3,573 results on '"Mei Zhen"'
Search Results
2. Robotic microinjection enables large-scale transgenic studies of Caenorhabditis elegans
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Peng Pan, Michael Zoberman, Pengsong Zhang, Sharanja Premachandran, Sanjana Bhatnagar, Pallavi P. Pilaka-Akella, William Sun, Chengyin Li, Charlotte Martin, Pengfei Xu, Zefang Zhang, Ryan Li, Wesley Hung, Hua Tang, Kailynn MacGillivray, Bin Yu, Runze Zuo, Karinna Pe, Zhen Qin, Shaojia Wang, Ang Li, W. Brent Derry, Mei Zhen, Arneet L. Saltzman, John A. Calarco, and Xinyu Liu
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Science - Abstract
Abstract The nematode Caenorhabditis elegans is widely employed as a model organism to study basic biological mechanisms. However, transgenic C. elegans are generated by manual injection, which remains low-throughput and labor-intensive, limiting the scope of approaches benefitting from large-scale transgenesis. Here, we report a robotic microinjection system, integrating a microfluidic device capable of reliable worm immobilization, transfer, and rotation, for high-speed injection of C. elegans. The robotic system provides an injection speed 2-3 times faster than that of experts with 7–22 years of experience while maintaining comparable injection quality and only limited trials needed by users to become proficient. We further employ our system in a large-scale reverse genetic screen using multiplexed alternative splicing reporters, and find that the TDP-1 RNA-binding protein regulates alternative splicing of zoo-1 mRNA, which encodes variants of the zonula occludens tight junction proteins. With its high speed, high accuracy, and high efficiency in worm injection, this robotic system shows great potential for high-throughput transgenic studies of C. elegans.
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- 2024
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3. The epithelial Na+ channel UNC-8 promotes an endocytic mechanism that recycles presynaptic components to new boutons in remodeling neurons
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Andrea Cuentas-Condori, Siqi Chen, Mia Krout, Kristin L. Gallik, John Tipps, Casey Gailey, Leah Flautt, Hongkyun Kim, Ben Mulcahy, Mei Zhen, Janet E. Richmond, and David M. Miller, III
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CP: Neuroscience ,CP: Cell biology ,Biology (General) ,QH301-705.5 - Abstract
Summary: Circuit refinement involves the formation of new presynaptic boutons as others are dismantled. Nascent presynaptic sites can incorporate material from recently eliminated synapses, but the recycling mechanisms remain elusive. In early-stage C. elegans larvae, the presynaptic boutons of GABAergic DD neurons are removed and new outputs established at alternative sites. Here, we show that developmentally regulated expression of the epithelial Na+ channel (ENaC) UNC-8 in remodeling DD neurons promotes a Ca2+ and actin-dependent mechanism, involving activity-dependent bulk endocytosis (ADBE), that recycles presynaptic material for reassembly at nascent DD synapses. ADBE normally functions in highly active neurons to accelerate local recycling of synaptic vesicles. In contrast, we find that an ADBE-like mechanism results in the distal recycling of synaptic material from old to new synapses. Thus, our findings suggest that a native mechanism (ADBE) can be repurposed to dismantle presynaptic terminals for reassembly at new, distant locations.
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- 2023
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4. mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops
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Elisa C. Pavarino, Emma Yang, Nagaraju Dhanyasi, Mona D. Wang, Flavie Bidel, Xiaotang Lu, Fuming Yang, Core Francisco Park, Mukesh Bangalore Renuka, Brandon Drescher, Aravinthan D. T. Samuel, Binyamin Hochner, Paul S. Katz, Mei Zhen, Jeff W. Lichtman, and Yaron Meirovitch
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affordable connectomics ,volume electron microscopy ,semi-automatic neural circuit reconstruction ,segmentation ,deep learning ,VAST ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.
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- 2023
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5. Signal requirement for cortical potential of transplantable human neuroepithelial stem cells
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Balazs V. Varga, Maryam Faiz, Helena Pivonkova, Gabriel Khelifi, Huijuan Yang, Shangbang Gao, Emma Linderoth, Mei Zhen, Ragnhildur Thora Karadottir, Samer M. Hussein, and Andras Nagy
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Science - Abstract
The regulatory pathways that control the human neural progenitor cell pool are not well understood. Here, Varga et al. identify signals that control the division of human pluripotent stem cell derived neural stem cells and their ability to make cortical neurons and glia.
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- 2022
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6. Sneak Path Interference-Aware Adaptive Detection and Decoding for Resistive Memory Arrays
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Li, Panpan, Cai, Kui, Song, Guanghui, and Mei, Zhen
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Computer Science - Information Theory - Abstract
Resistive random-access memory (ReRAM) is an emerging non-volatile memory technology for high-density and high-speed data storage. However, the sneak path interference (SPI) occurred in the ReRAM crossbar array seriously affects its data recovery performance. In this letter, we first propose a quantized channel model of ReRAM, based on which we design both the one-bit and multi-bit channel quantizers by maximizing the mutual information of the channel. A key channel parameter that affects the quantizer design is the sneak path occurrence probability (SPOP) of the memory cell. We first use the average SPOP calculated statistically to design the quantizer, which leads to the same channel detector for different memory arrays. We then adopt the SPOP estimated separately for each memory array for the quantizer design, which is generated by an effective channel estimator and through an iterative detection and decoding scheme for the ReRAM channel. This results in an array-level SPI-aware adaptive detection and decoding approach. Moreover, since there is a strong correlation of the SPI that affects memory cells in the same rows/columns than that affecting cells in different rows/columns, we further derive a column-level scheme which outperforms the array-level scheme. We also propose a channel decomposition method that enables effective ways for theoretically analyzing the ReRAM channel. Simulation results show that the proposed SPI-aware adaptive detection and decoding schemes can approach the ideal performance with three quantization bits, with only one decoding iteration.
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- 2024
7. Deep Transfer Learning-based Detection for Flash Memory Channels
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Mei, Zhen, Cai, Kui, Shi, Long, Li, Jun, Chen, Li, and Immink, Kees A. Schouhamer
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Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
The NAND flash memory channel is corrupted by different types of noises, such as the data retention noise and the wear-out noise, which lead to unknown channel offset and make the flash memory channel non-stationary. In the literature, machine learning-based methods have been proposed for data detection for flash memory channels. However, these methods require a large number of training samples and labels to achieve a satisfactory performance, which is costly. Furthermore, with a large unknown channel offset, it may be impossible to obtain enough correct labels. In this paper, we reformulate the data detection for the flash memory channel as a transfer learning (TL) problem. We then propose a model-based deep TL (DTL) algorithm for flash memory channel detection. It can effectively reduce the training data size from $10^6$ samples to less than 104 samples. Moreover, we propose an unsupervised domain adaptation (UDA)-based DTL algorithm using moment alignment, which can detect data without any labels. Hence, it is suitable for scenarios where the decoding of error-correcting code fails and no labels can be obtained. Finally, a UDA-based threshold detector is proposed to eliminate the need for a neural network. Both the channel raw error rate analysis and simulation results demonstrate that the proposed DTL-based detection schemes can achieve near-optimal bit error rate (BER) performance with much less training data and/or without using any labels., Comment: This paper has been accepted for publication in IEEE Transactions on Communications
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- 2024
8. Deep Learning-Based Decoding of Linear Block Codes for Spin-Torque Transfer Magnetic Random Access Memory (STT-MRAM)
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Zhong, Xingwei, Cai, Kui, Mei, Zhen, and Quek, Tony Q. S.
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Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Thanks to its superior features of fast read/write speed and low power consumption, spin-torque transfer magnetic random access memory (STT-MRAM) has become a promising non-volatile memory (NVM) technology that is suitable for many applications. However, the reliability of STT-MRAM is seriously affected by the variation of the memory fabrication process and the working temperature, and the later will lead to an unknown offset of the channel. Hence, there is a pressing need to develop more effective error correction coding techniques to tackle these imperfections and improve the reliability of STT-MRAM. In this work, we propose, for the first time, the application of deep-learning (DL) based algorithms and techniques to improve the decoding performance of linear block codes with short codeword lengths for STT-MRAM. We formulate the belief propagation (BP) decoding of linear block code as a neural network (NN), and propose a novel neural normalized-offset reliability-based min-sum (NNORB-MS) decoding algorithm. We successfully apply our proposed decoding algorithm to the STT-MRAM channel through channel symmetrization to overcome the channel asymmetry. We also propose an NN-based soft information generation method (SIGM) to take into account the unknown offset of the channel. Simulation results demonstrate that our proposed NNORB-MS decoding algorithm can achieve significant performance gain over both the hard-decision decoding (HDD) and the regular reliability-based min-sum (RB-MS) decoding algorithm, for cases without and with the unknown channel offset. Moreover, the decoder structure and time complexity of the NNORB-MS algorithm remain similar to those of the regular RB-MS algorithm.
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- 2024
9. Quantization Design for Resistive Memories With Multiple Reads
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Mei, Zhen, Cai, Kui, Shi, Long, and Li, Jun
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Computer Science - Information Theory - Abstract
Due to the crossbar array architecture, the sneak-path problem severely degrades the data integrity in the resistive random access memory (ReRAM). In this letter, we investigate the channel quantizer design for ReRAM arrays with multiple reads, which is a typical technique to improve the data recovery performance of data storage systems. Starting with a quantized channel model of ReRAM with multiple reads, we first derive a general approach for designing the channel quantizer, for both single-bit and multiple-bit quantization. We then focus on the single-bit quantization, which is highly suitable for practical applications of ReRAM. In particular, we propose a semi-analytical approach to design the multiple-read single-bit quantizer with less complexity. We also derive the theoretical bit-error probability of the optimal single-bit detector/quantization as the benchmark. Results indicate that the multiple-read operation is effective in improving the error rate performance of ReRAM. Moreover, our proposed multiple-read detector outperforms the prior art detector and achieves the performance of the optimal detector.
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- 2024
10. Adversarial Federated Consensus Learning for Surface Defect Classification Under Data Heterogeneity in IIoT
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Cui, Jixuan, Li, Jun, Mei, Zhen, Ni, Yiyang, Chen, Wen, and Li, Zengxiang
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Signal Processing - Abstract
The challenge of data scarcity hinders the application of deep learning in industrial surface defect classification (SDC), as it's difficult to collect and centralize sufficient training data from various entities in Industrial Internet of Things (IIoT) due to privacy concerns. Federated learning (FL) provides a solution by enabling collaborative global model training across clients while maintaining privacy. However, performance may suffer due to data heterogeneity-discrepancies in data distributions among clients. In this paper, we propose a novel personalized FL (PFL) approach, named Adversarial Federated Consensus Learning (AFedCL), for the challenge of data heterogeneity across different clients in SDC. First, we develop a dynamic consensus construction strategy to mitigate the performance degradation caused by data heterogeneity. Through adversarial training, local models from different clients utilize the global model as a bridge to achieve distribution alignment, alleviating the problem of global knowledge forgetting. Complementing this strategy, we propose a consensus-aware aggregation mechanism. It assigns aggregation weights to different clients based on their efficacy in global knowledge learning, thereby enhancing the global model's generalization capabilities. Finally, we design an adaptive feature fusion module to further enhance global knowledge utilization efficiency. Personalized fusion weights are gradually adjusted for each client to optimally balance global and local features. Compared with state-of-the-art FL methods like FedALA, the proposed AFedCL method achieves an accuracy increase of up to 5.67% on three SDC datasets.
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- 2024
11. Open syntaxin overcomes exocytosis defects of diverse mutants in C. elegans
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Chi-Wei Tien, Bin Yu, Mengjia Huang, Karolina P. Stepien, Kyoko Sugita, Xiaoyu Xie, Liping Han, Philippe P. Monnier, Mei Zhen, Josep Rizo, Shangbang Gao, and Shuzo Sugita
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Science - Abstract
Opening of the UNC-64/syntaxin closed conformation by UNC-13/Munc13 to form the neuronal SNARE complex is critical for neurotransmitter release. Here the authors show that facilitating the opening of syntaxin enhances exocytosis not only in unc-13 nulls as well as in diverse C. elegans mutants.
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- 2020
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12. Escape steering by cholecystokinin peptidergic signaling
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Lili Chen, Yuting Liu, Pan Su, Wesley Hung, Haiwen Li, Ya Wang, Zhongpu Yue, Ming-Hai Ge, Zheng-Xing Wu, Yan Zhang, Peng Fei, Li-Ming Chen, Louis Tao, Heng Mao, Mei Zhen, and Shangbang Gao
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escape ,neuromodulator ,cholecystokinin receptor ,NLP-18 ,CKR-1 ,neuropeptide ,Biology (General) ,QH301-705.5 - Abstract
Summary: Escape is an evolutionarily conserved and essential avoidance response. Considered to be innate, most studies on escape responses focused on hard-wired circuits. We report here that a neuropeptide NLP-18 and its cholecystokinin receptor CKR-1 enable the escape circuit to execute a full omega (Ω) turn. We demonstrate in vivo NLP-18 is mainly secreted by the gustatory sensory neuron (ASI) to activate CKR-1 in the head motor neuron (SMD) and the turn-initiating interneuron (AIB). Removal of NLP-18 or CKR-1 or specific knockdown of CKR-1 in SMD or AIB neurons leads to shallower turns, hence less robust escape steering. Consistently, elevation of head motor neuron (SMD)'s Ca2+ transients during escape steering is attenuated upon the removal of NLP-18 or CKR-1. In vitro, synthetic NLP-18 directly evokes CKR-1-dependent currents in oocytes and CKR-1-dependent Ca2+ transients in SMD. Thus, cholecystokinin peptidergic signaling modulates an escape circuit to generate robust escape steering.
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- 2022
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13. Structural Analysis of the Caenorhabditis elegans Dauer Larval Anterior Sensilla by Focused Ion Beam-Scanning Electron Microscopy
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Sebastian Britz, Sebastian Matthias Markert, Daniel Witvliet, Anna Maria Steyer, Sarah Tröger, Ben Mulcahy, Philip Kollmannsberger, Yannick Schwab, Mei Zhen, and Christian Stigloher
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FIB-SEM ,3D reconstruction ,neuroanatomy ,IL2 branching ,amphids ,Caenorhabditis elegans (C. elegans) ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 ,Human anatomy ,QM1-695 - Abstract
At the end of the first larval stage, the nematode Caenorhabditis elegans developing in harsh environmental conditions is able to choose an alternative developmental path called the dauer diapause. Dauer larvae exhibit different physiology and behaviors from non-dauer larvae. Using focused ion beam-scanning electron microscopy (FIB-SEM), we volumetrically reconstructed the anterior sensory apparatus of C. elegans dauer larvae with unprecedented precision. We provide a detailed description of some neurons, focusing on structural details that were unknown or unresolved by previously published studies. They include the following: (1) dauer-specific branches of the IL2 sensory neurons project into the periphery of anterior sensilla and motor or putative sensory neurons at the sub-lateral cords; (2) ciliated endings of URX sensory neurons are supported by both ILso and AMso socket cells near the amphid openings; (3) variability in amphid sensory dendrites among dauers; and (4) somatic RIP interneurons maintain their projection into the pharyngeal nervous system. Our results support the notion that dauer larvae structurally expand their sensory system to facilitate searching for more favorable environments.
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- 2021
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14. Rogue waves excitation on zero-background in the (2+1)-dimensional KdV equation
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Zhang, Jie-Fang, Jin, Mei-zhen, and Zhang, Meng-yang
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Nonlinear Sciences - Pattern Formation and Solitons - Abstract
An analytical method for constructing various coherent localized solutions with short-lived characteristics is proposed based on a novel self-mapping transformation of the (2+1) dimensional KdV equation. The highlight of this method is that it allows one to generate a class of basic two--dimensional rogue waves excited on zero-background for this equation, which includes the line-soliton-induced rogue wave and dromion-induced rogue wave with exponentially decaying as well as the lump-induced rogue wave with algebraically decaying in the -plane. Our finding provides a proper candidate to describe two-dimensional rogue waves and paves a feasible path for studying rogue waves., Comment: 11 pages,3 figures
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- 2024
15. In-Bed Sensorimotor Rehabilitation in Early and Late Subacute Stroke Using a Wearable Elbow Robot: A Pilot Study
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Mei Zhen Huang, Yong-Soon Yoon, Jisu Yang, Chung-Yong Yang, and Li-Qun Zhang
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stroke rehabilitation ,robot ,recovery time course ,upper limbs ,subacute stroke ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Objects: To evaluate the feasibility and effectiveness of in-bed wearable elbow robot training for motor recovery in patients with early and late subacute stroke.Methods: Eleven in-patient stroke survivors (male/female: 7/4, age: 50.7 ± 10.6 years, post-stroke duration: 2.6 ± 1.9 months) received 15 sessions of training over about 4 weeks of hospital stay. During each hourly training, participants received passive stretching and active movement training with motivating games using a wearable elbow rehabilitation robot. Isometric maximum muscle strength (MVC) of elbow flexors and extensors was evaluated using the robot at the beginning and end of each training session. Clinical measures including Fugl-Meyer Assessment of upper extremity (FMA-UE), Motricity Index (MI) for upper extremities, Modified Ashworth Scale (MAS) were measured at baseline, after the 4-week training program, and at a 1-month follow-up. The muscle strength recovery curve over the training period was characterized as a logarithmic learning curve with three parameters (i.e., initial muscle strength, rate of improvement, and number of the training session).Results: At the baseline, participants had moderate to severe upper limb motor impairment {FMA-UE [median (interquartile range)]: 28 (18–45)} and mild spasticity in elbow flexors {MAS [median (interquartile range)]: 0 (0–1)}. After about 4 weeks of training, significant improvements were observed in FMA-UE (p = 0.003) and MI (p = 0.005), and the improvements were sustained at the follow-up. The elbow flexors MVC significantly increased by 1.93 Nm (95% CI: 0.93 to 2.93 Nm, p = 0.017) and the elbow extensor MVC increased by 0.68 Nm (95% CI: 0.05 to 1.98 Nm, p = 0.036). Muscle strength recovery curve showed that patients with severe upper limb motor impairment had a greater improvement rate in elbow flexor strength than those with moderate motor impairment.Conclusion: In-bed wearable elbow robotic rehabilitation is feasible and effective in improving biomechanical and clinical outcomes for early and late subacute stroke in-patients. Results from the pilot study suggested that patients with severe upper limb motor impairment may benefit more from the robot training compared to those with moderate impairment.
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- 2021
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16. Corollary discharge promotes a sustained motor state in a neural circuit for navigation
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Ni Ji, Vivek Venkatachalam, Hillary Denise Rodgers, Wesley Hung, Taizo Kawano, Christopher M Clark, Maria Lim, Mark J Alkema, Mei Zhen, and Aravinthan DT Samuel
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thermotaxis ,corollary discharge ,efferency copy ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Animals exhibit behavioral and neural responses that persist on longer timescales than transient or fluctuating stimulus inputs. Here, we report that Caenorhabditis elegans uses feedback from the motor circuit to a sensory processing interneuron to sustain its motor state during thermotactic navigation. By imaging circuit activity in behaving animals, we show that a principal postsynaptic partner of the AFD thermosensory neuron, the AIY interneuron, encodes both temperature and motor state information. By optogenetic and genetic manipulation of this circuit, we demonstrate that the motor state representation in AIY is a corollary discharge signal. RIM, an interneuron that is connected with premotor interneurons, is required for this corollary discharge. Ablation of RIM eliminates the motor representation in AIY, allows thermosensory representations to reach downstream premotor interneurons, and reduces the animal’s ability to sustain forward movements during thermotaxis. We propose that feedback from the motor circuit to the sensory processing circuit underlies a positive feedback mechanism to generate persistent neural activity and sustained behavioral patterns in a sensorimotor transformation.
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- 2021
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17. The Mechanical and Electrical Properties of the Smart Aggregate Based on the Mixed Cementitious Materials
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Wang, Haifeng, Yan, Handong, Xu, Yuye, Mei, Zhen, and Wang, Chen
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- 2024
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18. Overexpression of an ALS-associated FUS mutation in C. elegans disrupts NMJ morphology and leads to defective neuromuscular transmission
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Sebastian M. Markert, Michael Skoruppa, Bin Yu, Ben Mulcahy, Mei Zhen, Shangbang Gao, Michael Sendtner, and Christian Stigloher
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c. elegans ,fused in sarcoma ,amyotrophic lateral sclerosis ,super-resolution array tomography ,electron tomography ,neuromuscular junction ,Science ,Biology (General) ,QH301-705.5 - Abstract
The amyotrophic lateral sclerosis (ALS) neurodegenerative disorder has been associated with multiple genetic lesions, including mutations in the gene for fused in sarcoma (FUS), a nuclear-localized RNA/DNA-binding protein. Neuronal expression of the pathological form of FUS proteins in Caenorhabditis elegans results in mislocalization and aggregation of FUS in the cytoplasm, and leads to impairment of motility. However, the mechanisms by which the mutant FUS disrupts neuronal health and function remain unclear. Here we investigated the impact of ALS-associated FUS on motor neuron health using correlative light and electron microscopy, electron tomography, and electrophysiology. We show that ectopic expression of wild-type or ALS-associated human FUS impairs synaptic vesicle docking at neuromuscular junctions. ALS-associated FUS led to the emergence of a population of large, electron-dense, and filament-filled endosomes. Electrophysiological recording revealed reduced transmission from motor neurons to muscles. Together, these results suggest a pathological effect of ALS-causing FUS at synaptic structure and function organization. This article has an associated First Person interview with the first author of the paper.
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- 2020
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19. Optogenetic Manipulation of Postsynaptic cAMP Using a Novel Transgenic Mouse Line Enables Synaptic Plasticity and Enhances Depolarization Following Tetanic Stimulation in the Hippocampal Dentate Gyrus
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Thomas T. Luyben, Jayant Rai, Hang Li, John Georgiou, Ariel Avila, Mei Zhen, Graham L. Collingridge, Takashi Tominaga, and Kenichi Okamoto
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cAMP ,optogenetics ,photoactivatable adenylyl cyclase (PAC) ,VSD imaging ,electrophysiology ,long-term potentiation ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
cAMP is a positive regulator tightly involved in certain types of synaptic plasticity and related memory functions. However, its spatiotemporal roles at the synaptic and neural circuit levels remain elusive. Using a combination of a cAMP optogenetics approach and voltage-sensitive dye (VSD) imaging with electrophysiological recording, we define a novel capacity of postsynaptic cAMP in enabling dentate gyrus long-term potentiation (LTP) and depolarization in acutely prepared murine hippocampal slices. To manipulate cAMP levels at medial perforant path to granule neuron (MPP-DG) synapses by light, we generated transgenic (Tg) mice expressing photoactivatable adenylyl cyclase (PAC) in DG granule neurons. Using these Tg(CMV-Camk2a-RFP/bPAC)3Koka mice, we recorded field excitatory postsynaptic potentials (fEPSPs) from MPP-DG synapses and found that photoactivation of PAC during tetanic stimulation enabled synaptic potentiation that persisted for at least 30 min. This form of LTP was induced without the need for GABA receptor blockade that is typically required for inducing DG plasticity. The paired-pulse ratio (PPR) remained unchanged, indicating the cAMP-dependent LTP was likely postsynaptic. By employing fast fluorescent voltage-sensitive dye (VSD: di-4-ANEPPS) and fluorescence imaging, we found that photoactivation of the PAC actuator enhanced the intensity and extent of dentate gyrus depolarization triggered following tetanic stimulation. These results demonstrate that the elevation of cAMP in granule neurons is capable of rapidly enhancing synaptic strength and neuronal depolarization. The powerful actions of cAMP are consistent with this second messenger having a critical role in the regulation of synaptic function.
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- 2020
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20. Flexible motor sequence generation during stereotyped escape responses
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Yuan Wang, Xiaoqian Zhang, Qi Xin, Wesley Hung, Jeremy Florman, Jing Huo, Tianqi Xu, Yu Xie, Mark J Alkema, Mei Zhen, and Quan Wen
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motor sequence generation ,feedforward excitation ,winner-take-all ,escape response ,mutual inhibition ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Complex animal behaviors arise from a flexible combination of stereotyped motor primitives. Here we use the escape responses of the nematode Caenorhabditis elegans to study how a nervous system dynamically explores the action space. The initiation of the escape responses is predictable: the animal moves away from a potential threat, a mechanical or thermal stimulus. But the motor sequence and the timing that follow are variable. We report that a feedforward excitation between neurons encoding distinct motor states underlies robust motor sequence generation, while mutual inhibition between these neurons controls the flexibility of timing in a motor sequence. Electrical synapses contribute to feedforward coupling whereas glutamatergic synapses contribute to inhibition. We conclude that C. elegans generates robust and flexible motor sequences by combining an excitatory coupling and a winner-take-all operation via mutual inhibition between motor modules.
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- 2020
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21. Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
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Han, Xuefeng, Chen, Wen, Li, Jun, Ding, Ming, Wu, Qingqing, Wei, Kang, Deng, Xiumei, and Mei, Zhen
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Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
Federated learning (FL) has been recognized as a viable distributed learning paradigm for training a machine learning model across distributed clients without uploading raw data. However, FL in wireless networks still faces two major challenges, i.e., large communication overhead and high energy consumption, which are exacerbated by client heterogeneity in dataset sizes and wireless channels. While model quantization is effective for energy reduction, existing works ignore adapting quantization to heterogeneous clients and FL convergence. To address these challenges, this paper develops an energy optimization problem of jointly designing quantization levels, scheduling clients, allocating channels, and controlling computation frequencies (QCCF) in wireless FL. Specifically, we derive an upper bound identifying the influence of client scheduling and quantization errors on FL convergence. Under the longterm convergence constraints and wireless constraints, the problem is established and transformed into an instantaneous problem with Lyapunov optimization. Solving Karush-Kuhn-Tucker conditions, our closed-form solution indicates that the doubly adaptive quantization level rises with the training process and correlates negatively with dataset sizes. Experiment results validate our theoretical results, showing that QCCF consumes less energy with faster convergence compared with state-of-the-art baselines.
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- 2024
22. Do Rogue Wave Exist in the Kadomtesv-Petviashivili I Equation ?
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Zhang, Jie-Fang, Zhang, Zhao, Zhang, Meng-yang, and Jin, Mei-zhen
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Nonlinear Sciences - Pattern Formation and Solitons - Abstract
There is considerable fundamental theoretical and applicative interest in obtaining two-dimensional rogue wave similar to one-dimensional rogue wave of the nonlinear Schr\"odinger equation. Here, we first time proposes a self-mapping transformation and analytically predict the existence of a family of novel spatio-temporal rogue wave solutions for the Kadomtesv-Petviashivili equation. We discover that these spatio-temporal rogue waves showing a strong analogy characteristics of the short-lives with rogue waves of the NLS equation. Our fingdings can also provide a solid mathematical basis for theory and application in shallow water, plasma and optics. This technique could be available to construct rogue-like waves of (2+1)-dimensional nonlinear wave models. Also, these studies could be helpful to deepen our understandings and enrich our knowledge about rogue waves., Comment: 15 pages,2 figures,54 references
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- 2024
23. The HECT Family Ubiquitin Ligase EEL-1 Regulates Neuronal Function and Development
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Karla J. Opperman, Ben Mulcahy, Andrew C. Giles, Monica G. Risley, Rayna L. Birnbaum, Erik D. Tulgren, Ken Dawson-Scully, Mei Zhen, and Brock Grill
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EEL-1 ,HUWE1 ,intellectual disability ,motor neuron ,C. elegans ,RPM-1 ,GABA ,synaptic transmission ,acetylcholine ,seizure ,Biology (General) ,QH301-705.5 - Abstract
Genetic changes in the HECT ubiquitin ligase HUWE1 are associated with intellectual disability, but it remains unknown whether HUWE1 functions in post-mitotic neurons to affect circuit function. Using genetics, pharmacology, and electrophysiology, we show that EEL-1, the HUWE1 ortholog in C. elegans, preferentially regulates GABAergic presynaptic transmission. Decreasing or increasing EEL-1 function alters GABAergic transmission and the excitatory/inhibitory (E/I) balance in the worm motor circuit, which leads to impaired locomotion and increased sensitivity to electroshock. Furthermore, multiple mutations associated with intellectual disability impair EEL-1 function. Although synaptic transmission defects did not result from abnormal synapse formation, sensitizing genetic backgrounds revealed that EEL-1 functions in the same pathway as the RING family ubiquitin ligase RPM-1 to regulate synapse formation and axon termination. These findings from a simple model circuit provide insight into the molecular mechanisms required to obtain E/I balance and could have implications for the link between HUWE1 and intellectual disability.
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- 2017
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24. C. elegans neurons have functional dendritic spines
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Andrea Cuentas-Condori, Ben Mulcahy, Siwei He, Sierra Palumbos, Mei Zhen, and David M Miller III
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dendritic spines ,GABA ,acetylcholine ,motor neurons ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Dendritic spines are specialized postsynaptic structures that transduce presynaptic signals, are regulated by neural activity and correlated with learning and memory. Most studies of spine function have focused on the mammalian nervous system. However, spine-like protrusions have been reported in C. elegans (Philbrook et al., 2018), suggesting that the experimental advantages of smaller model organisms could be exploited to study the biology of dendritic spines. Here, we used super-resolution microscopy, electron microscopy, live-cell imaging and genetics to show that C. elegans motor neurons have functional dendritic spines that: (1) are structurally defined by a dynamic actin cytoskeleton; (2) appose presynaptic dense projections; (3) localize ER and ribosomes; (4) display calcium transients triggered by presynaptic activity and propagated by internal Ca++ stores; (5) respond to activity-dependent signals that regulate spine density. These studies provide a solid foundation for a new experimental paradigm that exploits the power of C. elegans genetics and live-cell imaging for fundamental studies of dendritic spine morphogenesis and function.
- Published
- 2019
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25. Gain-of-function mutations in the UNC-2/CaV2α channel lead to excitation-dominant synaptic transmission in Caenorhabditis elegans
- Author
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Yung-Chi Huang, Jennifer K Pirri, Diego Rayes, Shangbang Gao, Ben Mulcahy, Jeff Grant, Yasunori Saheki, Michael M Francis, Mei Zhen, and Mark J Alkema
- Subjects
ion channel ,neurotransmission ,GABA ,acetylcholine ,behavior ,calcium ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Mutations in pre-synaptic voltage-gated calcium channels can lead to familial hemiplegic migraine type 1 (FHM1). While mammalian studies indicate that the migraine brain is hyperexcitable due to enhanced excitation or reduced inhibition, the molecular and cellular mechanisms underlying this excitatory/inhibitory (E/I) imbalance are poorly understood. We identified a gain-of-function (gf) mutation in the Caenorhabditis elegans CaV2 channel α1 subunit, UNC-2, which leads to increased calcium currents. unc-2(zf35gf) mutants exhibit hyperactivity and seizure-like motor behaviors. Expression of the unc-2 gene with FHM1 substitutions R192Q and S218L leads to hyperactivity similar to that of unc-2(zf35gf) mutants. unc-2(zf35gf) mutants display increased cholinergic and decreased GABAergic transmission. Moreover, increased cholinergic transmission in unc-2(zf35gf) mutants leads to an increase of cholinergic synapses and a TAX-6/calcineurin-dependent reduction of GABA synapses. Our studies reveal mechanisms through which CaV2 gain-of-function mutations disrupt excitation-inhibition balance in the nervous system.
- Published
- 2019
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- View/download PDF
26. A 3D culture model of innervated human skeletal muscle enables studies of the adult neuromuscular junction
- Author
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Mohsen Afshar Bakooshli, Ethan S Lippmann, Ben Mulcahy, Nisha Iyer, Christine T Nguyen, Kayee Tung, Bryan A Stewart, Hubrecht van den Dorpel, Tobias Fuehrmann, Molly Shoichet, Anne Bigot, Elena Pegoraro, Henry Ahn, Howard Ginsberg, Mei Zhen, Randolph Scott Ashton, and Penney M Gilbert
- Subjects
3D co-culture ,neuromuscular junction ,skeletal muscle ,motor neuron ,myasthenia gravis ,acetylcholine receptor subunit epsilon ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Two-dimensional (2D) human skeletal muscle fiber cultures are ill-equipped to support the contractile properties of maturing muscle fibers. This limits their application to the study of adult human neuromuscular junction (NMJ) development, a process requiring maturation of muscle fibers in the presence of motor neuron endplates. Here we describe a three-dimensional (3D) co-culture method whereby human muscle progenitors mixed with human pluripotent stem cell-derived motor neurons self-organize to form functional NMJ connections. Functional connectivity between motor neuron endplates and muscle fibers is confirmed with calcium imaging and electrophysiological recordings. Notably, we only observed epsilon acetylcholine receptor subunit protein upregulation and activity in 3D co-cultures. Further, 3D co-culture treatments with myasthenia gravis patient sera shows the ease of studying human disease with the system. Hence, this work offers a simple method to model and evaluate adult human NMJ de novo development or disease in culture.
- Published
- 2019
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- View/download PDF
27. Corrigendum: A Pipeline for Volume Electron Microscopy of the Caenorhabditis elegans Nervous System
- Author
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Ben Mulcahy, Daniel Witvliet, Douglas Holmyard, James Mitchell, Andrew D. Chisholm, Yaron Meirovitch, Aravinthan D. T. Samuel, and Mei Zhen
- Subjects
C. elegans ,volume electron microscopy ,connectome ,nervous system ,high-pressure freezing ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 2019
- Full Text
- View/download PDF
28. An Improved Production Method of Bioactive Peptides from Sturgeon Fish Cartilage
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Lin, Mei-Zhen and Chen, Bing-Huei
- Published
- 2024
- Full Text
- View/download PDF
29. The association between baseline viral load and long-term risk in patients with COVID-19 in Hong Kong: a territory-wide study
- Author
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Tromp, Jasper, Wong, Michael, Ouwerkerk, Wouter, Wu, Mei-Zhen, Ren, Qing-wen, Chandramouli, Chanchal, Teramoto, Kanako, Teng, Katherine Tiew-Hwa, Huang, Jiayi, To, Kelvin-Kai-Wang, Hung, Ivan-Fan-Ngai, Tse, Hung-Fat, Lam, Carolyn S. P., and Yiu, Kai Hang
- Published
- 2024
- Full Text
- View/download PDF
30. Increased expression of the proapoptotic presenilin associated protein is involved in neuronal tangle formation in human brain
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Yang, Chen, Sun, Zhong-Ping, Jiang, Juan, Cai, Xiao-Lu, Wang, Yan, Wang, Hui, Che, Chong, Tu, Ewen, Pan, Ai-hua, Zhang, Yan, Wang, Xiao-Ping, Cui, Mei-Zhen, Xu, Xue-min, Yan, Xiao-Xin, and Zhang, Qi-Lei
- Published
- 2024
- Full Text
- View/download PDF
31. Lactiplantibacillus plantarum 299V-fermented soy whey improved the safety and shelf life of Pacific oysters (Magallana gigas)
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Chen, Lipin, Hua, Qian, Ten, Mei Zhen Michelle, Li, Zhaojie, Xue, Changhu, and Li, Dan
- Published
- 2024
- Full Text
- View/download PDF
32. Nocardamine mitigates cellular dysfunction induced by oxidative stress in periodontal ligament stem cells
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He, Hai-Peng, Zhao, Mei-Zhen, Jiao, Wei-Hua, Liu, Zhi-Qiang, Zeng, Xian-Hai, Li, Quan-Li, Hu, Tian-Yong, and Cheng, Bao-Hui
- Published
- 2024
- Full Text
- View/download PDF
33. Manipulating host secreted protein gene expression: an indirect approach by HPV11/16 E6/E7 to suppress PBMC cytokine secretion
- Author
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Zhong, Mei-zhen, Xu, Mei-nian, Zheng, Si-qi, Cheng, Shu-qiong, Zeng, Kang, and Huang, Xiao-wen
- Published
- 2024
- Full Text
- View/download PDF
34. Multi-modal molecular determinants of clinically relevant osteoporosis subtypes
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Yuan, Chunchun, Yu, Xiang-Tian, Wang, Jing, Shu, Bing, Wang, Xiao-Yun, Huang, Chen, Lv, Xia, Peng, Qian-Qian, Qi, Wen-Hao, Zhang, Jing, Zheng, Yan, Wang, Si-Jia, Liang, Qian-Qian, Shi, Qi, Li, Ting, Huang, He, Mei, Zhen-Dong, Zhang, Hai-Tao, Xu, Hong-Bin, Cui, Jiarui, Wang, Hongyu, Zhang, Hong, Shi, Bin-Hao, Sun, Pan, Zhang, Hui, Ma, Zhao-Long, Feng, Yuan, Chen, Luonan, Zeng, Tao, Tang, De-Zhi, and Wang, Yong-Jun
- Published
- 2024
- Full Text
- View/download PDF
35. Production of recombinant HPV11/16 E6/E7-MBP-His6 fusion proteins and their potential to induce cytokine secretion by immune cells in peripheral blood
- Author
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Xu, Mei-nian, Zhong, Mei-zhen, Feng, Si-ning, Xu, Yan-qin, Peng, Xiao-ming, Zeng, Kang, and Huang, Xiao-wen
- Published
- 2024
- Full Text
- View/download PDF
36. A Pipeline for Volume Electron Microscopy of the Caenorhabditis elegans Nervous System
- Author
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Ben Mulcahy, Daniel Witvliet, Douglas Holmyard, James Mitchell, Andrew D. Chisholm, Yaron Meirovitch, Aravinthan D. T. Samuel, and Mei Zhen
- Subjects
C. elegans ,volume electron microscopy ,connectome ,nervous system ,high-pressure freezing ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The “connectome,” a comprehensive wiring diagram of synaptic connectivity, is achieved through volume electron microscopy (vEM) analysis of an entire nervous system and all associated non-neuronal tissues. White et al. (1986) pioneered the fully manual reconstruction of a connectome using Caenorhabditis elegans. Recent advances in vEM allow mapping new C. elegans connectomes with increased throughput, and reduced subjectivity. Current vEM studies aim to not only fill the remaining gaps in the original connectome, but also address fundamental questions including how the connectome changes during development, the nature of individuality, sexual dimorphism, and how genetic and environmental factors regulate connectivity. Here we describe our current vEM pipeline and projected improvements for the study of the C. elegans nervous system and beyond.
- Published
- 2018
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37. The UBR-1 ubiquitin ligase regulates glutamate metabolism to generate coordinated motor pattern in Caenorhabditis elegans.
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Jyothsna Chitturi, Wesley Hung, Anas M Abdel Rahman, Min Wu, Maria A Lim, John Calarco, Renee Baran, Xun Huang, James W Dennis, and Mei Zhen
- Subjects
Genetics ,QH426-470 - Abstract
UBR1 is an E3 ubiquitin ligase best known for its ability to target protein degradation by the N-end rule. The physiological functions of UBR family proteins, however, remain not fully understood. We found that the functional loss of C. elegans UBR-1 leads to a specific motor deficit: when adult animals generate reversal movements, A-class motor neurons exhibit synchronized activation, preventing body bending. This motor deficit is rescued by removing GOT-1, a transaminase that converts aspartate to glutamate. Both UBR-1 and GOT-1 are expressed and critically required in premotor interneurons of the reversal motor circuit to regulate the motor pattern. ubr-1 and got-1 mutants exhibit elevated and decreased glutamate level, respectively. These results raise an intriguing possibility that UBR proteins regulate glutamate metabolism, which is critical for neuronal development and signaling.
- Published
- 2018
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38. Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding
- Author
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Cui, Jixuan, Li, Jun, Mei, Zhen, Wei, Kang, Wei, Sha, Ding, Ming, Chen, Wen, and Guo, Song
- Subjects
Computer Science - Machine Learning - Abstract
Deep learning-based fault diagnosis (FD) approaches require a large amount of training data, which are difficult to obtain since they are located across different entities. Federated learning (FL) enables multiple clients to collaboratively train a shared model with data privacy guaranteed. However, the domain discrepancy and data scarcity problems among clients deteriorate the performance of the global FL model. To tackle these issues, we propose a novel framework called representation encoding-based federated meta-learning (REFML) for few-shot FD. First, a novel training strategy based on representation encoding and meta-learning is developed. It harnesses the inherent heterogeneity among training clients, effectively transforming it into an advantage for out-of-distribution generalization on unseen working conditions or equipment types. Additionally, an adaptive interpolation method that calculates the optimal combination of local and global models as the initialization of local training is proposed. This helps to further utilize local information to mitigate the negative effects of domain discrepancy. As a result, high diagnostic accuracy can be achieved on unseen working conditions or equipment types with limited training data. Compared with the state-of-the-art methods, such as FedProx, the proposed REFML framework achieves an increase in accuracy by 2.17%-6.50% when tested on unseen working conditions of the same equipment type and 13.44%-18.33% when tested on totally unseen equipment types, respectively.
- Published
- 2023
39. Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity
- Author
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Han, Xuefeng, Li, Jun, Chen, Wen, Mei, Zhen, Wei, Kang, Ding, Ming, and Poor, H. Vincent
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training. However, data heterogeneity, e.g., non-independently identically distributions and different sizes of training data among clients, poses major challenges to wireless FL. Limited communication resources complicate the implementation of fair scheduling which is required for training on heterogeneous data, and further deteriorate the overall performance. To address this issue, this paper focuses on performance analysis and optimization for wireless FL, considering data heterogeneity, combined with wireless resource allocation. Specifically, we first develop a closed-form expression for an upper bound on the FL loss function, with a particular emphasis on data heterogeneity described by a dataset size vector and a data divergence vector. Then we formulate the loss function minimization problem, under constraints on long-term energy consumption and latency, and jointly optimize client scheduling, resource allocation, and the number of local training epochs (CRE). Next, via the Lyapunov drift technique, we transform the CRE optimization problem into a series of tractable problems. Extensive experiments on real-world datasets demonstrate that the proposed algorithm outperforms other benchmarks in terms of the learning accuracy and energy consumption.
- Published
- 2023
40. Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning.
- Author
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Kristin Verena Kaltdorf, Maria Theiss, Sebastian Matthias Markert, Mei Zhen, Thomas Dandekar, Christian Stigloher, and Philip Kollmannsberger
- Subjects
Medicine ,Science - Abstract
Synaptic vesicles (SVs) are a key component of neuronal signaling and fulfil different roles depending on their composition. In electron micrograms of neurites, two types of vesicles can be distinguished by morphological criteria, the classical "clear core" vesicles (CCV) and the typically larger "dense core" vesicles (DCV), with differences in electron density due to their diverse cargos. Compared to CCVs, the precise function of DCVs is less defined. DCVs are known to store neuropeptides, which function as neuronal messengers and modulators [1]. In C. elegans, they play a role in locomotion, dauer formation, egg-laying, and mechano- and chemosensation [2]. Another type of DCVs, also referred to as granulated vesicles, are known to transport Bassoon, Piccolo and further constituents of the presynaptic density in the center of the active zone (AZ), and therefore are important for synaptogenesis [3]. To better understand the role of different types of SVs, we present here a new automated approach to classify vesicles. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, the ImageJ macro 3D ART VeSElecT. With that we reliably distinguish CCVs and DCVs in electron tomograms of C. elegans NMJs using image-based features. Analysis of the underlying ground truth data shows an increased fraction of DCVs as well as a higher mean distance between DCVs and AZs in dauer larvae compared to young adult hermaphrodites. Our machine learning based tools are adaptable and can be applied to study properties of different synaptic vesicle pools in electron tomograms of diverse model organisms.
- Published
- 2018
- Full Text
- View/download PDF
41. Excitatory motor neurons are local oscillators for backward locomotion
- Author
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Shangbang Gao, Sihui Asuka Guan, Anthony D Fouad, Jun Meng, Taizo Kawano, Yung-Chi Huang, Yi Li, Salvador Alcaire, Wesley Hung, Yangning Lu, Yingchuan Billy Qi, Yishi Jin, Mark Alkema, Christopher Fang-Yen, and Mei Zhen
- Subjects
motor neuron ,rhythm ,Central Pattern Generator (CPG) ,locomotion ,C. elegans ,oscillation ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron’s oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron’s intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network.
- Published
- 2018
- Full Text
- View/download PDF
42. Lowering Hippocampal miR-29a Expression Slows Cognitive Decline and Reduces Beta-Amyloid Deposition in 5×FAD Mice
- Author
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Mei, Zhen, Liu, Jiaqi, Schroeder, Jason P, Weinshenker, David, Duong, Duc M., Seyfried, Nicholas T., Li, Yujing, Jin, Peng, Wingo, Aliza P., and Wingo, Thomas S.
- Published
- 2024
- Full Text
- View/download PDF
43. Correction: Neuroendocrine modulation sustains the C. elegans forward motor state
- Author
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Maria Lim, Jyothsna Chitturi, Valeriya Laskova, Jun Meng, Daniel Findeis, Anne Wiekenberg, Ben Mulcahy, Linjiao Luo, Yan Li, Yangning Lu, Wesley Hung, Yixin Qu, Chiyip Ho, Douglas Holmyard, Ni Ji, Rebecca D McWhirter, Aravinthan DT Samuel, David M Miller, Ralf Schnabel, John A Calarco, and Mei Zhen
- Subjects
Medicine ,Science ,Biology (General) ,QH301-705.5 - Published
- 2017
- Full Text
- View/download PDF
44. Neuroendocrine modulation sustains the C. elegans forward motor state
- Author
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Maria A Lim, Jyothsna Chitturi, Valeriya Laskova, Jun Meng, Daniel Findeis, Anne Wiekenberg, Ben Mulcahy, Linjiao Luo, Yan Li, Yangning Lu, Wesley Hung, Yixin Qu, Chi-Yip Ho, Douglas Holmyard, Ni Ji, Rebecca McWhirter, Aravinthan DT Samuel, David M Miller, Ralf Schnabel, John A Calarco, and Mei Zhen
- Subjects
peptidergic neurons ,neuroendocrine ,motor state ,RNA profiling ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Neuromodulators shape neural circuit dynamics. Combining electron microscopy, genetics, transcriptome profiling, calcium imaging, and optogenetics, we discovered a peptidergic neuron that modulates C. elegans motor circuit dynamics. The Six/SO-family homeobox transcription factor UNC-39 governs lineage-specific neurogenesis to give rise to a neuron RID. RID bears the anatomic hallmarks of a specialized endocrine neuron: it harbors near-exclusive dense core vesicles that cluster periodically along the axon, and expresses multiple neuropeptides, including the FMRF-amide-related FLP-14. RID activity increases during forward movement. Ablating RID reduces the sustainability of forward movement, a phenotype partially recapitulated by removing FLP-14. Optogenetic depolarization of RID prolongs forward movement, an effect reduced in the absence of FLP-14. Together, these results establish the role of a neuroendocrine cell RID in sustaining a specific behavioral state in C. elegans.
- Published
- 2016
- Full Text
- View/download PDF
45. Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic Segmentation
- Author
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Ye, Peng, Li, Baopu, Chen, Tao, Fan, Jiayuan, Mei, Zhen, Lin, Chen, Zuo, Chongyan, Chi, Qinghua, and Ouyan, Wanli
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Semantic segmentation is a popular research topic in computer vision, and many efforts have been made on it with impressive results. In this paper, we intend to search an optimal network structure that can run in real-time for this problem. Towards this goal, we jointly search the depth, channel, dilation rate and feature spatial resolution, which results in a search space consisting of about 2.78*10^324 possible choices. To handle such a large search space, we leverage differential architecture search methods. However, the architecture parameters searched using existing differential methods need to be discretized, which causes the discretization gap between the architecture parameters found by the differential methods and their discretized version as the final solution for the architecture search. Hence, we relieve the problem of discretization gap from the innovative perspective of solution space regularization. Specifically, a novel Solution Space Regularization (SSR) loss is first proposed to effectively encourage the supernet to converge to its discrete one. Then, a new Hierarchical and Progressive Solution Space Shrinking method is presented to further achieve high efficiency of searching. In addition, we theoretically show that the optimization of SSR loss is equivalent to the L_0-norm regularization, which accounts for the improved search-evaluation gap. Comprehensive experiments show that the proposed search scheme can efficiently find an optimal network structure that yields an extremely fast speed (175 FPS) of segmentation with a small model size (1 M) while maintaining comparable accuracy.
- Published
- 2022
46. An Energy Loss Calculating Method for Wind Power System Based on the Shape Factor
- Author
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Ruan Bo, Qian Junjie, You Dahai, Hou Tingting, Chen Xi, and Mei Zhen
- Subjects
Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
The large-scale access of the new energy makes various changes to the power system characteristics. For example, the acute volatility of the new energy such as wind power and photovoltaic energy makes the power-loss-calculation for the system more complex. The traditional typical daily method is inaccurate when used in new energy system because of its overlook of the generator output volatility. This paper proposes a new power-loss-calculation method for wind power system which based on the shape factor and gain a more accurate result. On the basis of this new calculating method, finds that the shape factor of the wind power plant for an hour period usually falls in a certain range. Therefore, proposes to directly use the expectation of shape factor in whole year to compute the annual energy loss with at least two values and once power flow calculation. And the acceptable relative error proves its large engineering practicability.
- Published
- 2018
- Full Text
- View/download PDF
47. Iterative Transfer Knowledge Distillation and Channel Pruning for Unsupervised Cross-Domain Compression
- Author
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Wang, Zhiyuan, Shi, Long, Mei, Zhen, Zhao, Xiang, Wang, Zhe, Li, Jun, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jin, Cheqing, editor, Yang, Shiyu, editor, Shang, Xuequn, editor, Wang, Haofen, editor, and Zhang, Yong, editor
- Published
- 2024
- Full Text
- View/download PDF
48. Multi-sensor feature fusion for vehicle detection based on the fuzzy longest common subsequence
- Author
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Zhao, Linfeng, Mei, Zhen, Shao, Wenbin, Fang, Ting, Hu, Jinfang, Zhang, Manling, and Jiang, Ping
- Published
- 2025
- Full Text
- View/download PDF
49. Interior-point policy optimization based multi-agent deep reinforcement learning method for secure home energy management under various uncertainties
- Author
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Zhang, Yiwen, Lin, Rui, Mei, Zhen, Lyu, Minghao, Jiang, Huaiguang, Xue, Ying, Zhang, Jun, and Gao, David Wenzhong
- Published
- 2024
- Full Text
- View/download PDF
50. Oleanolic acid derivatives against drug-resistant bacteria and fungi by multi-targets to avoid drug resistance
- Author
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Wei, Mei-Zhen, Wang, Zhao-Jie, Zhu, Yan-Yan, Zu, Wen-Biao, Zhao, Yun-Li, and Luo, Xiao-Dong
- Published
- 2024
- Full Text
- View/download PDF
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