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Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen in the worldwide pandemic of coronavirus disease 2019 (COVID-19), is readily transmitted via respiratory droplets during close contact. The [...], SARS-CoV-2 infection of the upper airway and the subsequent immune response are early, critical factors in COVID-19 pathogenesis. By studying infection of human biopsies in vitro and in a hamster model in vivo, we demonstrated a transition in nasal tropism from olfactory to respiratory epithelium as the virus evolved. Analyzing each variant revealed that SARS-CoV-2 WA1 or Delta infect a proportion of olfactory neurons in addition to the primary target sustentacular cells. The Delta variant possessed broader cellular invasion capacity into the submucosa, while Omicron displayed enhanced nasal respiratory infection and longer retention in the sinonasal epithelium. The olfactory neuronal infection by WA1 and the subsequent olfactory bulb transport via axon were more pronounced in younger hosts. In addition, the observed viral clearance delay and phagocytic dysfunction in aged olfactory mucosa were accompanied by a decline of phagocytosis-related genes. Further, robust basal stem cell activation contributed to neuroepithelial regeneration and restored ACE2 expression postinfection. Together, our study characterized the nasal tropism of SARS- CoV-2 strains, immune clearance, and regeneration after infection. The shifting characteristics of viral infection at the airway portal provide insight into the variability of COVID-19 clinical features, particularly long COVID, and may suggest differing strategies for early local intervention.

Throughput analysis plays an important role in the operations and management of automotive manufacturing. Predicting how the system throughput changes over time helps the plant managers to make timely operational decisions to meet the daily production requirement. In today's automotive production systems, the availability of sensing data reflecting process variables and machine status across the plant floor raises new opportunities for improving the throughput prediction accuracy. However, challenges exist in extracting the most important features from the high-dimensional data and capturing the complicated time-vary interdependency among different assets in the system. To overcome such challenges, in this paper we propose a hierarchical Recurrent Neural Network (RNN)-based framework that is composed of clustering, dimension reduction and feature selection, regression, and prediction pruning/adjustment. In addition to predicting end-of-line throughput, our framework then identifies the associations for low throughput to facilitate downtime prevention and maintenance decision-making. The proposed framework is applied to an automotive production system, and its effectiveness is demonstrated by comparison with conventional methods. [ABSTRACT FROM AUTHOR]

Dysfunctional autophagy induced by excessive reactive oxygen species (ROS) load and inflammation accelerates the development of Alzheimer's disease (AD). Recently, there has been an increasing interest in selenium-enriched ingredients (SEIs), such as selenoproteins, selenoamino acids and selenosugars, which could improve AD through antioxidant and anti-inflammation, as well as autophagy modulating effects. This review indicates that SEIs eliminate excessive ROS by activating the nuclear translocation of nuclear factor erythroid2-related factor 2 (Nrf2) and alleviate inflammation by inhibiting the mitogen-activated protein kinases (MAPKs)/nuclear factor kappa-B (NF-κB) pathway. Furthermore, they can activate the adenosine 5'-monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) pathway, and subsequently promote amyloid beta (Aβ) clearance and reduce memory impairments. SEIs are ubiquitous in many plants and microorganisms, such as Brassicaceae vegetables, yeast, and mushroom. Enzymatic hydrolysis, as well as physical processing, such as thermal, high pressure and microwave treatment, are the main techniques to modify the properties of dietary selenium. This work highlights the fact that SEIs can inhibit inflammation and oxidative stress and provides evidence that supports the potential use of these dietary materials to be a novel strategy for improving AD. [ABSTRACT FROM AUTHOR]

This study focuses on the large passenger flow control problem, after an operation interruption occurs, to develop a methodology that can efficiently control the passenger inflows of multiple stations and avoid overcrowding inside stations. An early-warning model for irregular large-scale passenger flows (ILSPF) and a dynamic ILSPF control model are proposed. The early-warning model is developed to predict passenger flows in the future with historical data and detect when to start control measures in actual time. The ILSPF cooperative control model focuses on cooperatively controlling the passenger inflows of multiple stations to ensure passenger safety in vehicles and stations, as well as maximize the number of passengers transported and minimize the passengers' total waiting times. An improved particle swarm optimization algorithm was designed to determine an optimal solution, and a case study on the Chengdu metro in China was carried out to examine the performance of the model. The obtained results verify the effectiveness of the model and algorithm and prove that ILSPF control can regulate the passenger inflow demand, better match the passenger demand and capability on the line, increase the total number of passengers transported, and balance the proportion of passenger boarding at each station., Author(s): Wei Zhu [1,2,3]; Mengfei Chen [1,2,3]; Pengling Wang (corresponding author) [1,2,3] 1. Introduction Recently, urban rail transit (URT) preferred by more and more passengers and government word-wide because it [...]

Cellular pyroptosis is a pro-inflammatory mode of programmed cell death that has been identified in recent years, and studies have shown that the LncRNA SOX2OT regulates myocardial injury during sepsis, but the exact regulatory mechanism is unclear. The aim of this study was to assess the role of SOX2OT in regulating cardiomyocyte injury during sepsis cardiomyopathy. Methods: Rat cardiomyocytes, C57BL/6 mice, and transgenic mice were divided into four groups: control, LPS, LPS+ knockout LncRNA SOX2OT, and LPS+ overexpression LncRNA SOX2OT. Inflammatory factor levels were detected by qPCR. Associated proteins and gene expression were detected by Western blotting and qPCR. Dual luciferase was used to detect the target genes of SOX2OT. Nrf2 and EZH2 knockdown and overexpression cell lines were established, and the expression of related genes was detected by qPCR. Results: Results In this study, we found that SOX2OT knockdown exacerbated LPS-induced levels of inflammatory factors and procalcitoninogen (PCT), and increased the expression of pyroptosis-related proteins and LDH. The results of dual luciferase reporter gene assay showed that EZH2 is the target gene of SOX2OT, and overexpression of SOX2OT decreased the expression of EZH2; we also found that knockdown of EZH2 in H9c2 cells decreased the expression of Nrf2, which was positively correlated with the expression level of NLRP3. Further in vivo results showed that overexpression of SOX2OT attenuated SIMD (sepsis-induced myocardial dysfunction), as evidenced by improved myocardial structural integrity and reduced inflammatory cell infiltration. The expression of pyroptosis-related proteins and LDH was significantly increased in the mice in the LPS group; this effect was reversed by overexpression of SOX2OT, and potentiated by knockdown of SOX2OT. Conclusion: Our data reveal a novel mechanism by which SOX2OT inhibits cardiomyocyte sepsis through the EZH2/Nrf-2/NLRP3 pathway, thereby attenuating septic myocardial injury, which may contribute to the development of new therapeutic strategies. [ABSTRACT FROM AUTHOR]