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Artificial Intelligence-Guided Identification of IGFBP7 as a Critical Indicator in Lactic Metabolism Determines Immunotherapy Response in Stomach Adenocarcinoma.
J Cell Mol Med
January 2025
Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Due to considerable tumour heterogeneity, stomach adenocarcinoma (STAD) has a poor prognosis and varies in response to treatment, making it one of the main causes of cancer-related mortality globally. Recent data point to a significant role for metabolic reprogramming, namely dysregulated lactic acid metabolism, in the evolution of STAD and treatment resistance. This study used a series of artificial intelligence-related approaches to identify IGFBP7, a Schlafen family member, as a critical factor in determining the response to immunotherapy and lactic acid metabolism in STAD patients.
View Article and Find Full Text PDFArtificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.
ACS Appl Mater Interfaces
January 2025
Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.
Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable implants as planar and tubular thermal mechanical metamaterials (thermo-metamaterials). These thermo-metamaterial implants exhibit tunable mechanical properties and volume change in response to temperature changes, enabling minimally invasive and personalized surgery.
View Article and Find Full Text PDFProtocol for artificial intelligence-guided neural control using deep reinforcement learning and infrared neural stimulation.
STAR Protoc
December 2024
Weldon School of Biomedical Engineering, the Center for Implantable Devices, and the Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA. Electronic address:
Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neural control in rats using deep reinforcement learning (RL) and infrared neural stimulation (INS). We describe steps for integrating RL closed-loop control into neuroscience and neuromodulation studies.
View Article and Find Full Text PDFArtificial intelligence guided search for van der Waals materials with high optical anisotropy.
Mater Horiz
December 2024
National Graphene Institute (NGI), University of Manchester, Manchester, M13 9PL, UK.
The exploration of van der Waals (vdW) materials, renowned for their unique optical properties, is pivotal for advanced photonics. These materials exhibit exceptional optical anisotropy, both in-plane and out-of-plane, making them an ideal platform for novel photonic applications. However, the manual search for vdW materials with giant optical anisotropy is a labor-intensive process unsuitable for the fast screening of materials with unique properties.
View Article and Find Full Text PDFFirst comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Coron Artery Dis
December 2024
Department of Cardiology, David Geffen School of Medicine, University of California, Los Angeles.
Background: Noninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery disease. We aimed to evaluate whether a novel artificial intelligence (AI)-assisted CCTA program is comparable to SPECT imaging for ischemic testing.
Methods: CCTA images were analyzed using an artificial intelligence convolutional neural network machine-learning-based model, atherosclerosis imaging-quantitative computed tomography (AI-QCT)ISCHEMIA.
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