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An elaboration of the photonic based sensors is the most promising direction in modern analytical chemistry from the point of view of real clinical applications. The highest sensitivity is demonstrated by sensors based on photonic integrated circuits (PICs). This type of sensor has been recently successfully combined with microfluidics, which decreased the analyte volume for analysis down to microliter units. The most significant disadvantage regarding these photonic sensors is low specificity. One of the methods that could be useful for such type of problem is the layer by layer (LBL) assembly. The peculiarity of a PIC based sensor is the ability to precisely control surface modification by using measurements of a minimum resonance position shift. The bovine serum albumin (BSA) and tannic acid (TA) molecules were selected for LBL assembly because on one side they form a stable LBL assembly film based on hydrogen bonds, while the other side of both TA and BSA molecules can be used for conjugation with target molecules. A microring resonator (MRR) and a Mach-Zehnder interferometer (MZI) based on a silicon nitride platform combined with a microfluidic system were elaborated and used for monitoring the LBL film assembly. Obtained results have a good correlation with measurements carried out by atom force microscopy. Thus, the ability of using PIC based sensors for

Tissue trauma often causes hematoma formation. Recently, we proposed to use the optoacoustic technique for hematoma detection and performed studies on hematoma monitoring and imaging in the brain and skin. It is well known that methemoglobin is produced during hematoma aging. In this work we propose to use the optoacoustic technique for staging, monitoring, and imaging of hematomas during their formation and aging. We measured optoacoustic spectra of methemoglobin in the 800-950 nm spectral range in which it has strong absorption and demonstrated that this spectral range can be used for of hematoma staging, monitoring, and imaging.

Extracellular vesicle (EV) quantification is a procedure through which the biomedical potential of EVs can be used and their biological function can be understood. The number of EVs isolated from cell culture media depends on the cell status and is especially important in studies on cell-to-cell signaling, disease modeling, drug development, etc. Currently, the methods that can be used to quantify isolated EVs are sparse, and each have limitations. In this report, we introduce the application of a quartz crystal microbalance (QCM) as a biosensor for quantifying EVs in a small drop of volatile solvent after it evaporates and leaves desiccated EVs on the surface of the quartz crystal. The shifts in the crystal’s resonant frequency were found to obey Sauerbrey’s relation for EV quantities up to 6 × 107, and it was determined that the biosensors could resolve samples that differ by at least 2.7 × 105 EVs. A ring-shaped pattern enriched in EVs after the samples had dried on the quartz crystal is also reported and discussed. QCM technology is highly sensitive and only requires small sample volumes and is significantly less costly compared with the approaches that are currently used for EV quantification.

Today, a lab-on-a-chip is one of the most promising ways to create sensor devices for gas and liquid analysis for environmental monitoring, early diagnosis, and treatment effectiveness assessment. On the one hand, this requires a large number of measurements and, on the other hand, involves minimum consumption of the test analytes. Combination of highly sensitive photonic integrated circuits (PICs) with microfluidic channels (MFCs) is necessary to solve this problem. In this work, PICs based on a silicon nitride platform integrated with MFCs for studying liquids and gases were developed. Different concentrations of isopropanol in de-ionized water were used as the analyte. Based on this, the sensitivity (S) and detection limit (DL) of the analyzed solution were evaluated. Entire system calibration was carried out to calculate S and DL, considering experimental and numerical simulation data. This development may be of interest as a promising platform for environmental monitoring and realization of point-of-care strategy for biomedical applications.