Molecular evidence for SARS-CoV-2 in samples collected from patients with morbilliform eruptions since late 2019 in Lombardy, northern Italy.

As a reference laboratory for measles and rubella surveillance in Lombardy, we evaluated the association between SARS-CoV-2 infection and measles-like syndromes, providing preliminary evidence for undetected early circulation of SARS-CoV-2. Overall, 435 samples from 156 cases were investigated. RNA from oropharyngeal swabs (N = 148) and urine (N = 141) was screened with four hemi-nested PCRs and molecular evidence for SARS-CoV-2 infection was found in 13 subjects. Two of the positive patients were from the pandemic period (2/12, 16.7%, March 2020-March 2021) and 11 were from the pre-pandemic period (11/44, 25%, August 2019-February 2020). Sera (N = 146) were tested for anti-SARS-CoV-2 IgG, IgM, and IgA antibodies. Five of the RNA-positive individuals also had detectable anti-SARS-CoV-2 antibodies. No strong evidence of infection was found in samples collected between August 2018 and July 2019 from 100 patients. The earliest sample with evidence of SARS-CoV-2 RNA was from September 12, 2019, and the positive patient was also positive for anti-SARS-CoV-2 antibodies (IgG and IgM). Mutations typical of B.1 strains previously reported to have emerged in January 2020 (C3037T, C14408T, and A23403G), were identified in samples collected as early as October 2019 in Lombardy. One of these mutations (C14408T) was also identified among sequences downloaded from public databases that were obtained by others from samples collected in Brazil in November 2019. We conclude that a SARS-CoV-2 progenitor capable of producing a measles-like syndrome may have emerged in late June-late July 2019 and that viruses with mutations characterizing B.1 strain may have been spreading globally before the first Wuhan outbreak. Our findings should be complemented by high-throughput sequencing to obtain additional sequence information. We highlight the importance of retrospective surveillance studies in understanding the early dynamics of COVID-19 spread and we encourage other groups to perform retrospective investigations to seek confirmatory proofs of early SARS-CoV-2 circulation.

Bendamustine in combination with pomalidomide and dexamethasone in relapsed/refractory multiple myeloma: A phase II trial.

Treatment of patients with resistant/refractory multiple myeloma (MM) is an unmet need. In this phase II study, we evaluated the role of bendamustine, pomalidomide and dexamethasone combination in this setting. Between February 2020 and December 2021, 28 patients were recruited. Patients received bendamustine 120 mg/m2 day 1, pomalidomide 3 mg days 1-21, and dexamethasone 40 mg days 1, 8, 11, 22, regimen given for a maximum of six cycles. The median (range) age of the patients was 54 (30-76) years and 15 (53.6%) were males. Patients had received a median (range) of three (two-six) prior lines and 85.7% were refractory to both lenalidomide and bortezomib. The primary end-point was the overall response rate (ORR) defined as ≥partial response after at least three cycles. Secondary objectives were toxicity, progression-free survival (PFS), time to progression and overall survival (OS). An intent-to-treat analysis was done. An ORR of 57.6% was achieved. Patients with extramedullary myeloma had a better response rate. At a median follow-up of 8.6 months, the median PFS and OS were 6.2 and 9.7 months respectively. Toxicity was manageable; mainly haematological (neutropenia, 46.4%; anaemia, 42.8%; and thrombocytopenia, 7.1%). Bendamustine, pomalidomide and dexamethasone could be a novel combination for the heavily pretreated, lenalidomide-refractory myeloma population.

Trends in antibiotic use before and during the coronavirus disease 2019 (COVID-19) pandemic across an integrated health system with different antimicrobial stewardship program models trends in antibiotic use by ASP model.

Changes in antimicrobial use during the pandemic in relation to long-term trends in utilization among different antimicrobial stewardship program models have not been fully characterized. We analyzed data from an integrated health system using joinpoint regression and found temporal fluctuations in prescribing as well as continuation of existing trends.

TopHap: Rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity.

MOTIVATION: Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of SARS-CoV-2 strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites and millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate and fast phylogenetic inference of resolvable phylogenetic features. RESULTS: We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. We develop a bootstrap resampling strategy that resamples genomes spatiotemporally to assess topological robustness. The application of TopHap to build a phylogeny of 68,057 SARS-CoV-2 genomes (68KG) from the first year of the pandemic produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million SARS-CoV-2 genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major variants of concern. AVAILABILITY: TopHap is available at https://github.com/SayakaMiura/TopHap.

Waiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?

Two years after the start of the COVID-19 pandemic, key questions about the emergence of its aetiological agent (SARS-CoV-2) remain a matter of considerable debate. Identifying when SARS-CoV-2 began spreading among people is one of those questions. Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time. However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests. In this paper, we critically review current evidence that SARS-CoV-2 had been circulating prior to December of 2019, and emphasise how, despite some scientific limitations, this hypothesis should no longer be ignored and considered sufficient to warrant further larger-scale studies to determine its veracity.

Thioredoxin Prevents Loss of UCP2 in Hyperoxia via MKK4-p38 MAPK-PGC1α Signaling and Limits Oxygen Toxicity.

Administration of high concentrations of oxygen (hyperoxia) is one of few available options to treat acute hypoxemia-related respiratory failure, as seen in the current coronavirus disease (COVID-19) pandemic. Although hyperoxia can cause acute lung injury through increased production of superoxide anion (O2•-), the choice of high-concentration oxygen administration has become a necessity in critical care. The objective of this study was to test the hypothesis that UCP2 (uncoupling protein 2) has a major function of reducing O2•- generation in the lung in ambient air or in hyperoxia. Lung epithelial cells and wild-type; UCP2-/-; or transgenic, hTrx overexpression-bearing mice (Trx-Tg) were exposed to hyperoxia and O2•- generation was measured by using electron paramagnetic resonance, and lung injury was measured by using histopathologic analysis. UCP2 expression was analyzed by using RT-PCR analysis, Western blotting analysis, and RNA interference. The signal transduction pathways leading to loss of UCP2 expression were analyzed by using IP, phosphoprotein analysis, and specific inhibitors. UCP2 mRNA and protein expression were acutely decreased in hyperoxia, and these decreases were associated with a significant increase in O2•- production in the lung. Treatment of cells with rhTrx (recombinant human thioredoxin) or exposure of Trx-Tg mice prevented the loss of UCP2 protein and decreased O2•- generation in the lung. Trx is also required to maintain UCP2 expression in normoxia. Loss of UCP2 in UCP2-/- mice accentuated lung injury in hyperoxia. Trx activates the MKK4-p38MAPK (p38 mitogen-activated protein kinase)-PGC1α (PPARγ [peroxisome proliferator-activated receptor γ] coactivator 1α) pathway, leading to rescue of UCP2 and decreased O2•- generation in hyperoxia. Loss of UCP2 in hyperoxia is a major mechanism of O2•- production in the lung in hyperoxia. rhTrx can protect against lung injury in hyperoxia due to rescue of the loss of UCP2.

The durability of immunity against reinfection by SARS-CoV-2: a comparative evolutionary study.

BACKGROUND: Among the most consequential unknowns of the devastating COVID-19 pandemic are the durability of immunity and time to likely reinfection. There are limited direct data on SARS-CoV-2 long-term immune responses and reinfection. The aim of this study is to use data on the durability of immunity among evolutionarily close coronavirus relatives of SARS-CoV-2 to estimate times to reinfection by a comparative evolutionary analysis of related viruses SARS-CoV, MERS-CoV, human coronavirus (HCoV)-229E, HCoV-OC43, and HCoV-NL63. METHODS: We conducted phylogenetic analyses of the S, M, and ORF1b genes to reconstruct a maximum-likelihood molecular phylogeny of human-infecting coronaviruses. This phylogeny enabled comparative analyses of peak-normalised nucleocapsid protein, spike protein, and whole-virus lysate IgG antibody optical density levels, in conjunction with reinfection data on endemic human-infecting coronaviruses. We performed ancestral and descendent states analyses to estimate the expected declines in antibody levels over time, the probabilities of reinfection based on antibody level, and the anticipated times to reinfection after recovery under conditions of endemic transmission for SARS-CoV-2, as well as the other human-infecting coronaviruses. FINDINGS: We obtained antibody optical density data for six human-infecting coronaviruses, extending from 128 days to 28 years after infection between 1984 and 2020. These data provided a means to estimate profiles of the typical antibody decline and probabilities of reinfection over time under endemic conditions. Reinfection by SARS-CoV-2 under endemic conditions would likely occur between 3 months and 5·1 years after peak antibody response, with a median of 16 months. This protection is less than half the duration revealed for the endemic coronaviruses circulating among humans (5-95% quantiles 15 months to 10 years for HCoV-OC43, 31 months to 12 years for HCoV-NL63, and 16 months to 12 years for HCoV-229E). For SARS-CoV, the 5-95% quantiles were 4 months to 6 years, whereas the 95% quantiles for MERS-CoV were inconsistent by dataset. INTERPRETATION: The timeframe for reinfection is fundamental to numerous aspects of public health decision making. As the COVID-19 pandemic continues, reinfection is likely to become increasingly common. Maintaining public health measures that curb transmission-including among individuals who were previously infected with SARS-CoV-2-coupled with persistent efforts to accelerate vaccination worldwide is critical to the prevention of COVID-19 morbidity and mortality. FUNDING: US National Science Foundation.

Pathogenetic factors fanning the flames of COVID-19 to cause rhino-orbito-cerebral mucormycosis: An observational study.

BACKGROUND AND AIMS: Published studies on coronavirus disease 19 (COVID-19) associated rhino-orbito-cerebral mucormycosis (CAROCM) were primarily descriptive. Therefore, we aimed to identify features of COVID-19 that could predispose to CAROCM and explore the pathogenic pathways. PATIENTS AND METHODS: This retrospective hospital-based study was done during the first (March 2020 - January 2021) and the second (February 2021 - June 2021) waves of the COVID-19 pandemic. Subjects were grouped into four categories: first-wave CAROCM (n-4); second-wave CAROCM (n-27); first-wave non-mucor COVID (n-75), and second-wave non-mucor COVID (n-50). Data elements included age, gender, comorbidities, COVID-19 severity, steroid therapy, peak values of interleukin-6 (IL-6), serum ferritin and D-dimer, nadir values of absolute lymphocyte count (ALC), absolute neutrophil count (ANC) and platelet count (Pl. C). RESULTS: Thirty-one patients of CAROCM were included. The mean (SD) age was 51.26 (11.48) years. 27 (87.1%) were aged ≥ 40 years and males. Severe COVID-19 was seen more often in the second wave than the first wave (P-0.001). CAROCM group was significantly younger (P-0.008) and showed a higher incidence of uncontrolled diabetes (P-0.001) and renal dysfunction (P-0.004) than non-mucor COVID. While IL-6, ferritin and D-dimer were significantly elevated in CAROCM than non-mucor COVID, clinical severity, ANC, ALC and Pl. C showed no significant difference. CONCLUSION: CAROCM is seen often in middle-aged diabetic males with uncontrolled hyperglycaemia, diabetic ketoacidosis, renal dysfunction and those infected by more transmissible delta variants and treated with steroids. IL-6, D-dimer, serum ferritin are more often elevated in CAROCM and might play a pathogenic role.

An Evolutionary Portrait of the Progenitor SARS-CoV-2 and Its Dominant Offshoots in COVID-19 Pandemic.

Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic.

We report the likely most recent common ancestor of SARS-CoV-2 - the coronavirus that causes COVID-19. This progenitor SARS-CoV-2 genome was recovered through a novel application and advancement of computational methods initially developed to reconstruct the mutational history of tumor cells in a patient. The progenitor differs from the earliest coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the USA harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide as soon as weeks after the first reported cases of COVID-19. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains, which have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic. There have been multiple replacements of predominant coronavirus strains in Europe and Asia and the continued presence of multiple high-frequency strains in Asia and North America. We provide a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

Where Did SARS-CoV-2 Come From?

Identifying the origin of SARS-CoV-2, the etiological agent of the current COVID-19 pandemic, may help us to avoid future epidemics of coronavirus and other zoonoses. Several theories about the zoonotic origin of SARS-CoV-2 have recently been proposed. Although Betacoronavirus found in Rhinolophus bats from China have been broadly implicated, their genetic dissimilarity to SARS-CoV-2 is so high that they are highly unlikely to be its direct ancestors. Thus, an intermediary host is suspected to link bat to human coronaviruses. Based on genomic CpG dinucleotide patterns in different coronaviruses from different hosts, it was suggested that SARS-CoV-2 might have evolved in a canid gastrointestinal tract prior to transmission to humans. However, similar CpG patterns are now reported in coronaviruses from other hosts, including bats themselves and pangolins. Therefore, reduced genomic CpG alone is not a highly predictive biomarker, suggesting a need for additional biomarkers to reveal intermediate hosts or tissues. The hunt for the zoonotic origin of SARS-CoV-2 continues.