Publications by authors named "Chenyi Xie"

Heterochromatin, a key component of the eukaryotic nucleus, is fundamental to the regulation of genome stability, gene expression and cellular functions. However, the factors and mechanisms involved in heterochromatin formation and maintenance still remain largely unknown. Here, we show that insulin receptor tyrosine kinase substrate (IRTKS), an I-BAR domain protein, is indispensable for constitutive heterochromatin formation via liquid‒liquid phase separation (LLPS).

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Elevated expression and genetic aberration of IRTKS, also named as BAIAP2L1, have been observed in many tumors, especially in tumor progression. however, the molecular and cellular mechanisms involved in the IRTKS-enhanced tumor progression are obscure. Here we show that higher IRTKS level specifically increases histone H3 lysine 9 trimethylation (H3K9me3) by promoting accumulation of the histone methyltransferase SETDB1.

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Purpose: Metabolic acidosis as one of the most common perioperative complications has been associated with increased risks for poor prognosis. Routine monitoring methods include blood gas analysis and electrocardiogram, which are limited by time delay effects. And the existing intravital imaging modalities are difficult to achieve in one step.

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Background: Lymph node status is vital for prognosis and treatment decisions for esophageal squamous cell carcinoma (ESCC). This study aimed to construct and evaluate an optimal radiomics-based method for a more accurate evaluation of individual regional lymph node status in ESCC and to compare it with traditional size-based measurements.

Methods: The study consecutively collected 3225 regional lymph nodes from 530 ESCC patients receiving upfront surgery from January 2011 to October 2015.

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Objective: To evaluate the application of endoscopic ultrasound (EUS) combined with multislice spiral CT (MSCT) in the diagnosis and treatment of patients with gastric eminence lesions.

Methods: A total of 160 patients with gastric eminence lesions enrolled in our hospital from June 2018 to June 2021 were included and received EUS and MSCT. The results of the two examinations and the postoperative pathological results were compared.

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PET/CT scan has been used as a tool for the diagnosis and management of nasopharyngeal carcinoma (NPC). It has been proven to be highly valuable for the imaging and management of patients with NPC with strengths in N and M staging as well as treatment planning and is recommended to be incorporated into the standard clinical assessment. Novel quantitative techniques such as the use of radiomics may provide valuable prognostic information.

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Esophageal cancer (EC) is of public health significance as one of the leading causes of cancer death worldwide. Accurate staging, treatment planning and prognostication in EC patients are of vital importance. Recent advances in machine learning (ML) techniques demonstrate their potential to provide novel quantitative imaging markers in medical imaging.

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Background: A(H1N1)pdm09 influenza viruses replicate efficiently in respiratory epithelia and are transmitted via respiratory droplets and aerosols expelled by infected hosts. The relative onward transmission potential of influenza viruses replicating in the upper and lower respiratory epithelial cells has not been fully defined.

Methods: Wild-type and barcoded A(H1N1)pdm09 viruses that differed by 2 synonymous mutations per gene segment were inoculated into ferrets via intranasal and intratracheal routes.

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Purpose: To evaluate the prognostic value of baseline and restaging CT-based radiomics with features associated with gene expression in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiation (nCRT) plus surgery.

Methods: We enrolled 106 ESCC patients receiving nCRT from two institutions. Gene expression profiles of 28 patients in the training set were used to detect differentially expressed (DE) genes between patients with and without relapse.

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Purpose: The coronavirus disease 2019 (COVID-19) has evolved into a worldwide pandemic. CT although sensitive in detecting changes suffers from poor specificity in discrimination from other causes of ground glass opacities (GGOs). We aimed to develop and validate a CT-based radiomics model to differentiate COVID-19 from other causes of pulmonary GGOs.

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Background: Deep learning is promising to predict treatment response. We aimed to evaluate and validate the predictive performance of the CT-based model using deep learning features for predicting pathologic complete response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC).

Materials And Methods: Patients were retrospectively enrolled between April 2007 and December 2018 from two institutions.

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Pseudoaneurysm (PSA) formation is the most common arterial complication of endovascular procedures requiring arterial puncture. The present study reported a case of a 72-year-old male patient with iatrogenic femoral artery PSA treated with contrast-enhanced ultrasound (CEUS)-guided thrombin injection. Conventional ultrasound (US) and CEUS were used to diagnose, guide treatment, and evaluate the treatment efficacy.

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Importance: For patients with locally advanced esophageal squamous cell carcinoma, neoadjuvant chemoradiation has been shown to improve long-term outcomes, but the treatment response varies among patients. Accurate pretreatment prediction of response remains an urgent need.

Objective: To determine whether peritumoral radiomics features derived from baseline computed tomography images could provide valuable information about neoadjuvant chemoradiation response and enhance the ability of intratumoral radiomics to estimate pathological complete response.

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Purpose: Biomedical data frequently contain imbalance characteristics which make achieving good predictive performance with data-driven machine learning approaches a challenging task. In this study, we investigated the impact of re-sampling techniques for imbalanced datasets in PET radiomics-based prognostication model in head and neck (HNC) cancer patients.

Methods: Radiomics analysis was performed in two cohorts of patients, including 166 patients newly diagnosed with nasopharyngeal carcinoma (NPC) in our centre and 182 HNC patients from open database.

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Background: Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at nonhealthcare locations vs surveillance data obtained by conventional means has not been fully assessed.

Methods: From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong.

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