Melanin diagnostics with nonlinear optics: a mini-review

Optical methods are widely used to perform fundamental studies of living systems and solve problems of biomedical diagnostics. Along with the classical spectroscopy, methods of nonlinear optics (e.g., multiphoton microscopy) are also applied in biophotonics. The potential of nonlinear optical methods for visualisation and analysis of the properties of endogenous chromophore molecules are considered in this minireview. Melanin - a pigment with specific spectral features of photophysical properties in the visible and near-IR ranges - is taken as an example. It is discussed what information about its localisation in tissues and structural organisation can be obtained by nonlinear optical methods: multiphoton fluorescence microscopy (including fluorescence lifetime imaging), third harmonic generation, pump - probe spectroscopy, and coherent anti- Stokes Raman spectroscopy.

Photon-counting distributed free-space spectroscopy

Spectroscopy is a well-established nonintrusive tool that has played an important role in identifying and quantifying substances, from quantum descriptions to chemical and biomedical diagnostics. Challenges exist in accurate spectrum analysis in free space, which hinders us from understanding the composition of multiple gases and the chemical processes in the atmosphere. A photon-counting distributed free-space spectroscopy is proposed and demonstrated using lidar technique, incorporating a comb-referenced frequency-scanning laser and a superconducting nanowire single-photon detector. It is suitable for remote spectrum analysis with a range resolution over a wide band. As an example, a continuous field experiment is carried out over 72 h to obtain the spectra of carbon dioxide (CO2) and semi-heavy water (HDO, isotopic water vapor) in 6 km, with a range resolution of 60 m and a time resolution of 10 min. Compared to the methods that obtain only column-integrated spectra over kilometer-scale, the range resolution is improved by 2–3 orders of magnitude in this work. The CO2 and HDO concentrations are retrieved from the spectra acquired with uncertainties as low as ±1.2% and ±14.3%, respectively. This method holds much promise for increasing knowledge of atmospheric environment and chemistry researches, especially in terms of the evolution of complex molecular spectra in open areas.

Sensor Applications in Analysis of Drugs and Formulations

Biosensors are currently widely used in biomedical diagnostics, as well as point-of-care assessment of therapy and disease advancement, environmental sensing, food safety, drug development, forensics, and biomedical research. Biosensors may be developed using several different approaches. Due to the growing requirement for efficient and low-cost analytical methods, biosensors have gained increasing attention for application in the quality analysis of pharmaceuticals and other pharmaceutically relevant analytes. Biosensors enable the analysis of active ingredients in pharmaceutical formulations as well as the determination of degraded products and intermediates in biological matrices. The current study discusses several types of biosensors and their applications in drug analysis and formulations.

Application of Raman Spectroscopy in Biomedical Diagnostics

In vivo cellular imaging and in vitro assays or sensors are fundamentally used to study the spatiotemporal interaction of molecules at biological interfaces. The study of these interfaces informs various applications such as diagnostics/detection of foreign materials or processes in the biological system. Raman spectroscopy, an optical, non-destructive, label-free fingerprinting tool offers a wide array of applications in both in vitro and in vivo diagnostics owing to its relatively short acquisition time, non-invasiveness and ability to provide biochemical molecular information. It has been explored in tissue imaging, in vitro diagnosis, DNA/RNA analysis, metabolic accretions, single cell analysis photodynamic therapy, etc. The chapter details the application of the optical Raman platform in the detection and imaging of diseases/tissues. The challenges associated with SERS applications and the future outlook as a biomedical diagnostic tool are also discussed.

Dynamic near-field microwave diagnostics of lungs.

Results of theoretical and experimental studies of the method of the near-field microwave tomography of the thorax are presented. Integral equations of inverse tomography problem of 3D blood- and air content inhomogeneities by data of multisensory measurements are obtained. Methods of air and blood content profiling in processes of breathing and heart activity by data of bistatic measurements of the scattered signal are proposed and solving algorithms of inverse problems are studied in the numerical simulation. Multifrequency and pulse measurements of scattered signals are carried out in processes of cardiorespiratory activity. By data of bistatic measurements of scattered signals parameters from the thorax, profiling relative air- and blood content profiles has been realized. Application possibilities of the method in the biomedical diagnostics are considered.

Ionic Liquid-Based Quartz Crystal Microbalance Sensors for Organic Vapors: A Tutorial Review

Organic vapor sensors are used in diverse applications ranging from environmental monitoring to biomedical diagnostics. Among a number of these sensors, quartz crystal microbalance (QCM) sensors prepared by coating ionic liquids (ILs) or their composites are promising devices for the analysis of volatile organic compounds (VOCs) in complex chemical mixtures. Ionic liquids are remarkable materials, which exhibit tunable physico-chemical properties, chemical and thermal stability, multiple interactions with diverse group of molecules, and enormous structural variability. Moreover, ILs exhibit viscoelastic properties, and hence these materials are ideal for creation of QCM virtual sensor arrays. While the scientific literature on IL-coated QCM sensors is rapidly growing, there is still much to learn. This manuscript provides a comprehensive review on the development of IL-coated QCM sensors and multi-sensor arrays as well as their applications for the analysis of VOCs in complex mixtures. Furthermore, IL-coated QCM virtual sensor arrays and their applications are presented. A short overview of some of the QCM designs, future research areas, and recommendations are also discussed. This short review is a necessary first step towards standardization and further development of QCM for the analysis of VOCs.

U-Net-Based Surrogate Model for Evaluation of Microfluidic Channels

Microfluidics have shown great promise in multiple applications, especially in biomedical diagnostics and separations. While the flow properties of these microfluidic devices can be solved by numerical methods such as computational fluent dynamics (CFD), the process of mesh generation and setting up a numerical solver requires some domain familiarity, while more intuitive commercial programs such as fluent and StarCCM can be expensive. Hence, in this work, we demonstrated the use of a U-Net convolutional neural network as a surrogate model for predicting the velocity and pressure fields that would result for a particular set of microfluidic filter designs. The surrogate model is fast, easy to set-up and can be used to predict and assess the flow velocity and pressure fields across the domain for new designs of interest via the input of a geometry-encoding matrix. In addition, we demonstrate that the same methodology can also be used to train a network to predict pressure based on velocity data, and propose that this can be an alternative to numerical algorithms for calculating pressure based on velocity measurements from particle image velocimetry measurements. Critically, in both applications, we demonstrate prediction test errors of less than 1%, suggesting that this is indeed a viable method.

A Survey on Biomedical Informatics for Computer-Aided Decision Support System

Biomedical computing for computer-aided biomedical diagnostics and the decision support system has developed a platform for the biomedical setting during the last few decades. As early as 1971, there were elaborate and basic applications of management information systems driven by biomedical informatics. According to a 1994 assessment, this field's literature stretches back to the 1950s. Medical decision is more challenging than ever for doctors and other caregivers due to the amount and complexity of contemporary patient information. This circumstance necessitates the application of medical computing technologies to evaluate data and formulate suggestions and/or forecasts to aid decision makers. Over the past two decades, healthcare informatics tools, such as computer-aided decision support, have grown indispensable and extensively employed. This article gives a quick overview of such technologies, their productivity applications and methodology, as well as the problems and directions they imply for the future.