ABSTRACT
The COVID-19 pandemic presented new challenges for scholars and government officials to predict people's evacuation decisions under a conflicting natural disaster. In this study, we examined households' evacuation and shelter intentions given the potential conflicts between the perceived risks from a hurricane and the coexisting public health crisis. We surveyed households living inside hurricane evacuation zones in Florida during the 2020 hurricane season. Data were first used to examine the evacuation and shelter intentions before and during the pandemic. We then measured respondents' hurricane and COVID-19 risk perception, respectively. The impacts of both risk perceptions on respondents' hurricane evacuation intentions were explored. We found that when people felt unsafe to stay home for a Category 2, 3, or 4 hurricane, their intended evacuation was about the same before and during the pandemic regardless of their COVID-19 risk perception. The COVID-19 risk perception, however, significantly lowered the evacuation intention for a Category 1 hurricane. It also significantly influenced evacuees' preference for nontraditional shelters such as government-contracted hotels. The results of our study have practical implications for emergency management and public health governance. Our study also provides insights into decision-making under the conflict between natural hazards and infectious diseases. (English) [ FROM AUTHOR] La pandemia del COVID-19 planteó nuevos retos a los eruditos y funcionarios gubernamentales para predecir las decisiones de evacuación de la gente sometida a un desastre natural conflictivo. En este estudio, examinamos la evacuación e intenciones de albergue de familias teniendo en cuenta potenciales conflictos entre los riesgos percibidos de un huracán y las crisis coexistentes en la salud pública. Encuestamos a las familias que residían en las zonas de evacuación por huracanes de la Florida durante la temporada de huracanes del 2020. Los datos se usaron primero para examinar las intenciones de evacuación y de refugio antes y durante la pandemia. Después, medimos la percepción del riesgo de afectaciones por huracanes y COVID-19 de los encuestados, respectivamente. Se exploraron los impactos de ambos tipos de percepciones de riesgo en las intenciones de evacuación, por encuestado. Hallamos que cuando la gente se siente insegura de permanecer en casa frente a huracanes de las categorías 2, 3 y 4, su evacuación intencionada era más o menos la misma de antes y durante la pandemia, sin importar la percepción del riesgo de COVID-19. No obstante, la percepción del riesgo de COVID-19 redujo de manera significativa la evaluación de la intención de evacuación para un huracán de categoría 1. Eso también influyó significativamente en la preferencia de los evacuados por refugios no tradicionales, como los hoteles contratados por el gobierno. Los resultados de nuestro estudio tienen implicaciones prácticas en el manejo de las emergencias y la gobernanza de la salud pública. También proporciona nuestro estudio nuevas visiones en lo que concierne a toma de decisiones bajo condiciones de conflicto entre las catástrofes naturales y la enfermedades contagiosas. (Spanish) [ FROM AUTHOR] 新冠肺炎流行病与其它自然灾害相互冲突, 给专家和政府预测人群的疏散决定提出了新的挑战。我们探讨了家庭疏散和避难的意愿, 考虑了飓风的感知风险与公共卫生危机之间的潜在冲突。我们调查了2020年飓风季节美国佛罗里达州飓风疏散区内的家庭。首先, 基于数据探讨了流行病之前和期间的疏散和避难意愿。然后, 我们分别度量了受访者对飓风和新冠肺炎的风险感知。探讨了这两种风险感知对受访者飓风疏散意愿的影响。我们发现, 在2、3或4级飓风中, 当人们认为居家危险时, 不管如何感知新冠肺炎风险, 人们在新冠肺炎流行之前和期间的疏散意愿大致相同。然而, 新冠肺炎风险感知显著降低了1级飓风的撤离意愿。它还显著影响了疏散者对非传统庇护所（如, 政府指定酒店）的偏好。我们的研究结果, 对应急管理和公共卫生治理具有实际意义。我们的研究, 还为自然灾害和传染病相互冲突情况下的决策提供了见解。 (Chinese) [ FROM AUTHOR] Copyright of Professional Geographer is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-of-the-art approaches. It is also able to give automated veracity assessment and ranked supporting evidence with the stance towards the claim to be checked. In addition, PANACEA adapts the bi-directional graph convolutional networks model, which is able to detect rumours based on comment networks of related tweets, instead of relying on the knowledge base. This rumour detection module assists by warning the users in the early stages when a knowledge base may not be available. © 2023 Association for Computational Linguistics.
ABSTRACT
The immune system is developed to preserve its hosts from an ever-expanding cluster of pathogenic microbes. The elimination of toxic substances, allergens, or any other harmful existences that come in, passing the mucosal surfaces, is as well the responsibility of this special system. Its ability to distinguish self (our bodies' functioning cells and tissues) from non-self is the key aspect to its ability to mobilize some reaction to an invasion initiated by the stranger substances listed above. To identify and kill unsafe microorganisms, the host applies both natural and versatile systems, our innate and adaptive immune systems. Vaccines are used to combat the current SARS-CoV-2 strain by utilizing immune system mechanisms, specifically the adaptive immune system. Vectored vaccines, protein vaccines, genetic vaccine, and monoclonal antibody for passive vaccination are among the vaccine platforms under consideration for SARS-CoV-2. Each vaccine has its own benefits and drawbacks. This paper is written to describe the three major forms of COVID-19 vaccines, as well as the unique mechanisms of elements of the immune system associated with the virus. © 2023 SPIE.
ABSTRACT
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the process of classifying reviews many researchers have adopted machine learning approaches. Keeping in view, the rising demand for educational applications, especially during COVID-19, this research aims to automate Android application education reviews' classification and sentiment analysis using natural language processing and machine learning techniques. A baseline corpus comprising 13,000 records has been built by collecting reviews of more than 20 educational applications. The reviews were then manually labelled with respect to sentiment and issue types mentioned in each review. User reviews are classified into eight categories and various machine learning algorithms are applied to classify users' sentiments and issues of applications. The results demonstrate that our proposed framework achieved an accuracy of 97% for sentiment identification and an accuracy of 94% in classifying the most significant issues. Moreover, the interpretability of the model is verified by using the explainable artificial intelligence technique of local interpretable model-agnostic explanations. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
Covid-19 virus variants identified so far are due to viral genetic diversity, genetic evolution, and variable infectivity, suggesting that high infection rates and high mortality rates may be contributed by these mutations. And it has been reported that the targeting strategies for innate immunity should be less vulnerable to viral evolution, variant emergence and resistance. Therefore, the most effective solution to Covid-19 infection has been proposed to prevent and treat severe exacerbation of patients with moderate disease by enhancing human immune responses such as NK cell and T cell. In previous studies, we demonstrated for the first time that gamma-PGA induced significant antitumor activity and antiviral activity by modulating NK cell-mediated cytotoxicity. Especially intranasal administration of gamma-PGA was found to effectively induce protective innate and CTL immune responses against viruses and we found out that gamma-PGA can be an effective treatment for cervical intraepithelial neoplasia 1 through phase 2b clinical trial. In this study, the possibility of gamma-PGA as a Covid-19 immune modulating agent was confirmed by animal experiments infected with Covid-19 viruses. After oral administration of gamma-PGA 300mug/mouse once a day for 5 days in a K18-hACE2 TG mouse model infected with SARS-CoV-2 (NCCP 43326;original strain) and SARS-CoV-2 (NCCP 43390;Delta variant), virus titer and clinical symptom improvement were confirmed. In the RjHan:AURA Syrian hamster model infected with SARS-CoV-2 (NCCP 49930;Delta variant), 350 or 550 mug/head of gamma-PGA was administered orally for 10 days once a day. The virus for infection was administered at 5 x 104 TCID50, and the titer of virus and the improvement of pneumonia lesions were measured to confirm the effectiveness in terms of prevention or treatment. In the mouse model infected with original Covid-19 virus stain, the weight loss was significantly reduced and the survival rate was also improved by the administration of gamma-PGA. And gamma-PGA alleviated the pneumonic lesions and reduced the virus titer of lung tissue in mice infected with delta variant. In the deltavariant virus infected hamster model, gamma-PGA showed statistically significant improvement of weight loss and lung inflammation during administration after infection. This is a promising result for possibility of Covid-19 therapeutics along with the efficacy results of mouse model, suggesting gammaPGA can be therapeutic candidate to modulate an innate immune response for Covid-19.
ABSTRACT
The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.
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PurposeThe purpose of this paper was to determine the profile of dairy product consumers in the organic market.Design/methodology/approachThe study was based on a survey questionnaire developed by the author and administered to a total of 1,108 respondents. The statistical analysis (including descriptive statistics, the analysis of the discriminative function and the Chi2 test was performed with the use of Statistica 13.1 PL. The respondents' gender was the factor behind the differences in how they behaved.FindingsThe consumers indicated the channels they rely upon to find information on organic dairy products;in addition to trusting the opinions of their family members and experts, they also use web platforms. Further, they specified their preferred locations for buying favorite products during the pandemic: specialized organic food shops, large distribution chains and online stores.Practical implicationsThese outcomes will help in identifying target consumer segments and information channels for specific information and advertising messages. They also form an important resource for developing some potential strategies which the supply chain stakeholders could implement to promote organic consumption of dairy products.Originality/valueThis study identifies consumers' preferred dairy products;motives for purchasing organic dairy products;barriers that consumers believe exist in the market;sources of knowledge about products purchased by consumers;and consumers' preferred channels for purchasing organic dairy products. To the best of the author's knowledge, this is the first study of dairy product consumers in the organic market in Poland.
ABSTRACT
On the verge of the expiry of land contracts, it is theoretically and practically important to explore the willingness and motivations of farmers to stabilize the land contract relationship, with regards to protecting their land contract rights, addressing potential contradictions during the land contract extension, and maintaining the stability of contracted land. Using China Land Economic Survey Data in 2020, this paper explores the impact of differences in areas per capita of household contracted land on farmers' willingness to stabilize land contract relationship. The findings show that most farmers support the stability of land contract relationship;the smaller areas per capita of contracted land are occupied by households than the average in the village, the weaker of the farmers' willingness to stabilize the land contract relationship. The difference between the areas per capita of contracted land ownership of a household and the average in the village has a greater impact on the willingness to stabilize land contract relationship for middle-and low-income farmers, while the development of land transfer market does not increased the willingness. Affected by the COVID-19 pandemic, the land plays a more important role of employment security, which reduces farmers' willingness to stabilize the land contract relationship. Furthermore, the promotion of socialized agricultural service has also mitigated the willingness of farmers o stabilize the land contract relationship.
ABSTRACT
Coronavirus (COVID-19) is now growing aggressively over the globe and is exceedingly tricky to control due to the lack of available treatments or vaccines. Multiple investigations are now underway with the aim of identifying suitable herbal remedies and phytochemicals to reduce the incidence of COVID-19. In conclusion, certain herbal medications and phytopharmaceuticals could be a potential treatment strategy for mitigating SARS-CoV-2 hazards. Extensive research has been performed in pursuit of fresh options, including the use of phytochemical substances, which, in agreement with previous research, are not only promising against SARS-CoV-2, but also as coadjuvants in other diseases like diabetes. In addition, plants have been used for eras to cure a variety of infections, and exploration with plant-based natural products has been emphasized by the low toxicity of their metabolites and minimal side effects. In this chapter, we draw attention to various plant species and phytochemicals, a few of them belonging to the structural classes like phenolic, alkaloids, and terpenes with significant antiviral efficacy against SARS-CoV-2 that could be investigated as prospective medicines for the treatment of COVID-19. © 2023 Elsevier Inc. All rights reserved.
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The coronavirus outbreak has resulted in unprecedented measures, forcing authorities to make decisions related to establishing lockdowns in areas most affected by the pandemic. Social Media have supported people during this difficult time. On November 9, 2020, when the first vaccine with an efficacy rate over 90% was announced, social media reacted and people around the world began to express their feelings about this vaccination. This paper aims to analyze the dynamics of opinion on COVID-19 vaccination, in which the civil society is highly manifested in the vaccination process. We compared classical machine learning algorithms to select the best performing classifier. 4,392 tweets were collected and analyzed. The proposed approach can help governments create and evaluate appropriate communication tools to provide clear and relevant information to the general public, increasing public confidence in vaccination campaigns. © 2022 Copyright for this paper by its authors.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is a fatal pandemic viral disease caused by the severe acute respiratory syndrome corona virus type-2 (SARS-CoV-2). The aim of this study is to observe the associations of IL-6, SARS-COV-2 viral load (RNAemia), IL- 6 gene polymorphism and lymphocytes and monocytes in peripheral blood with disease severity in COVID-19 patients. This study was carried out from March 2021 to January 2022. RT-PCR positive 84 COVID-19 patients and 28 healthy subjects were enrolled. Blood was collected to detect SARS-COV-2 viral RNA (RNAemia) by rRT-PCR, serum IL-6 level by chemiluminescence method, SNPs of IL-6 by SSP-PCR, immunophenotyping of lymphocytes and monocyte by flow cytometry. Serum IL-6 level (pg/ml) was considerably high among critical patients (102.02 +/- 149.7) compared to severe (67.20 +/- 129.5) and moderate patients (47.04 +/- 106.5) and healthy controls (3.5 +/- 1.8). Serum SARS-CoV-2 nucleic acid positive cases detected mostly in critical patients (39.28%) and was correlated with extremely high IL-6 level and high mortality (R =.912, P < 0.001). Correlation between IL-6 and monocyte was statistically significant with disease severity (severe group, p < 0.001, and 0.867*** and critical group p < 0.001 and 0.887***). In healthy controls, moderate, severe and critically ill COVID-19 patients, IL-6 174G/C (rs 1800795) GG genotype was 82.14%, 89.20%, 67.85% and 53.57% respectively. CC and GC genotype had strong association with severity of COVID-19 when compared with GG genotype. Significant statistical difference found in genotypes between critical and moderate groups (p < 0.001, OR-10.316, CI-3.22-23.86), where CC genotype was associated with COVID-19 severity and mortality. The absolute count of T cell, B cell, NK cell, CD4+ T cells and CD8+ T cells were significantly decreased in critical group compared to healthy, moderate and severe group (P < 0.001). Exhaustion marker CD94/NKG2A was increased on NK cells and CD8+ cytotoxic T cell among critical and severe group. Absolute count of monocyte was significantly increased in critical group (P < 0.001). Serum IL-6, IL-6 174 G/C gene and SARS-CoV-2 RNAaemia can be used in clinical practice for risk assessment;T cell subsets and monocyte as biomarkers for monitoring COVID-19 severity. Monoclonal antibody targeting IL-6 receptor and NKG2A for therapeutics may prevent disease progression and decrease morbidity and mortality.Copyright © 2023 Elsevier Inc.
ABSTRACT
In March 2020, a large number of people moved from cities to their homes in rural areas, and a few months later, many returned to cities. These journeys were undertaken not only during the COVID-19 pandemic against the advisory of governments and public health experts, but the circumstances of travel were also under extreme hardship. How may we understand this intense response by people? By drawing on the migration theory and the roles of social ties or social organisation, we can better explain peoples' reactions during this pandemic. Notably, we find non-material values, such as the dignity of labour or responsibilities to family, are significant to decision -making, and there is a desire not to compromise on these values. Further, our analyses find that the distinction between pre-disaster and post-disaster situations may not be helpful.
ABSTRACT
On social media, misinformation can spread quickly, posing serious problems. Understanding the content and sensitive nature of fake news and misinformation is critical to prevent the damage caused by them. To this end, the characteristics of information must first be discerned. In this paper, we propose a transformer-based hybrid ensemble model to detect misinformation on the Internet. First, false and true news on Covid-19 were analyzed, and various text classification tasks were performed to understand their content. The results were utilized in the proposed hybrid ensemble learning model. Our analysis revealed promising results, establishing the capability of the proposed system to detect misinformation on social media. The final model exhibited an excellent F1 score (0.98) and accuracy (0.97). The AUC (Area Under The Curve) score was also high at 0.98, and the ROC (Receiver Operating Characteristics) curve revealed that the true-positive rate of the data was close to one in this model. Thus, the proposed hybrid model was demonstrated to be successful in recognizing false information online. © 2022 IEEE.
ABSTRACT
The world is becoming a place where the number of emergencies and humanitarian crises is increasing rapidly due to economic inequality and the gap between developed and underdeveloped countries, as well as climate changes leading to disruption of the natural balance and development of natural disasters. The most vulnerable groups of the population including women and children always are affected by disasters. The younger the child, the more vulnerable he/she is, especially if not naturally fed or having a mother or parents. Various humanitarian organizations have been involved in a number of crises, with the World Health Organization and UNICEF and other United Nations-related organizations leading the way. In the care of mothers, infants and young children, most important is to ensure appropriate nutrition because otherwise it can result in life-threatening health conditions. The lack of protection, support and promotion of natural nutrition (breastfeeding) and its disruption and undermining by uncritical and uncontrolled donations and distribution of infant formula are the biggest challenge due to the lack of information of mothers, those who provide support in emergencies from both governmental and non-governmental sector, without cross-sectoral cooperation, thus causing uncoordinated and sometimes harmful interventions. Therefore, it is recommended that governments issue guidelines on infant and young child nutrition prior to the occurrence of an emergency, and crisis management regulations in which the issue of infant and young child nutrition will be given due consideration.Copyright © 2020 Croatian Paediatric Society. All rights reserved.
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Case history: We present the case of a 31-year-old Hispanic male with history of recurrent bronchiectasis, invasive aspergillosis, and severe persistent asthma, who is now status post lung transplant for end-stage lung disease. He initially presented at 7 years of age with diarrhea, failure to thrive, and nearly absent immunoglobulin levels (IgG < 33 mg/dL, IgA < 7 mg/dL, IgM = 11 mg/dL, IgE = 4 IU/dL) necessitating IVIG treatment. Small intestinal biopsy showed villous atrophy consistent with autoimmune enteropathy. Sweat chloride was reported as indeterminate (44 me/dL). Initial WBC, platelet, and T- and NK-cell counts were within normal range, and B-cell count and percentage were borderline low. Most recently, he was found to have increased immature B-cell count (CD21low), decreased memory B-cells, and poor pneumococcal vaccine antibody response. Patient has been hospitalized numerous times with increasingly severe bronchiectasis, pneumonitis, and COVID-19 infections twice despite vaccination, leading to respiratory failure and lung transplantation. Family history is negative for immune deficiency and lung diseases. Discussion(s): Of these 3 VUSs (see the table), the one in IRF2BP2 has the most pathogenic potential due to its autosomal dominant inheritance, its location in a conserved domain (Ring), and previous case reports of pathogenic variants at the same or adjacent alleles 1-3. Baxter et al reported a de novo truncating mutation in IRF2BP2 at codon 536 (c.1606CinsTTT), which is similar to our patient's mutation. This patient was noted to have an IPEX-like presentation, with chronic diarrhea, hypogammaglobulinemia, and recurrent infections. Variant Functional Prediction Score for our variant predicts a potentially high damage effect. There are 2 other case reports of heterozygous mutations in loci adjacent to this allele;one (c.1652G>A)2 with a similar clinical phenotype to our patient and the other (C.625-665 del)3 with primarily inflammatory features and few infections. Impact: This case highlights a variant in IRF2BP2 associated with severe hypogammaglobulinemia, recurrent pulmonary infections, and autoimmune enteropathy. [Table presented]Copyright © 2023 Elsevier Inc.
ABSTRACT
[...]it is often argued—as by Yifei Li and Judith Shapiro, for example—that China's dictatorship should be an advantage in this context: ‘Given the limited time that remains to mitigate climate change and protect millions of species from extinction, we need to consider whether a green authoritarianism can show us the way' (Li and Shapiro 2020, quoted from the publisher's book description). Since CCP bosses do not have to contend with public hearings, environmental studies, recalcitrant legislatures, labour unions, a critical press, and so on, Xi should be able to force state-owned polluters to stop polluting or else, and ram through his promised transition to renewable energy (see Smith 2017, 2020c). Climate Action Tracker estimates that in 2021 China's emissions increased by 3.4 per cent to 14.1 gigatonnes of carbon dioxide equivalent (GtCO2e)—nearly triple those of the United States (4.9 GtCO2e) with a gross domestic product just three-fourths as large (CAT n.d.;EIA 2022). Since 2019, China's emissions have exceeded those of all developed countries combined and presently account for 33 per cent of total global emissions (Larsen et al. 2021;IEA 2021). In the first half of 2021, rebounding from the first wave of Covid-19, China's carbon dioxide emissions surged past pre-pandemic levels to reach an all-time high 20 per cent increase in the second quarter before dropping back in late 2021 and the first half of 2022 as the real estate collapse, Omicron lockdowns, and drought-induced hydropower reductions slashed economic growth to near zero in the summer (Hancock 2021;Myllyvirta 2022a;Riordan and Hook 2022). China promised to stop building coal-fired power plants abroad, but it is building more than 200 new coal-fired plants at home in a drive to boost economic growth, maintain jobs in coal-dependent regions, and ensure energy self-sufficiency—locking the country into coal reliance for many decades to come, derailing the transition to renewables, and dooming Xi's UN pledge to transition to a green and low-carbon mode of development (Xie 2020).
ABSTRACT
This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.
ABSTRACT
Severe acute respiratory syndrome coronavirus (SARS-CoV-2), the causative agent of the current COVID-19 pandemic, has evolved to have a wide range of hosts, including non-human primates, wild and domestic animals. Determining the susceptibility of different animal species to SARS-CoV-2 infection and the role of animals in the epidemiology of the disease will be critical to designing appropriate human and veterinary public health responses to this pandemic. A better understanding of the susceptibility of animal species to SARS-CoV-2 may help clarify transmission mechanisms and identify potential reservoirs and sources of infection that are important for both animal and human health. The current pandemic produced by SARS CoV-2 and its variants represents an example of the unique concept of health (One Health) in which humans and animals are components of the same epidemiological chain. In this paper, only the natural infections found in different animals species will be reviewed, according to literature data, regarding the species of affected animals, the transmission patterns (human-animal, animal-human), clinical aspects, diagnosis confirmation and a brief presentation of the prevention possibilities through vaccination.
ABSTRACT
BackgroundAnti-MDA5 antibody-positive dermatomyositis (anti-MDA5+DM) is a rare autoimmune disease associated with a high mortality rate due to rapid-progressive interstitial lung disease (RP-ILD), particularly in East Asia[1]. MDA5, acts as a cytoplasmic sensor of viral RNA, thus activating antiviral responses including the type I interferon (IFN) signaling pathway[2]. The involvement of type 1 IFN in the pathogenesis of MDA5+DM has been proposed based on the significantly elevated expression of its downstream stimulated genes(ISG) in muscle, skin, lung, and peripheral blood[3;4]. Janus kinase inhibitor, which targets the IFN pathway, combined with glucocorticoid could improve the survival of early-stage MDA5+DM-ILD patients[5]. In clinical practice, there is still an urgent demand for sensitive biomarkers to facilitate clinical risk assessment and precise treatment.ObjectivesThis study aimed to investigate the clinical significance of interferon score, especially IFN-I score, in patients with anti-MDA5+DM.MethodsDifferent subtypes of idiopathic inflammatory myopathy, including anti-MDA5+DM(n=61), anti-MDA5-DM(n=20), antisynthetase syndrome(ASS,n=22),polymyositis(PM,n=6) and immune-mediated necrotizing myopathy(IMNM,n=9), and 58 healthy controls were enrolled.. A multiplex quantitative real-time PCR(RT-qPCR) assay using four TaqMan probes was utilized to evaluate two type I ISGs (IFI44, MX1, which are used for IFN-I score), one type II ISG (IRF1), and one housekeeping gene (HRPT1). Clinical features and disease activity index were compared between high and low IFN-I score groups in 61 anti-MDA5+DM patients. The association between laboratory findings and the predictive value of baseline IFN-I score level for mortality was analyzed.ResultsThe IFN scores were significantly higher in patients with anti-MDA5+DM than in HC (Figure 1A). The IFN-I score correlated positively with serum IFN α(r = 0.335, P =0.008), ferritin (r = 0.302, P = 0.018), and Myositis Disease Activity Assessment Visual Analogue Scale (MYOACT) score(r=0.426, P=0.001). Compared with patients with low IFN-I scores, patients with high IFN-I scores showed increased MYOACT score, CRP, AST, ferritin, and the percentages of plasma cells (PC%) but decreased lymphocyte count, natural killer cell count, and monocyte count. The 3-month survival rate was significantly lower in patients with IFN-I score > 4.9 than in those with IFN-I score ≤ 4.9(72.9% vs. 100%, P=0.044)(Figure 1B).ConclusionIFN score, especially IFN-I score, detected by multiplex RT-qPCR, can be a valuable biomarker for monitoring disease activity and predicting mortality in anti-MDA5+DM patients.References[1]I.E. Lundberg, M. Fujimoto, J. Vencovsky, R. Aggarwal, M. Holmqvist, L. Christopher-Stine, A.L. Mammen, and F.W. Miller, Idiopathic inflammatory myopathies. Nat Rev Dis Primers 7 (2021) 86.[2]G. Liu, J.H. Lee, Z.M. Parker, D. Acharya, J.J. Chiang, M. van Gent, W. Riedl, M.E. Davis-Gardner, E. Wies, C. Chiang, and M.U. Gack, ISG15-dependent activation of the sensor MDA5 is antagonized by the SARS-CoV-2 papain-like protease to evade host innate immunity. Nat Microbiol 6 (2021) 467-478.[3]G.M. Moneta, D. Pires Marafon, E. Marasco, S. Rosina, M. Verardo, C. Fiorillo, C. Minetti, L. Bracci-Laudiero, A. Ravelli, F. De Benedetti, and R. Nicolai, Muscle Expression of Type I and Type II Interferons Is Increased in Juvenile Dermatomyositis and Related to Clinical and Histologic Features. Arthritis Rheumatol 71 (2019) 1011-1021.[4]Y. Ye, Z. Chen, S. Jiang, F. Jia, T. Li, X. Lu, J. Xue, X. Lian, J. Ma, P. Hao, L. Lu, S. Ye, N. Shen, C. Bao, Q. Fu, and X. Zhang, Single-cell profiling reveals distinct adaptive immune hallmarks in MDA5+ dermatomyositis with therapeutic implications. Nat Commun 13 (2022) 6458.[5]Z. Chen, X. Wang, and S. Ye, Tofacitinib in Amyopathic Dermatomyositis–Associated Interstitial Lung Disease. New England Journal of Medicine 381 (2019) 291-293.AcknowledgementsThis work was supported by the National Natural Science Foundation of China [81974251], and Shanghai Hospital Develop ent Center, Joint Research of New Advanced Technology Project [SHDC12018106]Disclosure of InterestsNone Declared.
ABSTRACT
Microblogging sites such as Twitter play an important role in dealing with various mass emergencies including natural disasters and pandemics. The FIRE 2022 track on Information Retrieval from Microblogs during Disasters (IRMiDis) focused on two important tasks – (i) to detect the vaccine-related stance of tweets related to COVID-19 vaccines, and (ii) to detect reporting of COVID-19 symptom in tweets. © 2022 Copyright for this paper by its authors.