to be clarified. Here, we showed that ERRα deficiency conferred resistance to viral infection both in vivo and in vitro. Mechanistically, ERRα inhibited the production of type-I interferon (IFN-I) and the expression of multiple interferon-stimulated genes (ISGs). Furthermore, we found that viral infection induced TBK1-dependent ERRα stabilization, which in turn associated with TBK1 and IRF3 to impede the formation of TBK1-IRF3, IRF3 phosphorylation, IRF3 dimerization, and the DNA binding affinity of IRF3. The effect of ERRα on IFN-I production was independent of its transcriptional activity and PCG-1α. Notably, ERRα chemical inhibitor XCT790 has broad antiviral potency. This work not only identifies ERRα as a critical negative regulator of antiviral signaling, but also provides a potential target for future antiviral therapy. [ABSTRACT FROM AUTHOR]

In recent years, major discoveries have indicated that Ras homology family member C (RHOC) is involved in the occurrence and pathological progression of a number of malignant tumours; nevertheless, the role served by RHOC in glioma remains unclear. The present study aimed to gain further insight into the biological function and expression of RHOC in human glioma based on the Chinese Glioma Genome Atlas (CGGA). The current study analysed ~1,000 glioma samples from the CGGA. First, RHOC expression was analysed according to the clinical features associated with the prognosis of glioma, such as clinical stage, histological type and age. Second, the Kaplan-Meier method was used, revealing that the survival rate of patients with glioma with high RHOC expression was significantly lower than that of patients with low RHOC expression. Receiver operating characteristic curve analysis indicated that RHOC had moderate diagnostic value for patients with glioma. Gene set enrichment analysis indirectly indicated that RHOC mainly participated in the pathological mechanism of glioma through p53, extracellular matrix receptor interaction and focal adhesion. Finally, the aforementioned results were further verified using The Cancer Genome Atlas data and reverse transcription-quantitative PCR technology. To the best of our knowledge, the present study was the first comprehensive in-depth analysis of RHOC, revealing the potential value of RHOC as a novel oncogene in glioma. The current study provided a novel potential biomarker for the diagnosis and prognosis of glioma, and re-examined the pathological mechanism of glioma from a new perspective. [ABSTRACT FROM AUTHOR]

Berberine (BBR) has a neuroprotective effect against ischemic stroke, but its specific protective mechanism has not been clearly elaborated. This study explored the effect of BBR on the canopy FGF signaling regulator 2 (CNPY2) signaling pathway in the ischemic penumbra of rats. The model of cerebral ischemia-reperfusion injury (CIRI) was established by the thread embolization method, and BBR was gastrically perfused for 48 h or 24 h before operation and 6 h after operation. The rats were randomly divided into four groups: the Sham group, BBR group, CIRI group, and CIRI + BBR group. After 2 h of ischemia, followed by 24 h of reperfusion, we confirmed the neurologic dysfunction and apoptosis induced by CIRI in rats (p < 0.05). In the ischemic penumbra, the expression levels of CNPY2-regulated endoplasmic reticulum stress-induced apoptosis proteins (CNPY2, glucose-regulated protein 78 (GRP78), double-stranded RNA-activated protein kinase-like ER kinase (PERK), C/EBP homologous protein (CHOP), and Caspase-3) were significantly increased, but these levels were decreased after BBR treatment (p < 0.05). To further verify the inhibitory effect of BBR on CIRI-induced neuronal apoptosis, we added an endoplasmic reticulum-specific agonist and a PERK inhibitor to the treatment. BBR was shown to significantly inhibit the expression of apoptotic proteins induced by endoplasmic reticulum stress agonist, while the PERK inhibitor partially reversed the ability of BBR to inhibit apoptotic protein (p < 0.05). These results confirm that berberine may inhibit CIRI-induced neuronal apoptosis by downregulating the CNPY2 signaling pathway, thereby exerting a neuroprotective effect. [ABSTRACT FROM AUTHOR]

In the current shipping industry, quantitative measures of ship fuel consumption (SFC) have become one of the most important research topics in environmental protection and energy management related to shipping operations. In particular, the rapid development of sensor technologies enables multisource data collection to improve the modeling of the SFC problem. To address the features of such heterogeneous data, this paper proposes an integrated model for the estimation of SFC that includes three modules: a multisource data collection module, a heterogeneous data feature fusion module and a fuel consumption estimation module. First, in the data collection module, data related to SFC are collected by multiple sensors installed aboard the ship. Second, the feature fusion module employs a series of moving overlapped frames to merge different frequency data into small frames so that fusion features can be extracted from the heterogeneous data of multiple sources. Finally, in the fuel estimation module, the fusion features provide a novel way to consider the modeling and estimation of SFC as a classical time-series analysis using various machine learning techniques. Experimentally, linear regression (LR), support vector regression (SVR), and artificial neural network (ANN) were employed as the machine learning methods to train SFC models. Compared with the traditional feature extraction method, the accuracy of LR, SVR, and ANN were improved by 8.5, 0.35 and 51.5%, respectively, using the proposed method. The main contribution of this work is to consider the multisource and heterogeneous problem of sensor-based SFC data and propose an integrated model to extract the information of SFC data. Moreover, the experimental results showed that the estimation accuracy can be greatly improved. [ABSTRACT FROM AUTHOR]

Viral infection triggers the formation of mitochondrial antiviral signaling protein (MAVS) aggregates, which potently promote immune signaling. Autophagy plays an important role in controlling MAVS‐mediated antiviral signaling; however, the exact molecular mechanism underlying the targeted autophagic degradation of MAVS remains unclear. Here, we investigated the mechanism by which RNF34 regulates immunity and mitophagy by targeting MAVS. RNF34 binds to MAVS in the mitochondrial compartment after viral infection and negatively regulates RIG‐I‐like receptor (RLR)‐mediated antiviral immunity. Moreover, RNF34 catalyzes the K27‐/K29‐linked ubiquitination of MAVS at Lys 297, 311, 348, and 362 Arg, which serves as a recognition signal for NDP52‐dependent autophagic degradation. Specifically, RNF34 initiates the K63‐ to K27‐linked ubiquitination transition on MAVS primarily at Lys 311, which facilitates the autophagic degradation of MAVS upon RIG‐I stimulation. Notably, RNF34 is required for the clearance of damaged mitochondria upon viral infection. Thus, we elucidated the mechanism by which RNF34‐mediated autophagic degradation of MAVS regulates the innate immune response, mitochondrial homeostasis, and infection. Synopsis: Viral infection triggers the formation of mitochondrial antiviral signaling protein (MAVS) aggregates, which potently promote immune signaling. However, the exact molecular mechanism underlying the targeted autophagic degradation of MAVS remains unclear. Here, we investigated the mechanism by which RNF34 regulates immunity and mitophagy by targeting MAVS. RNF34 negatively regulates RIG‐I like receptor (RLR)‐mediated antiviral immunity.RNF34 catalyzes the K27/K29‐linked ubiquitination of MAVS at Lys 297, 311, 348, and 362.RNF34 initiates the K63‐ to K27‐linked ubiquitination transition on MAVS primarily at Lys 311.RNF34 facilitates the autophagic degradation of MAVS.RNF34 promotes NDP52‐dependent selective mitophagy. [ABSTRACT FROM AUTHOR]

Background: Acute liver failure (ALF) is a complicated clinical syndrome associated with high mortality, with liver transplantation as the only treatment option. Treatment of mesenchymal stem cells has shown a potential therapeutic option for acute liver failure. However, the lack of random clinical trials and large non-human primate studies makes it necessary to assess the efficacy and safety in the clinic. Methods: We treated the monkeys with peripheral delivery of human umbilical MSCs (hUC-MSCs) and investigated the role of hUC-MSCs in modulating the progress of acute liver failure. Results: The use of early peripheral infusion of human umbilical cord MSC infusion did not improve liver regeneration or modulate adaptive immunity. However, it significantly suppressed the hepatic aggregation and maturation of circulating monocytes and their IL-6 secretion, greatly improving liver histology, systemic homeostasis, and survival. Conclusions: Our study reveals the critical role of monocyte-derived IL-6 in initiating and accelerating acute liver failure and hUC-MSC treatment can disrupt the development of the inflammatory cascade by inhibiting monocyte activation. Early hUC-MSC treatment disrupts the development of the inflammatory cascade, indicating a potential clinical solution for acute liver failure. [ABSTRACT FROM AUTHOR]