Soybean Seeds (Glycine max L.) Extract Against Cytokine Storm in ARDS Rat Model through Inhibiting Inflammation Marker

Several studies have suggested that "cytokine storms" are significant causes of the severity of COVID-19. Controlling and inhibiting the cytokine storm in COVID-19 could prevent the spread of COVID-19 and saves patient lives. Soybean (Glycine max L.) is known to have various biological activities. This study aims to examine bioactive compounds in SSE and the effect of SSE on the ARDS rats model. A total of 25 Sprague Dawley Lipopolysaccharide-induced rats were used. Determination of serum IL-1β, IL-12, and lung TNF-α levels was performed by ELISA method. NF-κB and IFN-γ expression were determined by the qRTPCR method. IL-6 expressions were analyzed by immunohistochemistry assay. The bleeding, inflammation, and alveolus collapse score were analyzed using the HE staining method. The results showed that SSE could decrease the level of IL-1β, IL-12, TNF-α, IL-6, NF-kB, and IFN-γ and improve the bleeding, inflammation, and alveolus score in the lung. SSE could decrease the pro-inflammatory cytokines and improve lung condition in ARDS rats model. © 2023, Bogor Agricultural University. All rights reserved.

Integrated Water Resources Plan Using An Optimization Model

As part of the City of Atlanta's Department of Watershed Management (DWM) transition into a 5-year rolling Capital Improvement Program (CIP), the Atlanta Program Management Services Team (PMST) was tasked with developing the Atlanta Integrated Water Resources Plan (IWRP) to incorporate project recommendations from the City's three recently completed master plans for water, wastewater, and stormwater into an integrated CIP. This effort was especially difficult as the City's available budget for CIP projects was being significantly reduced from normal years because of the adverse revenue impacts associated with the coronavirus pandemic and the uncertain economic recovery forecasts for the 5-year rolling CIP time frame. This paper details the successful development of an optimization model designed to maximize triple bottom line (TBL) and risk reduction benefits from the universe of potential water, wastewater, and stormwater projects while meeting tight financial budget limitations. The optimization model was based on OptimizerTM software by Optimatics that uses a heuristic learning algorithm, which is an approach designed to solve multi-criteria problems in a faster and more efficient manner that favors speed of process over absolute accuracy or completeness. The model used in Atlanta was the 3-dimensional (3-D) version to accumulate as much triple bottom line per dollar (TBL/$) and risk reduction per dollar (RRB/$) as early as possible in the planning horizon while minimizing budget expenditures. Copyright © 2022 Water Environment Federation.

Photobiomodulation Reduces the Cytokine Storm Syndrome Associated with COVID-19 in the Zebrafish Model.

Although the exact mechanism of the pathogenesis of coronavirus SARS-CoV-2 (COVID-19) is not fully understood, oxidative stress and the release of pro-inflammatory cytokines have been highlighted as playing a vital role in the pathogenesis of the disease. In this sense, alternative treatments are needed to reduce the level of inflammation caused by COVID-19. Therefore, this study aimed to investigate the potential effect of red photobiomodulation (PBM) as an attractive therapy to downregulate the cytokine storm caused by COVID-19 in a zebrafish model. RT-qPCR analyses and protein-protein interaction prediction among SARS-CoV-2 and Danio rerio proteins showed that recombinant Spike protein (rSpike) was responsible for generating systemic inflammatory processes with significantly increased levels of pro-inflammatory (il1b, il6, tnfa, and nfkbiab), oxidative stress (romo1) and energy metabolism (slc2a1a and coa1) mRNA markers, with a pattern similar to those observed in COVID-19 cases in humans. On the other hand, PBM treatment was able to decrease the mRNA levels of these pro-inflammatory and oxidative stress markers compared with rSpike in various tissues, promoting an anti-inflammatory response. Conversely, PBM promotes cellular and tissue repair of injured tissues and significantly increases the survival rate of rSpike-inoculated individuals. Additionally, metabolomics analysis showed that the most-impacted metabolic pathways between PBM and the rSpike treated groups were related to steroid metabolism, immune system, and lipid metabolism. Together, our findings suggest that the inflammatory process is an incisive feature of COVID-19 and red PBM can be used as a novel therapeutic agent for COVID-19 by regulating the inflammatory response. Nevertheless, the need for more clinical trials remains, and there is a significant gap to overcome before clinical trials can commence.

The COVID-19 Crisis: An Opportunity to Integrate Food Democracy into Post-Pandemic Food Systems

The world economy is sliding yet into another recession (having arguably barely recovered from the previous economic downturn) due to the worldwide pressures and tensions created by the COVID-19 pandemic.1 With most countries in the world under lockdown (or in similar situations), almost all food is now consumed in the household. Arguably, agricultural producers and the retail industry appear to be the best placed to weather the storm in order to respond to such a change in demand. However, this is overly simplistic. Recent news of empty shelves in supermarkets whilst dairy farmers have been forced to pour milk down the drain have gone viral.

Integral Assessment of Atmospheric Air Quality in the Largest Cities of Russia Based on TROPOMI (Sentinel-5P) Data for 2019–2020

This paper considers the level of atmospheric air pollution of the 20 largest cities in Russia in 2019–2020. The data used for the study is initially collected by a TROPOMI instrument (on the Sentinel-5P satellite), including measurements of carbon monoxide, formaldehyde, nitrogen dioxide, sulfur dioxide, and aerosol (aerosol index). The measurements were obtained using the cloud-based platform, Google Earth Engine, which presents L3 level data available for direct analysis. The Tropomi Air Quality Index (TAQI) integrates available TROPOMI measurements into a single indicator. The calculation results showed that most of the cities under consideration (15 out of 20) have a low or higher than usual level of pollution. Formaldehyde (35.7%) and nitrogen dioxide (26.4%) play the main role in the composition of pollution particles. A significant share is occupied by sulfur dioxide (16.4%). The contribution of carbon monoxide and aerosol averages 10.8 and 10.6%, respectively. Air pollution in cities is caused by both natural (wildfires, dust storms) and anthropogenic (seasonal migrations of the population, restrictions due to the COVID-19 pandemic) factors. Estimating atmospheric pollution levels in urban areas using an integral index based on remote data (such as TAQI) can be considered as a valuable information addition to existing ground-based measuring systems within the multisensory paradigm.

STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19

Human mobility estimation is crucial during the COVID-19 pandemic due to its significant guidance for policymakers to make non-pharmaceutical interventions. While deep learning approaches outperform conventional estimation techniques on tasks with abundant training data, the continuously evolving pandemic poses a significant challenge to solving this problem due to data non-stationarity, limited observations, and complex social contexts. Prior works on mobility estimation either focus on a single city or lack the ability to model the spatio-temporal dependencies across cities and time periods. To address these issues, we make the first attempt to tackle the cross-city human mobility estimation problem through a deep meta-generative framework. We propose a Spatio-Temporal Meta-Generative Adversarial Network (STORM-GAN) model that estimates dynamic human mobility responses under a set of social and policy conditions related to COVID-19. Facilitated by a novel spatio-temporal task-based graph (STTG) embedding, STORM-GAN is capable of learning shared knowledge from a spatio-temporal distribution of estimation tasks and quickly adapting to new cities and time periods with limited training samples. The STTG embedding component is designed to capture the similarities among cities to mitigate cross-task heterogeneity. Experimental results on real-world data show that the proposed approach can greatly improve estimation performance and outperform baselines. © 2022 IEEE.

Heliogeophysical Conditions in Moscow during the Covid-19 Pandemic

In this paper we consider the effect of heliogeophysical activity on the COVID-19 epidemic associated with the spread of the SARS-CoV-2 coronavirus in Moscow. An analysis of official data on the course of the pandemic has provided evidence of the effect of heliogeophysical activity on the spread of an infectious disease. The pandemic arose during the winter when solar activity was minimal and ultraviolet radiation was at its lowest. The study showed a significant relation between the infectious process and geomagnetic activity: periods of outbreaks in the number of infections and deaths correlated with periods of a decrease in geomagnetic activity lasting several months. The impact of magnetospheric storms and substorms on the human body during a pandemic is also considered. It is shown that, during the minimum of solar activity during periods of geomagnetic disturbances lasting from one to several days, both the number of infections and the number of deaths additionally and statistically significantly increase. Evidence of a direct or indirect effect of solar activity on the occurrence of outbreaks of infectious diseases is important from the viewpoint of understanding the emergence and development of epidemics.

Special issue. (Special issue.)

This special issue contains 17 papers covering a range of topics related to environmental, geological, and social issues in Bangladesh. The articles use various methodologies, including statistical analysis, satellite imaging, and case studies, to explore issues such as drought, urbanization, healthcare, greenhouse gas emissions, groundwater resources, COVID-19 stigmatization, oil rim reservoir development, coal permeability, seaweed composition, hailstorms, tropical cyclones, heavy metal contamination, flood hazard assessment, and climate change vulnerability. Overall, the articles provide valuable insights and information that can inform policy and decision-making in Bangladesh.

Deployment and surface operations of the SEIS instrument onboard the InSight mission

On November 26th, 2018, the InSight spacecraft successfully landed on Mars after a 6-month journey. After a long deployment and commissioning phase, the SEIS (Seismic Experiment for Interior Structure) instrument was ready to monitor seismic events on the Elysium Planitia plain on the surface of Mars, coupled with the APSS (Auxiliary Payload Sensor Suite) weather station equipped with a magnetometer, wind sensors, and a pressure sensor. The InSight mission goal is to characterize the deep interior structure of Mars, including the thickness and structure of the crust, the composition and structure of the mantle, and the size of the core. Its nominal duration of two years (2019–2020) has yielded unprecedented results with the detection of the first Martian seismic events ever recorded, and the in-depth characterization of its atmosphere with the best weather station ever deployed on Mars. InSight has collected an outstanding amount of high-quality measurements that the scientific community will spend many years analyzing. The extended mission has started and covers the years 2021 and 2022. This paper will describe the operations of the SEIS experiment on Mars since landing, as well as the challenges of operating this instrument. Energy becomes increasingly limited for payloads on Mars due to a significant amount of dust accumulated on the solar panels and the many dust storms in the Martian atmosphere. A new activity was decided for the extended mission in 2021 which consisted in burying the seismometer cable (or tether) with Martian regolith collected locally using the robotic arm, in order to reduce the seismic noise from that subsystem. Preparation activities, testing, results, associated challenges and lessons learned will be presented. Moreover, the paper will address the challenges faced in carrying out operations with COVID-related constraints, as finding oneself operating a seismometer on Mars from home can be challenging. Finally, management of periods of solar conjunctions, during which communication between Earth and Mars is unavailable, will be addressed. © 2022 IAA

The potential for traditional Chinese therapy in treating sleep disorders caused by COVID-19 through the cholinergic anti-inflammatory pathway.

Since the outbreak of Coronavirus disease (COVID-19) in 2019, it has spread rapidly across the globe. Sleep disorders caused by COVID-19 have become a major concern for COVID-19 patients and recovered patients. So far, there's no effective therapy on this. Traditional Chinese therapy (TCT) has a great effect on sleep disorders, with rare side effects and no obvious withdrawal symptoms. The cholinergic anti-inflammatory pathway, a neuroregulatory pathway in the central nervous system that uses cholinergic neurons and neurotransmitters to suppress inflammatory responses, has been reported to be associated with sleep disorders and psychiatric symptoms. Many studies have shown that TCT activates the cholinergic anti-inflammatory pathway (CAP), inhibits inflammation, and relieves associated symptoms. Therefore, we believe that TCT may be a potential therapeutic strategy to alleviate sleep disorders induced by COVID-19 through CAP. In this review, we analyzed the relationship between cytokine storm induced by Coronavirus and sleep disorders, explained the influence of CAP on sleep disorders, discussed the TCT's effect on CAP, and summarized the treatment effect of TCT on sleep disorders. Based on these practical researches and theoretical basis, we propose potential strategies to effectively improve the sleep disorders caused by COVID-19.

Current understanding on long non-coding RNAs in immune response to COVID-19.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic threatening the lives and health of people worldwide. Currently, there are no effective therapies or available vaccines for COVID-19. The molecular mechanism causing acute immunopathological diseases in severe COVID-19 is being investigated. Long noncoding RNAs (lncRNAs) have been proven to be involved in many viral infections, such as hepatitis, influenza and acquired immune deficiency syndrome. Many lncRNAs present differential expression between normal tissue and virus-infected tissue. However, the role of lncRNAs in SARS-CoV-2 infection has not been fully elucidated. This study aimed to review the relationship between lncRNAs and viral infection, interferon and cytokine storms in COVID-19, hoping to provide novel insights into promising targets for COVID-19 treatment.

IoT Based Cytokine Storm Symptoms Early Warning System for Covid-19 Self-Isolating Patient

Covid-19, which has spread throughout the world, has reportedly caused millions of deaths. Among the causes of the patient's death is the phase after the patient is declared negative for COVID, but there is a cytokine storm. In this study, an IoT-based technology was proposed to be able to detect abnormalities in COVID-19 patients, even though they already had a negative Covid status based on the PCR test. The implementation of this technology allows former Covid patients to be monitored from anywhere as long as they are connected to the internet, using designed wearable devices and dedicated mobile apps for them. Based on experiment result, all the sensors have the ability to work and sense patient body indicators with error below 5%. This study demonstrated the flawless use of a mobile app dedicated to monitor patients' health during the pandemic. When patient health condition indicating exposed to cytokine storm, a warning notification is appear at the mobile app. © 2022 IEEE.

Impact of COVID-19 Pandemic on Small and Medium-Sized Enterprises in Kosovo

The pandemic situation caused by coronavirus disease (COVID-19) has affected the global and Kosovo economy. Because of restricted measures to prevent the spread of viruses, SMEs have faced worsening financial results. The article aims to assess the impact of the COVID-19 outbreak on these businesses and provide policy recommendations to help SMEs reduce business losses and survive through the crisis. We adopted an explanatory methodology for comprehensively reviewing the available literature, including policy documents, research papers, and reports in the relevant field. Further, to add empirical evidence, we collected data from 70 Kosovo' SMEs by administrating an online questionnaire. Most of the participating enterprises have been directly affected and surface several issues, such as worsening financial results, decreasing demand, supply chain disruption, and liquidity problems. Based on the regression results, the financial results are affected by a decrease in turnover, but the drop in output and liquidity obstacles are not statistically significant. The findings of our study are consistent with previous studies. We recommend different policies to ease the adverse effects of the outbreak on SMEs. Although our suggested policy recommendations may not be sufficient to help SMEs go through the ongoing crisis, these measures will help weather the storm.

PLOS Sustainability and Transformation, empowering immediate actions for a sustainable future

Climate scientists at NASA's Goddard Institute for Space Studies reported 2020 as the warmest year on record [1];the Gulf Stream has slowed down dramatically [2];the Last Ice Area has melted away faster than previously estimated [3];and coral reefs continue their constant and global decline [4]. The effects of the pandemic and climate change have also led to a rebalance in focus between efficiency and resilience across the public, private, and people sectors in society. The fodder for our global body of knowledge ultimately are the outputs and insights from our researchers and thought leaders.

Role of mast cells in the pathogenesis of severe lung damage in COVID-19 patients.

BACKGROUND: There is still insufficient knowledge with regard to the potential involvement of mast cells (MCs) and their mediators in the pathology of coronavirus disease-2019 (COVID-19). Therefore, our study aimed to investigate the role of MCs, their activation and protease profiles in the pathogenesis of early and late lung damage in COVID-19 patients. METHODS: Formalin-fixed and paraffin embedded lung specimens from 30 patients who died from COVID-19 and 9 controls were used for histological detection of MCs and their proteases (tryptase, chymase) followed by morphometric quantification. RESULTS: Our results demonstrated increased numbers of MCs at early stage and further augmentation of MCs number during the late stage of alveolar damage in COVID-19 patients, as compared to the control group. Importantly, the percentage of degranulated (activated) MCs was higher during both stages of alveolar lesions in comparison to the controls. While there was no prominent alteration in the profile of tryptase-positive MCs, our data revealed a significant elevation in the number of chymase-positive MCs in the lungs of COVID-19 patients, compared to the controls. CONCLUSIONS: MCs are characterized by dysregulated accumulation and increased activation in the lungs of patients suffering from COVID-19. However, future profound studies are needed for precise analysis of the role of these immune cells in the context of novel coronavirus disease.

The Internet Design Framework for Improvement of Users' Positive Emotions

This study proposes an internet design framework for users to improve their positive emotions when they are in a negative mood. First, the literature review focuses on the definition of emotion, positive emotional design in internet experiences, and emotion regulation. Second, in order to construct an internet design framework that improves positive emotion, this paper adopts a qualitative analysis method to analyze 70 collected studies in the area of regulating emotion and stimulating positive emotions. Additionally, bibliometrics and statistics are conducted to summarize the framework and strategies. Third, two cases of internet design are presented: (a) Internet design that improves users' positive emotions is examined under the background of extreme rainstorm as an example;an applet service design is provided by case study;(b) in the context of COVID-19, we developed an Internet of things interactive design that improves users' positive emotions. Fourth, the internet design framework and the results of the case studies are analyzed and discussed. Finally, an internet design framework is proposed to improve users' positive emotions when they are in a negative mood, which includes the Detachment-empathy framework, External-protection framework, Ability-strengthen framework, Perspective-transformation framework, and Macro-cognitive framework. The framework can help designers to generate design ideas accurately and quickly when users are in a negative mood, to improve subjective well-being, and contribute to the development of internet experience design. Copyright © 2022 KSII.

An Analysis on Hybrid Brain Storm Optimisation Algorithms

Optimisation can be described as the process of finding optimal values for the variables of a given problem in order to minimise or maximise one or more objective function(s). Brain storm optimisation (BSO) algorithm is relatively new swarm intelligence algorithm that mimics the brainstorming process in which a group of people solves a problem together. The aim of this paper is to present hybrid BSO algorithm solutions in general, and particularly: (i) a hybrid BSO for improving the performances of the original BSO algorithm;(ii) a hybrid BSO for the flexible job-shop scheduling problem;and (iii) a feature selection by a hybrid BSO algorithm for the COVID-19 classification. The hybrid BSO algorithm overcomes the lack of exploitation in the original BSO algorithm, and simultaneously, the obtained better results prove their efficiency and robustness. © 2022, Springer Nature Switzerland AG.

Cytokine storm and stem cell activation in unveiling potential targets for diagnosis and therapy

Cytokine storms illustrate a robust, uncontrolled immune response that can severely disrupt the physiology of a person infected with a virus such as COVID-19. Cytokine storms during the most severe of COVID-19 infections are believed to be one of the major contributing factors to mortality and severe pathologic outcomes of the disease. Dysregulated levels of cytokines during a cytokine storm contribute to changes in different components of the local microenvironments including the stem cell components. Here, we review the pathophysiology of cytokine storms looking at different aspects of viral-induced cytokine release. In particular, we note the changes in the stem cell compartments that occur as well as therapeutic targets relying on targeting stem cells. © 2022 Elsevier Inc. All rights reserved.

Identification of Hub Genes and Key Pathways in TNF-α and IFN-γ Induced Cytokine Storms via Bioinformatics

Cytokine storms, an overaggressive immune response due to the overexpression of pro-inflammatory cytokines, have been identified to play a significant role in COVID-19 infections. Studies have shown that TNF-α and IFN-γ are integral to the process, however, its genetic mechanisms have yet to be fully elucidated. Herein, the key changes in the gene expression of TNF-α and IFN-γ induced cytokine storms are identified through differential gene analysis on the publicly available GEO GSE160163 dataset. GO and KEGG enrichment were used to annotate identified DEGs, and a PPI network was constructed based on the STRING database. A total of 446 differentially expressed genes were identified. Up-regulated genes and downregulated genes were enriched in viral immune response and infection pathways, and steroid biosynthesis and metabolic pathways, respectively. PPI construction revealed 1,834 interactions between 428 proteins, indicating their biological connectivity. Module analysis identified nine (9) hub genes: STAT1, CXCL10, CD274, CXCL9, IRF1, PSMB9, CD86, STAT3, and CXCR4, involved in viral immune response and three (3) significant modules involved in NOD-like receptor signaling, steroid biosynthesis, and viral infections. These identified DEGs, hub genes, and their respective enriched pathways aid us in understanding the molecular mechanisms of cytokine storms, as well as provide potential gene targets and druggable receptors for the treatment of cytokine storms. © 2022 IEEE.

School Snow Days, Absenteeism, and Student Achievement: A Comparative Study of Nova Scotia and Massachusetts

Recent research on the effects of school cancellations because of snow or storms confirms what school authorities in Canada and the United States have understood for some time: missed school days have a detrimental effect upon student learning. Disrupted instructional time and student learning have been analyzed in Massachusetts and in policy studies conducted in the Canadian province of Nova Scotia. One 2012 study in Massachusetts showed a strong relationship between student absences and achievement, but little or no impact attributable to inclement-weather school closures. Yet on balance, most research studies link school-day cancellations with declining student test scores. This research note assesses the impact of storm closings in Nova Scotia between the school years 2008-2009 and 2017-2018. There, the number of snow days is normally double that of Massachusetts and reported rates of student absenteeism are higher. This study assesses the ‘accumulative effect’ of missing whole school days, planned and unplanned, on student mathematics scores and high-school completion, and it proposes a some policy responses. Some consideration is given also to the profound impact of COVID-19 school disruptions and remote learning experiments on the changing policy landscapes in both Nova Scotia and Massachusetts.