Zhen Ling Wang
Heilongjiang University of Science and Technology
4 Papers
Zhen Ling Wang is an academic researcher from Heilongjiang University of Science and Technology. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 1, co-authored 1 publications.
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Papers
Piezoelectric ultrasound energy–harvesting device for deep brain stimulation and analgesia applications
Tao Zhang,Huagen Liang,Zhen Ling Wang,Chaorui Qiu,Yuan Bo Peng,Xinyu Zhu,Jiapu Li,Xu Ge,Jianbo Xu,Xian Huang,Junwei Tong,Jun Ou-Yang,Xiaofei Yang,Fei Li,Benpeng Zhu +14 more
TL;DR: A novel implantable piezoelectric ultrasound energy–harvesting device based on Sm-doped Pb(Mg1/3Nb2/3)O3-PbTiO3 (Sm-PMN-PT) single crystal that can reach up to 1.1 W/cm2 in vitro, which is 18 times higher than the previous record and provides new insights into the development of implantable devices in the future.
101
An in vitro human mammary epithelial cell permeability assay to assess drug secretion into breast milk
Tao Zhang,Zachary Applebee,Peng Zou,Zhen Ling Wang,Erika Diaz,Yanyan Li +5 more
- 22 Jun 2022
TL;DR: In this paper , the authors developed a human mammary epithelial cell (MEC)-based permeability assay to assess drug permeability across the mammary ephelium, which may have a potential to be developed as a useful in vitro technique for determining the transfer of small-molecule therapeutic drugs into breast milk.
7
Research on High Pressure Solidification Microstructure and the Microhardness of Al-Mg-Zn Alloy
TL;DR: In this article, the microhardness of Al-Mg-Zn alloy under high pressure was investigated by optical microscope, scanning electron microscope (SEM), X-ray diffraction(XRD) and micro-hardness tester.
3
Ribonucleotide reductase M2 subunit silencing suppresses tumorigenesis in pancreatic cancer via inactivation of PI3K/AKT/mTOR pathway.
Jinlan Shan,Zhen Ling Wang,Qiuping Mo,Jing Long,Yangfan Fan,Lu Cheng,Tao Zhang,Xiyong Liu,Xiaochen Wang +8 more
TL;DR: Wang et al. as mentioned in this paper analyzed RRM2 expression of 178 pancreatic cancer patients in Gene Expression Profiling Interactive Analysis (GEPIA) database and found that high RRM 2 expression predicted worse survival.