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Background: Acute ischemic stroke (AIS) is a common cerebrovascular disease with high mortality. AIS patients in the intensive care unit (ICU) often have severe conditions that require close monitoring and timely treatment. Receptor-interacting protein kinase 1 (RIPK1) and RIPK3 play important roles in cell apoptosis and inflammation. However, the relevance of serum RIPK1/3 to AIS patients in the ICU has not been clarified.
Objective: To explore the correlation of serum RIPK1 and RIPK3 with the prognosis of AIS patients in the ICU.
Methods: One hundred and twenty AIS patients were selected as the research subjects for the retrospective analysis. The subjects were grouped based on the volume of cerebral infarction and the score of the National Institute of Health Stroke Scale (NIHSS) and mRS. The correlation was explored using Pearson analysis. The predictive value was valued using the ROC curve.
Results: The content of serum RIPK1 and RIPK3 was gradually elevated with increased cerebral infarction volume and the severity of the disease (p < 0.05). Patients with poor prognosis had a higher content of serum RIPK1 and RIPK3 than those with good prognosis (p < 0.05). Serum RIPK1 and RIPK3 levels were positively correlated with infarct volume, NHISS, and mRS scores (p < 0.001). The area under the curve (AUC) of RIPK1 and RIPK3 for predicting the severity of AIS was 0.703, 0.883, and 0.912, respectively. The AUC for predicting poor prognosis of AIS was 0.797, 0.721, and 0.893, respectively. The cooperative detection of RIPK1 and RIPK3 had higher clinical value.
Conclusion: AIS patients in the ICU had abnormally elevated content of serum RIPK1 and RIPK3, which was closely related to the volume of cerebral infarction, severity, and prognosis. Combined detection of RIPK1 and RIPK3 might help to early identify the severity and evaluate the prognosis, providing a reference basis for clinical doctors to develop treatment strategies.
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http://dx.doi.org/10.1002/iid3.70085 | DOI Listing |
Int J Surg
September 2025
Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
Background: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD).
Methods: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images.
Rev Cardiovasc Med
August 2025
Department of Radiology, The Fourth Affiliated Hospital of Soochow University (Suzhou Dushu Lake Hospital), 215124 Suzhou, Jiangsu, China.
Background: Identifying the etiology of acute ischemic stroke (AIS) is critical for secondary prevention and treatment choice in stroke patients. This study aimed to investigate the dual-energy computed tomography (DECT) quantitative thrombus parameters associated with cardioembolic (CE) stroke and develop a nomogram that combines DECT and clinical data to identify CE stroke.
Methods: We retrospectively reviewed all consecutive patients from January 2020 to July 2022 with anterior circulation stroke and proximal intracranial occlusions.
Alpha Psychiatry
August 2025
Information Sciences and Technology, George Mason University, Fairfax, VA 22030, USA.
Background: Herein, we report on the initial development, progress, and future plans for an autonomous artificial intelligence (AI) system designed to manage major depressive disorder (MDD). The system is a web-based, patient-facing conversational AI that collects medical history, provides presumed diagnosis, recommends treatment, and coordinates care for patients with MDD.
Methods: The system includes seven components, five of which are complete and two are in development.
Comput Methods Programs Biomed
September 2025
Electrical and Computer Engineering Department, School of Engineering, Morgan State University, Baltimore, MD, 21251, USA. Electronic address:
Breast Cancer (BC) remains a leading cause of morbidity and mortality among women globally, accounting for 30% of all new cancer cases (with approximately 44,000 women dying), according to recent American Cancer Society reports. Therefore, accurate BC screening, diagnosis, and classification are crucial for timely interventions and improved patient outcomes. The main goal of this paper is to provide a comprehensive review of the latest advancements in BC detection, focusing on diagnostic BC imaging, Artificial Intelligence (AI) driven analysis, and health disparity considerations.
View Article and Find Full Text PDFCuad Bioet
September 2025
Universidad de A Coruña. Facultad de Derecho, Campus de Elviña, s/n, 15071, A Coruña. 981 167000 ext. 1640
The implications of the use of artificial intelligence (AI) in many areas of human existence compels us to reflect on its ethical relevance. This paper addresses the signification of its use in healthcare for patient informed consent. To this end, it first proposes an understanding of AI, as well as the basis for informed consent.
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