miRU: an automated plant miRNA target prediction server

MicroRNAs (miRNAs) play important roles in gene expression regulation in animals and plants. Since plant miRNAs recognize their target mRNAs by near-perfect base pairing, computational sequence similarity search can be used to identify potential targets. A web-based integrated computing system, miRU, has been developed for plant miRNA target gene prediction in any plant, if a large number of sequences are available. Given a mature miRNA sequence from a plant species, the system thoroughly searches for potential complementary target sites with mismatches tolerable in miRNA–target recognition. True or false positives are estimated based on the number and type of mismatches in the target site, and on the evolutionary conservation of target complementarity in another genome which can be selected according to miRNA conservation. The output for predicted targets, ordered by mismatch scores, includes complementary sequences with mismatches highlighted in colors, original gene sequences and associated functional annotations. The miRU web server is available at

The WRKY transcription factor superfamily: its origin in eukaryotes and expansion in plants

BACKGROUND: WRKY proteins are newly identified transcription factors involved in many plant processes including plant responses to biotic and abiotic stresses. To date, genes encoding WRKY proteins have been identified only from plants. Comprehensive search for WRKY genes in non-plant organisms and phylogenetic analysis would provide invaluable information about the origin and expansion of the WRKY family. RESULTS: We searched all publicly available sequence data for WRKY genes. A single copy of the WRKY gene encoding two WRKY domains was identified from Giardia lamblia, a primitive eukaryote, Dictyostelium discoideum, a slime mold closely related to the lineage of animals and fungi, and the green alga Chlamydomonas reinhardtii, an early branching of plants. This ancestral WRKY gene seems to have duplicated many times during the evolution of plants, resulting in a large family in evolutionarily advanced flowering plants. In rice, the WRKY gene family consists of over 100 members. Analyses suggest that the C-terminal domain of the two-WRKY-domain encoding gene appears to be the ancestor of the single-WRKY-domain encoding genes, and that the WRKY domains may be phylogenetically classified into five groups. We propose a model to explain the WRKY family's origin in eukaryotes and expansion in plants. CONCLUSIONS: WRKY genes seem to have originated in early eukaryotes and greatly expanded in plants. The elucidation of the evolution and duplicative expansion of the WRKY genes should provide valuable information on their functions

Fused deposition modelling of natural fibre/polylactic acid composites

Fused deposition modelling is a simple additive manufacturing technology utilising fine filament extrusion of predominantly thermoplastic materials to build 3D objects layer by layer. This research explores the feasibility and the factors involved in using fused deposition modelling to produce natural fibre reinforced composite components. Uniform 3-mm filaments of both hemp and harakeke (Phormium tenax) in varying weight percentages within polylactic acid (PLA) polymer were successfully produced and used to print tensile test samples. Tensile test results supported harakeke to be a useful fibre in terms of mechanical properties achieved which surpassed the Young’s modulus and tensile strength of plain PLA samples by 42.3% and 5.4%, respectively

Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfer

Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis. Retraining models leads to high latency and complex pipelines, which are impractical in clinical settings. The situation becomes more severe for ultrasound image analysis because of their large appearance shifts. In this paper, we propose a novel method for robust segmentation under unknown appearance shifts. Our contribution is three-fold. First, we advance a one-stage plug-and-play solution by embedding hierarchical style transfer units into a segmentation architecture. Our solution can remove appearance shifts and perform segmentation simultaneously. Second, we adopt Dynamic Instance Normalization to conduct precise and dynamic style transfer in a learnable manner, rather than previously fixed style normalization. Third, our solution is fast and lightweight for routine clinical adoption. Given 400*400 image input, our solution only needs an additional 0.2ms and 1.92M FLOPs to handle appearance shifts compared to the baseline pipeline. Extensive experiments are conducted on a large dataset from three vendors demonstrate our proposed method enhances the robustness of deep segmentation models

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

3D ultrasound (US) is widely used due to its rich diagnostic information, portability and low cost. Automated standard plane (SP) localization in US volume not only improves efficiency and reduces user-dependence, but also boosts 3D US interpretation. In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously. Our contribution is two-fold. First, we equip the MARL with a one-shot neural architecture search (NAS) module to obtain the optimal agent for each plane. Specifically, Gradient-based search using Differentiable Architecture Sampler (GDAS) is employed to accelerate and stabilize the training process. Second, we propose a novel collaborative strategy to strengthen agents' communication. Our strategy uses recurrent neural network (RNN) to learn the spatial relationship among SPs effectively. Extensively validated on a large dataset, our approach achieves the accuracy of 7.05 degree/2.21mm, 8.62 degree/2.36mm and 5.93 degree/0.89mm for the mid-sagittal, transverse and coronal plane localization, respectively. The proposed MARL framework can significantly increase the plane localization accuracy and reduce the computational cost and model size.Comment: Early accepted by MICCAI 202

FetusMapV2: Enhanced Fetal Pose Estimation in 3D Ultrasound

Fetal pose estimation in 3D ultrasound (US) involves identifying a set of associated fetal anatomical landmarks. Its primary objective is to provide comprehensive information about the fetus through landmark connections, thus benefiting various critical applications, such as biometric measurements, plane localization, and fetal movement monitoring. However, accurately estimating the 3D fetal pose in US volume has several challenges, including poor image quality, limited GPU memory for tackling high dimensional data, symmetrical or ambiguous anatomical structures, and considerable variations in fetal poses. In this study, we propose a novel 3D fetal pose estimation framework (called FetusMapV2) to overcome the above challenges. Our contribution is three-fold. First, we propose a heuristic scheme that explores the complementary network structure-unconstrained and activation-unreserved GPU memory management approaches, which can enlarge the input image resolution for better results under limited GPU memory. Second, we design a novel Pair Loss to mitigate confusion caused by symmetrical and similar anatomical structures. It separates the hidden classification task from the landmark localization task and thus progressively eases model learning. Last, we propose a shape priors-based self-supervised learning by selecting the relatively stable landmarks to refine the pose online. Extensive experiments and diverse applications on a large-scale fetal US dataset including 1000 volumes with 22 landmarks per volume demonstrate that our method outperforms other strong competitors.Comment: 16 pages, 11 figures, accepted by Medical Image Analysis(2023

Regulation of Gene Expression in Plants through miRNA Inactivation

Eukaryotic organisms possess a complex RNA-directed gene expression regulatory network allowing the production of unique gene expression patterns. A recent addition to the repertoire of RNA-based gene regulation is miRNA target decoys, endogenous RNA that can negatively regulate miRNA activity. miRNA decoys have been shown to be a valuable tool for understanding the function of several miRNA families in plants and invertebrates. Engineering and precise manipulation of an endogenous RNA regulatory network through modification of miRNA activity also affords a significant opportunity to achieve a desired outcome of enhanced plant development or response to environmental stresses. Here we report that expression of miRNA decoys as single or heteromeric non-cleavable microRNA (miRNA) sites embedded in either non-protein-coding or within the 3′ untranslated region of protein-coding transcripts can regulate the expression of one or more miRNA targets. By altering the sequence of the miRNA decoy sites, we were able to attenuate miRNA inactivation, which allowed for fine regulation of native miRNA targets and the production of a desirable range of plant phenotypes. Thus, our results demonstrate miRNA decoys are a flexible and robust tool, not only for studying miRNA function, but also for targeted engineering of gene expression in plants. Computational analysis of the Arabidopsis transcriptome revealed a number of potential miRNA decoys, suggesting that endogenous decoys may have an important role in natural modulation of expression in plants

Celastrol targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent cytotoxicity in tumor cells

<p>Abstract</p> <p>Background</p> <p>Celastrol is an active ingredient of the traditional Chinese medicinal plant <it>Tripterygium Wilfordii</it>, which exhibits significant antitumor activity in different cancer models <it>in vitro </it>and <it>in vivo</it>; however, the lack of information on the target and mechanism of action of this compound have impeded its clinical application. In this study, we sought to determine the mode of action of celastrol by focusing on the processes that mediate its anticancer activity.</p> <p>Methods</p> <p>The downregulation of heat shock protein 90 (HSP90) client proteins, phosphorylation of c-Jun NH2-terminal kinase (JNK), and cleavage of PARP, caspase 9 and caspase 3 were detected by western blotting. The accumulation of reactive oxygen species (ROS) was analyzed by flow cytometry and fluorescence microscopy. Cell cycle progression, mitochondrial membrane potential (MMP) and apoptosis were determined by flow cytometry. Absorption spectroscopy was used to determine the activity of mitochondrial respiratory chain (MRC) complexes.</p> <p>Results</p> <p>Celastrol induced ROS accumulation, G2-M phase blockage, apoptosis and necrosis in H1299 and HepG2 cells in a dose-dependent manner. N-acetylcysteine (NAC), an antioxidative agent, inhibited celastrol-induced ROS accumulation and cytotoxicity. JNK phosphorylation induced by celastrol was suppressed by NAC and JNK inhibitor SP600125 (SP). Moreover, SP significantly inhibited celastrol-induced loss of MMP, cleavage of PARP, caspase 9 and caspase 3, mitochondrial translocation of Bad, cytoplasmic release of cytochrome c, and cell death. However, SP did not inhibit celastrol-induced ROS accumulation. Celastrol downregulated HSP90 client proteins but did not disrupt the interaction between HSP90 and cdc37. NAC completely inhibited celastrol-induced decrease of HSP90 client proteins, catalase and thioredoxin. The activity of MRC complex I was completely inhibited in H1299 cells treated with 6 μM celastrol in the absence and presence of NAC. Moreover, the inhibition of MRC complex I activity preceded ROS accumulation in H1299 cells after celastrol treatment.</p> <p>Conclusion</p> <p>We identified ROS as the key intermediate for celastrol-induced cytotoxicity. JNK was activated by celastrol-induced ROS accumulation and then initiated mitochondrial-mediated apoptosis. Celastrol induced the downregulation of HSP90 client proteins through ROS accumulation and facilitated ROS accumulation by inhibiting MRC complex I activity. These results identify a novel target for celastrol-induced anticancer activity and define its mode of action.</p