Publications by authors named "Ming Dong"

607 Publications

Nanoarmour-shielded single-cell factory for bacteriotherapy of Parkinson's disease.

J Control Release 2021 Sep 10. Epub 2021 Sep 10.

Academy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Xincheng Hospital of Tianjin University, Tianjin University, Tianjin 300072, China; Healthina Academy of Cellular Intelligence Manufacturing & Neurotrauma Repair, Beijing Tangyi Huikang Biomedical Technology Co., Ltd, Beijing 100010, China. Electronic address:

Cell-based therapy for Parkinson's disease (PD) is a novel and promising approach in recent years. However, exogenous cells are easy to be captured and destroyed by the harsh environment in vivo, so their application prospects have been severely limited. Here, a facile yet versatile approach for decorating individual living cells with nano-armor coatings is reported. By simply self-assembly with liposome under a cyto-compatible condition, the lipid bimolecular coating on the surface of each cell acts as armor to effectively protect it from the attack and destruction of strong acids and digestive enzymes during the oral treatment of PD. Our results demonstrated that the liposome coated B. adolescentis (LCB) could significantly improve the colonization rate in the intestinal tract. LCB, as a living cell factory, can self-regulate to produce a constant concentration of γ-aminobutyric acid and maintain a longer half-life for the treatment of PD. Then, we also explored the specific mechanism of LCB to improve the behavior of murine models of PD, including abating inflammatory effects, reducing neuronal apoptosis, regulating the activity of dopaminergic neurons and microglia. The simple nano-armor shielded single-cell factory can produce neurotransmitters-like drugs on demand in vivo, introducing novel strategies of integration of producing and using to the research of drug delivery field.
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http://dx.doi.org/10.1016/j.jconrel.2021.09.009DOI Listing
September 2021

Integrated printed BDNF/collagen/chitosan scaffolds with low temperature extrusion 3D printer accelerated neural regeneration after spinal cord injury.

Regen Biomater 2021 Oct 12;8(6):rbab047. Epub 2021 Aug 12.

Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.

Recent studies have shown that 3D printed scaffolds integrated with growth factors can guide the growth of neurites and promote axon regeneration at the injury site. However, heat, organic solvents or cross-linking agents used in conventional 3D printing reduce the biological activity of growth factors. Low temperature 3D printing can incorporate growth factors into the scaffold and maintain their biological activity. In this study, we developed a collagen/chitosan scaffold integrated with brain-derived neurotrophic factor (3D-CC-BDNF) by low temperature extrusion 3D printing as a new type of artificial controlled release system, which could prolong the release of BDNF for the treatment of spinal cord injury (SCI). Eight weeks after the implantation of scaffolds in the transected lesion of T10 of the spinal cord, 3D-CC-BDNF significantly ameliorate locomotor function of the rats. Consistent with the recovery of locomotor function, 3D-CC-BDNF treatment could fill the gap, facilitate nerve fiber regeneration, accelerate the establishment of synaptic connections and enhance remyelination at the injury site.
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http://dx.doi.org/10.1093/rb/rbab047DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417565PMC
October 2021

Imagined speech increases the hemodynamic response and functional connectivity of the dorsal motor cortex.

J Neural Eng 2021 Sep 10. Epub 2021 Sep 10.

Tianjin University, 92, Weijin Road, Nankai District, Tianjin, China, Tianjin, Tianjin, 300072, CHINA.

Objective: Decoding imagined speech from brain signals could provide a more natural, user-friendly way for developing the next generation of the brain-computer interface (BCI). With the advantages of non-invasive, portable, relatively high spatial resolution and insensitivity to motion artifacts, the functional near-infrared spectroscopy (fNIRS) shows great potential for developing the non-invasive speech BCI. However, there is a lack of fNIRS evidence in uncovering the neural mechanism of imagined speech. Our goal is to investigate the specific brain regions and the corresponding cortico-cortical functional connectivity features during imagined speech with fNIRS.

Approach: fNIRS signals were recorded from thirteen subjects' bilateral motor and prefrontal cortex during overtly and covertly repeating words. Cortical activation was determined through the mean oxygen-hemoglobin concentration changes, and functional connectivity was calculated by Pearson's correlation coefficient.

Main Results: (1) The bilateral dorsal motor cortex was significantly activated during the covert speech, whereas the bilateral ventral motor cortex was significantly activated during the overt speech. (2) As a subregion of the motor cortex, sensorimotor cortex (SMC) showed a dominant dorsal response to covert speech condition, whereas a dominant ventral response to overt speech condition. (3) Broca's area was deactivated during the covert speech but activated during the overt speech. (4) Compared to overt speech, dorsal SMC-related functional connections were enhanced during the covert speech.

Significance: We provide fNIRS evidence for the involvement of dSMC in speech imagery. dSMC is the speech imagery network's key hub and is probably involved in the sensorimotor information processing during the covert speech. This study could inspire the BCI community to focus on the potential contribution of dSMC during speech imagery.
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http://dx.doi.org/10.1088/1741-2552/ac25d9DOI Listing
September 2021

White matter structural connectivity as a biomarker for detecting juvenile myoclonic epilepsy by transferred deep convolutional neural networks with varying transfer rates.

J Neural Eng 2021 Sep 10. Epub 2021 Sep 10.

Dept. of Biomedical Engineering, Tianjin University, School of Precision Instrument and Opto-Electronics Engineering, Tianjin 300072, Tianjin, Tianjin, 300072, CHINA.

Objective: By detecting the abnormal white matter changes, diffusion magnetic resonance imaging (MRI) contributes to the detection of juvenile myoclonic epilepsy (JME). In addition, deep learning has greatly improved the detection performance of various brain disorders. However, there is almost no previous study effectively detecting JME by deep learning approach with diffusion MRI.

Approach: In this study, the white matter structural connectivity was generated by tracking the white matter fibers in detail based on Q-ball imaging (QBI) and neurite orientation dispersion and density imaging (NODDI). Four advanced deep convolutional neural networks (CNNs) were deployed by using the transfer learning approach, in which the transfer rate searching strategy was proposed to achieve the best detection performance.

Main Results: Our results showed: (1) Compared to normal control (NC), white matter's neurite density of JME was significantly decreased. And the most significantly abnormal fiber tracts between two groups were found to be cortico-cortical connection tracts. (2) The proposed transfer rate searching approach contributed to find each CNN's best performance, in which the best JME detection accuracy of 92.2% was achieved by using Inception_resnet_v2 network with a 16% transfer rate.

Significance: The results revealed: (1) By detecting the abnormal white matter changes, the white matter structural connectivity is a useful biomarker for detecting JME, which helps to character the pathophysiology of epilepsy. (2) The proposed transfer rate, as a new hyper-parameter, promotes the CNNs' transfer learning performance on detecting JME.
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http://dx.doi.org/10.1088/1741-2552/ac25d8DOI Listing
September 2021

The Effects of the Structural and Acoustic Parameters of the Skull Model on Transcranial Focused Ultrasound.

Sensors (Basel) 2021 Sep 5;21(17). Epub 2021 Sep 5.

Laboratory of Neural Engineering and Rehabilitation, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China.

Transcranial focused ultrasound (tFUS) has great potential in brain imaging and therapy. However, the structural and acoustic differences of the skull will cause a large number of technical problems in the application of tFUS, such as low focus energy, focal shift, and defocusing. To have a comprehensive understanding of the skull effect on tFUS, this study investigated the effects of the structural parameters (thickness, radius of curvature, and distance from the transducer) and acoustic parameters (density, acoustic speed, and absorption coefficient) of the skull model on tFUS based on acrylic plates and two simulation methods (self-programming and COMSOL). For structural parameters, our research shows that as the three factors increase the unit distance, the attenuation caused from large to small is the thickness (0.357 dB/mm), the distance to transducer (0.048 dB/mm), and the radius of curvature (0.027 dB/mm). For acoustic parameters, the attenuation caused by density (0.024 dB/30 kg/m) and acoustic speed (0.021 dB/30 m/s) are basically the same. Additionally, as the absorption coefficient increases, the focus acoustic pressure decays exponentially. The thickness of the structural parameters and the absorption coefficient of the acoustic parameters are the most important factors leading to the attenuation of tFUS. The experimental and simulation trends are highly consistent. This work contributes to the comprehensive and quantitative understanding of how the skull influences tFUS, which further enhances the application of tFUS in neuromodulation research and treatment.
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http://dx.doi.org/10.3390/s21175962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434628PMC
September 2021

Acupuncture With Modulates the Hemodynamic Response and Functional Connectivity of the Prefrontal-Motor Cortical Network.

Front Neurosci 2021 16;15:693623. Epub 2021 Aug 16.

Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.

As a world intangible cultural heritage, acupuncture is considered an essential modality of complementary and alternative therapy to Western medicine. Despite acupuncture's long history and public acceptance, how the cortical network is modulated by acupuncture remains largely unclear. Moreover, as the basic acupuncture unit for regulating the central nervous system, how the cortical network is modulated during acupuncture at the Hegu acupoint is mostly unclear. Here, multi-channel functional near-infrared spectroscopy (fNIRS) data were recorded from twenty healthy subjects for acupuncture manipulation, pre- and post-manipulation tactile controls, and pre- and post-acupuncture rest controls. Results showed that: (1) acupuncture manipulation caused significantly increased acupuncture behavioral performance compared with tactile controls. (2) The bilateral prefrontal cortex (PFC) and motor cortex were significantly inhibited during acupuncture manipulation than controls, which was evidenced by the decreased power of oxygenated hemoglobin (HbO) concentration. (3) The bilateral PFC's hemodynamic responses showed a positive correlation trend with acupuncture behavioral performance. (4) The network connections with bilateral PFC as nodes showed significantly increased functional connectivity during acupuncture manipulation compared with controls. (5) Meanwhile, the network's efficiency was improved by acupuncture manipulation, evidenced by the increased global efficiency and decreased shortest path length. Taken together, these results reveal that a cooperative PFC-Motor functional network could be modulated by acupuncture manipulation at the Hegu acupoint. This study provides neuroimaging evidence that explains acupuncture's neuromodulation effects on the cortical network.
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http://dx.doi.org/10.3389/fnins.2021.693623DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415569PMC
August 2021

Potential distribution of the extremely endangered species Ostrya rehderiana (Betulaceae) in China under future climate change.

Environ Sci Pollut Res Int 2021 Sep 3. Epub 2021 Sep 3.

Key Laboratory of Hangzhou City for Ecosystem Protection and Restoration, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 311121, China.

Global climate change is a major threat to biodiversity, which may increase the extinction risk of rare species, particularly those like Ostrya rehderiana Chun (Betulaceae) with very few remaining extant wild individuals. We aimed to estimate the potential distribution of O. rehderiana under climate change and to analyze possible relevant climatic factors. Maximum entropy (Maxent) was employed to model the potential distribution of O. rehderiana under present and future climate scenarios. Suitable habitat areas in different periods and the main contributing climate factors were identified using species distribution models. The minimum temperature in winter and precipitation seasonality were the principal climatic factors influencing the establishment of O. rehderiana. The proportion of high potential distribution area in China was 3.91% and would further shrink significantly under changing climate, especially reduce by 97% under high radiative forcing. The extinction risk of O. rehderiana would still be extraordinarily high under future climate scenarios. The Tianmu and Luoxiao Mountains would be the only potential refugia for O. rehderiana in the future. Special conservation efforts are urgently required to rescue extremely endangered species as O. rehderiana. We propose priorities for the conservation region and suggestions for conservation management strategies.
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http://dx.doi.org/10.1007/s11356-021-16268-1DOI Listing
September 2021

Efficacy and breadth of adjuvanted SARS-CoV-2 receptor-binding domain nanoparticle vaccine in macaques.

Proc Natl Acad Sci U S A 2021 09;118(38)

US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD 20910.

Emergence of novel variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need for next-generation vaccines able to elicit broad and durable immunity. Here we report the evaluation of a ferritin nanoparticle vaccine displaying the receptor-binding domain of the SARS-CoV-2 spike protein (RFN) adjuvanted with Army Liposomal Formulation QS-21 (ALFQ). RFN vaccination of macaques using a two-dose regimen resulted in robust, predominantly Th1 CD4+ T cell responses and reciprocal peak mean serum neutralizing antibody titers of 14,000 to 21,000. Rapid control of viral replication was achieved in the upper and lower airways of animals after high-dose SARS-CoV-2 respiratory challenge, with undetectable replication within 4 d in seven of eight animals receiving 50 µg of RFN. Cross-neutralization activity against SARS-CoV-2 variant B.1.351 decreased only approximately twofold relative to WA1/2020. In addition, neutralizing, effector antibody and cellular responses targeted the heterotypic SARS-CoV-1, highlighting the broad immunogenicity of RFN-ALFQ for SARS-CoV-like Sarbecovirus vaccine development.
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http://dx.doi.org/10.1073/pnas.2106433118DOI Listing
September 2021

Workspace Volume of Human Bimanual Precision Manipulation Influenced by the Wrist Configuration and Finger Combination.

IEEE Trans Haptics 2021 Sep 1;PP. Epub 2021 Sep 1.

Bimanual precision manipulation is an essential ability in daily human lives. However, the kinematic ability of bimanual precision manipulation due to its complexity and randomness was rarely discussed. This study firstly presents an objective quantitative evaluation of bimanual precision manipulation based on workspace volume. It focuses on studying the effects of the wrist and finger factors on the bimanual manipulation abilities by measuring the workspaces through which ten participants manipulated an object under the 12 situations (3 wrist configurations 4 finger combinations). The results show that the wrists participation significantly increases the workspace for bimanual precision manipulation, while different finger combinations also substantially affect workspace volume. Therefore, we found an optimal hand situation (two indexes cooperating with the wrists participation), allowing the workspace to reach a volume of 1600cm3, which is ten times higher than the worst situation. Furthermore, the involvement of the right thumb can significantly increase the contribution ratio of finger movement in bimanual precision manipulation, making the movement more accurate and stable. The study has the potential to contribute to the researches in many domains, ranging from developing surgical devices, training doctors in microsurgical techniques, providing normative data for rehabilitation.
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http://dx.doi.org/10.1109/TOH.2021.3108855DOI Listing
September 2021

Computational analysis of protein conformational heterogeneity.

J Biomol Struct Dyn 2021 Aug 23:1-6. Epub 2021 Aug 23.

Department of Chemistry, North Carolina Agricultural and Technical State University, Greensboro, NC, USA.

In this paper, we applied the molecular dynamics (MD) simulations and used thermolysin as the system to study the overall protein dynamics and side chain dihedral angles across the Arrhenius break. Simulations were performed at a high temperature of 36 °C which is above the previously observed Arrhenius break, and the lower temperature of 20 °C which is below the Arrhenius break. We observed different protein dynamics and conformational heterogeneity of side chain dihedral angles of thermolysin at the two temperatures. Our results indicated that certain regions of thermolysin have a higher level of fluctuation at lower temperature. A temperature dependent dihedral angles were also observed at the two temperatures. The changes observed in the protein indicated key areas of temperature sensitivity within the protein.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1967784DOI Listing
August 2021

Enhancing transfer performance across datasets for brain-computer interfaces using a combination of alignment strategies and adaptive batch normalization.

J Neural Eng 2021 08 31;18(4). Epub 2021 Aug 31.

Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.

. Recently, transfer learning (TL) and deep learning (DL) have been introduced to solve intra- and inter-subject variability problems in brain-computer interfaces (BCIs). However, current TL and DL algorithms are usually validated within a single dataset, assuming that data of the test subjects are acquired under the same condition as that of training (source) subjects. This assumption is generally violated in practice because of different acquisition systems and experimental settings across studies and datasets. Thus, the generalization ability of these algorithms needs further validations in a cross-dataset scenario, which is closer to the actual situation. This study compared the transfer performance of pre-trained deep-learning models with different preprocessing strategies in a cross-dataset scenario.. This study used four publicly available motor imagery datasets, each was successively selected as a source dataset, and the others were used as target datasets. EEGNet and ShallowConvNet with four preprocessing strategies, namely channel normalization, trial normalization, Euclidean alignment, and Riemannian alignment, were trained with the source dataset. The transfer performance of pre-trained models was validated on the target datasets. This study also used adaptive batch normalization (AdaBN) for reducing interval covariate shift across datasets. This study compared the transfer performance of using the four preprocessing strategies and that of a baseline approach based on manifold embedded knowledge transfer (MEKT). This study also explored the possibility and performance of fusing MEKT and EEGNet.. The results show that DL models with alignment strategies had significantly better transfer performance than the other two preprocessing strategies. As an unsupervised domain adaptation method, AdaBN could also significantly improve the transfer performance of DL models. The transfer performance of DL models that combined AdaBN and alignment strategies significantly outperformed MEKT. Moreover, the generalizability of EEGNet models that combined AdaBN and alignment strategies could be further improved via the domain adaptation step in MEKT, achieving the best generalization ability among multiple datasets (BNCI2014001: 0.788, PhysionetMI: 0.679, Weibo2014: 0.753, Cho2017: 0.650).. The combination of alignment strategies and AdaBN could easily improve the generalizability of DL models without fine-tuning. This study may provide new insights into the design of transfer neural networks for BCIs by separating source and target batch normalization layers in the domain adaptation process.
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http://dx.doi.org/10.1088/1741-2552/ac1ed2DOI Listing
August 2021

Mesenchymal stem cell-derived exosomal miR-146a reverses diabetic β-cell dedifferentiation.

Stem Cell Res Ther 2021 08 11;12(1):449. Epub 2021 Aug 11.

Department of Endocrinology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, No. 107 Wenhua Xi Road, Jinan, 250012, Shandong, China.

Background: Mesenchymal stem cells (MSCs) show promising therapeutic potential in treating type 2 diabetes mellitus (T2DM) in clinical studies. Accumulating evidence has suggested that the therapeutic effects of MSCs are not due to their direct differentiation into functional β-cells but are instead mediated by their paracrine functions. Among them, exosomes, nano-sized extracellular vesicles, are important substances that exert paracrine functions. However, the underlying mechanisms of exosomes in ameliorating T2DM remain largely unknown.

Methods: Bone marrow mesenchymal stem cell (bmMSC)-derived exosomes (bmMDEs) were administrated to T2DM rats and high-glucose-treated primary islets in order to detect their effects on β-cell dedifferentiation. Differential miRNAs were then screened via miRNA sequencing, and miR-146a was isolated after functional verification. TargetScan, reporter gene detection, insulin secretion assays, and qPCR validation were used to predict downstream target genes and involved signaling pathways of miR-146a.

Results: Our results showed that bmMDEs reversed diabetic β-cell dedifferentiation and improved β-cell insulin secretion both in vitro and in vivo. Results of miRNA sequencing in bmMDEs and subsequent functional screening demonstrated that miR-146a, a highly conserved miRNA, improved β-cell function. We further found that miR-146a directly targeted Numb, a membrane-bound protein involved in cell fate determination, leading to activation of β-catenin signaling in β-cells. Exosomes derived from miR-146a-knockdown bmMSCs lost the ability to improve β-cell function.

Conclusions: These findings demonstrate that bmMSC-derived exosomal miR-146a protects against diabetic β-cell dysfunction by acting on the NUMB/β-catenin signaling pathway, which may represent a novel therapeutic strategy for T2DM.
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http://dx.doi.org/10.1186/s13287-021-02371-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356465PMC
August 2021

Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.

Cogn Neurodyn 2021 Aug 10;15(4):569-584. Epub 2021 Apr 10.

Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.

A brain-computer interface (BCI) can connect humans and machines directly and has achieved successful applications in the past few decades. Many new BCI paradigms and algorithms have been developed in recent years. Therefore, it is necessary to review new progress in BCIs. This paper summarizes progress for EEG-based BCIs from the perspective of encoding paradigms and decoding algorithms, which are two key elements of BCI systems. Encoding paradigms are grouped by their underlying neural meachanisms, namely sensory- and motor-related, vision-related, cognition-related and hybrid paradigms. Decoding algorithms are reviewed in four categories, namely decomposition algorithms, Riemannian geometry, deep learning and transfer learning. This review will provide a comprehensive overview of both modern primary paradigms and algorithms, making it helpful for those who are developing BCI systems.
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http://dx.doi.org/10.1007/s11571-021-09676-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286913PMC
August 2021

Maternal urinary cadmium concentrations in early pregnancy in relation to prenatal and postpartum size of offspring.

J Trace Elem Med Biol 2021 Jul 16;68:126823. Epub 2021 Jul 16.

National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China. Electronic address:

Background: The impacts of environmental cadmium (Cd) exposure on birth size parameters including weight, length and head circumference (HC) have been reported in multiple studies. However, little remains known of the impacts of maternal Cd exposure during pregnancy on size during in utero development and during early childhood. The aim of this study was to comprehensively investigate impacts of maternal Cd exposure during pregnancy on the size of offspring in utero (from 24 weeks pregnancy) until six months of age.

Methods: Pregnant mothers were recruited as part of an ongoing prospective birth cohort study based in Guangdong, China. Maternal urine samples were collected in the first and third trimesters of pregnancy, in which Cd concentrations were measured by inductively couple plasma mass spectrometry (ICPMS). In utero size indicators at 24 and 32 week of gestation, including biparietal diameter (BPD), abdominal circumference (AC), femur length (FL) and HC were derived from ultrasound examinations. Anthropometric measures of weight, height and HC at birth and one, three and six months of age were also collected. Associations of size measures at the various time points with maternal urinary Cd concentrations were assessed using linear regression models.

Results: The median urinary Cd concentration was 1.00 and 0.98 μg/g creatinine in the first and third trimesters respectively. In univariate analysis, increased maternal Cd levels in the first trimester were associated with decreased HC (-0.17 cm/ug/g urinary Cd) at birth, and the association was particularly pronounced among males (-0.30 cm/ug/g urinary Cd). First trimester Cd exposure was also found to be significantly associated with decreased infant weight at three and six months of age among girls (-101 g/ug/g and -97 g/ug/g urinary Cd, respectively). Associations of similar magnitude were observed after adjustment for various maternal factors. No significant associations were observed with infant size measures or with measures of Cd in the third trimester.

Conclusions: Our detailed study suggests that the first trimester is particularly critical window of susceptibility to sex-specific effects of Cd on size parameters at birth, with some effects persisting to six months of age. These compelling sex-dependent effects on HC and body weight warrant future studies examining longer-term health effects of pregnancy-related Cd exposures.
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http://dx.doi.org/10.1016/j.jtemb.2021.126823DOI Listing
July 2021

Optimization of Task Allocation for Collaborative Brain-Computer Interface Based on Motor Imagery.

Front Neurosci 2021 2;15:683784. Epub 2021 Jul 2.

Neural Engineering & Rehabilitation Laboratory, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.

Objective: Collaborative brain-computer interfaces (cBCIs) can make the BCI output more credible by jointly decoding concurrent brain signals from multiple collaborators. Current cBCI systems usually require all collaborators to execute the same mental tasks (common-work strategy). However, it is still unclear whether the system performance will be improved by assigning different tasks to collaborators (division-of-work strategy) while keeping the total tasks unchanged. Therefore, we studied a task allocation scheme of division-of-work and compared the corresponding classification accuracies with common-work strategy's.

Approach: This study developed an electroencephalograph (EEG)-based cBCI which had six instructions related to six different motor imagery tasks (MI-cBCI), respectively. For the common-work strategy, all five subjects as a group had the same whole instruction set and they were required to conduct the same instruction at a time. For the division-of-work strategy, every subject's instruction set was a subset of the whole one and different from each other. However, their union set was equal to the whole set. Based on the number of instructions in a subset, we divided the division-of-work strategy into four types, called "2 Tasks" … "5 Tasks." To verify the effectiveness of these strategies, we employed EEG data collected from 19 subjects who independently performed six types of MI tasks to conduct the pseudo-online classification of MI-cBCI.

Main Results: Taking the number of tasks performed by one collaborator as the horizontal axis (two to six), the classification accuracy curve of MI-cBCI was mountain-like. The curve reached its peak at "4 Tasks," which means each subset contained four instructions. It outperformed the common-work strategy ("6 Tasks") in classification accuracy ( vs. 58.53 ± 4.36%).

Significance: The results demonstrate that our proposed task allocation strategy effectively enhanced the cBCI classification performance and reduced the individual workload.
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http://dx.doi.org/10.3389/fnins.2021.683784DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282908PMC
July 2021

Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance.

Phys Imaging Radiat Oncol 2021 Apr 16;18:34-40. Epub 2021 Apr 16.

Department of Human Oncology, University of Wisconsin, Madison, Madison, WI 53792, United States.

Purpose: Emerging evidence suggests cardiac substructures are highly radiosensitive during radiation therapy for cancer treatment. However, variability in substructure position after tumor localization has not been well characterized. This study quantifies inter-fraction displacement and planning organ at risk volumes (PRVs) of substructures by leveraging the excellent soft tissue contrast of magnetic resonance imaging (MRI).

Methods: Eighteen retrospectively evaluated patients underwent radiotherapy for intrathoracic tumors with a 0.35 T MRI-guided linear accelerator. Imaging was acquired at a 17-25 s breath-hold (resolution 1.5 × 1.5 × 3 mm). Three to four daily MRIs per patient (n = 71) were rigidly registered to the planning MRI-simulation based on tumor matching. Deep learning or atlas-based segmentation propagated 13 substructures (e.g., chambers, coronary arteries, great vessels) to daily MRIs and were verified by two radiation oncologists. Daily centroid displacements from MRI-simulation were quantified and PRVs were calculated.

Results: Across substructures, inter-fraction displacements for 14% in the left-right, 18% in the anterior-posterior, and 21% of fractions in the superior-inferior were > 5 mm. Due to lack of breath-hold compliance, ~4% of all structures shifted > 10 mm in any axis. For the chambers, median displacements were 1.8, 1.9, and 2.2 mm in the left-right, anterior-posterior, and superior-inferior axis, respectively. Great vessels demonstrated larger displacements (> 3 mm) in the superior-inferior axis (43% of shifts) and were only 25% (left-right) and 29% (anterior-posterior) elsewhere. PRVs from 3 to 5 mm were determined as anisotropic substructure-specific margins.

Conclusions: This exploratory work derived substructure-specific safety margins to ensure highly effective cardiac sparing. Findings require validation in a larger cohort for robust margin derivation and for applications in prospective clinical trials.
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http://dx.doi.org/10.1016/j.phro.2021.03.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254195PMC
April 2021

Modulation of Sustained Attention by Theta-tACS over the Lateral and Medial Frontal Cortices.

Neural Plast 2021 19;2021:5573471. Epub 2021 Jun 19.

School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China.

Theta oscillations over the posterior medial frontal cortex (pMFC) and lateral prefrontal cortex (LPFC) play vital roles in sustained attention. Specifically, pMFC power and pMFC-LPFC synchronization correlate with cognitive control in sustained-attention-related tasks, but the causal relationships remain unknown. In the present study, we first analyzed the correlation between EEG theta oscillations (characterized by time-frequency power and phase-based connectivity) and the level of sustained attention (Experiment 1) and then utilized transcranial alternating current stimulation (tACS) to modulate theta oscillations and in turn observed its effects on sustained attention (Experiment 2). In Experiment 1, two time-frequency regions of interest (ROIs) were determined, in which high/low time-frequency power and high/low phase-based connectivity corresponded to high/low-level sustained attention. In Experiment 2, time-frequency power and phase-based connectivity of theta oscillations were compared between the sham and tACS groups within the time-frequency ROIs determined in Experiment 1. Results showed that phase-based connectivity between pMFC and LPFC significantly decreased in the tACS group compared with the sham group during the first five minutes of the poststimulation period. Moreover, a marginal trend existed that sustained attention was downregulated by tACS in the same time interval, suggesting that theta phase synchronization between pMFC and LPFC may play a causal role in sustained attention.
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http://dx.doi.org/10.1155/2021/5573471DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238627PMC
June 2021

A Minireview on Temperature Dependent Protein Conformational Sampling.

Authors:
Ming Dong

Protein J 2021 Aug 28;40(4):545-553. Epub 2021 Jun 28.

Department of Chemistry, North Carolina Agricultural and Technical State University, 1601 E Market Street, Greensboro, NC, 27410, USA.

In this minireview we discuss the role of the more subtle conformational change-protein conformational sampling and connect it to the classic relationship of protein structure and function. The theory of pre-existing functional states of protein are discussed in context of alternate protein conformational sampling. Last, we discuss how temperature, ligand binding and mutations affect the protein conformational sampling mode which is linked to the protein function regulation. The review includes several protein systems that showed temperature dependent protein conformational sampling. We also specifically included two enzyme systems, thermophilic alcohol dehydrogenase (ht-ADH) and thermolysin which we previously studied when discussing temperature dependent protein conformational sampling.
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http://dx.doi.org/10.1007/s10930-021-10012-xDOI Listing
August 2021

[Classification algorithms of error-related potentials in brain-computer interface].

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2021 Jun;38(3):463-472

Academy of Medical Engineering and Translational Medicine. Tianjin University, Tianjin 300072, P.R.China.

Error self-detection based on error-related potentials (ErrP) is promising to improve the practicability of brain-computer interface systems. But the single trial recognition of ErrP is still a challenge that hinters the development of this technology. To assess the performance of different algorithms on decoding ErrP, this paper test four kinds of linear discriminant analysis algorithms, two kinds of support vector machines, logistic regression, and discriminative canonical pattern matching (DCPM) on two open accessed datasets. All algorithms were evaluated by their classification accuracies and their generalization ability on different sizes of training sets. The study results show that DCPM has the best performance. This study shows a comprehensive comparison of different algorithms on ErrP classification, which could give guidance for the selection of ErrP algorithm.
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http://dx.doi.org/10.7507/1001-5515.202012013DOI Listing
June 2021

[Research progress and prospect of collaborative brain-computer interface for group brain collaboration].

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2021 Jun;38(3):409-416

Biomedical Engineering, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, P.R.China.

As the most common active brain-computer interaction paradigm, motor imagery brain-computer interface (MI-BCI) suffers from the bottleneck problems of small instruction set and low accuracy, and its information transmission rate (ITR) and practical application are severely limited. In this study, we designed 6-class imagination actions, collected electroencephalogram (EEG) signals from 19 subjects, and studied the effect of collaborative brain-computer interface (cBCI) collaboration strategy on MI-BCI classification performance, the effects of changes in different group sizes and fusion strategies on group multi-classification performance are compared. The results showed that the most suitable group size was 4 people, and the best fusion strategy was decision fusion. In this condition, the classification accuracy of the group reached 77%, which was higher than that of the feature fusion strategy under the same group size (77.31% 56.34%), and was significantly higher than that of the average single user (77.31% 44.90%). The research in this paper proves that the cBCI collaboration strategy can effectively improve the MI-BCI classification performance, which lays the foundation for MI-cBCI research and its future application.
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http://dx.doi.org/10.7507/1001-5515.202007059DOI Listing
June 2021

A Systematic Analysis of Hand Movement Functionality: Qualitative Classification and Quantitative Investigation of Hand Grasp Behavior.

Front Neurorobot 2021 7;15:658075. Epub 2021 Jun 7.

Academy of Medical Engineering and Translational Medicine (AMT), Tianjin University, Tianjin, China.

Understanding human hand movement functionality is fundamental in neuroscience, robotics, prosthetics, and rehabilitation. People are used to investigate movement functionality separately from qualitative or quantitative perspectives. However, it is still limited to providing an integral framework from both perspectives in a logical manner. In this paper, we provide a systematic framework to qualitatively classify hand movement functionality, build prehensile taxonomy to explore the general influence factors of human prehension, and accordingly design a behavioral experiment to quantitatively understand the hand grasp. In qualitative analysis, two facts are explicitly proposed: (1) the arm and wrist make a vital contribution to hand movement functionality; (2) the relative position (relative position in this paper is defined as the distance between the center of the human wrist and the object center of gravity) is a general influence factor significantly impacting human prehension. In quantitative analysis, the significant influence of three factors, object shape, size, and relative position, is quantitatively demonstrated. Simultaneously considering the impact of relative position, object shape, and size, the prehensile taxonomy and behavioral experiment results presented here should be more representative and complete to understand human grasp functionality. The systematic framework presented here is general and applicable to other body parts, such as wrist, arm, etc. Finally, many potential applications and the limitations are clarified.
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http://dx.doi.org/10.3389/fnbot.2021.658075DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216684PMC
June 2021

EEG-controlled functional electrical stimulation rehabilitation for chronic stroke: system design and clinical application.

Front Med 2021 Jun 22. Epub 2021 Jun 22.

Neural Engineering & Rehabilitation Laboratory, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, 300072, China.

Stroke is one of the most serious diseases that threaten human life and health. It is a major cause of death and disability in the clinic. New strategies for motor rehabilitation after stroke are undergoing exploration. We aimed to develop a novel artificial neural rehabilitation system, which integrates brain-computer interface (BCI) and functional electrical stimulation (FES) technologies, for limb motor function recovery after stroke. We conducted clinical trials (including controlled trials) in 32 patients with chronic stroke. Patients were randomly divided into the BCI-FES group and the neuromuscular electrical stimulation (NMES) group. The changes in outcome measures during intervention were compared between groups, and the trends of ERD values based on EEG were analyzed for BCI-FES group. Results showed that the increase in Fugl Meyer Assessment of the Upper Extremity (FMA-UE) and Kendall Manual Muscle Testing (Kendall MMT) scores of the BCI-FES group was significantly higher than that in the sham group, which indicated the practicality and superiority of the BCI-FES system in clinical practice. The change in the laterality coefficient (LC) values based on μ-ERD (ΔLC) had high significant positive correlation with the change in FMA-UE(r = 0.6093, P = 0.012), which provides theoretical basis for exploring novel objective evaluation methods.
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http://dx.doi.org/10.1007/s11684-020-0794-5DOI Listing
June 2021

A SARS-CoV-2 spike ferritin nanoparticle vaccine protects against heterologous challenge with B.1.1.7 and B.1.351 virus variants in Syrian golden hamsters.

bioRxiv 2021 Jun 16. Epub 2021 Jun 16.

The emergence of SARS-CoV-2 variants of concern (VOC) requires adequate coverage of vaccine protection. We evaluated whether a spike ferritin nanoparticle vaccine (SpFN), adjuvanted with the Army Liposomal Formulation QS21 (ALFQ), conferred protection against the B.1.1.7 and B.1.351 VOCs in Syrian golden hamsters. SpFN-ALFQ was administered as either single or double-vaccination (0 and 4 week) regimens, using a high (10 μg) or low (0.2 μg) immunogen dose. Animals were intranasally challenged at week 11. Binding antibody responses were comparable between high- and low-dose groups. Neutralizing antibody titers were equivalent against WA1, B.1.1.7, and B.1.351 variants following two high dose two vaccinations. SpFN-ALFQ vaccination protected against SARS-CoV-2-induced disease and viral replication following intranasal B.1.1.7 or B.1.351 challenge, as evidenced by reduced weight loss, lung pathology, and lung and nasal turbinate viral burden. These data support the development of SpFN-ALFQ as a broadly protective, next-generation SARS-CoV-2 vaccine.
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http://dx.doi.org/10.1101/2021.06.16.448525DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219092PMC
June 2021

Comparison effects of chronic sleep deprivation on juvenile and young adult mice.

J Sleep Res 2021 Jun 16:e13399. Epub 2021 Jun 16.

Institute of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.

Sleeplessness leads to a spectrum of neuropsychiatric disorders, affecting both juveniles and young adults. Studies have shown different sleep patterns at different stages of development. However, the molecular mechanisms underlying the effects of the same chronic sleep deprivation (CSD) on behaviours of juveniles and young adults remain elusive. Here, we aimed to evaluate the effects of CSD (6 days, 19 h per day) on anxiety-like behaviour, cognitive performance and molecular alterations in juvenile and young adult mice. Change in body weight suggested impaired physical development in CSD animals, specifically juveniles gaining weight at a lower rate and young adults losing weight. Behavioural performance indicated that CSD had little effect on spatial memory, but induced analogous anxiety-like phenotypes in both juveniles and young adults, as evidenced by no significant difference in the Y-maze experiment (Y-M) or the Morris water maze experiment (MWM), as well as the decreased open-arm distance percentage in the elevated plus maze experiment (EPM). In addition, CSD reduced the N-methyl-D-aspartic receptor subunit 2B (NR2B) and postsynaptic density protein 95 (PSD95) levels in juveniles, but these were increased in young adults. In conclusion, our results suggested that although CSD resulted in analogous anxiety-like behaviours in both juvenile and young adult mice, the underlying mechanisms might be different, which was indicated by the opposite change of synaptic proteins under CSD. These findings may help to better understand the important role of sleep and have constructive significance for human health.
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http://dx.doi.org/10.1111/jsr.13399DOI Listing
June 2021

Detection of fixation points using a small visual landmark for brain-computer interfaces.

J Neural Eng 2021 07 5;18(4). Epub 2021 Jul 5.

The Laboratory of Neural Engineering & Rehabilitation, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China.

The speed of visual brain-computer interfaces (v-BCIs) has been greatly improved in recent years. However, the traditional v-BCI paradigms require users to directly gaze at the intensive flickering items, which would cause severe problems such as visual fatigue and excessive visual resource consumption in practical applications. Therefore, it is imperative to develop a user-friendly v-BCI.According to the retina-cortical relationship, this study developed a novel BCI paradigm to detect the fixation point of eyes using a small visual stimulus that subtended only 0.6° in visual angle and was out of the central visual field. Specifically, the visual stimulus was treated as a landmark to judge the eccentricity and polar angle of the fixation point. Sixteen different fixation points were selected around the visual landmark, i.e. different combinations of two eccentricities (2° and 4°) and eight polar angles (0,π4,π2,3π4,π,5π4,3π2and7π4). Twelve subjects participated in this study, and they were asked to gaze at one out of the 16 points for each trial. A multi-class discriminative canonical pattern matching (Multi-DCPM) algorithm was proposed to decode the user's fixation point.We found the visual stimulation landmark elicited different spatial event-related potential patterns for different fixation points. Multi-DCPM could achieve an average accuracy of 66.2% with a standard deviation of 15.8% for the classification of the sixteen fixation points, which was significantly higher than traditional algorithms (p⩽0.001). Experimental results of this study demonstrate the feasibility of using a small visual stimulus as a landmark to track the relative position of the fixation point.The proposed new paradigm provides a potential approach to alleviate the problem of irritating stimuli in v-BCIs, which can broaden the applications of BCIs.
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http://dx.doi.org/10.1088/1741-2552/ac0b51DOI Listing
July 2021

Emotional Arousal and Valence Jointly Modulate the Auditory Response: A 40-Hz ASSR Study.

IEEE Trans Neural Syst Rehabil Eng 2021 24;29:1150-1157. Epub 2021 Jun 24.

Emotion is defined as a response to external stimuli and internal mental representations. It has been characterized as a multidimensional concept, primarily comprising two dimensions: valence and arousal. Existing studies have demonstrated that emotional experience exerts a powerful impact on auditory processing in terms of valence. However, it has also been shown that while negative emotion can improve auditory perception in healthy subjects, patients with depression show deficits in auditory perception. We thus speculated that both arousal and valence jointly modulate auditory perception. To examine the emotion-driven effects on the auditory response, we induced positive, negative, and neutral emotional states in healthy subjects and collected auditory steady-state response (ASSR) evoked by a 40-Hz chirp sound. We calculated peak-to-peak amplitude (PPA) and event-related spectral perturbation (ERSP) of evoked ASSRs and observed that the positive emotions significantly enhanced brain responses to auditory stimuli (p < 0.001), but that ASSRs in a negative state were not significantly enhanced compared with the neutral state. Subsequently, regression analysis showed a significant positive multiple linear relationship between the PPA and ratings of two emotional dimensions, indicating that arousal and valence jointly regulated the auditory cortex's synchronous oscillation, rather than the valence in isolation, offering the potential to clarify the conflicting results surrounding the role of negative emotions in auditory responses. Because depression is generally characterized by low arousal and low valence in actual life, whereas the negative emotion evoked under laboratory conditions is always with low valence but high arousal.
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http://dx.doi.org/10.1109/TNSRE.2021.3088257DOI Listing
June 2021

Living Rat SSVEP Mapping with Acoustoelectric Brain Imaging.

IEEE Trans Biomed Eng 2021 Jun 8;PP. Epub 2021 Jun 8.

Acoustoelectric Brain Imaging (ABI) is a potential method for mapping brain electrical activity with high spatial resolution (millimeter). To resolve the key issue for eventual realization of ABI, testing the hypothesis that recorded acoustoelectric (AE) signal can be used to decode intrinsic brain electrical activity, the experiment of living rat SSVEP measurement with ABI is implemented.

Method: A 1-MHz ultrasound transducer is focused on the visual cortex of anesthetized rat. With visual stimulus, the electroencephalogram and AE signal are simultaneously recorded with Ag electrode. Besides, with FUS transducer scanning at the visual cortex, corresponding AE signals at different spatial positions are decoded and imaged.

Results: Consistent with that of direct measurement of SSVEP, the decoded AE signal presents a clear event-related spectral perturbation (ERSP). And, the decoded AE signal is of high amplitude response at the base and harmonics of the visual stimulus frequency. Whats more, for timing signal, a significant positive amplitude correlation is observed between decoded AE signal and simultaneously measured SSVEP. In addition, the mean SNRs of SSVEP and decoded AE signal are both significantly higher than that of background EEG. Finally, with one fixed recording electrode, the active area with an inner diameter of 1mm is located within the 4mm4mm measurement region.

Conclusion: These experimental results demonstrate that the millimeter-level spatial resolution SSVEP measurement of living rat is achieved through ABI for the first time.

Significance: This study confirms that ABI should shed light on spatiotemporal resolution neuroimaging.
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http://dx.doi.org/10.1109/TBME.2021.3087177DOI Listing
June 2021

Enhancement for P300-speller classification using multi-window discriminative canonical pattern matching.

J Neural Eng 2021 06 4;18(4). Epub 2021 Jun 4.

College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China.

P300s are one of the most studied event-related potentials (ERPs), which have been widely used for brain-computer interfaces (BCIs). Thus, fast and accurate recognition of P300s is an important issue for BCI study. Recently, there emerges a lot of novel classification algorithms for P300-speller. Among them, discriminative canonical pattern matching (DCPM) has been proven to work effectively, in which discriminative spatial pattern (DSP) filter can significantly enhance the spatial features of P300s. However, the pattern of ERPs in space varies with time, which was not taken into consideration in the traditional DCPM algorithm.In this study, we developed an advanced version of DCPM, i.e. multi-window DCPM, which contained a series of time-dependent DSP filters to fine-tune the extraction of spatial ERP features. To verify its effectiveness, 25 subjects were recruited and they were asked to conduct the typical P300-speller experiment.As a result, multi-window DCPM achieved the character recognition accuracy of 91.84% with only five training characters, which was significantly better than the traditional DCPM algorithm. Furthermore, it was also compared with eight other popular methods, including SWLDA, SKLDA, STDA, BLDA, xDAWN, HDCA, sHDCA and EEGNet. The results showed multi-window DCPM preformed the best, especially using a small calibration dataset. The proposed algorithm was applied to the BCI Controlled Robot Contest of P300 paradigm in 2019 World Robot Conference, and won the first place.These results demonstrate that multi-window DCPM is a promising method for improving the performance and enhancing the practicability of P300-speller.
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http://dx.doi.org/10.1088/1741-2552/ac028bDOI Listing
June 2021

Attention-Guided Generative Adversarial Network to Address Atypical Anatomy in Synthetic CT Generation.

2020 IEEE 21st Int Conf Inf Reuse Integr Data Sci (2020) 2020 Aug 10;2020:188-193. Epub 2020 Sep 10.

Henry Ford Health System, Department of Radiation Oncology, Detroit, MI 48202, USA.

Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy. However, developing class solutions for medical images that contain atypical anatomy remains a major limitation. In this paper, we propose a novel spatial attention-guided generative adversarial network (attention-GAN) model to generate accurate synCTs using T1-weighted MRI images as the input to address atypical anatomy. Experimental results on fifteen brain cancer patients show that attention-GAN outperformed existing synCT models and achieved an average MAE of 85.223±12.08, 232.41±60.86, 246.38±42.67 Hounsfield units between synCT and CT-SIM across the entire head, bone and air regions, respectively. Qualitative analysis shows that attention-GAN has the ability to use spatially focused areas to better handle outliers, areas with complex anatomy or post-surgical regions, and thus offer strong potential for supporting near real-time MR-only treatment planning.
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http://dx.doi.org/10.1109/iri49571.2020.00034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174818PMC
August 2020

Altered spontaneous neural activity in the precuneus, middle and superior frontal gyri, and hippocampus in college students with subclinical depression.

BMC Psychiatry 2021 06 1;21(1):280. Epub 2021 Jun 1.

Department of Biomedical Engineering, Lab of Neural Engineering & Rehabilitation, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.

Background: Subclinical depression (ScD) is a prevalent condition associated with relatively mild depressive states, and it poses a high risk of developing into major depressive disorder (MDD). However, the neural pathology of ScD is still largely unknown. Identifying the spontaneous neural activity involved in ScD may help clarify risk factors for MDD and explore treatment strategies for mild stages of depression.

Methods: A total of 34 ScD subjects and 40 age-, sex-, and education-matched healthy controls were screened from 1105 college students. The amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) of resting-state fMRI were calculated to reveal neural activity. Strict statistical strategies, including Gaussian random field (GRF), false discovery rate (FDR), and permutation test (PT) with threshold-free cluster enhancement (TFCE), were conducted. Based on the altered ALFF and ReHo, resting-state functional connectivity (RSFC) was further analyzed using a seed-based approach.

Results: The right precuneus and left middle frontal gyrus (MFG) both showed significantly increased ALFF and ReHo in ScD subjects. Moreover, the left hippocampus and superior frontal gyrus (SFG) showed decreased ALFF and increased ReHo, respectively. In addition, ScD subjects showed increased RSFC between MFG and hippocampus compared to healthy controls, and significant positive correlation was found between the Beck Depression Inventory-II (BDI-II) score and RSFC from MFG to hippocampus in ScD group.

Conclusion: Spontaneous neural activities in the right precuneus, left MFG, SFG, and hippocampus were altered in ScD subjects. Functional alterations in these dorsolateral prefrontal cortex and default mode network regions are largely related to abnormal emotional processing in ScD, and indicate strong associations with brain impairments in MDD, which provide insight into potential pathophysiology mechanisms of subclinical depression.
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http://dx.doi.org/10.1186/s12888-021-03292-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167968PMC
June 2021
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