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  1. Article ; Online: YiXin-Shu, a ShengMai-San-based traditional Chinese medicine formula, attenuates myocardial ischemia/reperfusion injury by suppressing mitochondrial mediated apoptosis and upregulating liver-X-receptor α.

    Zhao, Yichao / Xu, Longwei / Qiao, Zhiqing / Gao, Lingchen / Ding, Song / Ying, Xiaoying / Su, Yuanyuan / Lin, Nan / He, Ben / Pu, Jun

    Scientific reports

    2016  Volume 6, Page(s) 23025

    Abstract: ... mechanisms. Here, we investigated the nature and underlying mechanisms of the effects of YiXin-Shu (YXS ...

    Abstract Positive evidence from clinical trials has fueled growing acceptance of traditional Chinese medicine (TCM) for the treatment of cardiac diseases; however, little is known about the underlying mechanisms. Here, we investigated the nature and underlying mechanisms of the effects of YiXin-Shu (YXS), an antioxidant-enriched TCM formula, on myocardial ischemia/reperfusion (MI/R) injury. YXS pretreatment significantly reduced infarct size and improved viable myocardium metabolism and cardiac function in hypercholesterolemic mice. Mechanistically, YXS attenuated myocardial apoptosis by inhibiting the mitochondrial mediated apoptosis pathway (as reflected by inhibition of mitochondrial swelling, cytochrome c release and caspase-9 activity, and normalization of Bcl-2 and Bax levels) without altering the death receptor and endoplasmic reticulum-stress death pathways. Moreover, YXS reduced oxidative/nitrative stress (as reflected by decreased superoxide and nitrotyrosine content and normalized pro- and anti-oxidant enzyme levels). Interestingly, YXS upregulated endogenous nuclear receptors including LXRα, PPARα, PPARβ and ERα, and in-vivo knockdown of cardiac-specific LXRα significantly blunted the cardio-protective effects of YXS. Collectively, these data show that YXS is effective in mitigating MI/R injury by suppressing mitochondrial mediated apoptosis and oxidative stress and by upregulating LXRα, thereby providing a rationale for future clinical trials and clinical applications.
    MeSH term(s) Animals ; Apoptosis/drug effects ; Caspase 9/biosynthesis ; Drug Combinations ; Drugs, Chinese Herbal/administration & dosage ; Endoplasmic Reticulum Stress/drug effects ; Gene Expression Regulation/drug effects ; Heart/drug effects ; Heart/physiopathology ; Humans ; Liver X Receptors/biosynthesis ; Liver X Receptors/genetics ; Medicine, Chinese Traditional ; Mice ; Mitochondria/drug effects ; Mitochondria/genetics ; Myocardial Ischemia/drug therapy ; Myocardial Ischemia/genetics ; Myocardial Ischemia/pathology ; Myocardium/pathology ; Oxidative Stress/drug effects ; Reperfusion Injury/drug therapy ; Reperfusion Injury/genetics ; Reperfusion Injury/pathology ; Signal Transduction
    Chemical Substances Drug Combinations ; Drugs, Chinese Herbal ; Liver X Receptors ; fructus schizandrae, radix ginseng, radix ophiopogonis drug combination ; Caspase 9 (EC 3.4.22.-)
    Language English
    Publishing date 2016-03-11
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/srep23025
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  2. Article ; Online: Enhancing View Synthesis with Depth-Guided Neural Radiance Fields and Improved Depth Completion.

    Wang, Bojun / Zhang, Danhong / Su, Yixin / Zhang, Huajun

    Sensors (Basel, Switzerland)

    2024  Volume 24, Issue 6

    Abstract: Neural radiance fields (NeRFs) leverage a neural representation to encode scenes, obtaining photorealistic rendering of novel views. However, NeRF has notable limitations. A significant drawback is that it does not capture surface geometry and only ... ...

    Abstract Neural radiance fields (NeRFs) leverage a neural representation to encode scenes, obtaining photorealistic rendering of novel views. However, NeRF has notable limitations. A significant drawback is that it does not capture surface geometry and only renders the object surface colors. Furthermore, the training of NeRF is exceedingly time-consuming. We propose Depth-NeRF as a solution to these issues. Specifically, our approach employs a fast depth completion algorithm to denoise and complete the depth maps generated by RGB-D cameras. These improved depth maps guide the sampling points of NeRF to be distributed closer to the scene's surface, benefiting from dense depth information. Furthermore, we have optimized the network structure of NeRF and integrated depth information to constrain the optimization process, ensuring that the termination distribution of the ray is consistent with the scene's geometry. Compared to NeRF, our method accelerates the training speed by 18%, and the rendered images achieve a higher PSNR than those obtained by mainstream methods. Additionally, there is a significant reduction in RMSE between the rendered scene depth and the ground truth depth, which indicates that our method can better capture the geometric information of the scene. With these improvements, we can train the NeRF model more efficiently and achieve more accurate rendering results.
    Language English
    Publishing date 2024-03-16
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s24061919
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  3. Article: Clinical and radiological characteristics of brain abscess due to different organisms in hospitalized patients: A 6-year retrospective study from China.

    Su, Jiachun / Hu, Bin / Zhang, Yixin / Li, Ying

    Heliyon

    2023  Volume 9, Issue 5, Page(s) e16003

    Abstract: Background: Brain abscess (BA) is a rare but life-threatening infection. Early identification of the pathogen is helpful to improve the outcomes. This study aimed to describe the clinical and radiological features of patients with BA caused by different ...

    Abstract Background: Brain abscess (BA) is a rare but life-threatening infection. Early identification of the pathogen is helpful to improve the outcomes. This study aimed to describe the clinical and radiological features of patients with BA caused by different organisms.
    Methods: A retrospective, observational study of patients with known etiologic diagnosis of BA in Huashan Hospital Affiliated to Fudan University in China between January 2015 and December 2020 was conducted. Data on patient demographics, clinical and radiological presenting features, microbiological results, surgical treatment, and outcomes were collected.
    Results: Sixty-five patients (49 male, 16 female) with primary BAs were included. Frequent clinical presentations included headache (64.6%), fever (49.2%) and confusion (27.3%).
    Conclusions: Patients with BAs caused by
    Language English
    Publishing date 2023-05-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2023.e16003
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  4. Article: Clinical Characteristics and Risk Factors for Intra-Abdominal Infection with

    Zhang, Yixin / Zhao, Xiaoyu / Xu, Su / Li, Ying

    Pathogens (Basel, Switzerland)

    2022  Volume 11, Issue 10

    Abstract: The incidence of hospital-acquired infections caused ... ...

    Abstract The incidence of hospital-acquired infections caused by
    Language English
    Publishing date 2022-09-29
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2695572-6
    ISSN 2076-0817
    ISSN 2076-0817
    DOI 10.3390/pathogens11101126
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  5. Article: Integrated Analysis of Coding and Non-coding RNAs Reveals the Molecular Mechanism Underlying Salt Stress Response in

    An, Yixin / Su, Haotian / Niu, Qichen / Yin, Shuxia

    Frontiers in plant science

    2022  Volume 13, Page(s) 891361

    Abstract: Salt stress is among the most severe abiotic stresses in plants worldwide. ...

    Abstract Salt stress is among the most severe abiotic stresses in plants worldwide.
    Language English
    Publishing date 2022-04-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2613694-6
    ISSN 1664-462X
    ISSN 1664-462X
    DOI 10.3389/fpls.2022.891361
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  6. Article ; Online: A Collaborative Learning Model for Skin Lesion Segmentation and Classification

    Ying Wang / Jie Su / Qiuyu Xu / Yixin Zhong

    Diagnostics, Vol 13, Iss 912, p

    2023  Volume 912

    Abstract: The automatic segmentation and classification of skin lesions are two essential tasks in computer-aided skin cancer diagnosis. Segmentation aims to detect the location and boundary of the skin lesion area, while classification is used to evaluate the ... ...

    Abstract The automatic segmentation and classification of skin lesions are two essential tasks in computer-aided skin cancer diagnosis. Segmentation aims to detect the location and boundary of the skin lesion area, while classification is used to evaluate the type of skin lesion. The location and contour information of lesions provided by segmentation is essential for the classification of skin lesions, while the skin disease classification helps generate target localization maps to assist the segmentation task. Although the segmentation and classification are studied independently in most cases, we find meaningful information can be explored using the correlation of dermatological segmentation and classification tasks, especially when the sample data are insufficient. In this paper, we propose a collaborative learning deep convolutional neural networks (CL-DCNN) model based on the teacher–student learning method for dermatological segmentation and classification. To generate high-quality pseudo-labels, we provide a self-training method. The segmentation network is selectively retrained through classification network screening pseudo-labels. Specially, we obtain high-quality pseudo-labels for the segmentation network by providing a reliability measure method. We also employ class activation maps to improve the location ability of the segmentation network. Furthermore, we provide the lesion contour information by using the lesion segmentation masks to improve the recognition ability of the classification network. Experiments are carried on the ISIC 2017 and ISIC Archive datasets. The CL-DCNN model achieved a Jaccard of 79.1% on the skin lesion segmentation task and an average AUC of 93.7% on the skin disease classification task, which is superior to the advanced skin lesion segmentation methods and classification methods.
    Keywords skin cancer ; segmentation ; classification ; self-training ; class activation mapping ; Medicine (General) ; R5-920
    Subject code 006
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Clinical and radiological characteristics of brain abscess due to different organisms in hospitalized patients

    Jiachun Su / Bin Hu / Yixin Zhang / Ying Li

    Heliyon, Vol 9, Iss 5, Pp e16003- (2023)

    A 6-year retrospective study from China

    2023  

    Abstract: Background: Brain abscess (BA) is a rare but life-threatening infection. Early identification of the pathogen is helpful to improve the outcomes. This study aimed to describe the clinical and radiological features of patients with BA caused by different ... ...

    Abstract Background: Brain abscess (BA) is a rare but life-threatening infection. Early identification of the pathogen is helpful to improve the outcomes. This study aimed to describe the clinical and radiological features of patients with BA caused by different organisms. Methods: A retrospective, observational study of patients with known etiologic diagnosis of BA in Huashan Hospital Affiliated to Fudan University in China between January 2015 and December 2020 was conducted. Data on patient demographics, clinical and radiological presenting features, microbiological results, surgical treatment, and outcomes were collected. Results: Sixty-five patients (49 male, 16 female) with primary BAs were included. Frequent clinical presentations included headache (64.6%), fever (49.2%) and confusion (27.3%). Streptococcus viridans was associated with thicker wall of abscesses (6.94 ± 8.43 mm for S. viridans versus 3.66 ± 1.74 mm for other organisms, P = 0.031) and larger oedema (89.40 ± 15.70 mm for S. viridans versus 74.72 ± 19.70 mm for other organisms, P = 0.023). The independent factor associated with poor outcome identified by multivariate analysis was confusion (Odds ratio 6.215, 95% confidence interval 1.406–27.466; P = 0.016). Conclusions: Patients with BAs caused by Streptococcus species had nonspecific clinical signs, but specific radiological features, which might be helpful for early diagnosis.
    Keywords Brain abscess ; Streptococcus viridans ; Confusion ; Clinical features ; Radiological features ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Subject code 610 ; 616
    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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  8. Article: A Collaborative Learning Model for Skin Lesion Segmentation and Classification.

    Wang, Ying / Su, Jie / Xu, Qiuyu / Zhong, Yixin

    Diagnostics (Basel, Switzerland)

    2023  Volume 13, Issue 5

    Abstract: The automatic segmentation and classification of skin lesions are two essential tasks in computer-aided skin cancer diagnosis. Segmentation aims to detect the location and boundary of the skin lesion area, while classification is used to evaluate the ... ...

    Abstract The automatic segmentation and classification of skin lesions are two essential tasks in computer-aided skin cancer diagnosis. Segmentation aims to detect the location and boundary of the skin lesion area, while classification is used to evaluate the type of skin lesion. The location and contour information of lesions provided by segmentation is essential for the classification of skin lesions, while the skin disease classification helps generate target localization maps to assist the segmentation task. Although the segmentation and classification are studied independently in most cases, we find meaningful information can be explored using the correlation of dermatological segmentation and classification tasks, especially when the sample data are insufficient. In this paper, we propose a collaborative learning deep convolutional neural networks (CL-DCNN) model based on the teacher-student learning method for dermatological segmentation and classification. To generate high-quality pseudo-labels, we provide a self-training method. The segmentation network is selectively retrained through classification network screening pseudo-labels. Specially, we obtain high-quality pseudo-labels for the segmentation network by providing a reliability measure method. We also employ class activation maps to improve the location ability of the segmentation network. Furthermore, we provide the lesion contour information by using the lesion segmentation masks to improve the recognition ability of the classification network. Experiments are carried on the ISIC 2017 and ISIC Archive datasets. The CL-DCNN model achieved a Jaccard of 79.1% on the skin lesion segmentation task and an average AUC of 93.7% on the skin disease classification task, which is superior to the advanced skin lesion segmentation methods and classification methods.
    Language English
    Publishing date 2023-02-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662336-5
    ISSN 2075-4418
    ISSN 2075-4418
    DOI 10.3390/diagnostics13050912
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  9. Article ; Online: Accurate Capture and Identification of Exosomes: Nanoarchitecture of the MXene Heterostructure/Engineered Lipid Layer.

    Nie, Yixin / Wang, Peilin / Wang, Shuo / Ma, Qiang / Su, Xingguang

    ACS sensors

    2023  Volume 8, Issue 4, Page(s) 1850–1857

    Abstract: Recently, exosome detection has become an important breakthrough in clinical diagnosis. However, the effective capture and accurate identification of cancer exosomes in a complex biomatrix are still a tough task. Especially, the large size and non- ... ...

    Abstract Recently, exosome detection has become an important breakthrough in clinical diagnosis. However, the effective capture and accurate identification of cancer exosomes in a complex biomatrix are still a tough task. Especially, the large size and non-conductivity of exosomes are not conducive to highly sensitive electrochemical or electrochemiluminescence (ECL) detection. Therefore, we have developed a Ti
    MeSH term(s) Humans ; Exosomes/chemistry ; Neoplasms/metabolism ; Lipids/analysis
    Chemical Substances MXene ; Lipids
    Language English
    Publishing date 2023-04-17
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2379-3694
    ISSN (online) 2379-3694
    DOI 10.1021/acssensors.3c00370
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  10. Article ; Online: Confined Gold Single Atoms-MXene Heterostructure-Based Electrochemiluminescence Functional Material and Its Sensing Application.

    Nie, Yixin / Wang, Peilin / Ma, Qiang / Su, Xingguang

    Analytical chemistry

    2022  Volume 94, Issue 31, Page(s) 11016–11022

    Abstract: Herein, based on electronic metal-support interaction (EMSI), a gold single atom confined MXene ( ... ...

    Abstract Herein, based on electronic metal-support interaction (EMSI), a gold single atom confined MXene (Au
    MeSH term(s) Electrochemical Techniques ; Gold/chemistry ; Luminescent Measurements ; Photometry
    Chemical Substances Gold (7440-57-5)
    Language English
    Publishing date 2022-07-28
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.2c01480
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