Publications by authors named "Dahua Yu"

Introduction: Smoking is associated with significant alterations in sleep architecture. Previous studies have revealed changes in the subjective sleep of young smokers, but research on objective sleep assessment using polysomnography (PSG) is limited. This study aims to explore electroencephalography (EEG) power and sleep spindle activity during the sleep of young smokers, as well as to assess the relationship between sleep and smoking variables.

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Vacuum freeze-drying (VFD) technology has gained extensive application across various sectors, particularly in environmental applications, where it is primarily utilized for the fabrication of environmental functional materials and the conservation of environmental organisms. This technology is applicable to soil enhancement, the remediation of aquatic pollutants, energy storage in thermoelectric materials, and the preservation of bacterial cultures. This review synthesizes the most recent advancements in VFD technology within the environmental domain, elaborating on its technical fundamentals, operational procedures, practical applications, and distinctive benefits.

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Aims: The objective of the current study was to investigate the dynamic functional connectivity among large-scale brain networks in patients with insomnia, and to assess the efficacy of repetitive transcranial magnetic stimulation (rTMS) treatment in these individuals.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data from 62 insomnia patients and 69 healthy controls were used to compare differences in dynamic functional connectivity between the two groups. A total of 26 insomnia patients underwent rTMS for four weeks.

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Aims: This study investigated the changes in the organizational and intrinsical activities of the white matter functional networks (WMFNs) in young smokers using resting-state functional magnetic resonance imaging.

Methods: A data-driven approach was used to characterize the WMFNs of 30 young smokers and 30 non-smokers. We applied K-means clustering to the neuroimaging data to delineate the WMFNs.

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Background: Chest X-ray image classification for multiple diseases is an important research direction in the field of computer vision and medical image processing. It aims to utilize advanced image processing techniques and deep learning algorithms to automatically analyze and identify X-ray images, determining whether specific pathologies or structural abnormalities exist in the images.

Objective: We present the MMPDenseNet network designed specifically for chest multi-label disease classification.

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The variation in improvement among individuals with addiction after abstinence is a critical issue. Here, we aimed to identify robust multimodal markers associated with high response to 8-month abstinence in the individuals with heroin use disorder (HUD) and explore whether the identified markers could be generalized to the individuals with methamphetamine use disorder (MUD). According to the median of craving changes, 53 individuals with HUD with 8-month abstinence were divided into two groups: higher craving reduction and lower craving reduction.

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Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area.

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Background: Insomnia disorder (ID) is one of the most common mental disorders. Research on ID focuses on exploring its mechanism of disease, novel treatments and treatment outcome prediction. An emerging technique in this field is the use of electroencephalography (EEG) microstates, which offer a new method of EEG feature extraction that incorporates information from both temporal and spatial dimensions.

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Previous studies demonstrated that reward circuit plays an important role in smoking. The differences of functional and structural connectivity were found among several brain regions such as thalamus and frontal lobe. However, few studies focused on functional connectivity (FC) in whole-brain voxel level of young smokers.

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Sleep health is both conceptually and operationally a composite concept containing multiple domains of sleep. In line with this, high dependence and interaction across different domains of sleep health encourage a transition in sleep health research from categorical to dimensional approaches that integrate neuroscience and sleep health. Here, we seek to identify the covariance patterns between multiple sleep health domains and distributed intrinsic functional connectivity by applying a multivariate approach (partial least squares).

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Great progress has been made in understanding the neural mechanisms associated with alcohol-dependent (AD) patients. However, the interactions within the reward circuits of the patients need further exploration. Glutamatergic projections from the prefrontal cortex to some brain regions are present in the reward circuit.

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Despite burgeoning evidence for cortical hyperarousal in insomnia disorder, the existing results on electroencephalography spectral features are highly heterogeneous. Phase-amplitude coupling, which refers to the modulation of the low-frequency phase to a high-frequency amplitude, is probably a more sensitive quantitative measure for characterizing abnormal neural oscillations and explaining the therapeutic effect of repetitive transcranial magnetic stimulation in the treatment of patients with insomnia disorder. Sixty insomnia disorder patients were randomly divided into the active and sham treatment groups to receive 4 weeks of repetitive transcranial magnetic stimulation treatment.

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Background: It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes.

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Background: Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users.

Objective: The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs).

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Exposure to nicotine is the first cause of entirely preventable death killing, which is commonly initiated in adolescence. Previous studies revealed the changes of electroencephalography (EEG) and inhibition control in smokers. However, little is known about the specific link between alpha coherence during the resting state and inhibition control ability in young smokers.

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The development of nicotine addiction was associated with the abnormalities of intrinsic functional networks during the resting state in young adult smokers. As a whole-brain imaging approach, EEG microstate analysis treated multichannel EEG recordings as a series of quasi-steady microscopic states which were related to the resting-state networks (RSNs) found by fMRI. The aim of this study was to examine whether the resting-state EEG microstate analysis may provide novel insights into the abnormal temporal properties of intrinsic brain activities in young smokers.

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Neuroimaging technologies can non-invasively characterize the structure and function of addiction brain, reveal the neural mechanism of addictive behavior, and provide a priori for the potential targets of brain stimulation. Neuroimaging technologies has played an important role in the study of drug addiction diseases, relapse prediction, and therapeutic evaluation of non-invasive brain stimulations, but it also faces many challenges. In this manuscript, we discuss the classification and analysis methods of neuroimaging technologies, its application in addiction and challenges, thus to promote the application of neuroimaging technology in the treatment of drug addiction.

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Neuroscientists have devoted efforts to explore potential brain recovery after prolonged abstinence in heroin users (HU). However, not much is known about whether frontostriatal circuits can recover after prolonged abstinence in HU. An eight-month longitudinal study was carried out for HU.

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Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in smokers. Exposure to nicotine disrupts neurodevelopment during adolescence, possibly by disrupting the trophic effects of acetylcholine. However, little is known about the diffusion parameters of specific fibre bundles at multiple locations in young smokers.

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Article Synopsis
  • Increased participation in online gaming and other addictive behaviors among adolescents poses risks for unhealthy addictions due to immature cognitive control and high risk-taking tendencies during this developmental stage.
  • The study emphasizes the role of frontostriatal circuits in addiction, particularly focusing on internet gaming disorder (IGD) and nicotine addiction as emerging serious issues.
  • Findings reveal that two brain systems—an affective system (striatum) driven by emotional stimuli and a cognitive system (prefrontal cortex) providing inhibitory control—impact behaviors associated with addiction, highlighting potential avenues for effective treatments.
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