Publications by authors named "Yanran Du"

Bacterial infections and long-term inflammation cause serious secondary damage to chronic diabetic wounds and hinder the wound healing processes. Currently, multifunctional hydrogels have shown promising effects in chronic wound repair. However, traditional hydrogels only keep the wound moist and protect it from bacterial infection, and cannot provide mechanical force to contract the wound edges to achieve facilitated wound closure.

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Inflammatory bowel disease (IBD) is a chronic nonspecific inflammatory disease of the intestine, with unknown etiology and the incidence is increasing year by year. Traditional treatment has limited effect. Mesenchymal stem cell-derived exosomes (MSC-Exos) are a group of nano-sized extracellular vesicles.

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Objective: To establish a classification model for the evaluation of rat fetal lung maturity (FLM) using radiomics technology.

Method: A total of 430 high-throughput features were extracted per fetal lung image from 134 fetal lung ultrasound images (four-cardiac-chamber views) of 67 Sprague-Dawley (SD) fetal rats with a gestational age of 16-21 days. The detection of fetal lung tissues included histopathological staining and the expression of surface proteins SP-A, SP-B, and SP-C.

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To develop a novel method for predicting neonatal respiratory morbidity (NRM) by ultrasound-based radiomics technology. In this retrospective study, 430 high-throughput features per fetal-lung image were extracted from 295 fetal lung ultrasound images (four-chamber view) in 295 single pregnancies. Images had been obtained between 28 and 37 weeks of gestation within 72 h before delivery.

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Article Synopsis
  • A non-invasive method was developed to predict neonatal respiratory issues using radiomics based on fetal lung ultrasound images, focusing on imbalanced data from 210 images (159 normal, 51 with issues).
  • The prediction model integrated radiomics features, gestational age, and diabetes status, using techniques like data augmentation and ensemble learning to handle imbalances in the dataset.
  • Results showed the model to be effective with high sensitivity (0.82), specificity (0.84), and overall accuracy (0.83), making it a promising alternative to invasive procedures for assessing neonatal respiratory morbidity.
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Objective: To evaluate the diagnostic performance of a new method of combined ultrasound elastography (UE) and thyroid imaging-reporting and data system (TI-RADS) in the differential diagnosis of small thyroid nodules.

Methods: Ultrasonography(US), TI-RADS, Elasticity Imaging (EI), Virtual Touch Tissue Imaging (VTI) and Virtual Touch Tissue Quantification (VTQ) features of 142 thyroid nodules (maximum diameter ≤10 mm according to conventional ultrasound measurement) confirmed by surgery or FNA were retrospectively analyzed. Different elastographic methods in small benign and malignant thyroid nodules were compared.

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Background: Breast cancer is the most common cancer in women worldwide. The purpose of the study was to observe the features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound for assessing small breast lesions.

Objectives: The study was to explore the small breast lesions' features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound, in order to improve the diagnostic accuracy of early breast cancer.

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