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  1. Article ; Online: Ferroptosis

    Wanqing Xie / Shivani Agarwal / Jindan Yu

    The Journal of Clinical Investigation, Vol 133, Iss

    the vulnerability within a cancer monster

    2023  Volume 10

    Abstract: Treatment-resistant cancer, such as neuroendocrine prostate cancer (NEPC), is a lethal disease with limited therapeutic options. RB1 is a tumor suppressor gene that is lost in a majority of NEPC tumors. In this issue of the JCI, Wang and colleagues ... ...

    Abstract Treatment-resistant cancer, such as neuroendocrine prostate cancer (NEPC), is a lethal disease with limited therapeutic options. RB1 is a tumor suppressor gene that is lost in a majority of NEPC tumors. In this issue of the JCI, Wang and colleagues examined how RB1 loss may sensitize cancer cells to ferroptosis inducers through elevation of ACSL4, a key enzyme that promotes lipid peroxidation and triggers ferroptosis. We discuss a high potential of RB1-deficient cells to undergo ferroptosis due to the elevation of ACSL4. This is normally kept in check by abundant expression of GPX4, an antioxidant enzyme, in cancer cells. This balance, however, is tilted by GPX4 inhibitors, leading to massive ferroptosis. We highlight possible therapeutic strategies that exploit this inherent vulnerability for targeting RB1-deficient, treatment-resistant cancer.
    Keywords Medicine ; R
    Language English
    Publishing date 2023-05-01T00:00:00Z
    Publisher American Society for Clinical Investigation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Assessment of Transcatheter or Surgical Closure of Atrial Septal Defect using Interpretable Deep Keypoint Stadiometry

    Jing Wang / Wanqing Xie / Mingmei Cheng / Qun Wu / Fangyun Wang / Pei Li / Bo Fan / Xin Zhang / Binbin Wang / Xiaofeng Liu

    Research, Vol

    2022  Volume 2022

    Abstract: Automated echocardiogram interpretation with artificial intelligence (AI) has the potential to facilitate the serial diagnosis of heart defects by primary clinician. However, the fully automated and interpretable analysis pipeline for suggesting a ... ...

    Abstract Automated echocardiogram interpretation with artificial intelligence (AI) has the potential to facilitate the serial diagnosis of heart defects by primary clinician. However, the fully automated and interpretable analysis pipeline for suggesting a treatment plan is largely underexplored. The present study targets to build an automatic and interpretable assistant for the transthoracic echocardiogram- (TTE-) based assessment of atrial septal defect (ASD) with deep learning (DL). We developed a novel deep keypoint stadiometry (DKS) model, which learns to precisely localize the keypoints, i.e., the endpoints of defects and followed by the absolute distance measurement with the scale. The closure plan and the size of the ASD occluder for transcatheter closure are derived based on the explicit clinical decision rules. A total of 3,474 2D and Doppler TTE from 579 patients were retrospectively collected from two clinical groups. The accuracy of closure classification using DKS (0.9425±0.0052) outperforms the “black-box” model (0.7646±0.0068; p<0.0001) for within-center evaluation. The results in cross-center cases or using the quadratic weighted kappa as an evaluation metric are consistent. The fine-grained keypoint label provides more explicit supervision for network training. While DKS can be fully automated, clinicians can intervene and edit at different steps of the process as well. Our deep learning keypoint localization can provide an automatic and transparent way for assessing size-sensitive congenital heart defects, which has huge potential value for application in primary medical institutions in China. Also, more size-sensitive treatment planning tasks may be explored in the future.
    Keywords Science ; Q
    Subject code 006
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher American Association for the Advancement of Science
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Chemokine receptor CXCR7 activates Aurora Kinase A and promotes neuroendocrine prostate cancer growth

    Galina Gritsina / Ka-wing Fong / Xiaodong Lu / Zhuoyuan Lin / Wanqing Xie / Shivani Agarwal / Dong Lin / Gary E. Schiltz / Himisha Beltran / Eva Corey / Colm Morrissey / Yuzhuo Wang / Jonathan C. Zhao / Maha Hussain / Jindan Yu

    The Journal of Clinical Investigation, Vol 133, Iss

    2023  Volume 15

    Abstract: CXCR7 is an atypical chemokine receptor that recruits β-arrestin (ARRB2) and internalizes into clathrin-coated intracellular vesicles where the complex acts as a scaffold for cytoplasmic kinase assembly and signal transduction. Here, we report that CXCR7 ...

    Abstract CXCR7 is an atypical chemokine receptor that recruits β-arrestin (ARRB2) and internalizes into clathrin-coated intracellular vesicles where the complex acts as a scaffold for cytoplasmic kinase assembly and signal transduction. Here, we report that CXCR7 was elevated in the majority of prostate cancer (PCa) cases with neuroendocrine features (NEPC). CXCR7 markedly induced mitotic spindle and cell cycle gene expression. Mechanistically, we identified Aurora Kinase A (AURKA), a key regulator of mitosis, as a novel target that was bound and activated by the CXCR7-ARRB2 complex. CXCR7 interacted with proteins associated with microtubules and golgi, and, as such, the CXCR7-ARRB2-containing vesicles trafficked along the microtubules to the pericentrosomal golgi apparatus, where the complex interacted with AURKA. Accordingly, CXCR7 promoted PCa cell proliferation and tumor growth, which was mitigated by AURKA inhibition. In summary, our study reveals a critical role of CXCR7-ARRB2 in interacting and activating AURKA, which can be targeted by AURKA inhibitors to benefit a subset of patients with NEPC.
    Keywords Oncology ; Medicine ; R
    Subject code 571
    Language English
    Publishing date 2023-08-01T00:00:00Z
    Publisher American Society for Clinical Investigation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Research on Characteristic of Chronic Spontaneous Urticaria Based on Multiscale Entropy

    Shujuan Wang / Ping Song / Rong Ma / Yanzhong Wang / Bin Yu / Min Wang / Meiqi Wang / Jihong Shen / Yuntao Dai / Yuming Wang / Wanqing Xie

    Computational and Mathematical Methods in Medicine, Vol

    2021  Volume 2021

    Abstract: Chronic spontaneous urticaria (CSU) is a common skin disease which symptom is local pruritus and pain. In medicine, researchers take a certain point that the brain is the control center of CSU, but in previous experiments, the researchers found that ... ...

    Abstract Chronic spontaneous urticaria (CSU) is a common skin disease which symptom is local pruritus and pain. In medicine, researchers take a certain point that the brain is the control center of CSU, but in previous experiments, the researchers found that cerebellum also had a certain effect on CSU. In order to find out the influence of CSU in the brain and cerebellum, we collected the brain resting-state fMRI data from 40 healthy controls and 32 CSU patients and used DPABI to preprocess. We calculated the entropy values of five scales by using multiscale entropy (MSE) and the average entropy values of two groups’ BOLD signals; 15 regions with significant differences were found which not only had a more detailed impact in the brain but also had an impact in the cerebellum, such as precentral gyrus, lenticular putamen, and vermis of cerebellum. In addition, we found that compared with the healthy controls, the entropy values of CSU patients showed two trends which need further study. The advantage of our experiment is that the multiscale entropy value is used to get more influence regions of CSU in the brain and cerebellum. The results of this paper may provide some help for the pathological study of CSU.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 616
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Robust Adaptive Switching Control for Markovian Jump Nonlinear Systems via Backstepping Technique

    Jin Zhu / Hongsheng Xi / Qiang Ling / Wanqing Xie

    Journal of Applied Mathematics, Vol

    2012  Volume 2012

    Keywords Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Mathematics ; DOAJ:Mathematics and Statistics
    Language English
    Publishing date 2012-01-01T00:00:00Z
    Publisher Hindawi Publishing Corporation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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