Influenza outbreak during the surge of SARS-CoV-2 omicron in a metropolitan area from southern Brazil: genomic surveillance.

Influenza circulation was significantly affected in 2020-21 by the COVID-19 pandemic. During this time, few influenza cases were recorded. However, in the summer of 2021-22, an increase in atypical influenza cases was observed, leading to the resurgence of influenza in the southernmost state of Brazil, Rio Grande do Sul (RS). The present study aimed to identify the circulation of FLUAV, FLUBV and SARS-CoV-2 and characterize the influenza genomes in respiratory samples using high-throughput sequencing technology (HTS). Respiratory samples (n = 694) from patients in RS were selected between July 2021 and August 2022. The samples were typed using reverse transcriptase real-time PCR (RT-qPCR) and showed 32% (223/694) of the samples to be positive for SARS-CoV-2, 7% for FLUAV (H3) (49/694). FLUBV was not detected. RT-qPCR data also resulted in FLUAV and SARS-CoV-2 co-infections in 1.7% (4/223) of samples tested. Whole genome sequencing of FLUAV produced 15 complete genomes of the H3N2 subtype, phylogenetically classified in the 3C.2a1b.2a.2a.3 subclade and revealing the dominance of viruses in the southern region of Brazil. Mutation analysis identified 72 amino acid substitutions in all genes, highlighting ongoing genetic evolution with potential implications for vaccine effectiveness, viral fitness, and pathogenicity. This study underscores limitations in current surveillance systems, advocating for comprehensive data inclusion to enhance understanding of influenza epidemiology in southern Brazil. These findings contribute valuable insights to inform more effective public health responses and underscore the critical need for continuous genomic surveillance.

Detection of Neutralizing Antibodies in Serum Samples Using a SARS-CoV-2 Pseudotyped Virus Assay.

Conventional live virus research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease-19 (COVID-19), requires Biosafety Level 3 (BSL-3) facilities. SARS-CoV-2 pseudotyped viruses have emerged as valuable tools in virology, mimicking the entry process of the SARS-CoV-2 virus into human cells by expressing its spike glycoprotein in a surrogate system using recombinant plasmids. One significant application of this tool is in functional assays for the evaluation of neutralizing antibodies. Pseudotyped viruses have the advantage of being competent for only a single cycle of infection, providing better safety and versatility and allowing them to be studied in BSL-2 laboratories. Here, we describe three protocols for the detection of SARS-CoV-2 neutralizing antibodies through a pseudotyped virus assay. First, SARS-CoV-2 S pseudotyped viruses (PV SARS-CoV-2 S) are produced using a Moloney murine leukemia virus (MuLV) three-plasmid system. The plasmids are designed to express the GagPol packing proteins, enhanced green fluorescent protein (eGFP) as a readout system, and the SARS-CoV-2 S protein modified to remove the endoplasmic reticulum retention domain and to improve infection. Next, the internalization of PV SARS-CoV-2 S protein in human embryonic kidney 293T (HEK-293T) cells overexpressing angiotensin-converting enzyme 2 (HEK-293T-ACE2) is confirmed by fluorescence microscopy and quantified using flow cytometry. Finally, PV SARS-CoV-2 S is used to screen neutralizing antibodies in serum samples from convalescent COVID-19 patients; it can also be used for studying the cell entry mechanisms of different SARS-CoV-2 variants, evaluating antiviral agents, and designing vaccines. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Generation of PV SARS-CoV-2 S pseudotyped virus Basic Protocol 2: Assay of PV SARS-CoV-2 S internalization in target cells. Basic Protocol 3: Detection of neutralizing antibodies in serum samples.

In Silico Design of miniACE2 Decoys with In Vitro Enhanced Neutralization Activity against SARS-CoV-2, Encompassing Omicron Subvariants.

The COVID-19 pandemic has overwhelmed healthcare systems and triggered global economic downturns. While vaccines have reduced the lethality rate of SARS-CoV-2 to 0.9% as of October 2024, the continuous evolution of variants remains a significant public health challenge. Next-generation medical therapies offer hope in addressing this threat, especially for immunocompromised individuals who experience prolonged infections and severe illnesses, contributing to viral evolution. These cases increase the risk of new variants emerging. This study explores miniACE2 decoys as a novel strategy to counteract SARS-CoV-2 variants. Using in silico design and molecular dynamics, blocking proteins (BPs) were developed with stronger binding affinity for the receptor-binding domain of multiple variants than naturally soluble human ACE2. The BPs were expressed in E. coli and tested in vitro, showing promising neutralizing effects. Notably, miniACE2 BP9 exhibited an average IC50 of 4.9 µg/mL across several variants, including the Wuhan strain, Mu, Omicron BA.1, and BA.2 This low IC50 demonstrates the potent neutralizing ability of BP9, indicating its efficacy at low concentrations.Based on these findings, BP9 has emerged as a promising therapeutic candidate for combating SARS-CoV-2 and its evolving variants, thereby positioning it as a potential emergency biopharmaceutical.

A novel viral RNA detection method based on the combined use of trans-acting ribozymes and HCR-FRET analyses.

The diagnoses of retroviruses are essential for controlling the rapid spread of pandemics. However, the real-time Reverse Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR), which has been the gold standard for identifying viruses such as SARS-CoV-2 in the early stages of infection, is associated with high costs and logistical challenges. To innovate in viral RNA detection a novel molecular approach for detecting SARS-CoV-2 viral RNA, as a proof of concept, was developed. This method combines specific viral gene analysis, trans-acting ribozymes, and Fluorescence Resonance Energy Transfer (FRET)-based hybridization of fluorescent DNA hairpins. In this molecular mechanism, SARS-CoV-2 RNA is specifically recognized and cleaved by ribozymes, releasing an initiator fragment that triggers a hybridization chain reaction (HCR) with DNA hairpins containing fluorophores, leading to a FRET process. A consensus SARS-CoV-2 RNA target sequence was identified, and specific ribozymes were designed and transcribed in vitro to cleave the viral RNA into fragments. DNA hairpins labeled with Cy3/Cy5 fluorophores were then designed and synthesized for HCR-FRET assays targeting the RNA fragment sequences resulting from ribozyme cleavage. The results demonstrated that two of the three designed ribozymes effectively cleaved the target RNA within 10 minutes. Additionally, DNA hairpins labeled with Cy3/Cy5 pairs efficiently detected target RNA specifically and triggered detectable HCR-FRET reactions. This method is versatile and can be adapted for use with other viruses. Furthermore, the design and construction of a DIY photo-fluorometer prototype enabled us to explore the development of a simple and cost-effective point-of-care detection method based on digital image analysis.

Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2.

Molecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based approaches have led to the understanding of specific structural changes observed in MD trajectories, including those induced by mutations. In this study, we model the trajectories resulting from MD simulations of the SARS-CoV-2 spike protein-ACE2, specifically the receptor-binding domain (RBD), as interresidue distance maps, and use deep convolutional neural networks to predict the functional impact of point mutations, related to the virus's infectivity and immunogenicity. Our model was successful in predicting mutant types that increase the affinity of the S protein for human receptors and reduce its immunogenicity, both based on MD trajectories (precision = 0.718; recall = 0.800; [Formula: see text] = 0.757; MCC = 0.488; AUC = 0.800) and their centroids. In an additional analysis, we also obtained a strong positive Pearson's correlation coefficient equal to 0.776, indicating a significant relationship between the average sigmoid probability for the MD trajectories and binding free energy (BFE) changes. Furthermore, we obtained a coefficient of determination of 0.602. Our 2D-RMSD analysis also corroborated predictions for more infectious and immune-evading mutants and revealed fluctuating regions within the receptor-binding motif (RBM), especially in the [Formula: see text] loop. This region presented a significant standard deviation for mutations that enable SARS-CoV-2 to evade the immune response, with RMSD values of 5Å in the simulation. This methodology offers an efficient alternative to identify potential strains of SARS-CoV-2, which may be potentially linked to more infectious and immune-evading mutations. Using clustering and deep learning techniques, our approach leverages information from the ensemble of MD trajectories to recognize a broad spectrum of multiple conformational patterns characteristic of mutant types. This represents a strategic advantage in identifying emerging variants, bypassing the need for long MD simulations. Furthermore, the present work tends to contribute substantially to the field of computational biology and virology, particularly to accelerate the design and optimization of new therapeutic agents and vaccines, offering a proactive stance against the constantly evolving threat of COVID-19 and potential future pandemics.

Sputnik V-Induced Antibodies against SARS-CoV-2 Variants during the Dissemination of the Gamma Variant in Venezuela.

The COVID-19 pandemic was characterized by the emergence and succession of SARS-CoV-2 variants able to evade the antibody response induced by natural infection and vaccination. To evaluate the IgG reactivity and neutralizing capacity of the serum of individuals vaccinated with Sputnik V (105 volunteers vaccinated) against different viral variants. IgG reactivity to the Spike protein (S) was evaluated by ELISA. A plaque reduction neutralization test was performed using different viral variant isolates. At 42 days post-vaccination, the frequency of recognition and reactivity to the S protein of the Omicron variant was lower compared to that of the other variants. In general, a higher average neutralization titer was seen against the ancestral variant compared to the variants, especially Omicron. However, some sera exhibited a higher neutralization titer to the Gamma variant compared to the ancestral variant, suggesting unapparent exposure during the clinical trial. Antibodies induced by Sputnik V can recognize, persist, and neutralize SARS-CoV-2 variants, with Omicron being the one that best evades this response. These results represent a unique report on the humoral response induced by a globally lesser-studied vaccine in terms of efficacy and immune escape, offering insights into developing vaccines targeting unknown coronaviruses.

Diagnosis of viral infectious diseases through sensitive detection of human serum antibodies using a modified label-free electrochemical biosensor.

Rapid virus identification is crucial for preventing outbreaks. The COVID-19 pandemic has highlighted the critical nature of rapid virus detection. Here, we designed a label-free electrochemical biosensor modified with gold nanoparticles (AuNPs) to detect IgG antibodies from human serum, enabling rapid point-of-care diagnostics. AuNPs were synthesized and characterized. A multivariate optimization was carried out to determine the optimal condition for functionalizing AuNPs with anti-IgG. Subsequently, using a glassy carbon electrode (GCE), a modified AuNPs/GCE electrochemical biosensor was developed for IgG detection. The results indicated that AuNPs displayed a spherical morphology with a size distribution of 19.54 nm. Additionally, the zeta potential was recorded at -7.84 mV. Central composite design (CCD) analysis determined the optimal conditions for functionalizing AuNPs to be an anti-IgG concentration of 320 µg mL-1, a temperature of 25 °C, and pH of 7.4. The characterization study confirmed the successful synthesis and functionalization of AuNPs. Through electrochemical impedance spectroscopy measurement, the biosensor demonstrated a limit of detection (LOD) of 0.2 ng mL-1 and limit of quantification (LOQ) of 0.8 ng mL-1. Furthermore, tests in real samples showed the interaction between IgG antibodies in serum samples and AuNPs/GCE, confirming the biosensor's ability to detect and quantify IgG in clinical samples.

Overcoming Limited Access to Virus Infection Rapid Testing: Development of a Lateral Flow Test for SARS-CoV-2 with Locally Available Resources.

The COVID-19 pandemic highlighted testing inequities in developing countries. Lack of lateral flow test (LFT) manufacturing capacity was a major COVID-19 response bottleneck in low- and middle-income regions. Here we report the development of an open-access LFT for SARS-CoV-2 detection comparable to commercial tests that requires only locally available supplies. The main critical resource is a locally developed horse polyclonal antibody (pAb) whose sensitivity and selectivity are greatly enhanced by affinity purification. We demonstrate that these Abs can perform similarly to commercial monoclonal antibodies (mAbs), as well as mAbs and other pAbs developed against the same antigen. We report a workflow for test optimization using nasopharyngeal swabs collected for RT-qPCR, spiked with the inactivated virus to determine analytical performance characteristics as the limit of detection, among others. Our final prototype showed a performance similar to available tests (sensitivity of 83.3% compared to RT-qPCR, and 90.9% compared to commercial antigen tests). Finally, we discuss the possibility and the challenges of utilizing affinity-purified pAbs as an alternative for the local development of antigen tests in an outbreak context and as a tool to address inequalities in access to rapid tests.

Optimizing next-generation sequencing efficiency in clinical settings: analysis of read length impact on cost and performance.

BACKGROUND: The expansion of sequencing technologies as a result of the response to the COVID-19 pandemic enabled pathogen (meta)genomics to be deployed as a routine component of surveillance in many countries. Scaling genomic surveillance, however, comes with associated costs in both equipment and sequencing reagents, which should be optimized. Here, we evaluate the cost efficiency and performance of different read lengths in identifying pathogens in metagenomic samples. We carefully evaluated performance metrics, costs, and time requirements relative to choices of 75, 150 and 300 base pairs (bp) read lengths in pathogen identification. RESULTS: Our findings revealed that moving from 75 bp to 150 bp read length approximately doubles both the cost and sequencing time. Opting for 300 bp reads leads to approximately two- and three-fold increases, respectively, in cost and sequencing time compared to 75 bp reads. For viral pathogen detection, the sensitivity median ranged from 99% with 75 bp reads to 100% with 150-300 bp reads. However, bacterial pathogens detection was less effective with shorter reads: 87% with 75 bp, 95% with 150 bp, and 97% with 300 bp reads. These findings were consistent across different levels of taxa abundance. The precision of pathogen detection using shorter reads was comparable to that of longer reads across most viral and bacterial taxa. CONCLUSIONS: During disease outbreak situations, when swift responses are required for pathogen identification, we suggest prioritizing 75 bp read lengths, especially if detection of viral pathogens is aimed. This practical approach allows better use of resources, enabling the sequencing of more samples using streamlined workflows, while maintaining a reliable response capability.

Text mining method to unravel long COVID's clinical condition in hospitalized patients.

Long COVID is characterized by persistent that extends symptoms beyond established timeframes. Its varied presentation across different populations and healthcare systems poses significant challenges in understanding its clinical manifestations and implications. In this study, we present a novel application of text mining technique to automatically extract unstructured data from a long COVID survey conducted at a prominent university hospital in São Paulo, Brazil. Our phonetic text clustering (PTC) method enables the exploration of unstructured Electronic Healthcare Records (EHR) data to unify different written forms of similar terms into a single phonemic representation. We used n-gram text analysis to detect compound words and negated terms in Portuguese-BR, focusing on medical conditions and symptoms related to long COVID. By leveraging text mining, we aim to contribute to a deeper understanding of this chronic condition and its implications for healthcare systems globally. The model developed in this study has the potential for scalability and applicability in other healthcare settings, thereby supporting broader research efforts and informing clinical decision-making for long COVID patients.

Advancement in the development of mRNA-based vaccines for respiratory viruses.

Acute respiratory infections are the leading cause of death and illness in children under 5 years old and represent a significant burden in older adults. Primarily caused by viruses infecting the lower respiratory tract, symptoms include cough, congestion, and low-grade fever, potentially leading to bronchiolitis and pneumonia. Messenger ribonucleic acid (mRNA)-based vaccines are biopharmaceutical formulations that employ mRNA molecules to induce specific immune responses, facilitating the expression of viral or bacterial antigens and promoting immunization against infectious diseases. Notably, this technology had significant relevance during the COVID-19 pandemic, as these formulations helped to limit SARS-CoV-2 virus infections, hospitalizations, and deaths. Importantly, mRNA vaccines promise to be implemented as new alternatives for fighting other respiratory viruses, such as influenza, human respiratory syncytial virus, and human metapneumovirus. This review article analyzes mRNA-based vaccines' main contributions, perspectives, challenges, and implications against respiratory viruses.

Unlocking secrets: lipid metabolism and lipid droplet crucial roles in SARS-CoV-2 infection and the immune response.

Lipid droplets (LDs) are crucial for maintaining lipid and energy homeostasis within cells. LDs are highly dynamic organelles that present a phospholipid monolayer rich in neutral lipids. Additionally, LDs are associated with structural and nonstructural proteins, rapidly mobilizing lipids for various biological processes. Lipids play a pivotal role during viral infection, participating during viral membrane fusion, viral replication, and assembly, endocytosis, and exocytosis. SARS-CoV-2 infection often induces LD accumulation, which is used as a source of energy for the replicative process. These findings suggest that LDs are a hallmark of viral infection, including SARS-CoV-2 infection. Moreover, LDs participate in the inflammatory process and cell signaling, activating pathways related to innate immunity and cell death. Accumulating evidence demonstrates that LD induction by SARS-CoV-2 is a highly coordinated process, aiding replication and evading the immune system, and may contribute to the different cell death process observed in various studies. Nevertheless, recent research in the field of LDs suggests these organelles according to the pathogen and infection conditions may also play roles in immune and inflammatory responses, protecting the host against viral infection. Understanding how SARS-CoV-2 influences LD biogenesis is crucial for developing novel drugs or repurposing existing ones. By targeting host lipid metabolic pathways exploited by the virus, it is possible to impact viral replication and inflammatory responses. This review seeks to discuss and analyze the role of LDs during SARS-CoV-2 infection, specifically emphasizing their involvement in viral replication and the inflammatory response.

Metaviromic reveals the dynamics and diversity of the virosphere in wastewater samples from Natal, Brazil.

The COVID-19 pandemic underscored the significance of omics technology and Wastewater-Based Epidemiology for epidemic preparedness. This study investigates the virosphere in wastewater samples from Natal (Brazil), aiming to understand its structure, relationships, and potential. Metaviromic analysis was used on DNA and RNA from weekly samples collected over a year (June/2021 to May/2022) from three wastewater treatment plants. The virosphere showed stability, particularly in viruses infecting microorganisms and plants. However, an alternation of representatives of viruses that infect animals has been observed. Among the most abundant viruses infecting microorganisms are genera associated with the bacterial genera Escherichia, Pseudomonas, and Caulobacte. Regarding the viruses infecting plants, Sobemovirus and Tobamovirus are the most abundant genera. Odontoglossum ringspot virus was identified as a possible RNA virus biomarker. Among DNA viruses infecting animals, genera Bocaparvovirus and Mastadenovirus are the most prevalent. Intriguingly, some Poxviridae family members were observed in the samples. Co-occurrence network analysis identified potential biomarkers like Volepox virus, Anatid herpesvirus 1, and Caviid herpesvirus 2. Among RNA viruses affecting animals, Mamastrovirus, Rotavirus, and Norovirus genera were the most abundant pathogens. Furthermore, members of the Coronaviridae family exhibited a high degree of centrality values in the co-occurrence network, even connecting with unclassified viruses. The study emphasizes the importance of research in understanding the roles of unclassified viruses. In addition, we observed an association between Coronaviridae reads, rainfall, and the number of reported COVID-19 cases. Our study highlights the diversity and complexity of the viral community in wastewater and the need for research to understand better the ecological roles unclassified viruses play. Such advances will significantly contribute to our preparedness and response to future viral threats. Furthermore, our study contributes to knowledge of virosphere dynamics, offering insights that can contribute to the direction of future public health policies and interventions.

An unexpected IgE anti-receptor binding domain response following natural infection and different types of SARS-CoV-2 vaccines.

Humoral response to SARS-CoV-2 has been studied, predominantly the classical IgG and its subclasses. Although IgE antibodies are typically specific to allergens or parasites, a few reports describe their production in response to SARS-CoV-2 and other viruses. Here, we investigated IgE specific to receptor binding domain (RBD) of SARS-CoV-2 in a Brazilian cohort following natural infection and vaccination. Samples from 59 volunteers were assessed after infection (COVID-19), primary immunization with vectored (ChAdOx1) or inactivated (CoronaVac) vaccines, and booster immunization with mRNA (BNT162b2) vaccine. Natural COVID-19 induced IgE, but vaccination increased its levels. Subjects vaccinated with two doses of ChAdOx1 exhibited a more robust response than those immunized with two doses of CoronaVac; however, after boosting with BNT162b2, all groups presented similar IgE levels. IgE showed intermediate-to-high avidity, especially after the booster vaccine. We also found IgG4 antibodies, mainly after the booster, and they moderately correlated with IgE. ELISA results were confirmed by control assays, using IgG depletion by protein G and lack of reactivity with heterologous antigen. In our cohort, no clinical data could be associated with the IgE response. We advocate for further research on IgE and its role in viral immunity, extending beyond allergies and parasitic infections.

Challenges in the Diagnosis of SARS-CoV-2 Infection in the Nervous System.

Neurological involvement has been widely reported in SARS-CoV-2 infection. However, viral identification in the cerebrospinal fluid (CSF) is rarely found. The aim of this study is to evaluate the accuracy of virological and immunological biomarkers in CSF for the diagnosis of neuroCOVID-19. We analyzed 69 CSF samples from patients with neurological manifestations: 14 with suspected/confirmed COVID-19, with 5 additional serial CSF samples (group A), and as a control, 50 non-COVID-19 cases (group B-26 with other neuroinflammatory diseases; group C-24 with non-inflammatory diseases). Real-time reverse-transcription polymerase chain reaction (real-time RT-PCR) was used to determine SARS-CoV-2, and specific IgG, IgM, neopterin, and protein 10 induced by gamma interferon (CXCL-10) were evaluated in the CSF samples. No samples were amplified for SARS-CoV-2 by real-time RT-PCR. The sensitivity levels of anti-SARS-CoV-2 IgG and IgM were 50% and 14.28%, respectively, with 100% specificity for both tests. CXCL-10 showed high sensitivity (95.83%) and specificity (95.83%) for detection of neuroinflammation. Serial CSF analysis showed an association between the neuroinflammatory biomarkers and outcome (death and hospital discharge) in two cases (meningoencephalitis and rhombencephalitis). The detection of SARS-CoV-2 RNA and specific immunoglobulins in the CSF can be used for neuroCOVID-19 confirmation. Additionally, CXCL-10 in the CSF may contribute to the diagnosis and monitoring of neuroCOVID-19.

The Silent Syndrome of Long COVID and Gaps in Scientific Knowledge: A Narrative Review.

COVID-19 is still a major public health concern, mainly due to the persistence of symptoms or the appearance of new symptoms. To date, more than 200 symptoms of long COVID (LC) have been described. The present review describes and maps its relevant clinical characteristics, pathophysiology, epidemiology, and genetic and nongenetic risk factors. Given the currently available evidence on LC, we demonstrate that there are still gaps and controversies in the diagnosis, pathophysiology, epidemiology, and detection of prognostic and predictive factors, as well as the role of the viral strain and vaccination.

SARS-CoV-2 Modulation of HIV Latency Reversal in a Myeloid Cell Line: Direct and Bystander Effects.

Coronavirus disease 2019 (COVID-19) might impact disease progression in people living with HIV (PLWH), including those on effective combination antiretroviral therapy (cART). These individuals often experience chronic conditions characterized by proviral latency or low-level viral replication in CD4+ memory T cells and tissue macrophages. Pro-inflammatory cytokines, such as TNF-α, IL-1ß, IL-6, and IFN-γ, can reactivate provirus expression in both primary cells and cell lines. These cytokines are often elevated in individuals infected with SARS-CoV-2, the virus causing COVID-19. However, it is still unknown whether SARS-CoV-2 can modulate HIV reactivation in infected cells. Here, we report that exposure of the chronically HIV-1-infected myeloid cell line U1 to two different SARS-CoV-2 viral isolates (ancestral and BA.5) reversed its latent state after 24 h. We also observed that SARS-CoV-2 exposure of human primary monocyte-derived macrophages (MDM) initially drove their polarization towards an M1 phenotype, which shifted towards M2 over time. This effect was associated with soluble factors released during the initial M1 polarization phase that reactivated HIV production in U1 cells, like MDM stimulated with the TLR agonist resiquimod. Our study suggests that SARS-CoV-2-induced systemic inflammation and interaction with macrophages could influence proviral HIV-1 latency in myeloid cells in PLWH.

Single-cell transcriptomic analysis of B cells reveals new insights into atypical memory B cells in COVID-19.

Here, we performed single-cell RNA sequencing of S1 and receptor binding domain protein-specific B cells from convalescent COVID-19 patients with different clinical manifestations. This study aimed to evaluate the role and developmental pathway of atypical memory B cells (MBCs) in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The results revealed a proinflammatory signature across B cell subsets associated with disease severity, as evidenced by the upregulation of genes such as GADD45B, MAP3K8, and NFKBIA in critical and severe individuals. Furthermore, the analysis of atypical MBCs suggested a developmental pathway similar to that of conventional MBCs through germinal centers, as indicated by the expression of several genes involved in germinal center processes, including CXCR4, CXCR5, BCL2, and MYC. Additionally, the upregulation of genes characteristic of the immune response in COVID-19, such as ZFP36 and DUSP1, suggested that the differentiation and activation of atypical MBCs may be influenced by exposure to SARS-CoV-2 and that these genes may contribute to the immune response for COVID-19 recovery. Our study contributes to a better understanding of atypical MBCs in COVID-19 and the role of other B cell subsets across different clinical manifestations.

Biosocial Technical Systems: An Emerging Approach to Analyse Responses to Novel Diseases.

The COVID-19 pandemic emerged in the context of a parallel epidemic of information, namely an infodemic. With the development of vaccines occurring in record time, a disinformation campaign ensued rendering the infodemic ever more troubling. As COVID-19 had to be curbed with vaccines opinion pools and surveys indicated that a minority, but relevant, part of the general public had weakened trust in public health policies and also on governmental responses to the pandemic in general. This dissent in public opinion on pandemic response is interpreted in this chapter as a controversy related to the efficacy and risks associated to vaccines. Such controversy gained momentum partly because traditional scientific communication has been largely unidirectional rather than bi-directional. We propose to apply a novel biosocial technical perspective to examine the COVID-19 pandemic controversy and communication, articulating social, biological and technical issues. The interaction between COVID-19 and vaccines, i.e. artefact-biological interactions, resulted in vaccine development in record time. However, the interaction between social systems and vaccine as artefacts was plagued by partial public reluctance in their acceptance. This rendered communication efforts ever more relevant, bringing lessons related to the importance of a more fluid bi-directional communication in future disease epidemics.