High-efficiency freezing-induced loading of inorganic nanoparticles and proteins into micron- and submicron-sized porous particles

We demonstrate a novel approach to the controlled loading of inorganic nanoparticles and proteins into submicron- and micron-sized porous particles. The approach is based on freezing/thawing cycles, which lead to high loading densities. The process was tested for the inclusion of Au, magnetite nanoparticles, and bovine serum albumin in biocompatible vaterite carriers of micron and submicron sizes. The amounts of loaded nanoparticles or substances were adjusted by the number of freezing/thawing cycles. Our method afforded at least a three times higher loading of magnetite nanoparticles and a four times higher loading of protein for micron vaterite particles, in comparison with conventional methods such as adsorption and coprecipitation. The capsules loaded with magnetite nanoparticles by the freezing-induced loading method moved faster in a magnetic field gradient than did the capsules loaded by adsorption or coprecipitation. Our approach allows the preparation of multicomponent nanocomposite materials with designed properties such as remote control (e.g. via the application of an electromagnetic or acoustic field) and cargo unloading. Such materials could be used as multimodal contrast agents, drug delivery systems, and sensors

Lightsheet-based flow cytometer for whole blood with the ability for the magnetic retrieval of objects from the blood flow

Detection and extraction of circulating tumor cells and other rare objects in the bloodstream are of great interest for modern diagnostics, but devices that can solve this problem for the whole blood volume of laboratory animals are still rare. Here we have developed SPIM-based lightsheet flow cytometer for the detection of fluorescently-labeled objects in whole blood. The bypass channel between two blood vessels connected with the external flow cell was used to visualize, detect, and magnetically separate fluorescently-labeled objects without hydrodynamic focusing. Carriers for targeted drug delivery were used as model objects to test the device performance. They were injected into the bloodstream of the rat, detected fluorescently, and then captured from the bloodstream by a magnetic separator prior to filtration in organs. Carriers extracted from the whole blood were studied by a number of in vitro methods

Combination of Machine Learning and Raman Spectroscopy for Determination of the Complex of Whey Protein Isolate with Hyaluronic Acid

Macromolecules and their complexes remain interesting topics in various fields, such as targeted drug delivery and tissue regeneration. The complex chemical structure of such substances can be studied with a combination of Raman spectroscopy and machine learning. The complex of whey protein isolate (WPI) and hyaluronic acid (HA) is beneficial in terms of drug delivery. It provides HA properties with the stability obtained from WPI. However, differences between WPI-HA and WPI solutions can be difficult to detect by Raman spectroscopy. Especially when the low HA (0.1, 0.25, 0.5% w/v) and the constant WPI (5% w/v) concentrations are used. Before applying the machine learning techniques, all the collected data were divided into training and test sets in a ratio of 3:1. The performances of two ensemble methods, random forest (RF) and gradient boosting (GB), were evaluated on the Raman data, depending on the type of problem (regression or classification). The impact of noise reduction using principal component analysis (PCA) on the performance of the two machine learning methods was assessed. This procedure allowed us to reduce the number of features while retaining 95% of the explained variance in the data. Another application of these machine learning methods was to identify the WPI Raman bands that changed the most with the addition of HA. Both the RF and GB could provide feature importance data that could be plotted in conjunction with the actual Raman spectra of the samples. The results show that the addition of HA to WPI led to changes mainly around 1003 cm−1 (correspond to ring breath of phenylalanine) and 1400 cm−1, as demonstrated by the regression and classification models. For selected Raman bands, where the feature importance was greater than 1%, a direct evaluation of the effect of the amount of HA on the Raman intensities was performed but was found not to be informative. Thus, applying the RF or GB estimators to the Raman data with feature importance evaluation could detect and highlight small differences in the spectra of substances that arose from changes in the chemical structure; using PCA to filter out noise in the Raman data could improve the performance of both the RF and GB. The demonstrated results will make it possible to analyze changes in chemical bonds during various processes, for example, conjugation, to study complex mixtures of substances, even with small additions of the components of interest

Tip-Functionalized Au@Ag Nanorods as Ultrabright Surface-Enhanced Raman Scattering Probes for Bioimaging in Off-Resonance Mode

Surface-enhanced Raman scattering (SERS) performance of Au nanorods (AuNRs) can be enhanced by the tip adsorption of Raman molecules (RMs) through anisotropic polymer stabilization or through the embedding of RMs between AuNR cores and Ag shells of AuNR@RM@Ag composite particles. We propose a new strategy to design ultrabright SERS probes composed of high-aspect-ratio AuNRs with anisotropic Ag coatings, with preferred adsorption of RMs to open AuNR tips. Specifically, for 4-nitrobenzenethiol (NBT) concentrations above a threshold value <i>c</i> > <i>c</i>_tr, the fabricated Au@NBT@Ag particles had NBT-functionalized open Au tips, as well as anisotropic Ag shells grown on the AuNR sides. The SERS response of these probes with an optimal Ag shell was highest in the off-resonance mode, when the excitation wavelength was far from the plasmon resonance of the Au@NBT@Ag composites. Growing the Ag shell further to completely cover the AuNRs decreased the SERS enhancement. For biocompatibility and stability, the probes were additionally covered with a thin silica layer. Under optimal conditions, the probes demonstrated superstrong and superstable SERS spectra, as compared to those from common SERS tags (AuNRs, nanostars, and Au@Ag NRs) with surface-adsorbed NBT. The excellent SERS performance of the developed ultrabright probes is illustrated by single-particle detection of SERS spectra, Raman imaging of living cells, and deep tissue imaging

Magnetic Platelets as a Platform for Drug Delivery and Cell Trapping

The possibility of using magnetically labeled blood cells as carriers is a novel approach in targeted drug-delivery systems, potentially allowing for improved bloodstream delivery strategies. Blood cells already meet the requirements of biocompatibility, safety from clotting and blockage of small vessels. It would solve the important problem of the patient’s immune response to embedded foreign carriers. The high efficiency of platelet loading makes them promising research objects for the development of personalized drug-delivery systems. We are developing a new approach to use platelets decorated with magnetic nanoparticles as a targeted drug-delivery system, with a focus on bloodstream delivery. Platelets are non-nuclear blood cells and are of great importance in the pathogenesis of blood-clotting disorders. In addition, platelets are able to attach to circulating tumor cells. In this article, we studied the effect of platelets labeled with BSA-modified magnetic nanoparticles on healthy and cancer cells. This opens up broad prospects for future research based on the delivery of specific active substances by this method

Gold Nanoisland Films as Reproducible SERS Substrates for Highly Sensitive Detection of Fungicides

A wet-chemical approach is used to fabricate centimeter-scale gold nanoisland films (NIFs) with tunable morphology of islands and with strong electromagnetic coupling between them. The approach consists in a uniform seeding of small gold nanoparticles on a glass or silicon substrate, followed by controllable growth of the seeds into small nanoislands. A special technique for TEM sampling was developed to follow the gradual formation of larger-sized isolated nanoparticles, nanoislands of sintered overgrown seeds, and a complete gold layer with nanoscale cracks. The electromagnetic field distribution inside the fabricated NIFs was calculated by FDTD simulations applied to actual TEM images of the fabricated samples rather than to artificial models commonly used. SERS measurements with 1,4-aminothiophenol (ATP) molecules demonstrated the analytical enhancement factor about of 10⁷ and the fundamental enhancement factor about of 10⁸ for optimized substrates. These values were at least 1 order of magnitude higher than that for self-assembled arrays of gold nanostars and silver nanocubes. SERS spectra of independent samples demonstrated good sample-to-sample reproducibility in terms of the relative standard deviation (RSD) of the main peaks less than 20%. Additionally, Raman maps with 1 μm increment in <i>X</i>–<i>Y</i> directions of NIFs (800 spectral spots) demonstrated good point-to-point repeatability in the intensity of the main Raman vibration modes (RSD varied from 5% to 15% for 50 randomly selected points). A real-life application of the fabricated SERS substrates is exemplified by the detection of the thiram fungicide in apple peels within the 5–250 ppb linear detection range. Specifically, the NIF-based SERS technology detected thiram on apple peel down to level of 5 ng/cm²

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, various microorganisms and parasites in the blood during acute blood infections. All of these rare diagnostic objects can be detected and identified very rapidly to save a patient&rsquo;s life. This review outlines the main techniques of visualization of rare objects in the blood flow, methods for extraction of such objects from the blood flow for further investigations and new approaches to identify the objects automatically with the modern deep learning methods

Optical monitoring of adipose tissue destruction under encapsulated lipase action

Enzymatic destruction of adipose tissue has been achieved by encapsulation of lipase into the polymeric microcapsules. Adipose tissue destruction was delayed while lipase is encapsulated comparing with the direct lipase action as demonstrated by optical microscopy and optical coherence tomography in in vitro studies. Raman spectroscopy confirms that triglycerides in fat tissue were cleaved into free fatty acids, glycerol, and possible di- and monoglyceride residues. The results underpin the concept of local and controlled treatment of tissues via encapsulation. Effect of lipase encapsulation into the polymeric microcapsules on adipose tissue destruction compared to free lipase application

Comparing the spectral properties of the laser-induced acoustic responses from blood and cancer cells in vitro

Background ― The treatment of the cancer, especially in more aggressive metastatic forms is more effective at early disease stage. However, existing diagnostic techniques are not sensitive enough for early cancer detection. An alternative, perspective diagnostic approach can be based on photoacoustic (PA) method of irradiation of cancer cells in biotissue, blood and lymph by laser pulses. The fast thermal expansion of heated zones into cells associated with intrinsic or artificial PA contrast agents leads to generation of acoustic waves detected with ultrasound transducers. In particular, melanoma cells with melanin as a PA marker are darker than normal red blood cells and, therefore, produce greater acoustic responses. This technique can theoretically detect even a single cancer cell in the tissue and blood background; however, a robust algorithm of automated response detection is yet to be developed. Objective ― The main aim is to develop the approach for data pre-analysis that can improve the sensitivity and noise resistance of the automated in individual cancer cell detection algorithm, based on estimation of the amplitude of the acoustic responses. Methods ― Acoustic responses were obtained from a round polyurethane tube with human blood, or solution of the mouse melanoma cells in 10 mol/L concentration. In control experiments the laser was blocked by an opaque film. Many (up to 1000) acoustic responses were obtained from normal blood cells and pigmented cancer cells. Spectral analysis of the acoustic responses was used to find the spectral ranges that provide valuable diagnostic information with the sufficient signal-to-noise ratio. Results ― It was estimated that relevant diagnostics information in the acoustic responses is limited to the 0-12 MHz frequency band. Application of the 8th order low-pass Butterwort filter with 12 MHz cut-off frequency improved the signal-to-noise ratio from 21.14±10.39 to 110.81±56.94 for the cancer-related responses, and from 1.04±0.1 to 2.23±0.33 for the normal blood responses. Conclusions ― Adoption of low-pass filtering during the pre-analysis of acoustic responses results in better sensitivity of automated cancer cells detection algorithm