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Transparent ferroelectric crystals with ultrahigh piezoelectricity 期刊论文
NATURE, 2020, 577 (7790) : 350-+
作者:  Qiu, Chaorui;  Wang, Bo;  Zhang, Nan;  Zhang, Shujun;  Liu, Jinfeng;  Walker, David;  Wang, Yu;  Tian, Hao;  Shrout, Thomas R.;  Xu, Zhuo;  Chen, Long-Qing;  Li, Fei
收藏  |  浏览/下载:16/0  |  提交时间:2020/07/03

Transparent piezoelectrics are highly desirable for numerous hybrid ultrasound-optical devices ranging from photoacoustic imaging transducers to transparent actuators for haptic applications(1-7). However, it is challenging to achieve high piezoelectricity and perfect transparency simultaneously because most high-performance piezoelectrics are ferroelectrics that contain high-density light-scattering domain walls. Here, through a combination of phase-field simulations and experiments, we demonstrate a relatively simple method of using an alternating-current electric field to engineer the domain structures of originally opaque rhombohedral Pb(Mg1/3Nb2/3)O-3-PbTiO3 (PMN-PT) crystals to simultaneously generate near-perfect transparency, an ultrahigh piezoelectric coefficient d(33) (greater than 2,100 picocoulombs per newton), an excellent electromechanical coupling factor k(33) (about 94 per cent) and a large electro-optical coefficient gamma(33) (approximately 220 picometres per volt), which is far beyond the performance of the commonly used transparent ferroelectric crystal LiNbO3. We find that increasing the domain size leads to a higher d(33) value for the [001]-oriented rhombohedral PMN-PT crystals, challenging the conventional wisdom that decreasing the domain size always results in higher piezoelectricity(8-10). This work presents a paradigm for achieving high transparency and piezoelectricity by ferroelectric domain engineering, and we expect the transparent ferroelectric crystals reported here to provide a route to a wide range of hybrid device applications, such as medical imaging, self-energy-harvesting touch screens and invisible robotic devices.


  
Structure and mechanism of human diacylglycerol O-acyltransferase 1 期刊论文
NATURE, 2020, 581 (7808) : 329-+
作者:  Wu, Fan;  Zhao, Su;  Yu, Bin;  Chen, Yan-Mei;  Wang, Wen;  Song, Zhi-Gang;  Hu, Yi;  Tao, Zhao-Wu;  Tian, Jun-Hua;  Pei, Yuan-Yuan;  Yuan, Ming-Li;  Zhang, Yu-Ling;  Dai, Fa-Hui;  Liu, Yi;  Wang, Qi-Min;  Zheng, Jiao-Jiao;  Xu, Lin;  Holmes, Edward C.;  Zhang, Yong-Zhen
收藏  |  浏览/下载:24/0  |  提交时间:2020/07/03

The structure of human diacylglycerol O-acyltransferase 1, a membrane protein that synthesizes triacylglycerides, is solved with cryo-electron microscopy, providing insight into its function and mechanism of enzymatic activity.


Diacylglycerol O-acyltransferase 1 (DGAT1) synthesizes triacylglycerides and is required for dietary fat absorption and fat storage in humans(1). DGAT1 belongs to the membrane-bound O-acyltransferase (MBOAT) superfamily, members of which are found in all kingdoms of life and are involved in the acylation of lipids and proteins(2,3). How human DGAT1 and other mammalian members of the MBOAT family recognize their substrates and catalyse their reactions is unknown. The absence of three-dimensional structures also hampers rational targeting of DGAT1 for therapeutic purposes. Here we present the cryo-electron microscopy structure of human DGAT1 in complex with an oleoyl-CoA substrate. Each DGAT1 protomer has nine transmembrane helices, eight of which form a conserved structural fold that we name the MBOAT fold. The MBOAT fold in DGAT1 forms a hollow chamber in the membrane that encloses highly conserved catalytic residues. The chamber has separate entrances for each of the two substrates, fatty acyl-CoA and diacylglycerol. DGAT1 can exist as either a homodimer or a homotetramer and the two forms have similar enzymatic activity. The N terminus of DGAT1 interacts with the neighbouring protomer and these interactions are required for enzymatic activity.


  
The online competition between pro- and anti-vaccination views 期刊论文
NATURE, 2020, 582 (7811) : 230-+
作者:  Wu, Fan;  Zhao, Su;  Yu, Bin;  Chen, Yan-Mei;  Wang, Wen;  Song, Zhi-Gang;  Hu, Yi;  Tao, Zhao-Wu;  Tian, Jun-Hua;  Pei, Yuan-Yuan;  Yuan, Ming-Li;  Zhang, Yu-Ling;  Dai, Fa-Hui;  Liu, Yi;  Wang, Qi-Min;  Zheng, Jiao-Jiao;  Xu, Lin;  Holmes, Edward C.;  Zhang, Yong-Zhen
收藏  |  浏览/下载:10/0  |  提交时间:2020/07/03

Insights into the interactions between pro- and anti-vaccination clusters on Facebook can enable policies and approaches that attempt to interrupt the shift to anti-vaccination views and persuade undecided individuals to adopt a pro-vaccination stance.


Distrust in scientific expertise(1-14) is dangerous. Opposition to vaccination with a future vaccine against SARS-CoV-2, the causal agent of COVID-19, for example, could amplify outbreaks(2-4), as happened for measles in 2019(5,6). Homemade remedies(7,8) and falsehoods are being shared widely on the Internet, as well as dismissals of expert advice(9-11). There is a lack of understanding about how this distrust evolves at the system level(13,14). Here we provide a map of the contention surrounding vaccines that has emerged from the global pool of around three billion Facebook users. Its core reveals a multi-sided landscape of unprecedented intricacy that involves nearly 100 million individuals partitioned into highly dynamic, interconnected clusters across cities, countries, continents and languages. Although smaller in overall size, anti-vaccination clusters manage to become highly entangled with undecided clusters in the main online network, whereas pro-vaccination clusters are more peripheral. Our theoretical framework reproduces the recent explosive growth in anti-vaccination views, and predicts that these views will dominate in a decade. Insights provided by this framework can inform new policies and approaches to interrupt this shift to negative views. Our results challenge the conventional thinking about undecided individuals in issues of contention surrounding health, shed light on other issues of contention such as climate change(11), and highlight the key role of network cluster dynamics in multi-species ecologies(15).


  
PIK3CA variants selectively initiate brain hyperactivity during gliomagenesis 期刊论文
NATURE, 2020, 578 (7793) : 166-+
作者:  Qiu, Chaorui;  Wang, Bo;  Zhang, Nan;  Zhang, Shujun;  Liu, Jinfeng;  Walker, David;  Wang, Yu;  Tian, Hao;  Shrout, Thomas R.;  Xu, Zhuo;  Chen, Long-Qing;  Li, Fei
收藏  |  浏览/下载:7/0  |  提交时间:2020/07/03

Glioblastoma is a universally lethal form of brain cancer that exhibits an array of pathophysiological phenotypes, many of which are mediated by interactions with the neuronal microenvironment(1,2). Recent studies have shown that increases in neuronal activity have an important role in the proliferation and progression of glioblastoma(3,4). Whether there is reciprocal crosstalk between glioblastoma and neurons remains poorly defined, as the mechanisms that underlie how these tumours remodel the neuronal milieu towards increased activity are unknown. Here, using a native mouse model of glioblastoma, we develop a high-throughput in vivo screening platform and discover several driver variants of PIK3CA. We show that tumours driven by these variants have divergent molecular properties that manifest in selective initiation of brain hyperexcitability and remodelling of the synaptic constituency. Furthermore, secreted members of the glypican (GPC) family are selectively expressed in these tumours, and GPC3 drives gliomagenesis and hyperexcitability. Together, our studies illustrate the importance of functionally interrogating diverse tumour phenotypes driven by individual, yet related, variants and reveal how glioblastoma alters the neuronal microenvironment.


Glioblastoma tumours expressing oncogenic PIK3CA variants secrete the glycan GPC3, which promotes the formation of neural synapses, brain synaptic hyperexcitability and gliomagenesis.


  
H2A.Z facilitates licensing and activation of early replication origins (vol 35, pg 784, 2019) 期刊论文
NATURE, 2020, 578 (7793) : E8-E8
作者:  Cui, Jizhai;  Huang, Tian-Yun;  Luo, Zhaochu;  Testa, Paolo;  Gu, Hongri;  Chen, Xiang-Zhong;  Nelson, Bradley J.;  Heyderman, Laura J.
收藏  |  浏览/下载:12/0  |  提交时间:2020/07/03
Improved protein structure prediction using potentials from deep learning 期刊论文
NATURE, 2020, 577 (7792) : 706-+
作者:  Ma, Runze;  Cao, Duanyun;  Zhu, Chongqin;  Tian, Ye;  Peng, Jinbo;  Guo, Jing;  Chen, Ji;  Li, Xin-Zheng;  Francisco, Joseph S.;  Zeng, Xiao Cheng;  Xu, Li-Mei;  Wang, En-Ge;  Jiang, Ying
收藏  |  浏览/下载:142/0  |  提交时间:2020/07/03

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence(1). This problem is of fundamental importance as the structure of a protein largely determines its function(2)  however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures(3). Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force(4) that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction(5) (CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores(6) of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined(7).


  
The evolutionary history of vertebrate RNA viruses 期刊论文
NATURE, 2018, 556 (7700) : 197-+
作者:  Shi, Mang;  Lin, Xian-Dan;  Chen, Xiao;  Tian, Jun-Hua;  Chen, Liang-Jun;  Li, Kun;  Wang, Wen;  Eden, John-Sebastian;  Shen, Jin-Jin;  Liu, Li;  Holmes, Edward C.;  Zhang, Yong-Zhen
收藏  |  浏览/下载:13/0  |  提交时间:2019/11/27
Ground-to-satellite quantum teleportation 期刊论文
NATURE, 2017, 549 (7670) : 70-+
作者:  Ren, Ji-Gang;  Xu, Ping;  Yong, Hai-Lin;  Zhang, Liang;  Liao, Sheng-Kai;  Yin, Juan;  Liu, Wei-Yue;  Cai, Wen-Qi;  Yang, Meng;  Li, Li;  Yang, Kui-Xing;  Han, Xuan;  Yao, Yong-Qiang;  Li, Ji;  Wu, Hai-Yan;  Wan, Song;  Liu, Lei;  Liu, Ding-Quan;  Kuang, Yao-Wu;  He, Zhi-Ping;  Shang, Peng;  Guo, Cheng;  Zheng, Ru-Hua;  Tian, Kai;  Zhu, Zhen-Cai;  Liu, Nai-Le;  Lu, Chao-Yang;  Shu, Rong;  Chen, Yu-Ao;  Peng, Cheng-Zhi;  Wang, Jian-Yu;  Pan, Jian-Wei
收藏  |  浏览/下载:13/0  |  提交时间:2019/11/27