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Zarkali A, Thomas GEC, Zetterberg H, Weil RS. Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions. Nat Commun 2024; 15:5661. [PMID: 38969680 PMCID: PMC11226684 DOI: 10.1038/s41467-024-49949-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 06/19/2024] [Indexed: 07/07/2024] Open
Abstract
A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.
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Affiliation(s)
- Angeliki Zarkali
- Dementia Research Centre, Institute of Neurology, UCL, London, UK.
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Rimona S Weil
- Dementia Research Centre, Institute of Neurology, UCL, London, UK
- Department of Advanced Neuroimaging, UCL, London, UK
- Movement Disorders Centre, UCL, London, UK
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Bertran-Cobo C, Dumont E, Noordin NR, Lai MY, Stone W, Tetteh KK, Drakeley C, Krishna S, Lau YL, Wassmer SC. Plasmodium knowlesi infection is associated with elevated circulating biomarkers of brain injury and endothelial activation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306382. [PMID: 38712121 PMCID: PMC11071568 DOI: 10.1101/2024.04.25.24306382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Introduction Malaria remains a major public health concern with substantial morbidity and mortality worldwide. In Malaysia, the emergence of Plasmodium knowlesi has led to a surge in zoonotic malaria cases and deaths in recent years. Signs of cerebral involvement have been observed in a non-comatose, fatal case of severe knowlesi infection, but the potential impact of this malaria species on the brain remains underexplored. To address this gap, we investigated circulating levels of brain injury, inflammation, and vascular biomarkers in a cohort of knowlesi-infected patients and controls. Methods Archived plasma samples from 19 patients with confirmed symptomatic knowlesi infection and 19 healthy, age-matched controls from Peninsular Malaysia were analysed. A total of 52 plasma biomarkers of brain injury, inflammation, and vascular activation were measured using Luminex and SIMOA assays. Wilcoxon tests were used to examine group differences, and biomarker profiles were explored through hierarchical clustering heatmap analysis. Results Bonferroni-corrected analyses revealed significantly elevated brain injury biomarker levels in knowlesi-infected patients, including S100B (p<0.0001), Tau (p=0.0007), UCH-L1 (p<0.0001), αSyn (p<0.0001), Park7 (p=0.0006), NRGN (p=0.0022), and TDP-43 (p=0.005). Compared to controls, levels were lower in the infected group for BDNF (p<0.0001), CaBD (p<0.0001), CNTN1 (p<0.0001), NCAM-1 (p<0.0001), GFAP (p=0.0013), and KLK6 (p=0.0126). Hierarchical clustering revealed distinct group profiles for circulating levels of brain injury and vascular activation biomarkers. Conclusions Our findings highlight for the first time the impact of Plasmodium knowlesi infection on the brain, with distinct alterations in cerebral injury and endothelial activation biomarker profiles compared to healthy controls. Further studies are warranted to investigate the pathophysiology and clinical significance of these altered surrogate markers, through both neuroimaging and long-term neurocognitive assessments.
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Bao LX, Luo ZM, Zhu XL, Xu YY. Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images. Med Biol Eng Comput 2024; 62:1105-1119. [PMID: 38150111 DOI: 10.1007/s11517-023-02985-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 11/28/2023] [Indexed: 12/28/2023]
Abstract
Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular location in different mouse brain regions from immunofluorescence images. The brain regions and sub-regions were segmented through learning image features using an autoencoder and then performing K-means clustering and registration to align with the anatomical references. The protein expression intensities for those segmented structures were computed on the basis of the statistics of the image pixels, and patch-based weakly supervised methods and multi-instance learning were used to classify the cellular locations. Results demonstrated that the models achieved high accuracy in the expression intensity estimation, and the F1 score of the cellular location prediction was 74.5%. This work established an automated pipeline for analyzing mouse brain images and provided a foundation for further study of protein expression and functions.
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Affiliation(s)
- Lin-Xia Bao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
- Guangdong Provincial Key Laboratory of Medical Imaging Processing, Southern Medical University, Guangzhou, 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510623, China
| | - Zhuo-Ming Luo
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
- Guangdong Provincial Key Laboratory of Medical Imaging Processing, Southern Medical University, Guangzhou, 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510623, China
| | - Xi-Liang Zhu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
- Guangdong Provincial Key Laboratory of Medical Imaging Processing, Southern Medical University, Guangzhou, 510515, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510623, China
| | - Ying-Ying Xu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.
- Guangdong Provincial Key Laboratory of Medical Imaging Processing, Southern Medical University, Guangzhou, 510515, China.
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, 510623, China.
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Contini C, Fadda L, Lai G, Masala C, Olianas A, Castagnola M, Messana I, Iavarone F, Bizzarro A, Masullo C, Solla P, Defazio G, Manconi B, Diaz G, Cabras T. A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls. Proteomics 2024; 24:e2300202. [PMID: 37541286 DOI: 10.1002/pmic.202300202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/06/2023]
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.
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Affiliation(s)
- Cristina Contini
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Laura Fadda
- Department of Medical Sciences and Public Health, Institute of Neurology, Cagliari, Italy
| | - Greca Lai
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Carla Masala
- Department of Biomedical Sciences University of Cagliari, Cittadella Univ. Monserrato, Monserrato, Italy
| | - Alessandra Olianas
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Massimo Castagnola
- Proteomics Laboratory. European Center for Brain Research, (IRCCS) Santa Lucia Foundation, Rome, Italy
| | - Irene Messana
- Consiglio Nazionale delle Ricerche, Istituto di Scienze e Tecnologie Chimiche "Giulio Natta", Rome, Italy
| | - Federica Iavarone
- Department of Basic Biotechnological Sciences, Intensive and Perioperative Clinics, Rome, Italy
- Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
| | - Alessandra Bizzarro
- Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
- Department of Geriatrics, Orthopaedics and Rheumatology, Rome, Italy
| | - Carlo Masullo
- Department of Neuroscience, Neurology Section, Università Cattolica del Sacro Cuore Rome, Rome, Italy
| | - Paolo Solla
- Neurological Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, Sassari, Italy
| | - Giovanni Defazio
- Department of Medical Sciences and Public Health, Institute of Neurology, Cagliari, Italy
| | - Barbara Manconi
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Giacomo Diaz
- Department of Biomedical Sciences University of Cagliari, Cittadella Univ. Monserrato, Monserrato, Italy
| | - Tiziana Cabras
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
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Hepp DH, van Wageningen TA, Kuiper KL, van Dijk KD, Oosterveld LP, Berendse HW, van de Berg WDJ. Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease. Int J Mol Sci 2023; 24:14915. [PMID: 37834363 PMCID: PMC10573398 DOI: 10.3390/ijms241914915] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
An altered immune response has been identified as a pathophysiological factor in Parkinson's disease (PD). We aimed to identify blood immunity-associated proteins that discriminate PD from controls and that are associated with long-term disease severity in PD patients. Immune response-derived proteins in blood plasma were measured using Proximity Extension Technology by OLINK in a cohort of PD patients (N = 66) and age-matched healthy controls (N = 52). In a selection of 30 PD patients, we evaluated changes in protein levels 7-10 years after the baseline and assessed correlations with motor and cognitive assessments. Data from the Parkinson's Disease Biomarkers Program (PDBP) cohort and the Parkinson's Progression Markers Initiative (PPMI) cohort were used for independent validation. PD patients showed an altered immune response compared to controls based on a panel of four proteins (IL-12B, OPG, CXCL11, and CSF-1). The expression levels of five inflammation-associated proteins (CCL23, CCL25, TNFRSF9, TGF-alpha, and VEGFA) increased over time in PD and were partially associated with more severe motor and cognitive symptoms at follow-up. Increased CCL23 levels were associated with cognitive decline and the APOE4 genotype. Our findings provide further evidence for an altered immune response in PD that is associated with disease severity in PD over a long period of time.
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Affiliation(s)
- Dagmar H. Hepp
- Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; (D.H.H.)
- Department of Neurology, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1117, 1081 HZ Amsterdam, The Netherlands;
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
| | - Thecla A. van Wageningen
- Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; (D.H.H.)
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
| | - Kirsten L. Kuiper
- Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; (D.H.H.)
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
| | - Karin D. van Dijk
- Sleep Wake Centre, Stichting Epilepsie Instellingen Nederland (SEIN), 2103 SW Heemstede, The Netherlands
| | - Linda P. Oosterveld
- Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; (D.H.H.)
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
| | - Henk W. Berendse
- Department of Neurology, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1117, 1081 HZ Amsterdam, The Netherlands;
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
| | - Wilma D. J. van de Berg
- Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, de Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; (D.H.H.)
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands
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Salluzzo M, Vianello C, Abdullatef S, Rimondini R, Piccoli G, Carboni L. The Role of IgLON Cell Adhesion Molecules in Neurodegenerative Diseases. Genes (Basel) 2023; 14:1886. [PMID: 37895235 PMCID: PMC10606101 DOI: 10.3390/genes14101886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/29/2023] Open
Abstract
In the brain, cell adhesion molecules (CAMs) are critical for neurite outgrowth, axonal fasciculation, neuronal survival and migration, and synapse formation and maintenance. Among CAMs, the IgLON family comprises five members: Opioid Binding Protein/Cell Adhesion Molecule Like (OPCML or OBCAM), Limbic System Associated Membrane Protein (LSAMP), neurotrimin (NTM), Neuronal Growth Regulator 1 (NEGR1), and IgLON5. IgLONs exhibit three N-terminal C2 immunoglobulin domains; several glycosylation sites; and a glycosylphosphatidylinositol anchoring to the membrane. Interactions as homo- or heterodimers in cis and in trans, as well as binding to other molecules, appear critical for their functions. Shedding by metalloproteases generates soluble factors interacting with cellular receptors and activating signal transduction. The aim of this review was to analyse the available data implicating a role for IgLONs in neuropsychiatric disorders. Starting from the identification of a pathological role for antibodies against IgLON5 in an autoimmune neurodegenerative disease with a poorly understood mechanism of action, accumulating evidence links IgLONs to neuropsychiatric disorders, albeit with still undefined mechanisms which will require future thorough investigations.
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Affiliation(s)
- Marco Salluzzo
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy;
| | - Clara Vianello
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (C.V.); (R.R.)
| | - Sandra Abdullatef
- Department of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy; (S.A.); (G.P.)
| | - Roberto Rimondini
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy; (C.V.); (R.R.)
| | - Giovanni Piccoli
- Department of Cellular, Computational and Integrative Biology, University of Trento, 38123 Trento, Italy; (S.A.); (G.P.)
| | - Lucia Carboni
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy;
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Li Y, Tam WW, Yu Y, Zhuo Z, Xue Z, Tsang C, Qiao X, Wang X, Wang W, Li Y, Tu Y, Gao Y. The application of Aptamer in biomarker discovery. Biomark Res 2023; 11:70. [PMID: 37468977 DOI: 10.1186/s40364-023-00510-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 06/29/2023] [Indexed: 07/21/2023] Open
Abstract
Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.
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Affiliation(s)
- Yongshu Li
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China.
| | - Winnie Wailing Tam
- Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Yuanyuan Yu
- Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Zhenjian Zhuo
- State Key Laboratory of Chemical Oncogenomic, Peking University Shenzhen Graduate School, Shenzhen, China
- Laboratory Animal Center, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Zhichao Xue
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China
| | - Chiman Tsang
- Department of Anatomical and Cellular Pathology, State Key Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong, China
| | - Xiaoting Qiao
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Xiaokang Wang
- Department of Pharmacy, Shenzhen Longhua District Central Hospital, Shenzhen, China
| | - Weijing Wang
- Shantou University Medical College, Shantou, China
| | - Yongyi Li
- Laboratory Animal Center, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Yanyang Tu
- Research Center, Huizhou Central People's Hospital, Guangdong Medical University, Huizhou City, China.
| | - Yunhua Gao
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China.
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