PUBLICATIONS
LIST OF RECENT REFEREED PUBLICATIONS
(including 2 papers in Nature, 1 in Nature Nanotechnology, 1 in Nature Methods, 1 in Nature Genetics 2 in Materials Today, 1 in Physical Review Letters, 2 in Sci. Reports, 8 in Advanced Materials, 4 in Small, 3 in Applied Physics Letters, etc.)
* indicates the corresponding author;
193. Mahshid Iraniparast, Nishant Kumar, Igor Sokolov*, “Single Ultrabright Fluorescent Silica Nanoparticles Can Be Used as Individual Fast Real-Time Nanothermometers” Materials Horizons, 2025, in press.
192. Rajendra Prasad*, Berney Peng, Narendra Gupta, Avtar Singh Meena, Geetha Satya Sainaga Jyothi Vaskuri, Anuj Chandak, Igor Sokolov*, João Conde* “Long-Term Cell-Membrane-Coated Ultrabright Nanospheres for Targeted Cancer Cell Imaging and Hydrophobic Drug Delivery”, Chemistry of Materials, 2025, Vol 37, Issue 3, 845–856.
191. Mikhail Petrov, Daniel Canena, Nikita Kulachenkov, Nishant Kumar, Pierre Nickmilder, Philippe Leclère, Igor Sokolov*, “Mechanical spectroscopy of materials using atomic force microscopy (AFM-MS)”, Materials Today, Volume 80, November 2024, Pages 218-225.
190. I. Sokolov “Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: mini-review”, 2024, Nanoscale, 2024, 16, 10994-11004
189. I. Sokolov “On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition”, 2024, Physical Chemistry Chemical Physics (PCCP), 2024. 26(15): p. 11263-11270.
188. M Petrov, I Sokolov*, “Machine Learning Allows for Distinguishing Precancerous and Cancerous Human Epithelial Cervical Cells Using High-Resolution AFM Imaging of Adhesion Maps”, Cells 12 (21), 2536, 2023.
187. R Nabbout, D Dufault, C Shi, L Boardman, I Sokolov, J Roper, S374 Folate Receptor is a Marker of Colorectal Adenoma in a Prospective Cohort of Matched Colorectal Adenoma and Normal Colon Organoids, Official journal of the American College of Gastroenterology| ACG 118, p. S271
186. N Makarova, M Lekka, K Gnanachandran, I Sokolov*, “Mechanical Way To Study Molecular Structure of Pericellular Layer”, ACS Applied Materials & Interfaces 15 (30), 35962-35972.
185. M Iraniparast, B Peng, I Sokolov*, “Towards the Use of Individual Fluorescent Nanoparticles as Ratiometric Sensors: Spectral Robustness of Ultrabright Nanoporous Silica Nanoparticles”, Sensors 23 (7), 3471, 2023
184. Mikhail Petrov, Igor Sokolov* “Identification of Geometrical Features of Cell Surface Responsible for Cancer Aggressiveness: Machine Learning Analysis of Atomic Force Microscopy Images of Human Colorectal Epithelial Cells”, Biomedicines 11(1), 191, 2023.
183. Julien Ablain*, Harriet Rothschild, Amira Al Mahi, Meera Prasad, Song Yang, Maxim E. Dokukin, Michelle Dang, Igor Sokolov, Christine G. Lian, Leonard I. Zon* “Frequent deletion of adhesion gene NECTIN1 triggers melanoma dissemination upon local IGF1 depletion”, Nature Genetics, https://doi.org/10.1038/s41588-022-01191-z
Top 10 most influential recent publications
- Iyer, S., R.M. Gaikwad, V. Subba-Rao, C.D. Woodworth, and I. Sokolov*, AFM Detects Differences in the Surface Brush on Normal and Cancerous Cervical Cells Nature Nanotechnology, 2009, 4, p. 389-393.
Discovery of the distinction in the pericellular layer of cancer cells. - I. Sokolov*, M. E. Dokukin, V. Kalaparthi, M. Miljkovic, A. Wang, J. D. Seigne, P. Grivas, E. Demidenko, Noninvasive detection of bladder cancer using machine-learning-based analysis of nano-resolution images of cells from urine, Proceedings of the National Academy of Sciences (PNAS), 2018. 115(51), p. 12920-12925.
Nine years later, the discovered distinction in the pericellular layer, as mentioned in the above reference, led to the development of a new method for noninvasive detection of bladder cancer. - Berdyyeva, T.K., C.D. Woodworth, and I. Sokolov*, Human epithelial cells increase their rigidity with ageing in vitro: direct measurements. Physics in Medicine and Biology, 2005, 50(1), p. 81-92.
The discovery of age-related changes in cell mechanics. The physical and biological reasons have been identified. - Sokolov, I.*, Dokukin, M., N. Guz, Method for quantitative measurements of the elastic modulus of biological cells in AFM indentation experiments, Methods, 2013, 60(2), p. 202-213.
The development of the method (Brush model) for measuring the elastic modulus of biological cells. - N. Guz, M. Dokukin, V. Kalaparthy, and I. Sokolov* If cell mechanics can be described by elastic modulus: study of different models and probes used in indentation experiments, Biophysical J., 2014, 107, p. 564-575.
Demonstration that cells can be characterized with Young’s modulus in a self-consistent manner and how to do it properly. Comparison to the generally accepted methods of measurement of Young’s modulus at that time. - M. E. Dokukin, N. V. Guz, R. M. Gaikwad, C.D. Woodworth, I. Sokolov*, Cell surface as fractal: Normal and cancerous cervical cells demonstrate different fractal behavior of surface adhesion maps at the nanoscale, Phys. Rev. Lett. 2011, 107, 028101.
The analysis of the fractal behavior of the adhesion maps of the cell surface. Discovery of the change in fractal behavior of cells during progression towards cancer. - Mikhail Petrov, Daniel Canena, Nikita Kulachenkov, Nishant Kumar, Pierre Nickmilder, Philippe Leclère, Igor Sokolov*, Mechanical spectroscopy of materials using atomic force microscopy (AFM-MS), Materials Today, 2024, 80, p. 218-225.
A recent development of mechano-spectroscopy of materials. It enables the identification of specific materials in a complex mixture with single-nanometer resolution. - Dokukin, M., I. Sokolov *, On the measurements of rigidity modulus of soft materials in nanoindentation experiments at a small depth, Macromolecules, 2012, 45 (10), p. 4277–4288.
The discovery that the depth-dependence of the Young’s modulus measured in the indentation experiments was an artifact due to ignoring the nonlinear behavior of the material at small indentation depth. - Berney Peng, Mohammad Almeqdadi, Fabrice Laroche, Shajesh Palantavida, Maxim Dokukin, Omer H. Yilmaz, Jatin Roper, Hui Feng, Igor Sokolov*, Ultrabright fluorescent cellulose acetate nanoparticles for imaging tumors through systemic and topical applications, Materials Today, 2019, 23, p. 16-25.
The development of ultrabright nanoparticles for imaging of tumors. Besides being extremely bright, the particles demonstrated highly unusual specificity to colorectal tumors just by topical applications. Such topical specificity is outstanding and has not been studied for clinical applications related to colorectal cancer. - Pei-Hsun Wu, Dikla Raz-Ben Aroush, Atef Asnacios, Wei-Chiang Chen, Maxim E. Dokukin, Bryant L. Doss, Pauline Durand, Andrew Ekpenyong, Jochen Guck, Nataliia.V. Guz, Paul A. Janmey, Albrecht Ott, Robert Ros, Yeh-Chuin Poh, Mathias Sander, Igor Sokolov, Jack R. Stuanton, Ning Wang, Denis Wirtz* A comparison of methods to assess cell mechanical properties, Nature Methods, 2018, 15, p. 491– 498.
This collaborative research aimed at a precise comparison of the mechanical properties of the same cells prepared in different labs under the same conditions. A comprehensive set of tools has been utilized by multiple groups to compare the obtained results and discuss their potential applications in future medical contexts.
A comprehensive list of publications can be found here: Igor Sokolov – Google Scholar
Below is the topical list (under construction)
Atomic Force Microscopy for Medicine
OuterOmics
- Igor Sokolov, Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: a mini-review, Nanoscale, 2024, 16, 10994-11004
- Igor Sokolov, On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition, Physical Chemistry Chemical Physics, 2024, 26, 11263-11270
OuterOmics
- Igor Sokolov, Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: a mini-review, Nanoscale, 2024, 16, 10994-11004
- Igor Sokolov, On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition, Physical Chemistry Chemical Physics, 2024, 26, 11263-11270
Nanomaterials, Self-assembly
- Igor Sokolov, Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: a mini-review, Nanoscale, 2024, 16, 10994-11004
- Igor Sokolov, On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition, Physical Chemistry Chemical Physics, 2024, 26, 11263-11270
Nanomaterials
- Igor Sokolov, Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: a mini-review, Nanoscale, 2024, 16, 10994-11004
- Igor Sokolov, On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition, Physical Chemistry Chemical Physics, 2024, 26, 11263-11270
Nanomaterials
- Igor Sokolov, Ultrabright fluorescent particles via physical encapsulation of fluorescent dyes in mesoporous silica: a mini-review, Nanoscale, 2024, 16, 10994-11004
- Igor Sokolov, On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition, Physical Chemistry Chemical Physics, 2024, 26, 11263-11270