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Radar echo extrapolation is a critical technique for short-term weather forecasting. Timely warnings of severe convective weather events can be provided according to the extrapolated images. However, traditional echo extrapolation methods fail to fully utilize historical radar echo data, resulting in limited accuracy for future radar echo prediction. Existing deep learning echo extrapolation methods often face issues such as high-threshold echo attenuation and blurring distortion. In this paper, we propose a UNet-based multi-branch feature extraction model named MBFE-UNet for radar echo extrapolation to mitigate these issues. We design a Multi-Branch Feature Extraction Block, which extracts spatiotemporal features of radar echo data from various perspectives. Additionally, we introduce a Temporal Cross Attention Fusion Unit to model the temporal correlation between features from different network layers, which helps the model to better capture the temporal evolution patterns of radar echoes. Experimental results indicate that, compared to the Transformer-based Rainformer, the MBFE-UNet achieves an average increase of 4.8% in the critical success index (CSI), 5.5% in the probability of detection (POD), and 3.8% in the Heidke skill score (HSS). [ABSTRACT FROM AUTHOR]

Spray-induced gene silencing represents an eco-friendly approach for crop protection through the use of double-stranded RNA (dsRNA) to activate the RNA interference (RNAi) pathway, thereby silencing crucial genes in pathogens. The major challenges associated with dsRNA are its limited stability and poor cellular uptake, necessitating repeated applications for effective crop protection. In this study, RNA nanoparticles (NPs) were proposed as effectors in plants and pathogens by inducing the RNAi pathway and silencing gene expression. RNA structural motifs, such as hairpin-loop, kissing-loop, and tetra-U motifs, were used to link multiple siRNAs into a long, single-stranded RNA (lssRNA). The lssRNA, synthesized in Escherichia coli, self-assembled into stable RNA nanostructures via local base pairing. Comparative analyses between dsRNA and RNA NPs revealed that the latter displayed superior efficacy in inhibiting spore germination and mycelial growth of Botrytis cinerea. Moreover, RNA NPs had a more robust protective effect on plants against B. cinerea than did dsRNA. In addition, RNA squares are processed into expected siRNA in plants, thereby inhibiting the expression of the target gene. These findings suggest the potential of RNA NPs for use in plant disease control by providing a more efficient and specific alternative to dsRNA without requiring nanocarriers. [ABSTRACT FROM AUTHOR]

Coronavirus infectious disease 2019 (COVID-19), caused by severe acute respiratory virus type 2 (SARS-CoV-2), has caused a global public health crisis. As an RNA virus, the high gene mutability of SARS-CoV-2 poses significant challenges to the development of broad-spectrum vaccines and antiviral therapeutics. There remains a lack of specific therapeutics directly targeting SARS-CoV-2. With the ability to efficiently inhibit the expression of target genes in a sequence-specific way, small interfering RNA (siRNA) therapy has exhibited significant potential in antiviral and other disease treatments. In this work, we presented a highly effective self-assembled siRNA nanoparticle targeting multiple highly conserved regions of SARS-CoV-2. The siRNA sequences targeting viral conserved regions were first screened and evaluated by their thermodynamic features, off-target effects, and secondary structure toxicities. RNA motifs including siRNA sequences were then designed and self-assembled into siRNA nanoparticles. These siRNA nanoparticles demonstrated remarkable uniformity and stability and efficiently entered cells directly through cellular endocytic pathways. Moreover, these nanoparticles effectively inhibited the replication of SARS-CoV-2, exhibiting a superior inhibitory effect compared to free siRNA. These results demonstrated that these self-assembled siRNA nanoparticles targeting highly conserved regions of SARS-CoV-2 represent highly effective antiviral candidates for the treatment of infections, and are promisingly effective against current and future viral variants. [ABSTRACT FROM AUTHOR]

To solve the problems of the current deep learning radar extrapolation model consuming many resources and the final prediction result lacking details, a weather radar image super-resolution weather model based on SR3 (super-resolution via image restoration and recognition) for radar images is proposed. This model uses a diffusion model to super-resolve weather radar images to generate high-definition images and optimizes the performance of the U-Net denoising network on the basis of SR3 to further improve image quality. The model receives high-resolution images with Gaussian noise added and performs channel splicing with low-resolution images for conditional generation. The experimental results showed that the introduction of the diffusion model significantly improved the spatial resolution of weather radar images, providing new technical means for applications in related fields; when the amplification factor was 8, Radar-SR3, compared with the image super-resolution model based on the generative adversarial network (SRGAN) and the bicubic interpolation algorithm, the peak signal-to-noise ratio (PSNR) increased by 146% and 52% on average. According to this model, it is possible to train radar extrapolation models with limited computing resources with high-resolution images. [ABSTRACT FROM AUTHOR]

The aim of this work was to study the cloning and characterization of HMW-GS 1Dx2 promoter from Triticum aestivum. A 1050 bp partial promoter fragment including a putative TATA box and 5' encoding sequence of the gene was cloned by amplifying the upstream sequences using the nest-PCR with appropriate primers. The analysis of the promoter sequence against the PLACE (Plant cis-acting Regulatory DNA Elements) database showed the presence of certain putative endosperm-specific regulatory cis-elements in the sequence along with the TATA and CAAT boxes. The histochemical method detected the transient expressions of GUS in the seeds of wheat. The results showed that HMW-GS 1Dx2 promoter had the endosperm-specific transcription activity in the wheat seeds.

Background and Aim: Most patients with gastric tumors and precancerous lesions are asymptomatic, which often results in delayed diagnosis and treatment. Compared with conventional gastroscopy and capsule endoscopy, magnetic‐controlled capsule endoscopy is a non‐invasive, effective, and cost‐efficient diagnostic modality for gastric examination. We retrospectively investigated magnetic‐controlled capsule endoscopy as a screening tool for gastrointestinal lesions (particularly gastric tumors and precancerous lesions) in asymptomatic individuals. Methods: In this retrospective study, 1757 patients who voluntarily underwent magnetic‐controlled capsule endoscopy between January and December 2019 at nine medical centers across Shaanxi province based on strict inclusion and exclusion criteria were enrolled. The primary outcomes were gastric tumor and precancerous lesion detection rates and procedural safety. Results: The upper and lower gastrointestinal lesion detection rates were 98.35% (1728/1757) and 21.61% (78/361), respectively; 2.28% of patients were diagnosed with gastric tumors including gastric cancer (4/1757) and submucosal tumors (36/1757). Three types of precancerous lesions were found in 591 patients (33.64%), including chronic atrophic gastritis (23.16%), gastric polyp (10.98%), and gastric ulcer (2.96%). For patients aged over 40 years, the detection rate of precancerous lesions was higher (14.36% vs 42.58%, P < 0.001). No patient was diagnosed with small intestinal cancer. No adverse events occurred. Conclusions: Magnetic‐controlled capsule endoscopy could be used as a promising novel screening modality for diagnosis of gastrointestinal lesions in asymptomatic individuals, specifically gastric tumors and precancerous lesions, with the advantages of safety, non‐invasiveness, effectiveness, and cost‐efficiency. [ABSTRACT FROM AUTHOR]