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Optics and the Brain, BRAIN 2023 - Part of Optica Biophotonics Congress: Optics in the Life sciences 2023

作者： Fogarty, Morgan Rafferty, Sean M. O’Sullivan, Anthony C. Svoboda, Calamity F. Markow, Zachary E. Richter, Edward J. George, Tessa King, Kelsey Wilhelm, Dana Tripathy, Kalyan Trobaugh, Jason W. Eggebrecht, Adam T. Culver, Joseph P. Imaging Science Program Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States Department of Biomedical Engineering Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States Department of Neuroscience Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States Department of Electrical and Systems Engineering Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States Department of Radiology Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States Department of Physics Washington University in St. Louis 1 Brookings Drive St. LouisMO63130 United States

High-density diffuse optical tomography uses a dense array of overlapping measurements that provides functional brain images validated against fMRI. We doubled this optode density, improving resolution and expanding t... 详细信息

ISBN: (纸本)9781957171210

关键词： Diffuse optical tomography Functional imaging Image quality Magnetic resonance imaging Near infrared spectroscopy Optical imaging

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Spinal functional Magnetic Resonance Imaging (fMRI) on Human Studies: A Literature Review

Spinal functional Magnetic Resonance Imaging (fMRI) on Human...

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2019 Advances in science and engineering Technology International Conferences, ASET 2019

作者： Al-Momani, Sajedah Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering Biomedical Engineering Graduate Program Biosciences and Bioengineering Research Institute American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781538682715

Spinal functional Magnetic Resonance Imaging (fMRI) is a newly emerging non-invasive imaging technique that has been introduced to study the Blood Oxygenation Level Dependent (BOLD) changes in the spinal cord associated with a certain activity or even at rest. Spinal fMRI is also used to assess the treatment of many dysfunctions affect the spinal cord such as spinal cord injury (SCI) and Multiple sclerosis (MS). The purpose of this paper is to propose a literature review of spinal fMRI studies performed on healthy human volunteers. The studies reviewed are divided based on the paradigm being performed during image acquisition into (1) studies under activities and stimulus which are further classified according to the type of the stimuli, and (2) studies at resting state. Moreover, the limitations of spinal fMRI and how to tackle them are discussed. © 2019 IEEE.

关键词： Magnetic resonance imaging

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Inorganic Ions Activate Lineage-Specific Gene Regulatory Networks to Drive Stem Cells Differentiation

SSRN

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SSRN 2023年

作者： Kersey, Anna L. Gaharwar, Akhilesh K. Singh, Irtisha Department of Biomedical Engineering College of Engineering Texas A&M University College StationTX77843 United States Department of Cell Biology and Genetics College of Medicine Texas A&M University College StationTX77843 United States Interdisciplinary Program in Genetics Texas A&M University College StationTX77843 United States Center for Remote Health Technologies and Systems Texas A&M University College StationTX77843 United States Department of Material Science and Engineering Dwight Look College of Engineering Texas A&M University College StationTX77843 United States

Ions released from inorganic biomaterials play a vital role in defining cell identity. However, the effect of inorganic ions on cellular functions has yet to be investigated at the transcriptomic level, representing a critical knowledge gap in the development of next-generation of bioactive materials. To address this gap, we investigated the impact of various inorganic ions including silver, copper, titanium, and platinum on human stem cells. Our finding showed that silver and copper induce osteogenic and chondrogenic differentiation respectively, through enrichment of ion-dependent signaling pathways. Specifically, silver effectively induced Wnt and MAPK signaling, which are vital for osteogenesis. On the other hand, copper specifically stimulated TGFβ signaling, while suppressing JAK-STAT signaling, thereby promoting chondrogenesis. In contrast, platinum, tantalum, and titanium ions didn't stimulate regenerative responses. Titanium displayed minimal gene expression changes, demonstrating its relative inertness, while platinum and tantalum induced oxidative stress. These findings are further supported by gene and protein level validation using traditional techniques. Together, our findings highlight the potential of inorganic biomaterials in revolutionizing tissue regeneration strategies, which currently rely largely on growth factors and small molecule therapeutics. © 2023, The Authors. All rights reserved.

关键词： Stem cells

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Ranking Magnetic Colloid Performance for Magnetic Particle Imaging and Magnetic Particle Hyperthermia

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Advanced Functional Materials 2025年第2期35卷 2412321页

作者： Carlton, Hayden Salimi, Marzieh Arepally, Nageshwar Bentolila, Gabriela Sharma, Anirudh Bibic, Adnan Newgren, Matt Goodwill, Patrick Attaluri, Anilchandra Korangath, Preethi Bulte, Jeff W.M. Ivkov, Robert Department of Radiation Oncology and Molecular Radiation Sciences the Johns Hopkins University School of Medicine BaltimoreMD21231 United States Russell H. Morgan Department of Radiology and Radiological Science Division of MR Research the Johns Hopkins University School of Medicine BaltimoreMD21205 United States Cellular Imaging Section and Vascular Biology Program Institute for Cell Engineering the Johns Hopkins University School of Medicine BaltimoreMD21205 United States Department of Mechanical Engineering School of Science Engineering and Technology The Pennsylvania State University – Harrisburg HarrisburgPA17057 United States F.M. Kirby Research Center for Functional Brain Imaging Kennedy Krieger Inc. BaltimoreMD21205 United States Magnetic Insight Inc. AlamedaCA94502 United States Department of Biomedical Engineering the Johns Hopkins University School of Medicine BaltimoreMD21205 United States Department of Chemical & Biomolecular Engineering Whiting School of Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Oncology Sydney Kimmel Comprehensive Cancer Center Johns Hopkins University School of Medicine BaltimoreMD21287 United States Department of Mechanical Engineering Whiting School of Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Materials Science and Engineering Whiting School of Engineering Johns Hopkins University BaltimoreMD21218 United States

Magnetic particle imaging (MPI) is an emerging modality that can address longstanding technological challenges encountered with magnetic particle hyperthermia (MPH) cancer therapy. MPI is a tracer technology compatible with MPH for which magnetic nanoparticles (MNPs) provide signal for MPI and heat for MPH. Identifying whether a specific MNP formulation is suitable for both modalities is essential for clinical implementation. Current models predict that functional requirements of each modality impose conflicting demands on nanoparticle magnetic properties. This objective here is to develop a measurement and ranking scheme based on end-use performance to streamline evaluation of candidate MNP formulations. The measured MPI point-spread function (PSF) and specific loss power (SLP) is combined to generate a single numerical value for comparison on a relative ranking scale, or figure of merit (FoM). 12 aqueous iron-containing formulations are evaluated, including FDA-approved (parenteral) iron-containing colloids. MNPs with high (Synomag-D70: 123.4), medium (Synomag-D50: 63.2), and low (NanoXact: 0.147) FoM values are selected for in vivo validation of the selection scheme in subcutaneous 4T1 tumors. Results demonstrate that the proposed ranking accurately assessed the relative performance of MNPs for MPI and MPH. Data demonstrated that image quality and tumor temperature rise increased with FoM ranking, validating predictions. It isshown that the MPI signal correlated with MNP concentration in tissue. Computational heat transfer models anchored on tumor MPI data harmonized with experimental results to within an average of 2 °C when MNP content estimated from MPI data is included. Computational studies emphasized the importance of post-injection MNP quantitation and MPI spatial resolution. © 2024 The Author(s). Advanced Functional Materials published by Wiley-VCH GmbH.

关键词： Hyperthermia therapy

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Correction: Reconsidering invasion history of common land snails in Japan through genome-wide analyses

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Biological Invasions 2023年第11期25卷 3551-3552页

作者： Hirano, Takahiro Yamazaki, Daishi Ito, Shun Sato, Mitsuhiko P. Matsuo, Ayumi Saito, Takumi Nishi, Hirotaka Ye, Bin Dong, Zhengzhong Van Tu, Do Shau-Hwai, Aileen Tan Suyama, Yoshihisa Chiba, Satoshi Center for Northeast Asian Studies Tohoku University Sendai Japan Graduate School of Life Sciences Tohoku University Sendai Japan Biology Program Faculty of Science University of the Ryukyus Okinawa Japan Faculty of Agriculture and Marine Science Kochi University Nankoku Japan Department of Environmental Science Faculty of Science Toho University Funabashi Japan Kazusa DNA Research Institute Kisarazu Japan Kawatabi Field Science Center Graduate School of Agricultural Science Tohoku University Osaki Japan Department of Botany and Zoology Faculty of Science Masaryk University Brno Czech Republic Toyohashi Museum of Natural History Toyohashi Japan Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Agricultural Experiment Station Zhejiang University Hangzhou China Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology Hanoi Vietnam Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi Vietnam School of Biological Sciences Universiti Sains Malaysia Penang Malaysia Centre for Marine and Coastal Studies Universiti Sains Malaysia Penang Malaysia

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Application of Deep Artificial Neural Network to Model Characteristic Fluctuation of Multi-Channel Gate-All-Around Silicon Nanosheet and Nanofin MOSFETs Induced by Random Nanosized Metal Grains

Application of Deep Artificial Neural Network to Model Chara...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sagarika Dash Yiming Li Wen-Li Sung Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Center for mm Wave Smart Radar System and Technologies National Yang-Ming Chiao Tung University Hsinchu Taiwan

In this work, we propose a deep artificial neural network (D-ANN) to estimate the work function fluctuation (WKF) on 4-channel stacked gate-all-around (GAA) silicon (Si) nanosheet (NS) and nanofin (NF) MOSFET devices for the first time. The 2-layered simple deep model can well predict the transfer characteristics for both NS/NF FET with a large number of (128) input features, utilizing considerably lesser (1100 samples) data uniformly. The resultant model is evaluated by the $\mathrm{R}^{2}$ score and RMSE to witness its competency and the average error is $< 4\%$ . We do also discuss the circuit simulation possibility by applying the ANN approach.

关键词： Semiconductor device modeling MOSFET Gallium arsenide Artificial neural networks Predictive models Logic gates Silicon

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Review of Image-Guided Percutaneous Coronary Interventions

Review of Image-Guided Percutaneous Coronary Interventions

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2019 Advances in science and engineering Technology International Conferences, ASET 2019

作者： Alatoom, Aseel Farhat, Jumana Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering Biomedical Engineering Graduate Program Biosciences and Bioengineering Research Institute American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781538682715

Image-guided surgery (IGS) involves using surgical instruments tracking system to guide the surgeon during invasive surgical procedures. The use of preoperative or intraoperative images is very essential in providing navigation for different medical applications. In this paper, a literature review of different imaging modalities that aid in the diagnosis and treatment of coronary artery disease (CAD) is proposed. The imaging modalities discussed include x-ray fluoroscopy, coronary computed tomography angiography (CCTA), fractional flow reserve (FFR), cardiac single-photon emission computed tomography (SPECT), cardiovascular magnetic resonance imaging (CMRI) and ultrasound. Additionally, pseudoaneurysms, which can result from percutaneous coronary interventions (PCI) procedure, are reviewed as well as the treatment procedure. Finally, a comparison between the different imaging modalities is carried out, based on the number of papers that have been published, in addition to the sensitivity and specificity for each modality according to PubMed and Web of science databases. © 2019 IEEE.

关键词： Ultrasonics

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AI-driven 3D Spatial Transcriptomics

arXiv

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arXiv 2025年

作者： Almagro-Pérez, Cristina Song, Andrew H. Weishaupt, Luca Kim, Ahrong Jaume, Guillaume Williamson, Drew F.K. Hemker, Konstantin Lu, Ming Y. Singh, Kritika Chen, Bowen Le, Long Phi Baras, Alexander S. Jiang, Sizun Bashashati, Ali Liu, Jonathan T.C. Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Department of Computer Science & Technology University of Cambridge Cambridge United Kingdom Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Rutgers Robert Wood Johnson Medical School New BrunswickNJ United States Department of Pathology Johns Hopkins Hospital BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins Hospital BaltimoreMD United States Broad Institute of Harvard and MIT CambridgeMA United States Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Harvard Medical School BostonMA United States Department of Pathology Dana Farber Cancer Institute BostonMA United States Department of Pathology and Laboratory Medicine University of British Columbia VancouverBC Canada School of Biomedical Engineering University of British Columbia VancouverBC Canada Department of Mechanical Engineering Bioengineering Laboratory Medicine & Pathology University of Washington SeattleWA United States Harvard Data Science Initiative Harvard University CambridgeMA United States

A comprehensive three-dimensional (3D) map of tissue architecture and gene expression is crucial for illuminating the complexity and heterogeneity of tissues across diverse biomedical applications1. However, most spatial transcriptomics (ST) approaches remain limited to two-dimensional (2D) sections of tissue2–4. Although current 3D ST methods hold promise, they typically require extensive tissue sectioning, are complex, are not compatible with non-destructive 3D tissue imaging technologies, and often lack scalability5–8. Here, we present VOlumetrically Resolved Transcriptomics EXpression (VORTEX), an AI framework that leverages 3D tissue morphology and minimal 2D ST to predict volumetric 3D ST. By pretraining on diverse 3D morphology–transcriptomic pairs from heterogeneous tissue samples and then fine-tuning on minimal 2D ST data from a specific volume of interest, VORTEX learns both generic tissue-related and sample-specific morphological correlates of gene expression. This approach enables dense, high-throughput, and fast 3D ST, scaling seamlessly to large tissue volumes far beyond the reach of existing 3D ST techniques. By offering a cost-effective and minimally destructive route to obtaining volumetric molecular insights, we anticipate that VORTEX will accelerate biomarker discovery and our understanding of morphomolecular associations and cell states in complex tissues. Interactive 3D ST volumes can be viewed at https://***/. © 2025, CC BY-NC-ND.

关键词： Vortex flow

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Hypoglycemic activity of curcuma mangga val. Extract via modulation of GLUT4 and ppar-γ mrna expression in 3T3-L1 adipocytes

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Journal of Experimental Pharmacology 2020年 12卷 363-369页

作者： Pujimulyani, Dwiyati Yulianto, Wisnu Adi Setyowati, Astuti Arumwardana, Seila Kusuma, Hanna Sari Widya Sholihah, Ika Adhani Rizal, Rizal Widowati, Wahyu Maruf, Ali Faculty of Agroindustry University of Mercu Buana Yogyakarta Yogyakarta 55753 Indonesia Biomolecular and Biomedical Research Center Aretha Medika Utama Bandung 40163 Indonesia Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering University of Indonesia Jakarta 16424 Indonesia Medical Research Center Faculty of Medicine Maranatha Christian University Bandung 40164 Indonesia Key Laboratory for Biorheological Science and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular Implants Bioengineering College Faculty of Medicine Chongqing University Chongqing 400030 China

Background: There would be over 600 million people living with diabetes by 2040 as predicted by the World Health Organization. Diabetes is characterized by raised blood sugar and insulin resistance. Insulin regulates the influx of glucose into the cell by upregulating the glucose transporter type 4 (GLUT4) expression on the plasma membrane. Besides, PPAR-γ also controls the metabolism of glucose in adipose tissues. Curcuma mangga Val., denoted as C. mangga, is a native Indonesian medicinal plant that has many beneficial effects, including an antidiabetic potential. Purpose: In this research, we aimed to disclose the hypoglycemic activity of ethanol extract of C. mangga (EECM) in 3T3-L1 fibroblasts-derived adipocyte cells in regulating glucose uptake as confirmed by the GLUT4 and PPAR-γ gene expression. Methods: The uptake of glucose was determined using radioactive glucose, while the gene expression of GLUT4, PPAR-γ, and β-actin was quantified using mRNA segregation and real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Results: We discovered that EECM interventions (200 and 50 μg/mL) increased glucose uptake in lipid-laden 3T3-L1 cells by 14.75 and 8.86 fold compared to the control noninsulin, respectively (p < 0.05). At the same doses, they also increased GLUT4 mRNA expression by 8.41 and 11.18 fold compared to the control non-insulin, respectively (p < 0.05). In contrast, EECM interventions (200 and 50 μg/mL) showed lower levels of PPAR-γ mRNA expression compared to the control metformin, indicating the anti-adipogenic potentials of EECM. Conclusion: EECM showed hypoglycemic activity in lipid-laden 3T3-L1 cells by improving glucose ingestion into the cells, which was mediated by increased GLUT4 expression and downregulated PPAR-γ expression. © 2020 Pujimulyani et al.

关键词： 3T3-L1 adipocytes Curcuma mangga Val Glucose uptake GLUT4 PPAR-γ

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Tempered enthusiasm by interviewed experts for synthetic data and ELSI checklists for AI in medicine

AI and ethics

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AI and ethics 2025年第3期5卷 3241-3254页

作者： Laura Y Cabrera Jennifer Wagner Sara Gerke Daniel Susser Department of Engineering Science and Mechanics Pennsylvania State University W-316 Millennium Science Complex University Park PA 16802 USA. Department of Philosophy Pennsylvania State University University Park PA 16802 USA. Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Rock Ethics Institute Pennsylvania State University University Park PA 16802 USA. Bioethics Program Pennsylvania State University University Park PA 16802 USA. School of Engineering Design and Innovation Pennsylvania State University University Park PA 16802 USA. Department of Anthropology Pennsylvania State University University Park PA 16802 USA. Department of Biomedical Engineering Pennsylvania State University University Park PA 16802 USA. Institute for Computational and Data Sciences Pennsylvania State University University Park PA 16802 USA. College of Law and European Union Center University of Illinois Urbana-Champaign Champaign IL 61820 USA. Department of Information Science Cornell University Ithaca NY 14853 USA.

Synthetic data are increasingly being used in data-driven fields. While synthetic data is a promising tool in medicine, it raises new ethical, legal, and social implications (ELSI) challenges. There is a recognized need for well-designed approaches and standards for documenting and communicating relevant information about artificial intelligence (AI) research datasets and models, including consideration of the many ELSI challenges. This study investigates the ethical dimensions of synthetic data and explores the utility and challenges of ELSI-focused computational checklists for biomedical AI via semi-structure interviews with subject matter experts. Our results suggest that AI experts have tempered views about the promises and challenges of both synthetic data and ELSI-focused computational checklists. Experts discussed a number of ELSI issues covered by previous literature on the topic, such as issues of bias and privacy, yet other less discussed ELSI issues, such as social justice implications and issues of trust were also raised. When discussing ELSI-focused computational checklists our participants highlighted the challenges connected to developing and implementing them.

关键词： Artificial intelligence Computational checklists ELSI Synthetic data

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