New Atomic Decompositions of Weighted Local Hardy Spaces

We introduce a new class of weighted local approximate atoms including classical weighted local atoms. Then we further obtain the weighted local approximate atomic decompositions of weighted local Hardy spaces $h_{\omega} ^p(R^n)$ with $0<p\leq 1$ and weight $\omega\in A_1(R^n)$. As an application, we prove the boundedness of inhomogeneous Calder\'on-Zygmund operators on $h_{\omega}^p(R^n)$ via weighted local approximate atoms and molecules

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

BACKGROUND: BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. RESULTS: Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. CONCLUSION: PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform-independent, easily configurable and capable of comprehensive expansion, and user-intuitive. PLAN is freely available to academic users at . The source code for local deployment is provided under free license. Full support on system utilization, installation, configuration and customization are provided to academic users

Mining Functional Elements in Messenger RNAs: Overview, Challenges, and Perspectives

Eukaryotic messenger RNA (mRNA) contains not only protein-coding regions but also a plethora of functional cis-elements that influence or coordinate a number of regulatory aspects of gene expression, such as mRNA stability, splicing forms, and translation rates. Understanding the rules that apply to each of these element types (e.g., whether the element is defined by primary or higher-order structure) allows for the discovery of novel mechanisms of gene expression as well as the design of transcripts with controlled expression. Bioinformatics plays a major role in creating databases and finding non-evident patterns governing each type of eukaryotic functional element. Much of what we currently know about mRNA regulatory elements in eukaryotes is derived from microorganism and animal systems, with the particularities of plant systems lagging behind. In this review, we provide a general introduction to the most well-known eukaryotic mRNA regulatory motifs (splicing regulatory elements, internal ribosome entry sites, iron-responsive elements, AU-rich elements, zipcodes, and polyadenylation signals) and describe available bioinformatics resources (databases and analysis tools) to analyze eukaryotic transcripts in search of functional elements, focusing on recent trends in bioinformatics methods and tool development. We also discuss future directions in the development of better computational tools based upon current knowledge of these functional elements. Improved computational tools would advance our understanding of the processes underlying gene regulations. We encourage plant bioinformaticians to turn their attention to this subject to help identify novel mechanisms of gene expression regulation using RNA motifs that have potentially evolved or diverged in plant species

Defect detection method for key area guided transmission line components based on knowledge distillation

Introduction: The aim of this paper is to address the problem of the limited number of defect images for both metal tools and insulators, as well as the small range of defect features.Methods: A defect detection method for key area-guided transmission line components based on knowledge distillation is proposed. First, the PGW (Prediction-Guided Weighting) module is introduced to improve the foreground target distillation region, and the distillation range is precisely concentrated in the position of the first k feature pixels with the highest quality score in the form of a mask. The feature knowledge of defects of hardware and insulators is used as the focus for the teacher network to guide the student network. Then, the GcBlock module is used to capture the relationship between the target defects of the hardware and the transmission lines in the background, and the overall relationship information of the image is used to promote the students’ network to learn the teacher’s network perception ability of the relationship information. Finally, the classification task mask and regression task mask generated by the PGW module, combined with the overall image relationship loss, form a distillation loss function for network training to improve the accuracy of students’ network detection accuracy.Results and Discussion: The effectiveness of the proposed method is verified by using self-build metal fittings and insulator defect data sets. The experimental results show that the student network mAP_50 (Mean Average Precision at 50) in the Faster R-CNN model with the knowledge distillation algorithm added in this paper increases by 8.44%, and the RetinaNet model increases by 2.6%. The Cascade R-CNN model improved by 5.28%

TransportTP: A two-phase classification approach for membrane transporter prediction and characterization

<p>Abstract</p> <p>Background</p> <p>Membrane transporters play crucial roles in living cells. Experimental characterization of transporters is costly and time-consuming. Current computational methods for transporter characterization still require extensive curation efforts, especially for eukaryotic organisms. We developed a novel genome-scale transporter prediction and characterization system called TransportTP that combined homology-based and machine learning methods in a two-phase classification approach. First, traditional homology methods were employed to predict novel transporters based on sequence similarity to known classified proteins in the Transporter Classification Database (TCDB). Second, machine learning methods were used to integrate a variety of features to refine the initial predictions. A set of rules based on transporter features was developed by machine learning using well-curated proteomes as guides.</p> <p>Results</p> <p>In a cross-validation using the yeast proteome for training and the proteomes of ten other organisms for testing, TransportTP achieved an equivalent recall and precision of 81.8%, based on TransportDB, a manually annotated transporter database. In an independent test using the Arabidopsis proteome for training and four recently sequenced plant proteomes for testing, it achieved a recall of 74.6% and a precision of 73.4%, according to our manual curation.</p> <p>Conclusions</p> <p>TransportTP is the most effective tool for eukaryotic transporter characterization up to date.</p

DeGNServer: Deciphering Genome-Scale Gene Networks through High Performance Reverse Engineering Analysis

Analysis of genome-scale gene networks (GNs) using large-scale gene expression data provides unprecedented opportunities to uncover gene interactions and regulatory networks involved in various biological processes and developmental programs, leading to accelerated discovery of novel knowledge of various biological processes, pathways and systems. The widely used context likelihood of relatedness (CLR) method based on the mutual information (MI) for scoring the similarity of gene pairs is one of the accurate methods currently available for inferring GNs. However, the MI-based reverse engineering method can achieve satisfactory performance only when sample size exceeds one hundred. This in turn limits their applications for GN construction from expression data set with small sample size. We developed a high performance web server, DeGNServer, to reverse engineering and decipher genome-scale networks. It extended the CLR method by integration of different correlation methods that are suitable for analyzing data sets ranging from moderate to large scale such as expression profiles with tens to hundreds of microarray hybridizations, and implemented all analysis algorithms using parallel computing techniques to infer gene-gene association at extraordinary speed. In addition, we integrated the SNBuilder and GeNa algorithms for subnetwork extraction and functional module discovery. DeGNServer is publicly and freely available online

Distribution of Three Congeneric Shrub Species Along an Aridity Gradient Is Related to Seed Germination and Seedling Emergence

Environmental tolerance of a species has been shown to correlate positively with its geographical range. On the Ordos Plateau, three Caragana species are distributed sequentially along the precipitation gradient. We hypothesized that this geographical distribution pattern is related to environmental tolerances of the three Caragana species during seed germination and seedling emergence stages. To test this hypothesis, we examined seed germination under different temperature, light and water potentials, and monitored seedling emergence for seeds buried at eight sand depths and given different amounts of water. Seeds of C. korshinskii germinated to high percentages at 5 : 15 to 25 : 35 °C in both light and darkness, while those of C. intermedia and C. microphylla did so only at 15 : 25 and 25 : 35 °C, respectively. Nearly 30 % of the C. korshinskii seeds germinated at -1.4 MPa at 20 and 25 °C, while no seeds of the other two species did so. Under the same treatments, seedling emergence percentages of C. korshinskii were higher than those of the other two species. The rank order of tolerance to drought and sand burial of the three species is C. korshinskii \u3e C. intermedia \u3e C. microphylla. The amount of precipitation and sand burial depth appear to be the main selective forces responsible for the geographical distribution of these species

The predictive value of revised diastolic dysfunction in outcomes of liver transplantation: A propensity score matching analysis

BackgroundDiastolic dysfunction (DD), one of the earliest signs of cirrhotic cardiomyopathy (CCM), is included in the revised 2019 CCM criteria. Nonetheless, relevant research regarding the effects of revised DD on post-liver transplantation (LT) outcomes remains limited.MethodsThis retrospective study enrolled patients who underwent LT for decompensated cirrhosis, from January 2018 to March 2021. Patients were divided into DD and non-DD groups. Clinical data were collected. Patients were followed up with, for at least 1 year post-LT; cardiovascular adverse events (AEs) and survival status were recorded. Risk factors were identified using 1:2 propensity score matching (PSM), after adjusting for confounding factors. The caliper value was set to 0.02.ResultsOf 231 patients, 153 were diagnosed with DD (male, 81.8%; mean age, 51.5 ± 9.5 years). Nineteen patients with DD died within 1 year, post-LT. After PSM, 97 and 60 patients were diagnosed with and without DD, respectively. Patients with DD had longer intensive care unit (ICU) stays, higher perioperative cardiovascular AEs, and higher mortality rates than those without DD. In a multivariate analysis, interventricular septum (IVS), left atrial volume index (LAVI), and potassium levels were independent prognostic factors of perioperative cardiovascular AEs, while a decreased early diastolic mitral annular tissue velocity (e’), increased neutrophil-to-lymphocyte ratio (NLR) and tumor markers were predictors of mortality within 1 year post-LT after PSM (P &lt; 0.05).ConclusionCardiac DD may contribute to perioperative cardiovascular AEs and mortality post-LT. Clinicians should be aware of decompensated cirrhosis in patients with DD

Screening and Identification of Cardioprotective Compounds From Wenxin Keli by Activity Index Approach and in vivo Zebrafish Model

Wenxin Keli (WXKL) is a widely used Chinese botanical drug for the treatment of arrhythmia, which is consisted of four herbs and amber. In the present study, we analyzed the chemical composition of WXKL using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) to tentatively identify 71 compounds. Through typical separate procession, the total extract of WXKL was divided into fractions for further bioassays. Cardiomyocytes and zebrafish larvae were applied for assessment. In vivo arrhythmia model in Cmlc2-GFP transgenic zebrafish was induced by terfenadine, which exhibited obvious reduction of heart rate and occurrence of atrioventricular block. Dynamic beating of heart was recorded by fluorescent microscope and sensitive camera to automatically recognize the rhythm of heartbeat in zebrafish larvae. By integrating the chemical information of WXKL and corresponding bioactivities of these fractions, activity index (AI) of each identified compound was calculated to screen potential active compounds. The results showed that dozens of compounds including ginsenoside Rg1, ginsenoside Re, notoginsenoside R1, lobetyolin, and lobetyolinin were contributed to cardioprotective effects of WXKL. The anti-arrhythmic activities of five compounds were further validated in larvae model and mature zebrafish by measuring electrocardiogram (ECG). Our findings provide a successful example for rapid discovery of bioactive compounds from traditional Chinese medicine (TCM) by activity index based approach coupled with in vivo zebrafish model

Influences of nitrogen input forms and levels on phosphorus availability in karst grassland soils

The availability of soil phosphorus (P), a crucial nutrient influencing plant productivity and ecosystem function, is impacted by continuously increasing nitrogen (N) enrichment, which changes the soil P cycle. The effect of varying forms of N input on soil P dynamics in P-limited karst grassland ecosystems remains unclear. To address this knowledge gap, we conducted a greenhouse experiment to explore the effects of various forms of N addition [Ca(NO3)2, NH4Cl, NH4NO3, Urea] on soil P fractions in these ecosystems, applying two levels (N1: 50 mg N kg−1soil, N2: 100 mg N kg−1soil) of N input in two soils (yellow soil, limestone soil). Results indicated that P fractions in both soil types were significantly affected by N additions, with yellow soil demonstrating a higher sensitivity to these additions, and this effect was strongly modulated by the form and level of N added. High N addition, rather than low N, significantly affect the P fractions in both soil types. Specially, except for Ca(NO3)2, high N addition significantly increased the available P in both soils, following the order: Urea and NH4NO3 &gt; NH4Cl &gt; Ca(NO3)2, and decreased NaHCO3-Pi in both soils. High N addition also significantly reduced NaOH-Po and C.HCl-Po fractions in yellow soil. Additionally, the response of root biomass and alkaline phosphatase activity in both soils to N input paralleled the trends observed in the available P fractions. Notably, changes in soil available P were strongly correlated with plant root biomass and soil alkaline phosphatase activity. Our study highlights that the N addition form significantly influences soil P availability, which is closely tied to plant root biomass and alkaline phosphatase activity. This finding underscores the importance of considering N input form to boost soil fertility and promote sustainable agriculture