TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 \, {\rm km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} \, {\rm Hz}$ and $1 \, {\rm Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 \, {\rm cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 \, {\rm m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019—the first-round result shows that the satellite has exceeded all of its mission requirements.
Aspergillus flavus first gained scientific attention for its production of aflatoxin. The underlying regulation of aflatoxin biosynthesis has been serving as a theoretical model for biosynthesis of other microbial secondary metabolites. Nevertheless, for several decades, the DNA methylation status, one of the important epigenomic modifications involved in gene regulation, in A. flavus remains to be controversial. Here, we applied bisulfite sequencing in conjunction with a biological replicate strategy to investigate the DNA methylation profiling of A. flavus genome. Both the bisulfite sequencing data and the methylome comparisons with other fungi confirm that the DNA methylation level of this fungus is negligible. Further investigation into the DNA methyltransferase of Aspergillus uncovers its close relationship with RID-like enzymes as well as its divergence with the methyltransferase of species with validated DNA methylation. The lack of repeat contents of the A. flavus' genome and the high RIP-index of the small amount of remanent repeat potentially support our speculation that DNA methylation may be absent in A. flavus or that it may possess de novo DNA methylation which occurs very transiently during the obscure sexual stage of this fungal species. This work contributes to our understanding on the DNA methylation status of A. flavus, as well as reinforces our views on the DNA methylation in fungal species. In addition, our strategy of applying bisulfite sequencing to DNA methylation detection in species with low DNA methylation may serve as a reference for later scientific investigations in other hypomethylated species.
The TianQin-1 satellite (TQ-1), which is the first technology demonstration satellite for the TianQin project, was launched on
Background: Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population worldwide, and there is a large unmet need for DR screening in China. This observational, prospective, multicenter, gold standard-controlled study sought to evaluate the effectiveness and safety of the AIDRScreening system (v. 1.0), which is an artificial intelligence (AI)-enabled system that detects DR in the Chinese population based on fundus photographs.Methods: Participants with diabetes mellitus (DM) were recruited. Fundus photographs (field 1 and field 2) of 1 eye in each participant were graded by the AIDRScreening system (v. 1.0) to detect referable DR (RDR).The results were compared to those of the masked manual grading (gold standard) system by the Zhongshan Image Reading Center. The primary outcomes were the sensitivity and specificity of the AIDRScreening system in detecting RDR. The other outcomes evaluated included the system's diagnostic accuracy, positive predictive value, negative predictive value, diagnostic accuracy gain rate, and average diagnostic time gain rate.Results: Among the 1,001 enrolled participants with DM, 962 (96.1%) were included in the final analyses.The participants had a median age of 60.61 years (range: 20.18-85.78 years), and 48.2% were men. The manual grading system detected RDR in 399 (41.48%) participants. The AIDRScreening system had a sensitivity of 86.72% (95% CI: 83.39-90.05%) and a specificity of 96.09% (95% CI: 94.14-97.54%) in the detection of RDR, and a false-positive rate of 3.91%. The diagnostic accuracy gain rate of the AIDRScreening system was 16.57% higher than that of the investigator, while the average diagnostic time gain rate was −37.32% lower.Conclusions: The automated AIDRScreening system can detect RDR with high accuracy, but cannot detect maculopathy. The implementation of the AIDRScreening system may increase the efficiency of DR screening.
Visual impairment and blindness are common and seriously affect people’s work and quality of life in the world. Therefore, the effective therapies for eye diseases are of high priority. Zebrafish (Danio rerio) is an alternative vertebrate model as a useful tool for the mechanism elucidation and drug discovery of various eye disorders, such as cataracts, glaucoma, diabetic retinopathy, age-related macular degeneration, photoreceptor degeneration, etc. The genetic and embryonic accessibility of zebrafish in combination with a behavioral assessment of visual function has made it a very popular model in ophthalmology. Zebrafish has also been widely used in ocular drug discovery, such as the screening of new anti-angiogenic compounds or neuroprotective drugs, and the oculotoxicity test. In this review, we summarized the applications of zebrafish as the models of eye disorders to study disease mechanism and investigate novel drug treatments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.