A complete map of the Calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) signaling pathway

Calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) is a serine/threonine-protein kinase belonging to the Ca²⁺/calmodulin-dependent protein kinase subfamily. CAMKK2 has an autocatalytic site, which gets exposed when Ca²⁺/calmodulin (CAM) binds to it. This results in autophosphorylation and complete activation of CAMKK2. The three major known downstream targets of CAMKK2 are 5′-adenosine monophosphate (AMP)-activated protein kinase (AMPKα), calcium/calmodulin-dependent protein kinase 1 (CAMK1) and calcium/calmodulin-dependent protein kinase 4 (CAMK4). Activation of these targets by CAMKK2 is important for the maintenance of different cellular and physiological processes within the cell. CAMKK2 is found to be important in neuronal development, bone remodeling, adipogenesis, and systemic glucose homeostasis, osteoclastgensis and postnatal myogensis. CAMKK2 is reported to be involved in pathologies like Duchenne muscular dystrophy, inflammation, osteoporosis and bone remodeling and is also reported to be overexpressed in prostate cancer, hepatic cancer, ovarian and gastric cancer. CAMKK2 is involved in increased cell proliferation and migration through CAMKK2/AMPK pathway in prostate cancer and activation of AKT in ovarian cancer. Although CAMKK2 is a molecule of great importance, a public resource of the CAMKK2 signaling pathway is currently lacking. Therefore, we carried out detailed data mining and documentation of the signaling events associated with CAMKK2 from published literature and developed an integrated reaction map of CAMKK2 signaling. This resulted in the cataloging of 285 reactions belonging to the CAMKK2 signaling pathway, which includes 33 protein–protein interactions, 74 post-translational modifications, 7 protein translocation events, and 22 activation/inhibition events. Besides, 124 gene regulation events and 25 activator/inhibitors involved in CAMKK2 activation were also cataloged. The CAMKK2 signaling pathway map data is made freely accessible through WikiPathway database (https://www.wikipathways.org/index.php/Pathway:WP4874). We expect that data on a signaling map of CAMKK2 will provide the scientific community with an improved platform to facilitate further molecular as well as biomedical investigations on CAMKK2 and its utility in the development of biomarkers and therapeutic targets.Electronic supplementary materialThe online version of this article (10.1007/s12079-020-00592-1) contains supplementary material, which is available to authorized users.     

De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures

The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta''s FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5′ UTR; the reverse complement of the 5′ UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3′ UTR. For eleven of these elements (the stems in SL1–8, reverse complement of SL1–4, FSE, s2m and 3′ UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets (‘FARFAR2-SARS-CoV-2’, https://github.com/DasLab/FARFAR2-SARS-CoV-2; and ‘FARFAR2-Apo-Riboswitch’, at https://github.com/DasLab/FARFAR2-Apo-Riboswitch’) include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.     

SARS-CoV-2 outbreak in a tri-national urban area is dominated by a B.1 lineage variant linked to a mass gathering event

The first case of SARS-CoV-2 in Basel, Switzerland was detected on February 26^th 2020. We present a phylogenetic study to explore viral introduction and evolution during the exponential early phase of the local COVID-19 outbreak from February 26^th until March 23^rd. We sequenced SARS-CoV-2 naso-oropharyngeal swabs from 746 positive tests that were performed at the University Hospital Basel during the study period. We successfully generated 468 high quality genomes from unique patients and called variants with our COVID-19 Pipeline (COVGAP), and analysed viral genetic diversity using PANGOLIN taxonomic lineages. To identify introduction and dissemination events we incorporated global SARS-CoV-2 genomes and inferred a time-calibrated phylogeny. Epidemiological data from patient questionnaires was used to facilitate the interpretation of phylogenetic observations. The early outbreak in Basel was dominated by lineage B.1 (83·6%), detected first on March 2^nd, although the first sample identified belonged to B.1.1. Within B.1, 68·2% of our samples fall within a clade defined by the SNP C15324T (‘Basel cluster’), including 157 identical sequences at the root of the ‘Basel cluster’, some of which we can specifically trace to regional spreading events. We infer the origin of B.1-C15324T to mid-February in our tri-national region. The other genomes map broadly over the global phylogenetic tree, showing several introduction events from and/or dissemination to other regions of the world via travellers. Family transmissions can also be traced in our data. A single lineage variant dominated the outbreak in the Basel area while other lineages, such as the first (B.1.1), did not propagate. A mass gathering event was the predominant initial source of cases, with travel returners and family transmissions to a lesser extent. We highlight the importance of adding specific questions to epidemiological questionnaires, to obtain data on attendance of large gatherings and their locations, as well as travel history, to effectively identify routes of transmissions in up-coming outbreaks. This phylogenetic analysis in concert with epidemiological and contact tracing data, allows connection and interpretation of events, and can inform public health interventions.Trial Registration: ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT04351503","term_id":"NCT04351503"}}NCT04351503.     

Identifying modules of cooperating cancer drivers

Identifying cooperating modules of driver alterations can provide insights into cancer etiology and advance the development of effective personalized treatments. We present Cancer Rule Set Optimization (CRSO) for inferring the combinations of alterations that cooperate to drive tumor formation in individual patients. Application to 19 TCGA cancer types revealed a mean of 11 core driver combinations per cancer, comprising 2–6 alterations per combination and accounting for a mean of 70% of samples per cancer type. CRSO is distinct from methods based on statistical co‐occurrence, which we demonstrate is a suboptimal criterion for investigating driver cooperation. CRSO identified well‐studied driver combinations that were not detected by other approaches and nominated novel combinations that correlate with clinical outcomes in multiple cancer types. Novel synergies were identified in NRAS‐mutant melanomas that may be therapeutically relevant. Core driver combinations involving NFE2L2 mutations were identified in four cancer types, supporting the therapeutic potential of NRF2 pathway inhibition. CRSO is available at https://github.com/mikekleinsgit/CRSO/.     

The impact of COVID-19 on pregnancy outcomes: a systematic review and meta-analysis

Background:The impact of coronavirus disease 2019 (COVID-19) on maternal and newborn health is unclear. We aimed to evaluate the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy and adverse pregnancy outcomes.METHODS:We conducted a systematic review and meta-analysis of observational studies with comparison data on SARS-CoV-2 infection and severity of COVID-19 during pregnancy. We searched for eligible studies in MEDLINE, Embase, ClinicalTrials.gov, medRxiv and Cochrane databases up to Jan. 29, 2021, using Medical Subject Headings terms and keywords for “severe acute respiratory syndrome coronavirus 2 OR SARS-CoV-2 OR coronavirus disease 2019 OR COVID-19” AND “pregnancy.” We evaluated the methodologic quality of all included studies using the Newcastle–Ottawa Scale. Our primary outcomes were preeclampsia and preterm birth. Secondary outcomes included stillbirth, gestational diabetes and other pregnancy outcomes. We calculated summary odds ratios (ORs) or weighted mean differences with 95% confidence intervals (CI) using random-effects meta-analysis.RESULTS:We included 42 studies involving 438 548 people who were pregnant. Compared with no SARS-CoV-2 infection in pregnancy, COVID-19 was associated with preeclampsia (OR 1.33, 95% CI 1.03 to 1.73), preterm birth (OR 1.82, 95% CI 1.38 to 2.39) and stillbirth (OR 2.11, 95% CI 1.14 to 3.90). Compared with mild COVID-19, severe COVID-19 was strongly associated with preeclampsia (OR 4.16, 95% CI 1.55 to 11.15), preterm birth (OR 4.29, 95% CI 2.41 to 7.63), gestational diabetes (OR 1.99, 95% CI 1.09 to 3.64) and low birth weight (OR 1.89, 95% CI 1.14 to 3.12).INTERPRETATION:COVID-19 may be associated with increased risks of preeclampsia, preterm birth and other adverse pregnancy outcomes.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and was declared a global pandemic in March 2020.¹ Pregnant people and infants may be particularly susceptible to COVID-19 because the physiologic changes of pregnancy involve cardiorespiratory and immune systems, which may result in an altered response to SARS-CoV-2 infection in pregnancy. ² Fetuses may be exposed to SARS-CoV-2 during critical periods of fetal development.³ The nature of the association between COVID-19 and pregnancy outcomes remains unclear, and meta-analyses involving patients with COVID-19 who are pregnant are limited. Previous reviews have focused mostly on prevalence estimates from case reports or case series that are difficult to interpret and potentially biased.^4,5 A 2020 systematic review suggested that people who are pregnant did not have an increased risk of SARS-CoV-2 infection or symptomatic COVID-19, but they were at risk of severe COVID-19 compared with those who were not pregnant.⁵ However, this review included suspected COVID-19 cases in addition to confirmed cases.⁵ Although some recent observational studies have suggested that people with confirmed asymptomatic and symptomatic COVID-19,^6–15 as well as mild and severe infections,^{6,8,9,15–22} may be at risk of adverse pregnancy outcomes, we are unaware of any systematic reviews that have comprehensively evaluated these data.We performed a systematic review and meta-analysis of maternal, fetal and neonatal outcomes among pregnant patients with COVID-19. We aimed to determine the association between SARS-CoV-2 infection and adverse pregnancy outcomes, including preeclampsia, preterm birth and stillbirth.     

Recent Clinical Trials on Natural Products and Traditional Chinese Medicine Combating the COVID-19

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing potentially fatal coronavirus disease-19 (COVID-19), with a significant health and economic burden around the globe. Currently many clinical studies are undergoing but still there is no any specific approved therapy or drug established for effective treatment of COVID-19. This review aimed to analyses various clinical studies which have been registered in www.clinicaltrials.gov and http://www.chictr.org.cn were registered with natural plant-based medicines and Traditional Chinese medicine (TCM) for discovering effective treatment and prevention of COVID-19. Total 46 and 64 natural drug and TCM interventions were identified which mainly determined the preventive strategies and possible treatments for COVID-19 infection. We identified that most of the clinical trial undergoing on natural compound like heparin and vitamin C as therapeutic agents and immune boosters for against COVID-19. Traditional Chinese medicines and herbal medicines can be effectively used as a preventive therapy against COVID-19 and after successful clinical trials and these potential therapies can be promoted by countries around the world. Supplementary InformationThe online version contains supplementary material available at (10.1007/s12088-020-00919-x).     

Early versus deferred anti-SARS-CoV-2 convalescent plasma in patients admitted for COVID-19: A randomized phase II clinical trial

BackgroundConvalescent plasma (CP), despite limited evidence on its efficacy, is being widely used as a compassionate therapy for hospitalized patients with COVID-19. We aimed to evaluate the efficacy and safety of early CP therapy in COVID-19 progression.Methods and findingsThe study was an open-label, single-center randomized clinical trial performed in an academic medical center in Santiago, Chile, from May 10, 2020, to July 18, 2020, with final follow-up until August 17, 2020. The trial included patients hospitalized within the first 7 days of COVID-19 symptom onset, presenting risk factors for illness progression and not on mechanical ventilation. The intervention consisted of immediate CP (early plasma group) versus no CP unless developing prespecified criteria of deterioration (deferred plasma group). Additional standard treatment was allowed in both arms. The primary outcome was a composite of mechanical ventilation, hospitalization for >14 days, or death. The key secondary outcomes included time to respiratory failure, days of mechanical ventilation, hospital length of stay, mortality at 30 days, and SARS-CoV-2 real-time PCR clearance rate. Of 58 randomized patients (mean age, 65.8 years; 50% male), 57 (98.3%) completed the trial. A total of 13 (43.3%) participants from the deferred group received plasma based on clinical aggravation. We failed to find benefit in the primary outcome (32.1% versus 33.3%, odds ratio [OR] 0.95, 95% CI 0.32–2.84, p > 0.999) in the early versus deferred CP group. The in-hospital mortality rate was 17.9% versus 6.7% (OR 3.04, 95% CI 0.54–17.17 p = 0.246), mechanical ventilation 17.9% versus 6.7% (OR 3.04, 95% CI 0.54–17.17, p = 0.246), and prolonged hospitalization 21.4% versus 30.0% (OR 0.64, 95% CI, 0.19–2.10, p = 0.554) in the early versus deferred CP group, respectively. The viral clearance rate on day 3 (26% versus 8%, p = 0.204) and day 7 (38% versus 19%, p = 0.374) did not differ between groups. Two patients experienced serious adverse events within 6 hours after plasma transfusion. The main limitation of this study is the lack of statistical power to detect a smaller but clinically relevant therapeutic effect of CP, as well as not having confirmed neutralizing antibodies in donor before plasma infusion.ConclusionsIn the present study, we failed to find evidence of benefit in mortality, length of hospitalization, or mechanical ventilation requirement by immediate addition of CP therapy in the early stages of COVID-19 compared to its use only in case of patient deterioration.Trial registration{"type":"clinical-trial","attrs":{"text":"NCT04375098","term_id":"NCT04375098"}}NCT04375098.

In this randomized trial, María Elvira Balcells and colleagues demonstrate that there is no benefit in immediate versus delayed convalescent plasma administration for COVID-19 patients.     

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.     

Serum Protein Profiling Reveals a Landscape of Inflammation and Immune Signaling in Early-stage COVID-19 Infection

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Highlights

• •In-depth profiling of the serum proteome in early-stage COVID-19 patients.
• •A landscape of inflammation and immune signaling related to the SARS-CoV-2 infection.
• •CCL2 and CXCL10 medicated cytokine signaling pathways may correlate with neutrophil and lymphocyte respectively.

     

A Daily-Updated Database and Tools for Comprehensive SARS-CoV-2 Mutation-Annotated Trees

The vast scale of SARS-CoV-2 sequencing data has made it increasingly challenging to comprehensively analyze all available data using existing tools and file formats. To address this, we present a database of SARS-CoV-2 phylogenetic trees inferred with unrestricted public sequences, which we update daily to incorporate new sequences. Our database uses the recently proposed mutation-annotated tree (MAT) format to efficiently encode the tree with branches labeled with parsimony-inferred mutations, as well as Nextstrain clade and Pango lineage labels at clade roots. As of June 9, 2021, our SARS-CoV-2 MAT consists of 834,521 sequences and provides a comprehensive view of the virus’ evolutionary history using public data. We also present matUtils—a command-line utility for rapidly querying, interpreting, and manipulating the MATs. Our daily-updated SARS-CoV-2 MAT database and matUtils software are available at http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/ and https://github.com/yatisht/usher, respectively.     

Neutralizing antibody responses over time in demographically and clinically diverse individuals recovered from SARS-CoV-2 infection in the United States and Peru: A cohort study

BackgroundPeople infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) experience a wide range of clinical manifestations, from asymptomatic and mild illness to severe illness and death, influenced by age and a variety of comorbidities. Neutralizing antibodies (nAbs) are thought to be a primary immune defense against the virus. Large, diverse, well-characterized cohorts of convalescent individuals provide standardized values to benchmark nAb responses to past SARS-CoV-2 infection and define potentially protective levels of immunity.Methods and findingsThis analysis comprises an observational cohort of 329 HIV–seronegative adults in the United States (n = 167) and Peru (n = 162) convalescing from SARS-CoV-2 infection from May through October 2020. The mean age was 48 years (range 18 to 86), 54% of the cohort overall was Hispanic, and 34% identified as White. nAb titers were measured in serum by SARS-CoV-2.D614G Spike-pseudotyped virus infection of 293T/ACE2 cells. Multiple linear regression was applied to define associations between nAb titers and demographic variables, disease severity and time from infection or disease onset, and comorbidities within and across US and Peruvian cohorts over time. nAb titers peaked 28 to 42 days post-diagnosis and were higher in participants with a history of severe Coronavirus Disease 2019 (COVID-19) (p < 0.001). Diabetes, age >55 years, male sex assigned at birth, and, in some cases, body mass index were also independently associated with higher nAb titers, whereas hypertension was independently associated with lower nAb titers. nAb titers did not differ by race, underlying pulmonary disease or smoking. Two months post-enrollment, nAb ID50 (ID80) titers declined 3.5 (2.8)-fold overall. Study limitations in this observational, convalescent cohort include survivorship bias and missing early viral loads and acute immune responses to correlate with the convalescent responses we observed.ConclusionsIn summary, in our cohort, nAb titers after SARS-CoV-2 infection peaked approximately 1 month post-diagnosis and varied by age, sex assigned at birth, disease severity, and underlying comorbidities. Our data show great heterogeneity in nAb responses among people with recent COVID-19, highlighting the challenges of interpreting natural history studies and gauging responses to vaccines and therapeutics among people with recent infection. Our observations illuminate potential correlations of demographic and clinical characteristics with nAb responses, a key element for protection from COVID-19, thus informing development and implementation of preventative and therapeutic strategies globally.Trial registrationClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT04403880","term_id":"NCT04403880"}}NCT04403880.

Shelly Karuna and co-workers study variations in neutralizing antibody responses after SARS-CoV-2 infection.     

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/).     

A pathway map of signaling events triggered upon SARS-CoV infection

Severe acute respiratory syndrome coronaviruses (SARS-CoVs) caused worldwide epidemics over the past few decades. Extensive studies on various strains of coronaviruses provided a basic understanding of the pathogenesis of the disease. Presently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading a global pandemic with unprecedented challenges. This is the third coronavirus outbreak of this century. A signaling pathway map of signaling events induced by SARS-CoV infection is not yet available. In this study, we present a literature-annotated signaling pathway map of reactions induced by SARS-CoV infected cells. Multiple signaling modules were found to be orchestrated including PI3K-AKT, Ras-MAPK, JAK-STAT, Type 1 IFN and NFκB. The signaling pathway map of SARS-CoV consists of 110 molecules and 101 reactions mediated by SARS-CoV proteins. The pathway reaction data are available in various community standard data exchange formats including Systems Biology Graphical Notation (SBGN). The pathway map is publicly available through the GitHub repository and data in various formats can be freely downloadable.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12079-021-00642-2.     

Anti-science kills: From Soviet embrace of pseudoscience to accelerated attacks on US biomedicine

The United States witnessed an unprecedented politicization of biomedical science starting in 2015 that has exploded into a complex, multimodal anti-science empire operating through mass media, political elections, legislation, and even health systems. Anti-science activities now pervade the daily lives of many Americans, and threaten to infect other parts of the world. We can attribute the deaths of tens of thousands of Americans from COVID-19, measles, and other vaccine-preventable diseases to anti-science. The acceleration of anti-science activities demands not only new responses and approaches but also international coordination. Vaccines and other biomedical advances will not be sufficient to halt COVID-19 or future potentially catastrophic illnesses, unless we simultaneously counter anti-science aggression.

This Essay argues that COVID-19 exposed how a rising tide of anti-science rhetoric and activities can dramatically exploit society''s vulnerabilities to an infectious disease, suggesting that anti-science extremism has become as big a threat as the virus itself.

“Without science, democracy has no future.”—Maxim Gorky, April 1917

The newest (October 2020) projections from the University of Washington Institute of Health Metrics and Evaluation (IHME) Coronavirus Disease 2019 (COVID-19) forecasting team reveal a grim reality. Their estimates indicate that more than 510,000 Americans could lose their lives by February 28, 2021 [1], representing more than a doubling of the current estimates of 220,000 deaths (although not all groups agree with these estimates). For most of 2020, the US has been the epicenter of the COVID-19 pandemic, leading the world in new cases and deaths. This dire situation is a consequence of our government’s failure to launch a coordinated national response and roadmap and refusing to aggressively promote nonpharmaceutical interventions (NPIs), especially face masks, social distancing mandates, school closures, testing, and contact tracing [2]. In its place, and as the cases and deaths mounted, the White House and its coronavirus task force, and famously the President himself, organized a campaign of disinformation [3].Central to White House anti-science promotion efforts were attempts by key officials to downplay the severity of COVID-19 and its long-haul consequences, inflate the curative properties of certain medicines such as hydroxychloroquine, falsely attribute COVID-19 deaths to comorbidities in order to artificially reduce actual disease mortality rates, and make scientifically unsubstantiated claims about herd immunity (or its links to the Great Barrington Declaration, which argued without evidence that restrictions cause more harm than the virus). There were also efforts to discredit the effectiveness of face masks to prevent COVID-19 or to refuse implementing mask mandates, invoking at times new political terms or slogans that gained popularity in recent years such as “health freedom” or “medical freedom” [4]. This is exemplified by a recent October 22 tweet from the Republican Governor Kristi Noem of South Dakota [5]:

If folks want to wear a mask, they are free to do so. Those who don’t want to wear a mask shouldn’t be shamed into it, and govt should not mandate it. We need to respect each other’s decisions. In SD, we know a little common courtesy can go a long way.

The open questioning of face masks or refusal to enforce mandates will likely continue to have tragic consequences for the American people. According to the IHME COVID-19 forecasting team, 95% public mask use would save almost 130,000 lives from September 22, 2020, through February 28, 2021 [1]. Thus, anti-science disinformation that advocates shunning masks could inflict a mass casualty event in the US. Its occurrence should not surprise us. Instead, our tragic loss of American lives would reflect the handiwork of an evolving anti-science movement that aggressively accelerated in the last 5 years beginning in California and Texas. In this Essay, I argue that to understand how a nation state might seek to attack and dissolve modern biomedicine, it is helpful to revisit a tragic period in 20th century Russia (see Box 1). The relentless attacks on science and scientists during Stalin’s Great Purge and the ascendancy of Lysokenkoism and other pseudoscientific theories provide a useful framework for addressing some stark reminders about the politicization of science occurring now in America, even if they play out at a far lesser scale.Box 1. Lessons from a dark chapter in historyOne of the darkest chapters in the history of the Soviet Union, the Great Purge, or the Great Terror (Большой террор), saw the widespread imprisonment, execution, and persecution of millions considered an enemy of Joseph Stalin’s government. It began following the assassination of Sergei Kirov in 1934, a Soviet leader and revolutionary, before halting in 1938, although significant elements of the purge remained throughout the 1940s. The intelligentsia was a Great Purge target, as were entire fields of science, including astrophysics, which was ultimately deemed as a “political platform” running counter to Marxism [6]. Another was the field of mendelian genetics, then led in the USSR by Nikolai Vavilov in his role as head of the Lenin All Union Academy of Agricultural Sciences, the scientific branch of the Commissariat of Agriculture. Vavilov was a botanist and a scientific pioneer in using genetic approaches to improve cereal crops for the USSR [6–8]. Ultimately, Vavilov came under attack by Trofim Lysenko, a peasant with no doctoral degree who popularized and laid claims to the concept of “vernalization” [6]. Lysenko and his colleagues proposed moistening and chilling winter wheat and allowing it to germinate in order to sense these conditions in time for the spring when it would supposedly flourish [6]. Through vernalization—which bore some resemblance to Lamarckian evolutionary theories by claiming that acquired traits could be inherited—Lysenko aspired to adapt wheat to the harsh Russian climate. As a sort of proof of concept, he had his father soak his winter wheat in water before burying it in a snowbank to keep it cold prior to spring planting [6].Initially, Vavilov took on a mentoring role for Lysenko, even touting his accomplishments at the Sixth International Congress of Genetics held at Cornell University in Ithaca, New York, in the summer of 1932 [8]. See, for example, Vavilov’s praise of Lysenko in a special news “flash,” as it was called by R. C. Cook, the editor of the Journal of Heredity during the 1940s [8]:

The remarkable discovery recently made by T. D. Lysenko of Odessa opens enormous new possibilities to plant breeders and plant geneticists of mastering individual variation.. . .The essence of these methods, which are specific for different plants and different variety groups, consists in the action upon the seeds of definite combinations of darkness (photo-periodism), temperature and humidity. This discovery enables us to utilize in our climate for breeding and genetic work tropical and sub-tropical varieties.... This creates the possibility of widening the scope of breeding. . . to an unprecedented extent, allowing the crossing of varieties requiring entirely different periods of vegetation.

Lysenko’s vernalization technology would theoretically make it possible, argues Simon Ings in his book, Stalin and the Scientists, “to grow alligator pears and Bananas in New York and lemons in New England” [6]. Its extraordinary claims aside, vernalization was seen as a form of Soviet homegrown science and a source of national pride. In contrast, Lysenko was able to convince Stalin that genetics was an evil science, much like relativity. Political expediency became the rationale for promoting pseudoscience even if it meant that millions of rural peasants would die of starvation in the USSR when Lysenko’s cold-resistant crops failed to materialize. Ultimately, Lysenko became the President of the Lenin Academy of Agricultural Science in 1939, whereas Vavilov was arrested in 1940 and rounded up with other intellectuals, including the founder of the Marx-Lenin Institute of World Literature. He was interrogated and sent to a Soviet prison in Saratov where he perished, possibly by starvation in January 1943, despite repeated appeals from international leaders including British Prime Minister, Winston Churchill (Fig 1) [6].Open in a separate windowFig 1Photo of the prisoner Nikolai Vavilov.Official photo from the file of the investigation. The People''s Commissariat for Internal Affairs (Народный комиссариат внутренних дел), Central Archive of the Federal Security Service of the Russian Federation (Moscow) (Центральный архив ФСБ РФ (Москва)) Institute of Plant Industry (Всероссийский институт растениеводства имени Н. И. Вавилова), created January 1, 1942. https://en.wikipedia.org/wiki/Nikolai_Vavilov#/media/File:Vavilov_in_prison.jpg.Vavilov received a posthumous pardon by Nikita Khrushchev during the 1950s, and in 2008, a book about his life, The Murder of Nikolai Vavilov: The Story of Stalin''s Persecution of One of the Great Scientists of the Twentieth Century was published in English [9]. It remains a great irony that Vavilov devoted his scientific career to the humanitarian cause of feeding the population of the Soviet Union only to die by starvation.Following the death of Stalin in 1953, the USSR began reopening to international science, ushering in a new era in vaccine development. Throughout the 1950s, both the US and Soviet Union suffered from severe polio epidemics prompting the 2 nations to embark on an unprecedented scientific collaboration [10]. Dr. Albert Sabin sent his polio strains to the USSR where they were manufactured at large scale to produce a trivalent vaccine. During the “Khrushchev Thaw,” it was tested in tens of millions of Soviet citizens and shown to be both safe and effective at preventing polio. A decade later, the US and USSR collaborated to improve a vaccine leading to the eradication of smallpox [10]. Nonetheless, state oppression of Soviet scientists continued, and Krushchev supported Lysenko’s work. Moreover, the physicist and father of the Soviet hydrogen bomb, Andrei Sakharov, won the Nobel Prize in 1975 advocating for human rights, but was subsequently arrested and exiled to Gorky [11]. The mathematician and chess champion, Natan Sharansky, was arrested on treason charges in 1977 and kept in solitary confinement before he was released through a prisoner exchange, later emigrating to Israel in 1980. The American physicist Robert Oppenheimer also endured persecution during the red scare in the 1950s, though on a lesser scale, having had his national security clearance revoked.     

A cohort autopsy study defines COVID-19 systemic pathogenesis

Severe COVID-19 disease caused by SARS-CoV-2 is frequently accompanied by dysfunction of the lungs and extrapulmonary organs. However, the organotropism of SARS-CoV-2 and the port of virus entry for systemic dissemination remain largely unknown. We profiled 26 COVID-19 autopsy cases from four cohorts in Wuhan, China, and determined the systemic distribution of SARS-CoV-2. SARS-CoV-2 was detected in the lungs and multiple extrapulmonary organs of critically ill COVID-19 patients up to 67 days after symptom onset. Based on organotropism and pathological features of the patients, COVID-19 was divided into viral intrapulmonary and systemic subtypes. In patients with systemic viral distribution, SARS-CoV-2 was detected in monocytes, macrophages, and vascular endothelia at blood–air barrier, blood–testis barrier, and filtration barrier. Critically ill patients with long disease duration showed decreased pulmonary cell proliferation, reduced viral RNA, and marked fibrosis in the lungs. Permanent SARS-CoV-2 presence and tissue injuries in the lungs and extrapulmonary organs suggest direct viral invasion as a mechanism of pathogenicity in critically ill patients. SARS-CoV-2 may hijack monocytes, macrophages, and vascular endothelia at physiological barriers as the ports of entry for systemic dissemination. Our study thus delineates systemic pathological features of SARS-CoV-2 infection, which sheds light on the development of novel COVID-19 treatment.Subject terms: Mechanisms of disease, Immunology     

SARS‐CoV‐2 structural coverage map reveals viral protein assembly,mimicry, and hijacking mechanisms

We modeled 3D structures of all SARS‐CoV‐2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that ˜6% of the proteome mimicked human proteins, while ˜7% was implicated in hijacking mechanisms that reverse post‐translational modifications, block host translation, and disable host defenses; a further ˜29% self‐assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is—and is not—known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria‐COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark.     

Potential role of nicotinamide analogues against SARS-COV-2 target proteins

Background and objectiveCoronavirus 2019 (COVID-19) is caused by ‘severe acute respiratory syndrome coronavirus 2′ (SARS-CoV-2), first reported in Wuhan, China in December 2019, which eventually became a global disaster. Various key mediators have been reported in the pathogenesis of COVID-19. However, no effective pharmacological intervention has been available to combat COVID-19 complications. The present study screens nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) as potential inhibitors of this present generation coronavirus infection using an in-silico approach.Materials and methodsThe SARS-CoV-2 proteins (nucleocapsid, proteases, post-fusion core, phosphatase, endoriboruclease) and ACE-2 protein were selected. The 2D structure of nicotinamide ribonucleoside and nicotinamide ribonucleotide was drawn using ChemDraw 14.0 and saved in .cdx format. The results were analyzed using two parameters: full fitness energy and binding free energy (ΔG).ResultsThe full fitness energy and estimated ΔG values from docking of NM, and NMN with selected SARS-CoV-2 target proteins, ADMET prediction and Target prediction indicate the interaction of NR and NMN in the treatment of COVID-19.ConclusionsBased on full fitness energy and estimated ΔG values from docking studies of NM and NAM with selected SARS-CoV-2 target proteins, ADME prediction, target prediction and toxicity prediction, we expect a possible therapeutic efficacy of NR in the treatment of COVID-19.Keyword: COVID-19, SARS-CoV-2, Molecular docking, Poly (ADP-ribose) polymerase enzyme, Nicotinamide