Publications by authors named "JianAn Ye"

Background: Recent studies have confirmed the critical role of neonatal microglia in wound healing and axonal regeneration following spinal cord injury (SCI). However, the limited migration of microglia to the center of adult lesion may significantly impede their potential benefits.

Methods: We established a model of microglial centripetal migration and prolonged retention in C57BL/6J and transgenic mice by injecting exogenous C-X3-C motif chemokine ligand 1 (CX3CL1) and macrophage colony-stimulating factor (M-CSF) directly into the lesion site post-SCI.

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Excessive iron deposition can lead to ferroptosis, a form of iron-dependent cell death detrimental to neuronal survival. Microglia have been identified as having a high capacity for iron deposition, yet it remains unclear whether microglia undergo ferroptosis while phagocytosing excessive amounts of iron after spinal cord injury (SCI). Here, we observed scattered iron around the epicenter of the injured spinal cord at 7 days post-injury (dpi) in mice, which then accumulated in the lesion core at 14 dpi.

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Fluorescence endoscopy technology utilizes a light source of a specific wavelength to excite the fluorescence signals of biological tissues. This capability is extremely valuable for the early detection and precise diagnosis of pathological changes. Identifying a suitable experimental approach and metric for objectively and quantitatively assessing the imaging quality of fluorescence endoscopy is imperative to enhance the image evaluation criteria of fluorescence imaging technology.

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Article Synopsis
  • IL-3 plays a significant role in lipid debris clearance by macrophages, which is crucial for recovery after spinal cord injuries (SCI), with its expression peaking at 14 days post-injury.
  • Neutralizing IL-3 results in increased lipid accumulation and decreased neuronal survival, leading to greater motor deficits, while augmenting IL-3 promotes neuron preservation and enhances axon regeneration.
  • These findings suggest that targeting the IL-3/IL-3Rα pathway could be a promising therapeutic approach for improving recovery after SCI.
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Objective: This study examines the association between dietary intake of live microbes (LM) and the risk of cardiovascular disease (CVD) and cardiovascular mortality in adults with diabetes.

Methods: A retrospective cohort study was conducted using National Health and Nutrition Examination Survey (NHANES) data from 2001 to 2010, with follow-up mortality data through December 31, 2019. A total of 3,955 adults with diabetes were included.

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Background: In the context of spinal cord injury (SCI), infiltrating macrophages assume prominence as the primary inflammatory cells within the lesion core, where the fibrotic scar is predominantly orchestrated by platelet-derived growth factor receptor beta (PDGFRβ) fibroblasts. Galectin-3, a carbohydrate-binding protein of the lectin family, is notably expressed by infiltrating hematogenous macrophages and mediates cell-cell interactions. Although Galectin-3 has been shown to contribute to the endocytic internalization of PDGFRβ in vitro, its specific role in driving fibrotic scar formation after SCI has not been determined.

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Objective: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

Study Design: The study involved pediatric glioma patients from the Surveillance, Epidemiology, and End Results (SEER) Registry (2000-2018) and Tangdu Hospital in China (2010-2018) within specific time frames. For training, we selected two neural network-based algorithms (DeepSurv, neural multi-task logistic regression [N-MTLR]) and one ensemble learning-based algorithm (random survival forest [RSF]).

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Article Synopsis
  • * The study analyzed gene expression data from the Cancer Genome Atlas (TCGA) to evaluate the relationship between tumor microenvironment scores and differentially expressed genes (DEGs), identifying 2346 DEGs that are linked to immune and cellular processes.
  • * Ten hub genes, including ACTB and IL-6, were found to have predictive value related to patient outcomes, such as overall and disease-free survival, emphasizing their potential significance in BC prognosis.
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Aim: To assess and verify the effect of the gut microbiome on the susceptibility and complications of type 1 diabetes (T1D).

Materials And Methods: To achieve this aim, a two-sample and reverse Mendelian randomization (MR) analysis was conducted. In addition, an external validation study was performed using individual microbiome data of patients with T1D from the gutMEGA datasets and the National Clinical Research Center for Metabolic Diseases.

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Aims: The aims of the present study were to assess the effects of lipid-lowering drugs [HMG-CoA reductase inhibitors, proprotein convertase subtilisin/kexin type 9 inhibitors, and Niemann-Pick C1-Like 1 (NPC1L1) inhibitors] on novel subtypes of adult-onset diabetes through a Mendelian randomisation study.

Materials And Methods: We first inferred causal associations between lipid-related traits [including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoproteins A-I, and apolipoproteins B] and novel subtypes of adult-onset diabetes. The expression quantitative trait loci of drug target genes for three classes of lipid-lowering drugs, as well as genetic variants within or nearby drug target genes associated with LDL-C, were then utilised as proxies for the exposure of lipid-lowering drugs.

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After spinal cord injury (SCI), the accumulation of myelin debris can serve as proinflammatory agents, hindering axon regrowth and exacerbating damage. While astrocytes have been implicated in the phagocytosis of myelin debris, the impact of this process on the phenotypic transformation of astrocytes and their characteristics following SCI in rats is not well understood. Here, we demonstrated that the conditioned medium of myelin debris can trigger apoptosis in rat primary astrocytes in vitro.

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Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure.

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After spinal cord injury (SCI), the accumulation of myelin debris at the lesion exacerbates cell death and hinders axonal regeneration. Transplanted bone marrow mesenchymal stem cells (BMSCs) have been proven to be beneficial for SCI repair, but they are susceptible to apoptosis. It remains unclear whether this apoptotic process is influenced by myelin debris.

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A cerebral contrast-enhanced electrical impedance tomography perfusion method is developed for acute ischemic stroke during intravenous thrombolytic therapy. Several clinical contrast agents with stable impedance characteristics and high-conductivity contrast were screened experimentally as electrical impedance contrast agent candidates. The electrical impedance tomography perfusion method was tested on rabbits with focal cerebral infarction, and its capability for early detection was verified based on perfusion images.

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Electrical impedance tomography (EIT) is a noninvasive and radiation-free imaging method. As a "soft-field" imaging technique, in EIT, the target signal in the center of the measured field is frequently swamped by the target signal at the edge, which restricts its further application. To alleviate this problem, this study presents an enhanced encoder-decoder (EED) method with an atrous spatial pyramid pooling (ASPP) module.

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Context: Diabetes is a major health problem and metabolically unhealthy is an important risk factor.

Objective: To conduct the first nationally representative study on epidemiological data of metabolically unhealthy normal weight (MUNW) focused only on nondiabetic subjects and determine the predictive effect on diabetes in China.

Methods: A longitudinal study was conducted using data from the Rich Healthcare Group in China.

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Following spinal cord injury (SCI), fibrotic scar inhibits axon regeneration and impairs neurological function recovery. It has been reported that T cell-derived interferon (IFN)-γ plays a pivotal role in promoting fibrotic scarring in neurodegenerative disease. However, the role of IFN-γ in fibrotic scar formation after SCI has not been declared.

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Glycemic variability (GV) in some patients with type 1 diabetes (T1D) remains heterogeneous despite comparable clinical indicators, and whether other factors are involved is yet unknown. Metabolites in the serum indicate a broad effect of GV on cellular metabolism and therefore are more likely to indicate metabolic dysregulation associated with T1D. To compare the metabolomic profiles between high GV (GV-H, coefficient of variation (CV) of glucose ≥ 36%) and low GV (GV-L, CV < 36%) groups and to identify potential GV biomarkers, metabolomics profiling was carried out on serum samples from 17 patients with high GV, 16 matched (for age, sex, body mass index (BMI), diabetes duration, insulin dose, glycated hemoglobin (HbA1c), fasting, and 2 h postprandial C-peptide) patients with low GV (exploratory set), and another 21 (GV-H/GV-L: 11/10) matched patients (validation set).

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Article Synopsis
  • * The application of deep learning in EIT image reconstruction has grown significantly, focusing on single network approaches, combining deep learning with traditional methods, and using hybrid networks.
  • * Future challenges in EIT image reconstruction involve optimizing datasets, improving network structures, and integrating multimodal deep learning, which could lead to enhanced diagnostic systems.
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Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring by EIT imaging suffers from image noise (IN) and resolution problems, causing blurred reconstructions. To address these problems, a least absolute shrinkage and selection operator model is built, and a fast iterative shrinkage-thresholding algorithm with continuation (FISTA-C) is proposed.

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Background: Real-time detection of cerebral blood perfusion can prevent adverse reactions, such as cerebral infarction and neuronal apoptosis. Our previous clinical trial have shown that the infusion of therapeutic fluid can significantly change the impedance distribution in the brain. However, whether this alteration implicates the cerebral blood perfusion remains unclear.

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Aims: To investigate glycaemic variability (GV) patterns in patients with type 1 diabetes (T1D), type 2 diabetes (T2D), and latent autoimmune diabetes in adults (LADA).

Materials And Methods: A total of 842 subjects (510 T1D, 105 LADA, 227 T2D) were enrolled and underwent 1 week of continuous glucose monitoring (CGM). Clinical characteristics and CGM parameters were compared among T1D, LADA, and T2D.

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Background: We aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring.

Methods: In total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared.

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Aims: The comorbidity of metabolic syndrome (MetS) and type 1 diabetes mellitus (T1DM) is an obstacle to glucose control in patients with T1DM. We compared glycemic profiles using continuous glucose monitoring (CGM) systems in patients with T1DM with or without MetS.

Methods: This was a multicenter cross-sectional study of patients with T1DM (N = 207) with or without MetS.

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Synopsis of recent research by authors named "JianAn Ye"

  • - Jianan Ye's research primarily focuses on the intersection of neural injury, cancer prognosis, and metabolic diseases, highlighting the exploration of factors such as immune responses, microbiome influences, and the application of advanced technologies such as deep learning for medical predictions.
  • - Recent findings demonstrate that Galectin-3 plays a critical role in fibrotic scarring post spinal cord injury, and insights into the gut microbiome significantly affect the susceptibility and complications related to type 1 diabetes.
  • - Ye's work includes developing machine learning models for predicting survival in pediatric glioma patients, addressing the impact of lipid-lowering drugs on diabetes subtypes, and enhancing early detection methods for acute ischemic stroke, showcasing a commitment to improving patient outcomes through innovative approaches.

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