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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 of M-pro from SARS-CoV-2 and discovery of its inhibitors 期刊论文
NATURE, 2020, 582 (7811) : 289-+
作者:  Li, Nan;  Jasanoff, Alan
收藏  |  浏览/下载:10/0  |  提交时间:2020/07/03

A programme of structure-assisted drug design and high-throughput screening identifies six compounds that inhibit the main protease of SARS-CoV-2, demonstrating the ability of this strategy to isolate drug leads with clinical potential.


A new coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the aetiological agent responsible for the 2019-2020 viral pneumonia outbreak of coronavirus disease 2019 (COVID-19)(1-4). Currently, there are no targeted therapeutic agents for the treatment of this disease, and effective treatment options remain very limited. Here we describe the results of a programme that aimed to rapidly discover lead compounds for clinical use, by combining structure-assisted drug design, virtual drug screening and high-throughput screening. This programme focused on identifying drug leads that target main protease (M-pro) of SARS-CoV-2: M-pro is a key enzyme of coronaviruses and has a pivotal role in mediating viral replication and transcription, making it an attractive drug target for SARS-CoV-2(5,6). We identified a mechanism-based inhibitor (N3) by computer-aided drug design, and then determined the crystal structure of M-pro of SARS-CoV-2 in complex with this compound. Through a combination of structure-based virtual and high-throughput screening, we assayed more than 10,000 compounds-including approved drugs, drug candidates in clinical trials and other pharmacologically active compounds-as inhibitors of M-pro. Six of these compounds inhibited M-pro, showing half-maximal inhibitory concentration values that ranged from 0.67 to 21.4 mu M. One of these compounds (ebselen) also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of our screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases for which no specific drugs or vaccines are available.


  
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:8/0  |  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.


  
Intercellular interaction dictates cancer cell ferroptosis via NF2-YAP signalling (vol 572, pg 402, 2019) 期刊论文
NATURE, 2019, 572 (7770) : E20-E20
作者:  Wu, Jiao;  Minikes, Alexander M.;  Gao, Minghui;  Bian, Huijie;  Li, Yong;  Stockwell, Brent R.;  Chen, Zhi-Nan;  Jiang, Xuejun
收藏  |  浏览/下载:11/0  |  提交时间:2019/11/27