Real-time red blood cell counting and osmolarity analysis using a photoacoustic-based microfluidic system

Design and prediction of laser-induced damage threshold of CNT-PDMS optoacoustic transducer

The optoacoustic transducer has emerged as a new candidate for medical ultrasound applications and attracts considerable attention. Optoacoustic diagnosis and treatment sometimes require high-intensity acoustic pressure, which is often accompanied by the problem of laser-induced damage. Addressing the laser-induced damage phenomenon from a theoretical perspective holds paramount importance. In this study, the theoretical model of laser-induced damage of the carbon nanotubes-polydimethylsiloxane (CNT-PDMS) composite optoacoustic transducer is established. It is found that this laser-induced damage belongs to thermal ablation damage. Furthermore, the correctness of this theory can be confirmed by experimental results. Most importantly, when the laser energy density is less than threshold value of laser energy density, the optoacoustic transducer can work stable for long time. These encouraging results demonstrate that this work can provide significant guidance for the exploration and utilization of optoacoustic transducers.

Dynamic modeling of photoacoustic sensor data to classify human blood samples

The photoacoustic effect is an attractive tool for diagnosis in several biomedical applications. Analyzing photoacoustic signals, however, is challenging to provide qualitative results in an automated way. In this work, we introduce a dynamic modeling scheme of photoacoustic sensor data to classify blood samples according to their physiological status. Thirty-five whole human blood samples were studied with a state-space model estimated by a subspace method. Furthermore, the samples are classified using the model parameters and the linear discriminant analysis algorithm. The classification performance is compared with time- and frequency-domain features and an autoregressive-moving-average model. As a result, the proposed analysis can predict five blood classes: healthy women and men, microcytic and macrocytic anemia, and leukemia. Our findings indicate that the proposed method outperforms conventional signal processing techniques to analyze photoacoustic data for medical diagnosis. Hence, the method is a promising tool in point-of-care devices to detect hematological diseases in clinical scenarios.

WITHDRAWN: Design and prediction of laser-induced damage threshold of CNT-PDMS optoacoustic transducer

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/policies/article-withdrawal.

Non-invasive detection of haemoglobin, platelets, and total bilirubin using hyperspectral cameras

Hyperspectral imaging has emerged as a promising high-resolution and real-time imaging technology with potential applications in medical diagnostics and surgical guidance. In this study, we developed a high-speed hyperspectral camera by integrating a Fabry-Perot cavity filter on each CMOS pixel. We used it to non-invasively detect three blood components (haemoglobin, platelet, and total bilirubin). Specifically, we acquired transmission images of the subject's fingers, extracted spectral signals at each wavelength, and used dynamic spectroscopy to obtain non-invasive blood absorption spectra. The prediction models were established using the PLSR method and were modelled and validated based on the standard clinical-biochemical test values. The experimental results demonstrated excellent performance. The best predictions were obtained for haemoglobin, with a high related coefficient (R) of 0.85 or more in both the calibration and prediction sets and a mean absolute percentage error (MAPE) of only 5.7%. The results for total bilirubin were also ideal, with R values exceeding 0.8 in both sets and a MAPE of 10.6%. Although the prediction results for platelets were slightly less satisfactory, the error was still less than 15%, indicating that the results were also acceptable. Overall, our study highlights the potential of hyperspectral imaging technology for the development of portable and affordable devices for blood analysis, which can be used in various settings.

Upconversion optogenetics-driven biohybrid sensor for infrared sensing and imaging

Living organisms are far superior to state-of-the-art devices in visual perception as they have evolved a wide number of capabilities that encompass our most advanced technologies. By leveraging the performance of living organisms and directly interfacing them with artificial components, it can use the intricacy and metabolic efficiency of biological visual sensing within artificial machines. Inspired by the molecular basis (transient receptor potential, TRP) for infrared detection of pit-bearing organisms, we propose a TRP-like biohybrid sensor by integrating upconversion nanoparticles (UCNP) and optogenetically engineered cells on a graphene transistor for infrared sensing and imaging. The UCNP converts infrared light irradiation into blue light, the blue light activates the cells expressed with channelrhodopsin-2 (ChR2) and induces transmembrane photocurrent, and the photocurrent is detected by a biocompatible graphene transistor. Stepwise and overall experimental results show that, upon infrared light irradiation, the UCNP can rapidly mediate cellular photocurrents, which further translates into the extra output current of the graphene transistor. More notably, the response speed of the biohybrid sensor is 1∼3 orders of magnitude faster than those of TRPs heterologously expressed in cell lines in the literature, which confirms the response time advantage of the combination of UCNP and ChR2 within the sensor in place of TRPs. The biohybrid sensor can successfully image infrared targets, proving the feasibility of developing bionic infrared sensing devices by biohybrid integration of nonliving nanomaterials and biological components. This work opens up an avenue for biohybrid sensors to develop the bionic infrared vision that promisingly reproduces the functional superiority of natural organisms. STATEMENT OF SIGNIFICANCE: Infrared sensing and imaging have a wide range of military and civilian applications. Organisms have evolved excellent infrared vision with the molecular basis, transient receptor potential (TRP), and the performance is superior to existing state-of-the-art infrared devices. Inspired by this, a TRP-like biohybrid sensor based on upconversion optogenetics and a 2D material-based device is developed for infrared sensing and imaging. The biohybrid sensor has a relatively fast response speed that is 1∼3 orders of magnitude faster than that of the heterologously expressed TRPs, which enables its capability of infrared imaging with a single pixel-based method. This work broadens the spectrum of biohybrid sensing based on engineered cells to infrared, advancing the process of reproducing the excellent infrared detection of organisms.

Noninvasive and simultaneous quantitative analysis of multiple human blood components based on the grey analysis system

Noninvasive detection of human blood components is the dream of human beings and the goal of clinical detection. From the perspective of mathematical analysis, based on the grey analysis system, the principle of spectral chemical quantitative analysis and the solution method of multivariate linear equation, this paper pioneers the spectrum elimination method, and obtains a complete, high-precision, synchronous and noninvasive detection system for a variety of human blood components. The spectral elimination method applies the principle of elimination method in mathematics to the noninvasive quantitative analysis of human blood components by spectral method, reduces the influence of non-target components on the detection of target components, and improves the accuracy of noninvasive quantitative analysis of human blood components. To demonstrate the effectiveness of the method, taking the analysis of the contents of seven blood components (hemoglobin, red blood cell count, neutrophils, lymphocytes, monocytes, eosinophils and basophils) in blood as an example, fourteen models were established by two different methods. From the comparison of modeling results, it can be concluded that when the seven models established by spectral elimination method predict the corresponding seven components of all samples, the predicted correlation coefficients are more than 0.9500. The experimental results show that the spectral elimination method and non-invasive detection system proposed can predict the content of human blood components with high accuracy. This paper studies a high-precision, simultaneous and noninvasive quantitative analysis system of multiple human blood components for the first time, which not only makes great progress in the non-invasive chemical quantitative analysis of human blood components by spectroscopy, but also has great application value for clinical medical treatment and disease diagnosis.

Microfluidic Systems for Blood and Blood Cell Characterization

A laboratory blood test is vital for assessing a patient's health and disease status. Advances in microfluidic technology have opened the door for on-chip blood analysis. Currently, microfluidic devices can reproduce myriad routine laboratory blood tests. Considerable progress has been made in microfluidic cytometry, blood cell separation, and characterization. Along with the usual clinical parameters, microfluidics makes it possible to determine the physical properties of blood and blood cells. We review recent advances in microfluidic systems for measuring the physical properties and biophysical characteristics of blood and blood cells. Added emphasis is placed on multifunctional platforms that combine several microfluidic technologies for effective cell characterization. The combination of hydrodynamic, optical, electromagnetic, and/or acoustic methods in a microfluidic device facilitates the precise determination of various physical properties of blood and blood cells. We analyzed the physical quantities that are measured by microfluidic devices and the parameters that are determined through these measurements. We discuss unexplored problems and present our perspectives on the long-term challenges and trends associated with the application of microfluidics in clinical laboratories. We expect the characterization of the physical properties of blood and blood cells in a microfluidic environment to be considered a standard blood test in the future.

A Study on the Uniform Distribution and Counting Method of Raw Cow's Milk Somatic Cells

The somatic cell count (SCC) in raw milk is an important basis for determining whether a cow is suffering from mastitis. To address the problem of an uneven distribution of somatic cells due to cell-adherent sedimentation, among other reasons, during milk sampling, which in turn results in unrepresentative somatic cell counting, a method is proposed for obtaining a uniform distribution of somatic cells and improving the counting accuracy based on a nine-cell grid microfluidic chip. Firstly, a simulation was performed to verify the uniformity of the somatic cell distribution within the chip observation cavities. Secondly, a nine-cell grid microfluidic chip was prepared and a negative-pressure injection system integrating staining and stirring was developed to ensure that the somatic cells were uniformly distributed and free from air contamination during the injection process. As well as the structure of the chip, a microscopic imaging system was developed, and the nine chip observation cavities were photographed. Finally, the somatic cells were counted and the uniformity of the somatic cell distribution was verified using image processing. The experimental results show that the standard deviation coefficient of the SCC in each group of nine images was less than 1.61%. The automatic counting accuracy of the system was between 97.07% and 99.47%. This research method lays the foundation for the detection and prevention of mastitis in cows.

A Review of Advanced Impedance Biosensors with Microfluidic Chips for Single-Cell Analysis

Electrical impedance biosensors combined with microfluidic devices can be used to analyze fundamental biological processes for high-throughput analysis at the single-cell scale. These specialized analytical tools can determine the effectiveness and toxicity of drugs with high sensitivity and demonstrate biological functions on a single-cell scale. Because the various parameters of the cells can be measured depending on methods of single-cell trapping, technological development ultimately determine the efficiency and performance of the sensors. Identifying the latest trends in single-cell trapping technologies afford opportunities such as new structural design and combination with other technologies. This will lead to more advanced applications towards improving measurement sensitivity to the desired target. In this review, we examined the basic principles of impedance sensors and their applications in various biological fields. In the next step, we introduced the latest trend of microfluidic chip technology for trapping single cells and summarized the important findings on the characteristics of single cells in impedance biosensor systems that successfully trapped single cells. This is expected to be used as a leading technology in cell biology, pathology, and pharmacological fields, promoting the further understanding of complex functions and mechanisms within individual cells with numerous data sampling and accurate analysis capabilities.