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  1. Article ; Online: Zea mays

    Jia, Qiong / Sun, Jiahua / Gan, Qiuyu / Shi, Nan-Nan / Fu, Shenglei

    Microbiology spectrum

    2024  Volume 12, Issue 4, Page(s) e0342723

    Abstract: Plant cultivation can influence the immobilization of heavy metals in soil. However, the roles of soil amendments and microorganisms in crop-based phytoremediation require further exploration. In this study, we evaluated the impact ... ...

    Abstract Plant cultivation can influence the immobilization of heavy metals in soil. However, the roles of soil amendments and microorganisms in crop-based phytoremediation require further exploration. In this study, we evaluated the impact of
    MeSH term(s) Mycorrhizae ; Zea mays/microbiology ; Plant Roots/microbiology ; Lead ; Soil Pollutants ; Metals, Heavy ; Soil ; Charcoal
    Chemical Substances biochar ; Lead (2P299V784P) ; Soil Pollutants ; Metals, Heavy ; Soil ; Charcoal (16291-96-6)
    Language English
    Publishing date 2024-02-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2807133-5
    ISSN 2165-0497 ; 2165-0497
    ISSN (online) 2165-0497
    ISSN 2165-0497
    DOI 10.1128/spectrum.03427-23
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Visual-Tactile Fused Graph Learning for Object Clustering.

    Zhang, Tao / Cong, Yang / Sun, Gan / Dong, Jiahua

    IEEE transactions on cybernetics

    2022  Volume 52, Issue 11, Page(s) 12275–12289

    Abstract: Object clustering has received considerable research attention most recently. However, 1) most existing object clustering methods utilize visual information while ignoring important tactile modality, which would inevitably lead to model performance ... ...

    Abstract Object clustering has received considerable research attention most recently. However, 1) most existing object clustering methods utilize visual information while ignoring important tactile modality, which would inevitably lead to model performance degradation and 2) simply concatenating visual and tactile information via multiview clustering method can make complementary information to not be fully explored, since there are many differences between vision and touch. To address these issues, we put forward a graph-based visual-tactile fused object clustering framework with two modules: 1) a modality-specific representation learning module M
    MeSH term(s) Algorithms ; Attention ; Cluster Analysis ; Learning ; Touch
    Language English
    Publishing date 2022-10-17
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2021.3080321
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: PFDN: Pyramid Feature Decoupling Network for Single Image Deraining.

    Wang, Qiang / Sun, Gan / Dong, Jiahua / Zhang, Yulun

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

    2022  Volume 31, Page(s) 7091–7101

    Abstract: Restoring images degraded by rain has attracted more academic attention since rain streaks could reduce the visibility of outdoor scenes. However, most existing deraining methods attempt to remove rain while recovering details in a unified framework, ... ...

    Abstract Restoring images degraded by rain has attracted more academic attention since rain streaks could reduce the visibility of outdoor scenes. However, most existing deraining methods attempt to remove rain while recovering details in a unified framework, which is an ideal and contradictory target in the image deraining task. Moreover, the relative independence of rain streak features and background features is usually ignored in the feature domain. To tackle these challenges above, we propose an effective Pyramid Feature Decoupling Network (i.e., PFDN) for single image deraining, which could accomplish image deraining and details recovery with the corresponding features. Specifically, the input rainy image features are extracted via a recurrent pyramid module, where the features for the rainy image are divided into two parts, i.e., rain-relevant and rain-irrelevant features. Afterwards, we introduce a novel rain streak removal network for rain-relevant features and remove the rain streak from the rainy image by estimating the rain streak information. Benefiting from lateral outputs, we propose an attention module to enhance the rain-irrelevant features, which could generate spatially accurate and contextually reliable details for image recovery. For better disentanglement, we also enforce multiple causality losses at the pyramid features to encourage the decoupling of rain-relevant and rain-irrelevant features from the high to shallow layers. Extensive experiments demonstrate that our module can well model the rain-relevant information over the domain of the feature. Our framework empowered by PFDN modules significantly outperforms the state-of-the-art methods on single image deraining with multiple widely-used benchmarks, and also shows superiority in the fully-supervised domain.
    Language English
    Publishing date 2022-11-14
    Publishing country United States
    Document type Journal Article
    ISSN 1941-0042
    ISSN (online) 1941-0042
    DOI 10.1109/TIP.2022.3219227
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With COVID-19 Pneumonia: A Retrospective Case-Control Study.

    Gan, Jiahua / Li, Jingjing / Li, Shusheng / Yang, Chunguang

    Frontiers in public health

    2020  Volume 8, Page(s) 299

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Adult ; Aged ; COVID-19/epidemiology ; Case-Control Studies ; Cytokines/blood ; Female ; Humans ; Leukocyte Count ; Lymphocyte Subsets ; Male ; Middle Aged ; Pneumonia ; Retrospective Studies ; SARS-CoV-2 ; Young Adult
    Chemical Substances Cytokines
    Keywords covid19
    Language English
    Publishing date 2020-06-18
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2711781-9
    ISSN 2296-2565
    ISSN 2296-2565
    DOI 10.3389/fpubh.2020.00299
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer.

    Long, Gongwei / Ouyang, Wei / Zhang, Yucong / Sun, Guoliang / Gan, Jiahua / Hu, Zhiquan / Li, Heng

    Frontiers in molecular biosciences

    2021  Volume 8, Page(s) 608369

    Abstract: Background: ...

    Abstract Background:
    Language English
    Publishing date 2021-03-11
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2814330-9
    ISSN 2296-889X
    ISSN 2296-889X
    DOI 10.3389/fmolb.2021.608369
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud Representation.

    Dong, Jiahua / Cong, Yang / Sun, Gan / Wang, Lixu / Lyu, Lingjuan / Li, Jun / Konukoglu, Ender

    IEEE transactions on neural networks and learning systems

    2023  Volume 34, Issue 10, Page(s) 6955–6967

    Abstract: 3-D object recognition has successfully become an appealing research topic in the real world. However, most existing recognition models unreasonably assume that the categories of 3-D objects cannot change over time in the real world. This unrealistic ... ...

    Abstract 3-D object recognition has successfully become an appealing research topic in the real world. However, most existing recognition models unreasonably assume that the categories of 3-D objects cannot change over time in the real world. This unrealistic assumption may result in significant performance degradation for them to learn new classes of 3-D objects consecutively due to the catastrophic forgetting on old learned classes. Moreover, they cannot explore which 3-D geometric characteristics are essential to alleviate the catastrophic forgetting on old classes of 3-D objects. To tackle the above challenges, we develop a novel Incremental 3-D Object Recognition Network (i.e., InOR-Net), which could recognize new classes of 3-D objects continuously by overcoming the catastrophic forgetting on old classes. Specifically, category-guided geometric reasoning is proposed to reason local geometric structures with distinctive 3-D characteristics of each class by leveraging intrinsic category information. We then propose a novel critic-induced geometric attention mechanism to distinguish which 3-D geometric characteristics within each class are beneficial to overcome the catastrophic forgetting on old classes of 3-D objects while preventing the negative influence of useless 3-D characteristics. In addition, a dual adaptive fairness compensations' strategy is designed to overcome the forgetting brought by class imbalance by compensating biased weights and predictions of the classifier. Comparison experiments verify the state-of-the-art performance of the proposed InOR-Net model on several public point cloud datasets.
    Language English
    Publishing date 2023-10-05
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2023.3247490
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Open-Ended Online Learning for Autonomous Visual Perception.

    Yu, Haibin / Cong, Yang / Sun, Gan / Hou, Dongdong / Liu, Yuyang / Dong, Jiahua

    IEEE transactions on neural networks and learning systems

    2023  Volume PP

    Abstract: The visual perception systems aim to autonomously collect consecutive visual data and perceive the relevant information online like human beings. In comparison with the classical static visual systems focusing on fixed tasks (e.g., face recognition for ... ...

    Abstract The visual perception systems aim to autonomously collect consecutive visual data and perceive the relevant information online like human beings. In comparison with the classical static visual systems focusing on fixed tasks (e.g., face recognition for visual surveillance), the real-world visual systems (e.g., the robot visual system) often need to handle unpredicted tasks and dynamically changed environments, which need to imitate human-like intelligence with open-ended online learning ability. Therefore, we provide a comprehensive analysis of open-ended online learning problems for autonomous visual perception in this survey. Based on "what to online learn" among visual perception scenarios, we classify the open-ended online learning methods into five categories: instance incremental learning to handle data attributes changing, feature evolution learning for incremental and decremental features with the feature dimension changed dynamically, class incremental learning and task incremental learning aiming at online adding new coming classes/tasks, and parallel and distributed learning for large-scale data to reveal the computational and storage advantages. We discuss the characteristic of each method and introduce several representative works as well. Finally, we introduce some representative visual perception applications to show the enhanced performance when using various open-ended online learning models, followed by a discussion of several future directions.
    Language English
    Publishing date 2023-02-22
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2023.3242448
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: MiR-5195-3p functions as a tumor suppressor in prostate cancer via targeting CCNL1.

    Zeng, Xing / Hu, Zhiquan / Shen, Yuanqing / Wei, Xian / Gan, Jiahua / Liu, Zheng

    Cellular & molecular biology letters

    2022  Volume 27, Issue 1, Page(s) 25

    Abstract: Background: Accumulating evidence indicates that miR-5195-3p exerts tumor-suppressive roles in several tumors. However, the clinical significance and biological function of miR-5195-3p in prostate cancer (PCa) have not been reported yet.: Methods: ... ...

    Abstract Background: Accumulating evidence indicates that miR-5195-3p exerts tumor-suppressive roles in several tumors. However, the clinical significance and biological function of miR-5195-3p in prostate cancer (PCa) have not been reported yet.
    Methods: The expression levels of miR-5195-3p and Cyclin L1 (CCNL1) were determined using quantitative real-time PCR in clinical specimens and cell lines. The clinical significance of miR-5195-3p in patients with PCa was evaluated using Kaplan-Meier survival analysis and Cox regression models. Cell proliferation and cell cycle distribution were measured by CCK-8 assay and flow cytometry, respectively. The association between miR-5195-3p and CCNL1 was analyzed by luciferase reporter assay.
    Results: MiR-5195-3p expression levels were significantly downregulated in 69 paired PCa tissues compared with matched adjacent normal tissues. The decreased miR-5195-3p expression was associated with Gleason score and TNM stage, as well as worse survival prognosis. The in vitro experiments showed that miR-5195-3p overexpression suppressed the proliferation and cell cycle G1/S transition in PC-3 and DU145 cells. Elevated miR-5195-3p abundance obviously impaired tumor formation in vivo using PC-3 xenografts. Mechanistically, CCNL1 was a direct target of miR-5195-3p in PCa cells, which was inversely correlated with miR-5195-3p in PCa tissues. Importantly, CCNL1 knockdown imitated, while overexpression reversed, the effects of miR-5195-3p overexpression on PCa cell proliferation and cell cycle G1/S transition.
    Conclusions: Our data suggest that miR-5195-3p functions as a tumor suppressor by targeting CCNL1 in PCa.
    MeSH term(s) Cell Line, Tumor ; Cell Movement ; Cell Proliferation/genetics ; Cyclins/genetics ; Cyclins/metabolism ; Genes, Tumor Suppressor ; Humans ; Male ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Prostatic Neoplasms/genetics ; Prostatic Neoplasms/pathology
    Chemical Substances CCNL1 protein, human ; Cyclins ; MIRN5195 microRNA, human ; MicroRNAs
    Language English
    Publishing date 2022-03-08
    Publishing country England
    Document type Letter
    ZDB-ID 2108724-6
    ISSN 1689-1392 ; 1689-1392
    ISSN (online) 1689-1392
    ISSN 1689-1392
    DOI 10.1186/s11658-022-00326-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With COVID-19 Pneumonia

    Gan, Jiahua / Li, Jingjing / Li, Shusheng / Yang, Chunguang

    Frontiers in Public Health

    A Retrospective Case-Control Study

    2020  Volume 8

    Keywords covid19
    Publisher Frontiers Media SA
    Publishing country ch
    Document type Article ; Online
    ZDB-ID 2711781-9
    ISSN 2296-2565
    ISSN 2296-2565
    DOI 10.3389/fpubh.2020.00299
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Leucocyte Subsets Effectively Predict the Clinical Outcome of Patients With COVID-19 Pneumonia

    Jiahua Gan / Jingjing Li / Shusheng Li / Chunguang Yang

    Frontiers in Public Health, Vol

    A Retrospective Case-Control Study

    2020  Volume 8

    Abstract: Background: The clinical characteristics of coronavirus disease 2019 (COVID-19) have been well-studied, while effective predictors for clinical outcome and research on underlying mechanisms are scarce.Methods: Hospitalized COVID-19 pneumonia patients ... ...

    Abstract Background: The clinical characteristics of coronavirus disease 2019 (COVID-19) have been well-studied, while effective predictors for clinical outcome and research on underlying mechanisms are scarce.Methods: Hospitalized COVID-19 pneumonia patients with definitive clinical outcome (cured or died) were retrospectively studied. The diagnostic performance of the leucocyte subsets and other parameters were compared using the area under the receiver operating characteristic curve (AUC). Further, the correlations between leucocyte subsets and inflammation-related factors associated with clinical outcome were subsequently investigated.Results: Among 95 subjects included, 56 patients were cured, and 39 died. Older age, elevated aspartate aminotransferase, total bilirubin, serum lactate dehydrogenase, blood urea nitrogen, prothrombin time, D-dimer, Procalcitonin, and C-reactive protein levels, decreased albumin, elevated serum cytokines (IL2R, IL6, IL8, IL10, and TNF-α) levels, and a decreased lymphocyte count indicated poor outcome in patients with COVID-19 pneumonia. Lymphocyte subset (lymphocytes, T cells, helper T cells, suppressor T cells, natural killer cells, T cells+B cells+NK cells) counts were positively associated with clinical outcome (AUC: 0.777; AUC: 0.925; AUC: 0.900; AUC: 0.902; AUC: 0.877; AUC: 0.918, resp.). The neutrophil-to-lymphocyte ratio (NLR), neutrophil to T lymphocyte count ratio (NTR), neutrophil percentage to T lymphocyte ratio (NpTR) effectively predicted mortality (AUC: 0.900; AUC: 0.905; AUC: 0.932, resp.). Binary logistic regression showed that NpTR was an independent prognostic factor for mortality. Serum IL6 levels were positively correlated with leucocyte count, neutrophil count, and eosinophil count and negatively correlated with lymphocyte count.Conclusion: These results indicate that leucocyte subsets predict the clinical outcome of patients with COVID-19 pneumonia with high efficiency. Non-self-limiting inflammatory response is involved in the development of fatal pneumonia.
    Keywords SARS-CoV-2 ; COVID-19 ; prognosis ; leucocyte ; lymphocyte ; cytokine ; Public aspects of medicine ; RA1-1270 ; covid19
    Subject code 610
    Language English
    Publishing date 2020-06-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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