Seasonal variations of the prevalence of metabolic syndrome and its markers using big-data of health check-ups.

BACKGROUND: It is crucial to understand the seasonal variation of Metabolic Syndrome (MetS) for the detection and management of MetS. Previous studies have demonstrated the seasonal variations in MetS prevalence and its markers, but their methods are not robust. To clarify the concrete seasonal variations in the MetS prevalence and its markers, we utilized a powerful method called Seasonal Trend Decomposition Procedure based on LOESS (STL) and a big dataset of health checkups. METHODS: A total of 1,819,214 records of health checkups (759,839 records for men and 1,059,375 records for women) between April 2012 and December 2017 were included in this study. We examined the seasonal variations in the MetS prevalence and its markers using 5 years and 9 months health checkup data and STL analysis. MetS markers consisted of waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG). RESULTS: We found that the MetS prevalence was high in winter and somewhat high in August. Among men, MetS prevalence was 2.64 ± 0.42 (mean ± SD) % higher in the highest month (January) than in the lowest month (June). Among women, MetS prevalence was 0.53 ± 0.24% higher in the highest month (January) than in the lowest month (June). Additionally, SBP, DBP, and HDL-C exhibited simple variations, being higher in winter and lower in summer, while WC, TG, and FPG displayed more complex variations. CONCLUSIONS: This finding, complex seasonal variations of MetS prevalence, WC, TG, and FPG, could not be derived from previous studies using just the mean values in spring, summer, autumn and winter or the cosinor analysis. More attention should be paid to factors affecting seasonal variations of central obesity, dyslipidemia and insulin resistance.

Mathematical Model for Evaluation of Tumor Response in Targeted Radionuclide Therapy with 211At Using Implanted Mouse Tumor.

Recent introduction of alpha-emitting radionuclides in targeted radionuclide therapy has stimulated the development of new radiopharmaceuticals. Preclinical evaluation using an animal experiment with an implanted tumor model is frequently used to examine the efficiency of the treatment method and to predict the treatment response before clinical trials. Here, we propose a mathematical model for evaluation of the tumor response in an implanted tumor model and apply it to the data obtained from the previous experiment of 211At treatment in a thyroid cancer mouse model. The proposed model is based on the set of differential equations, describing the kinetics of radiopharmaceuticals, the tumor growth, and the treatment response. First, the tumor growth rate was estimated from the control data without injection of 211At. The kinetic behavior of the injected radionuclide was used to estimate the radiation dose profile to the target tumor, which can suppress the tumor growth in a dose-dependent manner. An additional two factors, including the time delay for the reduction of tumor volume and the impaired recovery of tumor regrowth after the treatment, were needed to simulate the temporal changes of tumor size after treatment. Finally, the parameters obtained from the simulated tumor growth curve were able to predict the tumor response in other experimental settings. The model can provide valuable information for planning the administration dose of radiopharmaceuticals in clinical trials, especially to determine the starting dose at which efficacy can be expected with a sufficient safety margin.

Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data.

We sought to verify the reliability of machine learning (ML) in developing diabetes prediction models by utilizing big data. To this end, we compared the reliability of gradient boosting decision tree (GBDT) and logistic regression (LR) models using data obtained from the Kokuho-database of the Osaka prefecture, Japan. To develop the models, we focused on 16 predictors from health checkup data from April 2013 to December 2014. A total of 277,651 eligible participants were studied. The prediction models were developed using a light gradient boosting machine (LightGBM), which is an effective GBDT implementation algorithm, and LR. Their reliabilities were measured based on expected calibration error (ECE), negative log-likelihood (Logloss), and reliability diagrams. Similarly, their classification accuracies were measured in the area under the curve (AUC). We further analyzed their reliabilities while changing the sample size for training. Among the 277,651 participants, 15,900 (7978 males and 7922 females) were newly diagnosed with diabetes within 3 years. LightGBM (LR) achieved an ECE of 0.0018 ± 0.00033 (0.0048 ± 0.00058), a Logloss of 0.167 ± 0.00062 (0.172 ± 0.00090), and an AUC of 0.844 ± 0.0025 (0.826 ± 0.0035). From sample size analysis, the reliability of LightGBM became higher than LR when the sample size increased more than [Formula: see text]. Thus, we confirmed that GBDT provides a more reliable model than that of LR in the development of diabetes prediction models using big data. ML could potentially produce a highly reliable diabetes prediction model, a helpful tool for improving lifestyle and preventing diabetes.

Associations of kidney tests at medical facilities and health checkups with incidence of end-stage kidney disease: a retrospective cohort study.

No study has assessed the association between no health checkup and end-stage kidney disease (ESKD). This retrospective cohort study, including 69,147 adults aged ≥ 40 years in Japan who were insured by the National Health Insurance and the Late-Stage Medical Care System for the Elderly, assessed the associations of kidney tests at medical facilities and health checkups with incident ESKD. The main exposure was the histories of kidney tests using dipstick urinalysis and/or serum creatinine measurement at medical facilities and checkups in the past year: "checkups," "no kidney test (without checkup)," and "kidney tests (without checkup)" groups. During the median observational period of 5.0 years, ESKD was observed in 246 (0.8%) men and 124 (0.3%) women. The "no kidney test" group was associated with ESKD in men (adjusted subhazard ratio of "no kidney test" vs. "checkups": 1.66 [95% confidence interval, 1.04-2.65], but not in women. Age-specific subgroup analyses identified the "no kidney test" group as a high-risk population of ESKD in elderly men (1.30 [0.70-2.41] and 2.72 [1.39-5.33] in men aged 40-74 and ≥ 75 years, respectively). Elderly men with no kidney test at medical facilities and no health checkup were at higher risk of ESKD.

EGFR-mediated epidermal stem cell motility drives skin regeneration through COL17A1 proteolysis.

Skin regenerative capacity declines with age, but the underlying mechanisms are largely unknown. Here we demonstrate a functional link between epidermal growth factor receptor (EGFR) signaling and type XVII collagen (COL17A1) proteolysis on age-associated alteration of keratinocyte stem cell dynamics in skin regeneration. Live-imaging and computer simulation experiments predicted that human keratinocyte stem cell motility is coupled with self-renewal and epidermal regeneration. Receptor tyrosine kinase array identified the age-associated decline of EGFR signaling in mouse skin wound healing. Culture experiments proved that EGFR activation drives human keratinocyte stem cell motility with increase of COL17A1 by inhibiting its proteolysis through the secretion of tissue inhibitor of metalloproteinases 1 (TIMP1). Intriguingly, COL17A1 directly regulated keratinocyte stem cell motility and collective cell migration by coordinating actin and keratin filament networks. We conclude that EGFR-COL17A1 axis-mediated keratinocyte stem cell motility drives epidermal regeneration, which provides a novel therapeutic approach for age-associated impaired skin regeneration.

The time domain numerical method of three-dimensional conductors including radiation with lumped parameter circuit.

We formulate a numerical method on the transmission and radiation theory of three-dimensional conductors starting from the Maxwell equations in the time domain. We include the delay effect in the integral equations for the scalar and vector potentials rigorously, which is vital to obtain numerically stable solutions for transmission and radiation phenomena in conductors. We provide a formalism to connect the conductors to any passive lumped-parameter circuits. We show one example of numerical calculations, demonstrating that the new formalism provides stable solutions to the transmission and radiation phenomena.

WAM to SeeSaw model for cancer therapy - overcoming LQM difficulties.

PURPOSE: The assessment of biological effects caused by radiation exposure has been currently carried out with the linear-quadratic (LQ) model as an extension of the linear non-threshold (LNT) model. In this study, we suggest a new mathematical model named as SeaSaw (SS) model, which describes proliferation and cell death effects by taking account of Bergonie-Tribondeau's law in terms of a differential equation in time. We show how this model overcomes the long-standing difficulties of the LQ model. MATERIALS AND METHODS: We construct the SS model as an extended Wack-A-Mole (WAM) model by using a differential equation with respect to time in order to express the dynamics of the proliferation effect. A large number of accumulated data of such parameters as α and ß in the LQ based models provide us with valuable pieces of information on the corresponding parameter b1 and the maximum volume Vm of the SS model. The dose rate b1 and the notion of active cell can explain the present data without introduction of ß, which is obtained by comparing the SS model with not only the cancer therapy data but also with in vitro experimental data. Numerical calculations are presented to grasp the global features of the SS model. RESULTS: The SS model predicts the time dependence of the number of active- and inactive-cells. The SS model clarifies how the effect of radiation depends on the cancer stage at the starting time in the treatment. Further, the time dependence of the tumor volume is calculated by changing individual dose strength, which results in the change of the irradiation duration for the same effect. We can consider continuous irradiation in the SS model with interesting outcome on the time dependence of the tumor volume for various dose rates. Especially by choosing the value of the dose rate to be balanced with the total growth rate, the tumor volume is kept constant. CONCLUSIONS: The SS model gives a simple equation to study the situation of clinical radiation therapy and risk estimation of radiation. The radiation parameter extracted from the cancer therapy is close to the value obtained from animal experiment in vitro and in vivo. We expect the SS model leads us to a unified description of radiation therapy and protection and provides a great development in cancer-therapy clinical-planning.

Causal relations of health indices inferred statistically using the DirectLiNGAM algorithm from big data of Osaka prefecture health checkups.

Causal relations among many statistical variables have been assessed using a Linear non-Gaussian Acyclic Model (LiNGAM). Using access to large amounts of health checkup data from Osaka prefecture obtained during the six fiscal years of years 2012-2017, we applied the DirectLiNGAM algorithm as a trial to extract causal relations among health indices for age groups and genders. Results show that LiNGAM yields interesting and reasonable results, suggesting causal relations and correlation among the statistical indices used for these analyses.

Time-domain Formulation of a Multi-layer Plane Circuit Coupled with Lumped-parameter Circuits using Maxwell Equations.

We calculate electromagnetic phenomena in the multi-layer plane circuit starting from the Maxwell equations. We present a numerical method of potential and current density in two-dimensional conductors, where their time developments are treated as phenomena of wave propagation. We treat the plane conductors by dividing them into small finite-volume elements, similar to the case of the partial element equivalent circuit method, and the transport equations are then solved by the finite-difference time-domain method. Furthermore, we develop a calculation method for the boundary in a multi-layer plane by applying the method we have used in multi-transmission lines. We formulate the boundary conditions of a multi-layer plane coupled with lumped-parameter circuits and introduce an algorithm to reduce calculation costs that are largely associated with the two-dimensional extension from the multi-transmission-line case. We perform calculations of the wave propagation of potential, current density, and charge density in the time domain for a simple plane circuit. These calculations are presented as supplementary materials of the present paper.

Mechanism of Common-mode Noise Generation in Multi-conductor Transmission Lines.

The mechanism of common-mode noise generation in multi-conductor transmission lines is presented. Telegraphic equations, wave equations, and reflection coefficients in the normal and common modes are derived, which provide the mechanism of common-mode noise generation. In addition to coupling among transmission lines, the origin of the common-mode noise generation is elucidated by deriving the reflection coefficients in the normal and common modes.

Study of mutation from DNA to biological evolution.

Purpose: This is a paper based on a talk given in the BER2018 conference by M. Bando. We first emphasize the importance of collaborations among scientists in various fields for the low dose/dose-rate effects on biological body. We make comparisons of quantitative estimations of mutation caused by the radiation exposure on various animals and plants using one mathematical model. We derive the importance of the spontaneous mutation at the DNA level, which provides the key to understand the biological evolution. We try to make a guide map to solve this problem and find that the mutation is an important stage of the pathway from the DNA damage to the macroscopic biological evolution. Materials and methods: We construct a mathematical model for the mutation, named as 'WAM' model, which takes into account the recovery effect. The model setting is regarded as an extension of the survival and the hazard functions. The WAM model is used to reproduce accumulated data of mutation frequency of animals and plants. Especially the model analysis shows that the dose-rate dependence is important to understand various mutation data. Results and conclusions: The WAM model is successful in reproducing various mutation data of animals and plants. We find that the inclusion of the dose rate is important to understand all the mutation data. Hence, we are able to develop the 'scaling law' to make the cross-species comparison of mutation frequency data. With this finding, we can extract the dominant effect on the mutation to be caused by the spontaneous mutation, and quantify this amount. We are able to write then the artificial radiation frequency by subtracting the spontaneous mutation. With this success, we estimate the origin of the spontaneous mutation as due to ROS, the order of which agrees to the spontaneous mutation.

Theoretical Study of Lumped Parameter Circuits and Multiconductor Transmission Lines for Time-Domain Analysis of Electromagnetic Noise.

In order to find the origins of electromagnetic noise in the time domain, we formulate a system of lumped parameter circuits and multiconductor transmission lines (MTL). We present a discretized approach to treat any lumped parameter circuits and MTL systems, and the boundary conditions between these systems, where the lumped parameter circuits are described by coupled differential equations, and the MTL systems by coupled partial-differential equations. The introduction of the time-domain impedance and the element matrices enables us to perform a time-domain analysis that includes dependent sources and the coupling devices in the framework of the circuit theory. For three-line systems, we are able to calculate the coupling of the normal, common, and antenna modes, and to find out methods to reduce the noise.

Physics of epi-thermal boron neutron capture therapy (epi-thermal BNCT).

The physics of epi-thermal neutrons in the human body is discussed in the effort to clarify the nature of the unique radiologic properties of boron neutron capture therapy (BNCT). This discussion leads to the computational method of Monte Carlo simulation in BNCT. The method is discussed through two examples based on model phantoms. The physics is kept at an introductory level in the discussion in this tutorial review.

The properties of nuclear matter with lattice NN potential in relativistic Brueckner-Hartree-Fock theory.

We study the properties of nuclear matter with lattice nucleon-nucleon (NN) potential in the relativistic Brueckner-Hartree-Fock (RBHF) theory. To use this potential in such a microscopic many-body theory, we firstly have to construct a one-boson-exchange potential (OBEP) based on the latest lattice NN potential. Three mesons, pion, σ meson, and ω meson, are considered. Their coupling constants and cut-off momenta are determined by fitting the on-shell behaviors and phase shifts of the lattice force, respectively. Therefore, we obtain two parameter sets of the OBEP potential (named as LOBEP1 and LOBEP2) with these two fitting ways. We calculate the properties of symmetric and pure neutron matter with LOBEP1 and LOBEP2. In non-relativistic Brueckner-Hartree-Fock case, the binding energies of symmetric nuclear matter are around -3 and -5 MeV at saturation density, while it becomes -8 and -12 MeV in relativistic framework with 1S0, 3S1, and 3D1 channels using our two parameter sets. For the pure neutron matter, the equations of state in non-relativistic and relativistic cases are very similar due to only consideration 1S0 channel with isospin T = 1 case.

Cell motion predicts human epidermal stemness.

Image-based identification of cultured stem cells and noninvasive evaluation of their proliferative capacity advance cell therapy and stem cell research. Here we demonstrate that human keratinocyte stem cells can be identified in situ by analyzing cell motion during their cultivation. Modeling experiments suggested that the clonal type of cultured human clonogenic keratinocytes can be efficiently determined by analysis of early cell movement. Image analysis experiments demonstrated that keratinocyte stem cells indeed display a unique rotational movement that can be identified as early as the two-cell stage colony. We also demonstrate that α6 integrin is required for both rotational and collective cell motion. Our experiments provide, for the first time, strong evidence that cell motion and epidermal stemness are linked. We conclude that early identification of human keratinocyte stem cells by image analysis of cell movement is a valid parameter for quality control of cultured keratinocytes for transplantation.

New circuit theory of multiconductor transmission lines resulting from a new practice of noise reduction.

In modern life, we are surrounded by and filled with electromagnetic noise caused by the dominant use of energy in the form of electricity. This situation is brought about by the fact that the noise is not understood theoretically. A new practice of noise reduction was introduced for the construction of Heavy Ion Medical Accelerator in Chiba (HIMAC). The key concept is a symmetric three-line circuit that arranges power supplies, noise filters and magnets around a third central ground line. A continuous theoretical effort forced us to find a new circuit theory involving a multiconductor transmission-line system starting from Maxwell's equations without any approximation. We discuss the essence of all of these experimental and theoretical developments with the hope to remove unnecessary electromagnetic noise not only from power supplies, but also from all electric devices. The newly derived circuit theory of multiconductor transmission lines is universal, and establishes the validity of the practice of noise reduction.

Hair organ regeneration via the bioengineered hair follicular unit transplantation.

Organ regenerative therapy aims to reproduce fully functional organs to replace organs that have been lost or damaged as a result of disease, injury, or aging. For the fully functional regeneration of ectodermal organs, a concept has been proposed in which a bioengineered organ is developed by reproducing the embryonic processes of organogenesis. Here, we show that a bioengineered hair follicle germ, which was reconstituted with embryonic skin-derived epithelial and mesenchymal cells and ectopically transplanted, was able to develop histologically correct hair follicles. The bioengineered hair follicles properly connected to the host skin epithelium by intracutaneous transplantation and reproduced the stem cell niche and hair cycles. The bioengineered hair follicles also autonomously connected with nerves and the arrector pili muscle at the permanent region and exhibited piloerection ability. Our findings indicate that the bioengineered hair follicles could restore physiological hair functions and could be applicable to surgical treatments for alopecia.