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1.
Reprod Biol ; 23(3): 100792, 2023 Sep.
Article En | MEDLINE | ID: mdl-37523789

The teratomas formation has severely hindered the application of embryonic stem cells (ESCs) in clinical trials. Apurinic/apyrimidinic endonuclease 1 (APE1) is strongly involved in the development of tumors and differentiation process of stem cells. However, the role of APE1 in teratomas remains unknown. The expression of APE1 was examined in mouse ESCs (mESCs) by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blot. The role and mechanism of APE1 in the proliferation, pluripotency and differentiation of E14 cells were determined by cell counting, flow cytometry and western blot assays. Besides, the role of APE1 in teratomas was also probed in xenografted mice. The expression of APE1 was upregulated in mESCs with differentiation. Knockdown of APE1 reduced the cell numbers, induced the arrest of the G2/M phase, and decreased the expression of cell cycle-related proteins in E14 cells. Besides, loss- and gain-of-function assays revealed that APE1 enhanced the levels of proteins involved in pluripotency, reduced the protein expression of ectoderm markers, and increased the protein levels of endoderm markers in E14 cells. Mechanically, inhibition of APE1 downregulated the expression of GDNF and GFRα1 in E14 cells. GDNF reversed the role of APE1 in the proliferation, pluripotency and embryogenesis of E14 cells. Moreover, suppression of APE1 reduced the teratoma volume and the relative protein expression of endoderm markers, but increased the relative protein expression of ectoderm markers in xenografted mice. Collectively, knockdown of APE1 attenuated proliferation, pluripotency and embryogenesis of mESCs via GDNF/GFRα1 axis.


Glial Cell Line-Derived Neurotrophic Factor , Teratoma , Animals , Mice , Cell Differentiation , Cell Proliferation , Embryonic Stem Cells/metabolism , Glial Cell Line-Derived Neurotrophic Factor/metabolism , Teratoma/metabolism , Humans
2.
J Healthc Eng ; 2021: 7096286, 2021.
Article En | MEDLINE | ID: mdl-34824765

In this study, CT image technology based on level set intelligent segmentation algorithm was used to evaluate the postoperative enteral nutrition of neonatal high intestinal obstruction and analyze the clinical treatment effect of high intestinal obstruction, so as to provide a reasonable research basis for the clinical application of neonatal high intestinal obstruction. 60 children with high intestinal obstruction treated in the hospital were selected as the research objects. Based on the postoperative enteral nutrition treatment, they were divided into control group (noncatheterization group)-parenteral nutrition support. In the observation group, gastric tube was placed through nose for nutritional support. Then, CT images based on level set segmentation algorithm were used to compare the intestinal recovery of the two groups, and the biochemical indexes and hospitalization were compared. The level set algorithm can accurately segment the lesions in CT images. The segmentation time of the level set algorithm was shorter than that of the traditional algorithm (24.34 ± 2.01 s vs. 75.21 ± 5.91 s), and the segmentation accuracy was higher than that of the traditional algorithm (84.71 ± 3.91% vs. 70.04 ± 3.71%, P < 0.05). The weight of children in the observation group (100 ± 7 g) was higher than that in the control group (54 ± 5 g), and the ICU monitoring time (12.01 ± 2.65 days) and the hospital stay (17.82 ± 3.11 days) were shorter than those in the control group (13.42 ± 2.95 days, 19.13 ± 3.22 days, all P < 0.05). The level set segmentation algorithm can accurately segment the CT image, so that the disease location and its contour can be displayed more clearly. Moreover, the nasal placement of jejunal nutrition tube can effectively improve the intestinal function of children, maintain the steady-state environment of intestinal bacterial growth, and significantly improve the clinical treatment effect, which is worthy of clinical application and promotion.


Enteral Nutrition , Intestinal Obstruction , Algorithms , Artificial Intelligence , Child , Enteral Nutrition/methods , Humans , Infant, Newborn , Intestinal Obstruction/diagnostic imaging , Intestinal Obstruction/surgery , Tomography, X-Ray Computed
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