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  • MDPI AG  (25)
  • 1
    Online Resource
    Online Resource
    S-Propargyl-Cysteine Ameliorates Peripheral Nerve Injury through Microvascular Reconstruction
    MDPI AG ; 2023
    In:  Antioxidants Vol. 12, No. 2 ( 2023-01-28), p. 294-
    Details
    In: Antioxidants, MDPI AG, Vol. 12, No. 2 ( 2023-01-28), p. 294-
    Abstract: Microvascular reconstruction is essential for peripheral nerve repair. S-Propargyl-cysteine (SPRC), the endogenous hydrogen sulfide (H2S) donor, has been reported to promote angiogenesis. The aim of this study is to utilize the pro-angiogenic ability of SPRC to support peripheral nerve repair and to explore the potential mechanisms. The effects and mechanisms of SPRC on angiogenesis and peripheral nerve repair were examined under hypoxic condition by establishing a sciatic nerve crushed injury model in mice and rats, and a hypoxia model in human umbilical vascular endothelial cells (HUVECs) in vitro. We found that SPRC accelerated the function recovery of the injured sciatic nerve and alleviated atrophy of the gastrocnemius muscle in mice. It facilitated the viability of Schwann cells (SCs), the outgrowth and myelination of regenerated axons, and angiogenesis in rats. It enhanced the viability, proliferation, adhesion, migration, and tube formation of HUVECs under hypoxic condition. SPRC activated sirtuin1 (SIRT1) expression by promoting the production of endogenous H2S, and SIRT1 negatively regulated Notch signaling in endothelial cells (ECs), thereby promoting angiogenesis. Collectively, our study has provided important evidence that SPRC has an effective role in peripheral nerve repair through microvascular reconstruction, which could be a potentially effective medical therapy for peripheral nerve injury.
    Type of Medium: Online Resource
    ISSN: 2076-3921
    URL: Article
    DOI: 10.3390/antiox12020294
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704216-9
    SSG: 15,3
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  • 2
    Online Resource
    Online Resource
    Dynamic Prediction and Optimization of Energy Efficiency Operational Index (EEOI) for an Operating Ship in Varying Environments
    MDPI AG ; 2019
    In:  Journal of Marine Science and Engineering Vol. 7, No. 11 ( 2019-11-08), p. 402-
    Details
    In: Journal of Marine Science and Engineering, MDPI AG, Vol. 7, No. 11 ( 2019-11-08), p. 402-
    Abstract: The demands for lower Energy Efficiency Operational Index (EEOI) reflect the requirements of international conventions for green shipping. Within this context it is believed that practical solutions for the dynamic optimization of a ship’s main engine and the reduction of EEOI in real conditions are useful in terms of improving sustainable shipping operations. In this paper, we introduce a model for dynamic optimization of the main engine that can improve fuel efficiency and decrease EEOI. The model considers as input environmental factors that influence overall ship dynamics (e.g., wind speed, wind direction, wave height, water flow speed) and engine revolutions. Fuel consumption rate and ship speed are taken as outputs. Consequently, a genetic algorithm is applied to optimize the initial connection weight and threshold of nodes of a neural network (NN) that is used to predict fuel consumption rate and ship speed. Navigation data from the training ship “YUMING” are applied to train the network. The genetic algorithm is used to optimize engine revolution and obtain the lowest EEOI. Results show that the optimization method proposed may assist with the prediction of lower EEOI in different environmental conditions and operational speed.
    Type of Medium: Online Resource
    ISSN: 2077-1312
    URL: Article
    DOI: 10.3390/jmse7110402
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2738390-8
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  • 3
    Online Resource
    Online Resource
    Application and Progress of Artificial Intelligence in Fetal Ultrasound
    MDPI AG ; 2023
    In:  Journal of Clinical Medicine Vol. 12, No. 9 ( 2023-05-05), p. 3298-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 12, No. 9 ( 2023-05-05), p. 3298-
    Abstract: Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However, problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter-observer variability limit the development of traditional ultrasound in clinical applications. The combination of artificial intelligence (AI) and obstetric ultrasound may help optimize fetal ultrasound examination by shortening the examination time, reducing the physician’s workload, and improving diagnostic accuracy. AI has been successfully applied to automatic fetal ultrasound standard plane detection, biometric parameter measurement, and disease diagnosis to facilitate conventional imaging approaches. In this review, we attempt to thoroughly review the applications and advantages of AI in prenatal fetal ultrasound and discuss the challenges and promises of this new field.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm12093298
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662592-1
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  • 4
    Online Resource
    Online Resource
    A Semantic-Preserving Deep Hashing Model for Multi-Label Remote Sensing Image Retrieval
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 24 ( 2021-12-07), p. 4965-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 24 ( 2021-12-07), p. 4965-
    Abstract: Conventional remote sensing image retrieval (RSIR) systems perform single-label retrieval with a single label to represent the most dominant semantic content for an image. Improved spatial resolution dramatically boosts the remote sensing image scene complexity, as a remote sensing image always contains multiple categories of surface features. In this case, a single label cannot comprehensively describe the semantic content of a complex remote sensing image scene and therefore results in poor retrieval performance in practical applications. As a result, researchers have begun to pay attention to multi-label image retrieval. However, in the era of massive remote sensing data, how to increase retrieval efficiency and reduce feature storage while preserving semantic information remains unsolved. Considering the powerful capability of hashing learning in overcoming the curse of dimensionality caused by high-dimensional image representation in Approximate Nearest Neighbor (ANN) search problems, we propose a new semantic-preserving deep hashing model for multi-label remote sensing image retrieval. Our model consists of three main components: (1) a convolutional neural network to extract image features; (2) a hash layer to generate binary codes; (3) a new loss function to better maintain the multi-label semantic information of hash learning contained in context remote sensing image scene. As far as we know, this is the first attempt to apply deep hashing into the multi-label remote sensing image retrieval. Experimental results indicate the effectiveness and promising of the introduction of hashing methods in the multi-label remote sensing image retrieval.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13244965
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 5
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    Online Resource
    High Resolution Fourier Transform Spectrometer for Ground-Based Verification of Greenhouse Gases Satellites
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 6 ( 2023-03-20), p. 1671-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 6 ( 2023-03-20), p. 1671-
    Abstract: Satellite remote sensing is currently the best monitoring means to obtain global carbon source and sink data. The United States, Japan, China and other countries are vigorously developing spaceborne detection technology. However, the important factors that restrict the application of greenhouse gas satellite remote sensing technology include the limited accuracy of data products. How to improve the retrieval level of greenhouse gas payloads is a problem that needs to be solved urgently. One effective way to improve data quality is to carry out satellite ground synchronous authenticity verification and system error correction. This paper mainly aims at the shortcomings of the existing TCCON and the portable verification equipment EM27/SUN, and develops a High-Resolution Fourier Transform Spectrometer (HRFTS) based on dynamic collimation technology. Through the gas absorption method and the band scanning method of the hyperspectral monochromatic light source, the instrument’s absorption spectrum measurement capability and the Instrument Line Shape (ILS) are demonstrated. The instrument’s spectral resolution is consistent with the on-orbit greenhouse gas satellite load, reaching 0.26 cm−1. For the interference data obtained by the spectrometer, spectral restoration processing, data quality control and inversion algorithm optimization were carried out to solve the problems of baseline correction, spectral fine registration, and environmental parameter profile reconstruction, and cross comparison experiments with EM27/SUN were carried out simultaneously. Finally, for the gases monitoring instrument (GMI) of the GF5-02 satellite launched on 7 September 2021, the first satellite ground synchronization verification experiment with high space-time matching was carried out. The results showed that the CO2 column concentration deviation of the satellite ground synchronization inversion was about 1.5 ppm, and the CH4 column concentration deviation was about 11.3 ppb, which verified the on-orbit detection accuracy of the GMI, and laid a foundation for the subsequent satellite inversion algorithm optimization and systematic error correction.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15061671
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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  • 6
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    Role of Adiponectin in Cardiovascular Diseases Related to Glucose and Lipid Metabolism Disorders
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 24 ( 2022-12-09), p. 15627-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 24 ( 2022-12-09), p. 15627-
    Abstract: Lifestyle changes have led to increased incidence of cardiovascular disease (CVD); therefore, potential targets against CVD should be explored to mitigate its risks. Adiponectin (APN), an adipokine secreted by adipose tissue, has numerous beneficial effects against CVD related to glucose and lipid metabolism disorders, including regulation of glucose and lipid metabolism, increasing insulin sensitivity, reduction of oxidative stress and inflammation, protection of myocardial cells, and improvement in endothelial cell function. These effects demonstrate the anti-atherosclerotic and antihypertensive properties of APN, which could aid in improving myocardial hypertrophy, and reducing myocardial ischemia/reperfusion (MI/R) injury and myocardial infarction. APN can also be used for diagnosing and predicting heart failure. This review summarizes and discusses the role of APN in the treatment of CVD related to glucose and lipid metabolism disorders, and explores future APN research directions and clinical application prospects. Future studies should elucidate the signaling pathway network of APN cardiovascular protective effects, which will facilitate clinical trials targeting APN for CVD treatment in a clinical setting.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms232415627
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 7
    Online Resource
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    Microrna-130a Downregulates HCV Replication through an atg5-Dependent Autophagy Pathway
    MDPI AG ; 2019
    In:  Cells Vol. 8, No. 4 ( 2019-04-10), p. 338-
    Details
    In: Cells, MDPI AG, Vol. 8, No. 4 ( 2019-04-10), p. 338-
    Abstract: We previously identified that miR-130a downregulates HCV replication through two independent pathways: restoration of host immune responses and regulation of pyruvate metabolism. In this study, we further sought to explore host antiviral target genes regulated by miR-130a. We performed a RT² Profiler™ PCR array to identify the host antiviral genes regulated by miR-130a. The putative binding sites between miR-130a and its downregulated genes were predicted by miRanda. miR-130a and predicted target genes were over-expressed or knocked down by siRNA or CRISPR/Cas9 gRNA. Selected gene mRNAs and their proteins, together with HCV replication in JFH1 HCV-infected Huh7.5.1 cells were monitored by qRT-PCR and Western blot. We identified 32 genes that were significantly differentially expressed more than 1.5-fold following miR-130a overexpression, 28 of which were upregulated and 4 downregulated. We found that ATG5, a target gene for miR-130a, significantly upregulated HCV replication and downregulated interferon stimulated gene expression. miR-130a downregulated ATG5 expression and its conjugation complex with ATG12. ATG5 and ATG5-ATG12 complex affected interferon stimulated gene (ISG) such as MX1 and OAS3 expression and subsequently HCV replication. We concluded that miR-130a regulates host antiviral response and HCV replication through targeting ATG5 via the ATG5-dependent autophagy pathway.
    Type of Medium: Online Resource
    ISSN: 2073-4409
    URL: Article
    DOI: 10.3390/cells8040338
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2661518-6
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  • 8
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    A Proposal on the Restoration of Nostoc flagelliforme for Sustainable Improvement in the Ecology of Arid Steppes in China
    MDPI AG ; 2016
    In:  Environments Vol. 3, No. 4 ( 2016-06-02), p. 14-
    Details
    In: Environments, MDPI AG, Vol. 3, No. 4 ( 2016-06-02), p. 14-
    Type of Medium: Online Resource
    ISSN: 2076-3298
    URL: Article
    DOI: 10.3390/environments3020014
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2777960-9
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  • 9
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    Online Resource
    Neutron/Gamma Radial Shielding Design of Main Vessel in a Small Modular Molten Salt Reactor
    MDPI AG ; 2023
    In:  Journal of Nuclear Engineering Vol. 4, No. 1 ( 2023-02-22), p. 213-227
    Details
    In: Journal of Nuclear Engineering, MDPI AG, Vol. 4, No. 1 ( 2023-02-22), p. 213-227
    Abstract: The SM-MSR (small modular molten salt reactor) has a good prospect for development with regards to combining the superiority of the molten salt reactor and modularization technologies, showing the advantages of safety, reliability, low economic cost and flexibility of site selection. However, because its internal structural parts are not easily replaced, and the outer shielding structure is limited, the lifespan of the reactor vessel and its in-reactor shielding design needs to be addressed. In order to find an optimal shielding model with both high fuel efficiency and strong radiation shielding capability, five different design schemes were proposed in this work, which varied in thickness and boron concentration in inner-shielding materials. The neutron/gamma flux and DPA (displacements per atom)/helium production rates were evaluated to obtain an appropriate scheme. Several beneficial results were obtained. Considering the above factors and the actual manufacturing process, 20 cm-thick boron graphite with a 5 wt% Boron-10 concentration combined with a 1 cm-thick Hastelloy barrel was chosen as the in-reactor shielding structure. Outside the reactor, the neutron flux was reduced to 8.33 × 1010 cm−2 s−1, and the gamma flux was decreased to 1.13 × 1011 cm−2 s−1. The vessel/barrel material could maintain a lifespan of more than 10 years, while the burnup depth was 6.25% lower than that of a model without inner-shielding. The conclusions of this research can provide important references for the shielding design and parameter selections of small molten salt reactors in the future.
    Type of Medium: Online Resource
    ISSN: 2673-4362
    URL: Article
    DOI: 10.3390/jne4010017
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 3040700-X
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  • 10
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    Spectral Quantitative Analysis and Research of Fusarium Head Blight Infection Degree in Wheat Canopy Visible Areas
    MDPI AG ; 2023
    In:  Agronomy Vol. 13, No. 3 ( 2023-03-21), p. 933-
    Details
    In: Agronomy, MDPI AG, Vol. 13, No. 3 ( 2023-03-21), p. 933-
    Abstract: Obtaining complete and consistent spectral images of wheat ears in the visible areas of in situ wheat canopies poses a significant challenge due to the varying growth posture of wheat. Nevertheless, detecting the presence and degree of wheat Fusarium head blight (FHB) in situ is critical for formulating measures that ensure stable grain production and supply while promoting green development in agriculture. In this study, a spectral quantitative analysis model was developed to evaluate the infection degree of FHB in an in situ wheat canopy’s visible areas. To achieve this, a spectral acquisition method was used to evaluate the infection degree of FHB in a wheat canopy’s visible areas. Hyperspectral images were utilized to obtain spectral data from healthy and mildly, moderately, and severely infected wheat ear canopies. The spectral data were preprocessed, and characteristic wavelengths were extracted using twelve types of spectral preprocessing methods and four types of characteristic wavelength extraction methods. Subsequently, sixty-five spectral quantitative prediction models for the infection degree of FHB in the in situ wheat canopy visible areas were established using the PLSR method, based on the original spectral data, preprocessed spectral data, original spectral characteristic wavelengths extracted data, and preprocessed spectral characteristic wavelengths extracted data. Comparative analysis of the models indicated that the MMS + CARS + PLSR model exhibited the best prediction effect and could serve as the spectral quantitative analysis model for the evaluation of the infection degree of FHB in an in situ wheat canopy’s visible areas. The model extracted thirty-five characteristic wavelengths, with a modeling set coefficient of determination (R2) of 0.9490 and a root-mean-square error (RMSE) of 0.2384. The testing set of the coefficient of determination (R2) was 0.9312, with a root-mean-square error (RMSE) of 0.2588. The model can facilitate the spectral quantitative analysis of the infection degree of FHB in the in situ wheat canopy visible areas, thereby aiding in the implementation of China’s targeted poverty alleviation and agricultural power strategy.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy13030933
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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