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D’Ascenzo N, Antonecchia E, Angiolillo A, Bender V, Camerlenghi M, Xie Q, Di Costanzo A. Metabolomics of blood reveals age-dependent pathways in Parkinson’s Disease. Cell Biosci 2022; 12:102. [PMID: 35794650 PMCID: PMC9258166 DOI: 10.1186/s13578-022-00831-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 06/08/2022] [Indexed: 01/01/2023] Open
Abstract
Background Parkinson’s Disease (PD) is the second most frequent degenerative disorder, the risk of which increases with age. A preclinical PD diagnostic test does not exist. We identify PD blood metabolites and metabolic pathways significantly correlated with age to develop personalized age-dependent PD blood biomarkers. Results We found 33 metabolites producing a receiver operating characteristic (ROC) area under the curve (AUC) value of 97%. PCA revealed that they belong to three pathways with distinct age-dependent behavior: glycine, threonine and serine metabolism correlates with age only in PD patients; unsaturated fatty acids biosynthesis correlates with age only in a healthy control group; and, finally, tryptophan metabolism characterizes PD but does not correlate with age. Conclusions The targeted analysis of the blood metabolome proposed in this paper allowed to find specific age-related metabolites and metabolic pathways. The model offers a promising set of blood biomarkers for a personalized age-dependent approach to the early PD diagnosis. Supplementary Information The online version contains supplementary material available at 10.1186/s13578-022-00831-5.
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D'Ascenzo N, Xie Q, Antonecchia E, Ciardiello M, Pagnani G, Pisante M. Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals. Front Plant Sci 2022; 13:882382. [PMID: 35941942 PMCID: PMC9356293 DOI: 10.3389/fpls.2022.882382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts.
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Affiliation(s)
- Nicola D'Ascenzo
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Qingguo Xie
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
- Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Emanuele Antonecchia
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Mariachiara Ciardiello
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Giancarlo Pagnani
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Michele Pisante
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
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3
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Antonecchia E, Bäcker M, Cafolla D, Ciardiello M, Kühl C, Pagnani G, Wang J, Wang S, Zhou F, D'Ascenzo N, Gialanella L, Pisante M, Rose G, Xie Q. Design Study of a Novel Positron Emission Tomography System for Plant Imaging. Front Plant Sci 2022; 12:736221. [PMID: 35116047 PMCID: PMC8805640 DOI: 10.3389/fpls.2021.736221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 12/06/2021] [Indexed: 06/14/2023]
Abstract
Positron Emission Tomography is a non-disruptive and high-sensitive digital imaging technique which allows to measure in-vivo and non invasively the changes of metabolic and transport mechanisms in plants. When it comes to the early assessment of stress-induced alterations of plant functions, plant PET has the potential of a major breakthrough. The development of dedicated plant PET systems faces a series of technological and experimental difficulties, which make conventional clinical and preclinical PET systems not fully suitable to agronomy. First, the functional and metabolic mechanisms of plants depend on environmental conditions, which can be controlled during the experiment if the scanner is transported into the growing chamber. Second, plants need to be imaged vertically, thus requiring a proper Field Of View. Third, the transverse Field of View needs to adapt to the different plant shapes, according to the species and the experimental protocols. In this paper, we perform a simulation study, proposing a novel design of dedicated plant PET scanners specifically conceived to address these agronomic issues. We estimate their expected sensitivity, count rate performance and spatial resolution, and we identify these specific features, which need to be investigated when realizing a plant PET scanner. Finally, we propose a novel approach to the measurement and verification of the performance of plant PET systems, including the design of dedicated plant phantoms, in order to provide a standard evaluation procedure for this emerging digital imaging agronomic technology.
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Affiliation(s)
- Emanuele Antonecchia
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | - Markus Bäcker
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Daniele Cafolla
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | | | - Charlotte Kühl
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Giancarlo Pagnani
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Jiale Wang
- School of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute of University of Science and Technology of China, Quzhou, China
| | - Shuai Wang
- School of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute of University of Science and Technology of China, Quzhou, China
| | - Feng Zhou
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
| | - Nicola D'Ascenzo
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | - Lucio Gialanella
- Department of Mathematics and Physics, University of Campania L. Vanvitelli, Caserta, Italy
| | - Michele Pisante
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Georg Rose
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Qingguo Xie
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
- Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
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4
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Ba L, Huang L, He Z, Deng S, Xie Y, Zhang M, Jacob C, Antonecchia E, Liu Y, Xiao W, Xie Q, Huang Z, Yi C, D'Ascenzo N, Ding F. Does Chronic Sleep Fragmentation Lead to Alzheimer's Disease in Young Wild-Type Mice? Front Aging Neurosci 2022; 13:759983. [PMID: 34992526 PMCID: PMC8724697 DOI: 10.3389/fnagi.2021.759983] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/22/2021] [Indexed: 12/18/2022] Open
Abstract
Chronic sleep insufficiency is becoming a common issue in the young population nowadays, mostly due to life habits and work stress. Studies in animal models of neurological diseases reported that it would accelerate neurodegeneration progression and exacerbate interstitial metabolic waste accumulation in the brain. In this paper, we study whether chronic sleep insufficiency leads to neurodegenerative diseases in young wild-type animals without a genetic pre-disposition. To this aim, we modeled chronic sleep fragmentation (SF) in young wild-type mice. We detected pathological hyperphosphorylated-tau (Ser396/Tau5) and gliosis in the SF hippocampus. 18F-labeled fluorodeoxyglucose positron emission tomography scan (18F-FDG-PET) further revealed a significant increase in brain glucose metabolism, especially in the hypothalamus, hippocampus and amygdala. Hippocampal RNAseq indicated that immunological and inflammatory pathways were significantly altered in 1.5-month SF mice. More interestingly, differential expression gene lists from stress mouse models showed differential expression patterns between 1.5-month SF and control mice, while Alzheimer's disease, normal aging, and APOEε4 mutation mouse models did not exhibit any significant pattern. In summary, 1.5-month sleep fragmentation could generate AD-like pathological changes including tauopathy and gliosis, mainly linked to stress, as the incremented glucose metabolism observed with PET imaging suggested. Further investigation will show whether SF could eventually lead to chronic neurodegeneration if the stress condition is prolonged in time.
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Affiliation(s)
- Li Ba
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lifang Huang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ziyu He
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Saiyue Deng
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Xie
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cornelius Jacob
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Emanuele Antonecchia
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo Neuromed Istituto di Ricovero e Cura a Carattere Scientifico (I.R.C.C.S.), Pozzilli, Italy
| | - Yuqing Liu
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Wenchang Xiao
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Qingguo Xie
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo Neuromed Istituto di Ricovero e Cura a Carattere Scientifico (I.R.C.C.S.), Pozzilli, Italy.,Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Zhili Huang
- Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chenju Yi
- Research Centre, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Nicola D'Ascenzo
- Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo Neuromed Istituto di Ricovero e Cura a Carattere Scientifico (I.R.C.C.S.), Pozzilli, Italy
| | - Fengfei Ding
- Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, China
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Hu X, Liang X, Antonecchia E, Chiaravallotti A, Chu Q, Han S, Li Z, Wan L, D'Ascenzo N, Schillaci O, Xie Q. 3-D Textural Analysis of 2-[¹⁸F]FDG PET and Ki67 Expression in Nonsmall Cell Lung Cancer. IEEE Trans Radiat Plasma Med Sci 2022. [DOI: 10.1109/trpms.2021.3051376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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6
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Li J, Antonecchia E, Camerlenghi M, Chiaravalloti A, Chu Q, Costanzo AD, Li Z, Wan L, Zhang X, D'Ascenzo N, Schillaci O, Xie Q. Correlation of [ 18F]florbetaben textural features and age of onset of Alzheimer's disease: a principal components analysis approach. EJNMMI Res 2021; 11:40. [PMID: 33881633 PMCID: PMC8060386 DOI: 10.1186/s13550-021-00774-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 03/15/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND When Alzheimer's disease (AD) is occurring at an early onset before 65 years old, its clinical course is generally more aggressive than in the case of a late onset. We aim at identifying [[Formula: see text]F]florbetaben PET biomarkers sensitive to differences between early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). We conducted [[Formula: see text]F]florbetaben PET/CT scans of 43 newly diagnosed AD subjects. We calculated 93 textural parameters for each of the 83 Hammers areas. We identified 41 independent principal components for each brain region, and we studied their Spearman correlation with the age of AD onset, by taking into account multiple comparison corrections. Finally, we calculated the probability that EOAD and LOAD patients have different amyloid-[Formula: see text] ([Formula: see text]) deposition by comparing the mean and the variance of the significant principal components obtained in the two groups with a 2-tailed Student's t-test. RESULTS We found that four principal components exhibit a significant correlation at a 95% confidence level with the age of onset in the left lateral part of the anterior temporal lobe, the right anterior orbital gyrus of the frontal lobe, the right lateral orbital gyrus of the frontal lobe and the left anterior part of the superior temporal gyrus. The data are consistent with the hypothesis that EOAD patients have a significantly different [[Formula: see text]F]florbetaben uptake than LOAD patients in those four brain regions. CONCLUSIONS Early-onset AD implies a very irregular pattern of [Formula: see text] deposition. The authors suggest that the identified textural features can be used as quantitative biomarkers for the diagnosis and characterization of EOAD patients.
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Affiliation(s)
- Jing Li
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China
| | - Emanuele Antonecchia
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China.,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy
| | - Marco Camerlenghi
- NIM Competence Center for Digital Healthcare GmbH, Potsdamerplatz, 10, 10785, Berlin, Germany
| | - Agostino Chiaravalloti
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy. .,Department of Biomedicine and Prevention, University of Tor Vergata, 86100, Rome, Italy.
| | - Qian Chu
- Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road, Wuhan, 430030, China.,Department of Oncology, Tongji Hospital, Jiefang Avenue, Wuhan, 430030, China
| | - Alfonso Di Costanzo
- Universita degli Studi del Molise, Via Francesco de Sanctis, 1, 10115, Campobasso, Italy
| | - Zhen Li
- Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road, Wuhan, 430030, China.,Department of Radiology, Tongji Hospital, Jiefang Avenue, Wuhan, 430030, China
| | - Lin Wan
- Department of Software Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China
| | - Xiangsong Zhang
- The First Affiliated Hospital, Sun Yat-sen University, Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Nicola D'Ascenzo
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China. .,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.
| | - Orazio Schillaci
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.,Department of Biomedicine and Prevention, University of Tor Vergata, 86100, Rome, Italy
| | - Qingguo Xie
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Luoyu Road, Wuhan, 430074, China. .,Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S, Via Dell'Elettronica, 83008, Pozzilli, Italy.
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Liang X, Li J, Antonecchia E, Ling Y, Li Z, Xiao W, Chu Q, Wan L, Hu X, Han S, Teuho J, Wan L, Xiao P, Kao CM, Knuuti J, D'Ascenzo N, Xie Q. NEMA-2008 and In-Vivo Animal and Plant Imaging Performance of the Large FOV Preclinical Digital PET/CT System Discoverist 180. IEEE Trans Radiat Plasma Med Sci 2020. [DOI: 10.1109/trpms.2020.2983221] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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8
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D'Ascenzo N, Antonecchia E, Gao M, Zhang X, Baumgartner G, Brensing A, Li Z, Liu Q, Rose G, Shi X, Zhang B, Kao CM, Ni J, Xie Q. Evaluation of a Digital Brain Positron Emission Tomography Scanner Based on the Plug&Imaging Sensor Technology. IEEE Trans Radiat Plasma Med Sci 2020. [DOI: 10.1109/trpms.2019.2937681] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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9
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Pavesi A, Tan AT, Koh S, Chia A, Colombo M, Antonecchia E, Miccolis C, Ceccarello E, Adriani G, Raimondi MT, Kamm RD, Bertoletti A. A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors. JCI Insight 2017; 2:89762. [PMID: 28614795 DOI: 10.1172/jci.insight.89762] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 05/10/2017] [Indexed: 02/06/2023] Open
Abstract
The tumor microenvironment imposes physical and functional constraints on the antitumor efficacy of adoptive T cell immunotherapy. Preclinical testing of different T cell preparations can help in the selection of efficient immune therapies, but in vivo models are expensive and cumbersome to develop, while classical in vitro 2D models cannot recapitulate the spatiotemporal dynamics experienced by T cells targeting cancer. Here, we describe an easily customizable 3D model, in which the tumor microenvironment conditions are modulated and the functionality of different T cell preparations is tested. We incorporate human cancer hepatocytes as a single cell or as tumor cell aggregates in a 3D collagen gel region of a microfluidic device. Human T cells engineered to express tumor-specific T cell receptors (TCR-T cells) are then added in adjacent channels. The TCR-T cells' ability to migrate and kill the tumor target and the profile of soluble factors were investigated under conditions of varying oxygen levels and in the presence of inflammatory cytokines. We show that only the 3D model detects the effect that oxygen levels and the inflammatory environment impose on engineered TCR-T cell function, and we also used the 3D microdevice to analyze the TCR-T cell efficacy in an immunosuppressive scenario. Hence, we show that our microdevice platform enables us to decipher the factors that can alter T cell function in 3D and can serve as a preclinical assay to tailor the most efficient immunotherapy configuration for a specific therapeutic goal.
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Affiliation(s)
- Andrea Pavesi
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research, Singapore.,BioSystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, Singapore
| | - Anthony T Tan
- Emerging Infectious Disease Program, Duke-NUS Graduate Medical School, Singapore
| | - Sarene Koh
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore
| | - Adeline Chia
- Emerging Infectious Disease Program, Duke-NUS Graduate Medical School, Singapore
| | - Marta Colombo
- Department of Chemistry, Materials and Chemical Engineering "Giulio Natta," Politecnico di Milano, Milan, Italy
| | - Emanuele Antonecchia
- Department of Chemistry, Materials and Chemical Engineering "Giulio Natta," Politecnico di Milano, Milan, Italy
| | - Carlo Miccolis
- Department of Chemistry, Materials and Chemical Engineering "Giulio Natta," Politecnico di Milano, Milan, Italy
| | - Erica Ceccarello
- Emerging Infectious Disease Program, Duke-NUS Graduate Medical School, Singapore
| | - Giulia Adriani
- BioSystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, Singapore
| | - Manuela T Raimondi
- Department of Chemistry, Materials and Chemical Engineering "Giulio Natta," Politecnico di Milano, Milan, Italy
| | - Roger D Kamm
- BioSystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, Singapore.,MechanoBiology Laboratory, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Antonio Bertoletti
- Emerging Infectious Disease Program, Duke-NUS Graduate Medical School, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore
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