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  • Frontiers Media SA  (4)
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  • Frontiers Media SA  (4)
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  • 1
    Online Resource
    Online Resource
    Table_4.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Oncology Vol. 11 ( 2021-3-16)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-3-16)
    Abstract: Aberrant expression of CD123 (IL-3Rα) was observed in various hematological malignancies including acute lymphoblastic leukemia (ALL), which is the most common malignancy in childhood. Although widely used for minimal residual disease (MRD) monitoring, the prognostic value of CD123 has not been fully characterized in pediatric B-ALL. This retrospective study aims to evaluate the association between the CD123 expression of leukemic blasts and the outcomes of the pediatric B-ALL patients. Methods A total of 976 pediatric B-ALL, including 328 treated with CCLG-ALL-2008 protocol and 648 treated with CCCG-ALL-2015 protocol, were recruited in this retrospective study. CD123 expression was evaluated by flow cytometry. Patients with & gt;50, 20–50, or & lt;20% of CD123 expressing blasts were grouped into CD123 high , CD123 low , and CD123 neg , respectively. The correlation between CD123 expression and the patients’ clinical characteristics, overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS) were studied statistically. Results Of 976 pediatric B-ALL, 53.4% from the CCLG-ALL-2008 cohort and 49.2% from the CCCG-ALL-2015 cohort were CD123 high . In the CCLG-ALL-2008 cohort, CD123 high was significantly associated with chromosome hyperdiploidy (p & lt; 0.0001), risk stratification (p = 0.004), and high survival rate (p = 0.005). By comparing clinical outcomes, patients with CD123 high displayed favorable prognosis, with a significantly better OS (p = 0.005), EFS (p = 0.017), and RFS (p = 0.045), as compared to patients with CD123 low and CD123 neg . The prognostic value of CD123 expression was subsequently confirmed in the CCCG-ALL-2015 cohort. Univariate and multivariate cox regression model analysis showed that high CD123 expression was independently associated with favorable EFS (OR: 0.528; 95% CI: 0.327 to 0.853; p = 0.009) in this cohort. In patients without prognosis-defining genomic abnormalities, high CD123 expression strongly indicated superior survival rates and was identified as an independent prognosis factor for EFS and RFS in both cohorts. Conclusions A group of B-ALL lacks prognosis-defining genomic aberrations, which proposes a challenge in risk stratification. Our findings revealed that high CD123 expression of leukemic blasts was associated with favorable clinical outcomes in pediatric B-ALL and CD123 could serve as a promising prognosis predictor, especially in patients without prognosis-defining genetic aberrations.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
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    URL: Article
    DOI: 10.3389/fonc.2021.614420
    DOI: 10.3389/fonc.2021.614420.s001
    DOI: 10.3389/fonc.2021.614420.s002
    DOI: 10.3389/fonc.2021.614420.s003
    DOI: 10.3389/fonc.2021.614420.s004
    DOI: 10.3389/fonc.2021.614420.s005
    DOI: 10.3389/fonc.2021.614420.s006
    DOI: 10.3389/fonc.2021.614420.s007
    DOI: 10.3389/fonc.2021.614420.s008
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2649216-7
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Lightning Strike Location Identification Based on 3D Weather Radar Data
    Frontiers Media SA ; 2021
    In:  Frontiers in Environmental Science Vol. 9 ( 2021-8-4)
    Details
    In: Frontiers in Environmental Science, Frontiers Media SA, Vol. 9 ( 2021-8-4)
    Abstract: Lightning is an instantaneous, intense, and convective weather phenomenon that can produce great destructive power and easily cause serious economic losses and casualties. It always occurs in convective storms with small spatial scales and short life cycles. Weather radar is one of the best operational instruments that can monitor the detailed 3D structures of convective storms at high spatial and temporal resolutions. Thus, extracting the features related to lightning automatically from 3D weather radar data to identify lightning strike locations would significantly benefit future lightning predictions. This article makes a bold attempt to apply three-dimensional radar data to identify lightning strike locations, thereby laying the foundation for the subsequent accurate and real-time prediction of lightning locations. First, that issue is transformed into a binary classification problem. Then, a suitable dataset for the recognition of lightning strike locations based on 3D radar data is constructed for system training and evaluation purposes. Furthermore, the machine learning methods of a convolutional neural network, logistic regression, a random forest, and k-nearest neighbors are employed to carry out experiments. The results show that the convolutional neural network has the best performance in identifying lightning strike locations. This technique is followed by the random forest and k-nearest neighbors, and the logistic regression produces the worst manifestation.
    Type of Medium: Online Resource
    ISSN: 2296-665X
    URL: Article
    DOI: 10.3389/fenvs.2021.714067
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2741535-1
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Table_2.XLSX
    Frontiers Media SA ; 2021
    In:  Frontiers in Genetics Vol. 12 ( 2021-8-10)
    Details
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 12 ( 2021-8-10)
    Abstract: Submicroscopic segmental imbalances detected by array-comparative genomic hybridization (array-CGH) were discovered to be common in chronic myeloid leukemia (CML) patients with t (9;22) as the sole chromosomal anomaly. To confirm the findings of the previous study and expand the investigation, additional CML patients with t (9;22) as the sole chromosomal anomaly were recruited and copy number variants (CNVs) were searched for. Methods Karyotyping tests were performed on 106 CML patients during January 2010–September 2019 in our Genetics Laboratory. Eighty-four (79.2%) patients had the Philadelphia (Ph) chromosome as the sole chromosomal anomaly. Only 49(58.3%) of these 84 patients had sufficient marrow or leukemia blood materials to additionally be included in the array-CGH analysis. Fluorescence in situ hybridization (FISH) was carried out to confirm the genes covered by the deleted or duplicated regions of the CNVs. Results 11(22.4%) out of the 49 patients were found to have one to three somatic segmental somatic segmental (CNVs), including fourteen deletions and three duplications. The common region associated with deletions was on 9q33.3-34.12. Identified in five (45.5%) of the 11 positive patients with segmental CNVs, the deletions ranged from 106 kb to 4.1 Mb in size. Two (18.2%) cases had a deletion in the ABL1-BCR fusion gene on der (9), while three (27.3%) cases had a deletion in the ASS1 gene. The remaining CNVs were randomly distributed on different autosomes. Conclusion Subtle genomic CNVs are relatively common in CML patients without cytogenetically visible additional chromosomal aberrations (ACAs). Long-term studies investigating the potential impact on patient prognosis and treatment outcome is underway.
    Type of Medium: Online Resource
    ISSN: 1664-8021
    URL: Article
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    DOI: 10.3389/fgene.2021.697009
    DOI: 10.3389/fgene.2021.697009.s001
    DOI: 10.3389/fgene.2021.697009.s002
    DOI: 10.3389/fgene.2021.697009.s003
    DOI: 10.3389/fgene.2021.697009.s004
    DOI: 10.3389/fgene.2021.697009.s005
    DOI: 10.3389/fgene.2021.697009.s006
    DOI: 10.3389/fgene.2021.697009.s007
    DOI: 10.3389/fgene.2021.697009.s008
    DOI: 10.3389/fgene.2021.697009.s009
    DOI: 10.3389/fgene.2021.697009.s010
    DOI: 10.3389/fgene.2021.697009.s011
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606823-0
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  • 4
    Online Resource
    Online Resource
    Table_1.docx
    Frontiers Media SA ; 2024
    In:  Frontiers in Microbiology Vol. 15 ( 2024-3-14)
    Details
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 15 ( 2024-3-14)
    Abstract: Soil nitrogen (N) availability is one of the limiting factors of crop productivity, and it is strongly influenced by global change and agricultural management practices. However, very few studies have assessed how the winter drought affected soil N availability during the subsequent growing season under chemical fertilization. We conducted a field investigation involving snow removal to simulate winter drought conditions in a Mollisol cropland in Northeast China as part of a 6-year fertilization experiment, and we examined soil physicochemical properties, microbial characteristics, and N availability. Our results demonstrated that chemical fertilization significantly increased soil ammonium and total N availability by 42.9 and 90.3%, respectively; a combined winter drought and fertilization treatment exhibited the highest soil N availability at the end of the growing season. As the growing season continued, the variation in soil N availability was explained more by fertilization than by winter drought. The Mantel test further indicated that soil Olsen-P content and microbial carbon use efficiency (CUE) were significantly related to soil ammonium availability. A microbial community structure explained the largest fraction of the variation in soil nitrate availability. Microbial CUE showed the strongest correlation with soil N availability, followed by soil available C:P and bacteria:fungi ratios under winter drought and chemical fertilization conditions. Overall, we clarified that, despite the weak effect of the winter drought on soil N availability, it cannot be ignored. Our study also identified the important role of soil microorganisms in soil N transformations, even in seasonally snow-covered northern croplands.
    Type of Medium: Online Resource
    ISSN: 1664-302X
    URL: Article
    URL: Article
    DOI: 10.3389/fmicb.2024.1304985
    DOI: 10.3389/fmicb.2024.1304985.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2587354-4
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