Revolutionizing SARS-CoV-2 omicron variant detection: Towards faster and more reliable methods.

The emergence of the highly contagious Omicron variant of SARS-CoV-2 has inflicted significant damage during the ongoing COVID-19 pandemic. This new variant's significant sequence changes and mutations in both proteins and RNA have rendered many existing rapid detection methods ineffective in identifying it accurately. As the world races to control the spread of the virus, researchers are urgently exploring new diagnostic strategies to specifically detect Omicron variants with high accuracy and sensitivity. In response to this challenge, we have compiled a comprehensive overview of the latest reported rapid detection techniques. These techniques include strategies for the simultaneous detection of multiple SARS-CoV-2 variants and methods for selectively distinguishing Omicron variants. By categorizing these diagnostic techniques based on their targets, which encompass protein antigens and nucleic acids, we aim to offer a comprehensive understanding of the utilization of various recognition elements in identifying these targets. We also highlight the advantages and limitations of each approach. Our work is crucial in providing a more nuanced understanding of the challenges and opportunities in detecting Omicron variants and emerging variants.

Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant based on an Immunoinformatics Approach.

BACKGROUND: SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness. OBJECTIVES: Therefore, it is urgent to consider the protective and safe vaccine against all subcoronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases. METHODS: Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii. RESULTS: The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity. CONCLUSION: In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

Sulfated liposome-based artificial cell membrane glycocalyx nanodecoys for coronavirus inactivation by membrane fusion.

As a broad-spectrum antiviral nanoparticle, the cell membrane nanodecoy is a promising strategy for preventing viral infections. However, most of the cell membrane nanodecoys can only catch virus and cannot induce inactivation, which may bring about a considerably high risk of re-infection owing to the possible viral escape from the nanodecoys. To tackle this challenge, sulfated liposomes are employed to mimic the cell membrane glycocalyx for constructing an artificial cell membrane glycocalyx nanodecoy that exhibits excellent anti-coronavirus activity against HCoV-OC43, wild-type SARS-CoV-2, Alpha and Delta variant SARS-CoV-2 pseudovirus. In addition, this nanodecoy, loaded with surface sulfate groups as SARS-CoV-2 receptor arrays, can enhance the antiviral capability to virus inactivation through destroying the virus membrane structure and transfer the spike protein to postfusion conformation. Integrating bio-inspired recognition and inactivation of viruses in a single supramolecular entity, the artificial cell membrane nanodecoy opens a new avenue for the development of theranostic antiviral nanosystems, whose mass production is favored due to the facile engineering of sulfated liposomes.

Drivers and impacts of decreasing concentrations of atmospheric volatile organic compounds (VOCs) in Beijing during 2016-2020.

China has implemented various policies and measures for controlling air pollutants. However, our knowledge of the long-term trends in ambient volatile organic compounds (VOCs) after the implementation of these action plans in China remains limited. To address this, we conducted a five-year analysis (2016-2020) of VOC compositions and concentrations in Beijing. The annual VOC concentration decreased from 44.0 ± 28.8 to 26.2 ± 16.4 ppbv, with alkanes being the most prevalent group. The annual average concentrations of alkenes, alkynes, and aromatics have experienced a significant decrease of over 50 %. Seasonal variations indicated higher VOC concentrations in winter and autumn, with more significant reductions observed in winter and autumn. The impact of meteorological conditions caused variations in VOC reductions during the Chinese Spring Festival. Satellite-based measurements of formaldehyde (HCHO) columns confirmed the reduction of VOC emissions during the Coronavirus (COVID-19) lockdown. The normalized annual average VOC concentration decreased by 2.9ppbv yr-1 from 2016 to 2020, and emission reduction contributed to 58.8 % of VOC reduction from 2016 to 2020 after meteorological normalization, indicating the effectiveness of implemented control measures. Based on receptor model, vehicle emissions and industrial sources were identified as the largest contributors to VOC concentrations. Vehicle emissions, liquefied petroleum gas/natural gas (LPG/NG) use, and coal combustion were major drivers of VOC reduction. Potential source region analysis revealed that air masses transported from northwestern and southern regions significantly contributed to VOC concentrations in Beijing. The range of source regions shrunk in both northwestern and southern regions with the reduction in VOC concentrations. The annual variations of ozone formation potential indicated a significant decrease in VOC reactivities through emission control. These results could provide insights into future emission control and coordinated efforts to improve PM2.5 and ozone levels in China.

Ecological risk assessment of the typical anti-epidemic drugs in the Pearl River Delta by tracing their source and residual characteristics.

Since the outbreak of the COVID-19 pandemic, the anti-epidemic drugs have been used in extraordinary quantities with high intensity, and concerns have grown about their potential ecological risks due to their continued release and persistence in the receiving environments. A systematic investigation, covering the samples from hospital wastewater, effluent from wastewater treatment plants and receiving water bodies in the Pearl River Delta Region (PRDR), was carried out and aimed at tracing the sources and fate of 30 typical anti-epidemic in different water matrixes and evaluating their ecological risk. The results showed that these typical anti-epidemic drugs residues were detected in most of the sampling sites, with the highest concentration measured in hospital wastewater, whose concentrations were as high as ppb level, while the highest concentration of the surface water samples in tributaries was lower than ppb level. Anti-epidemic drugs contained in hospital wastewater and effluent from WWTPs were the main sources of drug residues in the surface water of this region. In the surface water of PRDR, although the detected concentration anti-epidemic drugs were basically in the range of 0-10 ng/L. The risk quotient of several anti-epidemic drugs, including Ciprofloxacin (CFX), Ofloxacin (OFX), Erythromycin (ETM), Clindamycin (CLI), and Sulfamethoxazole (SMX), was calculated to be a high value, which indicated that they might cause non-negligible ecological risk to the aquatic environment.

Tracing the footprints of SARS-CoV-2 in oceanic waters.

The detection of SARS-CoV-2 in water environments has predominantly focused on wastewater, neglecting its presence in oceanic waters. This study aimed to fill this knowledge gap by investigating the occurrence of SARS-CoV-2 in remote sea and oceanic waters, at large distances from the coastline. Forty-three 500-liter samples were collected between May 2022 and January 2023 from the Atlantic Ocean, the Mediterranean Sea, the Arctic region, the Persian Gulf and the Red Sea. Using molecular detection methods including real-time RT-qPCR and nested PCR followed by sequencing, we successfully detected SARS-CoV-2 RNA in 7 of the 43 marine water samples (16.3 %), and specifically in samples taken from the Atlantic Ocean and the Mediterranean Sea. The estimated concentrations of SARS-CoV-2 genome copies in the positive samples ranged from 6 to 470 per 100 l. The presence of mutations characteristic of the Omicron variant was identified in these samples by amplicon sequencing. These findings provide evidence of the unforeseen presence of SARS-CoV-2 in marine waters even at distances of miles from the coastline and in open ocean waters. It is important to consider that these findings only display the occurrence of SARS-CoV-2 RNA, and further investigations are required to assess if infectious virus can be present in the marine environment.

Zooming in to the neighborhood level: A year-long wastewater-based epidemiology monitoring campaign for COVID-19 in small intraurban catchments.

In recent years, wastewater-based epidemiology (WBE) has emerged as a valuable and cost-effective tool for monitoring the prevalence of COVID-19. Large-scale monitoring efforts have been implemented in numerous countries, primarily focusing on sampling at the entrance of wastewater treatment plants (WWTPs) to cover a large population. However, sampling at a finer spatial scale, such as at the neighborhood level (NGBs), pose new challenges, including the absence of composite sampling infrastructure and increased uncertainty due to the dynamics of small catchments. This study aims to investigate the feasibility and accuracy of WBE when deployed at the neighborhood level (sampling in sewers) compared to the city level (sampling at the entrance of a WWTP). To achieve this, we deployed specific WBE sampling stations at the intraurban scale within three NGBs in Barcelona, Spain. The study period covers the 5th and the 6th waves of COVID-19 in Spain, spanning from March 2021 to March 2022, along with the WWTP downstream from the NGBs. The results showed a strong correlation between the dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 loads at both the NGB and city levels. Notably, during the 5th wave, which was dominated by the Delta SARS-CoV-2 variant, wastewater loads were higher than during the 6th wave (Omicron variant), despite a lower number of clinical cases recorded during the 5th wave. The correlations between wastewater loads and clinical cases at the NGB level were stronger than at the WWTP level. However, the early warning potential varied across neighborhoods and waves, with some cases showing a one-week early warning and others lacking any significant early warning signal. Interestingly, the prevalence of COVID-19 did not exhibit major differences among NGBs with different socioeconomic statuses.

Characteristics and Presentations of Hospitalized Children Due to 3 Predominate COVID-19 Variants Within a Health Care Network.

Objective of this article is to describe differences in the demographic and clinical characteristics, severity of illness, and outcomes in pediatric patients with different SARS-CoV-2 variants. We conducted a retrospective study of pediatric patients admitted with COVID-19 during the 3 large waves of infection within a health network in New Jersey. We included demographic characteristics, clinical features, and outcomes and compared the data with respect to the different variants. Of 351 total patients included in this study, 74 were admitted during wave 1, 94 during wave 2, and 181 during wave 3. The median age of patients decreased from wave 1 (11.5 years) to wave 3 (3 years) (P = .0034). 87.7% of the patients were unvaccinated. The overall incidence of admissions due to pneumonia related to COVID-19 decreased in wave 3. COVID-19 bronchiolitis or croup admissions occurred mostly in wave 3. There was no significant difference in the number of patients requiring intensive care in any particular wave. Length of stay decreased across the waves (P < .0001). Treatments required did not vary between the waves except for a decrease in antibiotic use with each subsequent wave (P < .0001). The impact of COVID-19 on the pediatric population differs from the adult population, and the overall number of hospitalized children has mirrored the peak in cases observed during each infection wave. Our study illustrates the changes in clinical presentation and severity observed with the different coronavirus variants.

One-step immunoassay of SARS-CoV-2 using screened Fv-antibodies and switching peptides.

The Fv-antibodies were correponded to VH region of immunoglobulin G, which were composed of three complementarity determining regions (CDRs) for the specific binding of antigens. In this work, the Fv-antibodies against SARS-CoV-2 spike protein (SP) were screened from an autodisplayed Fv-antibody library which was expressed on E. coli outer membrane, and the receptor binding domain (RBD) of SP was used as a screening probe. The screened target clones were analyzed to have quantitative binding properties to the RBD, and the Fv-antibodies from the screened target clones were expressed as soluble proteins. The binding affinity (KD) of expressed Fv-antibodies to the RBD was estimated to be 70-85 nM using SPR biosensor. The specific binding properties of Fv-antibodies were analyzed for pseudo-virus particles with SARS-CoV-2 SP on the Lenti-virus envelope, such as wild type (Wuhan-1) and variants (Delta, Omicron BA.2, Omicron BA.4/5) using a SPR biosensor. The detection of real SARS-CoV-2 (Wild type, Wuhan-1) based on a SPR biosensor was also presented using the Fv-antibodies with the binding constant (KD) of cycle threshold value (Ct) = 33.8-32.9 (2.19-4.08 copies/µL) and LOD of 0.67-0.83 copies/µL (Ct = 35.5-35.2). Finally, one-step immunoassay based on switching peptide was demonstrated for the detection of the real SARS-CoV-2 (Wuhan-1) without any washing step. The binding constant (KD) was estimated to be Ct = 35.2-33.9 (0.83-2.04 copies/µL), and LOD was estimated to be 0.14-0.47 copies/µL (Ct = 37.8-36.0). Considering the LOD of the conventional RT-PCR (Ct = 35), the LOD of the one-step immunoassay based on the switching peptide was determined to be feasible for the medical diagnosis of COVID-19.

Rapid classification of SARS-CoV-2 variant strains using machine learning-based label-free SERS strategy.

The spread of COVID-19 over the past three years is largely due to the continuous mutation of the virus, which has significantly impeded global efforts to prevent and control this epidemic. Specifically, mutations in the amino acid sequence of the surface spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have directly impacted its biological functions, leading to enhanced transmission and triggering an immune escape effect. Therefore, prompt identification of these mutations is crucial for formulating targeted treatment plans and implementing precise prevention and control measures. In this study, the label-free surface-enhanced Raman scattering (SERS) technology combined with machine learning (ML) algorithms provide a potential solution for accurate identification of SARS-CoV-2 variants. We establish a SERS spectral database of SARS-CoV-2 variants and demonstrate that a diagnostic classifier using a logistic regression (LR) algorithm can provide accurate results within 10 min. Our classifier achieves 100% accuracy for Beta (B.1.351/501Y.V2), Delta (B.1.617), Wuhan (COVID-19) and Omicron (BA.1) variants. In addition, our method achieves 100% accuracy in blind tests of positive and negative human nasal swabs based on the LR model. This method enables detection and classification of variants in complex biological samples. Therefore, ML-based SERS technology is expected to accurately discriminate various SARS-CoV-2 variants and may be used for rapid diagnosis and therapeutic decision-making.

SARS-CoV-2 genetic variation and bacterial communities of naso-oropharyngeal samples in middle-aged and elderly COVID-19 patients in West Java, Indonesia.

Objective: The number of COVID-19 cases in Indonesia reflects the disease severity and rapid dissemination. In response to the mounting threat, SARS-CoV-2 genomic surveillance and the investigation of naso-oropharyngeal bacterial communities in West Java were conducted, as dysbiosis of the upper respiratory tract microbiota might adversely affect the clinical condition of patients. Methods: We utilized the Oxford Nanopore sequencing platform to analyze genetic variation of 43 samples of SARS-CoV-2 and 11 selected samples for 16S rRNA gene sequencing, using samples collected from May to August 2021. Results: The prevalence of AY.23 (>82%) predominated among five virus lineages in the populations (AY.23, AY.24, AY.26, AY.42, B.1.1.7). The region in the SARS-CoV-2 genome found to have the highest number of mutations was the spike (S) protein (>20%). There was no association between SARS-CoV-2 lineages, mutation frequency, patient profile, and COVID-19 rapid spread-categorized cases. There was no association of bacterial relative abundance, alpha-beta diversity, and linear discriminant analysis effect size analysis with patient profile and rapid spread cases. MetagenomeSeq analysis showed eight differential abundance species in individual patient profiles, including Pseudomonas aeruginosa and Haemophilus parainfluenzae. Conclusions: The data demonstrated relevant AY.23 dominance (the Delta variant) in West Java during that period supporting the importance of surveillance program in monitoring disease progression. The inconsistent results of the bacterial communities suggest that a complex multifactor process may contribute to the progression of bacterial-induced disease in each patient.

Pollution characteristics and source differences of VOCs before and after COVID-19 in Beijing.

During the outbreak of the COVID-19, the change in the way of people's living and production provided the opportunity to study the influence of human activity on Volatile organic compounds (VOCs) in the atmosphere. Therefore, this study analyzed VOCs concentration and composition characteristics in urban area of Beijing from 2019 to 2020. The results showed that the concentration of VOCs in Chaoyang district in 2020 was 73.1ppbv, lower than that in 2019 (92.8ppbv), and alkanes (45 % and 47 %) were the most dominant components. The concentrations of isopentane, n-pentane, n-hexane, and OVOCs significantly increased in 2020. According to the results of the PMF model, the contribution of VOCs from vehicle and pharmaceutical-related emissions increased to 45.8 % and 27.1 % in 2020, while coal combustion decreased by 23.7 %. This is likely linked to the strict implementation of the coal conversion policy, as well as the increment in individual travel and pharmaceutical production during the pandemic. The calculation results of OFP and SOAFP indicated that toluene had an increased impact on the formation of O3 and SOA in the Chaoyang district in 2020. Notably, VOCs emitted by vehicles have the highest potential for secondary generation. In addition, VOCs from vehicles and industries pose the greatest health risks, together accounting for 77.4 % and 79.31 % of the total carcinogenic risk in 2019 and 2020. Although industrial emission with the high proportions of halocarbons was controlled to some extent during the pandemic, the carcinogenic risk in 2020 was 3.74 × 10-6, which still exceeded the acceptable level, and more attention and governance efforts should be given to.

Development of highly sensitive one-step reverse transcription-quantitative PCR for SARS-CoV-2 detection in wastewater.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is a major public health concern that has highlighted the need to monitor circulating strains to better understand the coronavirus disease 2019 (COVID-19) pandemic. This study was carried out to monitor SARS-CoV-2 RNA and its variant-specific mutations in wastewater using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). One-step RT-qPCR using the SARS-CoV-2 Detection RT-qPCR Kit for Wastewater (Takara Bio), which amplified two N-gene regions simultaneously using CDC N1 and N2 assays with a single fluorescence dye, demonstrated better performance in detecting SARS-CoV-2 RNA (positive ratio, 66 %) compared to two-step RT-qPCR using CDC N1 or N2 assay (40 % each, and 52 % when combined), with significantly lower Ct values. The one-step RT-qPCR assay detected SARS-CoV-2 RNA in 59 % (38/64) of influent samples collected from a wastewater treatment plant in Japan between January 2021 and March 2022. The correlation between the concentration of SARS-CoV-2 RNA in the wastewater and the number of COVID-19 cases reported each day for 7 days pre- and post-sampling was significant (p < 0.05, r = 0.76 ± 0.03). Thirty-one influent samples which showed two-well positive for SARS-CoV-2 RNA were further tested by six mutations site-specific one-step RT-qPCR (E484K, L452R, N501Y, T478K, G339D, and E484A mutations). The N501Y mutation was detected between March and June 2021 but was replaced by the L452R and T478K mutations between July and October 2021, reflecting the shift from Alpha to Delta variants in the study region. The G339D and E484A mutations were identified in January 2022 and later when the incidence of the Omicron variant peaked. These findings indicate that wastewater-based epidemiology has the epidemiological potential to complement clinical tests to track the spread of COVID-19 and monitor variants circulating in communities.

Isothermal nucleic acid amplification combined with gold nanoparticles assisted electrochemical impedance for the sensitive and efficient porcine delta coronavirus detection.

The emergence of porcine delta coronavirus (PDCoV) has caused huge economic losses in the global pig industry. How to realize the sensitive and efficient detection for it is a difficult problem that need to be resolved. In this work, loop-mediated isothermal amplification (LAMP)-electrochemical impedance spectroscopy (EIS) detection platform for PDCoV based on nucleic acid level was constructed by combining the advantages of efficient amplification for LAMP and sensitive detection for EIS. Referring to a 159 bp fragment of PDCoV N gene (Genbank：KY078891, 641 bp-799 bp), primers (HS-FIP、BIP、F3、B3) were designed to screened and sulfhydryl groups were activated, and then loop-mediated isothermal amplification was carried out. Subsequently, gold nanoparticles were loaded on indium tin oxide glass by electrodeposition technology, and the amplified products were connected to the electrode surface through the formation of Au-S bonds. According to the difference of charge transfer resistance after double-stranded DNA was connected on the electrode surface, the detection platform can achieve valid detection of PDCoV in the concentration range of 102-107 copies/µL, the limit of detection is 28 copies/µL, and can be used for practical analysis of pig small intestine samples.

A descriptive study on the potential transmission of COVID-19 to hospitalized patients from a nursery school affiliated with it.

INTRODUCTION: During the epidemic of the Omicron variant of SARS-CoV-2, nosocomial transmissions from healthcare workers (HCWs) to patients occur frequently. The influence of COVID-19 on hospitalized patients from nursing schools affiliated with the hospitals is a concern but it had not been well studied. METHODS: We here describe COVID-19 outbreaks at the nursery school affiliated with an acute-care hospital, during the surges of the Omicron variants on the transmission of SARS-CoV-2 children as well as for the patients who were judged to be the close contacts of patients of COVID-19 by contact investigation by PCR testing. RESULTS: A total of 36 children and five caregivers were diagnosed with COVID-19 during the study period. Of the 206 preschoolers who had close contact with the infected persons, only 16 became positive (7.6%). Secondary transmission from the 36 preschool children to the parents as HCWs occurred in 19 (61%) out of 31 parents. Three hospitalized patients were judged to have unsafe contact with the infected HCWs but this did not result in their infections, making a total of zero transmission from the nursery school to the hospital. CONCLUSIONS: Children at the nursery school are potential reservoirs for nosocomial transmissions at the affiliated hospital, but multiple practical measures might have prevented them to occur.

Understanding the contagiousness of Covid-19 strains: A geometric approach.

Protein-protein interaction occurs on surface patches with some degree of complementary geometric and chemical features. Building on this understanding, this study endeavors to characterize the spike protein of the SARS-CoV-2 virus at the morphological and geometrical levels in its Alpha, Delta, and Omicron variants. In particular, the affinity between different SARS-CoV-2 spike proteins and the ACE2 receptor present on the membrane of the human respiratory system cells is investigated. To achieve an adequate degree of geometrical accuracy, the 3D depth maps of the proteins in exam are filtered by developing an ad-hoc convolutional filter with a kernel implemented as a sphere of varying radius, simulating a ball rolling on the surface (similar to the 'rolling ball' filter). This ball ideally models a hypothetical molecule that could interface with the protein and is inspired by the geometric approach to macromolecule-ligand interactions proposed by Kuntz et al. in 1982. The aim is to mitigate the imperfections and to obtain a smoother surface that could be studied from a geometrical perspective for binding purposes. A set of geometric descriptors, borrowed from the 3D face analysis context is then mapped point-by-point onto protein depth maps. Following a feature extraction phase inspired by Histogram of Oriented Gradients and Local Binary Patterns, the final histogram features are used as input for a Support Vector Machine classifier to automatically classify the proteins according to their surface affinity, where a similarity in shape is observed between ACE2 and the spike protein of the SARS-CoV-2 Omicron variant. Finally, Root Mean Square Error analysis is used to quantify the geometrical affinity between the ACE2 receptor and the respective Receptor Binding Domains of the three SARS-CoV-2 variants, culminating in a geometrical explanation for the higher contagiousness of Omicron relative to the other variants under study.

Remission of severe forms of long COVID following monoclonal antibody (MCA) infusions: A report of signal index cases and call for targeted research.

OBJECTIVE: Long COVID has afflicted tens of millions globally leaving many previously-healthy persons severely and indefinitely debilitated. The objective here was to report cases of complete, rapid remission of severe forms of long COVID following certain monoclonal antibody (MCA) infusions and review the corresponding pathophysiological implications. DESIGN: Case histories of the first three index events (among others) are presented. Unaware of others with similar remissions, each subject independently completed personal narratives and standardized surveys regarding demographics/occupation, past history, and the presence and respective severity grading of 33 signs/symptoms associated with long COVID, comparing the presence/severity of those symptoms during the pre-COVID, long-COVID, post-vaccination, and post-MCA phases. SETTING: Patient interviews, e-mails and telephone conversations. SUBJECTS: Three previously healthy, middle-aged, highly-functioning persons, two women and one man (ages 60, 43, and 63 years respectively) who, post-acute COVID-19 infection, developed chronic, unrelenting fatigue and cognitive impairment along with other severe, disabling symptoms. Each then independently reported incidental and unanticipated complete remissions within days of MCA treatment. INTERVENTIONS: The casirivimab/imdevimab cocktail. MEASUREMENTS AND MAIN RESULTS: Irrespective of sex, age, medical history, vaccination status, or illness duration (18, 8 and 5 months, respectively), each subject experienced the same complete remission of their persistent disabling disease within a week of MCA infusion. Each rapidly returned to normal health and previous lifestyles/occupations with normalized exercise tolerance, still sustained to date over two years later. CONCLUSIONS: These index cases provide compelling clinical signals that MCA infusions may be capable of treating long COVID in certain cases, including those with severe debilitation. While the complete and sustained remissions observed here may only apply to long COVID resulting from pre-Delta variants and the specific MCA infused, the striking rapid and complete remissions observed in these cases also provide mechanistic implications for treating/managing other post-viral chronic conditions and long COVID from other variants.

Implementing an adaptive, two-tiered SARS-CoV-2 wastewater surveillance program on a university campus using passive sampling.

Building-level wastewater-based surveillance (WBS) has been increasingly applied upstream from wastewater treatment plants to conduct targeted monitoring for SARS-CoV-2. In this study, a two-tiered, trigger-based wastewater surveillance program was developed on a university campus to monitor dormitory wastewater. The objective was to determine if passive sampling with cotton gauze as a sampling medium could be used to support institution-level public health action. Two nucleocapsid gene targets (N1 and N2) of SARS-CoV-2 as well as the endogenous fecal indicator pepper mild mottle virus (PMMoV) were quantified using RT-qPCR. >500 samples were analyzed during two contrasting surveillance periods. In the Fall of 2021 community viral burden was low and a tiered sampling network was able to isolate individual clinical cases at the building-scale. In the Winter of 2022 wastewater signals were quickly elevated by the emergence of the highly transmissible SARS-CoV-2 Omicron (B.1.1.529) variant. Prevalence of SARS-CoV-2 shifted surveillance objectives from isolating cases to monitoring trends, revealing both the benefits and limitations of a tiered surveillance design under different public health situations. Normalization of SARS-CoV-2 by PMMoV was not reflective of upstream population differences, suggesting saturation of the material occurred during the exposure period. The passive sampling method detected nearly all known clinical cases and in one instance was able to identify one pre-symptomatic individual days prior to confirmation by clinical test. Comparisons between campus samplers and municipal wastewater influent suggests that the spread of COVID-19 on the campus was similar to that of the broader community. The results demonstrate that passive sampling is an effective tool that can produce semi-quantitative data capable of tracking temporal trends to guide targeted public health decision-making at an institutional level. Practitioners of WBS can utilize these results to inform surveillance program designs that prioritize efficient resource use and rapid reporting.

Neutralization of SARS-CoV-2 Omicron BQ.1, BQ.1.1 and XBB.1 variants following SARS-CoV-2 infection or vaccination in children.

Emergence of highly transmissible Omicron subvariants led to increased SARS-CoV-2 infection and disease in children. However, minimal knowledge exists regarding the neutralization capacity against circulating Omicron BA.4/BA.5, BA.2.75, BQ.1, BQ.1.1 and XBB.1 subvariants following SARS-CoV-2 vaccination in children versus during acute or convalescent COVID-19, or versus multisystem inflammatory syndrome (MIS-C). Here, we evaluate virus-neutralizing capacity against SARS-CoV-2 variants in 151 age-stratified children ( <5, 5-11, 12-21 years old) hospitalized with acute severe COVID-19 or MIS-C or convalescent mild (outpatient) infection compared with 62 age-stratified vaccinated children. An age-associated effect on neutralizing antibodies is observed against SARS-CoV-2 following acute COVID-19 or vaccination. The primary series BNT162b2 mRNA vaccinated adolescents show higher vaccine-homologous WA-1 neutralizing titers compared with <12 years vaccinated children. Post-infection antibodies did not neutralize BQ.1, BQ.1.1 and XBB.1 subvariants. In contrast, monovalent mRNA vaccination induces more cross-neutralizing antibodies in young children <5 years against BQ.1, BQ.1.1 and XBB.1 variants compared with ≥5 years old children. Our study demonstrates that in children, infection and monovalent vaccination-induced neutralization activity is low against BQ.1, BQ.1.1 and XBB.1 variants. These findings suggest a need for improved SARS-CoV-2 vaccines to induce durable, more cross-reactive neutralizing antibodies to provide effective protection against emerging variants in children.

Safety, immunogenicity and efficacy of an mRNA-based COVID-19 vaccine, GLB-COV2-043, in preclinical animal models.

Several COVID-19 vaccines, some more efficacious than others, are now available and deployed, including multiple mRNA- and viral vector-based vaccines. With the focus on creating cost-effective solutions that can reach the low- and medium- income world, GreenLight Biosciences has developed an mRNA vaccine candidate, GLB-COV2-043, encoding for the full-length SARS-CoV-2 Wuhan wild-type spike protein. In pre-clinical studies in mice, GLB-COV2-043 induced robust antigen-specific binding and virus-neutralizing antibody responses targeting homologous and heterologous SARS-CoV-2 variants and a TH1-biased immune response. Boosting mice with monovalent or bivalent mRNA-LNPs provided rapid recall and long-lasting neutralizing antibody titers, an increase in antibody avidity and breadth that was held over time and generation of antigen-specific memory B- and T- cells. In hamsters, vaccination with GLB-COV2-043 led to lower viral loads, reduced incidence of SARS-CoV-2-related microscopic findings in lungs, and protection against weight loss after heterologous challenge with Omicron BA.1 live virus. Altogether, these data indicate that GLB-COV2-043 mRNA-LNP vaccine candidate elicits robust protective humoral and cellular immune responses and establishes our mRNA-LNP platform for subsequent clinical evaluations.