Precision for binary measurement methods and results under beta-binomial distributions

To handle typical problems from fields dealing with biological responses, this study develops a new statistical model and method for analysing the precision of binary measurement methods and results from collaborative studies. The model is based on beta-binomial distributions. In other words, we assume that the sensitivity of each laboratory obeys a beta distribution and the binary measurement results under a given sensitivity follow a binomial distribution. We propose the key precision indicators of repeatability and reproducibility for the model and derive their unbiased estimates. We further propose a confidence interval for repeatability by applying the Jeffreys interval, which utilizes the assumption of beta distributions for sensitivity. Moreover, we propose a statistical test for determining laboratory effects, using simultaneous confidence intervals based on the confidence interval of each laboratory's sensitivity. Finally, we apply the proposed method to real-world examples in the fields of food safety and chemical risk assessment and management

Tea Polyphenols Regulate Key Mediators on Inflammatory Cardiovascular Diseases

Tea polyphenols known as catechins are key components with many biological functions, including anti-inflammatory, antioxidative, and anticarcinogenic effects. These effects are induced by the suppression of several inflammatory factors including nuclear factor-kappa B (NF-κB). While these characteristics of catechins have been well documented, actions of catechins as mediators on inflammation-related cardiovascular diseases have not yet been well investigated. In this article, we reviewed recent papers to reveal the anti-inflammatory effects of catechins in cardiovascular diseases. In our laboratory, we performed oral administration of catechins into murine and rat models of cardiac transplantation, myocarditis, myocardial ischemia, and atherosclerosis to reveal the effects of catechins on the inflammation-induced ventricular and arterial remodeling. From our results, catechins are potent agents for the treatment and prevention of inflammation-related cardiovascular diseases because they are critically involved in the suppression of proinflammatory signaling pathways

Nucleic Acid Drugs for Prevention of Cardiac Rejection

Heart transplantation has been broadly performed in humans. However, occurrence of acute and chronic rejection has not yet been resolved. Several inflammatory factors, such as cytokines and adhesion molecules, enhance the rejection. The graft arterial disease (GAD), which is a type of chronic rejection, is characterized by intimal thickening comprised of proliferative smooth muscle cells. Specific treatments that target the attenuation of acute rejection and GAD formation have not been well studied in cardiac transplantation. Recent progress in the nucleic acid drugs, such as antisense oligodeoxynucleotides (ODNs) to regulate the transcription of disease-related genes, has important roles in therapeutic applications. Transfection of cis-element double-stranded DNA, named as “decoy,” has been also reported to be a useful nucleic acid drug. This decoy strategy has been not only a useful method for the experimental studies of gene regulation but also a novel clinical strategy. In this paper, we reviewed the experimental results of NF-κB, E2F, AP-1, and STAT-1 decoy and other ODNs using the experimental heart transplant models

Hysteretic Tricolor Electrochromic Systems Based on the Dynamic Redox Properties of Unsymmetrically Substituted Dihydrophenanthrenes and Biphenyl-2,2 '-Diyl Dications: Efficient Precursor Synthesis by a Flow Microreactor Method

A series of biphenyl-2, 2'-diylbis(diarylmethanol)s 3, which have two kinds of aryl groups at the bay region, were efficiently obtained by integrated flow microreactor synthesis. The diols 3NO/NX are the precursors of unsymmetric biphenylic dications 2NO/NX^[2+] which are transformed into the corresponding dihydrophenanthrenes 1NO/NX via 2NO/NX^[+•] upon reduction, when they exhibit two-stage color changes. On the other hand, the steady-state concentration of the intermediate 2NO/NX^[+•] is negligible during the oxidation of 1NO/NX to 2NO/NX^[2+], which reflects unique tricolor electrochromicity with a hysteretic pattern of color change [color 1→color 2→color 3→color 1]

Analysis of the long-range random field quantum antiferromagnetic Ising model

We introduce a solvable quantum antiferromagnetic model. The model, with Ising spins in a transverse field, has infinite range antiferromagnetic interactions with random fields on each site, following an arbitrary distribution. As is well-known, frustration in the random field Ising model gives rise to a many-valley structure in the spin-configuration space. In addition, the antiferromagnetism also induces a regular frustration even for the ground state. In this paper, we investigate analytically the critical phenomena in the model, having both randomness and frustration and we report some analytical results for it.Comment: 18 pages, 5 figures, Euro. Phys. J B (to be published

Immunological quantitation of tyrosinase from wild-type and albino mutant mice

AbstractThe relationship between gene dosage, enzyme activity, and level of immunologically cross-reacting material (CRM) was examined in mammalian tyrosinase (EC 1.14.18.1) by rocket immunoelectrophoresis. Skin extracts from mice heterozygous (C/c) and homozygous (c/c) for the albino locus contain 46% and 0% of CRM, respectively, as compared with wild-type (C/C) animals. Enzyme activity and CRM level were directly proportional in these genotypes, suggesting that the albino locus controls the quantity of tyrosinase produced in melanocytes

Spatial-photonic Boltzmann machines: low-rank combinatorial optimization and statistical learning by spatial light modulation

The spatial-photonic Ising machine (SPIM) [D. Pierangeli et al., Phys. Rev. Lett. 122, 213902 (2019)] is a promising optical architecture utilizing spatial light modulation for solving large-scale combinatorial optimization problems efficiently. However, the SPIM can accommodate Ising problems with only rank-one interaction matrices, which limits its applicability to various real-world problems. In this Letter, we propose a new computing model for the SPIM that can accommodate any Ising problem without changing its optical implementation. The proposed model is particularly efficient for Ising problems with low-rank interaction matrices, such as knapsack problems. Moreover, the model acquires learning ability and can thus be termed a spatial-photonic Boltzmann machine (SPBM). We demonstrate that learning, classification, and sampling of the MNIST handwritten digit images are achieved efficiently using SPBMs with low-rank interactions. Thus, the proposed SPBM model exhibits higher practical applicability to various problems of combinatorial optimization and statistical learning, without losing the scalability inherent in the SPIM architecture.Comment: 7 pages, 5 figures (with a 3-page supplemental