Publications by authors named "Zigang Huang"

The locus coeruleus (LC), as the primary source of norepinephrine (NE) in the brain, is central to modulating cognitive and behavioral processes. This review synthesizes recent findings to provide a comprehensive understanding of the LC-NE system, highlighting its molecular diversity, neurophysiological properties, and role in various brain functions. We discuss the heterogeneity of LC neurons, their differential responses to sensory stimuli, and the impact of NE on cognitive processes such as attention and memory.

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Background/objectives: A prominent endophenotype in Autism Spectrum Disorder (ASD) is the synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigate the postsynaptic signal transduction network in glutamatergic neurons and integrate single-cell nucleus transcriptomics data from the Prefrontal Cortex (PFC) to unveil the malfunction of translation control.

Methods: We devise an innovative and highly dependable pipeline to transform our acquired signal transduction network into an mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level.

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Chronic pain alters the configuration of brain functional networks. Primary dysmenorrhea (PDM) is a form of chronic visceral pain, which has been identified spatial alterations in brain functional networks using static functional connectivity analysis methods. However, the dynamics alterations of brain functional networks during pain-free periovulation phase remain unclear.

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Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting-state dynamic evolution of large-scale functional brain networks following rTMS has rarely been investigated. Here, using resting-state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex.

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The human brain is a dynamic system that shows frequency-specific features. Neuroimaging studies have shown that both healthy individuals and those with chronic pain disorders experience pain influenced by various processes that fluctuate over time. Primary dysmenorrhea (PDM) is a chronic visceral pain that disrupts the coordinated activity of brain's functional network.

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Article Synopsis
  • The study explores how spontaneous brain activity (intrinsic neural activities) changes over time when the brain is locally disturbed.
  • Researchers developed a method using statistical physics to analyze brain dynamics by examining patterns of nonreversibility in fMRI data.
  • Key findings indicate that longer analysis windows reduce variability of nonreversibility, show consistent states across different datasets, and reveal effects of stimulation on certain brain regions.
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Background: The brain in resting state has complex dynamic properties and shows frequency dependent characteristics. The frequency-dependent whole-brain dynamic changes of resting state across the scans have been ignored in Alzheimer's disease (AD).

Objective: Coactivation pattern (CAP) analysis can identify different brain states.

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Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics.

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Article Synopsis
  • Research identifies three key brain networks that are affected during resting states in Alzheimer's patients: the default mode network (DMN), salient network (SN), and central executive network (CEN).
  • Using an innovative method called energy landscape, the study examines how these networks function differently in Alzheimer's patients compared to healthy individuals.
  • Findings reveal that Alzheimer's patients exhibit unstable brain dynamics with heightened flexibility in state transitions, which correlates with clinical symptoms, thus shedding light on the underlying mechanisms of brain activity in the condition.
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Stroke is the leading cause of disability globally in need of novel and effective methods of rehabilitation. Intermittent theta burst stimulation (iTBS) has been adopted as a Level B recommendation for lower limb spasticity in guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS). Nonetheless, the methodological differences and deficits of existing work bring about heterogenous results and therefore limit the universal clinical use of rTMS in lower extremity (LE) rehabilitation.

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  • Poststroke aphasia results from damage to specific brain regions and disrupts overall brain network function, highlighting the complexity of language recovery.
  • Research into long-term brain changes in poststroke aphasia is limited, but this study uses fMRI to analyze brain dynamics in patients with left-frontal-stroke aphasia during an auditory task.
  • Findings show that patients experience restricted brain activity patterns shortly after a stroke, but improve in brain flexibility over time, linking these dynamics to abnormal brain network coordination, thus offering new insights into the recovery mechanisms of poststroke aphasia.
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Primary insomnia (PI) is among the most prevalent sleep-related disorders and has a far-reaching impact on daytime functioning. Repetitive transcranial magnetic stimulation (rTMS) has drawn attention because of its effectiveness and safety. The purpose of the current study was to detect changes in the topological organization of whole-brain functional networks and to determine their associations with the clinical treatment effects of rTMS.

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Fibroblast growth factor binding protein 3 (Fgfbp3) have been known to be crucial for the process of neural proliferation, differentiation, migration, and adhesion. However, the specific role and the molecular mechanisms of fgfbp3 in regulating the development of motor neurons remain unclear. In this study, we have investigated the function of fgfbp3 in morphogenesis and regeneration of motor neuron in zebrafish.

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Article Synopsis
  • Spatially separate, self-sustained oscillations in artificial neural networks are crucial for how these systems encode, store, and process information.
  • A new method allows for inducing a variety of oscillatory patterns and easily switching between them by manipulating a specific group of network nodes, known as the minimum feedback vertex set (mFVS).
  • Reactivating different combinations of these nodes can create numerous unique neuronal firing patterns, while being near a critical state can lead to chaotic behavior, allowing for flexible pattern switching in these networks.
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  • This study examined the differences in brain connectivity and small-world topology in patients with optic neuritis (ON) using resting-state fMRI and graph theory.
  • A total of 21 ON patients and 21 healthy controls were analyzed, revealing that ON patients had higher global network efficiency and small-world values but lower clustering coefficients compared to controls.
  • Overall, ON patients demonstrated unique "small world" brain networks with reduced connectivity in several brain regions, suggesting potential implications for understanding neural changes in this condition.
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is a fatal canker pathogen that causes significant reduction of crop yield in pear orchards. invades the trunk phloem, and is difficult to control by chemical treatment. In this work, it was found for the first time that -produced dipicolinic acid (DPA) exhibits antifungal activity against different canker pathogens, including , , , and .

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Non-coding RNAs are fundamental to the competing endogenous RNA (CeRNA) hypothesis in oncology. Previous work focused on static CeRNA networks. We construct and analyze CeRNA networks for four sequential stages of lung adenocarcinoma (LUAD) based on multi-omics data of long non-coding RNAs (lncRNAs), microRNAs and mRNAs.

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Sex-determining region Y box 2 (Sox2), expressed in neural tissues, plays an important role as a transcription factor not only in the pluripotency and proliferation of neuronal cells but also in the opposite function of cell differentiation. Nevertheless, how Sox2 is linked to motor neuron development remains unknown. Here, we showed that Sox2 was localized in the motor neurons of spinal cord by hybridization and cell separation, which acted as a positive regulator of motor neuron development.

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Primary human hepatocytes (PHHs) are the 'gold standard' for investigating hepatitis B virus (HBV) infection and antiviral drugs. However, poor availability, variation between batches and ethical issues regarding PHHs limit their applications. The discovery of human sodium taurocholate co‑transporting polypeptide (hNTCP) as a functional HBV receptor has enabled the development of a surrogate model to supplement the use of PHHs.

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The main point of this paper is to provide an affirmative answer through exploiting reinforcement learning (RL) in artificial intelligence (AI) for eliminating herding without any external control in complex resource allocation systems. In particular, we demonstrate that when agents are empowered with RL (e.g.

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We analyze five big data sets from a variety of online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors. For example, there is linear growth associated with online recommendation and sharing platforms, a plateaued (or an "S"-shape) type of growth behavior in a web service devoted to helping users to collect bookmarks, and an exponential increase on the largest and most popular microblogging website in China. Does a universal mechanism with a common set of dynamical rules exist, which can explain these empirically observed, distinct growth behaviors? We provide an affirmative answer in this paper.

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Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model.

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Radiotherapy plays a vital role in cancer treatment, for which accurate prognosis is important for guiding sequential treatment and improving the curative effect for patients. An issue of great significance in radiotherapy is to assess tumor radiosensitivity for devising the optimal treatment strategy. Previous studies focused on gene expression in cells closely associated with radiosensitivity, but factors such as the response of a cancer patient to irradiation and the patient survival time are largely ignored.

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Alzheimer's disease (AD) is a worldwide progressive neurodegenerative disorder in the elderly. Previous research has indicated that Alzheimer's disease impairs white matter (WM) tracts. Anatomical and neuroimaging studies have indicated that WM tracts are associated with cognitive function.

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Clique percolation has attracted much attention due to its significance in understanding topological overlap among communities and dynamical instability of structured systems. Rich critical behavior has been observed in clique percolation on Erdős-Rényi (ER) random graphs, but few works have discussed clique percolation on finite dimensional systems. In this paper, we have defined a series of characteristic events, i.

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