Colloids and suspensions are part of our daily routines. Even the blood is considered a “naturally” occurring colloid. However, the majority of colloids are complex and composed by a diversity of nano to microparticles. The characterization of both synthetic and physiological fluids in terms of particulate types, size and surface characteristics plays a vital role in products formulation, and in the early diagnosis through the identification of abnormal scatterers in physiological fluids, respectively. Several methods have been proposed for characterizing suspensions, including imaging, electrical sensing counters, hydrodynamic or field flow fractionation. However, the Dynamic Light Scattering (DLS) has evolved as the most convenient method from these. Based also on the scattering signal, we propose a novel, simple and fast method able to determine the number of different scatterers type present in a suspension, without any previous information about its composition (in terms of particle classes). This is achieved by collecting features from a 980 nm laser back-scattered signal acquired through a polymeric lensed optical fiber tip dipped into the solution. Unlike DLS, this technique allows the trapping of particles whose diameter ≥ 1 μm. For smaller particles, despite not guaranteeing their immobilization, it is also able to determine the number of different nanoparticles classes in an ensemble. The number of particle types was correctly determined for suspensions of synthetic particles and yeasts; different bacteria; and 100 nm nanoparticles types, using both Principal Component Analysis and K-means algorithms. This method could be a valuable alternative to complex and time-consuming methods for particles separation, such as field flow fractionation.
In view of the growing importance of nanotechnologies, the detection of nanoparticles type in several contexts has been considered a relevant topic. Several organisms, including the National Institutes of Health, have been highlighting the urge of developing nanoparticles exposure risk assessment assays, since very little is known about their physiological responses. Although the identification/characterization of synthetically produced nanoparticles is considered a priority, there are many examples of “naturally” generated nanostructures that provide useful information about food components or human physiology. In fact, several nanoscale extracellular vesicles are present in physiological fluids with high potential as cancer biomarkers. However, scientists have struggled to find a simple and rapid method to accurately detect/identify nanoparticles, since their majority have diameters between 100-150 nm - far below the diffraction limit. Currently, there is a lack of instruments for nanoparticles detection and the few instrumentation that is commonly used is costly, bulky, complex and time consuming. Thus, considering our recent studies on particles identification through back-scattering, we examined if the time/frequency-domain features of the back-scattered signal provided from a 100 nm polystyrene nanoparticles suspension are able to detect their presence only by dipping a polymeric lensed optical fiber in the solution. This novel technique allowed the detection of synthetic nanoparticles in distilled water versus “blank solutions” (only distilled water) through Multivariate Statistics and Artificial Intelligence (AI)-based techniques. While the state-of-the-art methods do not offer affordable and simple approaches for nanoparticles detection, our technique can contribute for the development of a device with innovative characteristics.
Optical Tweezers (OTs) have been widely applied in Biology, due to their outstanding focusing abilities, which make them able to exert forces on micro-sized particles. The magnitude of such forces (pN) is strong enough to trap their targets. However, the most conventional OT setups are based on complex configurations, being associated with focusing difficulties with biologic samples. Optical Fiber Tweezers (OFTs), which consist in optical fibers with a lens in one of its extremities are valuable alternatives to Conventional Optical Tweezers (COTs). OFTs are flexible, simpler, low-cost and easy to handle. However, its trapping performance when manipulating biological and complex structures remains poorly characterized. In this study, we experimentally characterized the optical trapping of a biological cell found within a culture of rodent glial neuronal cells, using a polymeric lens fabricated through a photo-polymerization method on the top of a fiber. Its trapping performance was compared with two synthetic microspheres (PMMA, polystyrene) and two simple cells (a yeast and a Drosophila Melanogaster cell). Moreover, the experimental results were also compared with theoretical calculations made using a numerical model based on the Finite Differences Time Domain. It was found that, although the mammalian neuronal cell had larger dimensions, the magnitude of forces exerted on it was the lowest among all particles. Our results allowed us to quantify, for the first time, the complexity degree of manipulating such "demanding" cells in comparison with known targets. Thus, they can provide valuable insights about the influence of particle parameters such as size, refractive index, homogeneity degree and nature (biologic, synthetic). Furthermore, the theoretical results matched the experimental ones which validates the proposed model.
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