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| 1 | Expression of miR-15/107 Family MicroRNAs in Human Tissues and Cultured Rat Brain Cells显示文摘The miR-15/107 family comprises a group of 10 paralogous microRNAs(miRNAs),sharing a 50AGCAGC sequence.These miRNAs have overlapping targets.In order to characterize the expression of miR-15/107 family miRNAs,we employed customized TaqMan Low-Density micro-fluid PCR-array to investigate the expression of miR-15/107 family members,and other selected miRNAs,in 11 human tissues obtained at autopsy including the cerebral cortex,frontal cortex,primary visual cortex,thalamus,heart,lung,liver,kidney,spleen,stomach and skeletal muscle.miR-103,miR-195 and miR-497 were expressed at similar levels across various tissues,whereas miR-107 is enriched in brain samples.We also examined the expression patterns of evolutionarily conserved miR-15/107 miRNAs in three distinct primary rat brain cell preparations(enriched for cortical neurons,astrocytes and microglia,respectively).In primary cultures of rat brain cells,several members of the miR-15/107 family are enriched in neurons compared to other cell types in the central nervous system(CNS).In addition to mature miRNAs,we also examined the expression of precursors(pri-miRNAs).Our data suggested a generally poor correlation between the expression of mature miRNAs and their precursors.In summary,we provide a detailed study of the tissue and cell type-specific expression profile of this highly expressed and phylogenetically conserved family of miRNA genes. | Wang-Xia Wang Robert J.Danaher Craig S.Miller Joseph R.Berger Vega G.Nubia Bernard S.Wilfred Janna H.Neltner Christopher M.Norris Peter T.Nelson | 2014 | Genomics, Proteomics & Bioinformatics2014，12，1： | 9 |
| 2 | 资源型城市财源建设的风险识别与制度优化路径--以陕西省延安市为例显示文摘1994年财税体制改革促成了此后延续至今的改革红利,但其财政分权的改革远未到位,近年来能源富集区经济发展中遇到的地方税收体系建设滞后、地方政府财政困难、提供基本公共服务能力弱等问题均与此密切相关。今后所实施新一轮改革中,财税体制改革是全面深化经济体制改革的核心之一,应重点解决资源富集区矿产资源开发收益没有得到合理分配对地方政府财源建设所带来的风险。本文以陕西省延安市为例,认真分析财源结构、三次产业税收收入、税收收入与非税收收入的状况,以及省市分税的影响,深入研究现行财政分权影响地方财源建设的四大风险:税收与税源分离的风险、三次产业税源结构调整的风险、财政收支缺口的风险和税制改革滞后所引发的潜在风险,并深入剖析问题根源,积极探索优化资源型城市财源建设的制度路径。 | 宋敏 刘学敏 Hal T.Nelson | 2016 | 中国软科学2016，，10： | 7 |
| 3 | Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data显示文摘Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy,with the applications ranging from feature extraction to information compression and elucidation of relevant order parameters to inversion of imaging data to reconstruct structural models.However,the fundamental limitation of machine learning methods is their correlative nature,leading to extreme susceptibility to confounding factors.Here,we implement the workflow for causal analysis of structural scanning transmission electron microscopy(STEM)data and explore the interplay between physical and chemical effects in a ferroelectric perovskite across the ferroelectric–antiferroelectric phase transitions. | Maxim Ziatdinov Christopher T.Nelson Xiaohang Zhang Rama K.Vasudevan Eugene Eliseev Anna N.Morozovska Ichiro Takeuchi Sergei V.Kalinin | 2020 | npj Computational Materials2020，，1： | 2 |
| 4 | ISUOG consensus statement: what constitutes a fetal echocardiogram?显示文摘 | W.Lee L.Allan J. S.Carvalho R.Chaoui J.Copel G.Devore K.Hecher H.Munoz T.Nelson D.Paladini S.Yagel | 2008 | Ultrasound Obstet Gynecol2008，，2： | 1 |
| 5 | A simple, practical methodology for routine VSMOW/SLAP normalization of water samples analyzed by continuous flow methods显示文摘 | Stephen T.Nelson TylerCoplen | 2000 | Rapid Commun Mass Spectrom2000，，12： | 1 |
| 6 | Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding显示文摘Over the last decade,scanning transmission electron microscopy(STEM)has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision,opening the pathway toward exploring ferroelectric,ferroelastic,and chemical phenomena on the atomic scale.Analyses to date extracting a polarization signal from lattice coupled distortions in STEM imaging rely on discovery of atomic positions from intensity maxima/minima and subsequent calculation of polarization and other order parameter fields from the atomic displacements.Here,we explore the feasibility of polarization mapping directly from the analysis of STEM images using deep convolutional neural networks(DCNNs).In this approach,the DCNN is trained on the labeled part of the image(i.e.,for human labelling),and the trained network is subsequently applied to other images.We explore the effects of the choice of the descriptors(centered on atomic columns and grid-based),the effects of observational bias,and whether the network trained on one composition can be applied to a different one.This analysis demonstrates the tremendous potential of the DCNN for the analysis of high-resolution STEM imaging and spectral data and highlights the associated limitations. | Christopher T.Nelson Ayana Ghosh Mark Oxley Xiaohang Zhang Maxim Ziatdinov Ichiro Takeuchi Sergei V.Kalinin | 2021 | npj Computational Materials2021，，1： | 1 |
| 7 | Hydrophobic bile salts inhibit gallbladder smooth muscle function via stimulation of GPBAR1 receptors and activation of KATP channels显示文摘 | BrigitteLavoie Onesmo B.Balemba CodyGodfrey Conall A.Watson GalyaVassileva Carlos U.Corvera Mark T.Nelson Gary M.Mawe | 2010 | The Journal of Physiology2010，，17： | 1 |
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