Novel fractal characteristic of atomic force microscopy images

Стародубцева, М. Н.; Стародубцев, И. Е.; Starodubtsev, E. G.

doi:10.1016/j.micron.2017.02.009

Cited by 19 publications

(4 citation statements)

References 16 publications

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“…Simple roughness measurements are not sensitive enough to highlight subtle changes. Analyzing the fractal dimension of the cellular surface could be a valuable alternative to distinguish subtle differences occurring after drug treatment (Starodubtseva et al, 2017a(Starodubtseva et al, , 2017bStarodubtseva et al, 2019). All these data strongly suggest that following online cell surface changes upon drug action can help in distinguishing sensitive from resistant cancer cells.…”

Section: Imaging Of Cancer Cellsmentioning

confidence: 98%

Advanced technological tools to study multidrug resistance in cancer

Luca

Kasas

Garrido

et al. 2020

Drug Resistance Updates

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The complexity of cancer biology and its clinical manifestation are driven by genetic, epigenetic, transcriptomic, proteomic and metabolomic alterations, supported by genomic instability as well as by environmental conditions and lifestyle factors. Although novel therapeutic modalities are being introduced, efficacious cancer therapy is not achieved due to the frequent emergence of distinct mechanisms of multidrug resistance (MDR). Advanced technologies with the potential to identify and characterize cancer MDR could aid in selecting the most efficacious therapeutic regimens and prevent inappropriate treatments of cancer patients. Herein, we aim to present technological tools that will enhance our ability to surmount drug resistance in cancer in the upcoming decade. Some of these tools are already in practice such as next-generation sequencing. Identification of genes and different types of RNAs contributing to the MDR phenotype, as well as their molecular targets, are of paramount importance for the development of new therapeutic strategies aimed to enhance drug response in resistant tumors. Other techniques known for many decades are in the process of adaptation and improvement to study cancer cells' characteristics and biological behavior including atomic force microscopy (AFM) and live-cell imaging. AFM can monitor in real-time single molecules or molecular complexes as well as structural alterations occurring in cancer cells induced upon treatment with various antitumor agents. Cell tracking methodologies and software tools recently progressed towards quantitative analysis of the spatio-temporal dynamics of heterogeneous cancer cell populations and enabled direct monitoring of cells and their descendants in 3D cultures. Besides, novel 3D systems with the advanced mimicking of the in vivo tumor microenvironment are applicable to study different cancer biology phenotypes, particularly drug-resistant and aggressive ones. They are also suitable for investigating new anticancer treatment modalities. The ultimate goal of using phenotype-driven 3D cultures for the investigation of patient biopsies as the most appropriate in vivo mimicking model, can be achieved in the near future.

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Section: Imaging Of Cancer Cellsmentioning

confidence: 98%

Advanced technological tools to study multidrug resistance in cancer

Luca

Kasas

Garrido

et al. 2020

Drug Resistance Updates

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“…The binary pictures of composites fracture surface for EMP, IMP, and HPMP were diverse ( Figure 8), and the surface fractal dimension of the three types were different; EMP composites needed the least potential energy to change the structure, the interfacial adhesion of EMP composites was the best, while the HPMP composite was the worst [72]. The fractal dimension of AFM images describing the characteristic structure of z-scale factors can reflect the fractal characteristics of materials more comprehensively than the fractal dimension obtained by roughness [73]. Gabibov et al [74] found that the composite structure composed of styrene butadiene rubber (SBR) and epoxy resin ED-20 filled with nanoparticles is a combination of two fractals.…”

Section: Fractal Characteristics and Fractal Dimension Of Polymers Anmentioning

confidence: 99%

Review about the Application of Fractal Theory in the Research of Packaging Materials

Duan

Mao

et al. 2021

Materials

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The work is intended to summarize the recent progress in the work of fractal theory in packaging material to provide important insights into applied research on fractal in packaging materials. The fractal analysis methods employed for inorganic materials such as metal alloys and ceramics, polymers, and their composites are reviewed from the aspects of fractal feature extraction and fractal dimension calculation methods. Through the fractal dimension of packaging materials and the fractal in their preparation process, the relationship between the fractal characteristic parameters and the properties of packaging materials is discussed. The fractal analysis method can qualitatively and quantitatively characterize the fractal characteristics, microstructure, and properties of a large number of various types of packaging materials. The method of using fractal theory to probe the preparation and properties of packaging materials is universal; the relationship between the properties of packaging materials and fractal dimension will be a critical trend of fractal theory in the research on properties of packaging materials.

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“…In histopathology image analysis, second-order effects and lacunarity (distribution, size of gaps between cells) [41] were proposed as marking factors. The correlation between the fractal dimension of AFM images and the z-scale factor serves as a mechanical mark of human lung carcinoma [42]. Analysis of the AFM adhesion of cells [43] reveals that fractality differences are evident when premalignant cells transform into cancerous cells [44].…”

Section: Introductionmentioning

confidence: 99%

Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections

Gavriil

Ferraro

Cefalas

et al. 2023

Cancers

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Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement, and, most importantly, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement to metastatic cancer detection with 97.7 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. This methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds based on relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low metastatic potential to those of high metastatic potential. This metastatic differentiation, which is also identified in higher moments of variograms, sets different hierarchical levels for metastatic progression dynamics.

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Novel fractal characteristic of atomic force microscopy images

Cited by 19 publications

References 16 publications

Advanced technological tools to study multidrug resistance in cancer

Advanced technological tools to study multidrug resistance in cancer

Review about the Application of Fractal Theory in the Research of Packaging Materials

Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections

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