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.

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.

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.

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.

Antenatal screening timeline and cutoff scores of the Edinburgh Postnatal Depression Scale for predicting postpartum depressive symptoms in healthy women: a prospective cohort study.

BACKGROUND: It is worthwhile to identify women at risk of developing postpartum depression during pregnancy. This study aimed to determine the optimal time and cutoff score for antenatal screening for prediction of postpartum depressive symptoms (PDS) using the Edinburgh Postnatal Depression Scale (EPDS) and to identify risk factors for PDS. METHODS: The target population was healthy pregnant women receiving antenatal care at a university hospital in Tokyo, Japan. During the first, second, and third trimesters, 3-4 days postpartum, and one month postpartum, they were asked to take the Japanese version of the EPDS questionnaire. The primary outcome of the study was PDS, defined as an EPDS score ≥ 9 at one month postpartum. The area under the receiver operating characteristics curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of EPDS scores at each antenatal screening time were calculated. RESULTS: From 139 pregnant women, 129 were successfully followed up throughout the study. The number of women with an EPDS score ≥ 9 during the first, second, and third trimesters, 3-4 days postpartum, and one month postpartum were 6/126 (4.8%), 9/124 (7.3%), 5/117 (4.3%), 17/123 (13.8%), and 15/123 (12.2%), respectively. Screening during the second trimester had the highest AUC to predict PDS (0.89) among antenatal screenings. The optimal EPDS cutoff score during the second trimester was 4/5 (sensitivity: 85.7%; specificity: 77.1%; PPV: 33.3%; NPV: 97.6%). An EPDS score ≥ 5 during the second trimester (adjusted odds ratio [aOR]: 15.9; 95% confidence interval [95%CI]: 3.2-78.1) and a family history of mental illness (aOR: 4.5; 95%CI: 1.2-17.5) were significantly associated with PDS. CONCLUSIONS: Our study suggests that the EPDS score at the second trimester with the cutoff value of 4/5 may be adequate for initial screening for prediction of PDS. Women with an EPDS score ≥ 5 at the second trimester require more elaborate follow-up.

External Radiation Dose, Obesity, and Risk of Childhood Thyroid Cancer After the Fukushima Daiichi Nuclear Power Plant Accident: The Fukushima Health Management Survey.

BACKGROUND: The 2011 Great East Japan Earthquake led to a nuclear accident at Fukushima Daiichi Nuclear Power Plant. This study examines the associations of radiation dose and lifestyle factors with incidence of thyroid cancer in Fukushima. METHODS: We designed a prospective study with 300,473 participants aged 18 years or younger, who underwent thyroid examinations from October 2011. Follow-up surveys were conducted through June 2017, and 245,530 participants (123,480 men and 122,050 women, 82% follow-up) received follow-up examinations. Fukushima Prefecture was divided into five areas based on individual external radiation dose. We calculated relative risks and 95% confidence intervals (CIs) for thyroid cancer in each area, with area of lowest dose as reference, using age-adjusted Poisson regression models. We also calculated risks associated with overweight and obesity. RESULTS: The incidence per 100,000 for Groups A (highest dose), B, C, D, and E (lowest dose) were 13.5, 19.2, 17.3, 9.0, and 8.3, respectively. Compared with Group E, the age-adjusted risks (95% CIs) were 1.62 (0.59, 4.47) for group A, 2.32 (0.86, 6.24) for group B, 2.21 (0.82, 5.94) for group C, and 1.02 (0.36, 2.86) for group D. Obesity was positively associated with thyroid cancer incidence; the multivariable-adjusted risk of thyroid cancer was 2.23 (1.01, 4.90) for obese individuals compared with nonobese individuals. CONCLUSION: Regional differences in radiation dose were not associated with increased risk of thyroid cancer among children in Fukushima within 4 to 6 years after the nuclear power plant accident. Obesity may be an important factor for further follow-up in Fukushima.

Trends in the Incidence of Sudden Deaths and Heart Diseases in Fukushima After the Great East Japan Earthquake.

On March 11, 2011, a great earthquake, known as the Great East Japan Earthquake, hit northeastern Japan, resulting in a tsunami that caused a nuclear disaster, the Fukushima Daiichi Nuclear Power Plant accident, forcing about 160,000 people to evacuate. We, therefore, sought to examine the effects of this evacuation on the onset of cardiovascular diseases and sudden death (SD) in Fukushima Prefecture, three years after the earthquake. We divided the evacuation zone into two areas, whole evacuation zone (Area 1) and partial evacuation zone (Area 2), and we defined the north district of the prefecture as the control area (Area 3). We cross-referenced the death certificate data with data from the Fukushima Prefecture acute myocardial infarction registration survey. For each area, we tallied the number of people who fell into the SD, myocardial infarction (MI), and MI suspected groups. We calculated the age-adjusted incidence rates and analyzed the differences in the adjusted incidence rates across three years using a Poisson regression model. The age-adjusted death rate of the SD group was significantly higher in 2011 in all areas than in 2012 or 2013 (P < 0.05). The total death rate was higher in Area 1 in March 2011, just after the disaster, than in the other two areas. The rate of SD was also higher in Area 1 than in the other areas in March 2011. The incidence of sudden cardiac death might have increased just after the Great East Japan Earthquake in the evacuation area, but not in other areas in Fukushima Prefecture.

Errata: Internal doses from radionuclides and their health effects following the Fukushima accident (J. Radiol. Prot. 2018 38 1253-68).

This article presents errata on a published article.

Internal doses from radionuclides and their health effects following the Fukushima accident.

This paper presents an overview of current internal dose estimates from the Fukushima accident, potential population specific uncertainties in these estimates are investigated, along with the relative effects of internal and external exposures. Thyroid doses were largely due to 131I, but variations in thyroid weight and fractional uptake and retention times of 131I in the thyroid contribute to uncertainties in thyroid dose estimates. Lower values for these parameters in the Japanese population, as compared to international reference assumptions, would lead to underestimation of doses on the basis of reference thyroid weights and overestimation of doses using reference thyroid uptake and retention times. Any overall bias in thyroidal doses due to population specific factors is the net result of the balance between these effects. Internal doses to other organs are largely due to 134Cs and 137Cs and their whole body distribution, population specific differences in these dose estimates are driven by average body mass, due to the inverse relationship between this and retention times. Potential differences in dose estimates and any inferred risks, due to local population specific factors, may be less than a factor of two for children and male adults, but the potential difference may be slightly underestimated for female adults. Recent micro-dosimetric studies have confirmed the existing perception that risk from internal exposures to 137Cs, 134Cs, and 131I should be nearly equivalent to that from external exposure to gamma rays at the same absorbed dose. Epidemiological studies provide comparisons between external and internal exposures to 131I in children and suggest that effects of internal exposure are similar to those of external exposure. Effective dose has been formulated to harmonise internal and external exposure risks for radiation protection purposes. On the basis of this review, the use of effective dose in this context does not seem to be unreasonable.

Representativeness of individual external doses estimated for one quarter of residents in the Fukushima Prefecture after the nuclear disaster: the Fukushima Health Management Survey.

After the Fukushima Dai-ichi Nuclear Power Plant accident, the Fukushima Health Management Survey (FHMS) was launched. The Basic Survey, a component of FHMS, is a questionnaire used to survey residents across the Fukushima Prefecture about their behaviour in the first 4 months after the accident. The questionnaire findings are used to determine individual external doses by linking behaviour data to a computer programme with daily gamma ray dose rate maps, drawn after the accident. Through 30 June 2015, the response rate was only 27.2% (558 550 population), indicating that the findings might not be generalisable because of poor representativeness of the population. The objective of this study was to clarify if the data from the FHMS Basic Survey were representative of the entire population, by conducting a new survey to compare the external doses between non-respondents and respondents in the previous survey. A total of 5350 subjects were randomly selected from 7 local regions of Fukushima Prefecture. An interview survey was conducted with the non-respondents to the FHMS Basic Survey. A total of 990 responses were obtained from the previous non-responders by interview survey. For the regions Kempoku, Kenchu, Kennan, Aizu, Minami-Aizu, Soso, and Iwaki, differences in mean effective dose (95% confidence interval) in mSv between the non-responders and previous responders were 0.12 (0.01-0.23), -0.09 (-0.21-0.03), -0.06 (-0.18-0.07), 0.05 (-0.04-0.14), 0.01 (-0.01-0.02), 0.09 (0.01-0.17), 0.09 (0.00-0.17), respectively. The differences fall neither within the interval (-∞, -0.25) nor within the interval (0.25, ∞). These findings imply that mean effective doses between the previous and new respondents were not different, with a significantly indifferent region of 0.25 mSv according to equivalence tests. The present study indicates that the dose distribution obtained from about one-quarter of Fukushima residents represents the dose distribution for the entire Fukushima Prefecture.

Radiation dose due to radon and thoron progeny inhalation in high-level natural radiation areas of Kerala, India.

In order to evaluate internal exposure to radon and thoron, concentrations for radon, thoron, and thoron progeny were measured for 259 dwellings located in high background radiation areas (HBRAs, outdoor external dose: 3-5 mGy y-1) and low background radiation areas (control areas, outdoor external dose: 1 mGy y-1) in Karunagappally Taluk, Kerala, India. The measurements were conducted using passive-type radon-thoron detectors and thoron progeny detectors over two six-month measurement periods from June 2010 to June 2011. The results showed no major differences in radon and thoron progeny concentrations between the HBRAs and the control areas. The geometric mean of the annual effective dose due to radon and thoron was calculated as 0.10 and 0.44 mSv, respectively. The doses were small, but not negligible compared with the external dose in the two areas.

Health effects of radiation and other health problems in the aftermath of nuclear accidents, with an emphasis on Fukushima.

437 nuclear power plants are in operation at present around the world to meet increasing energy demands. Unfortunately, five major nuclear accidents have occurred in the past--ie, at Kyshtym (Russia [then USSR], 1957), Windscale Piles (UK, 1957), Three Mile Island (USA, 1979), Chernobyl (Ukraine [then USSR], 1986), and Fukushima (Japan, 2011). The effects of these accidents on individuals and societies are diverse and enduring. Accumulated evidence about radiation health effects on atomic bomb survivors and other radiation-exposed people has formed the basis for national and international regulations about radiation protection. However, past experiences suggest that common issues were not necessarily physical health problems directly attributable to radiation exposure, but rather psychological and social effects. Additionally, evacuation and long-term displacement created severe health-care problems for the most vulnerable people, such as hospital inpatients and elderly people.

An influential factor for external radiation dose estimation for residents after the Fukushima Daiichi Nuclear Power Plant accident-time spent outdoors for residents in Iitate Village.

Many studies have been conducted on radiation doses to residents after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. Time spent outdoors is an influential factor for external dose estimation. Since little information was available on actual time spent outdoors for residents, different values of average time spent outdoors per day have been used in dose estimation studies on the FDNPP accident. The most conservative value of 24 h was sometimes used, while 2.4 h was adopted for indoor workers in the UNSCEAR 2013 report. Fukushima Medical University has been estimating individual external doses received by residents as a part of the Fukushima Health Management Survey by collecting information on the records of moves and activities (the Basic Survey) after the accident from each resident. In the present study, these records were analyzed to estimate an average time spent outdoors per day. As an example, in Iitate Village, its arithmetic mean was 2.08 h (95% CI: 1.64-2.51) for a total of 170 persons selected from respondents to the Basic Survey. This is a much smaller value than commonly assumed. When 2.08 h is used for the external dose estimation, the dose is about 25% (23-26% when using the above 95% CI) less compared with the dose estimated for the commonly used value of 8 h.

Meeting report: suggestions for studies on future health risks following the Fukushima accident.

In October 2013, the Radiation Medical Science Center of the Fukushima Medical University and the Section of Environment and Radiation of the International Agency for Research on Cancer held a joint workshop in Fukushima, Japan to discuss opportunities and challenges for long-term studies of the health effects following the March 2011 Fukushima Daiichi Nuclear Power Plant Accident. This report describes four key areas of discussion -- thyroid screening, dosimetry, mental health, and non-radiation risk factors -- and summarizes recommendations resulting from the workshop. Four recommendations given at the workshop were to: 1) build-up a population-based cancer registry for long-term monitoring of the cancer burden in the prefecture; 2) enable future linkage of data from the various independent activities, particularly those related to dose reconstruction and health status ascertainment; 3) establish long-term observational studies with repeated measurements of lifestyle and behavioural factors to disentangle radiation and non-radiation factors; and 4) implement primary prevention strategies targeted for populations affected by natural disasters, including measures to better understand and address health risk concerns in the affected population. The workshop concluded that coordinated data collection between researchers from different institutes and disciplines can both reduce the burden on the population and facilitate efforts to examine the inter-relationships between the many factors at play.

Simultaneous sampling of indoor and outdoor airborne radioactivity after the Fukushima Daiichi nuclear power plant accident.

Several studies have estimated inhalation doses for the public because of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. Most of them were based on measurement of radioactivity in outdoor air and included the assumption that people stayed outdoors all day. Although this assumption gives a conservative estimate, it is not realistic. The "air decontamination factor" (ratio of indoor to outdoor air radionuclide concentrations) was estimated from simultaneous sampling of radioactivity in both inside and outside air of one building. The building was a workplace and located at the National Institute of Radiological Sciences (NIRS) in Chiba Prefecture, Japan. Aerosol-associated radioactive materials in air were collected onto filters, and the filters were analyzed by γ spectrometry at NIRS. The filter sampling was started on March 15, 2011 and was continued for more than 1 year. Several radionuclides, such as (131)I, (134)Cs, and (137)Cs were found by measuring the filters with a germanium detector. The air decontamination factor was around 0.64 for particulate (131)I and 0.58 for (137)Cs. These values could give implications for the ratio of indoor to outdoor radionuclide concentrations after the FDNPP accident for a similar type of building.

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.

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.