field-deployable-lens-free-imaging-platform-for-rapid-label-free

Field-Deployable Lens-Free Imaging Platform for Rapid Label-Free Analysis of Natural Killer Cell Activation

Natural killer (NK) cells are important effectors of innate immunity that eliminate virus-infected and malignant cells. Monitoring NK cell activity is ...

Korea University

The refractive index (RI), an important optical property of a material, is measured by commercial refractometers in the food, agricultural, chemical, and manufacturing industries. Most of these refractometers must be equipped with a prism for light dispersion, which drastically limits the design and size of the refractometer. Recently, there have been several reports on the development of a surface plasmon resonance (SPR)-based RI detector, which is characterized by its high sensitivity and simplicity. However, regardless of the prism, an expensive spectrometer is required to analyze the resonance wavelength or angle of incidence. This paper proposes a method that eliminates the need for the prism and other conventional spectrometer components. For this purpose, total internal reflection SPR technology was used on an Ag thin film, and RI analysis was combined with a lens-free CMOS image sensor or a smartphone camera. A finite-difference time-domain (FDTD) numerical simulation was performed to evaluate the relationship between the output power intensity and Ag film thickness for different RIs at three wavelengths of commercial light-emitting diodes (LEDs). The maximum sensitivity of -824.54 RIU was achieved with AG20 at an incident wavelength of 559 nm. Due to its simple design and cost effectiveness, this prism-less, SPR-based refractometer combined with a lens-free CMOS image sensor or a smartphone could be a superior candidate for a point-of-care device that can determine the RIs of various analytes in the field of biological or chemical sensing.

A CMOS Image Sensor Based Refractometer without Spectrometry.

The complete blood count (CBC) is one of the most important clinical steps in clinical diagnosis. The instruments used for CBC are usually expensive and bulky and require well-trained operators. Therefore, it is difficult for medical institutions below the tertiary level to provide these instruments, especially in underprivileged countries. Several reported on-chip blood cell tests are still in their infancy and do not deviate from conventional microscopic or impedance measurement methods. In this study, we (i) combined magnetically activated cell sorting and the differential density method to develop a method to selectively isolate three types of leukocytes from blood and obtain samples with high purity and concentration for portable leukocyte classification using the lens-free shadow imaging technique (LSIT), and (ii) established several shadow parameters to identify the type of leukocytes in a complete leukocyte shadow image by shadow image analysis. The purity of the separated leukocytes was confirmed by flow cytometry. Several shadow parameters such as the "order ratio" and "minimum ratio" were developed to classify the three types of leukocytes. A shadow image library corresponding to each type of leukocyte was created from the tested samples. Compared with clinical reference data, a correlation index of 0.98 was obtained with an average error of 6% and a confidence level of 95%. This technique offers great potential for biological, pharmaceutical, environmental, and clinical applications, especially where point-of-care detection of rare cells is required.

Field-Portable Leukocyte Classification Device Based on Lens-Free Shadow Imaging Technique.

Quantum dots (QDs) have emerged as an important class of materials for diverse applications such as solid-state lighting, energy conversion, displays, biomedicine, and plasmonics due to their excellent photonic properties and durability. Soft lithography, inkjet printing, nanoimprinting, and polymer deep-pen lithography are primary lithography techniques employed to implement micro-patterns with QDs, however, there are limited reports on QD photolithography using conventional photolithography processes suitable for mass production. This study reports a QD photolithography technique using a custom-developed QD photoresist made of an organic-inorganic hybrid coating layer. Using this QD photoresist, various QD micro-patterns, including red or green micro lines, RGB color filters for smartphone displays at 340 ppi, and atypical micro logo patterns of the Korea University, were successfully fabricated. Furthermore, various process parameters were developed for the QD photolithography with this custom QD photoresist, and the optical properties of the QD films were also investigated. To demonstrate its applicability in contemporary smartphone displays, the color coordinates of the QD films were compared to those of the BT.2020 standard. The chromaticity of the QD photoresist in CIE 1931 color space covered 98.7% of the NTSC (1987) area while providing more expansive color space. Overall, the QD photoresist and its photolithography techniques reported in this study hold great promise in various fields of QD-based applications, including bio-labeling, optical detectors, and solar cells.

Quantum dot photolithography using a quantum dot photoresist composed of an organic-inorganic hybrid coating layer.

Glancing angle deposition (GLAD) is a technique for the fabrication of sculpted micro- and nanostructures under the conditions of oblique vapor flux incident and limited adatom diffusion. GLAD-based nanostructures are emerging platforms with broad sensing applications due to their high sensitivity, enhanced optical and catalytic properties, periodicity, and controlled morphology. GLAD-fabricated nanochips and substrates for chemical and biosensing applications are replacing conventionally used nanomaterials due to their broad scope, ease of fabrication, controlled growth parameters, and hence, sensing abilities. This review focuses on recent advances in the diverse nanostructures fabricated via GLAD and their applications in the biomedical field. The effects of morphology and deposition conditions on GLAD structures, their biosensing capability, and the use of these nanostructures for various biosensing applications such as surface plasmon resonance (SPR), fluorescence, surface-enhanced Raman spectroscopy (SERS), and colorimetric- and wettability-based bio-detection will be discussed in detail. GLAD has also found diverse applications in the case of molecular imaging techniques such as fluorescence, super-resolution, and photoacoustic imaging. In addition, some in vivo applications, such as drug delivery, have been discussed. Furthermore, we will also provide an overview of the status of GLAD technology as well as future challenges associated with GLAD-based nanostructures in the mentioned areas.

GLAD Based Advanced Nanostructures for Diversified Biosensing Applications: Recent Progress.

The accidental spill of hazardous and noxious substances (HNSs) in the ocean has serious environmental and human health consequences. Assessing the ecotoxicity of seawater exposed to various HNS is challenging due to the constant development of new HNS or mixtures, and assessment methods are also limited. Microalgae viability tests are often used among the various biological indicators for ecotoxicity testing, as they are the primary producers in aquatic ecosystems. However, since the conventional cell growth rate test measures cell viability over three to four days using manual inspection under a conventional optical microscope, it is labor- and time-intensive and prone to subjective errors. In this study, we propose a rapid and automated method to evaluate seawater ecotoxicity by quantification of the morphological changes of microalgae exposed to more than 30 HNSs. This method was further validated using conventional growth rate test results. Dunaliella tertiolecta, a microalgae species without rigid cell walls, was selected as the test organism. Its morphological changes in response to HNS exposure were measured at the single cell level using a custom-developed device that uses lens-free shadow imaging technology. The ecotoxicity evaluation induced by the morphological change could be available in as little as 5 min using the proposed method and device, and it could be effective for 20 HNSs out of 30 HNSs tested. Moreover, the test results of six selected HNSs with high marine transport volume and toxicity revealed that the sensitivity of the proposed method extends to half the maximum effective concentration (EC50) and even to the lowest observed effective concentration (LOEC). Furthermore, the average correlation index between the growth inhibition test (three to four days) and the proposed morphology changes test (5 min) for the six selected HNSs was 0.84, indicating great promise in the field of various point-of-care water quality monitoring. Thus, the proposed equipment and technology may provide a viable alternative to traditional on-site toxicity testing, and the potential of rapid morphological analysis may replace traditional growth inhibition testing.

Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology.

Plasmonics is the study of surface plasmons formed by the interaction of incident light with electrons to form a surface-bound electromagnetic wave [...].

Plasmonic Sensors: A New Frontier in Nanotechnology.

Smartphone-based point-of-care testing (POCT) is rapidly emerging as an alternative to traditional screening and laboratory testing, particularly in resource-limited settings. In this proof-of-concept study, we present a smartphone- and cloud-based artificial intelligence quantitative analysis system (SCAISY) for relative quantification of SARS-CoV-2-specific IgG antibody lateral flow assays that enables rapid evaluation (<60 s) of test strips. By capturing an image with a smartphone camera, SCAISY quantitatively analyzes antibody levels and provides results to the user. We analyzed changes in antibody levels over time in more than 248 individuals, including vaccine type, number of doses, and infection status, with a standard deviation of less than 10%. We also tracked antibody levels in six participants before and after SARS-CoV-2 infection. Finally, we examined the effects of lighting conditions, camera angle, and smartphone type to ensure consistency and reproducibility. We found that images acquired between 45° and 90° provided accurate results with a small standard deviation and that all illumination conditions provided essentially identical results within the standard deviation. A statistically significant correlation was observed (Spearman correlation coefficient: 0.59,  = 0.008; Pearson correlation coefficient: 0.56,  = 0.012) between the OD450 values of the enzyme-linked immunosorbent assay and the antibody levels obtained by SCAISY. This study suggests that SCAISY is a simple and powerful tool for real-time public health surveillance, enabling the acceleration of quantifying SARS-CoV-2-specific antibodies generated by either vaccination or infection and tracking of personal immunity levels.

Proof-of-Concept: Smartphone- and Cloud-Based Artificial Intelligence Quantitative Analysis System (SCAISY) for SARS-CoV-2-Specific IgG Antibody Lateral Flow Assays.

Micro/nano patterns based on quantum dots (QDs) are of great interest for applications ranging from electronics to photonics to sensing devices for biomedical purposes. Several patterning methods have been developed, but all lack the precision and reproducibility required to fabricate precise, complex patterns of less than one micrometer in size, or require specialized crosslinking ligands, limiting their application. In this study, we present a novel approach to directly pattern QD nanopatterns by electron beam lithography using commercially available colloidal QDs without additional modifications. We have successfully generated reliable dot and line QD patterns with dimensions as small as 140 nm. In addition, we have shown that using a 10 nm SiO spacer layer on a 50 nm Au layer substrate can double the fluorescence intensity compared to QDs on the Au layer without SiO. This method takes advantage of traditional nanolithography without the need for a resist layer.

Colloidal Quantum Dot Nanolithography: Direct Patterning via Electron Beam Lithography.

Fluorescent microbeads (MBs) are widely used as next-generation biosensors for the detection of target chemicals at highly sensitive concentrations, and for imaging and tracking  and . However, most known methods for producing fluorescent MBs require complicated multistep processes that result in low production rates. In this study, we report a method for fabricating micrometer-sized quantum dot microbeads (QD-MBs) using a microfluidic chip and specially designed QD photoresist (QD-PR). This on-demand lab-on-a-chip method yielded monodispersed QD-MBs ranging from 1.89 to 33 μm with a coefficient of variation of less than 10%. The size distribution of the fabricated QD-MBs was Gaussian with a peak around the mean diameter and a spread of sizes around the peak. Compared with nanoscale QDs, the fabricated QD-MBs showed no emission loss. The full-width at half-maximum of the emission peak of the QD-MBs was smaller than that of the colloidal QDs, indicating a more uniform distribution and a higher density of QDs within the MB structure. In addition, we investigated the microfluidic flow regime that yielded the most uniform and controllable QD-MB. The MBs in the dripping regime were spherical and monodisperse, with an excellent particle size distribution. In this study, we present a simple and effective strategy for producing QD-MBs with controllable sizes, which can be crucial in diverse fields such as biosensing, drug delivery, and imaging.

Facile microfluidic synthesis of monodispersed size-controllable quantum dot (QD) microbeads using custom developed QD photoresist.

Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, such as flow cytometry, are complex, time-consuming, and require specialized expertise and equipment. This study proposes a novel approach for the label-free identification of CD34+ cells using a deep learning model and lens-free shadow imaging technology (LSIT). LSIT is a portable and user-friendly technique that eliminates the need for cell staining, enhances accessibility to nonexperts, and reduces the risk of sample degradation. The study involved three phases: sample preparation, dataset generation, and data analysis. Bone marrow and peripheral blood samples were collected from leukemia patients, and mononuclear cells were isolated using Ficoll density gradient centrifugation. The samples were then injected into a cell chip and analyzed using a proprietary LSIT-based device (Cellytics). A robust dataset was generated, and a custom AlexNet deep learning model was meticulously trained to distinguish CD34+ from non-CD34+ cells using the dataset. The model achieved a high accuracy in identifying CD34+ cells from 1929 bone marrow cell images, with training and validation accuracies of 97.3% and 96.2%, respectively. The customized AlexNet model outperformed the Vgg16 and ResNet50 models. It also demonstrated a strong correlation with the standard fluorescence-activated cell sorting (FACS) technique for quantifying CD34+ cells across 13 patient samples, yielding a coefficient of determination of 0.81. Bland-Altman analysis confirmed the model's reliability, with a mean bias of -2.29 and 95% limits of agreement between 18.49 and -23.07. This deep-learning-powered LSIT offers a groundbreaking approach to detecting CD34+ cells without the need for cell staining, facilitating rapid CD34+ cell classification, even by individuals without prior expertise.

Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology.

Natural killer (NK) cells are a crucial component of the innate immune system. This study introduces Cellytics NK, a novel platform for rapid and precise measurement of NK cell activity. This platform combines an NK-specific activation stimulator cocktail (ASC) and lens-free shadow imaging technology (LSIT), using optoelectronic components. LSIT captures digital hologram images of resting and ASC-activated NK cells, while an algorithm evaluates cell size and cytoplasmic complexity using shadow parameters. The combined shadow parameter derived from the peak-to-peak distance and width standard deviation rapidly distinguishes active NK cells from inactive NK cells at the single-cell level within 30 s. Here, the feasibility of the system was demonstrated by assessing NK cells from healthy donors and immunocompromised cancer patients, demonstrating a significant difference in the innate immunity index (I). Cancer patients showed a lower I value (161%) than healthy donors (326%). I was strongly correlated with NK cell activity measured using various markers such as interferon-gamma, tumor necrosis factor-alpha, perforin, granzyme B, and CD107a. This technology holds promise for advancing immune functional assays, offering rapid and accurate on-site analysis of NK cells, a crucial innate immune cell, with its compact and cost-effective optoelectronic setup, especially in the post-COVID-19 era.

Use of a platform with lens-free shadow imaging technology to monitor natural killer cell activity.

Morphological changes in leukocytes are valuable markers for diseases and immune responses. In our earlier work, we presented Cellytics, a device that uses lens-free shadow imaging technology (LSIT) to monitor natural killer cell activity. Here, we present an improved Cellytics system that has been upgraded to a four-channel configuration to achieve higher throughput while maintaining robust reproducibility for rapid and cost-effective leukocyte analysis. The performance of this multi-channel Cellytics system was improved through refinements to the micro-pinhole chip. Etched pinholes provided better image resolution and clarity compared to drilled pinholes. To stimulate leukocytes, we used an activation stimulator cocktail (ASC) and quantified the resulting morphological changes using shadow-based metrics, including peak-to-peak distance (PPD) and maxima-to-minima standard deviation (MMD-SD). In addition, we developed a new leukocyte activation parameter (LAP) to specifically assess these activation-induced morphological changes. After ASC stimulation, leukocytes showed significantly increased PPD and LAP values and decreased MMD-SD compared to non-activated leukocytes. These results are consistent with the results of the flow cytometric analysis. These results emphasize the potential of Cellytics for the rapid and accurate assessment of leukocyte activation and provide a valuable tool for both clinical diagnostics and basic immunological research.

Article	Year
A CMOS Image Sensor Based Refractometer without Spectrometry. Sensors (Basel, Switzerland)\| PubMed ID: 35161953	2022
Field-Portable Leukocyte Classification Device Based on Lens-Free Shadow Imaging Technique. Biosensors\| PubMed ID: 35200308	2022
Quantum dot photolithography using a quantum dot photoresist composed of an organic-inorganic hybrid coating layer. Nanoscale advances\| PubMed ID: 36131767	2022
GLAD Based Advanced Nanostructures for Diversified Biosensing Applications: Recent Progress. Biosensors\| PubMed ID: 36551082	2022
Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology. Water research\| PubMed ID: 36638739	2023
Plasmonic Sensors: A New Frontier in Nanotechnology. Biosensors\| PubMed ID: 36979597	2023
Proof-of-Concept: Smartphone- and Cloud-Based Artificial Intelligence Quantitative Analysis System (SCAISY) for SARS-CoV-2-Specific IgG Antibody Lateral Flow Assays. Biosensors\| PubMed ID: 37366988	2023
Colloidal Quantum Dot Nanolithography: Direct Patterning via Electron Beam Lithography. Nanomaterials (Basel, Switzerland)\| PubMed ID: 37513122	2023
Facile microfluidic synthesis of monodispersed size-controllable quantum dot (QD) microbeads using custom developed QD photoresist. Nanoscale\| PubMed ID: 37861429	2023
Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology. Biosensors\| PubMed ID: 38131753	2023
Use of a platform with lens-free shadow imaging technology to monitor natural killer cell activity. Biosensors & bioelectronics\| PubMed ID: 38908292	2024
Multi-Channel Cellytics for Rapid and Cost-Effective Monitoring of Leukocyte Activation. Biosensors\| PubMed ID: 40136941	2025

Samir Kumar

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