A5103059171- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- NMR spectroscopy and applications
- Gut microbiota and health
- Aortic Disease and Treatment Approaches
- Spinal Cord Injury Research
- Image and Signal Denoising Methods
- Medical Image Segmentation Techniques
- Stroke Rehabilitation and Recovery
- RNA Research and Splicing
- Integrated Energy Systems Optimization
- Genetic Syndromes and Imprinting
- Cerebral Palsy and Movement Disorders
- Optical Imaging and Spectroscopy Techniques
- Traumatic Brain Injury and Neurovascular Disturbances
- Hydrogen's biological and therapeutic effects
- Photoacoustic and Ultrasonic Imaging
- Gaze Tracking and Assistive Technology
- Cardiac Ischemia and Reperfusion
- Advanced Technologies in Various Fields
- Exercise and Physiological Responses
- Music Therapy and Health
- Bone Metabolism and Diseases
- Advanced Mathematical Modeling in Engineering
- Cardiomyopathy and Myosin Studies
China Rehabilitation Research Center
2023-2025
Capital Medical University
2023-2025
Chinese Institute for Brain Research
2023-2025
Zhejiang Chinese Medical University
2025
Shenyang University of Technology
2024
Weifang Medical University
2024
Yanshan University
2024
Northeastern University
2024
Tsinghua University
2024
Anhui University of Finance and Economics
2023
Abstract Spinal cord injury (SCI) can reshape gut microbial composition, significantly affecting clinical outcomes in SCI patients. However, mechanisms regarding gut–brain interactions and their implications have not been elucidated. We hypothesized that short-chain fatty acids (SCFAs), intestinal bioactive metabolites, may affect the axis enhance functional recovery a mouse model of SCI. enrolled 59 patients 27 healthy control subjects collected samples. Thereafter, microbiota SCFAs were...
Abstract Diffusion magnetic resonance imaging is an important tool for mapping tissue microstructure and structural connectivity non‐invasively in the vivo human brain. Numerous diffusion signal models are proposed to quantify microstructural properties. Nonetheless, accurate estimation of model parameters computationally expensive impeded by image noise. Supervised deep learning‐based approaches exhibit efficiency superior performance but require additional training data may be not...
Atopic dermatitis (AD) is a common inflammatory skin condition characterized by erythema and pruritus. Its precise pathogenesis remains unclear, though factors such as genetic predisposition, autoantigen response, allergen exposure, infections, barrier dysfunction are involved. Research suggests correlation between AD mitochondrial dysfunction, well oxidative stress in tissues. Skin sample datasets related to (GSE36842, GSE120721, GSE16161, GSE121212) were retrieved from the GEO database....
Accumulating data suggest that remodeling aged gut microbiota improves aging-related imbalance in intestinal homeostasis. However, evidence favor of the beneficial effect on stress and immune responses during aging is scarce. The current study revealed old mice presented impaired barrier integrity. Transcriptome sequencing coupled with bioinformatics analysis altered gene expression profiles colon mesenteric lymph nodes, which are involved mainly responses, respectively. Notably, was closely...
Aging is a complex, time-dependent biological process that involves decline of overall function. Over the past decade, field intestinal microbiota associated with aging has received considerable attention. However, there limited information surrounding microbiota-gut-brain axis (MGBA) to further reveal mechanism aging.
The objective of this study is to evaluate the efficacy deep learning (DL) techniques in improving quality diffusion MRI (dMRI) data clinical applications. aims determine whether use artificial intelligence (AI) methods medical images may result loss critical information and/or appearance false information. To assess this, focus was on angular resolution dMRI and a trial conducted migraine, specifically between episodic chronic migraine patients. number gradient directions had an impact...
The expression of large conductance calcium-activated potassium channels (BK channels) in adipose tissue has been identified for years. BK channel deletion can improve metabolism vivo, but the relative mechanisms remain unclear. Here, we examined effects on differentiation adipose-derived stem cells (ADSCs) and related mechanisms. BKα β1 subunits were expressed adipocytes. We found that both KCNMA1 gene, encoding pore forming α subunit channels, inhibitor paxilline increased key genes...
Abstract The interaction between viral components and cellular proteins plays a crucial role in replication. In previous study, we showed that the 3′—untranslated region (3′—UTR) is an essential element for replication of duck hepatitis A virus type 1 (DHAV-1). However, underlying mechanism still unclear. To gain deeper understanding this mechanism, used RNA pull-down matrix-assisted laser desorption/ionization time-of-flight mass spectrometry assay to identify new host factors interact with...
In recent years, there has been a significant growth in research on emotion expression the field of human-robot interaction. process interaction, effect robot's emotional determines user's experience and acceptance. Gaze is widely accepted as an important media to express emotions human-human But it found that users have difficulty effectively recognizing such happiness anger expressed by animaloid robots use eye contact individually. addition, real effective nonverbal includes not only but...
The accurate estimation of diffusion model parameter values using non-linear optimization is time-consuming. Supervised learning methods neural networks (NNs) are faster and more but require external ground-truth data for training. A unified self-supervised learning-based method DIMOND proposed. maps to NNs, synthesizes the input from predictions forward model, minimizes difference between raw synthetic data. outperforms conventional ordinary least square regression (OLS) has a high...
Motivation: MRI with high resolution and/or acceleration factor suffers from intrinsic low signal-to-noise ratio. Supervised learning-based denoising significantly improves image quality, but requires high-SNR data as training targets. Goal(s): To denoise images using noisy repetitions without additional acquisition. Approach: Noise2Average trains CNN to map each its residual compared the average of all at iteration 1 and denoised k-1 k. The opposite phase-encoding directions EPI or...
Motivation: gSlider utilizes radio-frequency encoding to acquire high and isotropic resolution brain diffusion-MRI with SNR. However, this comes at the cost of prolonged acquisition time, which also increases sensitivity motion. Goal(s): This work proposes Network (gNET) accelerate from acquisitions jointly subsampled RF- q-space. Approach: The self-supervised model was trained tested on a 1mm3 BUDA-gSlider dataset (Tacq = 32 min). FSL DIMOND were used estimate diffusion parameters. Results:...
Motivation: Diffusion modeling is an important tool for quantifying microstructure properties from diffusion data, but its optimization computationaly expensive. Goal(s): To achieve rapid model parameter estimation while outperforming conventional methods. Approach: DIMOND employs a neural network (NN) to map input data parameters and optimizes NN by minimizing the difference between synthetic generated via parametrized outputs. Results: outperforms methods fitting kurtosis NODDI models in...
Motivation: Accurate estimation of relaxation parameters using MRF requires lengthy acquisitions as it benefits from having multiple spiral interleaves to boost the data quality. Goal(s): We aim reduce acquisition time by denoising highly under-sampled while retaining fidelity estimated parameter maps. Approach: An unsupervised convolutional neural network called DAES is proposed. It combines Denoising Auto-coder (DAE) with subspace modeling, taking advantage both framework and Bloch...
Currently, financial derivatives are important instruments. Financial can provide investors with the opportunity to hedge, speculate, and arbitrage. But due impact of COVID-19. The performance has changed dramatically compared pre-epidemic period. This dissertation focuses on three major which include futures, options, credit under phenotypes these analyzed separately. In this paper, we examine extensive literature demonstrate changes in during By collecting a large amount data about...
The requirement for high-SNR reference data reduces the feasibility of supervised deep learning-based denoising. Noise2Noise addresses this challenge by learning to map one noisy image another repetition but suffers from blurring resulting imperfect alignment and intensity mismatch empirical MRI data. A novel approach, Noise2Average, is proposed improve Noise2Noise, which employs residual preserve sharpness transfer subject-specific training. Noise2Average demonstrated effective in denoising...
People’s spending patterns are changing due to the economy’s quick expansion, and one such change is advent of e-commerce, which has drawn a lot investors. This article uses JD as an example study fundamental elements its business model assess evaluate it from standpoint value creation.
Aims: In order to study the future trend of Anhui residents’ consumption level and predict residents in next three years (2022-2024), this paper constructs a combination prediction model based on induced ordered weighted averaging (IOWA) operator.
 Study Design: This selects national resident province from 2000 2021, which covers period 21 years. Based data, an IOWA operator is constructed using multiple regression model, ARIMA (2,2,0) machine learning decision tree model. qualitative...