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  1. Article ; Online: SEER-Based Survival Nomogram (1998-2015) Based on 'Stage, Lymph Node Dissection, Tumor Size and Degree of Differentiation, and Therapies' for Prognosis of Primary Pulmonary Sarcoma.

    Gu, Hao / Song, Ruixia / Beeraka, Narasimha M / Li, Tingxuan / Zhao, Di / Liu, Junqi / Fan, Ruitai

    Technology in cancer research & treatment

    2023  Volume 22, Page(s) 15330338221150732

    Abstract: Objective: ...

    Abstract Objective:
    MeSH term(s) Humans ; Nomograms ; Prognosis ; Lung Neoplasms/therapy ; Lymph Node Excision ; Sarcoma ; SEER Program ; Neoplasm Staging
    Language English
    Publishing date 2023-01-31
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2146365-7
    ISSN 1533-0338 ; 1533-0346
    ISSN (online) 1533-0338
    ISSN 1533-0346
    DOI 10.1177/15330338221150732
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5871: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: Two human monoclonal SARS-CoV-2 antibodies that maintain neutralizing potency against the SARS-CoV-2 Omicron BA.1 and BA.2 variants

    Qianqian Zheng / Liangwei Duan / Zhihua Jiang / Tingxuan Gu / Bojie Zhang / Jiaoyang Li / Yang Zhang / Shiyu Zhang / Yinming Liang / Hui Wang

    Genes and Diseases, Vol 10, Iss 3, Pp 664-

    2023  Volume 667

    Keywords Medicine (General) ; R5-920 ; Genetics ; QH426-470
    Language English
    Publishing date 2023-05-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: MARS-GAN: Multilevel-Feature-Learning Attention-Aware Based Generative Adversarial Network for Removing Surgical Smoke.

    Hong, Tingxuan / Huang, Pu / Zhai, Xiangyu / Gu, Changming / Tian, Baolong / Jin, Bin / Li, Dengwang

    IEEE transactions on medical imaging

    2023  Volume 42, Issue 8, Page(s) 2299–2312

    Abstract: Surgical smoke caused poor visibility during laparoscopic surgery, the smoke removal is important to improve the safety and efficiency of the surgery. We propose the Multilevel-feature-learning Attention-aware based Generative Adversarial Network for ... ...

    Abstract Surgical smoke caused poor visibility during laparoscopic surgery, the smoke removal is important to improve the safety and efficiency of the surgery. We propose the Multilevel-feature-learning Attention-aware based Generative Adversarial Network for Removing Surgical Smoke (MARS-GAN) in this work. MARS-GAN incorporates multilevel smoke feature learning, smoke attention learning, and multi-task learning together. Specifically, the multilevel smoke feature learning adopts the multilevel strategy to adaptively learn non-homogeneity smoke intensity and area features with specific branches and integrates comprehensive features to preserve both semantic and textural information with pyramidal connections. The smoke attention learning extends the smoke segmentation module with the dark channel prior module to provide the pixel-wise measurement for focusing on the smoke features while preserving the smokeless details. And the multi-task learning strategy fuses the adversarial loss, cyclic consistency loss, smoke perception loss, dark channel prior loss, and contrast enhancement loss to help the model optimization. Furthermore, a paired smokeless/smoky dataset is synthesized for elevating smoke recognition ability. The experimental results show that MARS-GAN outperforms the comparative methods for removing surgical smoke on both synthetic/real laparoscopic surgical images, with the potential to be embedded in laparoscopic devices for smoke removal.
    MeSH term(s) Smoke ; Laparoscopy ; Semantics ; Attention ; Image Processing, Computer-Assisted
    Chemical Substances Smoke
    Language English
    Publishing date 2023-08-01
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 622531-7
    ISSN 1558-254X ; 0278-0062
    ISSN (online) 1558-254X
    ISSN 0278-0062
    DOI 10.1109/TMI.2023.3245298
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2546: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  4. Article: COVID-19 and Strategies for Its Therapeutics.

    Ma, Fayang / Gu, Tingxuan / Zhao, Simin / Liu, Kangdong / Dong, Zigang

    Critical reviews in immunology

    2021  Volume 40, Issue 6, Page(s) 513–526

    Abstract: Currently the epidemic of SARS-CoV-2-caused COVID-19 is a major threat to global public health. The latest clinical data, laboratory results, and autopsy information are summarized herein to provide a brief review of the significant issues surrounding ... ...

    Abstract Currently the epidemic of SARS-CoV-2-caused COVID-19 is a major threat to global public health. The latest clinical data, laboratory results, and autopsy information are summarized herein to provide a brief review of the significant issues surrounding SARS-CoV-2 and COVID-19. In this review, we also cover research on the ways in which the virus enters the human body, general clinical symptoms, immunopathological responses in severe cases of COVID-19, and the issues surrounding the potential therapeutic responses to the illness.
    MeSH term(s) COVID-19/pathology ; COVID-19/therapy ; COVID-19/virology ; Disease Management ; Disease Susceptibility ; Host-Pathogen Interactions/immunology ; Humans ; SARS-CoV-2/physiology
    Language English
    Publishing date 2021-04-26
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 1353116-5
    ISSN 1040-8401
    ISSN 1040-8401
    DOI 10.1615/CritRevImmunol.2020035633
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    Zs.A 1699: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: Acetylshikonin inhibits inflammatory responses and Papain-like protease activity in murine model of COVID-19.

    Lu, Ning / Gu, Tingxuan / Tian, Xueli / Zhao, Simin / Jin, Guoguo / Mangaladoss, Fredimoses / Qiao, Yan / Liu, Kangdong / Zhao, Ran / Dong, Zigang

    Signal transduction and targeted therapy

    2022  Volume 7, Issue 1, Page(s) 371

    MeSH term(s) Mice ; Animals ; Papain ; Disease Models, Animal ; COVID-19 ; Anthraquinones/pharmacology
    Chemical Substances acetylshikonin (ST04094S3X) ; Papain (EC 3.4.22.2) ; Anthraquinones
    Language English
    Publishing date 2022-10-27
    Publishing country England
    Document type Letter ; Research Support, Non-U.S. Gov't
    ZDB-ID 2886872-9
    ISSN 2059-3635 ; 2095-9907
    ISSN (online) 2059-3635
    ISSN 2095-9907
    DOI 10.1038/s41392-022-01220-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Two human monoclonal SARS-CoV-2 antibodies that maintain neutralizing potency against the SARS-CoV-2 Omicron BA.1 and BA.2 variants.

    Zheng, Qianqian / Duan, Liangwei / Jiang, Zhihua / Gu, Tingxuan / Zhang, Bojie / Li, Jiaoyang / Zhang, Yang / Zhang, Shiyu / Liang, Yinming / Wang, Hui

    Genes & diseases

    2022  Volume 10, Issue 3, Page(s) 664–667

    Language English
    Publishing date 2022-06-07
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2821806-1
    ISSN 2352-3042 ; 2352-3042
    ISSN (online) 2352-3042
    ISSN 2352-3042
    DOI 10.1016/j.gendis.2022.05.027
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Intratumoural delivery of TRAIL mRNA induces colon cancer cell apoptosis.

    Gu, Tingxuan / Wang, Mengqiao / Fu, Xiaorong / Tian, Xueli / Bi, Juanjuan / Lu, Ning / Chen, Chen / Yan, Shijia / Li, Ang / Wang, Luyun / Li, Xiang / Liu, Kangdong / Dong, Zigang

    Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie

    2024  Volume 174, Page(s) 116603

    Abstract: Novel strategies in intratumoral injection and emerging immunotherapies have heralded a new era of precise cancer treatments. The affinity of SARS-CoV-2 to ACE2 receptors, a feature which facilitates virulent human infection, is leveraged in this ... ...

    Abstract Novel strategies in intratumoral injection and emerging immunotherapies have heralded a new era of precise cancer treatments. The affinity of SARS-CoV-2 to ACE2 receptors, a feature which facilitates virulent human infection, is leveraged in this research. Colon cancer cells, with their high ACE2 expression, provide a potentially strategic target for using this SARS-CoV-2 feature. While the highly expression of ACE2 is observed in several cancer types, the idea of using the viral spike protein for targeting colon cancer cells offers a novel approach in cancer treatment. Intratumoral delivery of nucleic acid-based drugs is a promising alternative to overcoming the limitations of existing therapies. The increasing importance of nucleic acids in this realm, and the use of Lipid Nanoparticles (LNPs) for local delivery of nucleic acid therapeutics, are important breakthroughs. LNPs protect nucleic acid drugs from degradation and enhance cellular uptake, making them a rapidly evolving nano delivery system with high precision and adaptability. Our study leveraged a tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) combined with a receptor-binding domain from the SARS-CoV-2 spike protein, encapsulated in LNPs, to target colon cancer cells. Our results indicated that the TRAIL fusion-mRNA induced apoptosis in vitro and in vivo. Collectively, our findings highlight LNP-encapsulated TRAIL fusion-mRNA as a potential colon cancer therapy.
    Language English
    Publishing date 2024-04-17
    Publishing country France
    Document type Journal Article
    ZDB-ID 392415-4
    ISSN 1950-6007 ; 0753-3322 ; 0300-0893
    ISSN (online) 1950-6007
    ISSN 0753-3322 ; 0300-0893
    DOI 10.1016/j.biopha.2024.116603
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    Ud II Zs.198: Show issues Location:
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  8. Article ; Online: Interpretable machine learning assisted spectroscopy for fast characterization of biomass and waste.

    Liang, Rui / Chen, Chao / Sun, Tingxuan / Tao, Junyu / Hao, Xiaoling / Gu, Yude / Xu, Yaru / Yan, Beibei / Chen, Guanyi

    Waste management (New York, N.Y.)

    2023  Volume 160, Page(s) 90–100

    Abstract: The combination of machine learning and infrared spectroscopy was reported as effective for fast characterization of biomass and waste (BW). However, this characterization process is lack of interpretability towards its chemical insights, leading to less ...

    Abstract The combination of machine learning and infrared spectroscopy was reported as effective for fast characterization of biomass and waste (BW). However, this characterization process is lack of interpretability towards its chemical insights, leading to less satisfactory recognition for its reliability. Accordingly, this paper aimed to explore the chemical insights of the machine learning models in the fast characterization process. A novel dimensional reduction method with significant physicochemical meanings was thus proposed, where the high loading spectral peaks of BW were selected as input features. Combined with functional groups attribution of these spectral peaks, the machine learning models established based on the dimensionally reduced spectral data could be explained with clear chemical insights. The performance of classification and regression models between the proposed dimensional reduction method and principal component analysis method was compared. The influence mechanism of each functional group on the characterization results were discussed. CH deformation, CC stretch & CO stretch and ketone/aldehyde CO stretch played essential roles in C, H/ LHV and O prediction, respectively. The results of this work demonstrated the theoretical fundamentals of the machine learning and spectroscopy based BW fast characterization method.
    MeSH term(s) Reproducibility of Results ; Biomass ; Machine Learning ; Spectrum Analysis
    Language English
    Publishing date 2023-02-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2001471-5
    ISSN 1879-2456 ; 0956-053X
    ISSN (online) 1879-2456
    ISSN 0956-053X
    DOI 10.1016/j.wasman.2023.02.012
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Acetylshikonin inhibits inflammatory responses and Papain-like protease activity in murine model of COVID-19

    Ning Lu / Tingxuan Gu / Xueli Tian / Simin Zhao / Guoguo Jin / Fredimoses Mangaladoss / Yan Qiao / Kangdong Liu / Ran Zhao / Zigang Dong

    Signal Transduction and Targeted Therapy, Vol 7, Iss 1, Pp 1-

    2022  Volume 3

    Keywords Medicine ; R ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2022-10-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Molecular classification of human papilloma virus-negative head and neck squamous cell carcinomas

    Hao Gu / Tingxuan Li / Narasimha M. Beeraka / Yufei Zheng / Xintan Zhang / Ruixia Song / Runze Zhou / Xiaoyan Wang / Olga Sukocheva / Ruitai Fan / Junqi Liu

    PLoS ONE, Vol 18, Iss

    Cell cycle-based classifier and prognostic signature

    2023  Volume 10

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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