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Hua Zhang

Researcher at Chinese Academy of Sciences

Publications -  1778
Citations -  144014

Hua Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Graphene. The author has an hindex of 163, co-authored 1503 publications receiving 116769 citations. Previous affiliations of Hua Zhang include Shenzhen University & Zhengzhou University.

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Surface Modification of Smooth Poly(l-lactic acid) Films for Gelatin Immobilization

TL;DR: The experimental results show that the gelatin immobilized on aminosilane- and aldehyde-silane-modified PLLA improves the cellular affinity of HUVECs, whereas that immobilization on epoxy- silane- modified PllA does not show significant improvement on the cell proliferation.
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Antisite defects and Mg doping in LiFePO4: a first-principles investigation

TL;DR: In this paper, the authors investigated the properties of LiFePO4 with the antisite defect and Mg doping at Li and Fe sites using first-principles density functional theory with the on-site Coulomb interaction taken into account.
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The two classes of primordial follicles in the mouse ovary: their development, physiological functions, and implications for future research

TL;DR: This review summarizes early pioneering studies and focuses on recent progress that has shown that there are two distinct classes of primordial follicles in the ovary: the first wave of prim Primordial follicles that are activated immediately after they are formed and the adult primordial hair follicle populations that areactivated gradually in later life.
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Stage-specific germ-somatic cell interaction directs the primordial folliculogenesis in mouse fetal ovaries.

TL;DR: Using an in vitro follicle reconstitution culture model, the possibility of producing transgenetic follicles in vitro offers an alternative approach to produce transgenic oocytes/follicles, and thus animal models and uncovered a potentially important regulatory mechanism for normal oocyte differentiation and follicle formation.
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An integrated biosensor system with mobile health and wastewater-based epidemiology (iBMW) for COVID-19 pandemic.

TL;DR: The iBMW will provide an effective approach to prevent, evaluate and intervene in a fast, affordable and reliable way, thus enabling real-time guidance for the government in providing effective intervention and evaluating the effectiveness of intervention.