Publications by authors named "Yunkai Sun"

6 Publications

  • Page 1 of 1

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.

J Psychiatr Res 2021 Jun 8;138:569-575. Epub 2021 May 8.

College of Education, Hangzhou Normal University, Hangzhou, 311121, China.

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.
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http://dx.doi.org/10.1016/j.jpsychires.2021.05.010DOI Listing
June 2021

Rational Compositional Control of Electrodeposited Ag-Fe films.

Inorg Chem 2020 Apr 2;59(8):5405-5417. Epub 2020 Apr 2.

Department of Materials Science and Engineering, University of Virginia, Charlottesville, Virginia 22904, United States.

Some alloys are very difficult to electrodeposit, due to problems such as the large difference in the equilibrium potentials and/or deposition kinetics of the alloy components, as well as the bath instability due to the spontaneous reactions in the bulk electrolyte. The Ag-Fe system is one of those. In this work, a novel alkaline citrate-dimethylhydantoin (DMH) complex has been used to synthesize thermodynamically immiscible Ag-Fe alloy films. The large difference in standard potentials and deposition kinetics of Ag and Fe is partially resolved by complexing Ag(I) with DMH, while the instability caused from spontaneous reduction of Ag(I) by Fe(II) was partially resolved by adding 1% Fe, based on the philosophy of the mixed potential theory. Furthermore, a paradigm for control of film composition is developed, based on the mass-transfer coefficient ratio, tested with various bath constitutions. Uniform and high-quality films are obtained, with a composition error of <4 at. % comparing with the predicted values. Electrochemical reactions involved in the deposition baths were systematically investigated using cyclic voltammetry, showing satisfactory agreement with the predicted deposition potentials calculated by equilibrium thermodynamics. The films deposited at high overpotential are proven to be biphasic, containing Ag-fcc and Fe-bcc phases, with a trend of decreasing crystallinity at increasing overpotentials when deposited at constant deposition time. A narrow transition potential range (<0.05 V) from the onset of Fe deposition to its limiting current condition was observed.
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http://dx.doi.org/10.1021/acs.inorgchem.9b03600DOI Listing
April 2020

Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach.

Neuropsychiatr Dis Treat 2020 10;16:691-702. Epub 2020 Mar 10.

Center for Cognition and Brain Disorders, Institute of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 311121, People's Republic of China.

Purpose: In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from whole-brain resting-state functional connectivity patterns using machine learning.

Patients And Methods: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests.

Results: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD ( < 0.05).

Conclusion: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.
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http://dx.doi.org/10.2147/NDT.S239013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071874PMC
March 2020

Cooperative Capture of Uranyl Ions by a Carbonyl-Bearing Hierarchical-Porous Cu-Organic Framework.

Angew Chem Int Ed Engl 2019 Dec 8;58(52):18808-18812. Epub 2019 Nov 8.

Department of Chemistry, CICECO-Aveiro Institute of Materials, University of Aveiro, Santiago Campus, Aveiro, 3810-193, Portugal.

To efficiently capture the toxic uranyl ions (UO ), a new hierarchical micro-macroporous metal-organic framework was prepared under template-free conditions, featuring interconnected multi-nanocages bearing carbonyl groups derived from a semi-rigid ligand. The material exhibits an unusually high UO sorption capacity of 562 mg g , which occurs in an intriguing two-steps process, on the macropore-based crystal surface and in the inner nanocages. Notably, the latter is attributed to the cooperative interplay of the shrinkage of the host porous framework induced by uranyl accommodation and the free carbonyl coordination sites, as shown by both single-crystal X-ray diffraction and a red-shift of the infrared [O=U =O] antisymmetric vibration band.
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http://dx.doi.org/10.1002/anie.201909045DOI Listing
December 2019

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder.

Neuropsychiatr Dis Treat 2019 11;15:2629-2638. Epub 2019 Sep 11.

Center for Cognition and Brain Disorders, Institutes of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 311121, People's Republic of China.

Purpose: Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients.

Patients And Methods: We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns.

Results: The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients.

Conclusion: This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.
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http://dx.doi.org/10.2147/NDT.S220743DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6750201PMC
September 2019

Altered hypothalamic functional connectivity patterns in major depressive disorder.

Neuroreport 2019 11;30(16):1115-1120

Center for Cognition and Brain Disorders, Institutes of Psychological Sciences and the Affiliated Hospital, Hangzhou Normal University.

The hypothalamus is a limbic structure involved in the emergence and persistence of major depressive disorder symptoms. Previous studies have indicated that major depressive disorder patients exhibited dysregulation between the hypothalamus and cerebral regions. However, it is still unclear about the exact hypothalamic functional connectivity patterns with other brain regions based on resting-state functional MRI in major depressive disorder. Here, we investigated the whole-brain voxel-based hypothalamic resting-state functional connectivity in 55 patients with major depressive disorder and 40 age sex-matched healthy controls. The results showed that major depressive disorder patients had a significant decrease in resting-state functional connectivity of the bilateral hypothalamus with the right insula, superior temporal gyrus, inferior frontal gyrus, and Rolandic operculum compared with healthy controls. This study suggests that the pathophysiology of major depressive disorder might be associated with the abnormal hypothalamic resting-state functional connectivity.
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http://dx.doi.org/10.1097/WNR.0000000000001335DOI Listing
November 2019