Publications by authors named "Yuanhang Gao"

Purpose: This study aims to optimize neoadjuvant radiotherapy target area for locally advanced rectal cancer (LARC) patients undergoing total neoadjuvant therapy (TNT) by examining local recurrence patterns.

Methods And Materials: We retrospectively analyzed the clinical data of rectal cancer patients who undergone local recurrence after surgery. Recurrence sites were categorized and compared with initial diagnosis imaging, focusing on visible and suspicious lesions.

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Rationale: Small-cell undifferentiated carcinoma (SmCC), as an aggressive malignancy, are most commonly arising in lung. Extrapulmonary SmCC is rare. It was reported that SmCC accounts for only 0.

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Background: Brain aging is a complex process that involves functional alterations in multiple subnetworks and brain regions. However, most previous studies investigating aging-related functional connectivity (FC) changes using resting-state functional magnetic resonance images (rs-fMRIs) have primarily focused on the linear correlation between brain subnetworks, ignoring the nonlinear casual properties of fMRI signals.

Methods: We introduced the neural Granger causality technique to investigate the sex-dependent nonlinear Granger connectivity (NGC) during aging on a publicly available dataset of 227 healthy participants acquired cross-sectionally in Leipzig, Germany.

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The electrolyte chemistry is crucially important for promoting the practical application of lithium metal batteries (LMBs). Here, we demonstrate for the first time that 1,3-dimethylimidazolium dimethyl phosphate (DIDP) and trimethylsilyl trifluoroacetate (TMSF) can undergo in situ transesterification in carbonate electrolyte to generate dimethyl trimethylsilyl phosphate (DTMSP) and 1,3-dimethylimidazolium trifluoroacetate (DITFA) as multifunctional additives for LMBs. HO and HF can be removed by the Si-O group in DTMSP to improve the moisture resistance of electrolyte and the stability of cathode.

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Removing noise from acquired images is a crucial step in various image processing and computer vision tasks. However, the existing methods primarily focus on removing specific noise and ignore the ability to work across modalities, resulting in limited generalization performance. Inspired by the iterative procedure of image processing used by professionals, we propose a pixel-wise crossmodal image-denoising method based on deep reinforcement learning to effectively handle noise across modalities.

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Background: Rectal squamous cell carcinoma (RSCC) is a rare malignancy of the rectal tumor. Due to its extremely low incidence, there is still a lack of high-level treatment evidence and clinical consensus on this disease.

Case Report: In this article, we report a treatment process of RSCC with high PD-L1 expression.

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It has been demonstrated that schizophrenia (SZ) is characterized by functional dysconnectivity involving extensive brain networks. However, the majority of previous studies utilizing resting-state functional magnetic resonance imaging (fMRI) to infer abnormal functional connectivity (FC) in patients with SZ have focused on the linear correlation that one brain region may influence another, ignoring the inherently nonlinear properties of fMRI signals..

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