Diverse biological effects of glycosyltransferase genes from Tartary buckwheat

Background: Tartary buckwheat (Fagopyrum tataricum) is an edible cereal crop whose sprouts have been marketed and commercialized for their higher levels of anti-oxidants, including rutin and anthocyanin. UDP-glucose flavonoid glycosyltransferases (UFGTs) play an important role in the biosynthesis of flavonoids in plants. So far, few studies are available on UFGT genes that may play a role in tartary buckwheat flavonoids biosynthesis. Here, we report on the identification and functional characterization of seven UFGTs from tartary buckwheat that are potentially involved in flavonoid biosynthesis (and have varying effects on plant growth and development when overexpressed in Arabidopsis thaliana.) Results: Phylogenetic analysis indicated that the potential function of the seven FtUFGT proteins, FtUFGT6, FtUFGT7, FtUFGT8, FtUFGT9, FtUFGT15, FtUFGT40, and FtUFGT41, could be divided into three Arabidopsis thaliana functional subgroups that are involved in flavonoid biosynthesis of and anthocyanin accumulation. A significant positive correlation between FtUFGT8 and FtUFGT15 expression and anthocyanin accumulation capacity was observed in the tartary buckwheat seedlings after cold stress. Overexpression in Arabidopsis thaliana showed that FtUFGT8, FtUFGT15, and FtUFGT41 significantly increased the anthocyanin content in transgenic plants. Unexpectedly, overexpression of FtUFGT6, while not leading to enhanced anthocyanin accumulation, significantly enhanced the growth yield of transgenic plants. When wild-type plants have only cotyledons, most of the transgenic plants of FtUFGT6 had grown true leaves. Moreover, the growth speed of the oxFtUFGT6 transgenic plant root was also significantly faster than that of the wild type. At later growth, FtUFGT6 transgenic plants showed larger leaves, earlier twitching times and more tillers than wild type, whereas FtUFGT15 showed opposite results. Conclusions: Seven FtUFGTs were isolated from tartary buckwheat. FtUFGT8, FtUFGT15, and FtUFGT41 can significantly increase the accumulation of total anthocyanins in transgenic plants. Furthermore, overexpression of FtUFGT6 increased the overall yield of Arabidopsis transgenic plants at all growth stages. However, FtUFGT15 shows the opposite trend at later growth stage and delays the growth speed of plants. These results suggested that the biological function of FtUFGT genes in tartary buckwheat is diverse

The Failure Criterion of Single-Layer Spherical Lattice Shell Based on Kinetic Energy

The dynamic failure criterion of single-layer spherical lattice shells has been an important research subject. The paper examines dynamic failures of single-layer spherical lattice shells and proposes the structure dynamic failure criterion based on the kinetic energy. The failure criterion was demonstrated through the dynamic failure test on a single-layer spherical lattice shell. Then, simulation analysis was carried out through two cases with material damage taken into account. The proposed failure criterion can accurately identify failure moments caused either by strength fracture or by stability fracture

Rehabilitation recognition skeleton data depth learning based on RNN

With the extensive application of deep learning in the field of human rehabilitation, skeleton based rehabilitation recognition is becoming more and more concerned with large-scale bone data sets. The key factor of this task is the two intra frame representations of the combined co-and the inter-frame. In this paper, an inter frame representation method based on RNN is proposed. Pointtion of each joint is joint-coded they are assembled into semantic both spatial and temporal domains.we introduce a global spatial aggregation which is able to learn superior joint co features over local aggregation

Validation of reference genes for gene expression studies in tartary buckwheat (Fagopyrum tataricum Gaertn.) using quantitative real-time PCR

Quantitative real-time reverse transcriptase polymerase chain reaction is a sensitive technique for quantifying gene expression levels. By implementing three distinct algorithms (geNorm, normFinder and BestKeeper), we have validated the stability of the expression of seven candidate reference genes in tartary buckwheat, including FtSAND, FtCACS, FtExpressed1, FtGAPDH, FtActin, FtEF-1a and FtH3. In this study, the results indicated that FtCACS and FtSAND were the best reference genes for ‘abiotic cotyledons’, FtExpressed1 and FtEF-1α were the best reference genes for aluminium treatment, FtCACS and FtExpressed1 performed the best for the immature seed stage, FtCACS was best for the abiotic treatment, and FtH3 appeared to be the most suitable reference gene for the abiotic treatment in hypocotyls and all samples in this study. In contrast, FtActin and FtGAPDH are unsuitable genes. Our findings offer additional stable reference genes for gene expression research on tartary buckwheat at the immature seed stage and under abiotic treatment

The prognostic significance of circulating plasma cells in newly diagnosed multiple myeloma patients

ObjectiveMultiple myeloma (MM) is a highly characteristic tumor that is influenced by numerous factors that determine its prognosis. Studies indicate that the presence of circulating plasma cells (cPCs) is a detrimental factor that significantly impacts the prognosis of patients with MM.MethodsThis study retrospectively analyzed the prognostic value of cPCs quantified by 10-color flow cytometry in 145 newly diagnosed MM (NDMM) cases in the First Affiliated Hospital of Soochow University from November 2018 to February 2021. The study was approved by the Ethics Committee of the hospital (2021 No. 93).ResultsOf the 145 patients, 99 (68.2%) were detected cPCs. Through receiver operating characteristics (ROC) analysis, an optimal threshold of 0.165% was identified as a predictor for overall survival (OS). The median progression-free survival (PFS) was 33 months in patients with cPCs ≥0.165%, whereas those with cPCs <0.165% had a PFS of <33 months (p=0.001). The median OS was not reached for two groups; the 3-year OS for patients with cPCs ≥0.165% was 71% compared with 87% for those with cPCs <0.165% (p=0.003). In transplant patients, cPCs ≥0.165% also predicted worse prognosis. Similarly, when considering cytogenetic risk factors in conjunction with cPC levels, comparable results were obtained. To evaluate whether the Revised International Staging System (R-ISS) groups could be further stratified based on different prognostic factors related to cPCs, our study revealed similar median PFS and OS rates in R-ISS II stage patients with cPCs ≥0.165% compared to those in the III stage (p=0.659 and 0.249, respectively).ConclusionThis study demonstrates that a high ratio of cPCs serves as a reliable indicator for predicting a poorer prognosis in MM cases. Furthermore, incorporating the R-ISS system and cytogenetic risk factors alongside the level of cPCs enhances the accuracy of prognostic predictions for patients with MM

A Comprehensive Pan-Cancer Analysis for Pituitary Tumor-Transforming Gene 1

Pituitary tumor-transforming gene 1 (PTTG1) encodes a multifunctional protein that is involved in many cellular processes. However, the potential role of PTTG1 in tumor formation and its prognostic function in human pan-cancer is still unknown. The analysis of gene alteration, PTTG1 expression, prognostic function, and PTTG1-related immune analysis in 33 types of tumors was performed based on various databases such as The Cancer Genome Atlas database, the Genotype-Tissue Expression database, and the Human Protein Atlas database. Additionally, PTTG1-related gene enrichment analysis was performed to investigate the potential relationship and possible molecular mechanisms between PTTG1 and tumors. Overexpression of PTTG1 may lead to tumor formation and poor prognosis in various tumors. Consequently, PTTG1 acts as a potential oncogene in most tumors. Additionally, PTTG1 is related to immune infiltration, immune checkpoints, tumor mutational burden, and microsatellite instability. Thus, PTTG1 could be potential biomarker for both prognosis and outcomes of tumor treatment and it could also be a promising target in tumor therapy

Identification of a hub gene VCL for atherosclerotic plaques and discovery of potential therapeutic targets by molecular docking

Abstract Background Atherosclerosis (AS) is a pathology factor for cardiovascular diseases and instability of atherosclerotic plaques contributes to acute coronary events. This study identified a hub gene VCL for atherosclerotic plaques and discovered its potential therapeutic targets for atherosclerotic plaques. Methods Differential expressed genes (DEGs) were screened between unstable and stable plaques from GSE120521 dataset and then used for construction of a protein-protein interactions (PPI) network. Through topological analysis, hub genes were identified within this PPI network, followed by construction of a diagnostic model. GSE41571 dataset was utilized to validate the diagnostic model. A key hub gene was identified and its association with immune characteristics and pathways were further investigated. Molecular docking and molecular dynamics (MD) simulation were employed to discover potential therapeutic targets. Results According to the PPI network, 3 tightly connected protein clusters were found. Topological analysis identified the top 5 hub genes, Vinculin (VCL), Dystrophin (DMD), Actin alpha 2 (ACTA2), Filamin A (FLNA), and transgelin (TAGLN). Among these hub genes, VCL had the highest diagnostic value. VCL was selected for further analysis and we found that VCL was negatively correlated with immune score and AS-related inflammatory pathways. Next, we identified 408 genes that were highly correlated with VCL and determined potential drug candidates. The results from molecular docking and MD simulation showed compound DB07117 combined with VCL protein stably, the binding energy is -7.7 kcal/mol, indicating that compound DB07117 was a potential inhibitor of VCL protein. Conclusion This study identified VCL as a key gene for atherosclerotic plaques and provides a potential therapeutic target of VCL for the treatment of atherosclerotic plaques

Catalytic Oxidative/Extractive Desulfurization of Model Oil using Transition Metal Substituted Phosphomolybdates-Based Ionic Liquids

Polyoxometalates based ionic liquids (POM-ILs) exhibit a high catalytic activity in oxidative desulfurization. In this paper, four new POM-IL hybrids based on transition metal mono-substituted Keggin-type phosphomolybdates, [Bmim]5[PMo11M(H2O)O39] (Bmim = 1-butyl 3-methyl imidazolium; M = Co2+, Ni2+, Zn2+, and Mn2+), have been synthesized and used as catalysts for the oxidation/extractive desulfurization of model oil, in which ILs are used as the extraction solvent and H2O2 as an oxidant under very mild conditions. The factors that affected the desulfurization efficiency were studied and the optimal reaction conditions were obtained. The results showed that the [Bmim]5[PMo11Co(H2O)O39] catalyst demonstrated the best catalytic activity, with sulfur-removal of 99.8%, 85%, and 63% for dibenzothiophene (DBT), 4,6-dimethyldibenzothiophene (4,6-DMDBT), and benzothiophene (BT), respectively, in the case of extraction combining with a oxidative desulfurization system under optimal reaction conditions (5 mL model oil (S content 500 ppm), n(catalyst) = 4 μmol, n(H2O2)/n(Substrate) = 5, T = 50 °C for 60 min with [Omim]BF4 (1 mL) as the extractant). The catalyst can be recycled at least 8 times, and still has stability and high catalytic activity for consecutive desulfurization. Probable reaction mechanisms have been proposed for catalytic oxidative/extractive desulfurization

Rehabilitation recognition skeleton data depth learning based on RNN

With the extensive application of deep learning in the field of human rehabilitation, skeleton based rehabilitation recognition is becoming more and more concerned with large-scale bone data sets. The key factor of this task is the two intra frame representations of the combined co-and the inter-frame. In this paper, an inter frame representation method based on RNN is proposed. Pointtion of each joint is joint-coded they are assembled into semantic both spatial and temporal domains.we introduce a global spatial aggregation which is able to learn superior joint co features over local aggregation