Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Paiva, Joana S.; Ribeiro, R. S. Rodrigues; Cunha, João Paulo Silva; Rosa, Carla C.; Jorge, P. A. S.

doi:10.3390/s18030710

Cited by 17 publications

(47 citation statements)

References 73 publications

(125 reference statements)

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“…fabrication of the polymeric microlens. The polymeric lens used in this study was fabricated through a guided wave photo-polymerization method developed by Soppera et al 21 in collaboration with our lab 4,15 . It has already shown to be suitable to trap synthetic microparticles and non-human cells 4,15 .…”

Section: Discussionmentioning

confidence: 99%

“…The polymeric lens used in this study was fabricated through a guided wave photo-polymerization method developed by Soppera et al 21 in collaboration with our lab 4,15 . It has already shown to be suitable to trap synthetic microparticles and non-human cells 4,15 . Its fabrication method is based on the assemble of cross-linked polymeric structures through monomers linking triggered by light 4,21 .…”

Section: Discussionmentioning

confidence: 99%

“…After collecting enough information for force analysis, each cell/particle was immobilized using the fiber tool as depicted in Supplementary Fig. S2 during 80-seconds 15 , for back-scattered signal acquisition. Part of the light There was no significant difference between cell type diameters (P Student7D1t-test > 0.05; unpaired, two tailed; n = 15).…”

Section: High-resolution Artificial Intelligence-based Cancer Cells Imentioning

confidence: 99%

“…It is clear that signal differences between the type of particles are not visible to the naked eye. Then, we trained a supervised learning-based algorithm, the Random Forests 31,32 , to correctly identify the type of particle trapped, taking into account the information provided from the features set enumerated in Table 1 15 , characterizing each signal portion.…”

Section: High-resolution Artificial Intelligence-based Cancer Cells Imentioning

confidence: 99%

“…Even though the development of OFT is a growing field, only a limited number of options are available for simultaneous cell trapping and sensing 1,2,5,15 . Plasmonic fiber tweezers are good candidates for such an hybrid task because, beyond trapping, they are sensitive to tiny changes of the surrounding environmental refractive index and can then provide some additional information about their target 16 .…”

mentioning

confidence: 99%

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iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

Paiva,

Jorge,

Ribeiro

et al. 2020

Sci Rep

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With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the "intelligent" Lab on Fiber (iLof) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLof is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.Recent research trends on healthcare point out to the movement to develop "smart" micro-tools to allow better personalized diagnostic and therapeutic approaches 1-3 . Considering that current medicine and biotechnology attempts are converging to novel methodologies at the micro (e.g., cancer cells detection) and nano scales (e.g., cancer-related extracellular vesicles detection), an effort towards the development of these "intelligent" microdevices with multifunctionalities is required 3 . In this regard, optical fiber tools -for example, Optical Fiber Tweezers (OFT) 1,4,5 -have emerged as suitable candidates thanks to their flexibility, small size and chemical inertness, which contributes to the advent of a novel concept of "Lab on Fiber" (LoF) devices 2 . The fruitful application of these optical-based microdevices in cancer screening has been envisioned as straightforward 1,2 . However, the high degree of heterogeneity among cancer subtypes must be taken into consideration 6,7 . This heterogeneity is mainly due to both cellular and microenvironmental factors, such as alterations in cellular glycosylation 8 . In particular, the selective detection of specific cancer-associated glycoforms expressed at the surface of circulating cancer cells could increase the specificity of cancer biomarker assays and therapeutic approaches 8-10 . In fact, tumor heterogeneity is considered to be a major barrier to an effective cancer diagnosis and treatment 6,7 . Recent evidence has shown that glycans can determine the acquisition of certain cellular features controlling tumor growth and progression 8,11,12 . For example, shorter trun...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: High-resolution Artificial Intelligence-based Cancer Cells Imentioning

confidence: 99%

Section: High-resolution Artificial Intelligence-based Cancer Cells Imentioning

confidence: 99%

mentioning

confidence: 99%

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iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

Paiva,

Jorge,

Ribeiro

et al. 2020

Sci Rep

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Advances in Fiber‐Optic Technology for Point‐of‐Care Diagnosis and In Vivo Biosensing

Tabassum

Kumar

2020

Adv Materials Technologies

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Development of reliable, sensitive, selective, and miniaturized sensing technologies is critical for health assessment and early diagnosis and treatment of diseases/anomalies while simultaneously mitigating the challenges associated with in vivo measurements. Some critical constraints to the realization of in vivo measurements include the necessity to fabricate the sensor on a tightly constrained footprint while ensuring acceptable biocompatibility, accuracy, and reliability. The inherent light-guiding properties of optical fibers over long distances, their microscopic cross-section that can be structured at the nanoscale to manipulate the light transmittance/reflectance spectrum, excellent biocompatibility enabling their efficient integration with bio-recognition molecules, immunity to electromagnetic interference, mechanical flexibility, and low cost have been inviting research attention to utilize these unique features for in vivo and label-free point-ofcare diagnostics. Hence, fiber-optic biosensing has become a promising research thrust, with a plethora of emerging methodologies to develop ultrasensitive and selective sensing probes.A unified presentation of the research trends on biosensors incorporated into optical fibers is presented.

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The pro‐proliferative effect of insulin in human breast epithelial DMBA‐transformed and non‐transformed cell lines is PI3K‐, mTOR‐ and GLUT1‐dependent

Silva

Andrade

Guimarães

et al. 2022

Cell Biochemistry & Function

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Type 2 diabetes mellitus (T2DM) is linked to an increased risk of breast cancer. We aimed to investigate how T2DM‐associated characteristics (high levels of glucose, insulin, leptin, inflammatory mediators and oxidative stress) influence breast cancer carcinogenesis, in DMBA‐treated (MCF‐12ADMBA) and non‐treated breast epithelial (MCF‐12A) cell lines. Insulin (50 nM) promotes cell proliferation, 3H‐DG uptake and lactic acid production in both cell lines. The stimulatory effects of insulin upon cell proliferation and 3H‐DG uptake were hampered by rapamycin, LY294001 and BAY‐876, in both cell lines. In conclusion, hyperinsulinemia, one important characteristic of T2DM, contributes to the initiation of breast cancer by a PI3K‐ and mTOR‐dependent mechanism involving increased GLUT1‐mediated glucose uptake. Significance The pro‐proliferative effect of insulin in human breast epithelial DMBA‐transformed and non‐transformed cell lines is PI3K‐, mTOR‐ and GLUT1‐dependent.

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Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Cited by 17 publications

References 73 publications

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

Advances in Fiber‐Optic Technology for Point‐of‐Care Diagnosis and In Vivo Biosensing

The pro‐proliferative effect of insulin in human breast epithelial DMBA‐transformed and non‐transformed cell lines is PI3K‐, mTOR‐ and GLUT1‐dependent

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