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  • MDPI AG  (23)
  • 1
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    Changes in Homogalacturonan Metabolism in Banana Peel during Fruit Development and Ripening
    MDPI AG ; 2021
    In:  International Journal of Molecular Sciences Vol. 23, No. 1 ( 2021-12-27), p. 243-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 1 ( 2021-12-27), p. 243-
    Abstract: Though numerous studies have focused on the cell wall disassembly of bananas during the ripening process, the modification of homogalacturonan (HG) during fruit development remains exclusive. To better understand the role of HGs in controlling banana fruit growth and ripening, RNA-Seq, qPCR, immunofluorescence labeling, and biochemical methods were employed to reveal their dynamic changes in banana peels during these processes. Most HG-modifying genes in banana peels showed a decline in expression during fruit development. Four polygalacturonase and three pectin acetylesterases showing higher expression levels at later developmental stages than earlier ones might be related to fruit expansion. Six out of the 10 top genes in the Core Enrichment Gene Set were HG degradation genes, and all were upregulated after softening, paralleled to the significant increase in HG degradation enzyme activities, decline in peel firmness, and the epitope levels of 2F4, CCRC-M38, JIM7, and LM18 antibodies. Most differentially expressed alpha-1,4-galacturonosyltransferases were upregulated by ethylene treatment, suggesting active HG biosynthesis during the fruit softening process. The epitope level of the CCRC-M38 antibody was positively correlated to the firmness of banana peel during fruit development and ripening. These results have provided new insights into the role of cell wall HGs in fruit development and ripening.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms23010243
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 2
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    Fabrication of Porous SiC by Direct Selective Laser Sintering Effect of Boron Carbide
    MDPI AG ; 2021
    In:  Metals Vol. 11, No. 5 ( 2021-04-29), p. 737-
    Details
    In: Metals, MDPI AG, Vol. 11, No. 5 ( 2021-04-29), p. 737-
    Abstract: Additive manufactured porous SiC is a promising material applied in extreme conditions characterised by high temperatures, chemical corrosion, and irradiation etc. However, residual Si’s existence deteriorates its performance and limits its application in harsh environments. In this study, B4C was introduced into the selective laser sintering process of SiC, and its effects on forming ability, pore parameters, microstructure, and phases were investigated. The results showed that when B4C was added, the processing window was enlarged. The minimum energy density was reduced from 457 J/cm2 to 214 J/cm2 when the content of B4C reached 15 wt%. Microstructure orientation was enhanced, and the residual silicon content was decreased from 38 at.% to about 8 at.%. Small pores were turned into large pores with the increase of B4C addition. The findings indicate that the addition of B4C increases the amount of liquid phase during the laser sintering process of silicon carbide, improving the SiC struts’ density and reducing the residual silicon by reacting with it. Therefore, the addition of B4C will help improve the application performance of selected laser-sintered silicon carbide under extreme conditions.
    Type of Medium: Online Resource
    ISSN: 2075-4701
    URL: Article
    DOI: 10.3390/met11050737
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662252-X
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  • 3
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    Detection of Chlorophyll a and CDOM Absorption Coefficient with a Dual-Wavelength Oceanic Lidar: Wavelength Optimization Method
    MDPI AG ; 2020
    In:  Remote Sensing Vol. 12, No. 18 ( 2020-09-16), p. 3021-
    Details
    In: Remote Sensing, MDPI AG, Vol. 12, No. 18 ( 2020-09-16), p. 3021-
    Abstract: To overcome the retrieval problems in complex water, dual working wavelengths are required instead of a single wavelength in oceanic lidar. The wavelength optimization method of detecting chlorophyll a and Colored Dissolved Organic Matter (CDOM) absorption coefficient with a dual-wavelength lidar is studied in this paper. The inversion methods of chlorophyll a and CDOM absorption are developed based on the water absorption characteristics, which then lead to the inversion error equations. The effects of the wavelength on the inversion errors are studied. For the case in which λ1 and λ2 are both random, the errors are relatively small when λ1 is chosen between 420 and 560 nm and λ2 is selected under 420 nm. For the case in which λ1 is fixed at 532 nm, the errors generally decrease with decreasing λ2, with minimums around 300 and 356–360 nm under different water conditions. The wavelength optimization method discussed in this paper and the penetration depth criterion will be beneficial to the design of the dual-wavelength lidar.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs12183021
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 4
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    BrrA02.LMI1 Encodes a Homeobox Protein That Affects Leaf Margin Development in Brassica rapa
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 18 ( 2023-09-18), p. 14205-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 18 ( 2023-09-18), p. 14205-
    Abstract: Leaf margin morphology is an important quality trait affecting the commodity and environmental adaptability of crops. Brassica rapa is an ideal research material for exploring the molecular mechanisms underlying leaf lobe development. Here, we identified BrrA02.LMI1 to be a promising gene underlying the QTL qBrrLLA02 controlling leaf lobe formation in B. rapa, which was detected in our previous study. Sequence comparison analysis showed that the promoter divergences were the most obvious variations of BrrA02.LMI1 between parental lines. The higher expression level and promoter activity of BrrA02.LMI1 in the lobe-leafed parent indicated that promoter variations of BrrA02.LMI1 were responsible for elevating expression and ultimately causing different allele effects. Histochemical GUS staining indicated that BrrA02.LMI1 is mainly expressed at the leaf margin, with the highest expression at the tip of each lobe. Subcellular localization results showed that BrrA02.LMI1 was in the nucleus. The ectopic expression of BrrA02.LMI1 in A. thaliana resulted in a deep leaf lobe in the wild-type plants, and lobed leaf formation was disturbed in BrrA02.LMI11-downregulated plants. Our findings revealed that BrrA02.LMI1 plays a vital role in regulating the formation of lobed leaves, providing a theoretical basis for the selection and breeding of leaf-shape-diverse varieties of B. rapa.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms241814205
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 5
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    Maize (Zea mays L.) Stem Target Region Extraction and Stem Diameter Measurement Based on an Internal Gradient Algorithm in Field Conditions
    MDPI AG ; 2023
    In:  Agronomy Vol. 13, No. 5 ( 2023-04-22), p. 1185-
    Details
    In: Agronomy, MDPI AG, Vol. 13, No. 5 ( 2023-04-22), p. 1185-
    Abstract: The target region and diameter of maize stems are important phenotyping parameters for evaluating crop vitality and estimating crop biomass. To address the issue that the target region and diameter of maize stems obtained after transplantation may not accurately reflect the true growth conditions of maize, a phenotyping monitoring technology based on an internal gradient algorithm is proposed for acquiring the target region and diameter of maize stems. Observations were conducted during the small bell stage of maize. First, color images of maize plants were captured by an Intel RealSense D435i camera. The color information in the color image was extracted by the hue saturation value (HSV) color space model. The maximum between-class variance (Otsu) algorithm was applied for image threshold segmentation to obtain the main stem of maize. Median filtering, image binarization, and morphological opening operations were then utilized to remove noise from the images. Subsequently, the morphological gradient algorithm was applied to acquire the target region of maize stems. The similarity between the three types of gradient images and the manually segmented image was evaluated by pixel ratio extraction and image quality assessment indicators. Evaluation results indicated that the internal gradient algorithm could more accurately obtain the target region of maize stems. Finally, a checkerboard was employed as a reference for measurement assistance, and the stem diameter of maize was calculated by the pinhole imaging principle. The mean absolute error of stem diameter was 1.92 mm, the mean absolute percentage error (MAPE) was 5.16%, and the root mean square error (RMSE) was 2.25 mm. The R² value was 0.79. With an R² greater than 0.7 and a MAPE within 6%, the phenotyping monitoring technology based on the internal gradient algorithm was proven to accurately measure the diameter of maize stems. The application of phenotyping monitoring technology based on the internal gradient algorithm in field conditions provides technological support for smart agriculture.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy13051185
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 6
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    Nomograms for Predicting Disease-Free Survival Based on Core Needle Biopsy and Surgical Specimens in Female Breast Cancer Patients with Non-Pathological Complete Response to Neoadjuvant Chemotherapy
    MDPI AG ; 2023
    In:  Journal of Personalized Medicine Vol. 13, No. 2 ( 2023-01-29), p. 249-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 13, No. 2 ( 2023-01-29), p. 249-
    Abstract: Purpose: While a pathologic complete response (pCR) is regarded as a surrogate endpoint for pos-itive outcomes in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC), fore-casting the prognosis of non-pCR patients is still an open issue. This study aimed to create and evaluate nomogram models for estimating the likelihood of disease-free survival (DFS) for non-pCR patients. Methods: A retrospective analysis of 607 non-pCR BC patients was conducted (2012–2018). After converting continuous variables to categorical variables, variables entering the model were progressively identified by univariate and multivariate Cox regression analyses, and then pre-NAC and post-NAC nomogram models were developed. Regarding their discrimination, ac-curacy, and clinical value, the performance of the models was evaluated by internal and external validation. Two risk assessments were performed for each patient based on two models; patients were separated into different risk groups based on the calculated cut-off values for each model, including low-risk (assessed by the pre-NAC model) to low-risk (assessed by the post-NAC model), high-risk to low-risk, low-risk to high-risk, and high-risk to high-risk groups. The DFS of different groups was assessed using the Kaplan–Meier method. Results: Both pre-NAC and post-NAC nomogram models were built with clinical nodal (cN) status and estrogen receptor (ER), Ki67, and p53 status (all p 〈 0.05), showing good discrimination and calibration in both internal and external validation. We also assessed the performance of the two models in four subtypes, with the tri-ple-negative subtype showing the best prediction. Patients in the high-risk to high-risk subgroup have significantly poorer survival rates (p 〈 0.0001). Conclusion: Two robust and effective nomo-grams were developed to personalize the prediction of DFS in non-pCR BC patients treated with NAC.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm13020249
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662248-8
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  • 7
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    Genome-Wide Identification, Classification, Characterization, and Expression Analysis of the Wall-Associated Kinase Family during Fruit Development and under Wound Stress in Tomato (Solanum lycopersicum L.)
    MDPI AG ; 2020
    In:  Genes Vol. 11, No. 10 ( 2020-10-12), p. 1186-
    Details
    In: Genes, MDPI AG, Vol. 11, No. 10 ( 2020-10-12), p. 1186-
    Abstract: The wall-associated kinase (WAK) and wall-associated kinase like (WAKL) is a subfamily of receptor-like kinases associated with the cell wall, which have been suggested as sensors of the extracellular environment and triggers of intracellular signals. However, these proteins have not yet been comprehensively analyzed in tomato (Solanum lycopersicum L.). In this study, 11 SlWAK and 18 SlWAKL genes were identified in an uneven distribution in 9 of 12 chromosomes. GUB-WAK-bind (wall-associated receptor kinase galacturonan-binding) and epidermal growth factor (EGF) domains appear more often in SlWAK proteins. However, more SlWAKLs (wall-associated kinase like) have a WAK-assoc (wall-associated receptor kinase C-terminal) domain. Based on their phylogenetic relationships, 29 SlWAK-RLKs (wall associated kinase-receptor like kinases) were clustered into three distinct categories analogous to those in Arabidopsis thaliana. High similarities were found in conserved motifs of the genes within each group. Cis-elements in the promoter region of these 29 genes were found mainly in response to methyl jasmonate (MeJA), abscisic acid (ABA), salicylic acid (SA), anaerobic, light, wound, and MYB transcription factors. Public tomato genome RNA-seq data indicates that multiple SlWAK-RLKs showed different expression patterns under developmental and ripening stages of fruits, such as SlWAK4, SlWAKL11, SlWAKL9, SlWAKL15, SlWAKL14, and SlWAKL1, their RPKM (Reads Per Kilo bases per Million reads) value constantly increases during the fruit expansion period, and decreases as the fruit matures. In tomato leaves, our RNA-seq data showed that nine SlWAK-RLKs transcripts (SlWAK3, SlWAK4, SlWAK10,SlWAKL1, SlWAKL2, SlWAKL3, SlWAKL5, SlWAKL14, and SlWAKL18) were significantly induced (p 〈 0.001), and three transcripts (SlWAK2, SlWAK5, and SlWAKL15) were significantly inhibited (p 〈 0.001) under mechanical wounding. The qRT-PCR (Quantitative reverse transcription polymerase chain reaction) of SlWAKL1 and SlWAKL6 verify these results.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    URL: Article
    DOI: 10.3390/genes11101186
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2527218-4
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  • 8
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    Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 2 ( 2023-01-16), p. 1617-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 2 ( 2023-01-16), p. 1617-
    Abstract: Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p 〈 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20021617
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
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  • 9
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    Simulation of Land Use Change and Habitat Quality in the Yellow River Basin under Multiple Scenarios
    MDPI AG ; 2022
    In:  Water Vol. 14, No. 22 ( 2022-11-19), p. 3767-
    Details
    In: Water, MDPI AG, Vol. 14, No. 22 ( 2022-11-19), p. 3767-
    Abstract: Habitat quality is the key to regional ecological restoration and green development, and land use change is an essential factor affecting habitat quality. Studying the spatial and temporal evolution characteristics of land use change and habitat quality under multiple scenarios is significant for regional ecological restoration and management, and for preventing future ecological and environmental risks. We used the improved Logistic-CA-Markov (Logistic-Cellular Automata-Markov) and InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) models to establish the spatial patterns of habitat quality in the Yellow River Basin from 2000 to 2040 and analyzed the characteristics of land use and habitat quality changes under scenarios of natural development (S1), ecological protection (S2), and urban expansion (S3). The results showed that in 2000, 2005, 2010, 2015, and 2020, the main land use types in the watershed were dryland and grassland, accounting for more than 72%. Paddy land, dryland, woodland, middle-coverage grassland, and unused land all showed decreasing trends, whereas all other land types showed increasing trends. Influenced by human activities and the environment, the watershed habitat quality was low, with 80% of the areas with middle to low grades, but the overall trend was rising. The spatial variability in habitat quality of the watershed was significant, with habitat quality improvements in the central and northern regions and continued deterioration around the cities in the southern and western parts. The spatial autocorrelation and aggregation of habitat quality in the watershed were strong, and future land use patterns in the study area had a significant relationship with human activities. Simulation of future scenarios revealed ecological conservation catalytic effects on habitat quality in the study area, whereas urban expansion deteriorated watershed habitat quality. This study could provide support for future ecological conservation decisions.
    Type of Medium: Online Resource
    ISSN: 2073-4441
    URL: Article
    DOI: 10.3390/w14223767
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2521238-2
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  • 10
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    Maize Stem Contour Extraction and Diameter Measurement Based on Adaptive Threshold Segmentation in Field Conditions
    MDPI AG ; 2023
    In:  Agriculture Vol. 13, No. 3 ( 2023-03-14), p. 678-
    Details
    In: Agriculture, MDPI AG, Vol. 13, No. 3 ( 2023-03-14), p. 678-
    Abstract: Solving the problem of the stem contour extraction of maize is difficult under open field conditions, and the stem diameter cannot be measured quickly and nondestructively. In this paper, maize at the small and large bell stages was the object of study. An adaptive threshold segmentation algorithm based on the color space model was proposed to obtain the stem contour and stem diameter of maize in the field. Firstly, 2D images of the maize stem in the field were captured with an RGB-D camera. Then, the images were processed by hue saturation value (HSV) color space. Next, the stem contour of the maize was extracted by maximum between-class variance (Otsu). Finally, the reference method was used to obtain the stem diameter of the maize. Scatter plots and Dice coefficients were used to compare the contour extraction effects of the HSV + fixed threshold algorithm, the HSV + Otsu algorithm, and the HSV + K-means algorithm. The results showed that the HSV + Otsu algorithm is the optimal choice for extracting the maize stem contour. The mean absolute error, mean absolute percentage error (MAPE), and root mean square error (RMSE) of the maize stem diameter at the small bell stage were 4.30 mm, 10.76%, and 5.29 mm, respectively. The mean absolute error, MAPE, and RMSE of the stem diameter of the maize at the large bell stage were 4.78 mm, 12.82%, and 5.48 mm, respectively. The MAPE was within 10–20%. The results showed that the HSV + Otsu algorithm could meet the requirements for stem diameter measurement and provide a reference for the acquisition of maize phenotypic parameters in the field. In the meantime, the acquisition of maize phenotypic parameters under open field conditions provides technical and data support for precision farming and plant breeding.
    Type of Medium: Online Resource
    ISSN: 2077-0472
    URL: Article
    DOI: 10.3390/agriculture13030678
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2651678-0
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