Experimental investigation of pulsed entangled photons and photonic quantum channels

The development of key devices and systems in quantum information technology, such as entangled particle sources, quantum gates and quantum cryptographic systems, requires a reliable and well-established method for characterizing how well the devices or systems work. We report our recent work on experimental characterization of pulsed entangled photonic states and photonic quantum channels, using the methods of state and process tomography. By using state tomography, we could reliably evaluate the states generated from a two-photon source under development and develop a highly entangled pulsed photon source. We are also devoted to characterization of single-qubit and two-qubit photonic quantum channels. Characterization of typical single-qubit decoherence channels has been demonstrated using process tomography. Characterization of two-qubit channels, such as classically correlated channels and quantum mechanically correlated channels is under investigation. These characterization techniques for quantum states and quantum processes will be useful for developing photonic quantum devices and for improving their performances.Comment: 12 pages, 8 figures, in Quantum Optics in Computing and Communications, Songhao Liu, Guangcan Guo, Hoi-Kwong Lo, Nobuyuki Imoto, Eds., Proceedings of SPIE Vol. 4917, pp.13-24 (2002

Aflatoxins in Rice Artificially Contaminated with Aflatoxin-producing Aspergillus flavus under Natural Storage in Japan

Aflatoxin (AFT) contamination is frequent in foods grown in tropical regions, including rice. Although AFTs are generally not found in temperate-region foods, global warming has affected typical temperate-region climates, potentially permitting the contamination of foods with AFT-producing Aspergillus flavus (A. flavus). Here we investigated the AFT production in rice during storage under natural climate conditions in Japan. We examined AFTs in brown rice and rough rice artificially contaminated with A. flavus for 1 year in Japan, and we subjected AFTs in white rice to the same treatment in airtight containers and examined the samples in warm and cold seasons, simulating the storage of white rice in general households. In the brown rice, AFTs increased after 2 months (March) and peaked after 9 months (October). The AFT contamination in the rough rice was minimal. After the polishing and cooking of the brown rice, AFTs were undetectable. In the white rice stored in airtight containers, AFTs increased after 1 month (August) and peaked after 2 months (September). Minimal AFTs were detected in the cold season. Thus, AFT contamination in rice may occur in temperate regions following A. flavus contamination. The storage of rice as rough rice could provide be useful for avoiding AFT contamination

Jasmonate-dependent plant defense restricts thrips performance and preference

<p>Abstract</p> <p>Background</p> <p>The western flower thrips (<it>Frankliniella occidentalis </it>[Pergande]) is one of the most important insect herbivores of cultivated plants. However, no pesticide provides complete control of this species, and insecticide resistance has emerged around the world. We previously reported the important role of jasmonate (JA) in the plant's immediate response to thrips feeding by using an <it>Arabidopsis </it>leaf disc system. In this study, as the first step toward practical use of JA in thrips control, we analyzed the effect of JA-regulated <it>Arabidopsis </it>defense at the whole plant level on thrips behavior and life cycle at the population level over an extended period. We also studied the effectiveness of JA-regulated plant defense on thrips damage in Chinese cabbage (<it>Brassica rapa </it>subsp. <it>pekinensis</it>).</p> <p>Results</p> <p>Thrips oviposited more on <it>Arabidopsis </it>JA-insensitive <it>coi1-1 </it>mutants than on WT plants, and the population density of the following thrips generation increased on <it>coi1-1 </it>mutants. Moreover, thrips preferred <it>coi1-1 </it>mutants more than WT plants. Application of JA to WT plants before thrips attack decreased the thrips population. To analyze these important functions of JA in a brassica crop plant, we analyzed the expression of marker genes for JA response in <it>B. rapa</it>. Thrips feeding induced expression of these marker genes and significantly increased the JA content in <it>B. rapa</it>. Application of JA to <it>B. rapa </it>enhanced plant resistance to thrips, restricted oviposition, and reduced the population density of the following generation.</p> <p>Conclusion</p> <p>Our results indicate that the JA-regulated plant defense restricts thrips performance and preference, and plays an important role in the resistance of <it>Arabidopsis </it>and <it>B. rapa </it>to thrips damage.</p

Macrophage centripetal migration drives spontaneous healing process after spinal cord injury.

Traumatic spinal cord injury (SCI) brings numerous inflammatory cells, including macrophages, from the circulating blood to lesions, but pathophysiological impact resulting from spatiotemporal dynamics of macrophages is unknown. Here, we show that macrophages centripetally migrate toward the lesion epicenter after infiltrating into the wide range of spinal cord, depending on the gradient of chemoattractant C5a. However, macrophages lacking interferon regulatory factor 8 (IRF8) cannot migrate toward the epicenter and remain widely scattered in the injured cord with profound axonal loss and little remyelination, resulting in a poor functional outcome after SCI. Time-lapse imaging and P2X/YRs blockade revealed that macrophage migration via IRF8 was caused by purinergic receptors involved in the C5a-directed migration. Conversely, pharmacological promotion of IRF8 activation facilitated macrophage centripetal movement, thereby improving the SCI recovery. Our findings reveal the importance of macrophage centripetal migration via IRF8, providing a novel therapeutic target for central nervous system injury

Impact of functional studies on exome sequence variant interpretation in early-onset cardiac conduction system diseases

Aims The genetic cause of cardiac conduction system disease (CCSD) has not been fully elucidated. Whole-exome sequencing (WES) can detect various genetic variants; however, the identification of pathogenic variants remains a challenge. We aimed to identify pathogenic or likely pathogenic variants in CCSD patients by using WES and 2015 American College of Medical Genetics and Genomics (ACMG) standards and guidelines as well as evaluating the usefulness of functional studies for determining them. Methods and Results We performed WES of 23 probands diagnosed with early-onset (&amp;lt;65 years) CCSD and analyzed 117 genes linked to arrhythmogenic diseases or cardiomyopathies. We focused on rare variants (minor allele frequency &amp;lt; 0.1%) that were absent from population databases. Five probands had protein truncating variants in EMD and LMNA which were classified as “pathogenic” by 2015 ACMG standards and guidelines. To evaluate the functional changes brought about by these variants, we generated a knock-out zebrafish with CRISPR-mediated insertions or deletions of the EMD or LMNA homologs in zebrafish. The mean heart rate and conduction velocities in the CRISPR/Cas9-injected embryos and F2 generation embryos with homozygous deletions were significantly decreased. Twenty-one variants of uncertain significance were identified in 11 probands. Cellular electrophysiological study and in vivo zebrafish cardiac assay showed that 2 variants in KCNH2 and SCN5A, 4 variants in SCN10A, and 1 variant in MYH6 damaged each gene, which resulted in the change of the clinical significance of them from “Uncertain significance” to “Likely pathogenic” in 6 probands. Conclusions Of 23 CCSD probands, we successfully identified pathogenic or likely pathogenic variants in 11 probands (48%). Functional analyses of a cellular electrophysiological study and in vivo zebrafish cardiac assay might be useful for determining the pathogenicity of rare variants in patients with CCSD. SCN10A may be one of the major genes responsible for CCSD. Translational Perspective Whole-exome sequencing (WES) may be helpful in determining the causes of cardiac conduction system disease (CCSD), however, the identification of pathogenic variants remains a challenge. We performed WES of 23 probands diagnosed with early-onset CCSD, and identified 12 pathogenic or likely pathogenic variants in 11 of these probands (48%) according to the 2015 ACMG standards and guidelines. In this context, functional analyses of a cellular electrophysiological study and in vivo zebrafish cardiac assay might be useful for determining the pathogenicity of rare variants, and SCN10A may be one of the major development factors in CCSD

Random regression for modeling soybean plant response to irrigation changes using time-series multispectral data

Plant response to drought is an important yield-related trait under abiotic stress, but the method for measuring and modeling plant responses in a time series has not been fully established. The objective of this study was to develop a method to measure and model plant response to irrigation changes using time-series multispectral (MS) data. We evaluated 178 soybean (Glycine max (L.) Merr.) accessions under three irrigation treatments at the Arid Land Research Center, Tottori University, Japan in 2019, 2020 and 2021. The irrigation treatments included W5: watering for 5 d followed by no watering 5 d, W10: watering for 10 d followed by no watering 10 d, D10: no watering for 10 d followed by watering 10 d, and D: no watering. To capture the plant responses to irrigation changes, time-series MS data were collected by unmanned aerial vehicle during the irrigation/non-irrigation switch of each irrigation treatment. We built a random regression model (RRM) for each of combination of treatment by year using the time-series MS data. To test the accuracy of the information captured by RRM, we evaluated the coefficient of variation (CV) of fresh shoot weight of all accessions under a total of nine different drought conditions as an indicator of plant’s stability under drought stresses. We built a genomic prediction model (MTRRM model) using the genetic random regression coefficients of RRM as secondary traits and evaluated the accuracy of each model for predicting CV. In 2020 and 2021,the mean prediction accuracies of MTRRM models built in the changing irrigation treatments (r = 0.44 and 0.49, respectively) were higher than that in the continuous drought treatment (r = 0.34 and 0.44, respectively) in the same year. When the CV was predicted using the MTRRM model across 2020 and 2021 in the changing irrigation treatment, the mean prediction accuracy (r = 0.46) was 42% higher than that of the simple genomic prediction model (r =0.32). The results suggest that this RRM method using the time-series MS data can effectively capture the genetic variation of plant response to drought