Anastasia Yendiki

Associate Professor

Director of Circuit Analysis
Laboratory for Computational Neuroimaging (LCN)

ayendiki@mgh.harvard.edu

Tagged:Algorithm Development, Brain, Brain Mapping, Data Science, Diffusion MRI, FreeSurfer, Machine Learning, Software Development

Dr. Anastasia Yendiki’s background is in statistical signal and image processing. She received a PhD in Electrical Engineering: Systems from the University of Michigan at Ann Arbor, where she worked on inverse problems in tomographic reconstruction for nuclear imaging under the supervision of Jeff Fessler. As a postdoctoral research fellow at the Athinoula A. Martinos Center for Biomedigal Imaging, Harvard Medical School and Massachusetts General Hospital, she trained in functional and diffusion-weighted MRI. She received an NIH K99/R00 Pathway to Independence award, which led to the development of TRACULA, the diffusion-weighted MRI analysis stream in FreeSurfer, under the supervision of Bruce Fischl. She is now on the faculty at the Martinos Center and a member of the Laboratory for Computational Neuroimaging (LCN), continuing to develop publicly available, open-source algorithms for studying white-matter anatomy in health and disease.

Education

PhD in Electrical Engineering: Systems, University of Michigan at Ann Arbor

Select Publications

1. Haber SN, Lehman J, Maffei C, Yendiki A. The Rostral Zona Incerta: A Subcortical Integrative Hub and Potential Deep Brain Stimulation Target for Obsessive-Compulsive Disorder. Biol Psychiatry. 2023 Jun 1;93(11):1010-1022.

2. Yendiki A, Aggarwal M, Axer M, Howard AFD, van Walsum AVC, Haber SN. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage. 2022 Aug 1;256:119146.

3. Maffei C, Lee C, Planich M, Ramprasad M, Ravi N, Trainor D, Urban Z, Kim M, Jones RJ, Henin A, Hofmann SG, Pizzagalli DA, Auerbach RP, Gabrieli JDE, Whitfield-Gabrieli S, Greve DN, Haber SN, Yendiki A. Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data. Neuroimage. 2021 Dec 15;245:118706.

Highlights

Large-scale Imaging of Neural Circuits (LINC): A BRAIN CONNECTS Center

OHBM2022: Keynote Interview with Anastasia Yendiki: On Track with Anastasia

OHBM Neurosaliance Podcast: Anastasia Yendiki: Diffusion-based tract tracing tool developer and validator

Website

Diffusion MRI at the Martinos Center @ MGH

Caterina Mainero

Associate Professor

Multiple Sclerosis Imaging Laboratory (Director)

CMAINERO@mgh.harvard.edu

Caterina Mainero, MD, PhD, is an Associate Professor of Radiology at Harvard Medical School, Assistant in Neuroscience at Massachusetts General Hospital and Director of Multiple Sclerosis Research at the Athinoula A. Martinos Center for Biomedical Imaging.

Dr. Mainero is a neuroscientist with a background in clinical neurology, specializing in the translation of novel multimodal imaging techniques for investigating structure, function and pathology within the brain and spinal cord of different neurological conditions, with a particular emphasis on multiple sclerosis and migraine.

The Multiple Sclerosis Imaging Laboratory that Dr. Mainero directs at the Martinos Center focuses on using advanced imaging modalities to investigate the heterogenous aspects of multiple sclerosis pathology that include neuroinflammation, demyelination, neurodegeneration, and tissue repair. The goal is to integrate novel imaging methods with clinical and biological markers of the disease to investigate the brain mechanisms underlying disease activity and progression, and to define the most sensitive neuroimaging tools for improving disease diagnosis and monitoring.

Dr. Mainero’s group was the first to image and characterize in vivo, using ultra high field 7 Tesla MRI, the different types of cortical multiple sclerosis lesions described by neuropathology, and to show that the cortical lesion load assessed at 7 Tesla is an independent and main predictor of disease progression. For her pioneering work on imaging cortical lesions in MS, Dr. Mainero has been awarded the “2020 Distinguished Investigator Award” from the Academy for Radiology and Biomedical Imaging Research.

Highlights

MGH Claflin Distinguished Award

2020 Distinguished Investigator Award, Academy for Radiology and Biomedical Imaging Research

Select Publications

See PubMed for a list of Dr. Mainero’s publications.

Website

Multiple Sclerosis Imaging Laboratory

Matthew Rosen

Associate Professor

Low-field MRI and Hyperpolarized Media Laboratory (Director)

msrosen@mgh.harvard.edu
617-643-8636

Dr. Matt Rosen is a physicist, tool-builder and inventor whose research bridges the spectrum from fundamental physics to applied bioimaging work in the field of MRI. He established the Low-Field MRI and Hyperpolarized Media Laboratory at the Athinoula A. Martinos Center for Biomedical Imaging to focus on the continued development of new hyperpolarization methods and MRI-based tools.

The Rosen Lab focuses on new methods and tools to enable unconventional approaches to MRI scanner construction. This includes the development of new acquisition strategies for robust ultra-low magnetic field implementations of MRI focused on brain imaging. The laboratory also explores opportunities provided by hyperpolarization including in vivo Overhauser DNP, SABRE and spin-exchange optical pumping. The lab creates new quantitative strategies for the acquisition and the reconstruction of highly undersampled imaging data including neural network deep learning-based approaches such as AUTOMAP that leverage low-cost scalable-compute. Dr. Rosen co-directs the Center for Machine Learning at the Martinos Center.

Education

PhD in Physics, University of Michigan, Ann Arbor

Select Publications

[1] K. N. Sheth, M. H. Mazurek, M. M. Yuen, B. A. Cahn, J. T. Shah, A. Ward, J. A. Kim, E. J. Gilmore, G. J. Falcone, N. Petersen, K. T. Gobeske, F. Kaddouh, D. Y. Hwang, J. Schindler, L. Sansing, C. Matouk, J. Rothberg, G. Sze, J. Siner, M. S. Rosen, S. Spudich, and W. T. Kimberly, “Assessment of Brain Injury Using Portable, Low-Field Magnetic Resonance Imaging at the Bedside of Critically Ill Patients,” JAMA Neurol, Sep. 2020.
https://jamanetwork.com/journals/jamaneurology/fullarticle/2769858

[2] D. E. J. Waddington, T. Boele, R. Maschmeyer, Z. Kuncic, and M. S. Rosen, “High-sensitivity in vivo contrast for ultra-low field magnetic resonance imaging using superparamagnetic iron oxide nanoparticles,” Science Advances, vol. 6, no. 29, p. eabb0998, Jul. 2020.
https://advances.sciencemag.org/content/6/29/eabb0998

[3] B. Zhu, J. Z. Liu, S. F. Cauley, B. R. Rosen, and M. S. Rosen, “Image reconstruction by domain-transform manifold learning ,” Nature, vol. 555, no. 7697, pp. 487–492, Mar. 2018.
https://www.nature.com/articles/nature25988

[4] M. Sarracanie, C. D. LaPierre, N. Salameh, D. E. J. Waddington, T. Witzel, and M. S. Rosen, “Low-Cost High-Performance MRI,” Sci Rep, vol. 5, no. 1, p. 15177, Oct. 2015.
https://www.nature.com/articles/srep15177

Highlights

Co-founder: Hyperfine Research, BlinkAI, Vizma Life Sciences, Intact Data Services

Website

Rosen Lab

David Salat

Associate Professor

Brain Aging and Dementia (BAnD) Laboratory (Director)
The Translational Research Center for TBI and Stress Disorders (TRACTS)

salat@nmr.mgh.harvard.edu

The overarching aim of Dr. Salat’s work is to understand mechanisms of neural disease and to implement novel approaches to reduce the impact of disease on the brain, cognition and clinical status. Clinically, there are two main clinical foci to his research. At the MGH Martinos Center, he directs the Brain Aging and Dementia Laboratory, with a research focus on understanding systemic and neural mechanisms of age-associated cognitive decline and dementia. A major focus of this work is to understand cerebrovascular contributions to brain aging and dementia. He is also the MGH site Principal Investigator for the Human Connectome Project – Mapping the Human Connectome with Typical Aging multisite effort (Central PI: Van Essen).

Education

PhD in Behavioral Neuroscience, Oregon Health & Science University

Select Publications

1. Bookheimer SY, Salat DH, Terpstra M, Ances BM, Barch DM, Buckner RL, et al. The Lifespan Human Connectome Project in Aging: An overview. Neuroimage. 2019;185:335-48.

2. Sitnikova TA, Hughes JW, Ahlfors SP, Woolrich MW, Salat DH. Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer’s disease. Neuroimage Clin. 2018;20:128-52.

3. Robinson ME, Clark DC, Milberg WP, McGlinchey RE, Salat DH. Characterization of Differences in Functional Connectivity Associated with Close-Range Blast Exposure. J Neurotrauma. 2017;34(S1):S53-S61.

Websites

Brain Aging and Dementia (BAnD) Laboratory
The Translational Research Center for TBI and Stress Disorders (TRACTS)

Douglas Greve

Associate Professor

Laboratory for Computational Neuroimaging (LCN)

dgreve@mgh.harvard.edu
617-724-2358

Tagged:Aging, Algorithm Development, Alzheimer's Disease, bbregister, Brain, Data Science, Diffusion MRI, fMRI, FreeSurfer, FSFAST, Functional Magnetic Resonance Imaging, Machine Learning, Meditation, optseq, PET, PETsurfer, Positron Emission Tomography, Software Development

Douglas Greve, PhD, has a passion for delivering cutting-edge tools to the neuroscience community. He joined the FreeSurfer team 20 years ago and has been developing neuroimaging software ever since. His career has offered him an exciting mixture of engineering, physics, software development and neuroscience. He understands the biophysics of many brain imaging modalities (e.g., MRI structural, fMRI, DTI, MRS, as well as PET). He has especially enjoyed collaborating with experts from neurology, psychiatry and psychology — they know what tools they need to study their diseases, and he knows how to realize those tools through technology.

Education

PhD in Cognitive and Neural Systems, Boston University

Publications

1. Greve DN, Fischl B. False positive rates in surface-based anatomical analysis. Neuroimage. 2018 May 1;171:6-14.

2. Greve DN, Salat DH, Bowen SL, Izquierdo-Garcia D, Schultz AP, Catana C, Becker JA, Svarer C, Knudsen GM, Sperling RA, Johnson KA. Different partial volume correction methods lead to different conclusions: An (18)F-FDG-PET study of aging. Neuroimage. 2016 May 15;132:334-343.

3. Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009 Oct 15;48(1):63-72.

Highlights

FreeSurfer software development
Group statistics for neuroimaging
Multi-modal neuroimaging integration
PET partial volume correction
Surface-based kinetic modeling

Website

Laboratory for Computational Neuroimaging

Jerome Ackerman

Associate Professor

15T and Extremity Scanner Labs (Director)

jerry@nmr.mgh.harvard.edu
617-726-3083

Tagged:Algorithm Development, High-field Imaging, Interventional MR, Magnetic Resonance Imaging, Metabolic Bone Disease, MRI, Point of Care MR, Preclinical, Scanner and Interventional Device Development, Skeleton, Solid State MR Imaging and Spectroscopy, Spectroscopy

Jerome Ackerman, PhD, has conducted research in magnetic resonance for over 45 years, and has led the solid-state MR program at MGH for over 30 years. As of May, 2019, his work (over 100 peer-reviewed journal articles, reviews, chapters and patents; over 200 abstracts) has been cited 5048 times (886 times since 2014). He has trained or supervised approximately 53 postdoctoral fellows and PhD, MS and undergraduate students and two staff engineers (prime faculty advisor for eight PhD and three MS dissertations, mentor for one K99/R00 awardee) and hosted two visiting scientists.

He has been developing NMR spectrometers and MRI scanners and their associated components and software since the 1970s. In the Martinos Center, he has been the Principal Investigator of four Shared Instrumentation and High End Instrumentation grants. Also, he pioneered the first use of high-resolution magic angle spinning (HRMAS) spectroscopy for tissue specimens, the use of true solid-state MRI for MR-PET attenuation correction, and the use of RF microcoils for position tracking.

Education

PhD in Physical Chemistry (Solid State NMR Spectroscopy), Massachusetts Institute of Technology (MIT)

Select Publications

1. Wu Y, Chesler DA, Glimcher MJ, Garrido L, Wang J, Jiang HJ, et al. Multinuclear solid-state three-dimensional MRI of bone and synthetic calcium phosphates. Proc Natl Acad Sci U S A. 1999;96(4):1574-8.

2. Cho G, Wu Y, Ackerman JL. Detection of hydroxyl ions in bone mineral by solid-state NMR spectroscopy. Science. 2003;300(5622):1123-7.

3. Cohen O, Zhao M, Nevo E, Ackerman JL. MR Coagulation: A Novel Minimally Invasive Approach to Aneurysm Repair. J Vasc Interv Radiol. 2017;28(11):1592-8.

Highlights

Dr. Ackerman’s current interests include:

Development of a cryogen-free compact point-of-care superconducting extremity MRI scanner for conventional and solid state MR characterization of bone (collaboration with Superconducting Systems, Inc.)
A magnesium diboride/solid nitrogen table-top superconducting MRI scanner (collaboration with MIT)
Ultrahigh field (15T) MR
MR-mediated RF ablation and coagulation technologies in which the scanner sources and controls the energy for these interventional procedures (collaboration with Robin Medical, Inc.)

Website

15T MR Laboratory

Steven Stufflebeam

Associate Professor

Stufflebeam Laboratory (PI), TMS Lab, The David Cohen MEG Laboratory

sms@nmr.mgh.harvard.edu

Steven Stufflebeam, MD, translates basic science and advanced imaging technology into everyday clinical practice. His laboratory aims to improve the health care for patients with epilepsy, schizophrenia, brain tumors and hearing impairments. His training is in biomedical engineering, mathematics and neuroradiology. He has experience with the development of clinically relevant MRI pulse sequences and 3T and 7T. His research focuses on combining advanced imaging techniques: magnetoencephalography (MEG), electroencephalography (EEG), near-infrared spectroscopy (optical imaging), and magnetic resonance imaging (MRI). During the past few years, he has personally scanned over 2000 subjects with various neurological disorders, including epilepsy and brain tumors, with MEG and positron emission tomography (PET) as well as 3T and 7T MRI. Additionally, he is a board-certified radiologist with fellowship training in neuroradiology and the Medical Director of the Martinos Center for Biomedical Imaging.

Education

MD, Harvard Medical School

Publications

1. Stufflebeam SM, Liu H, Sepulcre J, Tanaka N, Buckner RL, Madsen JR. Localization of focal epileptic discharges using functional connectivity magnetic resonance imaging. J Neurosurg. 2011 Jun;114(6):1693-7.

2. Douw L, Wakeman DG, Tanaka N, Liu H, Stufflebeam SM. State-dependent variability of dynamic functional connectivity between frontoparietal and default networks relates to cognitive flexibility. Neuroscience. 2016 Dec 17;339:12-21.

3. DeSalvo MN, Tanaka N, Douw L, Leveroni CL, Buchbinder BR, Greve DN, Stufflebeam SM. Resting-State Functional MR Imaging for Determining Language Laterality in Intractable Epilepsy. Radiology. 2016 Oct;281(1):264-9.

Highlights

Medical Director, Martinos Center for Biomedical Imaging

Co-Founder, Functional Imaging Neural Datasets, Llc.

Founder, American Clinical MEG Society (ACMEGS)

Websites

Stufflebeam Laboratory
The David Cohen MEG Laboratory

Daphne Holt

Associate Professor

Emotion and Social Neuroscience Laboratory (Director)

dholt@mgh.harvard.edu

Tagged:Brain, Clinical, fMRI, FreeSurfer, High-field Imaging, MRI, Schizophrenia

Dr. Holt has studied the neural basis of psychosis throughout her career, initially in post-mortem samples and subsequently (since 2002) using neuroimaging. Using functional neuroimaging in combination with physiology, behavioral tasks and clinical assessments, she has investigated the neurocognitive basis of the core symptoms of psychotic illness, including delusions, negative affect and social impairment, reporting some of the first evidence for abnormalities in basic mechanisms that underlie emotional perception (e.g. fear extinction memory, fear generalization, response to perceptual threat) in psychotic illness.

Recently Dr. Holt’s group has also focused on identifying changes in brain function and behavior linked with risk for serious mental illness and has been developing novel interventions aimed at increasing resilience and potentially preventing serious mental illnesses in at-risk youth. Dr. Holt also serves as Co-Director of the MGH Schizophrenia Clinical and Research Program, which includes a First-Episode and Early Psychosis Program (FEPP) focused on comprehensive treatment of psychosis in the earliest phases of illness.

Education

PhD in Neurobiology, University of Chicago
MD, University of Chicago

Select Publications

1. Holt DJ, Kunkel L, Weiss AP, Goff DC, Wright CI, Shin LM, Rauch SL, Hootnick J, Heckers S. Increased medial temporal lobe activation during the passive viewing of emotional and neutral facial expressions in schizophrenia. Schizophr Res. 2006 Feb 28;82(2-3):153-62.

2. Holt DJ, Coombs G, Zeidan MA, Goff DC, Milad MR. Failure of neural responses to safety cues in schizophrenia. Arch Gen Psychiatry. 2012 Sep;69(9):893-903.

3. Ho NF, Iglesias JE, Sum MY, Kuswanto CN, Sitoh YY, De Souza J, Hong Z, Fischl B, Roffman JL, Zhou J, Sim K, Holt DJ. Progression from selective to general involvement of hippocampal subfields in schizophrenia. Mol Psychiatry. 2017 Jan;22(1):142-152.

Highlights

2018: MGH Scholar Award recipient, MGH Executive Committee on Research (ECOR)

Website

Emotion and Social Neuroscience Laboratory

Zdravka Medarova

Associate Professor

Image-Guided Cancer Therapy (Director)

zmedarova@mgh.harvard.edu
617-643-4889

Tagged:Cell Biology, Genetics, Metastasis, Molecular Biology, Molecular Imaging, MRI, Multimodal Imaging, Optical Imaging, Optics

Zdravka Medarova, PhD, is an Associate Professor of Radiology at Harvard Medical School. She is a geneticist/cancer biologist by training and has an extensive background in molecular biology, genetics, and tumor biology and therapy. The focus of her research has been the development and testing of multi-functional imaging/delivery vehicles for combined cancer imaging and therapy. Dr. Medarova’s earliest work described, for the first time, the design and application of ultrasmall iron oxide nanoparticles as imaging-capable carriers of siRNA to tumors. This work generated substantial interest in the research community, since it illustrated the value of these nanoparticles for the delivery of small RNA therapy to challenging organ targets and also described an approach for the noninvasive monitoring of small RNA delivery. More recently, her lab developed magnetic nanoparticles as delivery vehicles of miRNA-targeted therapy to metastases. This work resulted in multiple publications in high-impact journals such as Cancer Research, Nature Medicine, Oncogene, and Scientific Reports, as well as grants from private foundations and the NIH.

Dr. Medarova obtained a BA degree in pre-medicine from the University of Southern Maine (1998) and a PhD in Genetics from the University of New Hampshire (2002).

Education

PhD in Genetics, University of New Hampshire

Select Publications

1. Yigit MV, Ghosh SK, Kumar M, Petkova V, Kavishwar A, Moore A, Medarova Z. Context-dependent differences in miR-10b breast oncogenesis can be targeted for the prevention and arrest of lymph node metastasis. Oncogene. 2013 Mar 21;32(12):1530-8.

2. Yoo B, Kavishwar A, Ross A, Wang P, Tabassum DP, Polyak K, Barteneva N, Petkova V, Pantazopoulos P, Tena A, Moore A, Medarova Z. Combining miR-10b-Targeted Nanotherapy with Low-Dose Doxorubicin Elicits Durable Regressions of Metastatic Breast Cancer. Cancer Res. 2015 Oct 15;75(20):4407-15.

3. Yoo B, Kavishwar A, Wang P, Ross A, Pantazopoulos P, Dudley M, Moore A, Medarova Z. Therapy targeted to the metastatic niche is effective in a model of stage IV breast cancer. Sci Rep. 2017 Mar 21;7:45060.

Highlights

Anna V. Moore, Zdravka Medarova. miRNA profiling compositions and methods of use. USPTO: 10086093. October 2, 2018.

Zdravka Medarova, Mehmet V. Yigit, Anna Moore. Therapeutic nanoparticles and methods of use thereof. USPTO: 9763891 and 9629812. September 19, 2017 and April 25, 2017.

Stephen J. Lippard, Xiao-an Zhang, Zdravka Medarova, Anna Moore. Methods for mobile zinc measurement. USPTO: 8574914. November 5, 2013.

Stefan Carp

Associate Professor

Optics @ Martinos

stefan.carp@mgh.harvard.edu
617-643-2230

Tagged:Algorithm Development, Brain, Breast, Cancer, Cardiovascular Disease / Disorders, Cardiovascular System, Clinical, Hardware Development, Machine Learning, Magnetic Resonance Imaging, Molecular Imaging, MRI, Near Infrared Spectroscopy, Optical Imaging, Optics, Probe Development, Software Development, Spectroscopy

Dr. Carp’s research group focuses on the development and clinical translation of light-based non-invasive sensing and imaging methods for disease detection and management. Major thrusts include the use of near-infrared spectroscopy and tomography as well as diffuse correlation spectroscopy to advance brain health monitoring and breast cancer management. Through collaborations with clinicians at MGH and beyond, he and his group are able to test their devices and data processing algorithms in the intended use setting to guide our technology development towards meaningful clinical integration.

Education

PhD in Biomedical Optics, University of California, Irvine

Select Publications

1. Carp SA, Farzam P, Redes N, Hueber DM, Franceschini MA. Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis. Biomed Opt Express. 2017 Aug 7;8(9):3993-4006.

2. Zimmermann BB, Deng B, Singh B, Martino M, Selb J, Fang Q, Sajjadi AY, Cormier J, Moore RH, Kopans DB, Boas DA, Saksena MA, Carp SA. Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis. J Biomed Opt. 2017 Apr 1;22(4):46008.

3. Boas DA, Sakadžić S, Selb J, Farzam P, Franceschini MA, Carp SA. Establishing the diffuse correlation spectroscopy signal relationship with blood flow. Neurophotonics. 2016 Jul;3(3):031412.

Highlights

Inventions:

Cancer detection by optical measurement of compression-induced transients, US10010277B2
Systems and methods for characterizing biological material using near-infrared spectroscopy, WO2018052933A1
Optical fiber probe arrangement for use with X-ray mammography, US9265460B2

Website

Optics @ Martinos

Chongzhao Ran

Associate Professor

Chongzhao Ran Lab

cran@mgh.harvard.edu
617-643-4886

Tagged:Aging, Alzheimer's Disease, Brain, Cancer, Chemistry, Magnetic Resonance Imaging, Molecular Imaging, MRI, Multimodal Imaging, Optical Imaging, Optics, PET, PET-MRI, Positron Emission Tomography, Preclinical, Probe Development, Spectroscopy

Chongzhao Ran, PhD, is an Associate Professor in Radiology at Massachusetts General Hospital and Harvard Medical School. He received a Master’s degree in medicinal chemistry from China Pharmaceutical University and a PhD in medicinal chemistry from Shanghai Institute of Pharmaceutical Industry, China. He did his postdoctoral training at the University of Chicago and Harvard Medical School. Dr. Ran’s research focuses on the development of molecular imaging probe and imaging technologies. He has published nearly 60 papers in the fields of chemistry and molecular imaging, some in high-ranking journals such as PNAS and J. Amer. Chem. Soc. Since 2010, his research has been continuously supported by multiple NIH grants from NIA, NIDDK and other foundations. In recent years, his research group has successfully developed numerous near-infrared fluorescence (NIRF) imaging probes, which revolve around their own brand CRANAD-X, for in vivo detection of amyloid beta in mouse models of Alzheimer’s disease (AD). Particularly, his research has been focusing on seeking “smart” NIR probes for soluble amyloid beta species, which are widely believed to be the most neurotoxic species at the early stage of AD. Recently, his research group has successfully designed and synthesized secnd-generation PET tracers for amyloid beta species. In addition, his group has discovered several NIRF probes and PET tracers for imaging brown adipose tissue. These probes have remarkable potential for future diagnosis and monitoring the efficacy of drugs for Alzheimer’s disease, diabetes and obesity in preclinical studies and clinical trials.

Education

PhD in medicinal chemistry, Shanghai Institute of Pharmaceutical Industry, China

Select Publications

1. Ran C, Xu X, Raymond SB, Ferrara BJ, Neal K, Bacskai BJ, Medarova Z, Moore A. Design, synthesis, and testing of difluoroboron-derivatized curcumins as near-infrared probes for in vivo detection of amyloid-beta deposits. J Am Chem Soc. 2009 Oct 28;131(42):15257-61.

2. Zhang X, Tian Y, Li Z, Tian X, Sun H, Liu H, Moore A, Ran C. Design and synthesis of curcumin analogues for in vivo fluorescence imaging and inhibiting copper-induced cross-linking of amyloid beta species in Alzheimer’s disease. J Am Chem Soc. 2013 Nov 6;135(44):16397-409.

3. Zhang X, Tian Y, Zhang C, Tian X, Ross AW, Moir RD, Sun H, Tanzi RE, Moore A, Ran C. Near-infrared fluorescence molecular imaging of amyloid beta species and monitoring therapy in animal models of Alzheimer’s disease. Proc Natl Acad Sci U S A. 2015 Aug 4;112(31):9734-9.

4. Yang J, Zhang X, Yuan P, Yang J, Xu Y, Grutzendler J, Shao Y, Moore A, Ran C. Oxalate-curcumin-based probe for micro- and macroimaging of reactive oxygen species in Alzheimer’s disease. Proc Natl Acad Sci U S A. 2017 Nov 21;114(47):12384-12389.

Highlights

2010 K25 NIH/NIA Career Development Award