Pathophysiological correlations between SARS-CoV-2 and arrhythmogenesis: a literature review.

Introduction: SARS-CoV-2 represents one of the most extensively researched pathogens in the last decade due to its major impact on humanity. Not only does this viral infection cause respiratory disturbances, but it also generates cardiovascular injury. Cardiac arrhythmias represent one of the main consequences of SARS-CoV-2 infection, but they can also occur in the context of antiviral treatment. Furthermore, arrhythmias do not always seem to be correlated with the severity of the lung injury. However, they represent a poor prognostic factor in terms of mortality, increasing the need for intensive care and the length of hospitalization. Methods: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 Statement, from September 2022 to October 2023, we conducted this study by examining the literature through the PubMed database using the following keywords: COVID-19, cardiac arrhythmias, and, in terms of study design, observational studies. Results: We initially identified 266 studies across PubMed. After applying the inclusion/exclusion criteria, we managed to include 22 studies in our review. Conclusions: Deducing the pathophysiological mechanisms behind SARS-CoV-2's ability to disrupt the electrical activity of the heart, as well as identifying associated risk factors in patients with SARS-CoV-2 infection, could allow targeted therapeutic interventions to decrease the risk of mortality in hospitalized patients.

A comprehensive survey on exploring and analyzing COVID-19 mobile apps: Meta and exploratory analysis.

During the current COVID-19 pandemic, many digital solutions around the world have been proposed to cope with the deadly virus but the role of mobile-based applications is dominant one. In Pakistan, during the current COVID-19 pandemic, an array of mobile health applications (apps) and platforms have been launched to grapple with the impacts of the COVID-19 situation. In this survey, our major focus is to explore and analyze the starring role of mobile apps based on the features and functionalities to tackle the COVID-19 disease, particularly in Pakistan. In this study, over fifty (50) mobile apps have been scrapped from the well-known three different sources i.e. Google Play Store, iOS Play Store, and web source. We developed our own data set after searching through the different play stores. We have designed two criteria such that the first criteria are known as eligibility criteria, while the second one is known as assessment criteria. The features and functions of each mobile app are pinpointed and discussed against the parameters of the assessment criteria. The major parameters of assessment criteria are: (i) Home monitoring; (ii) COVID-19 awareness; (iii) contact tracing; (iv) telemedicine; (v) health education; (vi) COVID-19 surveillance; (vii) self-assessment; (viii) security; and (ix) accessibility. This study conducted exploratory analysis and quantitative meta-data analysis by adopting PRISMA guidelines. This survey article is not only discussing the function and features of each COVID-19-centered app in Pakistan, but it also sheds light on the limitations of every mobile app as well. The results of this survey might be helpful for the mobile developers to review the current app products and enhance the existing mobile platforms targeted towards the COVID-19 pandemic. This is the first attempt of its kind to present a state-of-the-art survey of the COVID-19-centered mobile health apps in Pakistan.

Comprehensive analysis of malabar tamarind fruit rind total extract: HPTLC fingerprinting, in-silico exploration of its metabolites for SARS-cov-2 omicron spike protein, antibacterial and antidiabetic potentials with in vitro evaluation of antidiabetic and antioxidant activities.

Malabar tamarind tropical fruit, scientifically known as Garcinia gummi-gutta, is indigenous to Southeast Asia. In this work, the total methanolic extract of the Malabar fruit rind was examined by HPTLC fingerprinting, with quantitative evaluation of the total phenolics and flavonoids. Library of previously reported natural metabolites was utilized to demonstrate their affinity for specific target sites, they were evaluated against Omicron SARS-CoV-2 mainly it's Spike Protein, bacterial tyrosinase, and antidiabetic targets such α-glucosidase, pancreatic lipase and also α-amylase enzymes. The molecular docking revealed that the Guttiferone R possessed the highest binding affinity toward the Omicron Spike Protein with a stable binding mode, -8.67 kcal/mol binding energy and a 1.07 Å RMSD value compared to reference, Azithromycin, which has -8.90 kcal/mol binding affinity and a 1.20 Å RMSD value. On the other hand, the identified polyphenolic compounds; Vitexin, Prunin, Naringin, Hinokiflavone, Kaempherol-3-O-rutinoside, Gallic acid, Naringenin, and Catechin, showed remarkable antidiabetic activity by strong inhibitory activity against α-glucosidase and notable activity against α-amylase compared with acarbose as reference. According to antibacterial activity, the identified compounds showed low affinity with weak activity against screened bacterial strains. In-vitro evaluation of Tamarind antioxidant and antidiabetic potentials, it exhibited a free radical-scavenging potential with 71.75 % retardation and α-glucosidase, α-amylase and pancreatic lipase inhibitor activities with an IC50 of 391.3 ± 26.27, 95.03 ± 0.03 and 0.01043 ± 0.0004 µg/mL, respectively that emphasize the molecular docking study. The findings imply that Malabar tamarind fruit rind possess antioxidant, antidiabetic, antibacterial and antiviral activities.

Development and characterization of monoclonal antibodies recognizing nucleocapsid protein of multiple SARS-CoV-2 variants.

Rapid antigen test (RAT) is widely used for SARS-CoV-2 infection diagnostics. However, test sensitivity has decreased recently due to the emergence of the Omicron variant and its sublineages. Here we developed a panel of SARS-CoV-2 nucleocapsid protein (NP) specific mouse monoclonal antibodies (mAbs) and assessed their sensitivity and specificity to important SARS-CoV-2 variants. We identified seven mAbs that exhibited strong reactivity to SARS-CoV-2 variants and recombinant NP (rNP) by Western immunoblot or ELISA. Their specificity to SARS-CoV-2 was confirmed by negative or low reactivity to rNPs from SARS-CoV-1, MERS, and common human coronaviruses (HCoV-HKU1, HCoV-CO43, HCoV-NL63, and HCoV-229E). These seven mAbs were further tested by immunoplaque assay against selected variants of concern (VOCs), including two Omicron sublineages, and five mAbs (F461G13, F461G7, F459G7, F457G3, and F461G6), showed strong reactions, warranting further suitability testing for the development of diagnostic assay.

Global impact of COVID-19 on food safety and environmental sustainability: Pathways to face the pandemic crisis.

The COVID-19 pandemic poses ongoing challenges to the sustainability of various socioeconomic sectors, including agriculture, the food supply chain, the food business, and environmental sustainability. This study employs data obtained from the World Health Organization (WHO), and Food and Agriculture Organization (FAO), as well as scientific and technical research publications, to evaluate the impacts of COVID-19 on agriculture and food security. This article seeks to highlight the profound influence of the COVID-19 pandemic on agriculture, the supply and demand of food, and the overall safety of food. The article also explores the several pathways by which COVID-19 can be transmitted in these areas and the various technologies employed for its detection. The ongoing and post-pandemic ramifications are substantial since they could decrease agricultural output due to limitations on migration, a downturn in international trade, less buying capacity, and disturbances in food production and processing. Therefore, based on this thorough investigation, recommendations are issued for mitigating and controlling the pandemic's effects.

Tirofiban prevents the effects of SARS-CoV-2 spike protein on macrophage activation and endothelial cell death.

SARS-CoV-2 viral-derived particles have been proposed to have a causal role in tissue inflammation. Macrophage is the culprit cell in the pathogenesis of destructive inflammatory response to the SARS-CoV-2 virus. We investigated whether the spike protein might play a role in perturbing the physiological process of resolution of inflammation. Using an in vitro model of M2 polarized macrophages, we found that recombinant spike protein produced typical M1 morphological features in these alternative differentiated cells. In the presence of spike, M2-macrophages lose their elongated morphology, become rounded and acquire a strong capability to stimulate lymphocyte activation and proliferation. Moreover, in M2 macrophages, spike activated the signal transducer and activator-1 (STAT1) the pivotal mediator of pro-inflammatory macrophages. We observed STAT1 activation also in endothelial cells cultured with recombinant spike, accompanied by Bax upregulation and cell death. Blockade of beta3 integrin with the RGD mimetic tirofiban reverted the spike-induced costimulatory effects on M2 macrophages. Also, tirofiban counteracted STAT1 and Bax activation in endothelial cells cultured with spike and reduced endothelial cell death. In conclusion, we found that some proinflammatory effects of the spike protein can involve the integrin pathway and provide elements supporting use of RGD mimetics against SARS-Cov-2.

Hub genes identification and validation of ferroptosis in SARS-CoV-2 induced ARDS: perspective from transcriptome analysis.

Introduction: Acute Respiratory Distress Syndrome (ARDS) poses a significant health challenge due to its high incidence and mortality rates. The emergence of SARS-CoV-2 has added complexity, with evidence suggesting a correlation between COVID-19 induced ARDS and post-COVID symptoms. Understanding the underlying mechanisms of ARDS in COVID-19 patients is crucial for effective clinical treatment. Method: To investigate the potential role of ferroptosis in SARS-CoV-2 induced ARDS, we conducted a comprehensive analysis using bioinformatics methods. Datasets from the Gene Expression Omnibus (GEO) were utilized, focusing on COVID-19 patients with varying ARDS severity. We employed weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and single-cell sequencing to identify key genes associated with ferroptosis in ARDS. Hub genes were validated using additional GEO datasets and cell experiment. Result: The analysis discerned 916 differentially expressed genes in moderate/severe ARDS patients compared to non-critical individuals. Weighted Gene Co-expression Network Analysis (WGCNA) unveiled two modules that exhibited a positive correlation with ARDS, subsequently leading to the identification of 15 hub genes associated with ferroptosis. Among the noteworthy hub genes were MTF1, SAT1, and TXN. Protein-protein interaction analysis, and pathway analysis further elucidated their roles. Immune infiltrating analysis highlighted associations between hub genes and immune cells. Validation in additional datasets confirmed the upregulation of MTF1, SAT1, and TXN in SARS-CoV-2-induced ARDS. This was also demonstrated by qRT-PCR results in the BEAS-2B cells vitro model, suggesting their potential as diagnostic indicators. Discussion: This study identifies MTF1, SAT1, and TXN as hub genes associated with ferroptosis in SARS-CoV-2-induced ARDS. These findings provide novel insights into the molecular mechanisms underlying ARDS in COVID-19 patients and offer potential targets for immune therapy and targeted treatment. Further experimental validation is warranted to solidify these findings and explore therapeutic interventions for ARDS in the context of COVID-19.

Effectiveness of Pfizer Vaccine BNT162b2 Against SARS-CoV-2 in Americans 16 and Older: A Systematic Review.

This systematic review evaluates the efficacy and long-term effectiveness of the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) across diverse clinical and observational settings within the United States in Americans aged 16 and older. We conducted an extensive literature search utilizing various types of studies to assess the vaccine's performance in preventing symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes. Our initial search in PubMed on March 14, 2022, yielded 6,725 potentially relevant articles, with 26 undergoing full-text assessment and eight meeting the inclusion criteria. To incorporate the most up-to-date findings, a secondary search was conducted on July 6, 2024, using improved and refined Medical Subject Headings (MeSH) terms within the PubMed and Scopus databases. This expanded approach resulted in 78 potentially relevant articles from PubMed and 1,567 from Scopus, with 40 articles undergoing full-text assessment and an additional 14 articles meeting the inclusion criteria. Early clinical trials reported initial vaccine effectiveness (VE) up to 95% with sustained immunity in various populations. Observational studies and systematic reviews further confirmed VE above 90% against symptomatic infections and highlighted nearly complete protection against hospitalizations and deaths. Recent research underscores the critical role of booster doses in maintaining high VE, especially against emerging variants, showing restored effectiveness up to 95% and supporting their strategic importance in ongoing pandemic responses. Despite observed waning immunity and breakthrough infections, the BNT162b2 vaccine continues to exhibit robust protection across different demographic groups and under varying epidemiological conditions. Our findings advocate for continuous booster updates and adaptive vaccination strategies to manage emerging SARS-CoV-2 variants, reinforcing the pivotal role of mRNA vaccine technology in addressing global health emergencies.

Hematological, inflammatory and serological responses among COVID-19 patients admitted to intensive care unit.

Aim: To correlate hematological, inflammatory indicators and serological responses among COVID-19 patients to point out the significant biomarkers for disease management and prognosis.Materials & methods: Standard analytical and molecular methods were used to assess various inflammatory and serological Responses among COVID-19 patients (ICU- (n = 99) and non-ICU patients (n = 64) as compared with health control (n = 40).Results: Significant differences in the Hb, WBC, Lymphocyte count, CRP and serum ferritin (p < 0.05) were observed. Patients' IgM/IgG antibodies against SARS-CoV-2 were associated with increased CRP, LDH and serum ferritin levels.Conclusion: A significant association between serum IgG/IgM and ICU admission was observed. Although serum ferritin and LDH can offer information about the extent of inflammation, they are exclusive factors for ICU admission.

This study aimed to find the best biomarkers among COVID-19 patients to be used as indicators of patient eligibility for admission to the intensive care unit and for evaluating the disease complications and proper intervention before cases deteriorated. For the COVID-19 as compared with healthy individuals, results showed significant differences in many hematological indicators such as hemoglobin level, white blood cells and Lymphocyte count. Results also showed a strong correlation between certain serum antibody levels against COVID-19 and admission to intensive care unit.

Exploration of medicinal plants as potential therapeutics against COVID-19: molecular insights and drug development prospects with other significant medicinal information a retrospective exposition.

OBJECTIVES: The study aims to explore the potential of medicinal plants and their phytoconstituents as effective inhibitors of the coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus. The focus is on investigating specific medicinal plants known for their pharmacological properties, such as: antioxidant, anti-inflammatory, and immunomodulatory effects, to determine their viability in developing COVID-19 treatments. MATERIALS AND METHODS: This study involves a comprehensive study of medicinal plants, including: Withania somnifera (Ashwagandha) and Ocimum sanctum (Holy Basil), known for their beneficial health effects. Molecular docking studies were conducted to assess the interactions between phytoconstituents from these plants and SARS-CoV-2 proteins. The compounds' drug-like characteristics and safety profiles were also evaluated to determine their potential as therapeutic agents. RESULTS: The molecular docking studies revealed that the phytoconstituents from the studied medicinal plants exhibit favourable interactions with SARS-CoV-2 proteins, suggesting their potential as therapeutic targets. These compounds demonstrated promising drug-like characteristics and safety profiles, indicating their suitability for further development as COVID-19-fighting medications. DISCUSSION: The results indicate that medicinal plants and their bioactive substances hold significant potential for developing therapies against COVID-19. The ability of these organic substances to interact with key viral proteins and provide various therapeutic benefits highlights their potential as multi-functional treatment options. However, further research is necessary to confirm these findings and to understand the full scope of their therapeutic efficacy and safety in clinical settings. CONCLUSIONS: Medicinal plants and their phyto-constituents represent a promising avenue for developing effective treatments for COVID-19. The favourable interactions with SARS-CoV-2 proteins and the promising drug-like characteristics observed in this study suggest that these natural compounds could be integral in the fight against the COVID-19 pandemic. Further research and clinical trials are essential to fully validating their potential and translating these findings into practical medical applications.

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput, limited integration, and complex reagent preparation. Here, a system, microfluidic multiplate-based ultrahigh throughput analysis of SARS-CoV-2 variants of concern using CRISPR/Cas12a and nonextraction RT-LAMP (mutaSCAN), is proposed for rapid detection of SARS-CoV-2 and its variants with limited resource requirements. With the aid of the self-developed reagents and deep-learning enabled prototype device, our mutaSCAN system can detect SARS-CoV-2 in mock swab samples below 30 min as low as 250 copies/mL with the throughput up to 96 per round. Clinical specimens were tested with this system, the accuracy for routine and mutation testing (22 wildtype samples, 26 mutational samples) was 98% and 100%, respectively. No false-positive results were found for negative (n = 24) samples.

Association between human leukocyte antigen alleles and COVID-19 disease severity.

BACKGROUND: the human leukocyte antigen (HLA) loci have been widely characterized to be associated with viral infectious diseases. Several studies including various ethnic groups and populations suggested associations between certain HLA alleles and SARS-CoV-2 infection. Despite the numerous associations identified, the role of HLA polymorphisms in determining the individual response to SARS-CoV-2 infection is controversial among different Saudi populations. METHOD: Here, we performed HLA typing by next-generation sequencing to investigate if variations in polymorphic HLA genes are linked to COVID-19 severity in the Saudi population. Namely, we analyzed HLA loci at allele level in 575 Saudi patients with SARS-CoV-2 infection. HLA class I and class II frequencies in patients were compared with allele frequency data from healthy Saudi population. RESULTS: in our cohort HLA-A* 02:01:01 G was associated with mild disease but was not associated with moderate and severe disease. HLA-B* 51:01:01 G was protective from severe disease while HLA-B* 50:01:01 G, HLA-C* 06:02:01 G and HLA-DRB1 * 07:01:01 G were associated with risk to severe disease as well as the total COVID-19 cohort. HLA-DRB1 * 15:01:01 G was associated with risk to all severity groups. CONCLUSION: in conclusion, we found significant associations between HLA alleles and COVID-19 disease severity in Saudis. Further studies are warranted to include HLA typing in the workup for any new COVID-19 patients.

Concerted deletions eliminate a neutralizing supersite in SARS-CoV-2 BA.2.87.1 spike.

BA.2.87.1 represents a major shift in the BA.2 lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is unusual in having two lengthy deletions of polypeptide in the spike (S) protein, one of which removes a beta-strand. Here we investigate its neutralization by a variety of sera from infected and vaccinated individuals and determine its spike (S) ectodomain structure. The BA.2.87.1 receptor binding domain (RBD) is structurally conserved and the RBDs are tightly packed in an "all-down" conformation with a small rotation relative to the trimer axis as compared to the closest previously observed conformation. The N-terminal domain (NTD) maintains a remarkably similar structure overall; however, the rearrangements resulting from the deletions essentially destroy the so-called supersite epitope and eliminate one glycan site, while a mutation creates an additional glycan site, effectively shielding another NTD epitope. BA.2.87.1 is relatively easily neutralized but acquisition of additional mutations in the RBD could increase antibody escape allowing it to become a dominant sub-lineage.

Facility wastewater monitoring as an effective tool for pandemic infection control: An experience in COVID-19 pandemic with long-term monitoring.

INTRODUCTION: Since the first report of a novel coronavirus infection caused by SARS-CoV-2 in late 2019, the infection has spread rapidly and had a significant impact on our lives. In the early stages of the COVID-19 pandemic, there was no adequate testing system in place, despite an urgent need for infection control measures in student dormitories. METHODS: We have been monitoring SARS-CoV-2 in wastewater as part of our infection control efforts in the university facilities since fall 2020. In the four dormitories, absorbent cotton was placed in the drains that the facility wastewater passed through, and samples were collected twice a week and processed by RT-PCR for SARS-CoV-2. The dormitory residents were informed of the monitoring results the next morning. RESULTS: The positivity of residents in the dormitories was highly consistent with the positivity of wastewater. Wastewater was positive in 89% of cases before any residents were tested and found positive. Facility wastewater monitoring showed sensitivities of 80.4% and specificities of 87.6%. No traceable resident-to-resident transmission of infection within the facility was confirmed during the study period. CONCLUSION: Sampling a single wastewater outlet in a building for SARS-CoV-2 PCR can effectively indicate the presence or absence of COVID-19 cases and be very useful for infection control of a facility. This simple and effective monitoring is applicable to future outbreaks of both emerging and re-emerging infectious diseases.

Estimating rates of change to interpret quantitative wastewater surveillance of disease trends.

BACKGROUND: Wastewater monitoring data can be used to estimate disease trends to inform public health responses. One commonly estimated metric is the rate of change in pathogen quantity, which typically correlates with clinical surveillance in retrospective analyses. However, the accuracy of rate of change estimation approaches has not previously been evaluated. OBJECTIVES: We assessed the performance of approaches for estimating rates of change in wastewater pathogen loads by generating synthetic wastewater time series data for which rates of change were known. Each approach was also evaluated on real-world data. METHODS: Smooth trends and their first derivatives were jointly sampled from Gaussian processes (GP) and independent errors were added to generate synthetic viral load measurements; the range hyperparameter and error variance were varied to produce nine simulation scenarios representing different potential disease patterns. The directions and magnitudes of the rate of change estimates from four estimation approaches (two established and two developed in this work) were compared to the GP first derivative to evaluate classification and quantitative accuracy. Each approach was also implemented for public SARS-CoV-2 wastewater monitoring data collected January 2021-May 2023 at 25 sites in North Carolina, USA. RESULTS: All four approaches inconsistently identified the correct direction of the trend given by the sign of the GP first derivative. Across all nine simulated disease patterns, between a quarter and a half of all estimates indicated the wrong trend direction, regardless of estimation approach. The proportion of trends classified as plateaus (statistically indistinguishable from zero) for the North Carolina SARS-CoV-2 data varied considerably by estimation method but not by site. DISCUSSION: Our results suggest that wastewater measurements alone might not provide sufficient data to reliably track disease trends in real-time. Instead, wastewater viral loads could be combined with additional public health surveillance data to improve predictions of other outcomes.

Multifaceted exploration of acylthiourea compounds: In vitro cytotoxicity, DFT calculations, molecular docking and dynamics simulation studies ☆.

This study reports the synthesis and analysis of biologically active acylthiourea compounds (1 and 2) with a cyclohexyl moiety. The compounds were characterized using UV-Visible, FT-IR, 1H/13C NMR, and elemental analysis. The crystal structure of 2 was solved, revealing intra- and inter-molecular hydrogen bonds. Density functional theory (DFT) calculations provided insights into chemical reactivity and non-covalent interactions. Cytotoxicity assays showed the cyclohexyl group enhanced the activity of compound 2 compared to compound 1. Epoxide hydrolase 1 was predicted as the enzyme target for both compounds. We modeled the structure of epoxide hydrolase 1 and performed molecular dynamics simulation and docking studies. Additionally, in silico docking with SARS-CoV-2 main protease, human ACE2, and avian influenza H5N1 hemagglutinin indicated strong binding potential. This integrated approach improves our understanding of the biological potential of acylthiourea derivatives.

SARS-CoV-2 Mpro inhibitor identification using a cellular gain-of-signal assay for high-throughput screening.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2, SARS2) is responsible for the COVID-19 pandemic and infections that continue to affect the lives of millions of people worldwide, especially those who are older and/or immunocompromised. The SARS2 main protease enzyme, Mpro (also called 3C-like protease, 3CLpro), is a bona fide drug target as evidenced by potent inhibition with nirmatrelvir and ensitrelvir, the active components of the drugs Paxlovid and Xocova, respectively. However, the existence of nirmatrelvir and ensitrelvir-resistant isolates underscores the need to develop next-generation drugs with different resistance profiles and/or distinct mechanisms of action. Here, we report the results of a high-throughput screen of 649,568 compounds using a cellular gain-of-signal assay. In this assay, Mpro inhibits expression of a luciferase reporter, and 8,777 small molecules were considered hits by causing a gain in luciferase activity 3x SD above the sample field activity (6.8% gain-of-signal relative to 100 µM GC376). Single concentration and dose-response gain-of-signal experiments confirmed 3,522/8,762 compounds as candidate inhibitors. In parallel, all initial high-throughput screening hits were tested in a peptide cleavage assay with purified Mpro and only 39/8,762 showed inhibition. Importantly, 19/39 compounds (49%) re-tested positive in both SARS2 assays, including two previously reported Mpro inhibitors, demonstrating the efficacy of the overall screening strategy. This approach led to the rediscovery of known Mpro inhibitors such as calpain inhibitor II, as well as to the discovery of novel compounds that provide chemical information for future drug development efforts.

A mechanistic modeling and estimation framework for environmental pathogen surveillance.

Environmental pathogen surveillance is a promising disease surveillance modality that has been widely adopted for SARS-CoV-2 monitoring. The highly variable nature of environmental pathogen data is a challenge for integrating these data into public health response. One source of this variability is heterogeneous infection both within an individual over the course of infection as well as between individuals in their pathogen shedding over time. We present a mechanistic modeling and estimation framework for connecting environmental pathogen data to the number of infected individuals. Infected individuals are modeled as shedding pathogen into the environment via a Poisson process whose rate parameter λt varies over the course of their infection. These shedding curves λt are themselves random, allowing for variation between individuals. We show that this results in a Poisson process for environmental pathogen levels with rate parameter a function of the number of infected individuals, total shedding over the course of infection, and pathogen removal from the environment. Theoretical results include determination of identifiable parameters for the model from environmental pathogen data and simple, explicit formulas for the likelihood for particular choices of individual shedding curves. We give a two step Bayesian inference framework, where the first step corresponds to calibration from data where the number of infected individuals is known, followed by an estimation step from environmental surveillance data when the number of infected individuals is unknown. We apply this modeling and estimation framework to synthetic data, as well as to an empirical case study of SARS-CoV-2 in environmental dust collected from isolation rooms housing university students. Both the synthetic data and empirical case study indicate high inter-individual variation in shedding, leading to wide credible intervals for the number of infected individuals. We examine how uncertainty in estimates of the number of infected individuals from environmental pathogen levels scales with the true number of infected individuals and model misspecification. While credible intervals for the number of infected individuals are wide, our results suggest that distinguishing between no infection and small-to-moderate levels of infection (≈10 infected individuals) may be possible, and that it is broadly possible to differentiate between moderate (≈40) and high (≈200) numbers of infected individuals.

A heterocyclic compound inhibits viral release by inducing cell surface BST2/Tetherin/CD317/HM1.24.

The introduction of combined antiretroviral therapy (cART) has greatly improved the quality of life of human immunodeficiency virus type 1 (HIV-1)-infected individuals. Nonetheless, the ever-present desire to seek out a full remedy for HIV-1 infections makes the discovery of novel antiviral medication compelling. Owing to this, a new late-stage inhibitor, Lenacapavir/Sunlenca, an HIV multi-phase suppressor, was clinically authorized in 2022. Besides unveiling cutting-edge antivirals inhibiting late-stage proteins or processes, newer therapeutics targeting host restriction factors hold promise for the curative care of HIV-1 infections. Notwithstanding, bone marrow stromal antigen 2 (BST2)/Tetherin/CD317/HM1.24, which entraps progeny virions is an appealing HIV-1 therapeutic candidate. In this study, a novel drug screening system was established, using the Jurkat/Vpr-HiBiT T cells, to identify drugs that could obstruct HIV-1 release; the candidate compounds were selected from the Ono Pharmaceutical compound library. Jurkat T cells expressing Vpr-HiBiT were infected with NL4-3, and the amount of virus release was quantified indirectly by the amount of Vpr-HiBiT incorporated into the progeny virions. Subsequently, the candidate compounds that suppressed viral release were used to synthesize the heterocyclic compound, HT-7, which reduces HIV-1 release with less cellular toxicity. Notably, HT-7 increased cell surface BST2 coupled with HIV-1 release reduction in Jurkat cells but not Jurkat/KO-BST2 cells. Seemingly, HT-7 impeded simian immunodeficiency virus (SIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) release. Concisely, these results suggest that the reduction in viral release, following HT-7 treatment, resulted from the modulation of cell surface expression of BST2 by HT-7.

Participatory, Virologic, and Wastewater Surveillance Data to Assess Underestimation of COVID-19 Incidence, Germany, 2020-2024.

Using participatory, virologic, and wastewater surveillance systems, we estimated when and to what extent reported data of adult COVID-19 cases underestimated COVID-19 incidence in Germany. We also examined how case underestimation evolved over time. Our findings highlight how community-based surveillance systems can complement official notification systems for respiratory disease dynamics.