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  • 1
    Online Resource
    Online Resource
    In Silico Analysis of Correlations between Protein Disorder and Post-Translational Modifications in Algae
    MDPI AG ; 2015
    In:  International Journal of Molecular Sciences Vol. 16, No. 8 ( 2015-08-20), p. 19812-19835
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 16, No. 8 ( 2015-08-20), p. 19812-19835
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms160819812
    Language: English
    Publisher: MDPI AG
    Publication Date: 2015
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 2
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    Exercise Training-Enhanced Lipolytic Potency to Catecholamine Depends on the Time of the Day
    MDPI AG ; 2020
    In:  International Journal of Molecular Sciences Vol. 21, No. 18 ( 2020-09-21), p. 6920-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 21, No. 18 ( 2020-09-21), p. 6920-
    Abstract: Exercise training is well known to enhance adipocyte lipolysis in response to hormone challenge. However, the existence of a relationship between the timing of exercise training and its effect on adipocyte lipolysis is unknown. To clarify this issue, Wistar rats were run on a treadmill for 9 weeks in either the early part (E-EX) or late part of the active phase (L-EX). L-EX rats exhibited greater isoproterenol-stimulated lipolysis expressed as fold induction over basal lipolysis, with greater protein expression levels of hormone-sensitive lipase (HSL) phosphorylated at Ser 660 compared to E-EX rats. Furthermore, we discovered that Brain and muscle Arnt-like (BMAL)1 protein can associate directly with several protein kinase A (PKA) regulatory units (RIα, RIβ, and RIIβ) of protein kinase, its anchoring protein (AKAP)150, and HSL, and that the association of BMAL1 with the regulatory subunits of PKA, AKAP150, and HSL was greater in L-EX than in E-EX rats. In contrast, comparison between E-EX and their counterpart sedentary control rats showed a greater co-immunoprecipitation only between BMAL1 and ATGL. Thus, both E-EX and L-EX showed an enhanced lipolytic response to isoproterenol, but the mechanisms underlying exercise training-enhanced lipolytic response to isoproterenol were different in each group.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms21186920
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2019364-6
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  • 3
    Online Resource
    Online Resource
    Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning
    MDPI AG ; 2020
    In:  Cells Vol. 9, No. 9 ( 2020-08-21), p. 1938-
    Details
    In: Cells, MDPI AG, Vol. 9, No. 9 ( 2020-08-21), p. 1938-
    Abstract: High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes causing cell-to-cell variability for understanding tumor heterogeneity. However, most existing methods detect the related genes separately, without considering gene interactions. In this paper, we proposed a novel learning framework to detect the interactive gene groups for scRNA-seq data based on co-expression network analysis and subgraph learning. We first utilized spectral clustering to identify the subpopulations of cells. For each cell subpopulation, the differentially expressed genes were then selected to construct a gene co-expression network. Finally, the interactive gene groups were detected by learning the dense subgraphs embedded in the gene co-expression networks. We applied the proposed learning framework on a real cancer scRNA-seq dataset to detect interactive gene groups of different cancer subtypes. Systematic gene ontology enrichment analysis was performed to examine the detected genes groups by summarizing the key biological processes and pathways. Our analysis shows that different subtypes exhibit distinct gene co-expression networks and interactive gene groups with different functional enrichment. The interactive genes are expected to yield important references for understanding tumor heterogeneity.
    Type of Medium: Online Resource
    ISSN: 2073-4409
    URL: Article
    DOI: 10.3390/cells9091938
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2661518-6
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  • 4
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    Online Resource
    Field Measurements of Wind Characteristics Using LiDAR on a Wind Farm with Downwind Turbines Installed in a Complex Terrain Region
    MDPI AG ; 2020
    In:  Energies Vol. 13, No. 19 ( 2020-10-02), p. 5135-
    Details
    In: Energies, MDPI AG, Vol. 13, No. 19 ( 2020-10-02), p. 5135-
    Abstract: Downwind turbines have favorable characteristics such as effective energy capture in up-flow wind conditions over complex terrains. They also have reduced risk of severe accidents in the event of disruptions to electrical networks during strong storms due to the free-yaw effect of downwind turbines. These favorable characteristics have been confirmed by wind-towing tank experiments and computational fluid dynamics (CFD) simulations. However, these advantages have not been fully demonstrated in field experiments on actual wind farms. In this study—although the final objective was to demonstrate the potential advantages of downwind turbines through field experiments—field measurements were performed using a vertical-profiling light detection and ranging (LiDAR) system on a wind farm with downwind turbines installed in complex terrains. To deduce the horizontal wind speed, vertical-profiling LiDARs assume that the flow of air is uniform in space and time. However, in complex terrains and/or in wind farms where terrain and/or wind turbines cause flow distortion or disturbances in time and space, this assumption is not valid, resulting in erroneous wind speed estimates. The magnitude of this error was evaluated by comparing LiDAR measurements with those obtained using a cup anemometer mounted on a meteorological mast and detailed analysis of line-of-sight wind speeds. A factor that expresses the nonuniformity of wind speed in the horizontal measurement plane of vertical-profiling LiDAR is proposed to estimate the errors in wind speed. The possibility of measuring and evaluating various wind characteristics such as flow inclination angles, turbulence intensities, wind shear and wind veer, which are important for wind turbine design and for wind farm operation is demonstrated. However, additional evidence of actual field measurements on wind farms in areas with complex terrains is required in order to obtain more universal and objective evaluations.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en13195135
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2437446-5
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  • 5
    Online Resource
    Online Resource
    Imaging Liquid Water in a Polymer Electrolyte Fuel Cell with High-Energy X-ray Compton Scattering
    MDPI AG ; 2023
    In:  Applied Sciences Vol. 13, No. 19 ( 2023-09-27), p. 10753-
    Details
    In: Applied Sciences, MDPI AG, Vol. 13, No. 19 ( 2023-09-27), p. 10753-
    Abstract: Compton scattering imaging with intense, high-energy synchrotron X-rays allows us to visualize a light element substance in an operating electrochemical device. In this paper, we report the first experiment of Compton scattering imaging (CSI) on an operating polymer electrolyte fuel cell (PEFC). The novelty of the CSI technique is a non-destructive direct observation of cross-sectional images with a sensitivity to light elements and a capability of simultaneous measurements with fluorescent X-rays of heavy elements. Analyses of the observed images provide the cross-sectional distribution of generated liquid water and its current density dependency. The results show that the amount of generated water increases in the vicinity of the cathode catalyst layer at current densities ranging from 100 to 500 mA/cm2, while it remains constant or slightly decreases from 500 to 900 mA/cm2. In both the gas diffusion layer and the channel, liquid water is observed near the channel and rib interface above 500 mA/cm2, indicating the formation of a liquid water flow path. In addition, simultaneous measurements of fluorescent Pt-Ka X-rays reveal a significant correlation between the generated liquid water and Pt catalysts, using the Pearson correlation coefficient. The result shows that water is dispersed in the catalyst layer without any correlation with the amount of Pt catalysts at low current densities, but water tends to be distributed in the Pt-rich areas at high current densities. This study demonstrates that Compton scattering imaging is one of the unique techniques to characterize the behavior of generated liquid water in an operating PEFC.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app131910753
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704225-X
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  • 6
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    Online Resource
    γH2AX, a DNA Double-Strand Break Marker, Correlates with PD-L1 Expression in Smoking-Related Lung Adenocarcinoma
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 12 ( 2022-06-15), p. 6679-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 12 ( 2022-06-15), p. 6679-
    Abstract: In recent years, the choice of immune checkpoint inhibitors (ICIs) as a treatment based on high expression of programmed death-ligand 1 (PD-L1) in lung cancers has been increasing in prevalence. The high expression of PD-L1 could be a predictor of ICI efficacy as well as high tumor mutation burden (TMB), which is determined using next-generation sequencing (NGS). However, a great deal of effort is required to perform NGS to determine TMB. The present study focused on γH2AX, a double-strand DNA break marker, and the suspected positive relation between TMB and γH2AX was investigated. We assessed the possibility of γH2AX being an alternative marker of TMB or PD-L1. One hundred formalin-fixed, paraffin-embedded specimens of lung cancer were examined. All of the patients in the study received thoracic surgery, having been diagnosed with lung adenocarcinoma or squamous cell carcinoma. The expressions of γH2AX and PD-L1 (clone: SP142) were evaluated immunohistochemically. Other immunohistochemical indicators, p53 and Ki-67, were also used to estimate the relationships of γH2AX. Positive relationships between γH2AX and PD-L1 were proven, especially in lung adenocarcinoma. Tobacco consumption was associated with higher expression of γH2AX, PD-L1, Ki-67, and p53. In conclusion, the immunoexpression of γH2AX could be a predictor for the adaptation of ICIs as well of as PD-L1 and TMB.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms23126679
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
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  • 7
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    Automated Classification of Urinary Cells: Using Convolutional Neural Network Pre-trained on Lung Cells
    MDPI AG ; 2023
    In:  Applied Sciences Vol. 13, No. 3 ( 2023-01-30), p. 1763-
    Details
    In: Applied Sciences, MDPI AG, Vol. 13, No. 3 ( 2023-01-30), p. 1763-
    Abstract: Urine cytology, which is based on the examination of cellular images obtained from urine, is widely used for the diagnosis of bladder cancer. However, the diagnosis is sometimes difficult in highly heterogeneous carcinomas exhibiting weak cellular atypia. In this study, we propose a new deep learning method that utilizes image information from another organ for the automated classification of urinary cells. We first extracted 3137 images from 291 lung cytology specimens obtained from lung biopsies and trained a classification process for benign and malignant cells using VGG-16, a convolutional neural network (CNN). Subsequently, 1380 images were extracted from 123 urine cytology specimens and used to fine-tune the CNN that was pre-trained with lung cells. To confirm the effectiveness of the proposed method, we introduced three different CNN training methods and compared their classification performances. The evaluation results showed that the classification accuracy of the fine-tuned CNN based on the proposed method was 98.8% regarding sensitivity and 98.2% for specificity of malignant cells, which were higher than those of the CNN trained with only lung cells or only urinary cells. The evaluation results showed that urinary cells could be automatically classified with a high accuracy rate. These results suggest the possibility of building a versatile deep-learning model using cells from different organs.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app13031763
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704225-X
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  • 8
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    CPT-11-Induced Delayed Diarrhea Develops via Reduced Aquaporin-3 Expression in the Colon
    MDPI AG ; 2018
    In:  International Journal of Molecular Sciences Vol. 19, No. 1 ( 2018-01-06), p. 170-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 19, No. 1 ( 2018-01-06), p. 170-
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms19010170
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2019364-6
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  • 9
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    Online Resource
    Automated Classification of Idiopathic Pulmonary Fibrosis in Pathological Images Using Convolutional Neural Network and Generative Adversarial Networks
    MDPI AG ; 2022
    In:  Diagnostics Vol. 12, No. 12 ( 2022-12-16), p. 3195-
    Details
    In: Diagnostics, MDPI AG, Vol. 12, No. 12 ( 2022-12-16), p. 3195-
    Abstract: Interstitial pneumonia of uncertain cause is referred to as idiopathic interstitial pneumonia (IIP). Among the various types of IIPs, the prognosis of cases of idiopathic pulmonary fibrosis (IPF) is extremely poor, and accurate differentiation between IPF and non-IPF pneumonia is critical. In this study, we consider deep learning (DL) methods owing to their excellent image classification capabilities. Although DL models require large quantities of training data, collecting a large number of pathological specimens is difficult for rare diseases. In this study, we propose an end-to-end scheme to automatically classify IIPs using a convolutional neural network (CNN) model. To compensate for the lack of data on rare diseases, we introduce a two-step training method to generate pathological images of IIPs using a generative adversarial network (GAN). Tissue specimens from 24 patients with IIPs were scanned using a whole slide scanner, and the resulting images were divided into patch images with a size of 224 × 224 pixels. A progressive growth GAN (PGGAN) model was trained using 23,142 IPF images and 7817 non-IPF images to generate 10,000 images for each of the two categories. The images generated by the PGGAN were used along with real images to train the CNN model. An evaluation of the images generated by the PGGAN showed that cells and their locations were well-expressed. We also obtained the best classification performance with a detection sensitivity of 97.2% and a specificity of 69.4% for IPF using DenseNet. The classification performance was also improved by using PGGAN-generated images. These results indicate that the proposed method may be considered effective for the diagnosis of IPF.
    Type of Medium: Online Resource
    ISSN: 2075-4418
    URL: Article
    DOI: 10.3390/diagnostics12123195
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662336-5
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  • 10
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    A Case of Extramedullary Plasmacytoma of the Biliary Tract with a Poor Prognosis
    MDPI AG ; 2022
    In:  Reports Vol. 6, No. 1 ( 2022-12-29), p. 1-
    Details
    In: Reports, MDPI AG, Vol. 6, No. 1 ( 2022-12-29), p. 1-
    Abstract: Extramedullary plasmacytoma (EMP) is a rare disease consisting of the presence of monoclonal plasma cells in tissues other than the bone. Most EMPs are located in the head and neck region. We present an extremely rare case of an EMP originating from the biliary tract in a 76-year-old male. This is the fifth report of a primary EMP arising from the biliary tract. He was diagnosed with jaundice, and he was referred for an additional examination. Abdominal ultrasonography revealed a tumor in the gallbladder and bile ducts, and a bile duct biopsy was performed via endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA). The pathological and immunohistochemical examination revealed that the tumor was a plasmacytoma originating in the biliary tract. Although endoscopic biliary drainage was performed, the bile duct infection was not well controlled due to obstructive jaundice caused by the tumor. Furthermore, the bleeding from the tumor during chemotherapy was uncontrolled. Pancreaticoduodenectomy and cholecystectomy were performed to control the infection and bleeding. Although chemotherapy was continued after surgery, the tumor of the intrahepatic bile duct enlarged. He died seven months after the diagnosis because of the treatment-resistant tumor.
    Type of Medium: Online Resource
    ISSN: 2571-841X
    URL: Article
    DOI: 10.3390/reports6010001
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2963537-8
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