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Hair-bearing human skin generated entirely from pluripotent stem cells 期刊论文
NATURE, 2020
作者:  von Appen, Alexander;  LaJoie, Dollie;  Johnson, Isabel E.;  Trnka, Michael J.;  Pick, Sarah M.;  Burlingame, Alma L.;  Ullman, Katharine S.;  Frost, Adam
收藏  |  浏览/下载:80/0  |  提交时间:2020/07/03

Skin organoids generated in vitro from human pluripotent stem cells form complex, multilayered skin tissue with hair follicles, sebaceous glands and neural circuitry, and integrate with endogenous skin when grafted onto immunocompromised mice.


The skin is a multilayered organ, equipped with appendages (that is, follicles and glands), that is critical for regulating body temperature and the retention of bodily fluids, guarding against external stresses and mediating the sensation of touch and pain(1,2). Reconstructing appendage-bearing skin in cultures and in bioengineered grafts is a biomedical challenge that has yet to be met(3-9). Here we report an organoid culture system that generates complex skin from human pluripotent stem cells. We use stepwise modulation of the transforming growth factor beta (TGF beta) and fibroblast growth factor (FGF) signalling pathways to co-induce cranial epithelial cells and neural crest cells within a spherical cell aggregate. During an incubation period of 4-5 months, we observe the emergence of a cyst-like skin organoid composed of stratified epidermis, fat-rich dermis and pigmented hair follicles that are equipped with sebaceous glands. A network of sensory neurons and Schwann cells form nerve-like bundles that target Merkel cells in organoid hair follicles, mimicking the neural circuitry associated with human touch. Single-cell RNA sequencing and direct comparison to fetal specimens suggest that the skin organoids are equivalent to the facial skin of human fetuses in the second trimester of development. Moreover, we show that skin organoids form planar hair-bearing skin when grafted onto nude mice. Together, our results demonstrate that nearly complete skin can self-assemble in vitro and be used to reconstitute skin in vivo. We anticipate that our skin organoids will provide a foundation for future studies of human skin development, disease modelling and reconstructive surgery.


  
Recurrent interactions in local cortical circuits 期刊论文
NATURE, 2020, 579 (7798) : 256-+
作者:  Liu, Yang;  Nguyen, Phong T.;  Wang, Xun;  Zhao, Yuting;  Meacham, Corbin E.;  Zou, Zhongju;  Bordieanu, Bogdan;  Johanns, Manuel;  Vertommen, Didier;  Wijshake, Tobias;  May, Herman;  Xiao, Guanghua;  Shoji-Kawata, Sanae;  Rider, Mark H.
收藏  |  浏览/下载:18/0  |  提交时间:2020/07/03

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations(1-4). Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average(5,6). Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes(5-7), and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually(8). Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity(7) and photoablating(9,10) neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.


Computational modelling, imaging and single-cell ablation in layer 2/3 of the mouse vibrissal somatosensory cortex reveals that recurrent activity in cortical neurons can drive input-specific amplification during behaviour.


  
Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data 期刊论文
ECOLOGY LETTERS, 2020, 23 (4) : 607-619
作者:  Adams, Matthew P.;  Sisson, Scott A.;  Helmstedt, Kate J.;  Baker, Christopher M.;  Holden, Matthew H.;  Plein, Michaela;  Holloway, Jacinta;  Mengersen, Kerrie L.;  McDonald-Madden, Eve
收藏  |  浏览/下载:22/0  |  提交时间:2020/07/02
Conservation  decision science  ecological forecasting  ecological modelling  food webs  interaction network  population dynamics  predator-prey interactions  prediction  uncertainty propagation  
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:159/0  |  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).


  
Alarm communication networks as a driver of community structure in African savannah herbivores 期刊论文
ECOLOGY LETTERS, 2020, 23 (2) : 293-304
作者:  Meise, Kristine;  Franks, Daniel W.;  Bro-Jorgensen, Jakob
收藏  |  浏览/下载:16/0  |  提交时间:2020/07/02
Agent-based modelling  antipredator strategies  interspecific information transfer  mixed-species groups  resource competition  social affinity  social information use  social network analysis  spatial ecology  ungulates  
Alarm communication networks as a driver of community structure in African savannah herbivores 期刊论文
ECOLOGY LETTERS, 2020, 23 (2) : 293-304
作者:  Meise, Kristine;  Franks, Daniel W.;  Bro-Jorgensen, Jakob
收藏  |  浏览/下载:18/0  |  提交时间:2020/02/17
Agent-based modelling  antipredator strategies  interspecific information transfer  mixed-species groups  resource competition  social affinity  social information use  social network analysis  spatial ecology  ungulates  
Historic Flood Reconstruction With the Use of an Artificial Neural Network 期刊论文
WATER RESOURCES RESEARCH, 2019
作者:  Bomers, A.;  van der Meulen, B.;  Schielen, R. M. J.;  Hulscher, S. J. M. H.
收藏  |  浏览/下载:11/0  |  提交时间:2020/02/16
Flood reconstruction  Artificial Neural Network  Confidence interval  Surogatte modelling  
Is there a future for the gas network in a low carbon energy system? 期刊论文
ENERGY POLICY, 2019, 126: 480-493
作者:  Hickey, Conor;  Deane, Paul;  McInerney, Celine;  Gallachoir, Brian O.
收藏  |  浏览/下载:14/0  |  提交时间:2019/04/09
Gas network  TIMES  Decarbonisation  Stranded assets  Energy systems modelling  Investment  
Sustainable planning of the energy-water-food nexus using decision making tools 期刊论文
ENERGY POLICY, 2018, 113: 584-607
作者:  Bieber, Niclas;  Ker, Jen Ho;  Wang, Xiaonan;  Triantafyllidis, Charalampos;  van Dam, Koen H.;  Koppelaar, Rembrandt H. E. M.;  Shah, Nilay
收藏  |  浏览/下载:17/0  |  提交时间:2019/04/09
Integrated modelling  Energy-water-food nexus  Demand and supply  Energy deployment policies  Resource technology network optimization  Climate change  
Complex resource supply chains display higher resilience to simulated climate shocks 期刊论文
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS, 2017, 46
作者:  Lim-Camacho, Lilly;  Plaganyi, Eva E.;  Crimp, Steven;  Hodgkinson, Jane H.;  Hobday, Alistair J.;  Howden, Stuart Mark;  Loechel, Barton
收藏  |  浏览/下载:20/0  |  提交时间:2019/04/09
Supply chain  Climate change  Climate adaptation  Resilience  Disruption  Network modelling