Generative artificial intelligence and non-pharmacological bias: an experimental study on cancer patient sexual health communications.

Objectives The objective of this study was to explore the feature of generative artificial intelligence (AI) in asking sexual health among cancer survivors, which are often challenging for patients to discuss.Methods We employed the Generative Pre-trained Transformer-3.5 (GPT) as the generative AI platform and used DocsBot for citation retrieval (June 2023). A structured prompt was devised to generate 100 questions from the AI, based on epidemiological survey data regarding sexual difficulties among cancer survivors. These questions were submitted to Bot1 (standard GPT) and Bot2 (sourced from two clinical guidelines).Results No censorship of sexual expressions or medical terms occurred. Despite the lack of reflection on guideline recommendations, 'consultation' was significantly more prevalent in both bots' responses compared with pharmacological interventions, with ORs of 47.3 (p<0.001) in Bot1 and 97.2 (p<0.001) in Bot2.Discussion Generative AI can serve to provide health information on sensitive topics such as sexual health, despite the potential for policy-restricted content. Responses were biased towards non-pharmacological interventions, which is probably due to a GPT model designed with the 's prohibition policy on replying to medical topics. This shift warrants attention as it could potentially trigger patients' expectations for non-pharmacological interventions.

Effects of Overweight on Risk of Thyroid Nodules in Children and Adolescents: The Fukushima Health Management Survey.

CONTEXT: Examining how overweight/obesity impacts thyroid nodule development in children and adolescents by sex and age can speculate on the mechanism. OBJECTIVE: We examined whether overweight in children and adolescents are associated with thyroid nodule development by sex and age. DESIGN: Approximately 300,000 participants who underwent thyroid ultrasonography in the Fukushima Health Management Survey after a nuclear accident were enrolled. Those without nodules in the initial two examinations (1-3 and 4-5 years postaccident) were prospectively assessed for nodule development in the third examination (6-7 years postaccident) relative to baseline overweight status, with an average follow-up of 4.2 years. SETTING: A population-based prospective cohort study. PARTICIPANTS: The first and second thyroid examinations involved 299,939 and 237,691 participants, respectively, excluding those with thyroid nodules. After the third examination, 184,519 participants were finalized for analysis. MAIN OUTCOME MEASURES: Multivariable-adjusted odds ratios of new detected thyroid nodules for overweight participants compared with normal-weight participants. RESULTS: New thyroid nodules were detected in 660 participants. Being overweight was positively associated with thyroid nodules. The adjusted odds ratio (95% confidence interval) of thyroid nodules for overweight participants compared with other participants was 1.27 (1.04-1.57). Additionally, the multivariable-adjusted odds ratios for males and females with overweight were 1.21 and 1.32, respectively, and those for different age groups (0-9, 10-14, and 15-19 years) ranged from 1.17 to 1.75. CONCLUSIONS: Being overweight was associated with thyroid nodules in children and adolescents, mostly adolescent females, regardless of their proximity to the nuclear power plant.

Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.

BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (AD) patients undergoing treatment with dupilumab. Stratifying patients based on the erythema course is crucial for elucidating heterogeneous phenotypes and facilitating advanced drug efficacy predictions. OBJECTIVES: This study aimed to identify factors associated with facial erythema severity in dupilumab-treated AD patients and to establish a prediction model for drug response based on the identified factors. METHODS: Data from a retrospective study conducted between July 2018 and July 2021 were collected and analysed. Patients were categorized into three groups via hierarchical clustering based on the course of facial erythema: early remission, low remission and persistent residual. LightGBM, a supervised gradient boosting decision tree algorithm, was employed to discern group differences and construct a prediction model. The model incorporated patient demographic and clinical profiles, including pre- and post-treatment examinations. The model's performance was evaluated using accuracy and the area under the receiver operating characteristic curve (AUC). RESULTS: The binary classification model demonstrated an accuracy of 89.10% and an AUC of 0.862 when distinguishing between early remission and persistent residual patients. The eight prominent factors associated with facial erythema severity included age, sex, lactate dehydrogenase (LDH), immunoglobulin E (IgE), eosinophil count, white blood cell count, Alnus allergy and cedar allergy. CONCLUSIONS: This study has two main significances: first, three clusters were identified through unsupervised learning; second, a classification model was constructed that proved more accurate than random prediction. The stratification and identification of crucial factors associated with residual facial erythema in dupilumab-treated AD patients lay the foundation for AI-powered prognostic models. This groundwork provides a substantial basis for enhancing future medical AI support in AD treatment selection, potentially improving personalized treatment approaches and outcomes.

Explainable Machine Learning Classification to Identify Vulnerable Groups Among Parenting Mothers: Web-Based Cross-Sectional Questionnaire Study.

BACKGROUND: One life event that requires extensive resilience and adaptation is parenting. However, resilience and perceived support in child-rearing vary, making the real-world situation unclear, even with postpartum checkups. OBJECTIVE: This study aimed to explore the psychosocial status of mothers during the child-rearing period from newborn to toddler, with a classifier based on data on the resilience and adaptation characteristics of mothers with newborns. METHODS: A web-based cross-sectional survey was conducted. Mothers with newborns aged approximately 1 month (newborn cohort) were analyzed to construct an explainable machine learning classifier to stratify parenting-related resilience and adaptation characteristics and identify vulnerable populations. Explainable k-means clustering was used because of its high explanatory power and applicability. The classifier was applied to mothers with infants aged 2 months to 1 year (infant cohort) and mothers with toddlers aged >1 year to 2 years (toddler cohort). Psychosocial status, including depressed mood assessed by the Edinburgh Postnatal Depression Scale (EPDS), bonding assessed by the Postpartum Bonding Questionnaire (PBQ), and sleep quality assessed by the Pittsburgh Sleep Quality Index (PSQI) between the classified groups, was compared. RESULTS: A total of 1559 participants completed the survey. They were split into 3 cohorts, comprising populations of various characteristics, including parenting difficulties and psychosocial measures. The classifier, which stratified participants into 5 groups, was generated from the self-reported scores of resilience and adaptation in the newborn cohort (n=310). The classifier identified that the group with the greatest difficulties in resilience and adaptation to a child's temperament and perceived support had higher incidences of problems with depressed mood (relative prevalence [RP] 5.87, 95% CI 2.77-12.45), bonding (RP 5.38, 95% CI 2.53-11.45), and sleep quality (RP 1.70, 95% CI 1.20-2.40) compared to the group with no difficulties in perceived support. In the infant cohort (n=619) and toddler cohort (n=461), the stratified group with the greatest difficulties had higher incidences of problems with depressed mood (RP 9.05, 95% CI 4.36-18.80 and RP 4.63, 95% CI 2.38-9.02, respectively), bonding (RP 1.63, 95% CI 1.29-2.06 and RP 3.19, 95% CI 2.03-5.01, respectively), and sleep quality (RP 8.09, 95% CI 4.62-16.37 and RP 1.72, 95% CI 1.23-2.42, respectively) compared to the group with no difficulties. CONCLUSIONS: The classifier, based on a combination of resilience and adaptation to the child's temperament and perceived support, was able identify psychosocial vulnerable groups in the newborn cohort, the start-up stage of childcare. Psychosocially vulnerable groups were also identified in qualitatively different infant and toddler cohorts, depending on their classifier. The vulnerable group identified in the infant cohort showed particularly high RP for depressed mood and poor sleep quality.

Synthesis of causal and surrogate models by non-equilibrium thermodynamics in biological systems.

We developed a model to represent the time evolution phenomena of life through physics constraints. To do this, we took into account that living organisms are open systems that exchange messages through intracellular communication, intercellular communication and sensory systems, and introduced the concept of a message force field. As a result, we showed that the maximum entropy generation principle is valid in time evolution. Then, in order to explain life phenomena based on this principle, we modelled the living system as a nonlinear oscillator coupled by a message and derived the governing equations. The governing equations consist of two laws: one states that the systems are synchronized when the variation of the natural frequencies between them is small or the coupling strength through the message is sufficiently large, and the other states that the synchronization is broken by the proliferation of biological systems. Next, to simulate the phenomena using data obtained from observations of the temporal evolution of life, we developed an inference model that combines physics constraints and a discrete surrogate model using category theory, and simulated the phenomenon of early embryogenesis using this inference model. The results show that symmetry creation and breaking based on message force fields can be widely used to model life phenomena.

Relationship between the Residual Cesium Body Contents and Individual Behaviors among Evacuees from Municipalities near the Fukushima Daiichi Nuclear Power Plant.

ABSTRACT: To support estimations of early individual internal doses to residents who suffered from the 2011 accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP), we have sought to use whole-body counter (WBC) measurement results of subjects who lived in municipalities neighboring the FDNPP at the time of the accident. These WBC measurements started several months after the accident; the targeted radionuclides were 134Cs and 137Cs. Our previous study had analyzed the relationship between the residual Cs contents of individuals and evacuation behaviors in the period immediately after the accident for residents of Namie-town, one of the most radiologically affected municipalities. Those results suggested that the first major release event at the FDNPP on 12 March 2011 caused significant exposure, particularly to those who delayed evacuation on that day. The present study expanded its scope to include subjects from four towns neighboring the FDNPP (Namie, Futaba, Okuma, and Tomioka) to gather additional evidence of the exposure that took place on 12 March 2011. Additionally, we investigated the relationship between individual cesium doses and subjects' destinations following the largest release event on 15 March 2011. The study population was 1,145 adults. We first divided the subjects into two evacuation groups depending on the distance from the FDNPP and their evacuation whereabouts (25-km boundary) as of 15:00 on 12 March 2011: the G1 group (≥25 km) and the G2 group (<25 km). We further divided these two subject groups into seven subgroups based on the subjects' destinations as of 0:00 on 16 March 2011. Our four main findings are as follows. (1) The 137Cs detection rate was significantly different between the G1 and G2 groups of Namie-town and Futaba-town but not for those of Okuma-town and Tomioka-town. This result corresponds to the plume passage (flowing toward the northwest to the north) in the afternoon of 12 March 2011 and supports our previous study. (2) The upper-percentile committed effective doses (CEDs) of the G2 groups were higher than those of the G1 groups for all four towns, although the between-group difference varied with the town. The highest CEDs were found in the G2 group of Futaba-town, and the lowest CEDs were in the Namie-town G1 group: 0.16 mSv and 0.04 mSv at the 90th percentile, respectively. The CEDs for both the G1 and G2 groups were relatively high for Okuma-town and Tomioka-town compared to those of the G1 group of Namie-town, although the former subjects were expected to be less exposed on 12 March 2011 and then evacuated to remote places, as did the residents of the other towns. (3) The CEDs of the G1 subgroup that evacuated outside Fukushima Prefecture were extremely low, suggesting that these subjects were little exposed on both 12 and 15 March 2011. However, the CEDs of the same G1 subgroup were rather higher than those of the corresponding G2 subgroup for Futaba-town and Okuma-town. We thus speculate that the WBC measurements were likely to have been affected by the contamination occurring in the second-round temporary re-entry (except for the Namie-town residents). (4) The analyses of the Namie-town evacuees indicated that the area including the middle and northern parts of Fukushima Prefecture was relatively more affected by the major release event on 15 March 2011. In conclusion, the early cesium intake due to the FDNPP accident remained detectable in the WBC measurements of certain present subjects; however, further analyses of the available data are necessary for a full understanding of the WBC measurement results.

Epigenetic profiles guide improved CRISPR/Cas9-mediated gene knockout in human T cells.

Genetic modification of specific genes is emerging as a useful tool to enhance the functions of antitumor T cells in adoptive immunotherapy. Current advances in CRISPR/Cas9 technology enable gene knockout during in vitro preparation of infused T-cell products through transient transfection of a Cas9-guide RNA (gRNA) ribonucleoprotein complex. However, selecting optimal gRNAs remains a major challenge for efficient gene ablation. Although multiple in silico tools to predict the targeting efficiency have been developed, their performance has not been validated in cultured human T cells. Here, we explored a strategy to select optimal gRNAs using our pooled data on CRISPR/Cas9-mediated gene knockout in human T cells. The currently available prediction tools alone were insufficient to accurately predict the indel percentage in T cells. We used data on the epigenetic profiles of cultured T cells obtained from transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Combining the epigenetic information with sequence-based prediction tools significantly improved the gene-editing efficiency. We further demonstrate that epigenetically closed regions can be targeted by designing two gRNAs in adjacent regions. Finally, we demonstrate that the gene-editing efficiency of unstimulated T cells can be enhanced through pretreatment with IL-7. These findings enable more efficient gene editing in human T cells.

Improvement of spectral analysis using a NaI(Tl) scintillation spectrometer to evaluate ambient gamma dose rates from primordial radionuclides.

In-situ measurements by gamma-ray spectrometry using a NaI(Tl) scintillation spectrometer are performed to discriminate primordial and artificial radionuclides contributing to ambient gamma dose rates in the living environment to quantify prolonged influence of nuclear accidents. However, low energy resolution of the spectrometer causes poor discrimination in the measurements at high-dose-rate points, which leads to overestimation of ambient gamma dose rate from the primordial radionuclides. The present study clarified that photon fluxes originating from 40K and 214Bi were affected by the presence of 134Cs, whereas those from 208Tl were independent of it. In addition, the absorbed dose rates in air were strongly correlated with the 208Tl photon fluxes. These findings indicate that 208Tl photon fluxes can be used to evaluate absorbed dose rates in air from the primordial radionuclides. When estimated from the 208Tl photon fluxes only, the absorbed dose rates in air in Namie Town and Okuma Town, locations affected by the Fukushima Dai-ichi Nuclear Power Plant accident, were 19-71 and 20-47 nGy h-1, respectively.

No increase in translocated chromosomal aberrations, an indicator of ionizing radiation exposure, in childhood thyroid cancer in Fukushima Prefecture.

To investigate the effects of radiation exposure due to the Fukushima nuclear power plant accident, following the disaster Fukushima Prefecture launched thyroid ultrasound examinations of residents who were generally younger than 18 years at the time of the earthquake. As the rate of pediatric thyroid cancer was higher than expected, we conducted biological dose assessment based on the frequency of translocated chromosome (Tr) aberrations using peripheral blood lymphocytes. Tr formation frequency was compared among the thyroid cancer (n = 38, median age 18 years, age range 12-26 years), thyroid-related disease (n = 30, median age 21 years, age range 15-28 years), and healthy controls (n = 31, median age 22 years, age range 20-23 years) groups. Tr aberration frequency was initially significantly higher in the thyroid cancer than in the other two groups; however, differences among the groups disappeared after adjusting for history of CT scan, as 92%, 67%, and 28% of those in the thyroid cancer, thyroid-related disease, and control groups, respectively, had undergone CT previously. Therefore, the significant difference in the initial number of Tr formations is presumably due to radiation exposure from CT. Accordingly, the effects of medical exposure on the chromosomes of children and adolescents should be noted.

Non-negative tensor factorization workflow for time series biomedical data.

Non-negative tensor factorization (NTF) enables the extraction of a small number of latent components from high-dimensional biomedical data. However, NTF requires many steps, which is a hurdle to implementation. Here, we provide a protocol for TensorLyCV, an easy to run and reproducible NTF analysis pipeline using Snakemake workflow management system and Docker container. Using vaccine adverse reaction data as an example, we describe steps for data processing, tensor decomposition, optimal rank parameter estimation, and visualization of factor matrices. For complete details on the use and execution of this protocol, please refer to Kei Ikeda et al.1.

Fruit Peel Powder as Natural Antioxidant and Reinforcing Bio-Filler in Natural Rubber Latex Gloves: Cases of Mangosteen, Pomelo and Durian.

As the world is facing rapid increases in agricultural wastes that greatly affect global health, the environment, and economies, this work aims to alleviate such issues by introducing simple uses of waste fruit peel powder (FPP) derived from mangosteen (MPP), pomelo (PPP), or durian (DPP), as dual natural antioxidants and reinforcing bio-fillers in natural rubber latex (NRL) gloves. A thorough investigation was undertaken of the relevant characteristics for both FPP (morphological, functional groups, particle sizes, and thermals stability) and NRL gloves (morphological, functional groups, density, color, thermal stability, and mechanical properties-both before and after thermal/25 kGy gamma aging). The results indicated that the initial addition (2-4 parts per hundred parts of rubber by weight; phr) of FPP to NRL composites generally enhanced the strength and elongation at the break of the specimens, with the levels of the improvement varying depending on the type and content of FPPs. In addition to the reinforcing effects, the FPP also offered natural antioxidant properties, evidenced by higher values of aging coefficients for all FPP/NRL gloves under either thermal or 25 kGy gamma aging than those of pristine NRL. Furthermore, by comparing the tensile strength and elongation at break of the developed FPP/NRL gloves with the requirements for medical examination latex gloves according to ASTM D3578-05, the recommended FPP contents for actual glove production were 2-4 phr for MPP, 4 phr for PPP, and 2 phr for DPP. Consequently, based on the overall outcomes, the FPPs of interest showed promising potential for utilization as simultaneous natural antioxidants and reinforcing bio-fillers in NRL gloves, which would not only enhance the strength and ability of the gloves to resist oxidative degradation from heat and gamma irradiation but also increase their economical value as well as reducing the amounts of the investigated wastes.

Monitoring of blood biochemical markers for periprosthetic joint infection using ensemble machine learning and UMAP embedding.

INTRODUCTION: Periprosthetic joint infection (PJI) is a serious complication after total joint arthroplasty. It is important to accurately identify PJI and monitor postoperative blood biochemical marker changes for the appropriate treatment strategy. In this study, we aimed to monitor the postoperative blood biochemical characteristics of PJI by contrasting with non-PJI joint replacement cases to understand how the characteristics change postoperatively. MATERIALS AND METHODS: A total of 144 cases (52 of PJI and 92 of non-PJI) were reviewed retrospectively and split into development and validation cohorts. After exclusion of 11 cases, a total of 133 (PJI: 50, non-PJI: 83) cases were enrolled finally. An RF classifier was developed to discriminate between PJI and non-PJI cases based on 18 preoperative blood biochemical tests. We evaluated the similarity/dissimilarity between cases based on the RF model and embedded the cases in a two-dimensional space by Uniform Manifold Approximation and Projection (UMAP). The RF model developed based on preoperative data was also applied to the same 18 blood biochemical tests at 3, 6, and 12 months after surgery to analyze postoperative pathological changes in PJI and non-PJI. A Markov chain model was applied to calculate the transition probabilities between the two clusters after surgery. RESULTS: PJI and non-PJI were discriminated with the RF classifier with the area under the receiver operating characteristic curve of 0.778. C-reactive protein, total protein, and blood urea nitrogen were identified as the important factors that discriminates between PJI and non-PJI patients. Two clusters corresponding to the high- and low-risk populations of PJI were identified in the UMAP embedding. The high-risk cluster, which included a high proportion of PJI patients, was characterized by higher CRP and lower hemoglobin. The frequency of postoperative recurrence to the high-risk cluster was higher in PJI than in non-PJI. CONCLUSIONS: Although there was overlap between PJI and non-PJI, we were able to identify subgroups of PJI in the UMAP embedding. The machine-learning-based analytical approach is promising in consecutive monitoring of diseases such as PJI with a low incidence and long-term course.

Machine learning approach to stratify complex heterogeneity of chronic heart failure: A report from the CHART-2 study.

AIMS: Current approaches to classify chronic heart failure (HF) subpopulations may be limited due to the diversity of pathophysiology and co-morbidities in chronic HF. We aimed to elucidate the clusters of chronic patients with HF by data-driven approaches with machine learning in a hospital-based registry. METHODS AND RESULTS: A total of 4649 patients with a broad spectrum of left ventricular ejection fraction (LVEF) in the CHART-2 (Chronic Heart Failure Analysis and Registry in the Tohoku District-2) study were enrolled to this study. Chronic HF patients were classified using random forest clustering with 56 multiscale clinical parameters. We assessed the influence of the clusters on cardiovascular death, non-cardiovascular death, all-cause death, and free from hospitalization by HF. Latent class analysis using random forest clustering identified 10 clusters with four primary components: cardiac function (LVEF, left atrial and ventricular diameters, diastolic blood pressure, and brain natriuretic peptide), renal function (glomerular filtration rate and blood urea nitrogen), anaemia (red blood cell, haematocrit, haemoglobin, and platelet count), and nutrition (albumin and body mass index). All 11 significant clinical parameters in the four primary components and two disease aetiologies (ischaemic heart disease and valvular heart disease) showed statistically significant differences among the 10 clusters (P < 0.01). Cluster 1 (26.7% of patients), which is characterized by preserved LVEF (<59%, 37% of the total) with lowest brain natriuretic peptide (>111.3 pg/mL, 0.9%) and lowest left atrial diameter (>42 mm, 37.4%), showed the best 5 year survival rate of 98.1% for cardiovascular death, 95.9% for non-cardiovascular death, 92.9% for all-cause death, and 91.7% for free from hospitalization by HF. Cluster 10 (6.0% of the total), which is co-morbid disorders of all four primary components, showed the worst survival rate of 39.1% for cardiovascular death, 68.9% for non-cardiovascular death, 23.9% for all-cause death, and 28.1% for free from hospitalization by HF. CONCLUSIONS: These results suggest the potential applicability of the machine leaning approach, providing useful clinical prognostic information to stratify complex heterogeneity in patients with HF.

Comparison between external and internal doses to the thyroid after the Fukushima Daiichi Nuclear Power Plant accident.

To analyze the association between radiation dose and thyroid cancer after the 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, external doses have often been used because of the difficulty to estimate internal thyroid doses individually due to the lack of human data. However, no evaluation has been made as to whether external dose is a good surrogate marker for internal thyroid dose individually. This study aimed at analyzing the relationship between external doses and internal thyroid doses estimated by recently developed methodology. For four municipalities affected by the accident, 200 individuals aged under 20 at the time of the accident per municipality were randomly selected, and their external and internal thyroid doses and their ratios were estimated individually. In a separate analysis, median and arithmetic mean values for external thyroid doses estimated for persons of 16 municipalities that included the above four were compared with those for previously estimated internal thyroid doses. The ratios of the median of internal thyroid dose to that of external thyroid dose in these 16 municipalities ranged from 0.56 to 13.8 for 15-year-old children and 0.91 to 21.1 for 1-year-old children. No consistent relationship between external and internal thyroid doses was found in all 16 municipalities. Thus, thyroid doses from both external and internal exposures should be used to analyze the association between radiation dose and thyroid cancer detection rates for persons who lived in Fukushima Prefecture at the time of the FDNPP accident. (240).

Statistical Analysis of Mortality Rates of Coronavirus Disease 2019 (COVID-19) Patients in Japan Across the 4C Mortality Score Risk Groups, Age Groups, and Epidemiological Waves: A Report From the Nationwide COVID-19 Cohort.

Background: The mortality rates of coronavirus disease 2019 (COVID-19) have been changed across the epidemiological waves. The aim was to investigate the differences in mortality rates of COVID-19 patients in Japan across the 6 epidemiological waves stratified by age group and Coronavirus Clinical Characterisation Consortium (4C) mortality score risk group. Methods: A total of 56 986 COVID-19 patients in the COVID-19 Registry Japan from 2 March 2020 to 1 February 2022 were enrolled. These patients were categorized into 4 risk groups based on their 4C mortality score. Mortality rates of each risk group were calculated separately for different age groups: 18-64, 65-74, 75-89, and ≥90 years. In addition, mortality rates across the wave periods were calculated separately in 2 age groups: <75 and ≥75 years. All calculated mortality rates were compared with reported data from the United Kingdom (UK) during the early epidemic. Results: The mortality rates of patients in Japan were significantly lower than in the UK across the board, with the exception of patients aged ≥90 years at very high risk. The mortality rates of patients aged ≥75 years at very high risk in the fourth and fifth wave periods showed no significant differences from those in the UK, whereas those in the sixth wave period were significantly lower in all age groups and in all risk groups. Conclusions: The present analysis showed that COVID-19 patients had a lower mortality rate in the most recent sixth wave period, even among patients ≥75 years old at very high risk.

External Doses Available for Epidemiological Studies Related to the Fukushima Health Management Survey: First 4-month Individual Doses and Municipality-average Doses for the First Year.

BACKGROUND: One of the components of the Fukushima Health Management Survey (FHMS) is the Basic Survey, which estimates individual external doses for the first 4 months after the 2011 nuclear power plant accident. However, external exposure continues long-term. According to estimations by international organizations, the external dose during the first year accounts for a significant part of the long-term dose. Thus, the present study was intended to estimate the first-year doses by extrapolating the Basic Survey results. METHODS: For most municipalities of non-evacuated areas, ambient dose rate had been continuously measured for at least one designated point in each municipality after the accident. In the present study, a municipality-average dose received by residents for a period was assumed to be proportional to the ambient dose measured at the designated point of that municipality during the same period. Based on this assumption, 4-month municipality-average doses calculated from the Basic Survey results were extrapolated to obtain first-year doses. RESULTS: The extrapolated first-year doses for 49 municipalities in the non-evacuated areas had a good correlation with those estimated by UNSCEAR, although the extrapolated doses were generally higher (slope of the regression line: 1.23). The extrapolated municipality-average doses were in reasonable agreement (within 30%) with personal dosimeter measurements, suggesting that the extrapolation was reasonable. CONCLUSION: The present paper reports the first 4-month average doses for all 59 municipalities of Fukushima Prefecture and the extrapolated first-year doses for 49 municipalities. The extrapolated doses will be the basis for future epidemiological studies related to the FHMS.

Achievements and Current Status of the Fukushima Health Management Survey.

The Fukushima Health Management Survey (FHMS) was established in response to the Fukushima Daiichi Nuclear Power Plant accident on March 11, 2011. The primary objectives of the study are to monitor residents' long-term health and promote their future well-being, and to determine the health effects of long-term low-dose radiation exposure. This special issue summarizes the results and current status of the FHMS and discusses the challenges and future directions of the FHMS. The FHMS, a cohort study of all people who were residents in Fukushima Prefecture at the time of the accident, consists of a Basic Survey, Thyroid Ultrasound Examination, Comprehensive Health Check, Mental Health and Lifestyle Survey, and Pregnancy and Birth Survey. The radiation exposure was estimated based on the behavioral records examined using the Basic Survey. Although the response rate was low in the Basic Survey, the representativeness of the radiation exposure data was confirmed using additional surveys. There appears to be no relationship between the radiation exposure and risk of thyroid cancer, although more thyroid cancer cases were detected than initially expected. The ongoing Comprehensive Health Check and Mental Health and Lifestyle Survey have provided evidence of worsening physical and mental health status. The Pregnancy and Birth Survey showed rates of preterm delivery, low birth weight, and congenital abnormalities similar to the national average. Considering the above evidence, the Fukushima Prefectural Government decided to end the Pregnancy and Birth Survey at the end of March 2021, as recommended by the Prefectural Oversight Committee. The framework of the FHMS has not changed, but the FHMS needs to adapt according to the survey results and the changing needs of the eligible residents and municipalities.

Effects of External Radiation Exposure Resulting From the Fukushima Daiichi Nuclear Power Plant Accident on the Health of Residents in the Evacuation Zones: the Fukushima Health Management Survey.

BACKGROUND: Associations have been reported between lifestyle-related diseases and evacuation after the Great East Japan Earthquake (GEJE). However, the relationship between lifestyle-related diseases and the effective radiation dose due to external exposure (EDEE) after the GEJE remains unclear. METHODS: From among 72,869 residents of Fukushima Prefecture (31,982 men; 40,887 women) who underwent a comprehensive health check in fiscal year (FY) 2011, the data of 54,087 residents (22,599 men; 31,488 women) aged 16 to 84 years were analyzed. The EDEE data of 25,685 residents with incomplete results from the basic survey, performed to estimate the external radiation exposure dose, were supplemented using multiple imputation. The data were classified into three groups based on EDEE (0 to <1, 1 to <2, and ≥2 mSv groups and associations between the incidence of diseases and EDEE from FY2011 to FY2017 were examined using a Cox proportional hazards model, with FY2011 as the baseline. RESULTS: A higher EDEE was associated with a greater incidence of hypertension, diabetes mellitus, dyslipidemia, hyperuricemia, liver dysfunction, and polycythemia from FY2011 to FY2017 in the age- and sex-adjusted model. However, after further adjustment for evacuation status and lifestyle-related factors, the significant associations disappeared. No association was found between EDEE and other lifestyle-related diseases. CONCLUSION: EDEE was not directly associated with the incidence of lifestyle-related diseases after the GEJE. However, residents with higher external radiation doses in Fukushima Prefecture might suffer from lifestyle-related diseases related to evacuation and the resultant lifestyle changes.

Associations Between External Radiation Doses and the Risk of Psychological Distress or Post-traumatic Stress After the Fukushima Daiichi Nuclear Power Plant Accident: the Fukushima Health Management Survey.

BACKGROUND: The relationship between radiation levels and mental health status after a nuclear disaster is unknown. We examined the association between individual external radiation doses and psychological distress or post-traumatic stress after the Fukushima Daiichi nuclear power plant accident in March 2011 in Japan. METHODS: The Mental Health and Lifestyle Survey was conducted from January 2012. Based on the estimated external radiation doses for the first 4 months, a total of 64,184 subjects were classified into <1 mSv, 1 to <2 mSv, and ≥2 mSv groups. Odds ratios (ORs) and 95% confidence intervals (CIs) of psychological distress and post-traumatic stress, with the <1 mSv group as the reference, were calculated using logistic regression analysis adjusted for age, sex, evacuation, perception of radiation risk, and subjective health status. RESULTS: The prevalence of psychological distress/post-traumatic stress in the <1 mSv, 1 to <2 mSv, and ≥2 mSv groups was 15.1%/22.1%, 14.0%/20.1%, and 15.0%/21.7%, respectively. In women, although the ≥2 mSv group tended to have a higher risk of psychological distress with the age-adjusted OR of 1.13 (95% CI, 0.99-1.30), the adjusted OR decreased to 1.00 (95% CI, 0.86-1.16) after controlling for all variables. On the other hand, there were no dose-dependent associations between radiation dose and post-traumatic stress. CONCLUSION: Although external radiation doses were not associated with psychological distress, evacuation and perception of radiation risk may increase the risk of psychological distress in women in the higher dose group.

Proteogenomic landscape and clinical characterization of GH-producing pituitary adenomas/somatotroph pituitary neuroendocrine tumors.

The clinical characteristics of growth hormone (GH)-producing pituitary adenomas/somatotroph pituitary neuroendocrine tumors (GHomas/somatotroph PitNETs) vary across patients. In this study, we aimed to integrate the genetic alterations, protein expression profiles, transcriptomes, and clinical characteristics of GHomas/somatotroph PitNETs to identify molecules associated with acromegaly characteristics. Targeted capture sequencing and copy number analysis of 36 genes and nontargeted proteomics analysis were performed on fresh-frozen samples from 121 sporadic GHomas/somatotroph PitNETs. Targeted capture sequencing revealed GNAS as the only driver gene, as previously reported. Classification by consensus clustering using both RNA sequencing and proteomics revealed many similarities between the proteome and the transcriptome. Gene ontology analysis was performed for differentially expressed proteins between wild-type and mutant GNAS samples identified by nontargeted proteomics and involved in G protein-coupled receptor (GPCR) pathways. The results suggested that GNAS mutations impact endocrinological features in acromegaly through GPCR pathway induction. ATP2A2 and ARID5B correlated with the GH change rate in the octreotide loading test, and WWC3, SERINC1, and ZFAND3 correlated with the tumor volume change rate after somatostatin analog treatment. These results identified a biological connection between GNAS mutations and the clinical and biochemical characteristics of acromegaly, revealing molecules associated with acromegaly that may affect medical treatment efficacy.