Long-term evacuation and obesity: a 12-year follow-up comparative study of residents inside and outside Katsurao Village after the Fukushima nuclear disaster.

Objective: Evacuation, owing to a disaster, impacts various aspects of an individual's life, including health status. This study aimed to determine the prevalence of obesity among residents of Katsurao Village, Fukushima Prefecture, after the evacuation order due to the Fukushima nuclear disaster in 2011 was lifted in 2016 and to compare the prevalence of obesity by place of residence (inside or outside the village). Methods: The number of examinees, sex, age, place of residence, body mass index (BMI), exercise habits, smoking habits, drinking habits, and dietary status were extracted from the results of health checkups since 2016. We compared the BMI of the indigenes of Katsurao Village by place of residence (inside or outside the village) over time. Results: Although 7 years have passed since 2016, ~70% of the registered residents of Katsurao Village still live outside the village. The obesity rates have consistently been higher among people living outside the village compared to those inside, and the place of residence was the only factor significantly associated with obesity. Conclusion: The findings of this study suggest early intervention is necessary to prevent health risks associated with disaster evacuation if the evacuation period is prolonged.

The difficulty of nuclear emergency prevention measures during natural disasters: ongoing challenges in Japan.

It is crucial to anticipate nuclear emergency scenarios and implement effective measures. Japan's climate and topography make it vulnerable to natural disasters; thus, it is necessary to address compounding and cascading disaster scenarios involving the simultaneous occurrence of natural and nuclear disasters. On 1 January 2024, an earthquake hit the Noto region of Ishikawa Prefecture, resulting in damage to the area around the Shika Nuclear Power Plant, located 90 km from the epicenter. This earthquake revealed that, in the event of a complex disaster, it is possible that residents living within 30 km of the Shika Nuclear Power Plant will be completely unprepared for a nuclear disaster. In the event of a complex disaster, it is crucial to implement appropriate countermeasures while balancing responses to both nuclear and natural disasters and optimizing radiation disaster prevention measures.

Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population.

As we learned during the COVID-19 pandemic, vaccines are one of the most important tools in infectious disease control. To date, an unprecedentedly large volume of high-quality data on COVID-19 vaccinations have been accumulated. For preparedness in future pandemics beyond COVID-19, these valuable datasets should be analyzed to best shape an effective vaccination strategy. We are collecting longitudinal data from a community-based cohort in Fukushima, Japan, that consists of 2,407 individuals who underwent serum sampling two or three times after a two-dose vaccination with either BNT162b2 or mRNA-1273. Using the individually reconstructed time courses of the vaccine-elicited antibody response based on mathematical modeling, we first identified basic demographic and health information that contributed to the main features of the antibody dynamics, i.e., the peak, the duration, and the area under the curve. We showed that these three features of antibody dynamics were partially explained by underlying medical conditions, adverse reactions to vaccinations, and medications, consistent with the findings of previous studies. We then applied to these factors a recently proposed computational method to optimally fit an "antibody score", which resulted in an integer-based score that can be used as a basis for identifying individuals with higher or lower antibody titers from basic demographic and health information. The score can be easily calculated by individuals themselves or by medical practitioners. Although the sensitivity of this score is currently not very high, in the future, as more data become available, it has the potential to identify vulnerable populations and encourage them to get booster vaccinations. Our mathematical model can be extended to any kind of vaccination and therefore can form a basis for policy decisions regarding the distribution of booster vaccines to strengthen immunity in future pandemics.

Understanding Reasons for Vaccination Hesitancy and Implementing Effective Countermeasures: An Online Survey of Individuals Unvaccinated against COVID-19.

This online survey of unvaccinated people living in Japan aimed to identify the reasons for declining vaccination and to develop effective countermeasures. We conducted a hierarchical class analysis to classify participants, examine factors influencing their classification, and provide the information they needed about coronavirus disease 2019 (COVID-19) and trusted sources of COVID-19 information for each group. A total of 262 participants were classified into three groups: Group 1 with no specific reason (28 participants, 10.69%); Group 2 with clear concerns about trust in the vaccine (85 participants, 32.44%), and Group 3 with attitudinal barriers, such as distrust of the vaccine and complacency towards COVID-19, and structural barriers, such as vaccination appointments (149 participants, 56.87%). For each group, females tended to be classified in Group 2 more than Group 1 (Odds ratio (OR) [95% confidential intervals (95%CI)] = 1.64 (0.63 to 2.66), p = 0.001) and in Group 3 more than Group 1 (OR [95%CI] = 1.16 (0.19 to 2.12), p = 0.019). The information that the participants wanted to know about COVID-19 was different among each group (Safety: p < 0.001, Efficacy: p < 0.001, Genetic effects: p < 0.001). Those who did not receive the COVID-19 vaccine also had lower influenza vaccination coverage (8.02%). Additionally, 38 participants (14.50%) were subject to social disadvantages because they had not received the COVID-19 vaccine. Countermeasures should be carefully tailored according to the target population, reasons for hesitancy, and specific context. The findings of this study may help develop individualized countermeasures to address vaccine hesitancy.

Awareness of disaster preparedness between administrative staff and residents in the vicinity of the Genkai and Ikata nuclear power plants following the Fukushima Daiichi nuclear power plant disaster.

When considering disaster preparedness, one challenge is mitigating the health impacts of evacuations. Nuclear disaster preparedness has evolved based on past experiences from numerous disasters, including the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. However, there is a lack of comprehensive reporting on the awareness of administrative staff, medical personnel, and residents in the areas surrounding nuclear power plants (NPPs). This study reports on a survey aimed at gaining insights into the understanding and current state of disaster preparedness and elucidating the differences in perceptions of nuclear disaster preparedness among the relevant stakeholders surrounding NPPs. Interview surveys were conducted from 14 to 16 September 2022 in the area surrounding Kyushu Electric Power's Genkai NPP in Saga Prefecture and from 11 to 13 January 2023 in the area around Shikoku Electric Power's Ikata NPP. The surveys targeted administrative, medical, and nursing care facilities and residents. Responses from 57 participants indicated a lack of awareness of natural and nuclear disasters, challenges in evacuation planning, and a gap between nuclear disaster training and residents' understanding of evacuation protocols. This study highlights inadequacies in nuclear disaster preparedness and the need for a better understanding among residents regarding evacuation procedures. This study identified three key issues: (1) a lack of awareness about disasters, including nuclear disasters; (2) concerns about complex disasters and the difficulties in creating evacuation plans; and (3) a discrepancy between nuclear disaster training and residents' understanding of evacuation procedures. To bridge this gap, it is important to deepen residents' understanding of nuclear disasters, continuously convey the lessons learned from the FDNPP accident, and regularly reassess and update nuclear disaster preparedness strategies.

Diminished neutralizing activity against the XBB1.5 strain in 55.9% of individuals post 6 months COVID-19 mRNA booster vaccination: insights from a pseudovirus assay on 1,353 participants in the Fukushima vaccination community survey, Japan.

This study investigates the neutralizing activity against the XBB1.5 variant and the ancestral strain in a population post-bivalent vaccination using a pseudo virus assay validated with authentic virus assay. While bivalent booster vaccination and past infections enhanced neutralization against the XBB 1.5 strain, individuals with comorbidities showed reduced responses. The study suggests the need for continuous vaccine updates to address emerging SARS-CoV-2 variants and highlights the importance of monitoring real-world immune responses.

Fabrication of a high performance flexible capacitive porous GO/PDMS pressure sensor based on droplet microfluidic technology.

Porous structures are an effective way to improve the performance of flexible capacitive sensors, but the pore size uniformity of porous structures is not easily controlled by current methods, which may affect the inconsistent performance of different batches of sensors. In this paper, a high performance capacitive flexible porous GO/PDMS pressure sensor was prepared based on droplet microfluidic technology. By testing the performance of the sensor, we found that the sensor with a flow rate ratio of 1 : 3 has relatively good performance, with a degree of hysteresis (DH) of 8.64% and a coefficient of variation (CV) of 5.2%. Therefore, we studied the sensor performance based on this process. The result shows that the sensitivity of the flexible capacitive porous GO/PDMS pressure sensor reached 0.627 kPa-1 at low pressure (0-3 kPa), which is significantly higher than that of the pure PDMS thin film sensor (about 0.031 kPa-1) and the porous PDMS pressure sensor (0.263 kPa-1). At the same time, the sensor has a large range with a fast response time of 240 ms and a relaxation time of 300 ms at 30 kPa and an ultra-low detection limit (70 Pa). It can maintain stable operation under continuous force loading/unloading cycles and can respond well to different pressure step changes, so the sensor can be used to detect the movement process of each finger, knee, foot and other joints of the human body. In conclusion, the droplet microfluidic technology can effectively prepare high-performance capacitive flexible porous GO/PDMS pressure sensors.

Categorization of disaster-related deaths in Minamisoma city after the Fukushima nuclear disaster using clustering analysis.

The medical situation during disasters often differs from that at usual times. Disasters can lead to significant mortality that can be difficult to monitor. The types of disaster-related deaths are largely unknown. In this study, we conducted a survey to categorize the disaster-related deaths caused by a radiation disaster. A total of 520 people living in Minamisoma City, Fukushima Prefecture, at the time of the Fukushima Daiichi Nuclear Power Plant accident, who were certified to have died due to disaster-related causes were surveyed. We divided the participants into those who were at home at the time of the earthquake and those who were in hospitals or facilities when the disaster struck and conducted a hierarchical cluster analysis of the two groups. Disaster-related deaths could be divided into seven groups for those who were at home at the time of the disaster and five groups for those who were in hospitals or facilities at the time of the disaster. Each group showed different characteristics, such as "the group with disabilities," "the group receiving care," and "the group with depression," and it became evident that not only uniform post-disaster support, but support tailored to the characteristics of each group is necessary.

Predicting CKD progression using time-series clustering and light gradient boosting machines.

Predicting the transition of kidney function in chronic kidney disease is difficult as specific symptoms are lacking and often overlooked, and progress occurs due to complicating factors. In this study, we applied time-series cluster analysis and a light gradient boosting machine to predict the trajectories of kidney function in non-dialysis dependent chronic kidney disease patients with baseline estimated glomerular filtration rate (GFR) ≥ 45 mL/min/1.73 m2. Based on 5-year changes in estimated GFR, participants were stratified into groups with similar trajectories by cluster analysis. Next, we applied the light gradient boosting machine algorithm and Shapley addictive explanation to develop a prediction model for clusters and identify important parameters for prediction. Data from 780 participants were available for analysis. Participants were classified into five classes (Class 1: n = 78, mean [± standard deviation] estimated GFR 100 ± 19.3 mL/min/1.73 m2; Class 2: n = 176, 76.0 ± 9.3 mL/min/1.73 m2; Class 3: n = 191, 59.8 ± 5.9 mL/min/1.73 m2; Class 4: n = 261, 52.7 ± 4.6 mL/min/1.73 m2; and Class 5: n = 74, 53.5 ± 12.0 mL/min/1.73 m2). Declines in estimated GFR were 8.9% in Class 1, 12.2% in Class 2, 4.9% in Class 3, 12.0% in Class 4, and 45.1% in Class 5 during the 5-year period. The accuracy of prediction was 0.675, and the top three most important Shapley addictive explanation values were 1.61 for baseline estimated GFR, 0.12 for hemoglobin, and 0.11 for body mass index. The estimated GFR transition of patients with preserved chronic kidney disease mostly depended on baseline estimated GFR, and the borderline for estimated GFR trajectory was nearly 50 mL/min/1.73 m2.

Idobata-Nagaya: a community housing solution for socially isolated older adults following the great East Japan earthquake.

Introduction: Following the Great East Japan Earthquake, the living environment of socially isolated older adults has become a pressing concern. In response, Nagaya, a collective housing program, was established in Soma City, Fukushima, Japan to address social isolation among older adults and support their long-term health. This study aimed to identify characteristics of individuals in Nagaya and examine the sustainability of this initiative. Methods: We conducted a retrospective analysis of residents who were relocated to Nagaya, emphasizing their characteristics, the continuity of their stay in Nagaya, and their care certification levels, using data up to December 31, 2022. We employed Kaplan-Meier curves to analyze the duration for which residents continued to reside in Nagaya and the time leading up to the requiring care-level certification. Results: Of 65 people who moved to Nagaya after the disaster, 30 people (46.2%) continued to live there, 21 (32.3%) died during their stay, and 14 (21.5%) moved out. The overall duration of occupancy averaged 6.39 years (SD 3.83 years). The proportion of requiring care-level certification occurrences per person-year was 0.0577 for those without care certification and 0.3358 for those with requiring support level at the time of moving in. Conclusion: In summary, Nagaya-style communal housing may offer suitable living environments for older adults with diverse needs during disasters and serve as a valuable tool for developing public policies in aging societies.

Insights and viewpoints from a small-scale survey on current nuclear disaster preparedness measures in Japan after the Fukushima Daiichi Nuclear Power Plant accident.

In nuclear disaster prevention, it is essential not only to make daily efforts to prevent accidents from occurring but also to properly apply lessons learnt from actual disasters. Although significant changes have been made to nuclear disaster preparedness in Japan since the Fukushima Daiichi Nuclear Power Plant accident, there is insufficient information on whether these changes have been evaluated as practical and appropriate for the needs of the Japanese public. In this survey, 20 officials of the Cabinet Office and Japan Atomic Energy Agency, in charge of planning nuclear disaster prevention policy, were asked to evaluate the current nuclear disaster prevention plan through a questionnaire, and compare it with that before the accident, and indicate what elements are lacking in the current plan. The survey results revealed that 30% of the participants (six respondents) had a positive view of the enhancement of resources, including physical and human assets. However, as many as 60% (12 respondents) expressed negative sentiments, primarily due to perceived deficiencies in organisational measures, particularly the coordination of these resources. Moreover, the participants expressed keen interest in obtaining health data during evacuation, along with information on the physical and mental effects on evacuees living in evacuation centres. These crucial insights can inform the formulation of effective future preparedness plans for evacuation and radiation protection.

Antibody Profiling of Microbial Antigens in the Blood of COVID-19 mRNA Vaccine Recipients Using Microbial Protein Microarrays.

Although studies have demonstrated that infections with various viruses, bacteria, and parasites can modulate the immune system, no study has investigated changes in antibodies against microbial antigens after the COVID-19 mRNA vaccination. IgG antibodies against microbial antigens in the blood of vaccinees were comprehensively analyzed using microbial protein microarrays that carried approximately 5000 microbe-derived proteins. Changes in antibodies against microbial antigens were scrutinized in healthy participants enrolled in the Fukushima Vaccination Community Survey conducted in Fukushima Prefecture, Japan, after their second and third COVID-19 mRNA vaccinations. Antibody profiling of six groups stratified by antibody titer and the remaining neutralizing antibodies was also performed to study the dynamics of neutralizing antibodies against SARS-CoV-2 and the changes in antibodies against microbial antigens. The results showed that changes in antibodies against microbial antigens other than SARS-CoV-2 antigens were extremely limited after COVID-19 vaccination. In addition, antibodies against a staphylococcal complement inhibitor have been identified as microbial antigens that are associated with increased levels of neutralizing antibodies against SARS-CoV-2. These antibodies may be a predictor of the maintenance of neutralizing antibodies following the administration of a COVID-19 mRNA vaccine.

Multisite Lifestyle for Older People after the Fukushima Nuclear Disaster.

After the Fukushima nuclear power plant disaster in 2011, the Japanese government implemented a return policy, lifting most evacuation orders in former evacuation areas. Consequently, the return of residents is currently underway. However, it has become common for a large number of residents to carry out multisite living, a lifestyle involving returning to their hometown while maintaining their house at the evacuation site, or living at more than two sites. This report focuses on one aspect of the secondary effects of the nuclear incident, which forced affected residents to adopt a multisite lifestyle. Disasters always have a strong impact, via displacement, on those who are socially vulnerable, such as older people in an ageing society. They need intense support to resume their daily life as it was before the incident. For this report, we interviewed an elderly lady in her 90s, who is executing "multisite living" at evacuation sites, in order to obtain reassurance from neighbours and the local community. Our findings may provide valuable suggestions on how older people can restart their lives with the local community in an ageing society after disasters, which could apply to any kind of disaster preparedness.

Five doses of the mRNA vaccination potentially suppress ancestral-strain stimulated SARS-CoV2-specific cellular immunity: a cohort study from the Fukushima vaccination community survey, Japan.

The bivalent mRNA vaccine is recommended to address coronavirus disease variants, with additional doses suggested for high-risk groups. However, the effectiveness, optimal frequency, and number of doses remain uncertain. In this study, we examined the long-term cellular and humoral immune responses following the fifth administration of the mRNA severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in patients undergoing hemodialysis. To our knowledge, this is the first study to monitor long-term data on humoral and cellular immunity dynamics in high-risk populations after five doses of mRNA vaccination, including the bivalent mRNA vaccine. Whereas most patients maintained humoral immunity throughout the observation period, we observed reduced cellular immune reactivity as measured by the ancestral-strain-stimulated ELISpot assay in a subset of patients. Half of the individuals (50%; 14/28) maintained cellular immunity three months after the fifth dose, despite acquiring humoral immunity. The absence of a relationship between positive controls and T-Spot reactivity suggests that these immune alterations were specific to SARS-CoV-2. In multivariable analysis, participants aged ≥70 years showed a marginally significant lower likelihood of having reactive results. Notably, among the 14 individuals who received heterologous vaccines, 13 successfully acquired cellular immunity, supporting the effectiveness of this administration strategy. These findings provide valuable insights for future vaccination strategies in vulnerable populations. However, further research is needed to evaluate the involvement of immune tolerance and exhaustion through repeated vaccination to optimize immunization strategies.

Association of systemic adverse reaction patterns with long-term dynamics of humoral and cellular immunity after coronavirus disease 2019 third vaccination.

The objective of this study was to clarify the impact of adverse reactions on immune dynamics. We investigated the pattern of systemic adverse reactions after the second and third coronavirus disease 2019 (COVID-19) vaccinations and their relationship with immunoglobulin G against severe acute respiratory syndrome coronavirus 2 spike 1 protein titers, neutralizing antibody levels, peak cellular responses, and the rate of decrease after the third vaccination in a large-scale community-based cohort in Japan. Participants who received a third vaccination with BNT162b2 (Pfizer/BioNTech) or mRNA-1273 (Moderna), had two blood samples, had not had COVID-19, and had information on adverse reactions after the second and third vaccinations (n = 2198) were enrolled. We collected data on sex, age, adverse reactions, comorbidities, and daily medicine using a questionnaire survey. Participants with many systemic adverse reactions after the second and third vaccinations had significantly higher humoral and cellular immunity in the peak phase. Participants with multiple systemic adverse reactions after the third vaccination had small changes in the geometric values of humoral immunity and had the largest geometric mean of cellar immunity in the decay phase. Systemic adverse reactions after the third vaccination helped achieve high peak values and maintain humoral and cellular immunity. This information may help promote uptake of a third vaccination, even among those who hesitate due to adverse reactions.

Varying Cellular Immune Response against SARS-CoV-2 after the Booster Vaccination: A Cohort Study from Fukushima Vaccination Community Survey, Japan.

Booster vaccination reduces the incidence of severe cases and mortality related to COVID-19, with cellular immunity playing an important role. However, little is known about the proportion of the population that has achieved cellular immunity after booster vaccination. Thus, we conducted a Fukushima cohort database and assessed humoral and cellular immunity in 2526 residents and healthcare workers in Fukushima Prefecture in Japan through continuous blood collection every 3 months from September 2021. We identified the proportion of people with induced cellular immunity after booster vaccination using the T-SPOT.COVID test, and analyzed their background characteristics. Among 1089 participants, 64.3% (700/1089) had reactive cellular immunity after booster vaccination. Multivariable analysis revealed the following independent predictors of reactive cellular immunity: age < 40 years (adjusted odds ratio: 1.81; 95% confidence interval: 1.19-2.75; p-value: 0.005) and adverse reactions after vaccination (1.92, 1.19-3.09, 0.007). Notably, despite IgG(S) and neutralizing antibody titers of ≥500 AU/mL, 33.9% (349/1031) and 33.5% (341/1017) of participants, respectively, did not have reactive cellular immunity. In summary, this is the first study to evaluate cellular immunity at the population level after booster vaccination using the T-SPOT.COVID test, albeit with several limitations. Future studies will need to evaluate previously infected subjects and their T-cell subsets.

A Generic Graph-Based Neural Architecture Encoding Scheme With Multifaceted Information.

Neural architecture search (NAS) can automatically discover well-performing architectures in a large search space and has been shown to bring improvements to various applications. However, the computational burden of NAS is huge, since exploring a large search space can need evaluating more than thousands of architecture samples. To improve the sample efficiency of search space exploration, predictor-based NAS methods learn a performance predictor of architectures, and utilize the predictor to sample worth-evaluating architectures. The encoding scheme of NN architectures is crucial to the predictor's generalization ability, and thus crucial to the efficacy of the NAS process. To this end, we have designed a generic Graph-based neural ArchiTecture Encoding Scheme (GATES), a more reasonable modeling of NN architectures that mimics their data processing. Nevertheless, GATES is unaware of the concrete computing semantic of NN operations or architectures. Thus, the learning of operation embeddings and weights in GATES can only exploit the information in architectures-performance pairs. We propose GATES++, which incorporates multifaceted information about NN's operation-level and architecture-level computing semantics into its construction and training, respectively. Experiments on benchmark search spaces show that both the operation-level and architecture-level information can bring improvements alone, and GATES++ can discover better architectures after evaluating the same number of architectures.