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  • 1
    In: Molecules, MDPI AG, Vol. 24, No. 9 ( 2019-05-08), p. 1776-
    Abstract: α-glucosidase inhibitors (AGIs) have been an important category of oral antidiabetic drugs being widely exploited for the effective management of type 2 diabetes mellitus. However, the marketed AGIs not only inhibited the disaccharidases, but also exhibited an excessive inhibitory effect on α-amylase, resulting in undesirable gastrointestinal side effects. Compared to these agents, Ramulus Mori alkaloids (SZ-A), was a group of effective alkaloids from natural Morus alba L., and showed excellent hypoglycemic effect and fewer side effects in the Phase II/III clinical trials. Thus, this paper aims to investigate the selective inhibitory effect and mechanism of SZ-A and its major active ingredients (1-DNJ, FA and DAB) on different α-glucosidases (α-amylase and disaccharidases) by using a combination of kinetic analysis and molecular docking approaches. From the results, SZ-A displayed a strong inhibitory effect on maltase and sucrase with an IC50 of 0.06 μg/mL and 0.03 μg/mL, respectively, which was similar to the positive control of acarbose with an IC50 of 0.07 μg/mL and 0.68 μg/mL. With regard to α-amylase, SZ-A exhibited no inhibitory activity at 100 μg/mL, while acarbose showed an obvious inhibitory effect with an IC50 of 1.74 μg/mL. The above analysis demonstrated that SZ-A could selectively inhibit disaccharidase to reduce hyperglycemia with a reversible competitive inhibition, which was primarily attributed to the three major active ingredients of SZ-A, especially 1-DNJ molecule. In the light of these findings, molecular docking study was utilized to analyze their inhibition mechanisms at molecular level. It pointed out that acarbose with a four-ring structure could perform desirable interactions with various α-glucosidases, while the three active ingredients of SZ-A, belonging to monocyclic compounds, had a high affinity to the active site of disaccharidases through forming a wide range of hydrogen bonds, whose affinity and consensus score with α-amylase was significantly lower than that of acarbose. Our study illustrates the selective inhibition mechanism of SZ-A on α-glucosidase for the first time, which is of great importance for the treatment of type 2 diabetes mellitus.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2008644-1
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  • 2
    In: Marine Drugs, MDPI AG, Vol. 19, No. 7 ( 2021-06-24), p. 362-
    Abstract: Two new diterpenoids, hypoxyterpoids A (1) and B (2), and four new isocoumarin derivatives, hypoxymarins A–D (4–7), together, with seven known metabolites (3 and 8–13) were obtained from the crude extract of the mangrove-derived fungus Hypoxylon sp. The structures of the new compounds were elucidated on the basis of 1- and 2-dimensional (1D/2D) nuclear magnetic resonance (NMR) spectroscopic and mass spectrometric analysis. The absolute configurations of compounds 1, 2, 4, 5, and 7 were determined by comparison of experimental and calculated electronic circular dichroism (ECD) spectra, and the absolute configurations of C-4′ in 6 and C-9 in 7 were determined by [Rh2(OCOCF3)4]-induced ECD spectra. Compound 1 showed moderate α-glucosidase inhibitory activities with IC50 values of 741.5 ± 2.83 μM. Compounds 6 and 11 exhibited DPPH scavenging activities with IC50 values of 15.36 ± 0.24 and 3.69 ± 0.07 μM, respectively.
    Type of Medium: Online Resource
    ISSN: 1660-3397
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2175190-0
    SSG: 15,3
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  • 3
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  Current Issues in Molecular Biology Vol. 44, No. 5 ( 2022-05-19), p. 2287-2299
    In: Current Issues in Molecular Biology, MDPI AG, Vol. 44, No. 5 ( 2022-05-19), p. 2287-2299
    Abstract: Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.
    Type of Medium: Online Resource
    ISSN: 1467-3045
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2090836-2
    SSG: 12
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  • 4
    In: Toxins, MDPI AG, Vol. 13, No. 9 ( 2021-09-07), p. 626-
    Abstract: This study aims to investigate the effects of zearalenone (ZEA) on the localizations and expressions of follicle stimulating hormone receptor (FSHR), luteinizing hormone receptor (LHR), gonadotropin releasing hormone (GnRH) and gonadotropin releasing hormone receptor (GnRHR) in the ovaries of weaned gilts. Twenty 42-day-old weaned gilts were randomly allocated into two groups, and treated with a control diet and a ZEA-contaminated diet (ZEA 1.04 mg/kg), respectively. After 7-day adjustment, gilts were fed individually for 35 days and euthanized for blood and ovarian samples collection before morning feeding on the 36th day. Serum hormones of E2, PRG, FSH, LH and GnRH were determined using radioimmunoassay kits. The ovaries were collected for relative mRNA and protein expression, and immunohistochemical analysis of FSHR, LHR, GnRH and GnRHR. The results revealed that ZEA exposure significantly increased the final vulva area (p 〈 0.05), significantly elevated the serum concentrations of estradiol, follicle stimulating hormone and GnRH (p 〈 0.05), and markedly up-regulated the mRNA and protein expressions of FSHR, LHR, GnRH and GnRHR (p 〈 0.05). Besides, the results of immunohistochemistry showed that the immunoreactive substances of ovarian FSHR, LHR, GnRH and GnRHR in the gilts fed the ZEA-contaminated diet were stronger than the gilts fed the control diet. Our findings indicated that dietary ZEA (1.04 mg/kg) could cause follicular proliferation by interfering with the localization and expression of FSHR, LHR, GnRH and GnRHR, and then affect the follicular development of weaned gilts.
    Type of Medium: Online Resource
    ISSN: 2072-6651
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518395-3
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  • 5
    In: Applied Sciences, MDPI AG, Vol. 12, No. 17 ( 2022-09-05), p. 8889-
    Abstract: The scarcity of attack samples is the bottleneck problem of anomaly detection of underlying business data in the industrial control system. Predecessors have done a lot of research on temporal data generation, but most of them are not suitable for industrial control attack sample generation. The change patterns of the characteristics of the underlying business data attack samples can be divided into three types: oscillation type, step type, and pulse type. This paper proposes an adaptive industrial control attack sample expansion algorithm based on GAN, which expands the three types of features in different ways. The basic network structure of data expansion adopts GAN. According to the characteristics of oscillation type changes, momentum is selected as the optimizer. Aiming at the characteristics of step type changes, the Adam optimization method is improved. For pulse type features, attack samples are generated according to the location and length of the pulse. Compared with previous time-series data generation methods, this method is more targeted for each feature and has higher similarities.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 6
    In: Sustainability, MDPI AG, Vol. 15, No. 10 ( 2023-05-21), p. 8351-
    Abstract: Currently, tourism is an important contributor to the Chinese economy. The Chinese government issued Several Opinions of the State Council on Promoting the Reform and Development of Tourism and Several Opinions of the General Office of the State Council on Further Promoting Tourism Investment and Consumption, which are aimed at promoting tourism development. In this study, we use a multiregional and multisectoral computable general equilibrium model (CGE model) to simulate the effects of different levels of resident tourism subsidy policies on the economy and environment in China. Our analysis shows that tourism subsidies are beneficial to economic growth and support the transition to a low-carbon society. In addition, resident tourism subsidy policy has a positive effect on the national emission reduction of CO2, CO, NOX, PM2.5, and SO2. At the regional level, more significant emission reduction potential is present in provinces with more energy consumption and a more developed heavy industry, such as Shandong, Guizhou, and Inner Mongolia. Therefore, this study indicates that resident tourism subsidies can be an effective policy suggestion to promote the transition to a green society and air pollutant emission reduction.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518383-7
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  • 7
    In: Energies, MDPI AG, Vol. 15, No. 13 ( 2022-06-23), p. 4614-
    Abstract: The rolling bearing is a critical part of rotating machinery and its condition determines the performance of industrial equipment; it is necessary to detect rolling bearing faults as early as possible. The traditional methods of fault diagnosis are not efficient and are time-consuming. With the help of deep learning, the convolution neural network (CNN) plays a huge role in the data-driven methods of bearing fault diagnosis. However, the vibration signal is non-stationary, contains high noise, and is one-dimensional, which is difficult to analyze directly by the CNN model. Considering the multi-domain learning as an advantage of deep learning, this paper proposes a novel rolling bearing fault diagnosis approach using an improved one-dimensional (1D) and two-dimensional (2D) convolution neural network (CNN) of two-domain information learning. The constructed fault diagnosis model combining 1D and 2D CNN extracts the fault features from the two-domain information of bearing fault samples. The padding and dropout technology are utilized to fully extract features from the raw data and reduce over-fitting. To prove the validity of the proposed method, this paper performs two tests with two bearing datasets, the Case Western Reserve University (CWRU) bearing dataset and the Dalian University of Technology (DUT) vibration laboratory dataset. The experimental results show that our proposed method achieves high recognition accuracy of rolling bearing fault states via two-domain learning of monitoring data, and there is no manual experience necessary. Vibration data under strong noise were also used to test the method, and the results show the superiority and robustness of the proposed method.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2437446-5
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  • 8
    In: Molecules, MDPI AG, Vol. 22, No. 2 ( 2017-02-15), p. 293-
    Type of Medium: Online Resource
    ISSN: 1420-3049
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2008644-1
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  • 9
    In: Molecules, MDPI AG, Vol. 22, No. 10 ( 2017-09-26), p. 1616-
    Type of Medium: Online Resource
    ISSN: 1420-3049
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2008644-1
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  • 10
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 9 ( 2022-09-13), p. 483-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 9 ( 2022-09-13), p. 483-
    Abstract: The urban fringe area is a discontinuous spatial phenomenon that refers to the urban-rural interlacing zone which is undergoing urbanization on the fringe of the core built-up area of a large city after the emergence of industrialization. Dynamic, ambiguous, and complex interlacing of various types of lands make urban planners and managers fuzzy about the spatial scope of the urban fringe and it is difficult to control its evolution patterns scientifically. Based on remote sensing data from 2000 to 2020, the range of Wuhan’s urban fringe was extracted from the surface impermeability ratio mutation points, landscape flocculation, and population density. On this basis, the dynamic evolution characteristics of land-use and landscape patterns in the urban fringe area of Wuhan City were analyzed by using dynamic change and landscape pattern index analysis. The results show that: Wuhan City shows a clear “urban core area-urban fringe area-rural hinterland” circle structure, and the urban fringe area continuously extends to the rural hinterland. Moreover, most of the rural hinterland, in the process of moving to the urban core area, has gone through the process of the urban fringe. By comparison with other cities, it is found that the expansion of large cities is generally influenced by policies, topography, and traffic arteries, and gradually shifts from expansion to infill, with the urban core of Wuhan continuously extending and the urban fringe rapidly expanding from 2000 to 2010, and gradually entering a stable development state from 2010 to 2020. The future urban construction of Wuhan should pay attention to the influences of these characteristics on the implementation of urban territorial spatial planning.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
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