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  • MDPI AG  (50)
  • 1
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    Accurate Diagnosis and Survival Prediction of Bladder Cancer Using Deep Learning on Histological Slides
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 23 ( 2022-11-25), p. 5807-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 23 ( 2022-11-25), p. 5807-
    Abstract: (1) Background: Early diagnosis and treatment are essential to reduce the mortality rate of bladder cancer (BLCA). We aimed to develop deep learning (DL)-based weakly supervised models for the diagnosis of BLCA and prediction of overall survival (OS) in muscle-invasive bladder cancer (MIBC) patients using whole slide digitized histological images (WSIs). (2) Methods: Diagnostic and prognostic models were developed using 926 WSIs of 412 BLCA patients from The Cancer Genome Atlas cohort. We collected 250 WSIs of 150 BLCA patients from the Renmin Hospital of Wuhan University cohort for external validation of the models. Two DL models were developed: a BLCA diagnostic model (named BlcaMIL) and an MIBC prognostic model (named MibcMLP). (3) Results: The BlcaMIL model identified BLCA with accuracy 0.987 in the external validation set, comparable to that of expert uropathologists and outperforming a junior pathologist. The C-index values for the MibcMLP model on the internal and external validation sets were 0.631 and 0.622, respectively. The risk score predicted by MibcMLP was a strong predictor independent of existing clinical or histopathologic indicators, as demonstrated by univariate Cox (HR = 2.390, p 〈 0.0001) and multivariate Cox (HR = 2.414, p 〈 0.0001) analyses. The interpretability of DL models can help in the analysis of critical regions associated with tumors to enrich the information obtained from WSIs. Furthermore, the expression of six genes (ANAPC7, MAPKAPK5, COX19, LINC01106, AL161431.1 and MYO16-AS1) was significantly associated with MibcMLP-predicted risk scores, revealing possible potential biological correlations. (4) Conclusions: Our study developed DL models for accurately diagnosing BLCA and predicting OS in MIBC patients, which will help promote the precise pathological diagnosis of BLCA and risk stratification of MIBC to improve clinical treatment decisions.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14235807
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 2
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    Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 3 ( 2023-02-01), p. 2746-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 3 ( 2023-02-01), p. 2746-
    Abstract: Although the tumor-stroma ratio (TSR) has prognostic value in many cancers, the traditional semi-quantitative visual assessment method has inter-observer variability, making it impossible for clinical practice. We aimed to develop a machine learning (ML) algorithm for accurately quantifying TSR in hematoxylin-and-eosin (H & E)-stained whole slide images (WSI) and further investigate its prognostic effect in patients with muscle-invasive bladder cancer (MIBC). We used an optimal cell classifier previously built based on QuPath open-source software and ML algorithm for quantitative calculation of TSR. We retrospectively analyzed data from two independent cohorts to verify the prognostic significance of ML-based TSR in MIBC patients. WSIs from 133 MIBC patients were used as the discovery set to identify the optimal association of TSR with patient survival outcomes. Furthermore, we performed validation in an independent external cohort consisting of 261 MIBC patients. We demonstrated a significant prognostic association of ML-based TSR with survival outcomes in MIBC patients (p 〈 0.001 for all comparisons), with higher TSR associated with better prognosis. Uni- and multivariate Cox regression analyses showed that TSR was independently associated with overall survival (p 〈 0.001 for all analyses) after adjusting for clinicopathological factors including age, gender, and pathologic stage. TSR was found to be a strong prognostic factor that was not redundant with the existing staging system in different subgroup analyses (p 〈 0.05 for all analyses). Finally, the expression of six genes (DACH1, DEEND2A, NOTCH4, DTWD1, TAF6L, and MARCHF5) were significantly associated with TSR, revealing possible potential biological relevance. In conclusion, we developed an ML algorithm based on WSIs of MIBC patients to accurately quantify TSR and demonstrated its prognostic validity for MIBC patients in two independent cohorts. This objective quantitative method allows application in clinical practice while reducing the workload of pathologists. Thus, it might be of significant aid in promoting precise pathology services in MIBC.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms24032746
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 3
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    Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer
    MDPI AG ; 2022
    In:  Journal of Clinical Medicine Vol. 11, No. 23 ( 2022-11-29), p. 7081-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 11, No. 23 ( 2022-11-29), p. 7081-
    Abstract: (1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evaluate the prognostic value of quantitative TILs score based on a machine learning (ML) algorithm to identify MIBC patients who might benefit from immunotherapy or the de-escalation of therapy. (2) Methods: We constructed an artificial neural network classifier for tumor cells, lymphocytes, stromal cells, and “ignore” cells from hematoxylin-and-eosin-stained slide images using the QuPath open source software. We defined four unique TILs variables based on ML to analyze TILs measurements. Pathological slide images from 133 MIBC patients were retrospectively collected as the discovery set to determine the optimal association of ML-read TILs variables with patient survival outcomes. For validation, we evaluated an independent external validation set consisting of 247 MIBC patients. (3) Results: We found that all four TILs variables had significant prognostic associations with survival outcomes in MIBC patients (p 〈 0.001 for all comparisons), with higher TILs score being associated with better prognosis. Univariate and multivariate Cox regression analyses demonstrated that electronic TILs (eTILs) variables were independently associated with overall survival after adjustment for clinicopathological factors including age, sex, and pathological stage (p 〈 0.001 for all analyses). Results analyzed in different subgroups showed that the eTILs variable was a strong prognostic factor that was not redundant with pre-existing clinicopathological features (p 〈 0.05 for all analyses). (4) Conclusion: ML-driven cell classifier-defined TILs variables were robust and independent prognostic factors in two independent cohorts of MIBC patients. eTILs have the potential to identify a subset of high-risk stage II or stage III-IV MIBC patients who might benefit from adjuvant immunotherapy.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm11237081
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662592-1
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  • 4
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    The Influence of Temperature Changes on the Rice Starch Structure and Digestive Characteristics: One and Two-Step Annealing
    MDPI AG ; 2022
    In:  Foods Vol. 11, No. 22 ( 2022-11-14), p. 3641-
    Details
    In: Foods, MDPI AG, Vol. 11, No. 22 ( 2022-11-14), p. 3641-
    Abstract: This study investigated the effects of annealing on the structural and physicochemical properties of rice starch below the onset temperature (To) by 5 °C and 15 °C. The results revealed that annealing improved the gelatinization temperature of rice starch, decreased the swelling power, solubility, and paste viscosity of rice starch, and had no significant effects on the morphological structure and crystal configuration of rice starch. In one-step annealing, the annealing temperature of 60 °C is more conducive to the rearrangement of starch molecules, so its crystallinity, short-range ordered structure, and gelatinization temperature are higher than at 50 °C; however, its RDS, SDS, and RS contents will be increased. During the two-step annealing treatment, the temperature change is not conducive to the molecular chain rearrangement and to the formation of perfect crystalline structure, which increases the sensitivity of enzymes to starch, so the RDS content of starch increases significantly, while the RS content decreases.
    Type of Medium: Online Resource
    ISSN: 2304-8158
    URL: Article
    DOI: 10.3390/foods11223641
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704223-6
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  • 5
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    A Review of Smart Materials in Tactile Actuators for Information Delivery
    MDPI AG ; 2017
    In:  C Vol. 3, No. 4 ( 2017-12-08), p. 38-
    Details
    In: C, MDPI AG, Vol. 3, No. 4 ( 2017-12-08), p. 38-
    Type of Medium: Online Resource
    ISSN: 2311-5629
    URL: Article
    DOI: 10.3390/c3040038
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2813973-2
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  • 6
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    Red Blood Cells-Derived Iron Self–Doped 3D Porous Carbon Networks for Efficient Oxygen Reduction
    MDPI AG ; 2022
    In:  Catalysts Vol. 12, No. 3 ( 2022-02-28), p. 273-
    Details
    In: Catalysts, MDPI AG, Vol. 12, No. 3 ( 2022-02-28), p. 273-
    Abstract: In addition to C, H and O, some biomass is also rich in mineral elements. The recovery and utilization of special mineral elements is of great significance to prepare functional materials and alleviate the current energy shortage. Herein, we describe a facile strategy for making full use of the chemical composition (C, Fe) and special structure of red blood cells (RBCs) from waste pig blood to fabricate a dual metal (Fe, Co)-nitrogen (N)-doped porous carbon catalyst by pyrolysis of a mixture of RBCs biomass, cobaltous acetate, and melamine. The porous catalyst displays a comparable activity for oxygen reduction reaction (ORR) to that of commercial Pt/C catalyst, with a half-wave potential of 0.821 VvsRHE in alkaline media and 0.672 VvsRHE in acid electrolyte. Especially, the as-prepared catalyst shows excellent methanol tolerance and stability in both acidic and alkaline electrolytes, which is superior to commercial Pt/C catalysts. The excellent ORR activity of FeCo-N/C(RBC) can be ascribed to the porous morphology and the cooperation between metal and nitrogen species. This work provides a novel idea of exploiting the composition of renewable biomass to modulate the activity and stability of carbon-based ORR catalysts.
    Type of Medium: Online Resource
    ISSN: 2073-4344
    URL: Article
    DOI: 10.3390/catal12030273
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662126-5
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  • 7
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    Effects of Dietary Fiber, Crude Protein Level, and Gestation Stage on the Nitrogen Utilization of Multiparous Gestating Sows
    MDPI AG ; 2022
    In:  Animals Vol. 12, No. 12 ( 2022-06-14), p. 1543-
    Details
    In: Animals, MDPI AG, Vol. 12, No. 12 ( 2022-06-14), p. 1543-
    Abstract: To investigate the effects of dietary fiber (DF), crude protein (CP) level, and gestation stage on nitrogen utilization, 28 Landrace-Yorkshire cross gestating sows at parity two were randomly divided into four dietary treatments with seven duplicates of one pig with a repeated-measures design. The diets comprised one with normal crude protein (CP) of 13.3%, one with a low CP diet of 10.1%, and two diets, one with dietary fiber (DF) supplementation of inulin and cellulose at the ratio of 1:1 and one without DF. The total litter size, litter size alive, and newborn birthweight of piglets did not differ between treatment groups. Sows that received high DF levels had greater nitrogen output in feces, lower urinary nitrogen, and increased nitrogen retention. Sows that received a low CP diet had reduced nitrogen excretion in feces and urine, lower nitrogen retention, and an unchanged nitrogen retention ratio. Sows at the late stage of gestation on days 95 to 98 had lower nitrogen excretion in urine and greater nitrogen retention than in the early stage of gestation on days 35 to 38, associated with a significant decrease in serum amino acids in late gestation. Maternal protein deposition was increased by high DF, decreased by low CP, and lower in late gestation compared with early gestation. Collectively, DF improved nitrogen utilization by decreasing urine nitrogen output, and nitrogen utilization increased as gestation advanced.
    Type of Medium: Online Resource
    ISSN: 2076-2615
    URL: Article
    DOI: 10.3390/ani12121543
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2606558-7
    SSG: 23
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  • 8
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    Development and External Validation of an Improved Version of the Diagnostic Model for Opportunistic Screening of Malignant Esophageal Lesions
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 23 ( 2022-11-30), p. 5945-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 23 ( 2022-11-30), p. 5945-
    Abstract: We aimed to develop an improved version of the diagnostic model predicting the risk of malignant esophageal lesions in opportunistic screening and validate it in external populations. The development set involved 10,595 outpatients receiving endoscopy from a hospital in Hua County, a high-risk region for esophageal squamous cell carcinoma in northern China. Validation set A enrolled 9453 outpatients receiving endoscopy in a non-high-risk region in southern China. Validation set B involved 17,511 residents in Hua County. The improved diagnostic model consisted of seven predictors including age, gender, family history of esophageal squamous cell carcinoma, smoking, body mass index, dysphagia, and retrosternal pain, with an area under the receiver operating characteristic curve (AUC) of 0.860 (95% confidence interval: 0.835–0.886) in the development set. Ideal discrimination ability was achieved in external validations (AUC validation set A: 0.892, 95% confidence interval: 0.858–0.926; AUC validation set B: 0.799, 95% confidence interval: 0.705–0.894). This improved model also markedly increased the detection rate of malignant esophageal lesions compared with universal screening, demonstrating great potential for use in opportunistic screening of malignant esophageal lesions in heterogeneous populations.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14235945
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 9
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    Spatially Varying Relationships between Land Subsidence and Urbanization: A Case Study in Wuhan, China
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 2 ( 2022-01-09), p. 291-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 2 ( 2022-01-09), p. 291-
    Abstract: Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14020291
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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  • 10
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    Phthalate Esters Metabolic Strain Gordonia sp. GZ-YC7, a Potential Soil Degrader for High Concentration Di-(2-ethylhexyl) Phthalate
    MDPI AG ; 2022
    In:  Microorganisms Vol. 10, No. 3 ( 2022-03-17), p. 641-
    Details
    In: Microorganisms, MDPI AG, Vol. 10, No. 3 ( 2022-03-17), p. 641-
    Abstract: As commonly used chemical plasticizers in plastic products, phthalate esters have become a serious ubiquitous environmental pollutant, such as in soil of plastic film mulch culture. Microbial degradation or transformation was regarded as a suitable strategy to solve the phthalate esters pollution. Thus, a new phthalate esters degrading strain Gordonia sp. GZ-YC7 was isolated in this study, which exhibited the highest di-(2-ethylhexyl) phthalate degradation efficiency under 1000 mg/L and the strongest tolerance to 4000 mg/L. The comparative genomic analysis results showed that there exist diverse esterases for various phthalate esters such as di-(2-ethylhexyl) phthalate and dibutyl phthalate in Gordonia sp. GZ-YC7. This genome characteristic possibly contributes to its broad substrate spectrum, high degrading efficiency, and high tolerance to phthalate esters. Gordonia sp. GZ-YC7 has potential for the bioremediation of phthalate esters in polluted soil environments.
    Type of Medium: Online Resource
    ISSN: 2076-2607
    URL: Article
    DOI: 10.3390/microorganisms10030641
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2720891-6
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