Placental Thrombosis Resulting in Hypoxic Ischemic Encephalopathy in an Infant of a Mother with Covid-19

Case Report: Since the beginning of the Coronavirus Disease 2019 (COVID-19) pandemic, there has been much work to understand the negative effects of SARS-CoV-2 on tissues expressing the Angiotensin Converting Enzyme-2 (ACE2) receptor, including the placenta. However, there is limited information regarding placental pathology findings in mothers with COVID-19 and the effects of SARS-CoV-2 on the placenta. The available research reports effects on the fetus ranging from minimal to intrauterine fetal demise. Case Description: A 4680g baby boy was born at 38+1 weeks of gestation to 36y old G4P1021 female via repeat cesarian section. The pregnancy was complicated by advanced maternal age, chronic hypertension with superimposed pre-eclampsia with severe features, BMI of 80, and SARS-CoV-2 infection. The mother had mild COVID-19 symptoms and did not require hospitalization or oxygen support. Prenatal ultrasounds were limited due to body habitus. At the time of delivery, there was clear amniotic fluid. Upon delivery the infant was cyanotic and limp and was brought to the warmer immediately. Non-invasive positive pressure ventilation was initiated at 5 minutes of life with improvement in infant color and oxygen saturation. He was then admitted to the Neonatal Intensive Care Unit (NICU). APGARs were 2, 3, 5, and 7 at 1, 5, 10, and 15 minutes respectively. Cord gases showed severe metabolic acidosis. The patient was diagnosed with hypoxic-ischemic encephalopathy (HIE) and therapeutic hypothermia was initiated. Both the NICU and obstetric teams were unable to identify a clear perinatal cause of HIE in this patient. Later, the placenta pathology report revealed a large placenta for estimated gestational age corresponding to the 75th percentile, villous parenchyma with focal chorangiosis and thrombi, with unremarkable fetal membrane and three vessel umbilical cord. The cause of HIE was then thought to be due to the placental thrombi likely caused by SARS-CoV-2 infection. Discussion(s): Fetal vascular malperfusion and fetal vascular thrombus have been noted as a common finding in the placentas of pregnant women who test positive for SARS-CoV-2. There are various causes of HIE, from maternal, placental and fetal factors. This patient had no clinically evident hypoxic event, but information was limited due to the lack of monitoring of the fetus in utero. Given the mother's SARS-CoV-2 infection and the placental pathology findings, it is likely that the cause of this patient's HIE was related to the effects on the placenta from SARS-CoV-2. Conclusion(s): As more information comes to light about the effects of SARS-CoV-2 on the placenta, it is important to consider a maternal SARS-CoV-2 infection during pregnancy as a cause of HIE in a newborn.

Intelligent optimization design of electron barrier layer for AlGaN-based deep-ultraviolet light-emitting diodes

AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) are widely used in sterilization, sensing, water purification, medical treatment, non-line of sight (NLOS) communication and many other fields. Especially it has been reported that the global novel coronavirus (COVID-19) can be effectively inactivated by the DUV light with a wavelength below 280 nm (UVC) within a few seconds, which has also attracted great attention. However, the external quantum efficiency (EQE) of UVC LED is still at a low level, generally not more than 10%. As an important component of EQE, internal quantum efficiency (IQE) plays a crucial role in realizing high-performance DUV-LED. In order to improve the IQE of AlGaN-based DUV-LED, this work adopts an electron blocking layer (EBL) structure based on InAlGaN/AlGaN superlattice. The results show that the superlattice EBL structure can effectively improve the IQE compared with the traditional single-layer and double-layer EBL structure for the DUV-LED. On this basis, the optimization method based on JAYA intelligent algorithm for LED structure design is proposed in this work. Using the proposed design method, the InAlGaN/AlGaN superlattice EBL structure is further optimized to maximize the LED' s IQE. It is demonstrated that the optimized superlattice EBL structure is beneficial to not only the suppression of electron leakage but also the improvement of hole injection, leading to the increase of carrier recombination in the active region. As a result, the IQE of the DUV-LED at 200 mA injection current is 41.2% higher than that of the single-layer EBL structure. In addition, the optimized structure reduces IQE at high current from 25% to 4%. The optimization method based on intelligent algorithm can break through the limitation of the current LED structure design and provide a new method to improve the efficiency of AlGaN-based DUV-LED. © 2023 Chinese Physical Society.

Exploring the potential targets and mechanisms of Xuebijing Injection for COVID-19 based on network pharmacology and molecular docking technology

Objective To explore the potential regulatory mechanism of Xuebijing injection in the treatment of COVID-19 by using network pharmacology and molecular docking methods. Methods Corresponding target genes of all the active ingredients of Xuebijing injection were obtained by using the pharmacological database and analysis platform of TCM System (TCMSP). And intersections with the COVID-19 gene-related targets in GeneCards database, OMIM database, PharmGkb database, TTD database and DrugBank database using the R programming language. Thus, the core target of Xubijing injection in COVID-19 treatment was obtained;Cytoscape 3.7.2 software was used to construct TCM - compound - target network;PPI network of intersection target was obtained by STRING;Utilized data packets to perform gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to predict the mechanism of overlapping targets. Finally, molecular docking technology was implemented to dock key active ingredients with PPI core protein. Results GO functional enrichment analysis included 1 818 biological processes (BP), 20 cellular components (CC) and 89 molecular functions (MF). The first 30 KEGG related pathways involved inflammation and immune response, such as rheumatoid arthritis signaling pathway, IL-17 signaling pathway, Th17 cell differentiation pathway, hypoxia-inducible factor (HIF-1) signaling pathway, JAK-Stat signaling pathway, inflammatory bowel disease signaling pathway, NF-κB signaling pathway, etc. Quercetin, cryptotanshinone, luteolin, β -carotene can affect IL1B, STAT3, AKT1, VEGFA and other overlapping targets. Meanwhile, quercetin may exert anti-inflammatory, antiviral and immune responses through IL1B binding to treat COVID-19. Conclusion This study reveals that chemical components in Xuebijing injection are involved in multiple biological processes and pathways in COVID-19 treatment through binding to key target proteins. © 2022. China Tropical Medicine. All rights reserved.

Study on effective components of Ganoderma applanation and its mechanism of action in preventing COVID-19 based on UHPLC-Q- Exactive-Orbitrap-MS integrated network pharmacology

Aim To elucidate the effective components of Ganoderma applanatum and its mechanism of preventing the coronavirus disease 2019(COVID-19).Methods To begin with, UHPLC-Q-Exactive-Orbitrap-MS was established to identify the main chemical constituents of G.applanatum.Then, the predicted targets of G.applanatum were selected by Swiss Target Prediction.GO analysis and KEGG analysis of core target genes were performed using the DAVID database.Finally, to explore the potential mechanism of G.applanatum against COVID-19, core functional components-core target-metabolism path network diagram was constructed using Cytoscape 3.8.0, and molecular docking was used to analyze the binding force of the core effective compounds with angiotensin-converting enzyme II(ACE2)and three SARS CoV-2 proteins, nonstructural protein-15 Endoribonuclease(NSP15), the receptor-binding domain of spike protein(RBD of S protein), and main protease(Mpro/3CLpro).Results Sixty-two components were identified from G.applanatum by UHPLC-Q-Exactive-Orbitrap-MS study;30 active components were closely associated with 32 core targets including IL6, PTGS2, and MAPK1;KEGG analysis showed that it might treat COVID-19 through signaling pathways, such as PI3K-Akt signaling pathway, TNF signaling pathway, tuberculosis, and so on;molecular docking analysis showed that 1,4-Dihydroxy-2-naphthoic acid, parthenolide, 7,8-Dihydroxycoumarin, and other vital compounds had a certain degree of affinity with ACE2 and three SARS CoV-2 proteins.Conclusion This study clarifies the chemical composition and the potential mechanism of G.applanatum, providing a scientific basis for screening the effective ingredients of G.applanatum. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

High-throughput human primary cell-based airway model for evaluating influenza, coronavirus, or other respiratory viruses in vitro.

Influenza and other respiratory viruses present a significant threat to public health, national security, and the world economy, and can lead to the emergence of global pandemics such as from COVID-19. A barrier to the development of effective therapeutics is the absence of a robust and predictive preclinical model, with most studies relying on a combination of in vitro screening with immortalized cell lines and low-throughput animal models. Here, we integrate human primary airway epithelial cells into a custom-engineered 96-device platform (PREDICT96-ALI) in which tissues are cultured in an array of microchannel-based culture chambers at an air-liquid interface, in a configuration compatible with high resolution in-situ imaging and real-time sensing. We apply this platform to influenza A virus and coronavirus infections, evaluating viral infection kinetics and antiviral agent dosing across multiple strains and donor populations of human primary cells. Human coronaviruses HCoV-NL63 and SARS-CoV-2 enter host cells via ACE2 and utilize the protease TMPRSS2 for spike protein priming, and we confirm their expression, demonstrate infection across a range of multiplicities of infection, and evaluate the efficacy of camostat mesylate, a known inhibitor of HCoV-NL63 infection. This new capability can be used to address a major gap in the rapid assessment of therapeutic efficacy of small molecules and antiviral agents against influenza and other respiratory viruses including coronaviruses.

Magnetic-Nanosensor-Based Virus and Pathogen Detection Strategies before and during COVID-19. LID - acsanm.0c02048

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is a threat to the global healthcare system and economic security. As of July 2020, no specific drugs or vaccines are yet available for COVID-19;a fast and accurate diagnosis for SARS-CoV-2 is essential in slowing the spread of COVID-19 and for efficient implementation of control and containment strategies. Magnetic nanosensing is an emerging topic representing the frontiers of current biosensing and magnetic areas. The past decade has seen rapid growth in applying magnetic tools for biological and biomedical applications. Recent advances in magnetic nanomaterials and nanotechnologies have transformed current diagnostic methods to nanoscale and pushed the detection limit to early-stage disease diagnosis. Herein, this review covers the literature of magnetic nanosensors for virus and pathogen detection before COVID-19. We review popular magnetic nanosensing techniques including magnetoresistance, magnetic particle spectroscopy, and nuclear magnetic resonance. Magnetic point-of-care diagnostic kits are also reviewed aiming at developing plug-and-play diagnostics to manage the SARS-CoV-2 outbreak as well as preventing future epidemics. In addition, other platforms that use magnetic nanomaterials as auxiliary tools for enhanced pathogen and virus detection are also covered. The goal of this review is to inform the researchers of diagnostic and surveillance platforms for SARS-CoV-2 and their performances. FAU - Wu, Kai