Huw Summers

Huw Summers, PhD

Full Affiliate Member, Research Institute
Houston Methodist


Biography

Dr. Huw Summers is a professor in nanotechnology for health in the College of Engineering at Swansea University in Wales. Dr. Summers has extensive experience in metrologies for cell analysis and the development of nanoparticle-based diagnostics and therapeutics. He has more than 80 peer-reviewed publications in prestigious journals including Applied Physics Letters and Nature Nanotechnology and is supported by several European Union research grants.

As an Full Affiliate Member of Houston Methodist Research Institute, Dr. Summers collaborates with the nanomedicine department to develop physics and engineering approaches for cell analysis. Dr. Summers is also a mentor for the formal joint graduate training program between the Houston Methodist Academy and Swansea University.

Description of Research

In the field of nanomedicine, Dr. Summers’ group is one of only a handful, developing quantitative, statistical assays for the assessment of nanoparticle dose in proliferating cell populations. Dr. Summers’ research focuses on two areas: metrologies for cell analysis (cytometry) and the development of nanoparticle-based diagnostics and therapeutics (nanomedicine).

The goal of this work is to apply physics and engineering approaches to cell population analysis, e.g. systems analysis of cell cycle progression or statistical mechanics on nanoparticle-cell interactions. Computational and statistical analyses are applied to large cell populations (>106) with the enabling technology being high throughput, high content cytometry (microscope and flow system based) and the core aim to understand and quantify cell heterogeneity.

His research program exploits the customizability of micro and nano-engineered structures to provide novel optical analysis and manipulation of living cells. For example, using fluorescent nanocrystals (quantum dots) as intra-cellular markers cell populations allows tracking over multiple generations of cell division, and the evolution of different lineages can then be analyzed by their unique spectral signatures.

Areas Of Expertise

Nanomedicine Optical techniques for biomedicine Cytometry Nanoparticle fluorophores
Education & Training

PhD, Cardiff University
Postdoctoral Fellowship, University of Bath
Publications

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry
Barnes, CM, Power, AL, Barber, DG, Tennant, RK, Jones, RT, Lee, GR, Hatton, J, Elliott, A, Zaragoza-Castells, J, Haley, SM, Summers, HD, Doan, M, Carpenter, AE, Rees, P & Love, J 2023, , New Phytologist, vol. 240, no. 3, pp. 1305-1326. https://doi.org/10.1111/nph.19186

Label-free cell segmentation of diverse lymphoid tissues in 2D and 3D
Wills, JW, Robertson, J, Tourlomousis, P, Gillis, CMC, Barnes, CM, Miniter, M, Hewitt, RE, Bryant, CE, Summers, HD, Powell, JJ & Rees, P 2023, , Cell Reports Methods, vol. 3, no. 2, 100398. https://doi.org/10.1016/j.crmeth.2023.100398

Imaging flow cytometry
Rees, P, Summers, HD, Filby, A, Carpenter, AE & Doan, M 2022, , Nature Reviews Methods Primers, vol. 2, no. 1, 86. https://doi.org/10.1038/s43586-022-00167-x

Prevalence and correlates of compliance with 24-h movement guidelines among children from urban and rural Kenya—The Kenya-LINX project
Swindell, N, Wachira, LJ, Okoth, V, Kagunda, S, Owino, G, Ochola, S, Brophy, S, Summers, H, Richards, A, Fairclough, SJ, Onywera, V & Stratton, G 2022, , PLoS ONE, vol. 17, no. 12 December, e0279751. https://doi.org/10.1371/journal.pone.0279751

Spatial statistics is a comprehensive tool for quantifying cell neighbor relationships and biological processes via tissue image analysis
Summers, HD, Wills, JW & Rees, P 2022, , Cell Reports Methods, vol. 2, no. 11, 100348, pp. 100348. https://doi.org/10.1016/j.crmeth.2022.100348

The effects of curve registration on linear models of jump performance and classification based on vertical ground reaction forces
G. E. White, M, Neville, J, Rees, P, Summers, H & Bezodis, N 2022, , Journal of Biomechanics, vol. 140, 111167, pp. 111167. https://doi.org/10.1016/j.jbiomech.2022.111167

Determining jumping performance from a single body-worn accelerometer using machine learning
White, MGE, Bezodis, NE, Neville, J, Summers, H & Rees, P 2022, , PLoS ONE, vol. 17, no. 2, e0263846, pp. e0263846. https://doi.org/10.1371/journal.pone.0263846

Practical machine learning for disease diagnosis
Summers, HD 2021, , Cell Reports Methods, vol. 1, no. 6, 100103. https://doi.org/10.1016/j.crmeth.2021.100103

Data-driven modeling of the cellular pharmacokinetics of degradable chitosan-based nanoparticles
Summers, HD, Gomes, CP, Varela-Moreira, A, Spencer, AP, Gomez-Lazaro, M, Pêgo, AP & Rees, P 2021, , Nanomaterials, vol. 11, no. 10, 2606. https://doi.org/10.3390/nano11102606

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning
Wills, JW, Verma, JR, Rees, BJ, Harte, DSG, Haxhiraj, Q, Barnes, CM, Barnes, R, Rodrigues, MA, Doan, M, Filby, A, Hewitt, RE, Thornton, CA, Cronin, JG, Kenny, JD, Buckley, R, Lynch, AM, Carpenter, AE, Summers, HD, Johnson, GE & Rees, P 2021, , Archives of Toxicology, vol. 95, no. 9, pp. 3101-3115. https://doi.org/10.1007/s00204-021-03113-0

Empirical comparison of genotoxic potency estimations: The in vitro DNA-damage ToxTracker endpoints versus the in vivo micronucleus assay
Wills, JW, Halkes-Wellstead, E, Summers, HD, Rees, P & Johnson, GE 2021, , Mutagenesis, vol. 36, no. 4, pp. 311-320. https://doi.org/10.1093/mutage/geab020

Data Driven Cell Cycle Model to Quantify the Efficacy of Cancer Therapeutics Targeting Specific Cell-Cycle Phases From Flow Cytometry Results
James, DW, Filby, A, Brown, MR, Summers, HD, Francis, LW & Rees, P 2021, , Frontiers in Bioinformatics, vol. 1, 662210. https://doi.org/10.3389/fbinf.2021.662210

Design of experiment (DoE)-driven in vitro and in vivo uptake studies of exosomes for pancreatic cancer delivery enabled by copper-free click chemistry-based labelling
Xu, L, Faruqu, FN, Liam-or, R, Abu Abed, O, Li, D, Venner, K, Errington, RJ, Summers, H, Wang, JTW & Al-Jamal, KT 2020, , Journal of Extracellular Vesicles, vol. 9, no. 1, 1779458, pp. 1779458. https://doi.org/10.1080/20013078.2020.1779458

Label-Free Leukemia Monitoring by Computer Vision
Doan, M, Case, M, Masic, D, Hennig, H, McQuin, C, Caicedo, J, Singh, S, Goodman, A, Wolkenhauer, O, Summers, HD, Jamieson, D, Delft, FV, Filby, A, Carpenter, AE, Rees, P & Irving, J 2020, , Cytometry Part A, vol. 97, no. 4, pp. 407-414. https://doi.org/10.1002/cyto.a.23987

Diffusion Mapping of Eosinophil-Activation State
Piasecka, J, Thornton, CA, Rees, P & Summers, HD 2020, , Cytometry Part A, vol. 97, no. 3, pp. 253-258. https://doi.org/10.1002/cyto.a.23884

Activity mapping of children in play using multivariate analysis of movement events
Rocha, JN, Barnes, CM, Rees, P, Clark, CT, Stratton, G & Summers, HD 2020, , Medicine and science in sports and exercise, vol. 52, no. 1, pp. 259-266. https://doi.org/10.1249/MSS.0000000000002119

Image-Based Cell Profiling Enables Quantitative Tissue Microscopy in Gastroenterology
Wills, JW, Robertson, J, Summers, HD, Miniter, M, Barnes, C, Hewitt, RE, Keita, ÅV, Söderholm, JD, Rees, P & Powell, JJ 2020, , Cytometry Part A, vol. 97, no. 12, pp. 1222-1237. https://doi.org/10.1002/cyto.a.24042

Physical activity, motor competence and movement and gait quality: A principal component analysis
Clark, CCT, Barnes, CM, Duncan, MJ, Summers, HD & Stratton, G 2019, , Human Movement Science, vol. 68, 102523. https://doi.org/10.1016/j.humov.2019.102523

The origin of heterogeneous nanoparticle uptake by cells
Rees, P, Wills, JW, Brown, MR, Barnes, CM & Summers, HD 2019, , Nature Communications, vol. 10, no. 1, 2341. https://doi.org/10.1038/s41467-019-10112-4

Label-Free Identification of White Blood Cells Using Machine Learning
Nassar, M, Doan, M, Filby, A, Wolkenhauer, O, Fogg, DK, Piasecka, J, Thornton, CA, Carpenter, AE, Summers, HD, Rees, P & Hennig, H 2019, , Cytometry Part A, vol. 95, no. 8, pp. 836-842. https://doi.org/10.1002/cyto.a.23794