| 1. |
- Chen, Zhen, et al.
(författare)
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Synthesis and preliminary evaluation of a novel positron emission tomography (PET) ligand for imaging fatty acid amide hydrolase (FAAH)
- 2020
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Ingår i: Bioorganic & Medicinal Chemistry Letters. - : Elsevier. - 0960-894X .- 1464-3405. ; 30:21
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Tidskriftsartikel (refereegranskat)abstract
- Fatty acid amide hydrolase (FAAH) exerts its main function in the catabolism of the endogenous chemical messenger anandamide (AEA), thus modulating the endocannabinoid (eCB) pathway. Inhibition of FAAH may serve as an effective strategy to relieve anxiety and possibly other central nervous system (CNS)-related disorders. Positron emission tomography (PET) would facilitate us to better understand the relationship between FAAH in certain disease conditions, and accelerate clinical translation of FAAH inhibitors by providing in vivo quantitative information. So far, most PET tracers show irreversible binding patterns with FAAH, which would result in complicated quantitative processes. Herein, we have identified a new FAAH inhibitor (1-((1-methyl-1H-indol-2-yl)methyl)piperidin-4-yl)(oxazol-2-yl)methanone (8) which inhibits the hydrolysis of AEA in the brain with high potency (IC50 value 11 nM at a substrate concentration of 0.5 µM), and without showing time-dependency. The PET tracer [11C]8 (also called [11C]FAAH-1906) was successfully radiolabeled with [11C]MeI in 17 ± 6% decay-corrected radiochemical yield (n = 7) with >74.0 GBq/μmol (2 Ci/μmol) molar activity and >99% radiochemical purity. Ex vivo biodistribution and blocking studies of [11C]8 in normal mice were also conducted, indicating good brain penetration, high brain target selectivity, and modest to excellent target selectivity in peripheral tissues. Thus, [11C]8 is a potentially useful PET ligand with enzyme inhibitory and target binding properties consistent with a reversible mode of action.
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| 2. |
- Chen, Weili, et al.
(författare)
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Detecting Ponzi Schemes on Ethereum : Towards Healthier Blockchain Technology
- 2018
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Ingår i: WWW '18. - New York, New York, USA : ACM Digital Library. - 9781450356398 ; , s. 1409-1418
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Konferensbidrag (refereegranskat)abstract
- Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with this issue, this paper proposes an approach to detect Ponzi schemes on blockchain by using data mining and machine learning methods. By verifying smart contracts on Ethereum, we first extract features from user accounts and operation codes of the smart contracts and then build a classification model to detect latent Ponzi schemes implemented as smart contracts. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum. Based on these results, we propose to build a uniform platform to evaluate and monitor every created smart contract for early warning of scams.
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| 3. |
- Fan, Zheyong, et al.
(författare)
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GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
- 2022
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Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 1089-7690 .- 0021-9606. ; 157:11
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Tidskriftsartikel (refereegranskat)abstract
- We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.
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| 4. |
- Liu, Shuai, et al.
(författare)
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Development of Pdn/g-C3N4 adsorbent for Hg0 removal – DFT study of influences of the support and Pd cluster size
- 2019
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Ingår i: Fuel. - : Elsevier BV. - 0016-2361. ; 254
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Tidskriftsartikel (refereegranskat)abstract
- Elemental mercury in the flue gas is highly hazardous to the ecosystem. However, its removal from gas phase is of challenges as it is highly volatile, chemically very stable and insoluble in water. It is therefore imperative to develop novel adsorbents that are efficient in the removal of elemental mercury from gas mixtures. In this study, density functional theory (DFT) was adopted to assist the development of novel adsorbents for mercury removal based on the in-depth understanding of the adsorption of Hg0 on g-C3N4, single Pd atoms and Pdn(n=2–4) clusters as well as the influences of the support and the size of Pd clusters on Hg0 adsorption. It is found that Hg0 atoms are physically adsorbed on the pristine g-C3N4 and are chemisorbed on the pure Pdn clusters and the Pdn/g-C3N4. The strongest adsorption happens on the Pd2 cluster and the Pd3/g-C3N4, while single Pd atoms doped on the g-C3N4 do not adsorb Hg0 atoms effectively. For a Pd4 cluster, there are at least four adsorption sites for the adsorption of Hg0, while these sites become more active in the presence of the support and the number of active sites for Hg0 adsorption on a Pd4 cluster doped on the g-C3N4 becomes seven due to the enhanced charge transfer from Hg atoms to the Pd cluster and the g-C3N4 surface. The most charge transfers are found to take place in the case of Pd2, Pd2/g-C3N4 and Pd3/g-C3N4, indicating the most intensive interactions between Hg0 and these configurations. Moreover, the shortened Pd-Hg bonds in the Pd3/g-C3N4 and the Pd4/g-C3N4 also shows the enhanced mercury adsorption, while opposite phenomena were observed in the other two structures, i.e., the Pd/g-C3N4 and the Pd2/g-C3N4.
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| 5. |
- Wang, Ruifu, et al.
(författare)
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Morphology and Flow Behavior of Cellulose Nanofibers Dispersed in Glycols
- 2019
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Ingår i: Macromolecules. - : American Chemical Society (ACS). - 0024-9297 .- 1520-5835. ; 52:15, s. 5499-5509
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the morphology and flow behavior of cellulose nanofibers (CNFs) dispersed in organic solvents can improve the process of fabricating new cellulose-based nanocomposites. In this study, jute-based 2,2,6,6-tetramethylpiperidinyl-1-oxyl (TEMPO)-oxidized CNFs with two different charge densities (0.64 and 1.03 mmol/g) were dispersed in ethylene glycol (EG) and propylene glycol (PG) using the solvent exchange method. The morphology and dimensions of CNFs in dry and suspension states were characterized using transmission electron microscopy, atomic force microscopy, and small-angle X-ray scattering techniques. The results showed that the cross-sectional dimensions remained the same in different solvents. Rheological measurements revealed that CNF suspensions in water or glycol (EG and PG) behaved similar to typical polymer solutions with a solvent-independent overlap concentration corresponding to the crowding factor of about 14. Furthermore, a thixotropic behavior was found in the concentrated CNF/glycol systems as observed in typical CNF aqueous suspensions. The fact that TEMPO-oxidized CNFs can be well dispersed in organic solvents opens up new possibilities to improve the CNF–polymer matrix blending, where the use of a viscous solvent can delay the transition to turbulence in processing and improve the control of fiber orientation because of a slower Brownian diffusive motion.
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