GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Springer Science and Business Media LLC  (2)
  • Li, Hui  (2)
  • Zhang, Yan  (2)
Material
Publisher
  • Springer Science and Business Media LLC  (2)
Language
Years
  • 1
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2023
    In:  Aging Clinical and Experimental Research Vol. 35, No. 3 ( 2023-01-04), p. 639-647
    In: Aging Clinical and Experimental Research, Springer Science and Business Media LLC, Vol. 35, No. 3 ( 2023-01-04), p. 639-647
    Abstract: Elderly patients are susceptible to postoperative infections with increased mortality. Analyzing with a deep learning model, the perioperative factors that could predict and/or contribute to postoperative infections may improve the outcome in elderly. This was an observational cohort study with 2014 elderly patients who had elective surgery from 28 hospitals in China from April to June 2014. We aimed to develop and validate deep learning-based predictive models for postoperative infections in the elderly. 1510 patients were randomly assigned to be training dataset for establishing deep learning-based models, and 504 patients were used to validate the effectiveness of these models. The conventional model predicted postoperative infections was 0.728 (95% CI 0.688–0.768) with the sensitivity of 66.2% (95% CI 58.2–73.6) and specificity of 66.8% (95% CI 64.6–68.9). The deep learning model including risk factors relevant to baseline clinical characteristics predicted postoperative infections was 0.641 (95% CI 0.545–0.737), and sensitivity and specificity were 34.2% (95% CI 19.6–51.4) and 88.8% (95% CI 85.6–91.6), respectively. Including risk factors relevant to baseline variables and surgery, the deep learning model predicted postoperative infections was 0.763 (95% CI 0.681–0.844) with the sensitivity of 63.2% (95% CI 46–78.2) and specificity of 80.5% (95% CI 76.6–84). Our feasibility study indicated that a deep learning model including risk factors for the prediction of postoperative infections can be achieved in elderly. Further study is needed to assess whether this model can be used to guide clinical practice to improve surgical outcomes in elderly.
    Type of Medium: Online Resource
    ISSN: 1720-8319
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2119282-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2020
    In:  Cancer Cell International Vol. 20, No. 1 ( 2020-12)
    In: Cancer Cell International, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2020-12)
    Abstract: The prognosis of colon cancer is poor for metastasis, while the mechanism, especially adipocytes related, is not yet clear. The purpose of this study is to determine the effects of fatty acid binding protein 4 (FABP4), a transporter for lipids, on colon cancer progression. Methods The distribution of lipids and FABP4 was tested in the colon cancer tissues and adjacent normal tissues, and their relationship was also verified in vitro. Experiments about cellular invasion, migration and proliferation were performed to detect the impacts of FABP4 on the biological behaviors of colon cancer, and the positive results were checked in vivo. Meanwhile, the regulatory role of FABP4 in the energy and lipid metabolism was evaluated by the levels of triglyceride, ATP, LDH, glycerol and NEFA. At last, GO and KEGG analysis based on FABP4 overexpressed cells was performed, and the AKT pathway and epithelial–mesenchymal transition (EMT)-related proteins were determined by Western blot. Results Higher accumulation of lipids and stronger FABP4 transcription were observed in colon cancer tissues. Having been incubated with adipose tissue extract and overexpressed FABP4, colon cancer cells demonstrated enhanced lipid accumulation. In functional experiments, co-culture with adipose tissue extract significantly enhanced the invasion and migration of colon cancer cells, as well as the energy and lipid metabolism, and all these processes were reversed by FABP4 inhibitor. In addition, the metastasis of FABP4-overexpressed colon cancer cells was also significantly enhanced in vitro and in vivo. In terms of mechanism, the bioinformatics analysis showed that FABP4 was enriched in 11 pathways related to metabolic processes in FABP4 overexpressed cells. Finally, FABP4 overexpression improved EMT progression of colon cancer, as evidenced by the upregulation of Snail, MMP-2 and MMP-9, the downregulation of E-cadherin. The expression of p-Akt was also elevated. Conclusion FABP4 overexpression could increase FAs transport to enhance energy and lipid metabolism, and activate AKT pathway and EMT to promote the migration and invasion of colon cancer cells.
    Type of Medium: Online Resource
    ISSN: 1475-2867
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2091573-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...