A novel botybirnavirus with a unique satellite dsRNA causes latent infection in Didymella theifolia isolated from tea plants

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The unique, recently discovered fungus Didymella theifolia specifically infects local varieties of tea plant Camellia sinensis in China, and therefore, the characterization of its mycoviruses is important. Three double-stranded (ds) RNAs (1, 2, and 3, with 6,338, 5,910, and 727 bp in size, respectively) were identified in the avirulent D. theifolia strain CJP4-1, which exhibits normal growth and morphology. Characterization of these double-stranded RNAs (dsRNAs) revealed that the two largest elements are the genomic components of a novel botybirnavirus, tentatively named Didymella theifolia botybirnavirus 1 (DtBRV1). Conversely, dsRNA3 shares no detectable similarity with sequences deposited in public databases but has high similarity with the 5′-terminal regions of dsRNAs 1 and 2 and contains a duplicated region encoding a putative small peptide. All three dsRNAs are encapsidated in isometric virions ca. 40 nm in diameter, supporting the notion that dsRNA3 is a DtBRV1 satellite. SDS-polyacrylamide gel electrophoresis in combination with peptide mass fingerprint analysis revealed that the DtBRV1 capsid protein consists of polypeptides encoded by the 5′-terminal regions of both genomic components dsRNA1 and dsRNA2. Vertical transmission of DtBRV1 through conidia is efficient, while its horizontal transmission from CJP4-1 to other strains was not detected. DtBRV1, with or without dsRNA3, has no obvious effects on fungal growth and virulence, as illustrated following transfection of the virulent D. theifolia strain JYC1-6. In summary, DtBRV1 exhibits unique molecular traits and contributes to our understanding of mycovirus diversity.Peer reviewe

Single “Swiss-roll” microelectrode elucidates the critical role of iron substitution in conversion-type oxides

Advancing the lithium-ion battery technology requires the understanding of electrochemical processes in electrode materials with high resolution, accuracy, and sensitivity. However, most techniques today are limited by their inability to separate the complex signals from slurry-coated composite electrodes. Here, we use a three-dimensional “Swiss-roll” microtubular electrode that is incorporated into a micrometer-sized lithium battery. This on-chip platform combines various in situ characterization techniques and precisely probes the intrinsic electrochemical properties of each active material due to the removal of unnecessary binders and additives. As an example, it helps elucidate the critical role of Fe substitution in a conversion-type NiO electrode by monitoring the evolution of Fe2O3 and solid electrolyte interphase layer. The markedly enhanced electrode performances are therefore explained. Our approach exposes a hitherto unexplored route to tracking the phase, morphology, and electrochemical evolution of electrodes in real time, allowing us to reveal information that is not accessible with bulk-level characterization techniques

Simulation and analysis of microring electric field sensor based on a lithium niobate-on-insulator

With the increasing sensitivity and accuracy of contemporary high-performance electronic information systems to electromagnetic energy, they are also very vulnerable to be damaged by high-energy electromagnetic fields. In this work, an all-dielectric electromagnetic field sensor is proposed based on a microring resonator structure. The sensor is designed to work at 35 GHz RF field using a lithium niobate-on-insulator (LNOI) material system. The 2.5-D variational finite difference time domain (varFDTD) and finite difference eigenmode (FDE) methods are utilized to analyze the single-mode condition, bending loss, as well as the transmission loss to achieve optimized waveguide dimensions. In order to obtain higher sensitivity, the quality factor (Q-factor) of the microring resonator is optimized to be 106 with the total ring circumference of 3766.59 μm. The lithium niobate layer is adopted in z-cut direction to utilize TM mode in the proposed all-dielectric electric field sensor, and with the help of the periodically poled lithium niobate (PPLN) technology, the electro-optic (EO) tunability of the device is enhanced to 48 pm·μm/V

Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance

Background: This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function. Methods: The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson’s correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of –0.037 (limits of agreement: –0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78). Conclusions: This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis

Integrated Circuits Based on Bilayer MoS

Two-dimensional (2D) materials, such as molybdenum disulfide (MoS2), have been shown to exhibit excellent electrical and optical properties. The semiconducting nature of MoS2 allows it to overcome the shortcomings of zero-bandgap graphene, while still sharing many of graphene’s advantages for electronic and optoelectronic applications. Discrete electronic and optoelectronic components, such as field-effect transistors, sensors, and photodetectors made from few-layer MoS2 show promising performance as potential substitute of Si in conventional electronics and of organic and amorphous Si semiconductors in ubiquitous systems and display applications. An important next step is the fabrication of fully integrated multistage circuits and logic building blocks on MoS2 to demonstrate its capability for complex digital logic and high-frequency ac applications. This paper demonstrates an inverter, a NAND gate, a static random access memory, and a five-stage ring oscillator based on a direct-coupled transistor logic technology. The circuits comprise between 2 to 12 transistors seamlessly integrated side-by-side on a single sheet of bilayer MoS2. Both enhancement-mode and depletion-mode transistors were fabricated thanks to the use of gate metals with different work functions.United States. Office of Naval Research (Young Investigator Program)Microelectronics Advanced Research Corporation (MARCO) (Focus Center for Materials, Structure and Device (MARCO MSD))National Science Foundation (U.S.) (NSF DMR 0845358)United States. Army Research Offic

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

Mapping Aquaculture Areas with Multi-Source Spectral and Texture Features: A Case Study in the Pearl River Basin (Guangdong), China

Aquaculture has grown rapidly in the field of food industry in recent years; however, it brought many environmental problems, such as water pollution and reclamations of lakes and coastal wetland areas. Thus, the evaluation and management of aquaculture industry are needed, in which accurate aquaculture mapping is an essential prerequisite. Due to the difference between inland and marine aquaculture areas and the difficulty in processing large amounts of remote sensing images, the accurate mapping of different aquaculture types is still challenging. In this study, a novel approach based on multi-source spectral and texture features was proposed to map simultaneously inland and marine aquaculture areas. Time series optical Sentinel-2 images were first employed to derive spectral indices for obtaining texture features. The backscattering and texture features derived from the synthetic aperture radar (SAR) images of Sentinel-1A were then used to distinguish aquaculture areas from other geographical entities. Finally, a supervised Random Forest classifier was applied for large scale aquaculture area mapping. To address the low efficiency in processing large amounts of remote sensing images, the proposed approach was implemented on the Google Earth Engine (GEE) platform. A case study in the Pearl River Basin (Guangdong Province) of China showed that the proposed approach obtained aquaculture map with an overall accuracy of 89.5%, and the implementation of proposed approach on GEE platform greatly improved the efficiency for large scale aquaculture area mapping. The derived aquaculture map may support decision-making services for the sustainable development of aquaculture areas and ecological protection in the study area, and the proposed approach holds great potential for mapping aquacultures on both national and global scales