Publications by authors named "Shuang Ding"

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder characterized by dysplasia in early life. Psychoradiology studies have suggested that mental and behavioral deficits in individuals with PWS are linked to abnormalities in brain structural and functional networks. However, little is known about changes in network-based structural-functional coupling and structural/functional topological properties and their correlations with developmental scales in children with PWS.

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Background: Little is known about the precise impaired patterns of white matter (WM) fiber tracts in preschool-aged children with autism spectrum disorder (ASD). Thus, we used diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ) to explore the changes in WM fiber tracts in preschool-aged children with ASD and its correlation with the severity of clinical manifestations.

Methods: A total of 43 pediatric ASD and 42 age- and sex-matched typical developing children were examined with DTI.

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Myocardial infarction, a type of coronary artery disease, results from various factors such as genetic predisposition, lifestyle choices, and immune system regulation. The exact causal links between immune cells, plasma metabolites, and myocardial infarction are currently unclear. Therefore, our study employed the Mendelian randomization approach to explore these potential causal relationships.

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Jie-gu capsules are widely used for the treatment of fractures in China. However, the core active pharmaceutical ingredients of Jie-gu capsules and the potential mechanisms for treating fractures remain unclear. This study aims to preliminarily elucidate the potential mechanisms of Jie-gu capsules in the treatment of fractures through network pharmacology and mendelian randomization methods.

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To alleviate the impact of atmospheric turbulence on receiver carrier recovery in free-space optical communication, this study introduces a novel frame synchronization and carrier recovery method. This method employs a blend of pseudorandom sequences and specific cyclic quadrature phase shift keying (QPSK) training sequences, facilitating frame synchronization and frequency offset (FO) estimation. The research designs a time-series metric curve to counteract the effect of side peaks, enhancing the accuracy of frequency offset estimation via QPSK spectrum features.

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  • - The study aimed to predict bone marrow metastasis in neuroblastoma by analyzing radiomics features from contrast-enhanced CT scans using machine learning techniques.
  • - A total of 345 patients were examined, and after analyzing 1409 features, a predictive model was created using 16 key features, primarily related to texture, achieving high accuracy and sensitivity in identifying metastasis.
  • - The findings suggest that specific radiomics features from CT images are linked to bone marrow metastasis in neuroblastoma, indicating their potential as new biomarkers for diagnosis.
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  • The study explores how mutations in SARS-CoV-2 challenge efforts to reduce the virus's infectivity and identifies host factors that could serve as new antiviral drug targets.
  • Researchers found that SARS-CoV-2 reduces the stability and translation of ACTN4 mRNA, which then inhibits ACTN4 expression, affecting viral replication.
  • Two compounds, YS-49 and demethyl-coclaurine, were identified as effective in reducing SARS-CoV-2 infection in lab cells and animal models, highlighting ACTN4's significant role and potential for drug development.
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Objective: To investigate the impact and potential mechanisms of serum extracellular nano-vesicles (sEVs) miR-412-3p released from sub-centimeter lung nodules with a diameter of ⩽ 10 mm on the malignant biological function of micro-nodular lung cancer (mnLC).

Methods: A total of 87 participants were included and divided into a mnLC group (n= 30), a benign lung nodule (BLN) group (n= 27), and a healthy people control group (n= 30). Transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and Western blot (WB) were used to measure the morphological characteristics and surface markers of sEVs.

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Accurately predicting freeway accident severity is crucial for accident prevention, road safety, and emergency rescue services in intelligent freeway systems. However, current research lacks the required precision, hindering the effective implementation of freeway rescue. In this paper, we efficiently address this challenge by categorizing influencing factors into two levels: human and non-human, further subdivided into 6 and 36 categories, respectively.

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  • - The study focuses on Neuregulin 1 (NRG1), a gene linked to schizophrenia, examining how the rs6982890 SNP affects psychotic symptoms and cognitive functions in patients.
  • - Researchers analyzed data from over 1,300 schizophrenia patients and 871 healthy controls in Northern China, measuring NRG1 levels and correlating them with clinical symptoms before and after 8 weeks of treatment.
  • - Results showed that rs6982890 is associated with schizophrenia, revealing that patients with the CC genotype had significantly improved NRG1 levels and symptoms after treatment, while those with the CT genotype did not show significant changes.
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Investigational therapeutics that target toxic species of α-synuclein (αSyn) aim to slow down or halt disease progression in patients with Parkinson's disease (PD). Here this 44-week, randomized, placebo-controlled, double-blind, single-center phase 1 study investigated safety, tolerability and immunogenicity of UB-312, an active immunotherapeutic targeting pathological αSyn, in patients with PD. The primary outcome measures were adverse event frequency and change in anti-αSyn antibody titers in blood and cerebrospinal fluid (CSF).

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Objective: In this study, we performed RNA sequencing (RNA-seq) on the abdominal aorta tissue of New Zealand rabbits and investigated the potential association of lncRNA TCONS_02443383 with the development of AS through bioinformatics analysis of the sequencing data. The obtained results were further validated using quantitative real-time polymerase chain reaction (qRT-PCR).

Method: We induced an AS model in New Zealand rabbits by causing balloon injury to the abdominal aorta vascular wall and administering a high-fat diet.

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Objective: To investigate the alteration in structural and functional connectivity networks (SCN and FCN) as well as their coupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and determine if these properties could serve as potential biomarkers for the disease.

Materials And Methods: In total of 32 children with MOGAD and 30 age- and sex-matched healthy controls (HC) were employed to construct the SCN and FCN, respectively. The graph-theoretical analyses of the global properties, node properties of the 90 brain nodes, and the structural-functional connectivity (SC-FC) coupling of the two networks were performed.

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Background: Coronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment.

Methods: A total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study.

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Increasing evidences suggest that the methyltransferase NSUN2 catalyzes 5-methylcytosine (m5C) modifications on viral RNAs, which are essential for the replication of various viruses. Despite the function of m5C deposition is well characterized, other potential roles of NSUN2 in regulating viral replication remain largely unknown. In this study, the m5C modified residues catalyzed by NSUN2 on enterovirus 71 (EV71) RNAs were mapped.

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Objective: To observe the effect of acupotomy on heat shock protein A family member 5 (HSPA5)/glutathione peroxidase 4 (GPX4) signaling pathway in the chondrocytes of the rabbits with knee osteoarthritis (KOA) and explore the mechanism of acupotomy on chondrocyte ferroptosis in KOA.

Methods: Twenty-seven New Zealand rabbits were randomly divided into a normal group, a model group and an acupotomy group, with 9 rabbits in each group. The left hind limb was fixed by the modified Videman method for 6 weeks to establish KOA model.

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Purpose: Chronic hepatitis B virus (HBV) infection is the primary risk factor for the malignant progression of hepatocellular carcinoma (HCC). It has been reported that HBV X protein (HBx) possesses oncogenic properties, promoting hepatocarcinogenesis and chemoresistance. However, the detailed molecular mechanisms are not fully understood.

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Background: Rheumatoid arthritis is a systemic inflammatory autoimmune disease that severely impacts physical and mental health. Autophagy is a cellular process involving the degradation of cellular components in lysosomes. However, from a bioinformatics perspective, autophagy-related genes have not been comprehensively elucidated in rheumatoid arthritis.

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Microplastic pollution poses threats to aquatic ecosystems and human health. In this study, in order to investigate the characteristics of microplastic occurrence in different environmental media, the abundance, particle size, shape, color, and composition types of microplastics in the water column, sediment, riparian zone soil, and the benthic snail of the Manao River were analyzed using field sampling, microscopic observation, and Fourier infrared spectroscopy. The results showed that the average abundance of microplastics in the surface water of the Manao River was (5.

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Microplastics, as an emerging pollutant, have garnered global attention. Urban areas are key hotspots for the generation of microplastic pollution, whereas urban water bodies act as vital conduits for the dissemination of microplastics to other freshwater environments. In this study, the Dongshan Canal in the urban area of Yichang City was selected as the research subject.

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Rationale And Objectives: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine learning model.

Materials And Methods: 145 and 50 RRMS patients with structural MRI and at least 1-year follow-up Expanded Disability Status Scale (EDSS) results were retrospectively enrolled and placed in the discovery and external test cohorts, respectively. Six clinical and radiomics feature-based machine learning classifiers were trained and tested to predict disability progression in the discovery cohort and validated in the external test set.

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Article Synopsis
  • White matter lesions in relapsing-remitting multiple sclerosis (RRMS) can be categorized into three types: contrast enhancement lesions (CELs), iron rim lesions (IRLs), and non-iron rim lesions (NIRLs), but existing methods for classification, particularly using radiomics, are limited.
  • A study analyzed 875 WM lesions using machine learning techniques, with a focus on feature selection and model performance evaluation, comparing 2-class (IRLs and NIRLs) and 3-class (CELs, IRLs, and NIRLs) classification tasks.
  • Results showed that the LASSO with RF model excelled in 2-class classification, while LASSO with XGBoost performed best in
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Background And Objectives: Myelin oligodendrocyte glycoprotein antibody-associated diseases (MOGAD) is an idiopathic inflammatory demyelinating disorder in children, for which the precise damage patterns of the white matter (WM) fibers remain unclear. Herein, we utilized diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ) to identify patterns of fiber damage and to investigate the clinical significance of MOGAD-affected fiber tracts.

Methods: A total of 28 children with MOGAD and 31 healthy controls were included in this study.

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Synopsis of recent research by authors named "Shuang Ding"

  • - Shuang Ding's research predominantly focuses on applying machine learning and radiomics techniques to enhance predictive modeling in various medical conditions, emphasizing neuroblastoma metastasis, stroke outcomes, and disorders of consciousness in children.
  • - Recent findings include the successful identification of significant biomarkers and the development of clinical-radiomics models that can accurately predict functional outcomes and disease progression in these conditions, highlighting the importance of imaging features in clinical decision-making.
  • - Additionally, Ding's work extends to investigating novel therapeutic targets in viral diseases and understanding the mechanisms underlying diseases such as Parkinson's and atherosclerosis, showcasing a multidisciplinary approach bridging radiomics, genomics, and machine learning.