Oligonucleotide usage in coronavirus genomes mimics that in exon regions in host genomes.

BACKGROUND: Viruses use various host factors for their growth, and efficient growth requires efficient use of these factors. Our previous study revealed that the occurrence frequency of oligonucleotides in the influenza virus genome is distinctly different among derived hosts, and the frequency tends to adapt to the host cells in which they grow. We aimed to study the adaptation mechanisms of a zoonotic virus to host cells. METHODS: Herein, we compared the frequency of oligonucleotides in the genome of alpha- and betacoronavirus with those in the genomes of humans and bats, which are typical hosts of the viruses. RESULTS: By comparing the oligonucleotide frequency in coronaviruses and their host genomes, we found a statistically tested positive correlation between the frequency of coronaviruses and that of the exon regions of the host from which the virus is derived. To examine the characteristics of early-stage changes in the viral genome, which are assumed to accompany the host change from non-humans to humans, we compared the oligonucleotide frequency between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the beginning of the pandemic and the prevalent variants thereafter, and found changes towards the frequency of the host exon regions. CONCLUSIONS: In alpha- and betacoronaviruses, the genome oligonucleotide frequency is thought to change in response to the cellular environment in which the virus is replicating, and actually the frequency has approached the frequency in exon regions in the host.

Effect of tocilizumab treatment in mildly-obese patients with coronavirus disease 2019: a case series.

Background: The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is an increasingly widespread international medical problem. Several randomized trials and observational studies in patients with COVID-19 have been performed. However, the standard treatment strategy has not yet been established. The purpose of this study is to report effect of tocilizumab treatment combined with remdesivir, dexamethasone, and heparin on obese Japanese patients with COVID-19. Tocilizumab is a monoclonal antibody against the interleukin-6 (IL-6) receptor. Obesity, characterized by systemic enlarged adipocytes, promotes proinflammatory cytokine expression in adipose tissue. More specifically, obesity induces detrimental adipocytokine production including tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), and IL-6. In addition, its production in the adipose tissue is associated with body mass index (BMI) and adipocyte size. IL-6 can promote inflammation not only in the adipose tissues but also in endothelial cells and triggers systemic inflammation. Methods: A cross-sectional observational study was conducted. The study sample consisted of 96 patients between August 2020 and January 2021 at Showa University Fujigaoka Hospital. Results: Overall, 56.3% (54 of 96) were administered with remdesivir, 54.2% (52 of 96) with dexamethasone, 19.8% (19 of 96) with anticoagulant therapy with heparin. Of the patients, nine were administered tocilizumab with remdesivir, dexamethasone, and heparin. The current study indicated that single-dose treatment of tocilizumab in combination with remdesivir, dexamethasone, and heparin is beneficial for obese Japanese patients with COVID-19. Conclusions: We believe that the severity of obesity is related to the anti-IL-6 treatment sensitivity in patients with COVID-19.

AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies.

Among mutations that occur in SARS-CoV-2, efficient identification of mutations advantageous for viral replication and transmission is important to characterize and defeat this rampant virus. Mutations rapidly expanding frequency in a viral population are candidates for advantageous mutations, but neutral mutations hitchhiking with advantageous mutations are also likely to be included. To distinguish these, we focus on mutations that appear to occur independently in different lineages and expand in frequency in a convergent evolutionary manner. Batch-learning SOM (BLSOM) can separate SARS-CoV-2 genome sequences according by lineage from only providing the oligonucleotide composition. Focusing on remarkably expanding 20-mers, each of which is only represented by one copy in the viral genome, allows us to correlate the expanding 20-mers to mutations. Using visualization functions in BLSOM, we can efficiently identify mutations that have expanded remarkably both in the Omicron lineage, which is phylogenetically distinct from other lineages, and in other lineages. Most of these mutations involved changes in amino acids, but there were a few that did not, such as an intergenic mutation.

Effects of isometric handgrip exercise with or without blood flow restriction on interference control and feelings.

The purpose of this study was to investigate whether isometric handgrip exercise, with or without blood flow restriction, would alter interference control and feelings. 60 healthy young adults completed three experimental visits, consisting of four sets of 2 min isometric handgrip exercise, at 30% of maximal strength with or without blood flow restriction (50% of arterial occlusion pressure), or a non-exercise/time-matched control. Exercise-induced feeling inventory and Stroop Color Word Test were performed at pre- and ~10-min post-exercise, respectively. Bayes factors (BF10 ) quantified the evidence for or against the null. There were no changes or differences between conditions for interference control following exercise with or without blood flow restriction (Incongruent BF10 : 0.155; Stroop Interference BF10 : 0.082). There were also no differences in the error rate as well as no differences between conditions for changes in 'positivity' or 'revitalization'. Feelings of 'tranquility' were reduced relative to a control following exercise with (median δ [95% credible interval]: -0.74 (-1.05, -0.45), BF10 : 5515.7) and without (median δ: -0.72 [-1.02, -0.41], BF10 : 571.3) blood flow restriction. These changes were not different between exercise conditions. Feelings of 'physical exhaustion' were increased relative to a control following exercise without blood flow restriction (median δ: 0.35[0.09, 0.61], BF10 : 5.84). However, this increase was not different from the same exercise with blood flow restriction. These results suggest that 1) isometric handgrip exercise could be performed without impairing interference control, even when blood flow restriction is added, and that 2) changes in feelings occur independent of changes in interference control.

Unsupervised explainable AI for molecular evolutionary study of forty thousand SARS-CoV-2 genomes.

BACKGROUND: Unsupervised AI (artificial intelligence) can obtain novel knowledge from big data without particular models or prior knowledge and is highly desirable for unveiling hidden features in big data. SARS-CoV-2 poses a serious threat to public health and one important issue in characterizing this fast-evolving virus is to elucidate various aspects of their genome sequence changes. We previously established unsupervised AI, a BLSOM (batch-learning SOM), which can analyze five million genomic sequences simultaneously. The present study applied the BLSOM to the oligonucleotide compositions of forty thousand SARS-CoV-2 genomes. RESULTS: While only the oligonucleotide composition was given, the obtained clusters of genomes corresponded primarily to known main clades and internal divisions in the main clades. Since the BLSOM is explainable AI, it reveals which features of the oligonucleotide composition are responsible for clade clustering. Additionally, BLSOM also provided information concerning the special genomic region possibly undergoing RNA modifications. CONCLUSIONS: The BLSOM has powerful image display capabilities and enables efficient knowledge discovery about viral evolutionary processes, and it can complement phylogenetic methods based on sequence alignment.

Epidemiology and Genetic Analysis of SARS-CoV-2 in Myanmar during the Community Outbreaks in 2020.

We aimed to analyze the situation of the first two epidemic waves in Myanmar using the publicly available daily situation of COVID-19 and whole-genome sequencing data of SARS-CoV-2. From March 23 to December 31, 2020, there were 33,917 confirmed cases and 741 deaths in Myanmar (case fatality rate of 2.18%). The first wave in Myanmar from March to July was linked to overseas travel, and then a second wave started from Rakhine State, a western border state, leading to the second wave spreading countrywide in Myanmar from August to December 2020. The estimated effective reproductive number (Rt) nationwide reached 6-8 at the beginning of each wave and gradually decreased as the epidemic spread to the community. The whole-genome analysis of 10 Myanmar SARS-CoV-2 strains together with 31 previously registered strains showed that the first wave was caused by GISAID clade O or PANGOLIN lineage B.6 and the second wave was changed to clade GH or lineage B.1.36.16 with a close genetic relationship with other South Asian strains. Constant monitoring of epidemiological situations combined with SARS-CoV-2 genome analysis is important for adjusting public health measures to mitigate the community transmissions of COVID-19.

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.

Genomic Epidemiology Reveals Multiple Introductions of Severe Acute Respiratory Syndrome Coronavirus 2 in Niigata City, Japan, Between February and May 2020.

The coronavirus disease 2019 (COVID-19) has caused a serious disease burden and poses a tremendous public health challenge worldwide. Here, we report a comprehensive epidemiological and genomic analysis of SARS-CoV-2 from 63 patients in Niigata City, a medium-sized Japanese city, during the early phase of the pandemic, between February and May 2020. Among the 63 patients, 32 (51%) were female, with a mean (±standard deviation) age of 47.9 ± 22.3 years. Fever (65%, 41/63), malaise (51%, 32/63), and cough (35%, 22/63) were the most common clinical symptoms. The median C t value after the onset of symptoms lowered within 9 days at 20.9 cycles (interquartile range, 17-26 cycles), but after 10 days, the median C t value exceeded 30 cycles (p < 0.001). Of the 63 cases, 27 were distributed in the first epidemic wave and 33 in the second, and between the two waves, three cases from abroad were identified. The first wave was epidemiologically characterized by a single cluster related to indoor sports activity spread in closed settings, which included mixing indoors with families, relatives, and colleagues. The second wave showed more epidemiologically diversified events, with most index cases not related to each other. Almost all secondary cases were infected by droplets or aerosols from closed indoor settings, but at least two cases in the first wave were suspected to be contact infections. Results of the genomic analysis identified two possible clusters in Niigata City, the first of which was attributed to clade S (19B by Nexstrain clade) with a monophyletic group derived from the Wuhan prototype strain but that of the second wave was polyphyletic suggesting multiple introductions, and the clade was changed to GR (20B), which mainly spread in Europe in early 2020. These findings depict characteristics of SARS-CoV-2 transmission in the early stages in local community settings during February to May 2020 in Japan, and this integrated approach of epidemiological and genomic analysis may provide valuable information for public health policy decision-making for successful containment of chains of infection.

Clinical features and mechanism of liver injury in patients with mild or moderate coronavirus disease 2019.

BACKGROUND AND AIM: We aimed to identify clinical features that suggest that coronavirus disease 2019 (COVID-19) should be a differential diagnosis in patients presenting with a chief complaint of fever and abnormal liver function. METHODS: We retrospectively studied the presence or absence of abnormal liver function in 216 patients diagnosed with mild-moderate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection between February and September 2020. RESULTS: Abnormal liver function was observed in 51 patients with mild-moderate COVID-19. The median peak aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) levels were 57.5, 75.5, and 332.5 U/L, respectively. The median number of days from symptom onset to peak AST, ALT, and LDH were 8.5, 9, and 8.5, respectively. The median peak LDH/AST ratio was 9.0. Low lymphocyte-to-white blood cell ratio and elevated LDH were found to be independent contributing factors for intensive care unit (ICU) admission on a multivariate analysis. CONCLUSIONS: AST-predominant AST/ALT/LDH elevation peaking 8-9 days after symptom onset and not accompanied by elevated alkaline phosphatase or gamma-glutamyl transferase may be a useful clinical feature for differentiating COVID-19 from other diseases. Since the median LDH/AST ratio was 9.0, it seems that the abnormal liver function caused by SARS-CoV-2 is an indirect damage to liver cells due to elevated cytokine levels caused by liver-infiltrating lymphocytes. SARS-CoV-2 infection should be considered in patients presenting with a chief complaint of fever and liver injury; those with a high lymphocyte-to-white blood cell ratio or and a high LDH/AST ratio may be admitted to the ICU.

The Impact of Coronavirus (COVID-19) Related Public-Health Measures on Training Behaviours of Individuals Previously Participating in Resistance Training: A Cross-Sectional Survey Study.

INTRODUCTION: Understanding the impact of lockdown upon resistance training (RT), and how people adapted their RT behaviours, has implications for strategies to maintain engagement in similar positive health behaviours. Further, doing so will provide a baseline for investigation of the long-term effects of these public health measures upon behaviours and perceptions, and facilitate future follow-up study. OBJECTIVES: To determine how the onset of coronavirus (COVID-19), and associated 'lockdown', affected RT behaviours, in addition to motivation, perceived effectiveness, enjoyment, and intent to continue, in those who regularly performed RT prior to the pandemic. METHODS: We conducted an observational, cross-sectional study using online surveys in multiple languages (English, Danish, French, German, Italian, Portuguese, Slovakian, Swedish, and Japanese) distributed across social media platforms and through authors' professional and personal networks. Adults (n = 5389; median age = 31 years [interquartile range (IQR) = 25, 38]), previously engaged in RT prior to lockdown (median prior RT experience = 7 years [IQR = 4, 12]) participated. Outcomes were self-reported RT behaviours including: continuation of RT during lockdown, location of RT, purchase of specific equipment for RT, method of training, full-body or split routine, types of training, repetition ranges, exercise number, set volumes (per exercise and muscle group), weekly frequency of training, perception of effort, whether training was planned/recorded, time of day, and training goals. Secondary outcomes included motivation, perceived effectiveness, enjoyment, and intent to continue RT. RESULTS: A majority of individuals (82.8%) maintained participation in RT during-lockdown. Marginal probabilities from generalised linear models and generalised estimating equations for RT behaviours were largely similar from pre- to during-lockdown. There was reduced probability of training in privately owned gyms (~ 59% to ~ 7%) and increased probability of training at home (~ 18% to ~ 89%); greater probability of training using a full-body routine (~ 38% to ~ 51%); reduced probability of resistance machines (~ 66% to ~ 13%) and free weight use (~ 96% to ~ 81%), and increased probability of bodyweight training (~ 62% to ~ 82%); reduced probability of moderate repetition ranges (~ 62-82% to ~ 55-66%) and greater probability of higher repetition ranges (~ 27% to ~ 49%); and moderate reduction in the perception of effort experienced during-training (r = 0.31). Further, individuals were slightly less likely to plan or record training during lockdown and many changed their training goals. Additionally, perceived effectiveness, enjoyment, and likelihood of continuing current training were all lower during-lockdown. CONCLUSIONS: Those engaged in RT prior to lockdown these behaviours with only slight adaptations in both location and types of training performed. However, people employed less effort, had lower motivation, and perceived training as less effective and enjoyable, reporting their likelihood of continuing current training was similar or lower than pre-lockdown. These results have implications for strategies to maintain engagement in positive health behaviours such as RT during-restrictive pandemic-related public health measures. PRE-REGISTRATION: https://osf.io/qcmpf . PREPRINT: The preprint version of this work is available on SportRχiv: https://osf.io/preprints/sportrxiv/b8s7e/ .

Human cell-dependent, directional, time-dependent changes in the mono- and oligonucleotide compositions of SARS-CoV-2 genomes.

BACKGROUND: When a virus that has grown in a nonhuman host starts an epidemic in the human population, human cells may not provide growth conditions ideal for the virus. Therefore, the invasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is usually prevalent in the bat population, into the human population is thought to have necessitated changes in the viral genome for efficient growth in the new environment. In the present study, to understand host-dependent changes in coronavirus genomes, we focused on the mono- and oligonucleotide compositions of SARS-CoV-2 genomes and investigated how these compositions changed time-dependently in the human cellular environment. We also compared the oligonucleotide compositions of SARS-CoV-2 and other coronaviruses prevalent in humans or bats to investigate the causes of changes in the host environment. RESULTS: Time-series analyses of changes in the nucleotide compositions of SARS-CoV-2 genomes revealed a group of mono- and oligonucleotides whose compositions changed in a common direction for all clades, even though viruses belonging to different clades should evolve independently. Interestingly, the compositions of these oligonucleotides changed towards those of coronaviruses that have been prevalent in humans for a long period and away from those of bat coronaviruses. CONCLUSIONS: Clade-independent, time-dependent changes are thought to have biological significance and should relate to viral adaptation to a new host environment, providing important clues for understanding viral host adaptation mechanisms.