Depression-like phenotypes in mice following common bile duct ligation: Insights into the gut-liver-brain axis via the vagus nerve.

Depression frequently occurs in patients with liver cirrhosis, yet the reasons for this correlation are not fully understood. Dysbiosis of gut microbiota has been implicated in depression through the gut-brain axis via the vagus nerve. This study explored the potential role of the gut-liver-brain axis via the vagus nerve in depression-like phenotypes in mice with liver cirrhosis. These mice underwent common bile duct ligation (CBDL), a method used to stimulate liver cirrhosis. To assess depression-like behaviors, behavioral tests were conducted 10 days following either sham or CBDL surgeries. The mice with CBDL displayed symptoms such as splenomegaly, elevated plasma levels of interleukin-6 and tumor necrosis factor-α, depression-like behaviors, decreased levels of synaptic proteins in the prefrontal cortex (PFC), disrupted gut microbiota balance, and changes in blood metabolites (or lipids). Additionally, there were positive or negative correlations between the relative abundance of microbiome and behavioral data or blood metabolites (or lipids). Significantly, these changes were reversed in CBDL mice by performing a subdiaphragmatic vagotomy. Intriguingly, depression-like phenotypes in mice with CBDL were improved after a single injection of arketamine, a new antidepressant. These results suggest that CBDL-induced depression-like phenotypes in mice are mediated through the gut-liver-brain axis via the subdiaphragmatic vagus nerve, and that arketamine might offer a new treatment approach for depression in liver cirrhosis patients.

Changes in Place of Death among Patients with Dementia during the COVID-19 Pandemic in Japan: A Time Series Analysis.

BACKGROUND: A key measure of the effectiveness of end-of-life care is the place of death. The COVID-19 pandemic affected end-of-life care and the circumstances of patients with dementia. METHODS: This observational, retrospective cohort study used Japanese national data to examine the numbers and locations of reported deaths among patients with dementia older than 65 years during the COVID-19 pandemic. Locations were grouped as medical institutions, nursing facilities, homes, or all the above. The quasi-Poisson regression model known as the Farrington algorithm was employed. RESULTS: Between December 30, 2019, and January 29, 2023, 279,703 patients who died of causes related to dementia were reported in Japan. A decline was seen in early 2020, followed by increased numbers of deaths in homes, medical facilities, and nursing homes beginning in October 2020, December 2020, and March 2021, respectively. In 2021, the percentage of excess deaths at home peaked at 35.2%, while in 2022, those in medical facilities and nursing homes peaked at 18.8% and 16.6%, respectively. In 2022, the percentage of excess deaths in nursing homes exceeded that of other locations. CONCLUSIONS: The results suggest a change in the preferred place of death, along with pandemic-related visitation restrictions among healthcare facilities. Excess deaths also suggest strained medical resources and limited access to care. Methodological limitations include data from a limited period (2017 onwards) and post-2020 data used to estimate data after 2021, albeit with weighting. Considering these findings, physicians should reconfirm preferred places of death among older patients with dementia.

Association between maternal blood or cord blood metal concentrations and catch-up growth in children born small for gestational age: an analysis by the Japan environment and children's study.

BACKGROUND: Catch-up growth issues among children born small for gestational age (SGA) present a substantial public health challenge. Prenatal exposure to heavy metals can cause adverse effects on birth weight. However, comprehensive studies on the accurate assessment of individual blood concentrations of heavy metals and their effect on the failure to achieve catch-up growth remain unavailable. This study aimed to evaluate the effects of uterine exposure to toxic metals cadmium, lead, and mercury and essential trace metals manganese and selenium at low concentrations on the postnatal growth of children born SGA. METHODS: Data on newborn birth size and other factors were obtained from the medical record transcripts and self-administered questionnaires of participants in the Japan Environment and Children's Study. The blood concentrations of lead, cadmium, mercury, selenium, and manganese in pregnant women in their second or third trimester were determined by inductively coupled plasma mass spectrometry. These heavy metal concentrations were also assessed in pregnant women's cord blood. Furthermore, the relationship between each heavy metal and height measure/catch-up growth in SGA children aged 4 years was analyzed using linear and logistic regression methods. These models were adjusted for confounders. RESULTS: We studied 4683 mother-child pairings from 103,060 pregnancies included in the Japan Environment and Children's Study. Of these, 278 pairs were also analyzed using cord blood. At 3 and 4 years old, 10.7% and 9.0% of children who were born below the 10th percentile of body weight had height standard deviation scores (SDSs) below 2, respectively. Cord blood cadmium concentrations were associated with the inability to catch up in growth by 3 or 4 years old and the height SDS at 3 years old. In maternal blood, only manganese was positively associated with the height SDS of SGA children aged 2 years; however, it was not significantly associated with catch-up growth in these children. CONCLUSION: Cadmium exposure is associated with failed catch-up development in SGA children. These new findings could help identify children highly at risk of failing to catch up in growth, and could motivate the elimination of heavy metal (especially cadmium) pollution to improve SGA children's growth.

Role of the gut-brain axis via the subdiaphragmatic vagus nerve in stress resilience of 3,4-methylenedioxymethamphetamine in mice exposed to chronic restrain stress.

3,4-Methylenedioxymethamphetamine (MDMA) is the most widely used illicit substance worldwide. Nevertheless, recent observational studies demonstrated that lifetime MDMA use among U.S. adults was associated with a lower risk of depression and suicide thoughts. We recently reported that the gut-brain axis may contribute to MDMA-induced stress resilience in mice. To further explore this, we investigated the effects of subdiaphragmatic vagotomy (SDV) in modulating the stress resilience effects of MDMA in mice subjected to chronic restrain stress (CRS). Pretreatment with MDMA (10 mg/kg/day for 14 days) blocked anhedonia-like behavior and reduced expression of synaptic proteins and brain-derived neurotrophic factor in the prefrontal cortex (PFC) of CRS-exposed mice. Interestingly, SDV blocked the beneficial effects of MDMA on these alterations in CRS-exposed mice. Analysis of gut microbiome revealed alterations in four measures of α-diversity between the sham + MDMA + CRS group and the SDV + MDMA + CRS group. Moreover, specific microbes differed between the vehicle + CRS group and the MDMA + CRS group, and further differences in microbial composition were observed among all four groups. Untargeted metabolomics analysis showed that SDV prevented the increase in plasma levels of three compounds [lactic acid, 1-(2-hydroxyethyl)-2,2,6-tetramethyl-4-piperidinol, 8-acetyl-7-hydroxyvumaline] observed in the sham + MDMA + CRS group. Interestingly, positive correlations were found between the plasma levels of two of these compounds and the abundance of several microbes across all groups. In conclusion, our data suggest that the gut-brain axis via the subdiaphragmatic vagus nerve might contribute to the stress resilience of MDMA.

Key role of the gut-microbiota-brain axis via the subdiaphragmatic vagus nerve in demyelination of the cuprizone-treated mouse brain.

Multiple sclerosis (MS) is the most common demyelinating disease that attacks the central nervous system. Dietary intake of cuprizone (CPZ) produces demyelination resembling that of patients with MS. Given the role of the vagus nerve in gut-microbiota-brain axis in development of MS, we performed this study to investigate whether subdiaphragmatic vagotomy (SDV) affects demyelination in CPZ-treated mice. SDV significantly ameliorated demyelination and microglial activation in the brain compared with sham-operated CPZ-treated mice. Furthermore, 16S ribosomal RNA analysis revealed that SDV significantly improved the abnormal gut microbiota composition of CPZ-treated mice. An untargeted metabolomic analysis demonstrated that SDV significantly improved abnormal blood levels of metabolites in CPZ-treated mice compared with sham-operated CPZ-treated mice. Notably, there were correlations between demyelination or microglial activation in the brain and the relative abundance of several microbiome populations, suggesting a link between gut microbiota and the brain. There were also correlations between demyelination or microglial activation in the brain and blood levels of metabolites. Together, these data suggest that CPZ produces demyelination in the brain through the gut-microbiota-brain axis via the subdiaphragmatic vagus nerve.

Recent changes in the reporting of STIs in Japan during the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has had variable effects on the rates of STIs reported across the globe. This study sought to assess how the number of STI reports changed during the pandemic in Japan. METHODS: We used national infectious disease surveillance data from the National Institute of Infectious Diseases (Tokyo, Japan) for the period between January 2013 and December 2021. We compared reported rates of chlamydia, gonorrhoea, condyloma acuminata and genital herpes, as well as total notifications for HIV/AIDS and syphilis during the pandemic versus previous years in Japan. We used a quasi-Poisson regression to determine whether any given week or month between January 2018 and December 2021 had a significant excess or deficit of STIs. Notification values above or below the 95% upper and lower prediction thresholds were considered as statistically significant. The start of the pandemic was defined as January 2020. RESULTS: Chlamydia generally remained within predicted range during the pandemic period. Reporting of gonorrhoea was significantly higher than expected throughout early-to-mid 2021 but otherwise generally remained within predicted range prior to 2021. Condyloma, herpes and HIV/AIDS reporting were transiently significantly lower than expected throughout the pandemic period, but no significant periods of higher-than-expected reporting were detected. Syphilis showed widespread evidence of significantly lower-than-predicted reporting throughout 2020 but eventually reversed, showing significantly higher-than-predicted reporting in mid-to-late 2021. CONCLUSIONS: The COVID-19 pandemic was associated with variable changes in the reporting of STIs in Japan. Higher-than-predicted reporting was more likely to be observed in the later phases of the pandemic. These changes may have been attributable to pandemic-related changes in sexual behaviour and decreased STI clinic attendance and testing, but further research on the long-term impact of the pandemic on STIs is necessary.

Estimation of the time of exposure based on interval and censored data using the ε-accelerated EM algorithm.

Accurately estimating the timing of pathogen exposure plays a crucial role in outbreak control for emerging infectious diseases, including the source identification, contact tracing, and vaccine research and development. However, since surveillance activities often collect data retrospectively after symptoms have appeared, obtaining accurate data on the timing of disease onset is difficult in practice and can involve "coarse" observations, such as interval or censored data. To address this challenge, we propose a novel likelihood function, tailored to coarsely observed data in rapid outbreak surveillance, along with an optimization method based on an ε $$ \varepsilon $$ -accelerated EM algorithm for faster convergence to find maximum likelihood estimates (MLEs). The covariance matrix of MLEs is also discussed using a nonparametric bootstrap approach. In terms of bias and mean-squared error, the performance of our proposed method is evaluated through extensive numerical experiments, as well as its application to a series of epidemiological surveillance focused on cases of mass food poisoning. The experiments show that our method exhibits less bias than conventional methods, providing greater efficiency across all scenarios.

Impact of the COVID-19 pandemic on cancer death locations in Japan: an analysis up to February 2023 on excess mortality.

IntroductionThe Covid-19 pandemic has significantly impacted end-of-life decisions for cancer patients in Japan, with disparities existing between preferred and actual care settings. Our study investigates the potential shifts in cancer death locations during the pandemic and if there were excess cancer deaths.MethodsUtilizing national mortality data from the Ministry of Health, Labour, and Welfare from January 2012 to February 2023, we identified cancer deaths using ICD-10 codes. We assessed death locations, including medical institutions, nursing facilities, and homes. The Farrington algorithm was employed to estimate expected death counts, and the differences between observed and expected counts were denoted as excess deaths.ResultsFrom January 2018 to February 2023, there was consistently increase in the weekly observed cancer deaths. The presence of a definitive excess during the pandemic period remains uncertain. The percentage of deaths in medical institutions declined from 83.3% to 70.1% , while home deaths increased from 12.1% to 22.9%. Between April 2020 and February 2023, deaths in medical institutions frequently fell below the 95% prediction lower limit. Home deaths consistently exceeded the 95% prediction upper limit, with significant excess deaths reported annually.ConclusionOur study found a shift in cancer death locations from medical institutions to homes in Japan during the COVID-19 pandemic. Our study did not confirm an overall increase in cancer deaths during this period. As with global trends, the profound shift from hospitals to homes in Japan calls for a comprehensive exploration to grasp the pandemic's multifaceted impact on end-of-life cancer care decisions.

Effect of the COVID-19 pandemic and state of emergency declarations on the relative incidence of legionellosis and invasive pneumococcal disease in Japan.

INTRODUCTION: During the COVID-19 pandemic, the incidence of many droplet-transmitted infections decreased due to increased mask-wearing and social distancing. Contrastingly, there has been concern that COVID-19 countermeasures, such as lockdowns, may increase legionellosis incidence via water stagnation. During the pandemic in Japan, four state of emergency declarations were imposed between 2020 and 2021, which makes it particularly suitable to test this hypothesis. METHODS: We use country-level surveillance data from the National Institute of Infectious Diseases to track the relative incidence of legionellosis compared to invasive pneumococcal disease (IPD) during the COVID-19 pandemic in Japan, with a focus on the periods just after state of emergency declarations were lifted. RESULTS: The absolute number of legionellosis and IPD cases decreased in 2020 and 2021 compared to previous years. The average relative incidence of legionellosis as well as the variance of the relative incidence significantly increased during the pandemic compared to previous years. There were no increases in the relative incidence of legionellosis during the periods immediately following emergency declaration liftings, but the relative incidence did increase considerably during the first two states of emergency. CONCLUSIONS: COVID-19 countermeasures appear more effective at decreasing the incidence of human-to-human transmitted infections, such as IPD, compared to environmentally-transmitted infections, such as legionellosis. Though no evidence was found to suggest that legionellosis cases increased after state of emergency declarations, public health efforts should continue to emphasize the importance of routine sanitation and water system maintenance to prevent water stagnation and Legionella spp. contamination.

Distributed lag interrupted time series model for unclear intervention timing: effect of a statement of emergency during COVID-19 pandemic.

BACKGROUND: Interrupted time series (ITS) analysis has become a popular design to evaluate the effects of health interventions. However, the most common formulation for ITS, the linear segmented regression, is not always adequate, especially when the timing of the intervention is unclear. In this study, we propose a new model to overcome this limitation. METHODS: We propose a new ITS model, ARIMAITS-DL, that combines (1) the Autoregressive Integrated Moving Average (ARIMA) model and (2) distributed lag functional terms. The ARIMA technique allows us to model autocorrelation, which is frequently observed in time series data, and the decaying cumulative effect of the intervention. By contrast, the distributed lag functional terms represent the idea that the intervention effect does not start at a fixed time point but is distributed over a certain interval (thus, the intervention timing seems unclear). We discuss how to select the distribution of the effect, the model construction process, diagnosing the model fitting, and interpreting the results. Further, our model is implemented as an example of a statement of emergency (SoE) during the coronavirus disease 2019 pandemic in Japan. RESULTS: We illustrate the ARIMAITS-DL model with some practical distributed lag terms to examine the effect of the SoE on human mobility in Japan. We confirm that the SoE was successful in reducing the movement of people (15.0-16.0% reduction in Tokyo), at least between February 20 and May 19, 2020. We also provide the R code for other researchers to easily replicate our method. CONCLUSIONS: Our model, ARIMAITS-DL, is a useful tool as it can account for the unclear intervention timing and distributed lag effect with autocorrelation and allows for flexible modeling of different types of impacts such as uniformly or normally distributed impact over time.

Gut-microbiota-brain axis in the vulnerability to psychosis in adulthood after repeated cannabis exposure during adolescence.

Increasing epidemiological evidence shows that the use of cannabis during adolescence could increase the risk for psychosis in adulthood. However, the precise mechanisms underlying long-lasting cannabis-induced risk for psychosis remain unclear. Accumulating evidence suggests the role of gut microbiota in the pathogenesis of psychiatric disorders. Here, we examined whether gut microbiota plays a role in the risk for psychosis of adult after exposure of cannabinoid (CB) receptor agonist WIN55,212-2 during adolescence. Repeated administration of WIN55,212-2 (2 mg/kg/day) during adolescence (P35-P45) significantly increased the expression of Iba1 (ionized calcium-binding adapter molecule 1) in the medial prefrontal cortex (mPFC) and nucleus accumbens (NAc) of adult mice after administration of lipopolysaccharide (LPS: 0.5 mg/kg). In contrast, there were no changes in blood levels of pro-inflammatory cytokines between the two groups. Although alpha-diversity and beta-diversity of gut microbiota were no differences between the two groups, there were several microbes altered between the two groups. Interestingly, there were significant correlations between the relative abundance of microbiota and Iba1 expression in the mPFC and NAc. Furthermore, there were also significant correlations between the relative abundance of microbiota and several metabolites in the blood. These findings suggest that gut microbiota may play a role in the microglial activation in the mPFC and NAc of adult mice after repeated WIN55,212-2 exposure during adolescence. Therefore, it is likely that gut-microbiota-microglia crosstalk might play a role in increased risk for psychosis in adults with cannabis use during adolescence.

Inter-prefectural Travel and Network Connectedness During the COVID-19 Pandemic in Japan.

BACKGROUND: Increases in human mobility have been linked to rises in novel coronavirus disease 2019 (COVID-19) transmission. The pandemic era in Japan has been characterized by changes in inter-prefectural mobility across state of emergency (SOE) declarations and travel campaigns, but they have yet to be characterized. METHODS: Using Yahoo Japan mobility data extracted from the smartphones of more than 10 million Japanese residents, we calculated the monthly number of inter-prefectural travel instances, stratified by residential prefecture and destination prefecture. We then used this adjacency matrix to calculate two network connectedness metrics, closeness centrality and effective distance, that reliably predict disease transmission. RESULTS: Inter-prefectural mobility and network connectedness decreased most considerably during the first SOE, but this decrease dampened with each successive SOE. Mobility and network connectedness increased during the Go To Travel campaign. Travel volume between distant prefectures decreased more than travel between prefectures with geographic proximity. Closeness centrality was found to be negatively correlated with the rate of COVID-19 infection across prefectures, with the strength of this association increasing in tandem with the infection rate. Changes in effective distance were more visible among geographically isolated prefectures (Hokkaido and Okinawa) than among metropolitan, central prefectures (Tokyo, Aichi, Osaka, and Fukuoka). CONCLUSION: The magnitude of reductions in human mobility decreased with each subsequent state of emergency, consistent with pandemic fatigue. The association between network connectedness and rates of COVID-19 infection remained visible throughout the entirety of the pandemic period, suggesting that inter-prefectural mobility may have contributed to disease spread.

Salt intake reduction using umami substance-incorporated food: a secondary analysis of NHANES 2017-2018 data.

OBJECTIVE: Excessive salt intake raises blood pressure and increases the risk of non-communicable diseases (NCD), such as CVD, chronic kidney disease and stomach cancer. Reducing the Na content of food is an important public health measure to control the NCD. This study quantifies the amount of salt reduced by using umami substances, i.e. glutamate, inosinate and guanylate, for adults in the USA. DESIGN: The secondary data analysis was performed using data of the US nationally representative cross-sectional dietary survey, the National Health and Nutrition Examination Survey (NHANES) 2017-2018. Per capita daily salt intake corresponding to the NHANES food groups was calculated in the four hypothetical scenarios of 0 %, 30 %, 60 % and 90 % market share of low-Na foods in the country. The salt reduction rates by using umami substances were estimated based on the previous study results. SETTING: The USA. PARTICIPANTS: 4139 individuals aged 20 years and older in the USA. RESULTS: Replacing salt with umami substances could help the US adults reduce salt intake by 7·31-13·53 % (7·50-13·61 % for women and 7·18-13·53 % for men), which is equivalent to 0·61-1·13 g/d (0·54-0·98 g/d for women and 0·69-1·30 g/d for men) without compromising the taste. Approximately, 21·21-26·04 % of the US adults could keep their salt intake below 5 g/d, the WHO's recommendation in the scenario where there is no low-Na product on the market. CONCLUSIONS: This study provides essential information that the use of umami substances as a substitute for salt may help reduce the US adults' salt intake.

Neurological development in 36-month-old children conceived via assisted reproductive technology: The Japan Environment and Children's Study.

Purpose: This study aimed to investigate neurodevelopment in children conceived via in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) with several types of embryo transfers. Methods: We analyzed data for 77 928 children and their mothers included in a Japanese birth cohort study. Among the included children, 4071 were conceived via IVF, while 1542 were conceived via ICSI. Neurodevelopmental delay at the age of 3 years was assessed using the Japanese version of the Ages and Stages Questionnaires, 3rd edition. Results: In the crude model, the odds ratios for developmental delay in 1-4 domains were higher among children conceived via IVF, ICSI, and non-ART (ovulatory induction or intrauterine insemination) than in spontaneously conceived children. After adjusting for parental background factors and the child's sex, there were no differences in the risk of developmental delay when comparing singletons conceived by IVF, ICSI, or non-ART and those conceived spontaneously. Higher odds ratios for developmental delay in one domain were observed in singleton girls conceived via IVF when compared with those who were spontaneously conceived. Conclusion: Most cases of developmental delay may be associated with multiple pregnancies and factors related to infertility, such as parental age, irrespective of the use of ART.

Excess All-Cause Deaths during Coronavirus Disease Pandemic, Japan, January-May 20201.

To provide insight into the mortality burden of coronavirus disease (COVID-19) in Japan, we estimated the excess all-cause deaths for each week during the pandemic, January-May 2020, by prefecture and age group. We applied quasi-Poisson regression models to vital statistics data. Excess deaths were expressed as the range of differences between the observed and expected number of all-cause deaths and the 95% upper bound of the 1-sided prediction interval. A total of 208-4,322 all-cause excess deaths at the national level indicated a 0.03%-0.72% excess in the observed number of deaths. Prefecture and age structure consistency between the reported COVID-19 deaths and our estimates was weak, suggesting the need to use cause-specific analyses to distinguish between direct and indirect consequences of COVID-19.

Geographically weighted generalized Farrington algorithm for rapid outbreak detection over short data accumulation periods.

The demand for rapid surveillance and early detection of local outbreaks has been growing recently. The rapid surveillance can select timely and appropriate interventions toward controlling the spread of emerging infectious diseases, such as the coronavirus disease 2019 (COVID-19). The Farrington algorithm was originally proposed by Farrington et al (1996), extended by Noufaily et al (2012), and is commonly used to estimate excess death. However, one of the major challenges in implementing this algorithm is the lack of historical information required to train it, especially for emerging diseases. Without sufficient training data the estimation/prediction accuracy of this algorithm can suffer leading to poor outbreak detection. We propose a new statistical algorithm-the geographically weighted generalized Farrington (GWGF) algorithm-by incorporating both geographically varying and geographically invariant covariates, as well as geographical information to analyze time series count data sampled from a spatially correlated process for estimating excess death. The algorithm is a type of local quasi-likelihood-based regression with geographical weights and is designed to achieve a stable detection of outbreaks even when the number of time points is small. We validate the outbreak detection performance by using extensive numerical experiments and real-data analysis in Japan during COVID-19 pandemic. We show that the GWGF algorithm succeeds in improving recall without reducing the level of precision compared with the conventional Farrington algorithm.

Mobility Patterns in Different Age Groups in Japan during the COVID-19 Pandemic: a Small Area Time Series Analysis through March 2021.

In the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan-each defined as an area overlaid by several 125-meter grids-from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.

Travel restrictions and SARS-CoV-2 transmission: an effective distance approach to estimate impact.

OBJECTIVE: To estimate the effect of airline travel restrictions on the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) importation. METHODS: We extracted passenger volume data for the entire global airline network, as well as the dates of the implementation of travel restrictions and the observation of the first case of coronavirus disease (COVID-19) in each country or territory, from publicly available sources. We calculated effective distance between every airport and the city of Wuhan, China. We modelled the risk of SARS-CoV-2 importation by estimating survival probability, expressing median time of importation as a function of effective distance. We calculated the relative change in importation risk under three different hypothetical scenarios that all resulted in different passenger volumes. FINDINGS: We identified 28 countries with imported cases of COVID-19 as at 26 February 2020. The arrival time of the virus at these countries ranged from 39 to 80 days since identification of the first case in Wuhan. Our analysis of relative change in risk indicated that strategies of reducing global passenger volume and imposing travel restrictions at a further 10 hub airports would be equally effective in reducing the risk of importation of SARS-CoV-2; however, this reduction is very limited with a close-to-zero median relative change in risk. CONCLUSION: The hypothetical variations in observed travel restrictions were not sufficient to prevent the global spread of SARS-CoV-2; further research should also consider travel by land and sea. Our study highlights the importance of strengthening local capacities for disease monitoring and control.

Mother to Fetus Transfer of Hydroxylated Polychlorinated Biphenyl Congeners (OH-PCBs) in the Japanese Macaque (Macaca fuscata): Extrapolation of Exposure Scenarios to Humans.

Prenatal hydroxylated polychlorinated biphenyls (OH-PCBs) exposure may disrupt fetal brain development during the critical period of thyroid hormone (TH) action. However, there are limited studies on the OH-PCB transfer to the fetal brain, particularly in primates. In this study, we selected the Japanese macaque (Macaca fuscata) as a model animal for the fetal transfer of OH-PCBs in humans and revealed OH-PCB concentrations and their relationships in maternal and fetal blood, liver, and brain. l-thyroxine (T4)-like OH-PCBs including 4OH-CB187, a major congener in humans, were found in high proportions in the blood, liver, brain, and placenta of pregnant Japanese macaques. OH-PCBs were detected in the fetal brain and liver in the first trimester, indicating their transfer to the brain in the early pregnancy stage. 4OH-CB187 and 4OH-CB202 were the major congeners found in fetal brain, indicating that these T4-like OH-PCBs are transported from maternal blood to the fetal brain via the placenta. These results indicate that further studies are needed on the effects of OH-PCBs on the developing fetal brain.

Early SNS-Based Monitoring System for the COVID-19 Outbreak in Japan: A Population-Level Observational Study.

BACKGROUND: The World Health Organization declared the novel coronavirus outbreak (COVID-19) to be a pandemic on March 11, 2020. Large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan would improve preparation for and prevention of a massive outbreak. METHODS: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was developed using the LINE app to evaluate the current Japanese epidemiological situation. LINE users could participate in the system either though a QR code page in the prefectures' websites or a banner at the top of the LINE app screen. COOPERA asked participants questions regarding personal information, preventive actions, and non-specific symptoms related to COVID-19 and their duration. We calculated daily cross correlation functions between the reported number of infected cases confirmed using polymerase chain reaction and the symptom-positive group captured by COOPERA. RESULTS: We analyzed 206,218 participants from three prefectures reported between March 5 and 30, 2020. The mean age of participants was 44.2 (standard deviation, 13.2) years. No symptoms were reported by 96.93% of participants, but there was a significantly positive correlation between the reported number of COVID-19 cases and self-reported fevers, suggesting that massive monitoring of fever might help to estimate the scale of the COVID-19 epidemic in real time. CONCLUSIONS: COOPERA is the first real-time system being used to monitor trends in COVID-19 in Japan and provides useful insights to assist political decisions to tackle the epidemic.