BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy

Epilepsy is marked by hypersynchronous bursts of neuronal activity, and seizures can propagate variably to any and all areas, leading to brain network dynamic organization. However, the relationship between the network characteristics of scalp EEG and blood oxygenation level-dependent (BOLD) responses in epilepsy patients is still not well known. In this study, simultaneous EEG and fMRI data were acquired in 18 juvenile myoclonic epilepsy (JME) patients. Then, the adapted directed transfer function (ADTF) values between EEG electrodes were calculated to define the time-varying network. The variation of network information flow within sliding windows was used as a temporal regressor in fMRI analysis to predict the BOLD response. To investigate the EEG-dependent functional coupling among the responding regions, modulatory interactions were analyzed for network variation of scalp EEG and BOLD time courses. The results showed that BOLD activations associated with high network variation were mainly located in the thalamus, cerebellum, precuneus, inferior temporal lobe and sensorimotor-related areas, including the middle cingulate cortex (MCC), supplemental motor area (SMA), and paracentral lobule. BOLD deactivations associated with medium network variation were found in the frontal, parietal, and occipital areas. In addition, modulatory interaction analysis demonstrated predominantly directional negative modulation effects among the thalamus, cerebellum, frontal and sensorimotor-related areas. This study described a novel method to link BOLD response with simultaneous functional network organization of scalp EEG. These findings suggested the validity of predicting epileptic activity using functional connectivity variation between electrodes. The functional coupling among the thalamus, frontal regions, cerebellum and sensorimotor-related regions may be characteristically involved in epilepsy generation and propagation, which provides new insight into the pathophysiological mechanisms and intervene targets for JME

RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark

Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus images. Low-quality (LQ) degraded fundus images easily lead to uncertainty in clinical screening and generally increase the risk of misdiagnosis. Thus, real fundus image restoration is worth studying. Unfortunately, real clinical benchmark has not been explored for this task so far. In this paper, we investigate the real clinical fundus image restoration problem. Firstly, We establish a clinical dataset, Real Fundus (RF), including 120 low- and high-quality (HQ) image pairs. Then we propose a novel Transformer-based Generative Adversarial Network (RFormer) to restore the real degradation of clinical fundus images. The key component in our network is the Window-based Self-Attention Block (WSAB) which captures non-local self-similarity and long-range dependencies. To produce more visually pleasant results, a Transformer-based discriminator is introduced. Extensive experiments on our clinical benchmark show that the proposed RFormer significantly outperforms the state-of-the-art (SOTA) methods. In addition, experiments of downstream tasks such as vessel segmentation and optic disc/cup detection demonstrate that our proposed RFormer benefits clinical fundus image analysis and applications. The dataset, code, and models are publicly available at https://github.com/dengzhuo-AI/Real-FundusComment: IEEE J-BHI 2022; The First Benchmark and First Transformer-based Method for Real Clinical Fundus Image Restoratio

The Effect of the Antimicrobial Peptide Plectasin on the Growth Performance, Intestinal Health, and Immune Function of Yellow-Feathered Chickens

The goal of the study was to test the effects of an antibiotic substitute, plectasin, on the growth performance, immune function, intestinal morphology and structure, intestinal microflora, ileal mucosal layer construction and tight junctions, ileal immune-related cytokines, and blood biochemical indices of yellow-feathered chickens. A total of 1,500 one-day-old yellow-feathered chicks were randomly divided into four dietary treatment groups with five replicates in each group and 75 yellow-feathered chicks in each replication, as follows: basal diet (group A); basal diet supplemented with 10 mg enramycin/kg of diet (group B), basal diet supplemented with 100 mg plectasin/kg of diet (group C), and basal diet supplemented with 200 mg plectasin/kg of diet (group D). It was found that the dietary antimicrobial peptide plectasin could improve the ADG and had better F/G for the overall period of 1–63 days. Dietary plectasin can enhance H9N2 avian influenza virus (AIV) and Newcastle disease virus (NDV) antibody levels of yellow-feathered chickens at 21, and 35 days of age. Dietary plectasin can enhance the intestine structure, inhibit Escherichia coli and proinflammatory cytokines in the ileum, and ameliorate the blood biochemical indices of yellow-feathered chickens at 21 days of age. This study indicates that the antimicrobial peptide plectasin has beneficial effects on the growth performance, intestinal health and immune function of yellow-feathered chickens

Enhanced B7-H4 expression in gliomas with low PD-L1 expression identifies super-cold tumors.

BACKGROUND: Characterizing expression profiles of different immune checkpoint molecules are promising for personalized checkpoint inhibitory immunotherapy. Gliomas have been shown as potential targets for immune checkpoint inhibitors recently. Our study was performed to determine coexpression levels of two major B7 immune regulatory molecules programmed death ligand 1 (PD-L1) and B7-H4, both of which have been demonstrated to inhibit antitumor host immunity in gliomas. METHODS: We assessed tumor tissues from stage II-IV primary gliomas (n=505) by immunohistochemistry (IHC) for protein levels of both PD-L1 and B7-H4. Gene coexpression analysis assessing clusters based on extent of PD-L1/B7-H4 classifier genes expression were investigated in two transcriptome datasets (The Cancer Genome Atlas and Chinese Glioma Genome Atlas). In addition, levels of immune cell infiltrates were estimated with IHC and RNA-seq data for assessing the tumor immune microenvironment of PD-L1/B7-H4 subgroups. RESULTS: High expression of PD-L1 and B7-H4 in gliomas was 23% and 20%, respectively, whereas coexpression of two proteins at high levels was limited to 2% of the cases. Comparable results were seen in RNA-seq datasets where PD-L1 mRNA expression levels negatively correlated with that of B7-H4. Gene coexpression modules clustered within each grade of gliomas demonstrated lack of double-high modules (cluster with high expression of both PD-L1 and B7-H4 classifier genes). B7-H4 mRNA expression levels showed negative correlation with extent of immune cell infiltration and High-B7-H4 module gliomas (high B7-H4 but low PD-L1 classifier genes expression) had less tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs). IHC assessment also showed few TILs and TAMs in High-B7-H4 subgroup gliomas. CONCLUSIONS: The majority of gliomas express PD-L1 or B7-H4, however, coexpression of both at high levels is minimal. The high-B7-H4 patients could be considered as \u27super-cold\u27 gliomas with significantly deficient in TILs, suggesting that B7-H4 might inhibit T-cell trafficking into the central nervous system. This study demonstrated that PD-L1 and B7-H4 may serve as mutually compensatory immune checkpoint molecules in gliomas for immune targeted or active-specific immunotherapy. The distinct B7-H4 pathways modulating T-cell function and immune evasion in glioma patients deserved to be further explored in the future during immunotherapy

Peripheral Lung Squamous Carcinoma With ROS1 Rearrangement Sensitive to Crizotinib: A Case Report

ROS1 rearrangements have been identified as driver mutations, accounting for 1–2% of lung adenocarcinoma, but are extremely rare in case of lung squamous cell carcinoma. In this work, we report a lung squamous cell carcinoma in a patient with peripheral lung cancer radiological manifestation, harboring ROS1 rearrangement, with high sensitivity to crizotinib. Our findings suggest that clinicians should pay more attention toward the occurrence of ROS1 rearrangements and the application of crizotinib for lung squamous cell carcinoma treatment

Managing AI Risks in an Era of Rapid Progress

In this short consensus paper, we outline risks from upcoming, advanced AI systems. We examine large-scale social harms and malicious uses, as well as an irreversible loss of human control over autonomous AI systems. In light of rapid and continuing AI progress, we propose urgent priorities for AI R&D and governance

Managing extreme AI risks amid rapid progress

Preparation requires technical research and development, as well as adaptive, proactive governance

Wide‐bandwidth nanocomposite‐sensor integrated smart mask for tracking multiphase respiratory activities

Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID-19) even in its coming endemic phase. Therefore, deploying a “smart mask” to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure-based soundwave sensor (≈400 µm), which allows the high sensitivity in a wide-bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty-one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro-recalls of ≈95% in both individual and generalized models. With rich high-frequency (≈4000 Hz) information recorded, the two-/tri-phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life

Preparation of N-Doped Layered Porous Carbon and Its Capacitive Deionization Performance

In this study, N-doped layered porous carbon prepared by the high-temperature solid-state method is used as electrode material. Nano calcium carbonate (CaCO3) (40 nm diameter) is used as the hard template, sucrose (C12H22O11) as the carbon source, and melamine (C3H6N6) as the nitrogen source. The materials prepared at 850 °C, 750 °C, and 650 °C are compared with YP-50F commercial super-activated carbon from Japan Kuraray Company. The electrode material at 850 °C pyrolysis temperature has a higher specific surface area and more pores suitable for ion adsorption. Due to these advantages, the salt adsorption capacity (SAC) of the N-doped layered porous carbon at 850 °C reached 12.56 mg/g at 1.2 V applied DC voltage, 500 mg/L initial solution concentration, and 15 mL/min inlet solution flow rate, which is better than the commercial super activated carbon as a comparison. In addition, it will be demonstrated that the N-doped layered porous carbon at 850 °C has a high salt adsorption capacity CDI performance than YP-50F by studying parameters with different applied voltages and flow rates as well as solution concentrations