Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC.

In order to track complex-path tasks in three dimensional space without joint-drifts, a neural-dynamic based synchronous-optimization (NDSO) scheme of dual redundant robot manipulators is proposed and developed. To do so, an acceleration-level repetitive motion planning optimization criterion is derived by the neural-dynamic method twice. Position and velocity feedbacks are taken into account to decrease the errors. Considering the joint-angle, joint-velocity, and joint-acceleration limits, the redundancy resolution problem of the left and right arms are formulated as two quadratic programming problems subject to equality constraints and three bound constraints. The two quadratic programming schemes of the left and right arms are then integrated into a standard quadratic programming problem constrained by an equality constraint and a bound constraint. As a real-time solver, a linear variational inequalities-based primal-dual neural network (LVI-PDNN) is used to solve the quadratic programming problem. Finally, the simulation section contains experiments of the execution of three complex tasks including a couple task, the comparison with pseudo-inverse method and robustness verification. Simulation results verify the efficacy and accuracy of the proposed NDSO scheme.

Background: By using network pharmacology and molecular docking technology, we have explored the mechanism of action of Sanqi in the treatment of endometriosis (EMS), in order to provide reference for clinical studies of Chinese medicine treatment of Ems and Chinese medicine pharmacology. Methods: There are 123 intersecting targets between the active ingredients of Sanqi and disease targets. In the Protein-Protein Interaction network, Jun proto-oncogene, AP-1 transcription factor subunit, tumor necrosis factor, interleukin 6, etc., are the core proteins. The top 20 genes ranked by degree have been analyzed according to the Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analysis, and 20 pathways have been identified. Results: On the Kyoto Encyclopedia of Genes and Genomes pathway, the most important part is the phosphatidylinositol 3’-kinase-Akt signaling pathway, and on the Gene Ontology pathway, it is the Heme binding. The top 3 targets docked to quercetin have a certain affinity when it is docked to their degree value. Among the chemical components of Sanqi, quercetin has the most targets, suggesting that it may play a major role in the treatment of EMS. Conclusion: The results of molecular docking provide further evidence of the potential role of Sanqi for EMS. Overall, our study provides a new direction for the treatment of EMS and provides the basis for Sanqi as a drug for the treatment of EMS.

Extracellular vesicles (EVs) have become a research hotspot in recent years because they act as messengers between cells in the physiological and pathological processes of the human body. It can be produced by the follicle, prostate, embryo, uterus, and oviduct in the reproductive field and exists in the extracellular environment as follicular fluid, semen, uterine cavity fluid, and oviduct fluid. Because extracellular vesicles are more stable at transmitting information, it allows all cells involved in the physiological processes of embryo formation, development, and implantation to communicate with one another. Extracellular vesicles carried miRNAs and proteins as mail, and when the messenger delivers the mail to the recipient cell, the recipient cell undergoes a series of changes. Current research begins with intercepting and decoding the information carried by extracellular vesicles. This information may help us gain a better understanding of the secrets of reproduction, as well as assist reproductive technology as an emerging marker and treatment.

OBJECTIVE:To investigate the potential prognostic value of necroptosis-associated lncRNAs (NALncRNAs)in patients with ovarian cancer.METHODS: Gene expression data from ovarian cancer patients with clinical data were downloaded from TCGA database. This is the base data for screening NALncRNAs that represent different survival times.lncRNA risk models were constructed by Cox regression analysis and evaluated for their prognostic value. The link between lncRNA signatures and related pathways, immune cell activity, immunological checkpoints, m6A-related genes, and gene mutations was also investigated. RESULTS: In this study, eight NALncRNAs including USP30-AS1, MINCR, LINC01096, DNM3OS, LINC02574, DTNB-AS1, ACAP2-IT1, and ILVBL-AS1, all of which were well represented for the outcome of ovarian cancer patients. Noemogram after calibration curve validation has good clinical utility. Risk signatures were shown to be abundant in various pathways related to immunology and cell proliferation, according to gene set enrichment analysis. Patients' late survival outcome corresponds to differences in immune cells, immune checkpoints, immune function, etc.A better immune microenvironment would facilitate late survival, but inexplicably patients with long survival times have a higher immune escape. Patients with high mutations in genes appear to have better survival outcomes.CONCLUSION: This study identified eight NALncRNAs markers for the first time, providing a valuable basis for more accurate prediction of ovarian cancer prognosis.