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Primary extraskeletal osteosarcoma of rectal mesentery: a rare case and literature review.
World J Surg Oncol
January 2025
The Department of General Surgery, The Second Hospital of Jilin University, Changchun, 130041, China.
Background: Extraskeletal osteosarcoma (ESOS) is a rare kind of sarcoma with a low preoperative diagnosis and a poor prognosis. ESOS arising from abdominal mesentery is extremely rare. Increasing diagnostic methods and standardizing treatment protocols are crucial issues of ESOS.
View Article and Find Full Text PDFADSL promotes autophagy and tumor growth through fumarate-mediated Beclin1 dimethylation.
Nat Chem Biol
January 2025
Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
As an enzyme with a critical role in de novo purine synthesis, adenylosuccinate lyase (ADSL) expression is upregulated in various malignancies. However, whether ADSL possesses noncanonical functions that contribute to cancer progression remains poorly understood. Here, we demonstrate that protein kinase R-like endoplasmic reticulum kinase (PERK) activated by lipid deprivation or ER stress phosphorylates ADSL at S140, leading to an enhanced association between ADSL and Beclin1.
View Article and Find Full Text PDFIntricacies of human-AI interaction in dynamic decision-making for precision oncology.
Nat Commun
January 2025
Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
View Article and Find Full Text PDFMRI-based deep learning radiomics to differentiate dual-phenotype hepatocellular carcinoma from HCC and intrahepatic cholangiocarcinoma: a multicenter study.
Insights Imaging
January 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Objectives: To develop and validate radiomics and deep learning models based on contrast-enhanced MRI (CE-MRI) for differentiating dual-phenotype hepatocellular carcinoma (DPHCC) from HCC and intrahepatic cholangiocarcinoma (ICC).
Methods: Our study consisted of 381 patients from four centers with 138 HCCs, 122 DPHCCs, and 121 ICCs (244 for training and 62 for internal tests, centers 1 and 2; 75 for external tests, centers 3 and 4). Radiomics, deep transfer learning (DTL), and fusion models based on CE-MRI were established for differential diagnosis, respectively, and their diagnostic performances were compared using the confusion matrix and area under the receiver operating characteristic (ROC) curve (AUC).
The value of MRI in differentiating ovarian clear cell carcinoma from other adnexal masses with O-RADS MRI scores of 4-5.
Insights Imaging
January 2025
Department of Radiology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Objective: To assess the utility of clinical and MRI features in distinguishing ovarian clear cell carcinoma (CCC) from adnexal masses with ovarian-adnexal reporting and data system (O-RADS) MRI scores of 4-5.
Methods: This retrospective study included 850 patients with indeterminate adnexal masses on ultrasound. Two radiologists evaluated all preoperative MRIs using the O-RADS MRI risk stratification system.
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