Development of a method for walking step observation based on large-scale GPS data.

BACKGROUND: Widespread use of smartphones has enabled the continuous monitoring of people's movements and physical activity. Linking global positioning systems (GPS) data obtained via smartphone applications to physical activity data may allow for large-scale and retrospective evaluation of where and how much physical activity has increased or decreased due to environmental, social, or individual changes caused by policy interventions, disasters, and infectious disease outbreaks. However, little attention has been paid to the use of large-scale commercial GPS data for physical activity research due to limitations in data specifications, including limited personal attribute and physical activity information. Using GPS logs with step counts measured by a smartphone application, we developed a simple method for daily walking step estimation based on large-scale GPS data. METHODS: The samples of this study were users whose GPS logs were obtained in Sendai City, Miyagi Prefecture, Japan, during October 2019 (37,460 users, 36,059,000 logs), and some logs included information on daily step counts (731 users, 450,307 logs). The relationship between land use exposure and daily step counts in the activity space was modeled using the small-scale GPS logs with daily step counts. Furthermore, we visualized the geographic distribution of estimated step counts using a large set of GPS logs with no step count information. RESULTS: The estimated model showed positive relationships between visiting high-rise buildings, parks and public spaces, and railway areas and step counts, and negative relationships between low-rise buildings and factory areas and daily step counts. The estimated daily step counts tended to be higher in urban areas than in suburban areas. Decreased step counts were mitigated in areas close to train stations. In addition, a clear temporal drop in step counts was observed in the suburbs during heavy rainfall. CONCLUSIONS: The relationship between land use exposure and step counts observed in this study was consistent with previous findings, suggesting that the assessment of walking steps based on large-scale GPS logs is feasible. The methodology of this study can contribute to future policy interventions and public health measures by enabling the retrospective and large-scale observation of physical activity by walking.

Distinct Expansion of Group II Introns During Evolution of Prokaryotes and Possible Factors Involved in Its Regulation.

Group II introns (G2Is) are ribozymes that have retroelement characteristics in prokaryotes. Although G2Is are suggested to have been an important evolutionary factor in the prokaryote-to-eukaryote transition, comprehensive analyses of these introns among the tens of thousands of prokaryotic genomes currently available are still limited. Here, we developed a bioinformatic pipeline that systematically collects G2Is and applied it to prokaryotic genomes. We found that in bacteria, 25% (447 of 1,790) of the total representative genomes had an average of 5.3 G2Is, and in archaea, 9% (28 of 296) of the total representative genomes had an average of 3.0 G2Is. The greatest number of G2Is per genome was 101 in Arthrospira platensis (phylum Cyanobacteriota). A comprehensive sequence analysis of the intron-encoded protein (IEP) in each G2I sequence was conducted and resulted in the addition of three new IEP classes (U1-U3) to the previous classification. This analysis suggested that about 30% of all IEPs are non-canonical IEPs. The number of G2Is per genome was defined almost at the phylum level, and at least in the following two phyla, Firmicutes, and Cyanobacteriota, the type of IEP was largely associated as a factor in the G2I increase, i.e., there was an explosive increase in G2Is with bacterial C-type IEPs, mainly in the phylum Firmicutes, and in G2Is with CL-type IEPs, mainly in the phylum Cyanobacteriota. We also systematically analyzed the relationship between genomic signatures and the mechanism of these increases in G2Is. This is the first study to systematically characterize G2Is in the prokaryotic phylogenies.

Relationship between Internet use and out-of-home activities during the first wave of the COVID-19 outbreak in Japan.

Following the first wave of the COVID-19 outbreak, the Japanese government announced the declaration of a state of emergency in April 2020, which aimed to decrease contact between people and requested that residents refrain from outings. Even in the absence of penalties, outings decreased under the declaration. We are interested in how outings declined and studied the substitution relationship between Internet use and outings. A web-based survey was conducted to collect data on Internet use and outings in a retrospective manner. The period covered by our data is from mid-February to mid-May 2020. Multilevel analysis and binomial logistic regression analysis were performed to examine the relationship between Internet use and outings. The results clearly show that Internet use replaced outings. In particular, Internet use for socializing, exercise, and leisure/entertainment had a strong substitution relationship with outings. Internet use for socializing and leisure/entertainment was also associated with refraining from visiting restaurants. In contrast, there was a weak substitution relationship between Internet use for daily shopping and outings. Although telework tends to be an accepted focus of Internet use under the COVID-19 outbreak, it should not be overlooked that other uses of the Internet, such as for leisure/entertainment, also supported the decline in outings.

Coastal exposure and residents' mental health in the affected areas by the 2011 Great East Japan Earthquake and Tsunami.

No previous study has ever explored the association between coastal exposure and the mental health of residents in a post-disaster context. Therefore, we aimed to confirm whether there was an association between sea visibility and coastal proximity and the mental health of coastal residents a devastating tsunami. We targeted 15 coastal municipalities located in the Miyagi Prefecture, and obtained data from a community-based cohort study. The baseline survey was initiated 2 years after the 2011 Great East Japan Earthquake and Tsunami and the secondary survey was initiated 6 years after the disaster. We applied multilevel mixed-effects models to the longitudinal data. Our outcome measure was the Kessler Psychological Distress Scale (K6) score. We assessed the data collected from 2,327 respondents on both surveys as of April 2018 for this ongoing cohort study. We found that neither sea visibility nor coastal proximity was significantly associated with the recovery of mental health after the disaster. However, we found a distinctive trend of mental health recovery in people who lived alone with a sea view, indicating that visibility of the sea had a negative effect on their mental health immediately after the GEJET, but that the negative effect was subsequently eliminated.

Mobility Change and COVID-19 in Japan: Mobile Data Analysis of Locations of Infection.

BACKGROUND: As the COVID-19 pandemic spread, the Japanese government declared a state of emergency on April 7, 2020 for seven prefectures, and on April 16, 2020 for all prefectures. The Japanese Prime Minister and governors requested people to adopt self-restraint behaviors, including working from home and refraining from visiting nightlife spots. However, the effectiveness of the mobility change due to such requests in reducing the spread of COVID-19 has been little investigated. The present study examined the association of the mobility change in working, nightlife, and residential places and the COVID-19 outbreaks in Tokyo, Osaka, and Nagoya metropolitan areas in Japan. METHODS: First, we calculated the daily mobility change in working, nightlife, and residential places compared to the mobility before the outbreak using mobile device data. Second, we estimated the sensitivity of mobility changes to the reproduction number by generalized least squares. RESULTS: Mobility change had already started in March, 2020. However, mobility reduction in nightlife places was particularly significant due to the state of emergency declaration. Although the mobility in each place type was associated with the COVID-19 outbreak, the mobility changes in nightlife places were more significantly associated with the outbreak than those in the other place types. There were regional differences in intensity of sensitivity among each metropolitan area. CONCLUSIONS: Our findings indicated the effectiveness of the mobility changes, particularly in nightlife places, in reducing the outbreak of COVID-19.

Familial Clusters of Coronavirus Disease in 10 Prefectures, Japan, February-May 2020.

The overall coronavirus disease secondary attack rate (SAR) in family members was 19.0% in 10 prefectures of Japan during February 22-May 31, 2020. The SAR was lower for primary cases diagnosed early, within 2 days after symptom onset. The SAR of asymptomatic primary cases was 11.8%.

Relationships among changes in walking and sedentary behaviors, individual attributes, changes in work situation, and anxiety during the COVID-19 pandemic in Japan.

Studies from many countries, including Japan, have reported decreased physical activity during the coronavirus disease 2019 (COVID-19) pandemic. However, the individual attributes as related to changes in physical activity during the pandemic in Japan have been scarcely investigated. The present study explored the relationships among individual attributes including demographic, socioeconomic, and geographic characteristics, work situation changes, perception of anxiety, and changes in walking and sedentary behaviors, during the pandemic in Japan. To obtain data indicating individual circumstances during the first wave of the pandemic in Japan, we conducted a nationwide online survey from May 19 to May 23, 2020 (n = 1,200). To observe changes in walking behavior objectively and retrospectively, we collected data on the number of daily steps as measured by the iPhone's Health application. Path analysis was employed to examine relationships between individual attributes and changes in walking and sedentary behaviors. Decreased physical activity, especially, decreased walking behavior among younger individuals and those living in highest-density neighborhoods were identified. There was increased sedentary behavior among females. Moreover, individuals with higher socioeconomic status (SES) tended to become inactive due to work-from-home/standby-at-home and individuals with lower SES tended to become inactive due to decreased amount of work. Decreased walking behavior and increased sedentary behavior were associated with a perception of strong anxiety related to the pandemic. Our findings would be helpful in considering measures to counteract health risks during the pandemic by taking into account individual backgrounds.

Types of coastlines and the evacuees' mental health: A repeated cross-sectional study in Northeast Japan.

Although the health risks and benefits of coastal areas have long been researched, these effects of the different types of coastlines have rarely been explored on the evacuees living near the coast, in a post-disaster context. Thus, this study aimed to explore, with the passing of years after a disaster, what kind of coastline is a useful public health resource as a post-disaster reconstruction approach in coastal environments that have suffered significantly from the tsunami disaster in northeast Japan in 2011. This study compared the evacuees' mental health based on proximity to the coast and the types of coastlines (artificial, semi-natural, and natural). Data were drawn from the Miyagi Prefectural Government surveys, which targeted almost all evacuees of the 2011 Great East Japan Earthquakes and Tsunami (n = 96,203). We applied a pooled Poisson regression model to a repeated cross-sectional dataset of evacuees' mental health between 2012 and 2016. Moderate psychological distress, measured via the Kessler Psychological Distress Scale (K6) score, was the dependent variable, while proximity to the coast and type of coastline were the independent variables. The estimated main effects of type of coastline indicated that overall associations between K6 ≥5 and all types of coastlines within a 1.6 km buffer of participants' residential space were not statistically significant (p > 0.05). However, among types of coastlines, the interaction terms of semi-natural coastline × year (2015 and 2016) were significantly associated with lower incidence rate ratios (IRR), which decreased in 2015 and 2016 (IRR: 0.88, 95%CI: 0.79-0.98; IRR: 0.78, 95%CI: 0.68-0.90, respectively). Further, we computed the marginal effects of coastline types for each year to observe differences in the impact on moderate psychological distress depending on different accessible coastline types within a distance of 1.6 km from the participants' living space. We found that, after the revision of the coastal act in 2014, the moderate mental stress of participants who lived around semi-natural coastlines significantly tended to be low (dy/dx: -0.04, 95%CI: -0.08-0.01 in 2015; dy/dx: -0.07, 95%CI: -0.11-0.04 in 2016). This finding can encourage policymakers to manage coastal areas with green infrastructure in the post-disaster reconstruction sustainably.

Objective scoring of streetscape walkability related to leisure walking: Statistical modeling approach with semantic segmentation of Google Street View images.

Although the pedestrian-friendly qualities of streetscapes promote walking, quantitative understanding of streetscape functionality remains insufficient. This study proposed a novel automated method to assess streetscape walkability (SW) using semantic segmentation and statistical modeling on Google Street View images. Using compositions of segmented streetscape elements, such as buildings and street trees, a regression-style model was built to predict SW, scored using a human-based auditing method. Older female active leisure walkers living in Bunkyo Ward, Tokyo, are associated with SW scores estimated by the model (OR = 3.783; 95% CI = 1.459 to 10.409), but male walkers are not.

Clusters of Coronavirus Disease in Communities, Japan, January-April 2020.

We analyzed 3,184 cases of coronavirus disease in Japan and identified 61 case-clusters in healthcare and other care facilities, restaurants and bars, workplaces, and music events. We also identified 22 probable primary case-patients for the clusters; most were 20-39 years of age and presymptomatic or asymptomatic at virus transmission.

Large-Scale Molecular Evolutionary Analysis Uncovers a Variety of Polynucleotide Kinase Clp1 Family Proteins in the Three Domains of Life.

Clp1, a polyribonucleotide 5'-hydroxyl kinase in eukaryotes, is involved in pretRNA splicing and mRNA 3'-end formation. Enzymes similar in amino acid sequence to Clp1, Nol9, and Grc3, are present in some eukaryotes and are involved in prerRNA processing. However, our knowledge of how these Clp1 family proteins evolved and diversified is limited. We conducted a large-scale molecular evolutionary analysis of the Clp1 family proteins in all living organisms for which protein sequences are available in public databases. The phylogenetic distribution and frequencies of the Clp1 family proteins were investigated in complete genomes of Bacteria, Archaea and Eukarya. In total, 3,557 Clp1 family proteins were detected in the three domains of life, Bacteria, Archaea, and Eukarya. Many were from Archaea and Eukarya, but a few were found in restricted, phylogenetically diverse bacterial species. The domain structures of the Clp1 family proteins also differed among the three domains of life. Although the proteins were, on average, 555 amino acids long (range, 196-2,728), 122 large proteins with >1,000 amino acids were detected in eukaryotes. These novel proteins contain the conserved Clp1 polynucleotide kinase domain and various other functional domains. Of these proteins, >80% were from Fungi or Protostomia. The polyribonucleotide kinase activity of Thermus scotoductus Clp1 (Ts-Clp1) was characterized experimentally. Ts-Clp1 preferentially phosphorylates single-stranded RNA oligonucleotides (Km value for ATP, 2.5 µM), or single-stranded DNA at higher enzyme concentrations. We propose a comprehensive assessment of the diversification of the Clp1 family proteins and the molecular evolution of their functional domains.

Complete Genome Sequence of Halomonas olivaria, a Moderately Halophilic Bacterium Isolated from Olive Processing Effluents, Obtained by Nanopore Sequencing.

Here, we report the complete genome sequence of Halomonas olivaria strain TYRC17, a moderately halophilic, Gram-negative bacterium that was isolated from olive processing effluents. The 5-Mbp genome consists of 7,375 protein-coding sequences, including a variety of genes involved in tyrosol metabolism, nitrate respiration, and the production of polysaccharides.

Evolutionary Analysis of HIV-1 Pol Proteins Reveals Representative Residues for Viral Subtype Differentiation.

RNA viruses have been used as model systems to understand the patterns and processes of molecular evolution because they have high mutation rates and are genetically diverse. Human immunodeficiency virus 1 (HIV-1), the etiological agent of acquired immune deficiency syndrome, is highly genetically diverse, and is classified into several groups and subtypes. However, it has been difficult to use its diverse sequences to establish the overall phylogenetic relationships of different strains or the trends in sequence conservation with the construction of phylogenetic trees. Our aims were to systematically characterize HIV-1 subtype evolution and to identify the regions responsible for HIV-1 subtype differentiation at the amino acid level in the Pol protein, which is often used to classify the HIV-1 subtypes. In this study, we systematically characterized the mutation sites in 2,052 Pol proteins from HIV-1 group M (144 subtype A; 1,528 subtype B; 380 subtype C), using sequence similarity networks. We also used spectral clustering to group the sequences based on the network graph structures. A stepwise analysis of the cluster hierarchies allowed us to estimate a possible evolutionary pathway for the Pol proteins. The subtype A sequences also clustered according to when and where the viruses were isolated, whereas both the subtype B and C sequences remained as single clusters. Because the Pol protein has several functional domains, we identified the regions that are discriminative by comparing the structures of the domain-based networks. Our results suggest that sequence changes in the RNase H domain and the reverse transcriptase (RT) connection domain are responsible for the subtype classification. By analyzing the different amino acid compositions at each site in both domain sequences, we found that a few specific amino acid residues (i.e., M357 in the RT connection domain and Q480, Y483, and L491 in the RNase H domain) represent the differences among the subtypes. These residues were located on the surface of the RT structure and in the vicinity of the amino acid sites responsible for RT enzymatic activity or function.