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1.
BMC Med Inform Decis Mak ; 21(Suppl 9): 304, 2021 11 16.
Article in English | MEDLINE | ID: mdl-34789254

ABSTRACT

BACKGROUND: The historical data of rare disease is very scarce in reality, so how to perform drug repositioning for the rare disease is a great challenge. Most existing methods of drug repositioning for the rare disease usually neglect father-son information, so it is extremely difficult to predict drugs for the rare disease. METHOD: In this paper, we focus on father-son information mining for the rare disease. We propose GRU-Cooperation-Attention-Network (GCAN) to predict drugs for the rare disease. We construct two heterogeneous networks for information enhancement, one network contains the father-nodes of the rare disease and the other network contains the son-nodes information. To bridge two heterogeneous networks, we set a mapping to connect them. What's more, we use the biased random walk mechanism to collect the information smoothly from two heterogeneous networks, and employ a cooperation attention mechanism to enhance repositioning ability of the network. RESULT: Comparing with traditional methods, GCAN makes full use of father-son information. The experimental results on real drug data from hospitals show that GCAN outperforms state-of-the-art machine learning methods for drug repositioning. CONCLUSION: The performance of GCAN for drug repositioning is mainly limited by the insufficient scale and poor quality of the data. In future research work, we will focus on how to utilize more data such as drug molecule information and protein molecule information for the drug repositioning of the rare disease.


Subject(s)
Drug Repositioning , Rare Diseases , Algorithms , Computational Biology , Humans , Proteins , Rare Diseases/drug therapy
2.
Nanotechnology ; 31(20): 205707, 2020 May 15.
Article in English | MEDLINE | ID: mdl-32000158

ABSTRACT

Cadmium telluride (CdTe) nanocrystals with thiol stabilizers have been applied widely in the fields of energy storage and transformation. The aim of this work is to develop anhydrous proton exchange membranes (PEMs) by introducing CdTe nanocrystals bearing thioglycolic acid (tga) or mercaptopropionic acid (mpa) stabilizers into sulfonated poly(ether ether ketone) (SPEEK) and polyurethane (PU) systems. In the prepared SPEEK/PU/CdTe membranes, CdTe nanocrystals could provide desirable properties such as improving mechanical strength and enhancing proton conductivity by combining with phosphoric acid (PA) molecules. Successful preparation of SPEEK/PU/CdTe/PA membranes was demonstrated by the identification of high and stable proton conductivity and satisfactory thermal/chemical stability and mechanical properties. The fine appearance of membranes revealed uniform dispersion of components. Measurements of properties showed that the SPEEK(74%)/PU/CdTe-mpa(20/60/20)/100%PA membrane as a candidate anhydrous PEM is promising for use in high-temperature proton exchange membrane fuel cells. Specifically, the recommended membrane showed a proton conductivity of 1.18 × 10-1 S cm-1 at 160 °C and 3.96 × 10-2 S cm-1 at 100 °C, lasting for 600 h, and a tensile stress of 14.6 MPa at room temperature. Mixing inorganic CdTe nanocrystals with polymers to form inorganic/organic composite membranes is effective for producing anhydrous PEMs with cheaper polymers without functional groups to conduct protons.

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