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  1. Article ; Online: Long noncoding RNA PENG upregulates PDZK1 expression by sponging miR-15b to suppress clear cell renal cell carcinoma cell proliferation.

    Qi, Yijun / Ma, Yuanzhen / Peng, Zhiqiang / Wang, Lei / Li, Lanxin / Tang, Yilan / He, Junqi / Zheng, Junfang

    Oncogene

    2020  Volume 39, Issue 22, Page(s) 4404–4420

    Abstract: PDZK1 downregulation was reported to independently predict poor prognosis of clear cell renal cell carcinoma (ccRCC) patients and induce ccRCC development and progression. However, the underlying mechanism of PDZK1 downregulation remains unknown. ... ...

    Abstract PDZK1 downregulation was reported to independently predict poor prognosis of clear cell renal cell carcinoma (ccRCC) patients and induce ccRCC development and progression. However, the underlying mechanism of PDZK1 downregulation remains unknown. Competing endogenous RNA (ceRNA) networks are emerging as new players in gene regulation and are associated with cancer development. ceRNAs regulate other RNA transcripts by competing for shared miRNAs. To investigate the role and mechanism of ceRNAs in PDZK1 downregulation and the development of ccRCC, we searched databases for miRNAs and lncRNAs that regulate PDZK1 expression in ccRCC tissues and assessed their effects in ccRCC. We found that miR-15b was expressed at higher levels in ccRCC tissues, and its upregulation was clinically associated with lower PDZK1 level, larger tumor size and shorter survival time of ccRCC patients. Conversely, a novel lncRNA (lncPENG) was expressed at a lower level in ccRCC tissues, and its downregulation was associated with the same effects as upregulation of miR-15b. Downregulation of miR-15b and upregulation of lncPENG resulted in a significant increase in PDZK1 level and inhibition of proliferation in vitro and in vivo. Mechanistically, lncPENG directly bound to miR-15b and effectively functioned as a sponge for miR-15b to modulate the expression of PDZK1. Thus, lncPENG may function as a ceRNA to attenuate miR-15b-dependent PDZK1 downregulation and inhibit cell proliferation, suggesting that it may be clinically valuable as a therapeutic target and a prognostic biomarker of ccRCC.
    MeSH term(s) Animals ; Base Sequence ; Biomarkers, Tumor ; Carcinoma, Renal Cell/genetics ; Carcinoma, Renal Cell/metabolism ; Carcinoma, Renal Cell/pathology ; Cell Line, Tumor ; Cell Proliferation/genetics ; Female ; Gene Expression Regulation, Neoplastic ; Genes, Reporter ; Heterografts ; Humans ; In Situ Hybridization, Fluorescence ; Kidney Neoplasms/genetics ; Kidney Neoplasms/metabolism ; Kidney Neoplasms/pathology ; Membrane Proteins/biosynthesis ; Membrane Proteins/genetics ; Mice, Inbred BALB C ; Mice, Nude ; MicroRNAs/antagonists & inhibitors ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Neoplasm Proteins/biosynthesis ; Neoplasm Proteins/genetics ; Prognosis ; RNA, Long Noncoding/genetics ; RNA, Neoplasm/antagonists & inhibitors ; RNA, Neoplasm/genetics ; RNA, Neoplasm/metabolism ; Random Allocation ; Sequence Analysis, RNA ; Tumor Stem Cell Assay ; Up-Regulation
    Chemical Substances Biomarkers, Tumor ; MIRN15 microRNA, human ; Membrane Proteins ; MicroRNAs ; Neoplasm Proteins ; PDZK1 protein, human ; RNA, Long Noncoding ; RNA, Neoplasm
    Language English
    Publishing date 2020-04-27
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 639046-8
    ISSN 1476-5594 ; 0950-9232
    ISSN (online) 1476-5594
    ISSN 0950-9232
    DOI 10.1038/s41388-020-1297-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Editorial for "Deep Learning k-Space-to-Image Reconstruction Facilitates High Spatial Resolution and Scan Time Reduction in Diffusion-Weighted Imaging Breast MRI".

    Peng, Qi

    Journal of magnetic resonance imaging : JMRI

    2023  

    Language English
    Publishing date 2023-11-27
    Publishing country United States
    Document type Editorial
    ZDB-ID 1146614-5
    ISSN 1522-2586 ; 1053-1807
    ISSN (online) 1522-2586
    ISSN 1053-1807
    DOI 10.1002/jmri.29159
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: PT-symmetric PINN for integrable nonlocal equations: Forward and inverse problems.

    Peng, Wei-Qi / Chen, Yong

    Chaos (Woodbury, N.Y.)

    2024  Volume 34, Issue 4

    Abstract: Since the PT-symmetric nonlocal equations contain the physical information of the PT-symmetric, it is very appropriate to embed the physical information of the PT-symmetric into the loss function of PINN, named PTS-PINN. For general PT-symmetric nonlocal ...

    Abstract Since the PT-symmetric nonlocal equations contain the physical information of the PT-symmetric, it is very appropriate to embed the physical information of the PT-symmetric into the loss function of PINN, named PTS-PINN. For general PT-symmetric nonlocal equations, especially those equations involving the derivation of nonlocal terms due to the existence of nonlocal terms, directly using the original PINN method to solve such nonlocal equations will face certain challenges. This problem can be solved by the PTS-PINN method, which can be illustrated in two aspects. First, we treat the nonlocal term of the equation as a new local component so that the equation is coupled at this time. In this way, we successfully avoid differentiating nonlocal terms in neural networks. On the other hand, in order to improve the accuracy, we make a second improvement, which is to embed the physical information of the PT-symmetric into the loss function. Through a series of independent numerical experiments, we evaluate the efficacy of PTS-PINN in tackling the forward and inverse problems for the nonlocal NLS equation, the nonlocal derivative NLS equation, the nonlocal (2+1)-dimensional NLS equation, and the nonlocal three-wave interaction systems. The numerical experiments demonstrate that PTS-PINN has good performance. In particular, PTS-PINN has also demonstrated an extraordinary ability to learn large space-time scale rogue waves for nonlocal equations.
    Language English
    Publishing date 2024-04-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1472677-4
    ISSN 1089-7682 ; 1054-1500
    ISSN (online) 1089-7682
    ISSN 1054-1500
    DOI 10.1063/5.0197939
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Ferroptosis-mediated immune responses in cancer.

    Qi, Desheng / Peng, Milin

    Frontiers in immunology

    2023  Volume 14, Page(s) 1188365

    Abstract: Cell death is a universal biological process in almost every physiological and pathological condition, including development, degeneration, inflammation, and cancer. In addition to apoptosis, increasing numbers of cell death types have been discovered in ...

    Abstract Cell death is a universal biological process in almost every physiological and pathological condition, including development, degeneration, inflammation, and cancer. In addition to apoptosis, increasing numbers of cell death types have been discovered in recent years. The biological significance of cell death has long been a subject of interest and exploration and meaningful discoveries continue to be made. Ferroptosis is a newfound form of programmed cell death and has been implicated intensively in various pathological conditions and cancer therapy. A few studies show that ferroptosis has the direct capacity to kill cancer cells and has a potential antitumor effect. As the rising role of immune cells function in the tumor microenvironment (TME), ferroptosis may have additional impact on the immune cells, though this remains unclear. In this study we focus on the ferroptosis molecular network and the ferroptosis-mediated immune response, mainly in the TME, and put forward novel insights and directions for cancer research in the near future.
    MeSH term(s) Humans ; Ferroptosis ; Apoptosis ; Neoplasms ; Cell Death ; Inflammation ; Tumor Microenvironment
    Language English
    Publishing date 2023-05-30
    Publishing country Switzerland
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 2606827-8
    ISSN 1664-3224 ; 1664-3224
    ISSN (online) 1664-3224
    ISSN 1664-3224
    DOI 10.3389/fimmu.2023.1188365
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Identification and Characterization of a Plant Endophytic Fungus

    Shan, Jie / Peng, Fangren / Yu, Jinping / Li, Qi

    Journal of fungi (Basel, Switzerland)

    2024  Volume 10, Issue 2

    Abstract: Endophytic fungi establish mutualistic relationships with host plants and can promote the growth and development of plants. In this study, the endophytic fungus JRF11 was isolated ... ...

    Abstract Endophytic fungi establish mutualistic relationships with host plants and can promote the growth and development of plants. In this study, the endophytic fungus JRF11 was isolated from
    Language English
    Publishing date 2024-01-31
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2784229-0
    ISSN 2309-608X ; 2309-608X
    ISSN (online) 2309-608X
    ISSN 2309-608X
    DOI 10.3390/jof10020120
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Industrial Process Monitoring Based on Dynamic Overcomplete Broad Learning Network.

    Peng, Chang / Ying, Xu / ZhiQi, Hu

    IEEE transactions on neural networks and learning systems

    2024  Volume 35, Issue 2, Page(s) 1761–1772

    Abstract: Most industrial processes feature high nonlinearity, non-Gaussianity, and time correlation. Models based on overcomplete broad learning system (OBLS) have been successfully applied in the fault monitoring realm, which may relatively deal with the ... ...

    Abstract Most industrial processes feature high nonlinearity, non-Gaussianity, and time correlation. Models based on overcomplete broad learning system (OBLS) have been successfully applied in the fault monitoring realm, which may relatively deal with the nonlinear and non-Gaussian characteristics. However, these models barely take time correlation into full consideration, hindering the further improvement of the monitoring accuracy of the network. Therefore, an effective dynamic overcomplete broad learning system (DOBLS) based on matrix extension is proposed, which extends the raw data in the batch process with the idea of "time lag" in this article. Subsequently, the OBLS monitoring network is employed to continue the analysis of the extended dynamic input data. Finally, a monitoring model is established to tackle the coexistence of nonlinearity, non-Gaussianity, and time correlation in process data. To illustrate the superiority and feasibility, the proposed model is conducted on the penicillin fermentation simulation platform, the experimental result of which illustrates that the model can extract the feature of process data more comprehensively and be self-updated more efficiently. With shorter training time and higher monitoring accuracy, the proposed model can witness an improvement of average monitoring accuracy by 3.69% and 1.26% in 26 process fault types compared to the state-of-the-art fault monitoring methods BLS and OBLS, respectively.
    Language English
    Publishing date 2024-02-05
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2022.3185167
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Exploring into the Unseen: Enhancing Language-Conditioned Policy Generalization with Behavioral Information.

    Cao, Longhui / Wang, Chao / Qi, Juntong / Peng, Yan

    Cyborg and bionic systems (Washington, D.C.)

    2024  Volume 5, Page(s) 84

    Abstract: Generalizing policies learned by agents in known environments to unseen domains is an essential challenge in advancing the development of reinforcement learning. Lately, language-conditioned policies have underscored the pivotal role of linguistic ... ...

    Abstract Generalizing policies learned by agents in known environments to unseen domains is an essential challenge in advancing the development of reinforcement learning. Lately, language-conditioned policies have underscored the pivotal role of linguistic information in the context of cross-environments. Integrating both environmental and textual information into the observation space enables agents to accomplish similar tasks across different scenarios. However, for entities with varying forms of motion but the same name present in observations (e.g., immovable mage and fleeing mage), existing methods are unable to learn the motion information the entities possess well. They face the problem of ambiguity caused by motion. In order to tackle this challenge, we propose the entity mapper with multi-modal attention based on behavior prediction (EMMA-BBP) framework, comprising modules for predicting motion behavior and text matching. The behavioral prediction module is used to determine the motion information of the entities present in the environment to eliminate the semantic ambiguity of the motion information. The role of the text-matching module is to match the text given in the environment with the information about the entity's behavior under observation, thus eliminating false textual information. EMMA-BBP has been tested in the demanding environment of MESSENGER, doubling the generalization ability of EMMA.
    Language English
    Publishing date 2024-01-26
    Publishing country United States
    Document type Journal Article
    ISSN 2692-7632
    ISSN (online) 2692-7632
    DOI 10.34133/cbsystems.0084
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Leave It to Large Language Models! Correction and Planning with Memory Integration.

    Zhang, Yuan / Wang, Chao / Qi, Juntong / Peng, Yan

    Cyborg and bionic systems (Washington, D.C.)

    2024  Volume 5, Page(s) 87

    Abstract: As humans, we can naturally break down a task into individual steps in our daily lives and we are able to provide feedback or dynamically adjust the plan when encountering obstacles. Similarly, our aim is to facilitate agents in comprehending and ... ...

    Abstract As humans, we can naturally break down a task into individual steps in our daily lives and we are able to provide feedback or dynamically adjust the plan when encountering obstacles. Similarly, our aim is to facilitate agents in comprehending and carrying out natural language instructions in a more efficient and cost-effective manner. For example, in Vision-Language Navigation (VLN) tasks, the agent needs to understand instructions such as "go to the table by the fridge". This understanding allows the agent to navigate to the table and infer that the destination is likely to be in the kitchen. The traditional VLN approach mainly involves training models using a large number of labeled datasets for task planning in unseen environments. However, manual labeling incurs a high cost for this approach. Considering that large language models (LLMs) already possess extensive commonsense knowledge during pre-training, some researchers have started using LLMs as decision modules in embodied tasks, although this approach shows the LLMs' reasoning ability to plan a logical sequence of subtasks based on global information. However, executing subtasks often encounters issues, such as obstacles that hinder progress and alterations in the state of the target object. Even one mistake can cause the subsequent tasks to fail, which makes it challenging to complete the instructions through a single plan. Therefore, we propose a new approach-C (Correction) and P (Planning) with M (Memory) I (Integration)-that centered on an LLM for embodied tasks. In more detail, the auxiliary modules of the CPMI facilitate dynamic planning by the LLM-centric planner. These modules provide the agent with memory and generalized experience mechanisms to fully utilize the LLM capabilities, allowing it to improve its performance during execution. Finally, the experimental results on public datasets demonstrate that we achieve the best performance in the few-shot scenario, improving the efficiency of the successive task while increasing the success rate.
    Language English
    Publishing date 2024-03-27
    Publishing country United States
    Document type Journal Article
    ISSN 2692-7632
    ISSN (online) 2692-7632
    DOI 10.34133/cbsystems.0087
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Linear verrucous epidermal nevus on penis.

    Qi, Tengfei / Peng, Chen / Cheng, Yuanyuan

    Minerva pediatrics

    2023  Volume 75, Issue 4, Page(s) 636–637

    MeSH term(s) Male ; Humans ; Nevus, Sebaceous of Jadassohn/diagnosis ; Skin Neoplasms ; Nevus ; Pelvis ; Penis
    Language English
    Publishing date 2023-02-28
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 3062664-X
    ISSN 2724-5780
    ISSN (online) 2724-5780
    DOI 10.23736/S2724-5276.23.07188-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Mid-infrared Photons Released by NAD

    Peng, Daoling / Qi, Wenpeng / Zhang, Feng / Song, Bo

    Neuroscience bulletin

    2023  Volume 39, Issue 7, Page(s) 1146–1150

    MeSH term(s) Citric Acid Cycle ; NAD/metabolism ; Photons ; Neurons/metabolism
    Chemical Substances NAD (0U46U6E8UK)
    Language English
    Publishing date 2023-03-15
    Publishing country Singapore
    Document type Letter ; Research Support, Non-U.S. Gov't
    ZDB-ID 2419741-5
    ISSN 1995-8218 ; 1673-7067
    ISSN (online) 1995-8218
    ISSN 1673-7067
    DOI 10.1007/s12264-023-01044-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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