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فهرست مطالب نویسنده:

p. liu

  • Y. Zhou, Y. Bi, M. Wan, N. Xu, Y. Xu, P. Liu, H. Jiang, H. Fang, H. Hu, S. Xu*, S. Lan
    Background

    Conventional treatments on osteosarcoma (OS) yield limited improvements in metastatic or relapsed cases, necessitating innovative therapeutic strategies. This study's objective is to reveal the role of long non-coding RNAs (lncRNAs) in prognosis and potential molecular pathways of OS.

    Materials and Methods

    This study integrated bioinformatics, statistical analysis, and computational techniques to investigate m6A-related prognostic lncRNA clusters in OS. Consensus clustering and risk analysis were performed on the m6A-related prognostic lncRNAs. Nomogram model was built for survival prediction, and was assessed using survival time receiver operator characteristic (ROC) analysis and decision curves. A competitive endogenous RNA (ceRNA) network was built to explore lncRNA-miRNA (microRNA)-mRNA interactions using the microRNA database and metascape website, followed by functional enrichment analyses.

    Results

    The analysis unveiled three distinct OS clusters, with Cluster 2 exhibiting the highest risk in the immune microenvironment. High risk 7-lncRNA signature demonstrated strong prognostic value in predicting OS overall survival. The ceRNA network highlighted complex interactions among mRNAs, miRNAs and lncRNAs. Functional enrichment analysis indicated that mRNAs within the ceRNA network were linked to many biological functions. Furthermore, 30 differentially expressed genes (DEGs) derived from low-risk and high-risk groups enriched in GO-BP connected to MAGE (melanoma antigen gene) family member A2 (MAGEA2) and MAGEA2B. These DEGs in high risk group were also upregulated in the three KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway.

    Conclusion

    This study disclosed the role of high-risk m6A-associated lncRNAs in prognosis and potential molecular pathways of OS. These findings provided novel insights into OS pathogenesis and potential therapeutic targets, warranting further validation in clinical settings.

    Keywords: Osteosarcoma, Long Non-Coding RNA (Lncrna), M6a Modification, Prognosis, Chemoradiotherapy Response, Cerna Network
  • Y. Liu *, L. Wang, X. Peng, Y. Gu, Z. Zhou, P. Liu, L. Huang
    This paper studies the evolution and fluid distribution characteristics of a high-speed projectile’s cavity in the water based on joint research, a method involving experiment and numerical simulation. Specifically, we develop an experimental platform and a numerical calculation model for a high-speed projectile to observe its initial cavity evolution characteristics in the water at different velocities and close ranges. Additionally, this work investigates the evolution mechanism of the cavitation process and its fluid distribution law inside the cavity and studies the evolution characteristics of the cavitation stage under different velocities. The results reveal that after the projectile enters the water, the cavity is gourd-shaped and symmetrical, with a necking phenomenon at the tail and the cavity falling off. The cavitation process can be divided into the surface closure, saturation, deep closure, and collapse stages according to the fluid distribution changes in the cavity. Suppose the projectile has a certain speed with the water, its velocity increases. In that case, the cavity generation rate decreases, the growth rate of the water vapor volume in the cavity decreases, the peak water vapor volume content reduces, and the volume of air in the saturation phase of the cavity becomes increases having a range of 6% to 9%. Additionally, the cavity surface closure dimensionless time grows logarithmically as the velocity changes from 0 m/s to 500 m/s, the cavity saturation dimensionless time decreases approximately linearly, and the cavity depth closure dimensionless time is unaffected by velocity changes.
    Keywords: Cavity, Velocity, Fluid distribution characteristics, Projectiles, Numerical simulation
  • P. Liu *, T. Mahmood, Z. Ali
    The q-rung orthopair fuzzy set (q-ROFS) as a generalization of fuzzy set (FS), is characterized by membership and non-membership, and the sum of their q-powers is restricted to [0,1]. In this manuscript, a new Complex q-rung orthoapir fuzzy set (Cq-ROFS) is proposed by combining q-ROFS and complex fuzzy set (CFS). Cq-ROFS is a better way to process uncertain and imprecise information in decision making, which is characterized by complex-valued membership and complex-valued non-membership. First, some fundamental operational laws, score function and accuracy function, and comparison method are proposed. Further, because the vector similarity measures (VSMs) play a key role in statistics, physics and engineering sciences, some VSMs called Jaccard similarity measures (JSMs), dice similarity measures (DSMs) and cosine similarity measures (CSMs) for Cq-ROFSs and interval-valued complex q-rung orthopair fuzzy sets (IVCq-ROFSs) are investigated. Moreover, the hybrid vector similarity measures (HVSMs) called variation co-efficient similarity measures (VCSMs) for Cq-ROFSs and IVCq-ROFSs are also proposed and their properties are discussed. Finally, in order to demonstrate the feasibility of the investigated HVSMs, the existing similarity measures about complex Pythagorean fuzzy sets (CPFSs) and complex intuitionistic fuzzy sets (CIFSs) are compared with the proposed methods by numerical examples of medical diagnosis and pattern recognition.
    Keywords: Complex q-rung orthopair fuzzy sets, Interval-valued complex q-rung orthopair fuzzy sets, Jaccard Similarity measures, Hybrid vector similarity measures, Variation coefficient similarity measures
  • P. Liu *, W. Liu
    Linguistic Z-numbers (LZNs), as a more rational extension of linguistic description, not only consider the fuzzy restriction of assessment information but also take the reliability of the information into account. Maclaurin symmetric mean (MSM) operator has the advantage which can take account of interrelationship of different attributes and there are a lot of research results on it. However, it has not been used to handle multi-attribute decision-making (MADM) problems expressed by LZNs. To sum up the advantages of LZNs and MSM, in this paper, we present the linguistic Z-Numbers MSM (LZMSM) and linguistic Z-Numbers weight MSM (LZWMSM) operators, respectively, and several characters and several special cases of them are explored. Moreover, we propose an approach to handle some MADM problems by using LZWMSM operator. In the end, an example is given to illustrate the effectiveness and superiority of this new presented approach by comparing with several existing approaches.
    Keywords: linguistic Z-numbers, Maclaurin symmetric mean operator, Multi-attribute decision making
  • P. Liu, S. Wang, X. Fang, Z.D. Gao, W. Shao, L. Long, Y.C. Zhang*
    Background

    Radiation pneumonitis (RP) is a common complication of thoracic radiation which affects patients’ ability to breathe, limits the deliverable intensity of radiotherapy and impairs clinical outcomes, indicating the need for timely diagnosis and management. The purpose of this study was to determine the predictive capability of two peripheral inflammatory cells for RP.

    Materials and Methods

    A murine RP model was established using SD rats that received a single dose of 20 Gy thoracic radiation. At 2 and 4 weeks post-radiation, mice were processed to harvest lungs for hematoxylin-eosin (HE) staining and collect blood for flow cytometry analysis.

    Results

    By 2 weeks post-radiation, histopathological changes had occurred in the lungs indicating the onset of RP. Peripheral CD45+HIS48+ granulocytes were significantly increased by the radiation treatment at both the early and later time points (P<0.05). However, we did not observe a statistically significant increase of CD45+CD11b/c+HIS48- monocytes/macrophages.

    Conclusion

    Our study highlights the possibility that increased levels of peripheral CD45+HIS48+ granulocytes could serve as a predictive indicator of RP. Early detection provides the opportunity for early intervention and therefore, a reduction in the rate and extent of RP.

    Keywords: Radiation pneumonitis, granulocytes, monocytes, macrophages, peripheral, prediction
  • P. Liu *, X. Liu
    Considering the uncertainty of the natural state and the convenience of calculation, based on the third generation prospect theory (3-PT) and grey correlation analysis (GRA), we propose a method to solve the multi-attribute decision-making (MADM) problems where the attributes are described by the linguistic intuitionistic fuzzy numbers (LIFNs). Firstly, we transform the LIFNs into the belief structure that includes identity value and belief degree. Then, the evaluation information represented by belief structure is calculated by using the 3-PT, and the prospect matrix is gotten. The alternatives are ranked by the GRA. Finally, we use the proposed method to calculate an example and compare it with other methods to prove its effectiveness and superiority.
    Keywords: belief structure, third generation prospect theory, grey correlation analysis, Multi-attribute decision making
  • X. Zhang*, H. Liu, X. Xing, M. Tian, X. Hu, F. Liu, J. Feng, S. Chang, P. Liu, H. Zhang
    Backgrounds

    It remains unclear whether radiation-induced haemorrhage in the spleen causes iron accumulation, and subsequently, ferroptosis in splenic lymphocytes. In this study, we investigated the occurrence of ferroptosis in splenic lymphocytes of gamma-irradiated mice.

    Materials and Methods

    Mice were subjected to gamma radiation from a 137Cs source. Iron, Ferroportin 1, and iron regulatory protein (IRP) levels in the spleen, and serum iron and hepcidin levels in the blood were measured to study the change in iron metabolism of the irradiated spleen. After Ferrostatin 1/LDN193189 was intraperitoneally injected into mice post-irradiation, the viability of splenic lymphocytes and the splenic index were evaluated to investigate the mechanism of damage induction in splenic lymphocytes. The survival rate of mice was evaluated to identify the radiation mitigator based on the inhibition of ferroptosis.

    Results

    Iron accumulation (up to 0.62 g/g) observed in the spleen of irradiated mice was due to haemorrhage-based haemosiderin. The iron accumulation triggered the IRP-ferroportin 1 axis to increase the level of serum iron to 121.65 mmol/l. LDN193189 was used to demonstrate that the iron accumulation decreased the viability of splenic lymphocytes in irradiated mice, which was subsequently demonstrated to attribute to ferroptosis with the use of Ferrostatin 1 and through detection of ferroptosis-related parameters. The survival rate of irradiated mice was improved upon Ferrostatin-1 (60% with a duration of 120 days) or LDN193189 (40% for the same duration) treatment.

    Conclusion

    Radiation-induced haemorrhage causes ferroptosis in splenic lymphocytes, and anti-ferroptosis is a potential strategy to alleviate immune damage in hematopoietic acute radiation sickness.

    Keywords: Hematopoietic acute radiation sickness, iron metabolism, iron accumulation, splenic lymphocyte, ferroptosis
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