Publications by authors named "Runqi Wang"

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily.

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Objective: Advancements in medical science have improved non-metastatic renal cell carcinoma (NM-RCC) treatment strategies, but long-term survival is influenced by various factors, including perioperative blood transfusion. This study aims to analyse prognostic factors in patients with NM-RCC after radical nephrectomy.

Methods: From January 2018 to December 2021, a total of 132 patients with NM-RCC after radical nephrectomy were studied.

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Background: Increasing evidence shows that circRNA plays an essential regulatory role in diseases through interactions with disease-related miRNAs. Identifying circRNA-disease associations is of great significance to precise diagnosis and treatment of diseases. However, the traditional biological experiment is usually time-consuming and expensive.

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Adult tissue homeostasis is maintained by residential stem cells. The proliferation and differentiation of adult stem cells must be tightly balanced to avoid excessive proliferation or premature differentiation. However, how stem cell proliferation is properly controlled remains elusive.

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Article Synopsis
  • Understanding the link between non-coding RNAs (ncRNAs) and drug resistance is crucial for improving drug effectiveness and treatment strategies.
  • Traditional methods for studying this connection are slow and limited in scope, highlighting the need for computational approaches.
  • The paper presents LRGCPND, a new method using graph convolution to predict ncRNA-drug resistance associations, which outperforms existing techniques with an average AUC of 0.8987, demonstrating its effectiveness and reliability.
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While the deep convolutional neural network (DCNN) has achieved overwhelming success in various vision tasks, its heavy computational and storage overhead hinders the practical use of resource-constrained devices. Recently, compressing DCNN models has attracted increasing attention, where binarization-based schemes have generated great research popularity due to their high compression rate. In this article, we propose modulated convolutional networks (MCNs) to obtain binarized DCNNs with high performance.

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In this paper, modeling for a lateral impact ionization InGaAs/InP avalanche photodiode (APD) has been performed based on a device simulator, i.e., Silvaco ATLAS.

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Aquatic animals have developed various mechanisms to live in either hyperionic or hypoionic environments, and, as such, not many species are capable of surviving in both. The red-eared slider turtle, , a well-known freshwater species, has recently been found to invade and inhabit brackish water. Herein, we focus on some of the metabolic adaptations that are required to survive and cope with salinity stress.

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The pathophysiologic significance of the CD16 monocyte subset has been demonstrated by its expansion in various autoimmune disorders. To date, the characteristics and roles of monocyte subpopulations in patients with neuromyelitis optica (NMO) have been poorly defined. We measured the percentages of the monocyte subsets in the peripheral blood, the levels of IL-1β and TNF-α mRNA in monocyte subsets and the concentrations of IL-1β and TNF-α in plasma and CSF from NMO patients.

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MiR-15a is likely to be associated with autoimmunity. Here, we aimed to examine the expression of miR-15 cluster in PBMCs from myasthenia gravis (MG) patients and investigate the potential roles of miR-15a in MG. We found that the expression of all miR-15 cluster was decreased in MG, furthermore, miR-15a levels in ocular MG (oMG) were much lower, while CXCL10 production was increased in MG.

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