Jian Yang

Related publications (5)

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BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings. This resource describes a collection of neurons from a variety of light microscopy-based datasets, which can serve as a gold standard for testing automated tracing algorithms, as shown by comparison of the performance of 35 algorithms.

NATURE PORTFOLIO2023

Model of crop growth, water flow, and solute transport in layered soil

David Andrew Barry, Jian Yang

Agro-ecohydrological models are essential for managing scarce water resources and ensuring crop productivity. Here, a one-dimensional agro-ecohydrological model, LAWSTAC, capable of simulating water and solute transport in layered soil coupled with crop growth, is presented and validated. LAWSTAC considers eight hydraulic conductivity discretization methods to address the nonlinearity of Richards equation for soil water flow. LAWSTAC includes two root water uptake models and a flexible root distribution model for reliable transpiration simulation. Simulation of infiltration in layered soil demonstrated that the methods of arithmetic mean, geometric mean and triadic mean performed well among the eight discretization methods. The model was further verified by comparison with results from two widely used models, HYDRUS-1D and SWAP, based on the measured data in a spring wheat field for 2007 and 2008 in the Northwest China. The models produced similar results for flow in layered soil, although SWAP showed some instability in the salinity dynamics. LAWSTAC models crop growth with a more efficient parameterization than SWAP. In conclusion, LAWSTAC is suitable for simulating soil water and salinity dynamics, crop growth and their interactions.

2019

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Hua Bai, Lionel Blanc, Chih-Peng Chang, Qi Chen, Si Chen, Min Chen, Peiwen Chen, Yin Chen, Wei Chen, Zhen Chen, Zheng Dong, Nicolas Dupont, Yuchen Feng, Yunfei Huang, Ying Jiang, Hong Jiang, Li Jin, Andreas Kern, Yonghyun Kim, Deepak Kumar, Ajay Kumar, Rakesh Kumar, Chi Li, Ke Li, Sheng Li, Wei Li, Rui Li, Jun Li, Bo Liu, Fei Liu, Liang Liu, Chong Liu, Yang Liu, Ke Liu, Wei Liu, Xu Liu, Andreas Mayer, Maurizio Molinari, Darren Moore, Sandra Moreno, Paolo Paganetti, Xin Qi, Ziwei Qu, Jun Ren, Giuseppe Russo, Shweta Sharma, Rajat Singh, Yang Sun, Yi Sun, Françoise Gisou van der Goot Grunberg, Ying Wang, Yu Wang, Xin Wang, Jian Wang, Bo Wang, Peng Wang, Xin Wen, Jian Wu, Tian Xia, Liang Xu, Jian Xu, Feng Xu, Zhen Yan, Yi Yang, Jian Yang, Ying Yang, Li Yu, Yan Zhang, Fan Zhang, Yang Zhang, Jian Zhang, Lin Zhang, Li Zhang, Hong Zhang, Hao Zhang, Qing Zhong

Taylor & Francis Inc2016

Defining the role of common variation in the genomic and biological architecture of adult human height

Murielle Bochud, Jian Yang

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated similar to 2,000, similar to 3,700 and similar to 9,500 SNPs explained similar to 21%, similar to 24% and similar to 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Nature Publishing Group2014

Carbon nanotubes as reinforcements and interface modifiers in metal matrix composites

Jian Yang

Multi-wall carbon nanotubes (MWCNTs), catalytically grown by chemical vapour deposition (CVD), have been successfully employed in the development of bulk composites, where aluminium alloys (Al-4%Cu-1%Mg-0.5%Ag, called WFA) or commercial pure magnesium have been used as matrix, while MWCNTs served as interface modifiers and/or reinforcing phase. Four different composites, WFA or Mg reinforced with 25% volume fraction of Al2O3 SAFFIL fibres coated or not with MWCNTs were processed by low pressure infiltration. Two other composites, made of pure Mg reinforced with 1% and 2% weight fraction of MWCNTs, were fabricated by powder metallurgy. Scanning Electron Microscope (SEM) revealed fine microstructures of the produced specimens: locally homogeneous distribution of carbon nanotubes (CNTs) in 1% and 2% of CNTs reinforced Mg composites, and overall uniform dispersion of SAFFIL fibres in WFA-25%SAFFIL-CNTs and Mg-25%SAFFIL-CNTs. However, CNTs are not visible in WFA-25%SAFFIL-CNTs and Mg-25%SAFFIL-CNTs in this scale. It could be assumed that together with SAFFIL fibres, they are embedded completely in the matrix. A substantial increase in Young's modulus has been attributed to the addition of CNTs as well as the effective interface bonding between CNTs and matrix. Elastic and anelastic properties of the specimens of the six composites have been investigated by mechanical spectroscopy. Mechanical loss and shear modulus were characterized as a function of temperature. The obtained experimental results have demonstrated positive impacts of MWCNTs on the elastic and anelastic properties of these composites, by comparing to the corresponding MWCNTs-free materials, respectively, and the advantages of using CNTs as reinforcements in metal matrix composites (MMCs). A significant increase in transient damping due to CNTs has been measured in WFA-25%SAFFIL-CNTs and Mg-25%SAFFIL-CNTs. It indicates that a SAFFIL-matrix interface softening has been achieved. This has been interpreted by theoretical modelling as due to an additional density of mobile dislocations nucleated by CNT tips in the interface between SAFFIL fibres and matrix. On the other hand, the CNTs far away from the SAFFIL-matrix interface are assumed to pin dislocation loops, leading to a decrease in their mobility. Dislocation motion controlled by solid friction has been identified as the relaxation mechanism of thermal stresses. Damping in Mg-2%CNTs remains approximately as high as in pure Mg. Mechanical loss spectrum obtained in both Mg-1%CNTs and Mg-2%CNTs is composed of a relaxation peak superposed on an exponential background. The activation enthalpy of the peak is of 0.83 eV and the limit relaxation time of 2.3 × 10-11s. The peak is explained by a dislocation dragging model. An enhancement in the shear modulus has been measured in WFA-CNTs, Mg- 25%SAFFIL-CNTs and Mg-2%CNTs due to the addition of CNTs. Hot Isostatic Pressing (HIP), which was used in processing Mg-2%CNTs, was found to be advantageous in obtaining a CNTs - Mg composite with better interface bonding.

EPFL2004

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NATURE PORTFOLIO2023

Carbon nanotubes as reinforcements and interface modifiers in metal matrix composites

Jian Yang

EPFL2004