Microstructure and Bioactivity of Ca- and Mg-Modified Silicon Oxycarbide-Based Amorphous Ceramics.

Silicon oxycarbide (SiOC), Ca- and Mg-modified silicon oxycarbide (SiCaOC and SiMgOC) were synthesized via sol-gel processing with subsequent pyrolysis in an inert gas atmosphere. The physicochemical structures of the materials were characterized by XRD, SEM, FTIR, and Si MAS NMR. Biocompatibility and in vitro bioactivity were detected by MTT, cell adhesion assay, and simulated body fluid (SBF) immersion test.

Novel Optical Modulator Photonic Device Based on TiN/TiC Heterojunction.

Due to the ability of optical modulators to achieve rapid modulation of optical signals, meeting the demands of high-speed data transmission, modulators based on different novel nanomaterials have become one of the research hotspots over the past dacade. Recently, TiN/TiC heterojunction exhibits highly efficient thermo-optic performance and extremely strong stability. Therefore, we have demonstrated an all-optical modulator based on the principle of Michelson interference and the thermo-optic effect in this paper.

The Association Between Surgery and Mild Cognitive Impairment: Insight from a Case-Control Study.

Background: Surgery may be associated with postoperative cognitive impairment in elder participants, yet the extent of its association with mild cognitive impairment (MCI) remains undetermined.

Objective: To determine the relationship between surgery and MCI.

Methods: The data of participants from the Alzheimer's Disease Neuroimaging Initiative were analyzed, including individuals with MCI or normal cognition.

Astrocyte atrophy induced by L-PGDS/PGD2/Src signaling dysfunction in the central amygdala mediates postpartum depression.

Background: Postpartum depression (PPD) is a serious psychiatric disorder that has significantly adverse impacts on maternal health. Metabolic abnormalities in the brain are associated with numerous neurological disorders, yet the specific metabolic signaling pathways and brain regions involved in PPD remain unelucidated.

Methods: We performed behavioral test in the virgin and postpartum mice.

Attack-resilient fault detection for interconnected systems under DoS attack.

In light of the expanding cyber-space applications, the imperative consideration of cyber-attack ramifications on system security is evident. This paper presents a resilient dynamic event-triggered fault detection scheme for a class of nonlinear interconnected systems subjected to denial of service (DoS) attacks. To counteract multifaceted threats, the co-design challenge involving switched-type fault detection filters and a resilient dynamic event-triggered transmission mechanism is addressed.

Nomogram to predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection.

Objective: To construct and validate nomogram models that predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection.

Methods: Elderly patients (≥65y) tested positive for SARS-CoV-2 infection at the hospital were included. We used the 3-min diagnostic Confusion Assessment Method for delirium diagnosis.

Identification of potential hub genes linked to immune and metabolic alterations in postoperative systemic inflammatory dysregulation.

Background: Postoperative systemic inflammatory dysregulation (PSID) is characterised by strongly interlinked immune and metabolic abnormalities. However, the hub genes responsible for the interconnections between these two systemic alterations remain to be identified.

Methods: We analysed differentially expressed genes (DEGs) of individual peripheral blood nucleated cells in patients with PSID (n = 21, CRP > 250 mg/L) and control patients (n = 25, CRP < 75 mg/L) following major abdominal surgery, along with their biological functions.

Potential CSF biomarkers of postpartum depression following delivery via caesarian section.

Background: Postpartum depression (PPD), the depressive episodes following delivery, is a serious and frequent psychiatric disorder. While numerous screening tools existed for depressive episodes, e.g.

FDNet: An end-to-end fusion decomposition network for infrared and visible images.

Infrared and visible image fusion can generate a fusion image with clear texture and prominent goals under extreme conditions. This capability is important for all-day climate detection and other tasks. However, most existing fusion methods for extracting features from infrared and visible images are based on convolutional neural networks (CNNs).

TiN/TiC heterojunction-based photonic device for optical Kerr switch.

As one of the new nanomaterials, TiN/TiC shows excellent optoelectronic characteristics, thus it has been widely used in many applications, such as biomedicine, optical sensors, image processing, and optical switching. With the advancement of communication capabilities and communication networks, optical fiber communication has put a higher demand on signal processing. In order to overcome the limitations of the electronic transfer rate bottleneck, the concept of all-optical signal processing has been proposed.

Alterations in smell or taste in individuals infected with SARS-CoV-2 during periods of Omicron variant dominance.

Objectives: To characterize the prevalence, severity, correlation with initial symptoms, and role of vaccination in patients with COVID-19 with smell or taste alterations (STAs).

Methods: We conducted an observational study of patients infected with SARS-CoV-2 Omicron admitted to three hospitals between May 17 and June 16, 2022. The olfactory and gustatory functions were evaluated using the taste and smell survey and the numerical visual analog scale at two time points.

Aspect-Aware Graph Attention Network for Heterogeneous Information Networks.

Graph Convolutional Networks (GCNs) derive inspiration from recent advances in computer vision, by stacking layers of first-order filters followed by a nonlinear activation function to learn entity or graph embeddings. Although GCNs have been shown to boost the performance of many network analysis tasks, they still face tremendous challenges in learning from Heterogeneous Information Networks (HINs), where relations play a decisive role in knowledge reasoning. What's more, there are multiaspect representations of entities in HINs, and a filter learned in one aspect do not necessarily apply to another.

Growth modes of single-walled carbon nanotubes on catalysts.

Understanding the growth mechanism of single-walled carbon nanotubes (SWCNTs) and achieving selective growth requires insights into the catalyst structure-function relationship. Using an in situ aberration-corrected environmental transmission electron microscope, we reveal the effects of the state and structure of catalysts on the growth modes of SWCNTs. SWCNTs grown from molten catalysts via a vapor-liquid-solid process generally present similar diameters to those of the catalysts, indicating a size correlation between nanotubes and catalysts.

Nanoantidote for repression of acidosis pH promoting COVID-19 infection.

Acidosis, such as respiratory acidosis and metabolic acidosis, can be induced by coronavirus disease 2019 (COVID-19) infection and is associated with increased mortality in critically ill COVID-19 patients. It remains unclear whether acidosis further promotes SARS-CoV-2 infection in patients, making virus removal difficult. For antacid therapy, sodium bicarbonate poses great risks caused by sodium overload, bicarbonate side effects, and hypocalcemia.

Fentanyl induces autism-like behaviours in mice by hypermethylation of the glutamate receptor gene Grin2b.

Background: Environmental factors contribute to autism spectrum disorder. Fentanyl, one of the most widely used opioid analgesics in anaesthesia, can induce neurotoxicity, but its role in autism remains unknown. We determined whether fentanyl induced autism-like behaviours in young mice and the underlying mechanisms.

Corrigendum: ATPase Inhibitory Factor 1 Is Critical for Regulating Sevoflurane-Induced Microglial Inflammatory Responses and Caspase-3 Activation.

[This corrects the article DOI: 10.3389/fncel.2021.

Secure predictor-based neural dynamic surface control of nonlinear cyber-physical systems against sensor and actuator attacks.

This paper addresses a secure predictor-based neural dynamic surface control (SPNDSC) issue for a cyber-physical system in a nontriangular form suffering from both sensor and actuator deception attacks. To avoid the algebraic loop problem, only partial states are employed as input vectors of neural networks (NNs) for approximating unknown dynamics, and compensation terms are further developed to offset approximation errors from NNs. With introduction of nonlinear gain functions and attack compensators, adverse effects of an intelligent adversary are alleviated effectively.

ATPase Inhibitory Factor 1 Is Critical for Regulating Sevoflurane-Induced Microglial Inflammatory Responses and Caspase-3 Activation.

Postoperative delirium (POD) is one of the most important complications after surgery with general anesthesia, for which the neurotoxicity of general anesthetics is a high-risk factor. However, the mechanism remains largely unknown, which also hinders the effective treatment of POD. Here, we confirmed that a clinical concentration of the general anesthetic sevoflurane increased the expression of inflammatory factors and activated the caspase-3 by upregulating ATPase inhibitory factor 1 (ATPIF1) expression in microglia.

Predictor-Based Neural Dynamic Surface Control for Strict-Feedback Nonlinear Systems With Unknown Control Gains.

Neural dynamic surface control (NDSC) is an effective technique for the tracking control of nonlinear systems. The objective of this article is to improve closed-loop transient performance and reduce the number of learning parameters for a strict-feedback nonlinear system with unknown control gains. For this purpose, a predictor-based NDSC (PNDSC) approach is presented.

Systematic review and meta-analysis of the effect of continuous cerebrospinal fluid drainage on keyhole surgery during the perioperative period.

Background: Lumbar continuous drainage of fluid (LCDF) has become more widely used in the diagnosis and treatment of neurological diseases in recent years. The use of LCDF can enable a better understanding of the patient's condition and reduce the incidence of related complications. LCDF can also affect complications of perforation surgery, including mortality during hospitalization, cerebral vasospasm (CVS), bleeding, and aneurysmal subarachnoid hemorrhage (aSAH).

Correlation analysis between TSP2, MMP-9 and perihematoma edema, as well as the short-term prognosis of patients with hypertensive intracerebral hemorrhage.

Background: To analyze the correlation between thrombospondin-2 (TSP2), matrix metalloproteinase (MMP)-9, and perihematomal edema, as well as the short-term prognosis of patients with hypertensive intracerebral hemorrhage.

Methods: The clinical data of 114 patients with hypertensive intracerebral hemorrhage admitted to our hospital from January 2018 to February 2020 were collected and divided into groups according to the levels of TSP2 and MMP-9. We compared edema indexes in patients with different levels of TSP2 and MMP-9, and analyzed the correlation between TSP2, MMP-9 and relative edema volume index (REI), edema change index (AEI).

Anesthetic Propofol Promotes Tumor Metastasis in Lungs via GABA R-Dependent TRIM21 Modulation of Src Expression.

Generation of circulating tumor cells (CTCs), a key step in tumor metastasis, occurs during surgical tumor resection, often performed under general anesthesia. Propofol is the commonly used anesthetic, but its effects on CTCs and tumor metastasis remain largely unknown. Propofol effects are investigated in an experimental metastasis model by injecting tumor cells and, subsequently, low- or standard-dose propofol to nude mice through tail vein.

TriATNE: Tripartite Adversarial Training for Network Embeddings.

Existing network embedding algorithms based on generative adversarial networks (GANs) improve the robustness of node embeddings by selecting high-quality negative samples with the generator to play against the discriminator. Since most of the negative samples can be easily discriminated from positive samples in graphs, their poor competitiveness weakens the function of the generator. Inspired by the sales skills in the market, in this article, we present tripartite adversarial training for network embeddings (TriATNE), a novel adversarial learning framework for learning stable and robust node embeddings.

Predictor-Based Neural Dynamic Surface Control for Bipartite Tracking of a Class of Nonlinear Multiagent Systems.

This article is concerned with bipartite tracking for a class of nonlinear multiagent systems under a signed directed graph, where the followers are with unknown virtual control gains. In the predictor-based neural dynamic surface control (NDSC) framework, a bipartite tracking control strategy is proposed by the introduction of predictors and the minimal number of learning parameters (MNLPs) technology along with the graph theory. Different from the traditional NDSC, the predictor-based NDSC utilizes prediction errors to update the neural network for improving system transient performance.

Disrupted folate metabolism with anesthesia leads to myelination deficits mediated by epigenetic regulation of ERMN.

Background: Exposure to anesthetics during early life may impair cognitive functions. However, the underlying mechanisms remain largely unknown. We set out to determine effects of sevoflurane anesthesia on folate metabolism and myelination in young non-human primates, mice and children.