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Le Li

North China Electric Power University

ORCID: 0000-0001-8630-1098

Publishes on Supercapacitor Materials and Fabrication, Conducting polymers and applications, Advanced Sensor and Energy Harvesting Materials. 130 papers and 5.5k citations.

130Publications
5.5kTotal Citations

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Top publicationsby citations

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder
Chao‐Gan Yan, Xiao Chen, Le Li et al.|Proceedings of the National Academy of Sciences|2019
Cited by 856Open Access

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Cryopolymerization enables anisotropic polyaniline hybrid hydrogels with superelasticity and highly deformation-tolerant electrochemical energy storage
Le Li, Yu Zhang, Hengyi Lu et al.|Nature Communications|2020
Cited by 349Open Access

Abstract The development of energy storage devices that can endure large and complex deformations is central to emerging wearable electronics. Hydrogels made from conducting polymers give rise to a promising integration of high conductivity and versatility in processing. However, the emergence of conducting polymer hydrogels with a desirable network structure cannot be readily achieved using conventional polymerization methods. Here we present a cryopolymerization strategy for preparing an intrinsically stretchable, compressible and bendable anisotropic polyvinyl alcohol/polyaniline hydrogel with a complete recovery of 100% stretching strain, 50% compressing strain and fully bending. Due to its high mechanical strength, superelastic properties and bi-continuous phase structure, the as-obtained anisotropic polyvinyl alcohol/polyaniline hydrogel can work as a stretching/compressing/bending electrode, maintaining its stable output under complex deformations for an all-solid-state supercapacitor. In particular, it achieves an extremely high energy density of 27.5 W h kg −1 , which is among that of state-of-the-art stretchable supercapacitors.

Disrupted intrinsic functional brain topology in patients with major depressive disorder
Hong Yang, Xiao Chen, Zuo-Bing Chen et al.|Molecular Psychiatry|2021
Cited by 242Open Access

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.