Clustered surface amino acid residues modulate the acid stability of GH10 xylanase in fungi.

Acidic xylanases are widely used in industries such as biofuels, animal feeding, and fruit juice clarification due to their tolerance to acidic environments. However, the factors controlling their acid stability, especially in GH10 xylanases, are only partially understood. In this study, we identified a series of thermostable GH10 xylanases with optimal temperatures ranging from 70 to 90 °C, and among these, five enzymes (Xyn10C, Xyn10RE, Xyn10TC, Xyn10BS, and Xyn10PC) exhibited remarkable stability at pH 2.0. Our statistical analysis highlighted several factors contributing to the acid stability of GH10 xylanases, including electrostatic repulsion, π-π stacking, ionic bonds, hydrogen bonds, and Van der Waals interactions. Furthermore, through mutagenesis studies, we uncovered that acid stability is influenced by a complex interplay of amino acid residues. The key amino acid sites determining the acid stability of GH10 xylanases were thus elucidated, mainly concentrated in two surface regions behind the enzyme active center. Notably, the critical residues associated with acid stability markedly enhanced Xyn10RE's thermostability by more than sixfold, indicating a potential acid-thermal interplay in GH10 xylanases. This study not only reported a series of valuable genes but also provided a range of modification targets for enhancing the acid stability of GH10 xylanases. KEY POINTS: • Five acid stable and thermostable GH10 xylanases were reported. • The key amino acid sites, mainly forming two enriched surface regions behind the enzyme active center, were identified responsible for acid stability of GH10 xylanases. • The finding revealed interactive amino acid sites, offering a pathway for synergistic enhancement of both acid stability and thermostability in GH10 xylanase modifications.

The STING-mediated antiviral effect of fucoidan from Durvillaea antarctica.

Fucoidans have attracted increasing attention due to their minimal toxicity and various biological activities, such as antioxidant, anti-inflammatory, anti-tumor and immunomodulatory effects. In this study, the antiviral effect and mechanism of fucoidan (FU) derived from Durvillaea antarctica were explored in vitro. The results demonstrated that FU effectively inhibited the infection of both RNA virus (VSV) and DNA virus (HSV-1). The potential antiviral mechanism of FU is to trigger the production of type I IFN (IFN-I) and IFN-stimulated genes dependent on the cytoplasmic DNA adaptor STING (stimulator of interferon genes), and to enhance innate immune response via activating the STING-TBK1-IRF3 pathway. FU possesses the potential to be an antiviral and immunomodulatory agent in the future.

Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer.

BACKGROUND: Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. METHODS: Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). RESULTS: The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells. CONCLUSIONS: These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma.

The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.

Brain Topology Modeling With EEG-Graphs for Auditory Spatial Attention Detection.

OBJECTIVE: Despite recent advances, the decoding of auditory attention from brain signals remains a challenge. A key solution is the extraction of discriminative features from high-dimensional data, such as multi-channel electroencephalography (EEG). However, to our knowledge, topological relationships between individual channels have not yet been considered in any study. In this work, we introduced a novel architecture that exploits the topology of the human brain to perform auditory spatial attention detection (ASAD) from EEG signals. METHODS: We propose EEG-Graph Net, an EEG-graph convolutional network, which employs a neural attention mechanism. This mechanism models the topology of the human brain in terms of the spatial pattern of EEG signals as a graph. In the EEG-Graph, each EEG channel is represented by a node, while the relationship between two EEG channels is represented by an edge between the respective nodes. The convolutional network takes the multi-channel EEG signals as a time series of EEG-graphs and learns the node and edge weights from the contribution of the EEG signals to the ASAD task. The proposed architecture supports the interpretation of the experimental results by data visualization. RESULTS: We conducted experiments on two publicly available databases. The experimental results showed that EEG-Graph Net significantly outperforms the state-of-the-art methods in terms of decoding performance. In addition, the analysis of the learned weight patterns provides insights into the processing of continuous speech in the brain and confirms findings from neuroscientific studies. CONCLUSION: We showed that modeling brain topology with EEG-graphs yields highly competitive results for auditory spatial attention detection. SIGNIFICANCE: The proposed EEG-Graph Net is more lightweight and accurate than competing baselines and provides explanations for the results. Also, the architecture can be easily transferred to other brain-computer interface (BCI) tasks.

RGCnet: An Efficient Recursive Gated Convolutional Network for EEG-based Auditory Attention Detection.

Humans are able to listen to one speaker and disregard others in a speaking crowd, referred to as the "cocktail party effect". EEG-based auditory attention detection (AAD) seeks to identify whom a listener is listening to by decoding one's EEG signals. Recent research has demonstrated that the self-attention mechanism is effective for AAD. In this paper, we present the Recursive Gated Convolutional network (RGCnet) for AAD, which implements long-range and high-order interactions as a self-attention mechanism, while maintaining a low computational cost. The RGCnet expands the 2nd order feature interactions to a higher order to model the complex interactions between EEG features. We evaluate RGCnet on two public datasets and compare it with other AAD models. Our results demonstrate that RGCnet outperforms other comparative models under various conditions, thus potentially improving the control of neuro-steered hearing devices.

Natural recombination of the torque teno canis virus within the ORF1, -2, and -3 genes and the untranslated region.

The torque teno canis virus (TTCaV) was first reported in 2001 and it shares similarities with the known Torque teno virus (TTV) in terms of genomic organization and putative transcriptional features. It is a single-stranded DNA virus characterized by high rates of recombination and nucleotide substitution, like RNA viruses. Studies reported recombination events in torque teno virus; however, there is limited reporting of TTCaV reorganization events. This study screened fecal samples from domestic dogs in Henan Province. There was a positivity rate of 16.5% (19/115) for TTCaV. Four nearly complete TTCaV genomes, namely Canine/HeNan/4, 5, 6, and 13/2019, were obtained from the 19 positive fecal samples, whose genome sequence was obtained using gap-filling PCR. Sequence analysis revealed two unique amino acid mutation sites in the TTCaV strains, K278Q (compared with the first isolate Cf-TTV10 in Japan) and V/L268I (compared with the TTCaV strain from southern China). Subsequently, 17 near full-length TTCaV genome sequences were subjected to phylogenetic and recombination detection program analyzes. We obtained evidence supporting recombination events in the Chinese TTCaV strains. These findings suggest that mutation and recombination occurred in the three individual gene segments (ORF1, ORF2, ORF3) and the untranslated region, an area of major recombination in the Chinese TTCaV strain GX265 genome. Interestingly, the TTCaV strain (Canine/HeNan/6/2019) was a major parent involved in the genetic recombination of the GX265 strain. This study provides insights into the genetic variability and evolution of TTCaV.

A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain.

Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention from the brain signals is a major step toward the development of bionic ears emulating human capabilities. Electroencephalography (EEG)-based auditory attention detection (AAD) has attracted considerable interest recently. Despite much progress, the performance of traditional AAD decoders remains to be improved, especially in low-latency settings. State-of-the-art AAD decoders based on deep neural networks generally lack the intrinsic temporal coding ability in biological networks. In this study, we first propose a bio-inspired spiking attentional neural network, denoted as BSAnet, for decoding auditory attention. BSAnet is capable of exploiting the temporal dynamics of EEG signals using biologically plausible neurons and an attentional mechanism. Experiments on two publicly available datasets confirm the superior performance of BSAnet over other state-of-the-art systems across various evaluation conditions. Moreover, BSAnet imitates realistic brain-like information processing, through which we show the advantage of brain-inspired computational models.

Functional Connectivity of White Matter and Its Association with Sleep Quality.

Purpose: Functional magnetic resonance imaging (fMRI) has been widely adopted to investigate the neural activity in gray matter (GM) in the field of sleep research, but the neural activity in white matter (WM) has received much less attention. The current study set out to test our hypothesis that WM functional abnormality is associated with poor sleep quality. Participants and Methods: K-means clustering analysis was performed on 78 healthy adults drawn from the Human Connectome Project dataset to extract stable WM functional networks (WM-FNs) and GM-FNs. The differences in functional connectivity within WM-FNs and between WM- and GM-FNs, as well as the power spectrum between good sleep quality group (Pittsburgh Sleep Quality Index (PSQI) <6, daytime dysfunction = 0) and poor sleep quality group (PSQI >6, daytime dysfunction >0) were examined between groups with good and poor sleep quality. Additionally, linear relationships between sleep quality and altered functional characteristics of WM-FNs were evaluated. Results: Functional connectivity between middle and superficial WM-FNs, short- and long-range functional connectivity between WM- and GM-FNs were decreased in poor sleepers and negatively correlated with PSQI score. The mean amplitudes of right sensorimotor WM networks at whole, high and low frequency bands were higher in poor sleepers and were positively correlated with PSQI score. Conclusion: WM functional abnormality is associated with poor sleep quality. The neurobiological mechanisms that underlie the functional alterations of WM-FNs in poor sleepers need to be investigated in future studies.

Functional status and spatial architecture of tumor-infiltrating CD8+ T cells are associated with lymph node metastases in non-small cell lung cancer.

BACKGROUND: Anti-PD-(L)1 immunotherapy has been recommended for non-small cell lung cancer (NSCLC) patients with lymph node metastases (LNM). However, the exact functional feature and spatial architecture of tumor-infiltrating CD8 + T cells remain unclear in these patients. METHODS: Tissue microarrays (TMAs) from 279 IA-IIIB NSCLC samples were stained by multiplex immunofluorescence (mIF) for 11 markers (CD8, CD103, PD-1, Tim3, GZMB, CD4, Foxp3, CD31, αSMA, Hif-1α, pan-CK). We evaluated the density of CD8 + T-cell functional subsets, the mean nearest neighbor distance (mNND) between CD8 + T cells and neighboring cells, and the cancer-cell proximity score (CCPS) in invasive margin (IM) as well as tumor center (TC) to investigate their relationships with LNM and prognosis. RESULTS: The densities of CD8 + T-cell functional subsets, including predysfunctional CD8 + T cells (Tpredys) and dysfunctional CD8 + T cells (Tdys), in IM predominated over those in TC (P < 0.001). Multivariate analysis identified that the densities of CD8 + Tpredys cells in TC and CD8 + Tdys cells in IM were significantly associated with LNM [OR = 0.51, 95%CI (0.29-0.88), P = 0.015; OR = 5.80, 95%CI (3.19-10.54), P < 0.001; respectively] and recurrence-free survival (RFS) [HR = 0.55, 95%CI (0.34-0.89), P = 0.014; HR = 2.49, 95%CI (1.60-4.13), P = 0.012; respectively], independent of clinicopathological factors. Additionally, shorter mNND between CD8 + T cells and their neighboring immunoregulatory cells indicated a stronger interplay network in the microenvironment of NSCLC patients with LNM and was associated with worse prognosis. Furthermore, analysis of CCPS suggested that cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) selectively hindered CD8 + T cells from contacting with cancer cells, and were associated with the dysfunction of CD8 + T cells. CONCLUSION: Tumor-infiltrating CD8 + T cells were in a more dysfunctional status and in a more immunosuppressive microenvironment in patients with LNM compared with those without LNM.

RNAi-mediated CrebA silencing inhibits reproduction and immunity in Locusta migratoria manilensis.

Locusta migratoria manilensis is a major agricultural pest that causes severe direct and indirect damage to several crops. Thus, to provide a theoretical foundation for pest control, the role of CrebA in the reproduction and immune regulation of L. migratoria was investigated. CrebA is a bZIP transcription factor that critically regulates intracellular protein secretion. In this study, CrebA was widely expressed in the brain, fat body, integument, midgut, and reproductive tissues of different maturity stages of adult locusts, especially in the female fat body. RNA interfering (RNAi)-mediated silencing of CrebA inhibited locusts ovarian development, and key reproduction gene expressions, Vgs, VgRs, Chico, and JHAMT were downregulated. After the locusts were injected with Micrococcus luteus or Escherichia coli, M. luteus activated lysozyme expression, while the E. coli activated both phenol oxidase cascade and lysozyme expression. Furthermore, both bacteria stimulated the upregulation of the antimicrobial peptide genes DEF3 and DEF4. However, CrebA silencing is fatal to locusts infection with E. coli, with a mortality rate of up to 96.3%, and resulted in a significant decrease in the expression of DEF3 and DEF4 and changes in the activities of phenol oxidase and lysozyme of locusts infected by bacteria. Collectively, CrebA may be involved in diverse biological processes, including reproduction and immunity. CrebA inhibited locusts reproduction by regulating JH signaling pathway and inhibits the expression of immune genes TLR6, IMD, and AMPs. These results demonstrate CrebA seems to play a crucial role in reproduction and innate immunity.

The role of spatial interplay patterns between PD-L1-positive tumor cell and T cell in recurrence of locally advanced non-small cell lung cancer.

PURPOSE: To explore the relationship between the spatial interaction of programmed death-ligand 1(PD-L1)-positive tumor cell and T cell with specific functions and the recurrence of non-small cell lung cancer (NSCLC) and optimize prognostic stratification. MATERIALS AND METHODS: This study retrospectively included 104 patients with locally advanced NSCLC who underwent radical surgery. Tissue microarrays were constructed including tumor center (TC) and invasion margin (IM), and CK/CD4/CD8/PD-L1/programmed death-1 (PD-1) was labeled using multiplex immunofluorescence to decipher the counts and spatial distribution of tumor cells and T cells. The immune microenvironment and recurrence stratification were characterized using the Mann-Whitney U test and Cox proportional hazards model. RESULT: Compared with the IM, the proportion of tumor cells (especially PD-L1+) was increased in the TC, while T cells (especially PD-1+) were decreased. An increase in TC PD-1+ CD8 T cells promoted relapse (HR = 2.183), while PD-L1+ tumor cells alone or in combination with T cells had no predictive value for relapse. In addition, in both TC and IM, CD8 were on average closer to PD-L1+ tumor cells than CD4, especially exhausted CD8. The effective density and percentage of PD-1+ CD4 T cells interacting with PD-L1+ tumor cells in the IM were both associated with recurrence, and the HRs increased sequentially (HRs were 2.809 and 4.063, respectively). Patients with low PD-1+CD4 count combined high PD-1+CD4 effective density showed significantly poorer RFS compared to those with high PD-1+CD4 count combined low PD-1+CD4 effective density, in both the TC and IM regions (HRs were 5.810 and 8.709, respectively). CONCLUSION: Assessing the relative spatial proximity of PD-1/PD-L1 contributes to a deeper understanding of tumor immune escape and generates prognostic information in locally advanced NSCLC patients.

Identification of Two Isoforms of Canine Tetherin in Domestic Dogs and Characterization of Their Antiviral Activity against Canine Influenza Virus.

Canine influenza virus (CIV) significantly threatens the canine population and public health. Tetherin, an innate immune factor, plays an important role in the defense against pathogen invasion and has been discovered to restrict the release of various enveloped viruses. Two isoforms of canine tetherin (tetherin-X1 and tetherin-X2) were identified in peripheral blood leukocytes of mixed-breed dogs using reverse transcription polymerase chain reaction (RT-PCR). Amino acid alignment revealed that relative to full-length tetherin (tetherin-X1) and truncated canine tetherin (tetherin-X2) exhibited deletion of 34 amino acids. The deletion occurred at the C-terminus of the coiled-coiled ectodomain and the N-terminus of the glycosylphosphatidylinositol (GPI)-anchor domain. Tetherin-X2 was localized subcellularly at the cell membrane, which was consistent with the localization of tetherin-X1. In addition, canine tetherin-X1 and tetherin-X2 restricted the release of H3N2 CIV. However, canine tetherin-X1 had higher antiviral activity than canine tetherin-X2, indicating that the C-terminus of the coiled-coiled ectodomain and the N-terminus of the GPI-anchor domain of canine tetherin (containing the amino acids deleted in tetherin-X2) are critical for its ability to restrict H3N2 CIV release. This study provides insights for understanding the key functional domains of tetherin that restrict CIV release.

P130cas-FAK interaction is essential for YAP-mediated radioresistance of non-small cell lung cancer.

Based on the RNA-sequencing data, previous studies revealed that extracellular matrix receptor interaction and focal adhesion signaling pathways were enriched in radioresistant non-small cell lung cancer (NSCLC) cell lines. As the principal members of these signaling pathways, recent studies showed that FAK controlled YAP's nuclear translocation and activation in response to mechanical activation. However, the underlying mechanisms are largely unknown. This study was designed to determine whether P130cas plays a role in FAK-YAP axis-mediated radioresistance. We found that P130cas promoted proliferation, altered the cell cycle profile, and enhanced tumor growth using cell lines and xenograft mouse models. After treating the cell lines and xenograft models with a single dose of 5 Gy irradiation, we observed that P130cas effectively induced radioresistance in vitro and in vivo. We confirmed that P130cas interacted with and promoted YAP stabilization, thereby facilitating YAP's activation and nuclear translocation and downregulating the radiosensitivity of NSCLC. Our data also revealed that P130cas and FAK directly interacted with each other and worked together to regulate YAP's activation and nuclear translocation. Furthermore, the present study identified that P130cas, FAK and YAP formed a triple complex to induce radioresistance. Using P130cas-ΔSH3, FAK- P712/715A mutant, YAP-ΔSH3bm and YAP-ΔWW mutant, our results showed that targeting P130cas-FAK interaction may be a more cost-effective way to overcome the YAP activation mediated radioresistance in NSCLC. Using the data of the public database and our clinical samples, the present study suggested that the expression of P130cas correlated with YAP expression and indicated a poor overall response rate of NSCLC patients who underwent radiation therapy. Overall, our study extends the knowledge of FAK-YAP interaction and provides new insight into understanding the underlying mechanisms to overcome the radioresistance of NSCLC.

A neuroscience-inspired spiking neural network for EEG-based auditory spatial attention detection.

Recent studies have shown that alpha oscillations (8-13 Hz) enable the decoding of auditory spatial attention. Inspired by sparse coding in cortical neurons, we propose a spiking neural network model for auditory spatial attention detection. The proposed model can extract the patterns of recorded EEG of leftward and rightward attention, independently, and uses them to train the network to detect auditory spatial attention. Specifically, our model is composed of three layers, two of which are Integrate and Fire spiking neurons. We formulate a new learning rule that is based on the firing rate of pre- and post-synaptic neurons in the first and second layers of spiking neurons. The third layer has 10 spiking neurons and the pattern of their firing rate is used in the test phase to decode the auditory spatial attention of a given test sample. Moreover, the effects of using low connectivity rates of the layers and specific range of learning parameters of the learning rule are investigated. The proposed model achieves an average accuracy of 90% with only 10% of EEG signals as training data. This study also provides new insights into the role of sparse coding in both cortical networks subserving cognitive tasks and brain-inspired machine learning.

Identification and genetic characterization of bovine hepacivirus in China: A large scale epidemiological study.

Bovine hepacivirus (BovHepV) is a novel virus that was recently discovered in Ghana and Germany in 2015. Until now, this virus has been identified in cattle population worldwide and is classified into subtypes A-G. To fully understand the epidemic situation and genetic characteristic of BovHepV in China, a total of 612 cattle serum samples were collected from 20 farms in seven provinces and municipality in China between 2018 and 2020 and were tested for the presence of BovHepV RNA via semi-nested PCR. The results demonstrated that 49 (8.0%) samples were BovHepV RNA-positive. It is noted that BovHepV infection in yak was confirmed for the first time. BovHepV was detected in all the seven provinces, with the positive rate ranging from 3.1% to 13.3%, which indicates a wide geographical distribution pattern of BovHepV in China. Sequencing results revealed that 5' UTR of the 49 field BovHepV strains have a nucleotide similarity of 96.3%-100% between each other and 93.9%-100% with previously reported BovHepV strains. In addition, genetic analysis identified five critical nucleotide sites in 5' UTR to distinguish different subtypes, which was further verified by genomic sequencing and nucleotide similarity analysis. All the 49 Chinese field BovHepV strains were classified into subtype G and this subtype is only determined in cattle in China currently. This study will provide insights for us to better understand the epidemiology and genetic diversity of BovHepV.

Swine Interferon-Inducible Transmembrane Proteins Potently Inhibit African Swine Fever Virus Replication.

African swine fever virus (ASFV) causes an acute, hemorrhagic, and highly contagious disease in domestic swine, leading to significant economic losses to the global porcine industry. Restriction factors of innate immunity play a critical in host antiviral action. However, function of swine restriction factors of innate immunity on ASFV has been seldomly investigated. In this study, we determined five homologues of swine interferon-induced transmembrane proteins (SwIFITM [named SwIFITM1a, -1b, -2, -3, and -5]), and we found that they all exhibit potent antiviral activity against ASFV. Expression profile analysis indicated that these SwIFITMs are constitutively expressed in most porcine tissues. Whether infected with ASFV or treated with swine interferon, the expression levels of SwIFITMs were induced in vitro. The subcellular localization of SwIFITMs was similar to that of their human homologues. SwIFITM1a and -1b localized to the plasma membrane, SwIFITM2 and -3 focused on the cytoplasm and the perinuclear region, while SwIFITM5 accumulated in the cell surface and cytoplasm. The overexpression of SwIFITM1a, -1b, -2, -3, or -5 could significantly inhibit ASFV replication in Vero cells, whereas knockdown of these genes could enhance ASFV replication in PAMs. We blocked the constitutive expression of endogenous IFITMs in Vero cells using a CRISPR-Cas9 system and then infected them with ASFV. The results indicated that the knockout of endogenous IFITMs could enhance ASFV replication. Finally, we expressed five SwIFITMs in knockout Vero cell lines and then challenged them with ASFV. The results showed that all of the SwIFITMs had a strong antiviral effect on ASFV. This research will further expand the understanding of the anti-ASFV activity of porcine IFITMs.

Cerebrovascular Dysregulation in Patients with Glioma Assessed with Time-shifted BOLD fMRI.

Background Microscopic vascular events, such as neovascularization and neurovascular uncoupling, are common in cerebral glioma. Mapping the cerebrovascular network remodeling at the macroscopic level may provide an alternative approach to assess hemodynamic dysregulation in patients with glioma. Purpose To investigate cerebrovascular dynamics and their relevance to tumor aggressiveness by using time-shift analysis (TSA) of the systemic low-frequency oscillation (sLFO) of the resting-state blood oxygenation level-dependent signal and a decision tree model. Materials and Methods In this retrospective study, 96 patients with histologically confirmed cerebral glioma were consecutively included (March 2012 to February 2017). TSA was performed to quantify the temporal properties of sLFO signals. Alteration in the time-shift properties was assessed in the tumor region and the contralesional hemisphere relative to the brains of healthy controls by using the Mann-Whitney U test. A decision tree model based on time-shift features was developed to predict the World Health Organization (WHO) glioma grade. Results A total of 88 patients with glioma (WHO grade II, 45; grade III, 21; grade IV, 22; mean age, 42 years; age range, 20-73 years; 51 men) and 40 healthy individuals from the 1000 Functional Connectomes Project (mean age, 32 years; age range, 24-49 years; 19 men) were included. The sLFO of the brain tissues was characterized by increased time shift in the tumor region and enhanced correlation with the global reference signal in the contralesional hemisphere compared with healthy brains. The proportion of tumor voxels with negative correlation to the reference signal significantly increased with the glioma malignancy grade. The decision tree model achieved an accuracy of 91% (80 of 88 patients) in predicting the glioma malignancy grade at the individual level (P = .004) based on the time-shift features. Conclusion Gliomas induced grade-specific cerebrovascular dysregulation in the entire brain, with altered time-shift features of systemic low-frequency oscillation signals. © RSNA, 2022 Online supplemental material is available for this article.

STAnet: A Spatiotemporal Attention Network for Decoding Auditory Spatial Attention From EEG.

OBJECTIVE: Humans are able to localize the source of a sound. This enables them to direct attention to a particular speaker in a cocktail party. Psycho-acoustic studies show that the sensory cortices of the human brain respond to the location of sound sources differently, and the auditory attention itself is a dynamic and temporally based brain activity. In this work, we seek to build a computational model which uses both spatial and temporal information manifested in EEG signals for auditory spatial attention detection (ASAD). METHODS: We propose an end-to-end spatiotemporal attention network, denoted as STAnet, to detect auditory spatial attention from EEG. The STAnet is designed to assign differentiated weights dynamically to EEG channels through a spatial attention mechanism, and to temporal patterns in EEG signals through a temporal attention mechanism. RESULTS: We report the ASAD experiments on two publicly available datasets. The STAnet outperforms other competitive models by a large margin under various experimental conditions. Its attention decision for 1-second decision window outperforms that of the state-of-the-art techniques for 10-second decision window. Experimental results also demonstrate that the STAnet achieves competitive performance on EEG signals ranging from 64 to as few as 16 channels. CONCLUSION: This study provides evidence suggesting that efficient low-density EEG online decoding is within reach. SIGNIFICANCE: This study also marks an important step towards the practical implementation of ASAD in real life applications.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer.

Background: The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis. Methods: We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests. Results: In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s. Conclusions: In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.