An Emerging Role of Interferon Targeted Therapy in Mucocutaneous Sle: A Prospective Real-World Evaluation of Anifrolumab for Refractory Cutaneous Lupus

Background/Aims Advances in rational drug design and recent clinical trials are leading to emergence of a range of novel therapies for SLE and therapeutic options in clinical practice are expected to broaden rapidly. The optimal real-world place of emerging and established agents will be guided by understanding their differential efficacy on specific SLE manifestations as well as efficacy for more resistant disease. Anifrolumab, a type-I interferon receptor blocking monoclonal antibody, showed efficacy in SLE in phase III trials with a notable effect on mucocutaneous disease although specific lesion subtypes and chroncicity were not explored. Severe refractory mucocutaneous SLE such as scarring discoid lesions are an important and common clinical challenge in current practice. We therefore prospectively evaluated the real-world efficacy and quality of life impact of anifolumab for active mucocutaneous SLE, recalcitrant to multiple biologic and immunosuppressant therapies. Methods Seven patients commenced anifrolumab (300mg by monthly iv infusion) following application to the manufacturer's early access programme (NCT 04750057). Prior biologic therapies were discontinued at least 5 half-lives in advance. Mucocutaneous disease activity was captured by Cutaneous Lupus Disease Area and Severity Index (CLASI) activity score and medical photography. Patient reported health-related quality of life comprising the Dermatology Life Quality Index (DLQI);Lupus-QoL and EQ5D-5L were evaluated at baseline, three and six months. Results Seven female patients with active mucocutaneous SLE (Discoid LE n=5, chilblain LE n=1, subacute cutaneous LE n=1) and median disease duration of 17 years were evaluated. Median baseline CLASI activity score was 17 (range 10-26;higher scores indicating severe disease). Median number of previously failed therapies was 7 and included rituximab in 6/7, belimumab in 2/7 and thalidomide in 4/7. Rapid resolution of scale and erythema in DLE was established within 1 month of anifrolumab treatment. Improvements to chilblain lupus were evident by three months. CLASI activity score was improved >=75% in all patients at 3 months. Clinical responses were associated with significant improvements in DLQI (p<0.001) and EQ5D-VAS (p=0.002) by three months. Lupus-QoL trended toward improvement across all domains but most strongly for fatigue (p=0.01) and pain (p=0.002) by 6 months. One patient discontinued treatment after 4 months due to polydermatomal shingles complicated by sensorineural hearing loss. Infection coincided with background prednisolone dose >15mg daily, recent COVID-19 infection and new on-treatment hypogammaglobulinaemia (IgG <5g/L). Prolonged aciclovir treatment was required for lesion resolution. Conclusion We report rapid real-world efficacy and quality of life impact of anifrolumab on highly refractory mucocutaneous SLE, which exceeded that anticipated from existing clinical trial data. Findings suggest a unique role for emerging interferon targeting therapies in management of mucocutaneous SLE but emphasize need for enhanced VZV precautions among higher risk patients.

Learning the Protein Language Model of SARS-CoV-2 Spike Proteins

Ahstract-SARS-CoV-2 virus has long been evolving posing an increased risk in terms of infectivity and transmissibility which causes greater impact in communities worldwide. With the surge of collected SARS-CoV-2 sequences, studies found out that most of the emerging variants are linked to increased mutations in the spike (S) protein as observed in Alpha, Beta, Gamma, and Delta variants. Multiple approaches on genomic surveillance have been performed to monitor the mutational status and spread of the virus however most are heavily dependent on labels attributed to these sequences. Hence, this study features a system that has the capability to learn the protein language model of SARS-CoV-2 spike proteins, based on a bidirectional long-short term memory (BiLSTM) recurrent neural network, using sequence data alone. Upon obtaining the sequence embedding from the model, observed clusters are generated using the Leiden clustering algorithm and is visualized to monitor similarities between variants in terms of grammatical probability and semantic change. Additionally, the system measures the validity of a user-generated next-generation sequence capturing potential sequence mutations indicative of viral escape, particularly mutations by substitutions. Further studies on methods uncovering semantic rules that govern spike proteins are recommended to learn more about other viral characteristics conclusive of the future of the COVID-19 pandemic. © 2023 IEEE.

Forecasting COVID-19 Cases Using n-SARS-CoV-2 Variants

This work proposes a novel Deep Learning-based model to forecast the total number of confirmed COVID-19 cases in four of the worst-hit states of India. Along with statewide restrictions and public holidays, a novel parameter is introduced for training the proposed model, which considers the Alpha, Beta, Delta, and Omicron variants and the degree of their prevalence in each of the four states. Recurrent Neural Network-based Long-Short Term Memory is applied to the custom dataset, with the lowest Mean Absolute Percentage Error being 0.77% for the state of Maharashtra. SHapley Additive exPlanations values are used to examine the significance of the various parameters. The proposed model can be applied to other countries and can include newer variants of the novel coronavirus discovered in the future. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Detection of Covid-19 Using CT-Scan Images and Deep Transfer Learning

Several variants of the severe acute respiratory syndrome (SARS-Cov2) were identified globally in recent times. According to the survey conducted by World Health Organization (WHO) in the year 2021, there were four dominant variants of the virus, which were named alpha, beta, gamma, and delta, respectively. Radiological examinations such as CT scan and chest X-rays are considered to be effective clinical examinations that determine the presence of viruses in the human body. The study of these radiological examinations aids to prevent the spread of the virus and supports in treating the patients effectively. This paper aims to discuss various aspects of covid-19 and describes an automated system that uses the CT-scan images to diagnose covid-19. The proposed method uses deep learning technique along with SoftMax activation function and was found to be effective in determining the novel virus. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

In Silico Approach for the Evaluation of the Potential Antiviral Activity of Extra Virgin Olive Oil (EVOO) Bioactive Constituents Oleuropein and Oleocanthal on Spike Therapeutic Drug Target of SARS-CoV-2.

Since there is an urgent need for novel treatments to combat the current coronavirus disease 2019 (COVID-19) pandemic, in silico molecular docking studies were implemented as an attempt to explore the ability of selected bioactive constituents of extra virgin olive oil (EVOO) to act as potent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) antiviral compounds, aiming to explore their ability to interact with SARS-CoV-2 Spike key therapeutic target protein. Our results suggest that EVOO constituents display substantial capacity for binding and interfering with Spike (S) protein, both wild-type and mutant, via the receptor-binding domain (RBD) of Spike, or other binding targets such as angiotensin-converting enzyme 2 (ACE2) or the RBD-ACE2 protein complex, inhibiting the interaction of the virus with host cells. This in silico study provides useful insights for the understanding of the mechanism of action of the studied compounds at a molecular level. From the present study, it could be suggested that the studied active phytochemicals could potentially inhibit the Spike protein, contributing thus to the understanding of the role that they can play in future drug designing and the development of anti-COVID-19 therapeutics.

Performance Analysis of the Triple Exponential Smoothing Method during the Covid19 Pandemic on Tourist Visit Data

Data forecasting methods are essential in the business world to determine the company's future steps. However, the COVID-19 pandemic has hit the tourism economy hard, resulting in a slump in income. In this study, trials were conducted to analyze the reliability of forecasting methods on data affected by the COVID-19 pandemic. The method used is the Triple Exponential Smoothing method involving two models, namely Additive and Multiplicative. In this paper, the test is carried out using actual data derived from data from a service company engaged in tourist crossing transportation. Each method's alpha, beta, and gamma values are determined based on the parameters that produce the smallest error value. The experiment results show the predictability of the Triple Exponential Smoothing method by measuring the prediction error value based on the Mean Absolute Percentage Error (MAPE) value, which was 7.56% in the Additive model and 10.32% in the Multiplicative model before the pandemic happened. However, both methods' prediction measurements during a pandemic produce poor forecasts with an error percentage above 40%. Meanwhile, during the decline in pandemic cases, the value of the Triple Exponential Smoothing Multiplicative method was closer to the actual data with a prediction error value of 33.02%. Therefore, the Triple Exponential Smoothing Multiplicative method is more resistant and suitable for implementing into a forecasting system with actual data that influences pandemic events. © 2022 IEEE.

Interferon-mediated Responses to Human Metapneumovirus

Background: Acute respiratory infection (ARI) is the leading infectious cause of pediatric death worldwide, comprising 15% of all deaths in children under 5 years old. Human metapneumovirus (HMPV) is a primary cause of ARI, and accounts for a major portion of ARI-related hospitalizations in infants and young children. Although nearly every person is infected with HMPV during early childhood, re-infections occur often, highlighting the difficulty in building long-term immunity. There are no approved vaccines or antiviral therapies. Early host responses to HMPV are poorly characterized, and further understanding could identify important antiviral pathways and potential therapeutic targets. Type I (IFN-α/β) and III interferons (IFN-λ) display antiviral activity against numerous respiratory viruses and are currently being investigated for therapeutic use in several respiratory infections including SARS-CoV-2. However, their roles in HMPV infection remain largely unknown. Our laboratory has previously shown that type I IFN is critical for HMPV pathogenesis, as loss of IFN-α/β signaling reduces lung inflammation and lessens HMPV disease severity in mice. Here, we describe distinct antiviral roles for type I and III IFNs during HMPV infection using an established mouse model. Methods: In vivo studies were conducted using mice lacking either the IFN-α/ β receptor (IFNAR-/-) or IFN-λ receptor (IFNLR-/-). Early immune responses to HMPV strains TN/94-49 and C2-202 were assessed by clinical disease scoring, plaque assay, Luminex immunoassay, and spectral cytometry of mouse lung samples. In vitro studies were performed using CMT 64-61 mouse bronchial epithelial cells. Responses to TN/94-49 and C2-202 were measured by qPCR, plaque assay, and Luminex immunoassay of cell lysates and supernatants. Results: IFNAR-/- mice exhibited lower clinical disease scores, reduced lung levels of inflammatory cytokines IL6, MIP-1α, and MCP-1, and decreased numbers of lung interstitial macrophages during HMPV infection, highlighting their critical role in HMPV immune-mediated pathogenesis. IFNLR-/- mice with intact IFNAR showed moderate clinical disease, higher lung levels of inflammatory cytokines IL-6, MCP-1, and IFN-γ, and increased lung interstitial macrophage recruitment. A reduction in HMPV disease was also recapitulated by IFNAR-neutralizing antibody treatment of IFNLR-/- mice. Interestingly, IFNLR-/- showed higher HMPV viral titers, while IFNAR-/- mice showed no differences or slightly lower viral titers, compared to wild-type mice. Moreover, IFN-λ pre-treatment of infected CMT 64-61 cells reduced HMPV viral titers and decreased supernatant levels of inflammatory cytokines IL-6, IL-1β, TNFα, and MCP-1. Conclusion: These findings suggest that type I IFN is necessary for HMPV pathogenesis, while type III IFN is critical for limiting HMPV replication in the lungs but does not contribute to HMPV inflammatory disease. This work uncovers key functional differences between type I and III IFNs during HMPV infection, an important feature of innate immune responses to HMPV that may be utilized to inform treatment.

IFNAR2 relevance in the clinical outcome of individuals with severe COVID-19.

Interferons (IFNs) are a group of cytokines with antiviral, antiproliferative, antiangiogenic, and immunomodulatory activities. Type I IFNs amplify and propagate the antiviral response by interacting with their receptors, IFNAR1 and IFNAR2. In COVID-19, the IFNAR2 (interferon alpha and beta receptor subunit 2) gene has been associated with the severity of the disease, but the soluble receptor (sIFNAR2) levels have not been investigated. We aimed to evaluate the association of IFNAR2 variants (rs2236757, rs1051393, rs3153, rs2834158, and rs2229207) with COVID-19 mortality and to assess if there was a relation between the genetic variants and/or the clinical outcome, with the levels of sIFNAR2 in plasma samples from hospitalized individuals with severe COVID-19. We included 1,202 subjects with severe COVID-19. The genetic variants were determined by employing Taqman® assays. The levels of sIFNAR2 were determined with ELISA in plasma samples from a subgroup of 351 individuals. The rs2236757, rs3153, rs1051393, and rs2834158 variants were associated with mortality risk among patients with severe COVID-19. Higher levels of sIFNAR2 were observed in survivors of COVID-19 compared to the group of non-survivors, which was not related to the studied IFNAR2 genetic variants. IFNAR2, both gene, and soluble protein, are relevant in the clinical outcome of patients hospitalized with severe COVID-19.

Type I IFN Signaling Controls Damage and Clearance During Pulmonary Aspergillus Fumigatus Infection

RATIONALE: Recently, there has been an increased incidence of invasive pulmonary aspergillosis (IPA), caused by the human fungal pathogen Aspergillus fumigatus (Af), occurring in patients infected with influenza or SARS-CoV-2. Along with the recently described involvement of type I interferon (IFN) signaling in increased Af susceptibility during viral infection in mice, this strongly indicates that anti-viral immune responses, such as type I IFNs, create an environment permissive to fungal infection. Supporting this, we found that type I IFN signaling, via the type I IFN receptor 2 (IFNAR2) of IFNAR1/2, contributes to regulation of susceptibility to and damage from influenza in mice, while others have found that IFNAR2 expression correlates with SARS-CoV-2 infection severity. As clinical outcome to Af is associated with host tissue damage, this suggests that IFNAR2's regulation of damage response during pulmonary infection may control the immune status of the lung, via tissue damage, allowing for fungal infection to occur. METHODS: We are utilizing a murine pulmonary infection model, to identify distinct roles for IFNAR2 and IFNAR1 and type I IFN signaling in regulating both damage and clearance during IPA. We employed proteomic, histological, and molecular approaches to determine the components and extent of the damage response. RESULTS: We found that absence of IFNAR2 (Ifnar2-/- mice) resulted in increased damage, weight loss, and morbidity early during Af infection compared to WT and Ifnar1-/- mice. Additionally, we also found that both WT and Ifnar1-/- mice had decreased Af clearance early during infection compared to Ifnar2-/- mice and that this difference in killing of Af required in vivo interactions/signaling. However, as Af infection progressed we found that although Ifnar2-/- mice cleared Af early, this did not prevent invasive hyphal growth from occurring. This invasive growth in the Ifnar2-/- mice was found to be associated with increased damage and cell death in the Af lesions within the lung. Importantly, our results suggest that this IFNAR2 damage response is being mediated by distinct type I IFNs, specifically IFNβ. CONCLUSIONS: Together, our results begin to establish a role for IFNAR2 in regulation of the host damage response to Af and suggests that the type of type I IFN signaling may contribute to a permissive environment allowing for Af infection to occur. Understanding the mechanisms involved in IFNAR regulation of damage and anti-fungal immunity could inform design of better treatments aimed at minimizing damage in patients with IPA or controlling pulmonary tissue damage.

A Review on Deep Learning based diagnosis of COVID-19 from X-ray and CT Images

More than 400 million cases of the new coronavirus (COVID-19) have been confirmed since December 2019 in more than 200 countries. Since the spread of original COVID-19 virus SARS-CoV-2, thousands of mutations have been discovered. The most dominant ones are Alpha, Beta, Gama, Delta and Omicron variants, with the Omicron variant rapidly spreading and dominating the current phase of the COVID wave across the globe. It needs early detection and self-isolation to contain the virus. Molecular tests like rRTPCR are common for its detection. However, with the current spreading rate and lack of availability of large-scale testing laboratories, rapid diagnosis has become difficult. COVID-19 diagnosis from CT and X-ray images using deep learning techniques has been the subject of a lot of research in the last two years. This work presents a review of these studies sourced from top databases such as Web of Science and highlights challenges and research gaps with future research directions. © 2022 IEEE.

All hands on deck: SARS-CoV-2 proteins that block early anti-viral interferon responses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is responsible for the current pandemic coronavirus disease of 2019 (COVID-19). Like other pathogens, SARS-CoV-2 infection can elicit production of the type I and III interferon (IFN) cytokines by the innate immune response. A rapid and robust type I and III IFN response can curb viral replication and improve clinical outcomes of SARS-CoV-2 infection. To effectively replicate in the host, SARS-CoV-2 has evolved mechanisms for evasion of this innate immune response, which could also modulate COVID-19 pathogenesis. In this review, we discuss studies that have reported the identification and characterization of SARS-CoV-2 proteins that inhibit type I IFNs. We focus especially on the mechanisms of nsp1 and ORF6, which are the two most potent and best studied SARS-CoV-2 type I IFN inhibitors. We also discuss naturally occurring mutations in these SARS-CoV-2 IFN antagonists and the impact of these mutations in vitro and on clinical presentation. As SARS-CoV-2 continues to spread and evolve, researchers will have the opportunity to study natural mutations in IFN antagonists and assess their role in disease. Additional studies that look more closely at previously identified antagonists and newly arising mutants may inform future therapeutic interventions for COVID-19.

MicroRNAs based regulation of cytokine regulating immune expressed genes and their transcription factors in COVID-19.

BACKGROUND: Coronavirus disease 2019 is characterized by the elevation of a broad spectrum of inflammatory mediators associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future. METHODS: The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape. RESULTS: Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded ten miRNAs that are significantly involved in regulating these genes and their transcription factors. CONCLUSION: An in-silico representation of a network involving miRNAs, CRIEGs, and TF, which take part in the inflammatory response in COVID-19, has been elucidated. Thus, these regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.

Differential roles of interferons in innate responses to mucosal viral infections.

Interferons (IFNs) are among the first vertebrate immune pathways activated upon viral infection and are crucial for control of viral replication and dissemination, especially at mucosal surfaces as key locations for host exposure to pathogens. Inhibition of viral establishment and spread at and from these mucosal sites is paramount for preventing severe disease, while concomitantly limiting putative detrimental effects of inflammation. Here, we compare the roles of type I, II, and III IFNs in regulating three archetypal viruses - norovirus, herpes simplex virus, and severe acute respiratory virus coronavirus 2 (SARS-CoV-2) - which infect distinct mammalian mucosal tissues. Emerging paradigms include highly specific roles for IFNs in limiting local versus systemic infection, synergistic activities, and a spectrum of protective versus detrimental effects of IFNs during the infection response.

Human Disease Phenotypes Associated with Loss and Gain of Function Mutations in STAT2: Viral Susceptibility and Type I Interferonopathy.

STAT2 is distinguished from other STAT family members by its exclusive involvement in type I and III interferon (IFN-I/III) signaling pathways, and its unique behavior as both positive and negative regulator of IFN-I signaling. The clinical relevance of these opposing STAT2 functions is exemplified by monogenic diseases of STAT2. Autosomal recessive STAT2 deficiency results in heightened susceptibility to severe and/or recurrent viral disease, whereas homozygous missense substitution of the STAT2-R148 residue is associated with severe type I interferonopathy due to loss of STAT2 negative regulation. Here we review the clinical presentation, pathogenesis, and management of these disorders of STAT2.

Differential induction of type I and III interferon genes in the upper respiratory tract of patients with coronavirus disease 2019 (COVID-19).

The natural course of type I and III interferon (IFN) response in the respiratory tract of COVID-19 patients needs to be better defined. We showed that type I/III IFNs, IFN-regulatory factor 7 (IRF7), and IFN stimulated genes (ISGs), are highly expressed in the oropharyngeal cells of SARS-CoV-2 positive patients compared to healthy controls. Notably, the subgroup of critically-ill patients that required invasive mechanical ventilation had a general decrease in expression of IFN/ISG genes. Heterogeneous patterns of IFN-I/III response in the respiratory tract of COVID-19 patients may be associated to COVID-19 severity.

Inhibition of SARS-CoV-2 by type I and type III interferons.

The recently emerged severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative agent of the devastating COVID-19 lung disease pandemic. Here, we tested the inhibitory activities of the antiviral interferons of type I (IFN-α) and type III (IFN-λ) against SARS-CoV-2 and compared them with those against SARS-CoV-1, which emerged in 2003. Using two mammalian epithelial cell lines (human Calu-3 and simian Vero E6), we found that both IFNs dose-dependently inhibit SARS-CoV-2. In contrast, SARS-CoV-1 was restricted only by IFN-α in these cell lines. SARS-CoV-2 generally exhibited a broader IFN sensitivity than SARS-CoV-1. Moreover, ruxolitinib, an inhibitor of IFN-triggered Janus kinase/signal transducer and activator of transcription signaling, boosted SARS-CoV-2 replication in the IFN-competent Calu-3 cells. We conclude that SARS-CoV-2 is sensitive to exogenously added IFNs. This finding suggests that type I and especially the less adverse effect-prone type III IFN are good candidates for the management of COVID-19.