Detection of waterborne parasites using field-portable and cost-effective lensfree microscopy

Integrated Point-of-Care Immune Cell Analyzer with Rapid Blood Sample Reaction and Wide Field-of-View Detection

The development of affordable, reliable, and rapid diagnostic devices is crucial for monitoring immunological responses using a drop of blood. However, conventional automated diagnostic devices typically involve expensive and impractical robotic fluid-handling approaches. Herein, we developed an integrated cell analyzer comprising a cylindrical sample cartridge connected to a direct current motor and a compact fluorescence imaging module. Sample mixing and loading are performed automatically by a programmable sequence of single motor rotation controlled by an Android application. Two distinct stained immune cell samples can be identified by using two types of fluorescence imaging modes. The effectiveness of mixing performance in antigen-antibody (Ag-Ab) reactions was assessed through a compound objective lens that collects weak fluorescence emitted by the cell membrane. Active mixing with bidirectional rotation of the cartridge in a confined space shortened the Ag-Ab reaction time by a factor of 3.3 and achieved cell counting with higher accuracy while reducing reagent consumption by 4 times compared to the conventional incubation method. High-intensity fluorescence images of cells labeled with a nucleic acid stain were acquired through a single-lens-based fluorescence imaging module with a large field of view (FOV) in an unconventional detection chamber with a curved substrate. Compared with a flat chamber, the curved detection chamber reduces the effects of field curvature and provides aberration-free wide-FOV images, even with a simple lens. Our integrated cell analyzer thus offers a practical and cost-effective solution for monitoring patient immune responses in point-of-care settings.

Fluorescence-Based Portable Assays for Detection of Biological and Chemical Analytes

Fluorescence-based detection techniques are part of an ever-expanding field and are widely used in biomedical and environmental research as a biosensing tool. These techniques have high sensitivity, selectivity, and a short response time, making them a valuable tool for developing bio-chemical assays. The endpoint of these assays is defined by changes in fluorescence signal, in terms of its intensity, lifetime, and/or shift in spectrum, which is monitored using readout devices such as microscopes, fluorometers, and cytometers. However, these devices are often bulky, expensive, and require supervision to operate, which makes them inaccessible in resource-limited settings. To address these issues, significant effort has been directed towards integrating fluorescence-based assays into miniature platforms based on papers, hydrogels, and microfluidic devices, and to couple these assays with portable readout devices like smartphones and wearable optical sensors, thereby enabling point-of-care detection of bio-chemical analytes. This review highlights some of the recently developed portable fluorescence-based assays by discussing the design of fluorescent sensor molecules, their sensing strategy, and the fabrication of point-of-care devices.

sPhaseStation: a whole slide quantitative phase imaging system based on dual-view transport of intensity phase microscopy

Whole slide imaging scans a microscope slide into a high-resolution digital image, and it paves the way from pathology to digital diagnostics. However, most of them rely on bright-field and fluorescence imaging with sample labels. In this work, we designed sPhaseStation, which is a dual-view transport of intensity phase microscopy-based whole slide quantitative phase imaging system for label-free samples. sPhaseStation relies on a compact microscopic system with two imaging recorders that can capture both under and over-focus images. Combined with the field of view (FoV) scan, a series of these defocus images in different FoVs can be captured and stitched into two FoV-extended under and over-focus ones, which are used for phase retrieval via solving the transport of intensity equation. Using a 10× micro-objective, sPhaseStation reaches the spatial resolution of 2.19 µm and obtains the phase with high accuracy. Additionally, it acquires a whole slide image of a 3m m×3m m region in 2 min. The reported sPhaseStation could be a prototype of the whole slide quantitative phase imaging device, which may provide a new perspective for digital pathology.

Toward waterborne protozoa detection using sensing technologies

Drought and limited sufficient water resources will be the main challenges for humankind during the coming years. The lack of water resources for washing, bathing, and drinking increases the use of contaminated water and the risk of waterborne diseases. A considerable number of waterborne outbreaks are due to protozoan parasites that may remain active/alive in harsh environmental conditions. Therefore, a regular monitoring program of water resources using sensitive techniques is needed to decrease the risk of waterborne outbreaks. Wellorganized point-of-care (POC) systems with enough sensitivity and specificity is the holy grail of research for monitoring platforms. In this review, we comprehensively gathered and discussed rapid, selective, and easy-to-use biosensor and nanobiosensor technologies, developed for the early detection of common waterborne protozoa.

Multi-Illumination Single-Holographic-Exposure Lensless Fresnel (MISHELF) Microscopy: Principles and Biomedical Applications

Lensless holographic microscopy (LHM) comes out as a promising label-free technique since it supplies high-quality imaging and adaptive magnification in a lens-free, compact and cost-effective way. Compact sizes and reduced prices of LHMs make them a perfect instrument for point-of-care diagnosis and increase their usability in limited-resource laboratories, remote areas, and poor countries. LHM can provide excellent intensity and phase imaging when the twin image is removed. In that sense, multi-illumination single-holographic-exposure lensless Fresnel (MISHELF) microscopy appears as a single-shot and phase-retrieved imaging technique employing multiple illumination/detection channels and a fast-iterative phase-retrieval algorithm. In this contribution, we review MISHELF microscopy through the description of the principles, the analysis of the performance, the presentation of the microscope prototypes and the inclusion of the main biomedical applications reported so far.

Label-free detection and enumeration of Giardia cysts in agitated suspensions using in situ microscopy

Laboratory procedures performed in water treatment studies frequently require the characterization of (oo)cyst suspensions. Standard methods commonly used are laborious, expensive and time-consuming, besides requiring well-trained personnel to prepare samples with fluorescent staining and perform analysis under fluorescence microscopy. In this study, an easy cost-effective in situ microscope was assessed to acquire images of Giardia cysts directly from agitated suspensions without using any chemical labels or sample preparation steps. An image analysis algorithm analyzes the acquired images, and automatically enumerates and provides morphological information of cysts within 10 min. The proposed system was evaluated at different cyst concentrations, achieving a limit of detection of ~30 cysts/mL. The proposed system overcomes cost, time and labor demands by standard methods and has the potential to be an alternative technique for the characterization of Giardia cyst suspensions in resource-limited facilities, since it is independent of experts and free of consumables.

Resolution and Contrast Enhancement for Lensless Digital Holographic Microscopy and Its Application in Biomedicine

An important imaging technique in biomedicine, the conventional optical microscopy relies on relatively complicated and bulky lens and alignment mechanics. Based on the Gabor holography, the lensless digital holographic microscopy has the advantages of light weight and low cost. It has developed rapidly and received attention in many fields. However, the finite pixel size at the sensor plane limits the spatial resolution. In this study, we first review the principle of lensless digital holography, then go over some methods to improve image contrast and discuss the methods to enhance the image resolution of the lensless holographic image. Moreover, the applications of lensless digital holographic microscopy in biomedicine are reviewed. Finally, we look forward to the future development and prospect of lensless digital holographic technology.

Self-adjustment of spectral components to object wave field extraction in off-axis digital holography

In this paper, we introduce a positioning system to self-adjust the spectral components of holograms recorded by an off-axis digital holography setup. The incidence angle of the reference arm is carried out by two motorized actuators controlled by an algorithm that automatically adjusts it to avoid the overlapping of the spectral components. The right positioning of the spectral components allows selection of a spectral region to extract only the virtual component so that, after an inverse Fourier transformation, the object wave field can be obtained, thus eliminating the undesired components and increasing the image quality of the reconstructed image.

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Lensless holographic microscope (LHM) is an emerging very promising technology that provides high-quality imaging and analysis of biological samples without utilizing any lens for imaging. Due to its small size and reduced price, LHM can be a very useful tool for the point-of-care diagnosis of diseases, sperm assessment, or microfluidics, among others, not only employed in advanced laboratories but also in poor and/or remote areas. Recently, several LHMs have been reported in the literature. However, complete characterization of their optical parameters remains not much presented yet. Hence, we present a complete analysis of the performance of a compact, reduced cost, and high-resolution LHM. In particular, optical parameters such as lateral and axial resolutions, lateral magnification, and field of view are discussed into detail, comparing the experimental results with the expected theoretical values for different layout configurations. We use high-resolution amplitude and phase test targets and several microbeads to characterize the proposed microscope. This characterization is used to define a balanced and matched setup showing a good compromise between the involved parameters. Finally, such a microscope is utilized for visualization of static, as well as dynamic biosamples.

Comprehensive review of conventional and state-of-the-art detection methods of Cryptosporidium

Cryptosporidium is a critical waterborne protozoan pathogen found in water resources that have been a major cause of death and serious illnesses worldwide, costing millions of dollars annually for its detection and treatment. Over the past several decades, substantial efforts have been made towards developing techniques for the detection of Cryptosporidium. Early diagnostic techniques were established based on the existing tools in laboratories, such as microscopes. Advancements in fluorescence microscopy, immunological, and molecular techniques have led to the development of several kits for the detection of Cryptosporidium spp. However, these methods have several limitations, such as long processing times, large sample volumes, the requirement for bulky and expensive laboratory tools, and the high cost of reagents. There is an urgent need to improve these existing techniques and develop low-cost, portable and rapid detection tools for applications in the water quality industry. In this review, we compare recent advances in nanotechnology, biosensing and microfluidics that have facilitated the development of sophisticated tools for the detection of Cryptosporidium spp.Finally, we highlight the advantages and disadvantages, of these state-of-the-art detection methods compared to current analytical methodologies and discuss the need for future developments to improve such methods for detecting Cryptosporidium in the water supply chain to enable real-time and on-site monitoring in water resources and remote areas.

Volumetric monitoring of airborne particulate matter concentration using smartphone-based digital holographic microscopy and deep learning

Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome to handle for accurate and high throughput measurements. In addition, commercial particle counters have technical limitations in high-concentration measurement, and data fluctuations are induced during air sampling. In this study, a novel smartphone-based technique for monitoring airborne PM concentrations was developed using smartphone-based digital holographic microscopy (S-DHM) and deep learning network called Holo-SpeckleNet. Holographic speckle images of various PM concentrations were recorded by the S-DHM system. The recorded speckle images and the corresponding ground truth PM concentrations were used to train deep learning algorithms consisting of a deep autoencoder and regression layers. The performance of the proposed smartphone-based PM monitoring technique was validated through hyperparameter optimization. The developed S-DHM integrated with Holo-SpeckleNet can be smartly and effectively utilized for portable PM monitoring and safety alarm provision under perilous environmental conditions.

Accurate and fast modeling of scattering from random arrays of nanoparticles using the discrete dipole approximation and angular spectrum method

Lens-free microscopes can utilize holographic reconstruction techniques to recover the image of an object from the digitally recorded superposition of an unperturbed plane wave and a wave scattered by the object. Image reconstruction most commonly relies on the scalar angular spectrum method (ASM). While fast, the scalar ASM can be inaccurate for nanoscale objects, either because of the scalar approximation, or more generally, because it only models field propagation and not light-matter interaction, including inter-particle coupling. Here we evaluate the accuracy of the scalar ASM when combined with three different light-matter interaction models for computing the far-field light scattered by random arrays of gold and polystyrene nanoparticles. Among the three models-a dipole-matched transmission model, an optical path length model, and a binary amplitude model-we find that which model is most accurate depends on the nanoparticle material and packing density. For polystyrene particles at any packing density, there is always at least one model with error below 20%, while for gold nanoparticles with 40% or 50% surface coverage, there are no models that can provide errors better than 30%. The ASM error is determined in comparison to a discrete dipole approximation model, which is more computationally efficient than other full-wave modeling techniques. The knowledge of when and how the ASM fails can serve as a first step toward improved resolution in lens-free reconstruction and can also be applied to other random nanoparticle array applications such as lens-based super-resolution imaging, sub-diffraction beam focusing, and biomolecular sensing.

Three-dimensional volumetric monitoring of settling particulate matters on a leaf using digital in-line holographic microscopy

Plants are considered as a possible modality to reduce particulate matter (PM) particles from ambient air in an ecofriendly manner. A new precise monitoring technique that can explore interactions between individual PM particles and a leaf surface is necessary to understand the underlying mechanisms of PM removal of plant leaves. In this study, a digital in-line holographic microscopy (DIHM) was employed to experimentally investigate the settling motions of PM particles over the leaf surface. The in-plane positions and sizes of opaque PMs with irregular shapes were obtained from the projection images of numerically reconstructed holographic images. The depth positions of PMs were determined by using proper selection of an autofocusing criterion with automatic segmentation method. The edge of a hairy Perilla frutescens leaf was detected by adopting several digital imaging processing techniques. The DIHM technique was applied in this study to accurately detect 3D settling trajectories of PMs with velocity information of PMs in the midair and near leaf surface, simultaneously.

Lensfree Diffraction Reconstruction Approach Enables Early Detection of Cancer In Vitro Based on Molecular Diagnosis

Before there are any megascopic cancer clinical symptoms, molecular diagnosis is the main method for detecting cancer-associated gene and tumor marker. The existing detection facilities are all expensive, complicated to operate, and time-consuming, thereby making them difficult to popularize and benefit humans. In this study, we proposed a high-throughput and cost-effective approach, which enables accurate detection of extremely rare cancer cells based on molecular diagnosis of target tumor marker and a lensfree diffraction imaging platform. This approach achieves high-speed and high-quality reconstruction of huge images, which well solves the problem that precise recognition is almost impossible utilizing raw image because of significant pattern magnification and serious overlaps. Furthermore, the cells which are labeled with immune microbeads can be screened using the determined covered pixel sets, which are extracted in different focus reconstruction planes. The recognition strategy is implemented based on set intersection. With this method, the target cancer cells can be rapidly and accurately screened in a large number of benign cell samples. Besides, the detection equipment is cost-effective and easy to operate and popularize. It is expected to be widely used as a diagnostic tool for early detection of cancer.

Metagenomic water quality monitoring with a portable laboratory

We describe the technical feasibility of metagenomic water quality analysis using only portable equipment, for example mini-vacuum pumps and filtration units, mini-centrifuges, mini-PCR machines and the memory-stick sized MinION of Oxford Nanopore Technologies, for the library preparation and sequencing of 16S rRNA gene amplicons. Using this portable toolbox on site, we successfully characterized the microbiome of water samples collected from Birtley Sewage Treatment Plant, UK, and its environs. We also demonstrated the applicability of the portable metagenomics toolbox in a low-income country by surveying water samples from the Akaki River around Addis Ababa, Ethiopia. The 16S rRNA gene sequencing workflow, including DNA extraction, PCR amplification, sequencing library preparation, and sequencing was accomplished within one working day. The metagenomic data became available within 24-72 h, depending on internet speed. Metagenomic analysis clearly distinguished the microbiome of pristine samples from sewage influenced water samples. Metagenomic analysis identified the potential role of two bacterial genera not conventionally monitored, Arcobacter and Aeromonas, as predominant faecal pollution indicators/waterborne hazards. Subsequent quantitative PCR analysis validated the high Arcobacter butzleri abundances observed in the urban influenced Akaki River water samples by portable next generation sequencing with the MinION device. Overall, our field deployable metagenomics toolbox advances the capability of scientists to comprehensively monitor microbiomes anywhere in the world, including in the water, food and drinks industries, the health services, agriculture and beyond.

Deep learning-based hologram generation using a white light source

Digital holographic microscopy enables the recording of sample holograms which contain 3D volumetric information. However, additional optical elements, such as partially or fully coherent light source and a pinhole, are required to induce diffraction and interference. Here, we present a deep neural network based on generative adversarial network (GAN) to perform image transformation from a defocused bright-field (BF) image acquired from a general white light source to a holographic image. Training image pairs of 11,050 for image conversion were gathered by using a hybrid BF and hologram imaging technique. The performance of the trained network was evaluated by comparing generated and ground truth holograms of microspheres and erythrocytes distributed in 3D. Holograms generated from BF images through the trained GAN showed enhanced image contrast with 3-5 times increased signal-to-noise ratio compared to ground truth holograms and provided 3D positional information and light scattering patterns of the samples. The developed GAN-based method is a promising mean for dynamic analysis of microscale objects with providing detailed 3D positional information and monitoring biological samples precisely even though conventional BF microscopic setting is utilized.

Polarization holographic microscope slide for birefringence imaging of anisotropic samples in microfluidics

Birefringence is an important optical property of anisotropic materials arising from anisotropies of tissue microstructures. Birefringence parameters have been found to be important to understand optical anisotropic architecture of many materials and polarization imaging has been applied in many researches in the field of biology and medicine. Here, we propose a scheme to miniaturize a double-channel polarization holographic interferometer optics to create a polarization holographic microscope slide (P-HMS) suitable for integrating with microfluidic lab-on-a-chip (LoC) systems. Based on the P-HMS combined with a simple reconstruction algorithm described in the paper, we can not only simultaneously realize holographic imaging of two orthogonal polarization components of dynamic samples in a microfluidic channel but also quantitative measurement of 2D birefringence information, both including the birefringence phase retardation and optic-axis orientation. This chip interferometer allows for off-axis double-channel polarization digital holographic recording using only a single illumination beam without need of any beam splitter or mirror. Its quasi-common path configuration and self-aligned design also make it tolerant to vibrations and misalignment. This work about the P-HMS could play a positive role in promoting the application of birefringence imaging in microfluidic LoC technology.

3D-printable portable open-source platform for low-cost lens-less holographic cellular imaging

Digital holographic microscopy is an emerging, potentially low-cost alternative to conventional light microscopy for micro-object imaging on earth, underwater and in space. Immediate access to micron-scale objects however requires a well-balanced system design and sophisticated reconstruction algorithms, that are commercially available, however not accessible cost-efficiently. Here, we present an open-source implementation of a lens-less digital inline holographic microscope platform, based on off-the-shelf optical, electronic and mechanical components, costing less than $190. It employs a Blu-Ray semiconductor-laser-pickup or a light-emitting-diode, a pinhole, a 3D-printed housing consisting of 3 parts and a single-board portable computer and camera with an open-source implementation of the Fresnel-Kirchhoff routine. We demonstrate 1.55 μm spatial resolution by laser-pickup and 3.91 μm by the light-emitting-diode source. The housing and mechanical components are 3D printed. Both printer and reconstruction software source codes are open. The light-weight microscope allows to image label-free micro-spheres of 6.5 μm diameter, human red-blood-cells of about 8 μm diameter as well as fast-growing plant Nicotiana-tabacum-BY-2 suspension cells with 50 μm sizes. The imaging capability is validated by imaging-contrast quantification involving a standardized test target. The presented 3D-printable portable open-source platform represents a fully-open design, low-cost modular and versatile imaging-solution for use in high- and low-resource areas of the world.

Super-Resolution Lensless Imaging of Cells Using Brownian Motion

The lensless imaging technique, which integrates a microscope into a complementary metal oxide semiconductor (CMOS) digital image sensor, has become increasingly important for the miniaturization of biological microscope and cell detection equipment. However, limited by the pixel size of the CMOS image sensor (CIS), the resolution of a cell image without optical amplification is low. This is also a key defect with the lensless imaging technique, which has been studied by a many scholars. In this manuscript, we propose a method to improve the resolution of the cell images using the Brownian motion of living cells in liquid. A two-step algorithm of motion estimation for image registration is proposed. Then, the raw holographic images are reconstructed using normalized convolution super-resolution algorithm. The result shows that the effect of the collected cell image under the lensless imaging system is close to the effect of a 10× objective lens.

Learning-based automatic sensing and size classification of microparticles using smartphone holographic microscopy

A microparticle classifier is established by synergetic integration of smartphone-based digital in-line holographic microscopy and supervised machine learning.

Deep transfer learning-based hologram classification for molecular diagnostics

Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images from the complex diffraction patterns produced by LDIH. This limits LDIH utility for point-of-care applications, particularly in resource limited settings. We describe a deep transfer learning (DTL) based approach to process LDIH images in the context of cellular analyses. Specifically, we captured holograms of cells labeled with molecular-specific microbeads and trained neural networks to classify these holograms without reconstruction. Using raw holograms as input, the trained networks were able to classify individual cells according to the number of cell-bound microbeads. The DTL-based approach including a VGG19 pretrained network showed robust performance with experimental data. Combined with the developed DTL approach, LDIH could be realized as a low-cost, portable tool for point-of-care diagnostics.

Imaging & identification of malaria parasites using cellphone microscope with a ball lens

We have optimized the design and imaging procedures, to clearly resolve the malaria parasite in Giemsa-stained thin blood smears, using simple low-cost cellphone-based microscopy with oil immersion. The microscope uses a glass ball as the objective and the phone camera as the tube lens. Our optimization includes the optimal choice of the ball lens diameter, the size and the position of the aperture diaphragm, and proper application of immersion, to achieve diagnostic capacity in a wide field of view. The resulting system is potentially applicable to low-cost in-the-field optical diagnostics of malaria as it clearly resolves micron-sized features and allows for analysis of parasite morphology in the field of 50 × 50 μm, and parasite detection in the field of at least 150 × 150 μm.

Microfluidic Based Optical Microscopes on Chip

Last decade's advancements in optofluidics allowed obtaining an ever increasing integration of different functionalities in lab on chip devices to culture, analyze, and manipulate single cells and entire biological specimens. Despite the importance of optical imaging for biological sample monitoring in microfluidics, imaging is traditionally achieved by placing microfluidics channels in standard bench-top optical microscopes. Recently, the development of either integrated optical elements or lensless imaging methods allowed optical imaging techniques to be implemented in lab on chip systems, thus increasing their automation, compactness, and portability. In this review, we discuss known solutions to implement microscopes on chip that exploit different optical methods such as bright-field, phase contrast, holographic, and fluorescence microscopy.

Optimized sensing of sparse and small targets using lens-free holographic microscopy

Lens-free holographic microscopy offers sub-micron resolution over an ultra-large field-of-view >20 mm², making it suitable for bio-sensing applications that require the detection of small targets at low concentrations. Various pixel super-resolution techniques have been shown to enhance resolution and boost signal-to-noise ratio (SNR) by combining multiple partially-redundant low-resolution frames. However, it has been unclear which technique performs best for small-target sensing. Here, we quantitatively compare SNR and resolution in experiments using no regularization, cardinal-neighbor regularization, and a novel implementation of sparsity-promoting regularization that uses analytically-calculated gradients from Bayer-pattern image sensors. We find that sparsity-promoting regularization enhances the SNR by ~8 dB compared to the other methods when imaging micron-scale beads with surface coverages up to ~4%.

Space-variant video compression and processing in digital holographic microscopy sensor networks with application to potable water monitoring

Water-related diseases affect societies in all parts of the world. Online sensors are considered a solution to the problems associated with laboratory testing in potable water. One of the most active research areas of such online sensors has been within optics. Digital holographic microscopy (DHM) has the potential to rival state-of-the-art techniques such as advanced turbidity measurement. However, its use as an online sensor is limited by the large data requirements typical for digital holographic video. In this paper, we provide a solution that permits DHM to be applied to a whole class of online remote sensor networks, of which potable water analysis is one example. The designed sensors incorporate a novel space-variant quantization algorithm to preprocess each frame of a video sequence before transmission over a network. The system satisfies the generally accepted requirements of an online system: automated, near real-time, and operating in a real environment. To verify the effectiveness of the design, we implemented and evaluated it in an active potable water facility.

High-Precision Lens-Less Flow Cytometer on a Chip

We present a flow cytometer on a microfluidic chip that integrates an inline lens-free holographic microscope. High-speed cell analysis necessitates that cells flow through the microfluidic channel at a high velocity, but the image sensor of the in-line holographic microscope needs a long exposure time. Therefore, to solve this problem, this paper proposes an S-type micro-channel and a pulse injection method. To increase the speed and accuracy of the hologram reconstruction, we improve the iterative initial constraint method and propose a background removal method. The focus images and cell concentrations can be accurately calculated by the developed method. Using whole blood cells to test the cell counting precision, we find that the cell counting error of the proposed method is less than 2%. This result shows that the on-chip flow cytometer has high precision. Due to its low price and small size, this flow cytometer is suitable for environments far away from laboratories, such as underdeveloped areas and outdoors, and it is especially suitable for point-of-care testing (POCT).

Microfluidic multi-angle laser scattering system for rapid and label-free detection of waterborne parasites

A microfluidic laser scattering system for rapid and label-free detection of single waterborne parasites in microfluidic flows was designed, fabricated and demonstrated. The key novelty of the system lies in the integration of functional modules involving pre-concentration, on-chip laser scattering detection, and pattern recognition. The silicon-based pre-concentration chip can concentrate 10 ml reagent water sample spiked with protozoa (oo)cysts into a volume of 200 μl in ~30 minutes. The concentrated sample is further channeled into the on-chip laser scattering detection module at a flow rate of 10 μl/min, which can collect the multi-angle scattering pattern of single flowing microparticles. The Zernike moment features of scattering patterns are extracted using principal component analysis, and classification of scattering patterns are performed using the linear discriminator analysis algorithm. As a result, Cryptosporidium parvum oocysts and Giardia lamblia cysts spiked in ~10 ml reagent water can be enumerated and identified within an hour without labeling, with a mean recovery efficiency of ~73% and average accuracies of 96%, 97%, 97% and 98% at concentrations of 10, 50, 100, 300 (oo)cysts per 10 ml water, respectively. We believe that this compact microfluidic laser scattering system has potential for rapid and label-free water quality monitoring in field and resource-limited environments.

Effect of counting chamber depth on the accuracy of lensless microscopy for the assessment of boar sperm motility

Sperm motility is one of the most significant parameters in the prediction of male fertility. Until now, both motility analysis using an optical microscope and computer-aided sperm analysis (CASA-Mot) entailed the use of counting chambers with a depth to 20 µm. Chamber depth significantly affects the intrinsic sperm movement, leading to an artificial motility pattern. For the first time, laser microscopy offers the possibility of avoiding this interference with sperm movement. The aims of the present study were to determine the different motility patterns observed in chambers with depths of 10, 20 and 100 µm using a new holographic approach and to compare the results obtained in the 20-µm chamber with those of the laser and optical CASA-Mot systems. The ISAS®3D-Track results showed that values for curvilinear velocity (VCL), straight line velocity, wobble and beat cross frequency were higher for the 100-µm chambers than for the 10- and 20-µm chambers. Only VCL showed a positive correlation between chambers. In addition, Bayesian analysis confirmed that the kinematic parameters observed with the 100-µm chamber were significantly different to those obtained using chambers with depths of 10 and 20 µm. When an optical analyser CASA-Mot system was used, all kinematic parameters, except VCL, were higher with ISAS®3D-Track, but were not relevant after Bayesian analysis. Finally, almost three different three-dimensional motility patterns were recognised. In conclusion, the use of the ISAS®3D-Track allows for the analysis of the natural three-dimensional pattern of sperm movement.

Adaptive pixel-super-resolved lensfree in-line digital holography for wide-field on-chip microscopy

High-resolution wide field-of-view (FOV) microscopic imaging plays an essential role in various fields of biomedicine, engineering, and physical sciences. As an alternative to conventional lens-based scanning techniques, lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and FOV of conventional microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). Here, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method which can solve, or at least partially alleviate these limitations. Our approach addresses the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target (~29.85 mm²) and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist–Shannon sampling resolution limit imposed by the sensor pixel-size (1.67µm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

Endowing a plain fluidic chip with micro-optics: a holographic microscope slide

Lab-on-a-Chip (LoC) devices are extremely promising in that they enable diagnostic functions at the point-of-care. Within this scope, an important goal is to design imaging schemes that can be used out of the laboratory. In this paper, we introduce and test a pocket holographic slide that allows digital holography microscopy to be performed without an interferometer setup. Instead, a commercial off-the-shelf plastic chip is engineered and functionalized with this aim. The microfluidic chip is endowed with micro-optics, that is, a diffraction grating and polymeric lenses, to build an interferometer directly on the chip, avoiding the need for a reference arm and external bulky optical components. Thanks to the single-beam scheme, the system is completely integrated and robust against vibrations, sharing the useful features of any common path interferometer. Hence, it becomes possible to bring holographic functionalities out of the lab, moving complexity from the external optical apparatus to the chip itself. Label-free imaging and quantitative phase contrast mapping of live samples are demonstrated, along with flexible refocusing capabilities. Thus, a liquid volume can be analyzed in one single shot with no need for mechanical scanning systems.

Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring

Optical compound microscope has been a major tool in biomedical imaging for centuries. Its performance relies on relatively complicated, bulky and expensive lenses and alignment mechanics. In contrast, the lensless microscope digitally reconstructs microscopic images of specimens without using any lenses, as a result of which it can be made much smaller, lighter and lower-cost. Furthermore, the limited space-bandwidth product of objective lenses in a conventional microscope can be significantly surpassed by a lensless microscope. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable and cost-effective devices to potentially address various point-of-care, global-health and telemedicine related challenges. In this review, we discuss the operation principles and the methods behind lensless digital holographic on-chip microscopy. We also go over various applications that are enabled by cost-effective and compact implementations of lensless microscopy, including some recent work on air quality monitoring, which utilized machine learning for high-throughput and accurate quantification of particulate matter in air. Finally, we conclude with a brief future outlook of this computational imaging technology.

Compact, cost-effective and field-portable microscope prototype based on MISHELF microscopy

We report on a reduced cost, portable and compact prototype design of lensless holographic microscope with an illumination/detection scheme based on wavelength multiplexing, working with single hologram acquisition and using a fast convergence algorithm for image processing. All together, MISHELF (initials coming from Multi-Illumination Single-Holographic-Exposure Lensless Fresnel) microscopy allows the recording of three Fresnel domain diffraction patterns in a single camera snap-shot incoming from illuminating the sample with three coherent lights at once. Previous implementations have proposed an illumination/detection procedure based on a tuned (illumination wavelengths centered at the maximum sensitivity of the camera detection channels) configuration but here we report on a detuned (non-centered ones) scheme resulting in prototype miniaturization and cost reduction. Thus, MISHELF microscopy in combination with a novel and fast iterative algorithm allows high-resolution (μm range) phase-retrieved (twin image elimination) quantitative phase imaging of dynamic events (video rate recording speed). The performance of this microscope prototype is validated through experiments using both amplitude (USAF resolution test) and complex (live swine sperm cells and flowing microbeads) samples. The proposed method becomes in an alternative instrument improving some capabilities of existing lensless microscopes.

Label-free fingerprinting of tumor cells in bulk flow using inline digital holographic microscopy

Large-scale and label-free phenotyping of cells holds great promise in medicine, especially in cancer diagnostics and prognosis. Here, we introduce inline digital holography microscopy for volumetric imaging of cells in bulk flow and fingerprinting of flowing tumor cells based on two metrics, in-focus scattered intensity and cell diameter. Using planar distribution of immobilized particles, we identify the optimal recording distance and microscope objective magnification that minimizes the error in measurement of particle position, size and scattered intensity. Using the optimized conditions and the two metrics, we demonstrate the capacity to enumerate and fingerprint more than 100,000 cells. Finally, we highlight the power of our label-free and high throughput technology by characterizing breast tumor cell lines with different metastatic potentials and distinguishing drug resistant ovarian cancer cells from their parental cell line.

Laser Light-field Fusion for Wide-field Lensfree On-chip Phase Contrast Microscopy of Nanoparticles

Wide-field lensfree on-chip microscopy, which leverages holography principles to capture interferometric light-field encodings without lenses, is an emerging imaging modality with widespread interest given the large field-of-view compared to lens-based techniques. In this study, we introduce the idea of laser light-field fusion for lensfree on-chip phase contrast microscopy for detecting nanoparticles, where interferometric laser light-field encodings acquired using a lensfree, on-chip setup with laser pulsations at different wavelengths are fused to produce marker-free phase contrast images of particles at the nanometer scale. As a proof of concept, we demonstrate, for the first time, a wide-field lensfree on-chip instrument successfully detecting 300 nm particles across a large field-of-view of ~30 mm² without any specialized or intricate sample preparation, or the use of synthetic aperture- or shift-based techniques.

Wide Field-of-View Fluorescence Imaging with Optical-Quality Curved Microfluidic Chamber for Absolute Cell Counting

Field curvature and other aberrations are encountered inevitably when designing a compact fluorescence imaging system with a simple lens. Although multiple lens elements can be used to correct most such aberrations, doing so increases system cost and complexity. Herein, we propose a wide field-of-view (FOV) fluorescence imaging method with an unconventional optical-quality curved sample chamber that corrects the field curvature caused by a simple lens. Our optics simulations and proof-of-concept experiments demonstrate that a curved substrate with lens-dependent curvature can reduce greatly the distortion in an image taken with a conventional planar detector. Following the validation study, we designed a curved sample chamber that can contain a known amount of sample volume and fabricated it at reasonable cost using plastic injection molding. At a magnification factor of approximately 0.6, the curved chamber provides a clear view of approximately 119 mm², which is approximately two times larger than the aberration-free area of a planar chamber. Remarkably, a fluorescence image of microbeads in the curved chamber exhibits almost uniform intensity over the entire field even with a simple lens imaging system, whereas the distorted boundary region has much lower brightness than the central area in the planar chamber. The absolute count of white blood cells stained with a fluorescence dye was in good agreement with that obtained by a commercially available conventional microscopy system. Hence, a wide FOV imaging system with the proposed curved sample chamber would enable us to acquire an undistorted image of a large sample volume without requiring a time-consuming scanning process in point-of-care diagnostic applications.

Unconventional methods of imaging: computational microscopy and compact implementations

In the past two decades or so, there has been a renaissance of optical microscopy research and development. Much work has been done in an effort to improve the resolution and sensitivity of microscopes, while at the same time to introduce new imaging modalities, and make existing imaging systems more efficient and more accessible. In this review, we look at two particular aspects of this renaissance: computational imaging techniques and compact imaging platforms. In many cases, these aspects go hand-in-hand because the use of computational techniques can simplify the demands placed on optical hardware in obtaining a desired imaging performance. In the first main section, we cover lens-based computational imaging, in particular, light-field microscopy, structured illumination, synthetic aperture, Fourier ptychography, and compressive imaging. In the second main section, we review lensfree holographic on-chip imaging, including how images are reconstructed, phase recovery techniques, and integration with smart substrates for more advanced imaging tasks. In the third main section we describe how these and other microscopy modalities have been implemented in compact and field-portable devices, often based around smartphones. Finally, we conclude with some comments about opportunities and demand for better results, and where we believe the field is heading.

Wide-field imaging of birefringent synovial fluid crystals using lens-free polarized microscopy for gout diagnosis

Gout is a form of crystal arthropathy where monosodium urate (MSU) crystals deposit and elicit inflammation in a joint. Diagnosis of gout relies on identification of MSU crystals under a compensated polarized light microscope (CPLM) in synovial fluid aspirated from the patient's joint. The detection of MSU crystals by optical microscopy is enhanced by their birefringent properties. However, CPLM partially suffers from the high-cost and bulkiness of conventional lens-based microscopy, and its relatively small field-of-view (FOV) limits the efficiency and accuracy of gout diagnosis. Here we present a lens-free polarized microscope which adopts a novel differential and angle-mismatched polarizing optical design achieving wide-field and high-resolution holographic imaging of birefringent objects with a color contrast similar to that of a standard CPLM. The performance of this computational polarization microscope is validated by imaging MSU crystals made from a gout patient's tophus and steroid crystals used as negative control. This lens-free polarized microscope, with its wide FOV (>20 mm(2)), cost-effectiveness and field-portability, can significantly improve the efficiency and accuracy of gout diagnosis, reduce costs, and can be deployed even at the point-of-care and in resource-limited clinical settings.

Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle

Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of "smartphones" is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and "micro swimmers" of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the "vinegar eel." The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as "diagnostic fingerprints."

Color calibration and fusion of lens-free and mobile-phone microscopy images for high-resolution and accurate color reproduction

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed “digital color fusion microscopy” (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available.

Wide-field computational imaging of pathology slides using lens-free on-chip microscopy

Optical examination of microscale features in pathology slides is one of the gold standards to diagnose disease. However, the use of conventional light microscopes is partially limited owing to their relatively high cost, bulkiness of lens-based optics, small field of view (FOV), and requirements for lateral scanning and three-dimensional (3D) focus adjustment. We illustrate the performance of a computational lens-free, holographic on-chip microscope that uses the transport-of-intensity equation, multi-height iterative phase retrieval, and rotational field transformations to perform wide-FOV imaging of pathology samples with comparable image quality to a traditional transmission lens-based microscope. The holographically reconstructed image can be digitally focused at any depth within the object FOV (after image capture) without the need for mechanical focus adjustment and is also digitally corrected for artifacts arising from uncontrolled tilting and height variations between the sample and sensor planes. Using this lens-free on-chip microscope, we successfully imaged invasive carcinoma cells within human breast sections, Papanicolaou smears revealing a high-grade squamous intraepithelial lesion, and sickle cell anemia blood smears over a FOV of 20.5 mm(2). The resulting wide-field lens-free images had sufficient image resolution and contrast for clinical evaluation, as demonstrated by a pathologist's blinded diagnosis of breast cancer tissue samples, achieving an overall accuracy of ~99%. By providing high-resolution images of large-area pathology samples with 3D digital focus adjustment, lens-free on-chip microscopy can be useful in resource-limited and point-of-care settings.

Review of Telemicrobiology

CONTEXT

Microbiology laboratories are continually pursuing means to improve quality, rapidity, and efficiency of specimen analysis in the face of limited resources. One means by which to achieve these improvements is through the remote analysis of digital images. Telemicrobiology enables the remote interpretation of images of microbiology specimens. To date, the practice of clinical telemicrobiology has not been thoroughly reviewed.

OBJECTIVE

To identify the various methods that can be employed for telemicrobiology, including emerging technologies that may provide value to the clinical laboratory.

DATA SOURCES

Peer-reviewed literature, conference proceedings, meeting presentations, and expert opinions pertaining to telemicrobiology have been evaluated.

CONCLUSIONS

A number of modalities have been employed for telemicroscopy, including static capture techniques, whole slide imaging, video telemicroscopy, mobile devices, and hybrid systems. Telemicrobiology has been successfully implemented for several applications, including routine primary diagnosis, expert teleconsultation, and proficiency testing. Emerging areas of telemicrobiology include digital plate reading of bacterial cultures, mobile health applications, and computer-augmented analysis of digital images. To date, static image capture techniques have been the most widely used modality for telemicrobiology, despite newer technologies being available that may produce better quality interpretations. Telemicrobiology adds value, quality, and efficiency to the clinical microbiology laboratory, and increased adoption of telemicrobiology is anticipated.

Lens-free spectral light-field fusion microscopy for contrast- and resolution-enhanced imaging of biological specimens

A lens-free spectral light-field fusion microscopy (LSLFM) system is presented for enabling contrast- and resolution-enhanced imaging of biological specimens. LSLFM consists of a pulsed multispectral lens-free microscope for capturing interferometric light-field encodings at various wavelengths, and Bayesian-based fusion to reconstruct a fused object light-field from the encodings. By fusing unique object detail information captured at different wavelengths, LSLFM can achieve improved resolution, contrast, and signal-to-noise ratio (SNR) over a single-channel lens-free microscopy system. A five-channel LSLFM system was developed and quantitatively evaluated to validate the design. Experimental results demonstrated that the LSLFM system provided SNR improvements of 6-12 dB, as well as a six-fold improvement in the dispersion index (DI), over that achieved using a single-channel, resolution-enhancing lens-free deconvolution microscopy system or its multi-wavelength counterpart. Furthermore, the LSLFM system achieved an increase in numerical aperture (NA) of ∼16% over a single-channel resolution-enhancing lens-free deconvolution microscopy system at the highest resolution wavelength used in the study. Samples of Staurastrum paradoxum, a waterborne algae, and human corneal epithelial cells were imaged using the system to illustrate its potential for enhanced imaging of biological specimens.

Bayesian-based aberration correction and numerical diffraction for improved lensfree on-chip microscopy of biological specimens

Lensfree on-chip microscopy is an emerging imaging technique that can be used to visualize and study biological specimens without the need for imaging lens systems. Important issues that can limit the performance of lensfree on-chip microscopy include interferometric aberrations, acquisition noise, and image reconstruction artifacts. In this study, we introduce a Bayesian-based method for performing aberration correction and numerical diffraction that accounts for all three of these issues to improve the effective numerical aperture (NA) and signal-to-noise ratio (SNR) of the reconstructed microscopic image. The proposed method was experimentally validated using the USAF resolution target as well as real waterborne Anabaena flos-aquae samples, demonstrating improvements in NA by ∼25% over the standard method, and improvements in SNR of 2.8 and 8.2 dB in the reconstructed image when compared to the reconstructed images produced using the standard method and a maximum likelihood estimation method, respectively.

Quantification of plant chlorophyll content using Google Glass

Measuring plant chlorophyll concentration is a well-known and commonly used method in agriculture and environmental applications for monitoring plant health, which also correlates with many other plant parameters including, e.g., carotenoids, nitrogen, maximum green fluorescence, etc. Direct chlorophyll measurement using chemical extraction is destructive, complex and time-consuming, which has led to the development of mobile optical readers, providing non-destructive but at the same time relatively expensive tools for evaluation of plant chlorophyll levels. Here we demonstrate accurate measurement of chlorophyll concentration in plant leaves using Google Glass and a custom-developed software application together with a cost-effective leaf holder and multi-spectral illuminator device. Two images, taken using Google Glass, of a leaf placed in our portable illuminator device under red and white (i.e., broadband) light-emitting-diode (LED) illumination are uploaded to our servers for remote digital processing and chlorophyll quantification, with results returned to the user in less than 10 seconds. Intensity measurements extracted from the uploaded images are mapped against gold-standard colorimetric measurements made through a commercially available reader to generate calibration curves for plant leaf chlorophyll concentration. Using five plant species to calibrate our system, we demonstrate that our approach can accurately and rapidly estimate chlorophyll concentration of fifteen different plant species under both indoor and outdoor lighting conditions. This Google Glass based chlorophyll measurement platform can display the results in spatiotemporal and tabular forms and would be highly useful for monitoring of plant health in environmental and agriculture related applications, including e.g., urban plant monitoring, indirect measurements of the effects of climate change, and as an early indicator for water, soil, and air quality degradation.

Chagas parasite detection in blood images using AdaBoost

The Chagas disease is a potentially life-threatening illness caused by the protozoan parasite, Trypanosoma cruzi. Visual detection of such parasite through microscopic inspection is a tedious and time-consuming task. In this paper, we provide an AdaBoost learning solution to the task of Chagas parasite detection in blood images. We give details of the algorithm and our experimental setup. With this method, we get 100% and 93.25% of sensitivity and specificity, respectively. A ROC comparison with the method most commonly used for the detection of malaria parasites based on support vector machines (SVM) is also provided. Our experimental work shows mainly two things: (1) Chagas parasites can be detected automatically using machine learning methods with high accuracy and (2) AdaBoost + SVM provides better overall detection performance than AdaBoost or SVMs alone. Such results are the best ones known so far for the problem of automatic detection of Chagas parasites through the use of machine learning, computer vision, and image processing methods.

Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning

Rapid and sensitive detection of waterborne pathogens in drinkable and recreational water sources is crucial for treating and preventing the spread of water related diseases, especially in resource-limited settings. Here we present a field-portable and cost-effective platform for detection and quantification of Giardia lamblia cysts, one of the most common waterborne parasites, which has a thick cell wall that makes it resistant to most water disinfection techniques including chlorination. The platform consists of a smartphone coupled with an opto-mechanical attachment weighing ~205 g, which utilizes a hand-held fluorescence microscope design aligned with the camera unit of the smartphone to image custom-designed disposable water sample cassettes. Each sample cassette is composed of absorbent pads and mechanical filter membranes; a membrane with 8 μm pore size is used as a porous spacing layer to prevent the backflow of particles to the upper membrane, while the top membrane with 5 μm pore size is used to capture the individual Giardia cysts that are fluorescently labeled. A fluorescence image of the filter surface (field-of-view: ~0.8 cm(2)) is captured and wirelessly transmitted via the mobile-phone to our servers for rapid processing using a machine learning algorithm that is trained on statistical features of Giardia cysts to automatically detect and count the cysts captured on the membrane. The results are then transmitted back to the mobile-phone in less than 2 minutes and are displayed through a smart application running on the phone. This mobile platform, along with our custom-developed sample preparation protocol, enables analysis of large volumes of water (e.g., 10-20 mL) for automated detection and enumeration of Giardia cysts in ~1 hour, including all the steps of sample preparation and analysis. We evaluated the performance of this approach using flow-cytometer-enumerated Giardia-contaminated water samples, demonstrating an average cyst capture efficiency of ~79% on our filter membrane along with a machine learning based cyst counting sensitivity of ~84%, yielding a limit-of-detection of ~12 cysts per 10 mL. Providing rapid detection and quantification of microorganisms, this field-portable imaging and sensing platform running on a mobile-phone could be useful for water quality monitoring in field and resource-limited settings.

Capture and separation of biomolecules using magnetic beads in a simple microfluidic channel without an external flow device

The use of microfluidic devices and magnetic beads for applications in biotechnology has been extensively explored over the past decade. Many elaborate microfluidic chips have been used in efficient systems for biological assays. However most fail to achieve the ideal point of care (POC) status, as they require larger conventional external devices in conjunction with the microchip. This paper presents a simple technique to capture and separate biomolecules using magnetic bead movement on a microchip without the use of an external flow device. This microchip consisted of two well reservoirs (W1 and W2) connected via a tapered microchannel. Beads were dragged through the microchannel between the two wells at an equivalent speed to a permanent magnet that moved alongside the microchip. More than 95% of beads were transferred from W1 to W2 within 2 min at an average velocity of 0.7 mm s(-1). Enzymatic reactions were employed to test our microchip. Specifically, three assays were performed using the streptavidin coated magnetic beads as a solid support to capture and transfer biomolecules: (1) non-specific adsorption of the substrate, 6-8-difluoro-4-methylumbelliferyl phosphate (DiFMUP), (2) capture of the enzyme, biotinylated alkaline phosphatase (AP), and (3) separation of AP from DiFMUP. Our non-specific adsorption assay indicated that the microchip was capable of transferring the beads with less than 0.002% carryover of DiFMUP. Our capture assay indicated efficient capture and transfer of AP with beads to W2 containing DiFMUP, where the transferred AP converted 100% of DiFMUP to DiFMU within 15 minutes. Our separation assay showed effective separation of AP from DiFMUP and elucidated the binding capacity of the beads for AP. The leftover unbound AP in W1 converted 100% of DiFMUP within 10 minutes and samples with less than the full bead capacity of AP (i.e. all AP was transferred) did not convert any of the DiFMUP. The immobilization of AP on the bead surface resulted in 32% reduced enzymatic speed compared to that of free AP in solution, as a result of altered protein conformation and/or steric hindrance of the catalytic site. Overall, this microfluidic platform was established as a simple, efficient and effective approach for separating biomolecules without any flow apparatus.

A smartphone-based chip-scale microscope using ambient illumination

Portable chip-scale microscopy devices can potentially address various imaging needs in mobile healthcare and environmental monitoring. Here, we demonstrate the adaptation of a smartphone's camera to function as a compact lensless microscope. Unlike other chip-scale microscopy schemes, this method uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is based on the shadow imaging technique where the sample is placed on the surface of the image sensor, which captures direct shadow images under illumination. To improve the image resolution beyond the pixel size, we perform pixel super-resolution reconstruction with multiple images at different angles of illumination, which are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. The lensless imaging scheme allows for sub-micron resolution imaging over an ultra-wide field-of-view (FOV). Image acquisition and reconstruction are performed on the device using a custom-built Android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system.

High-throughput monitoring of major cell functions by means of lensfree video microscopy

Quantification of basic cell functions is a preliminary step to understand complex cellular mechanisms, for e.g., to test compatibility of biomaterials, to assess the effectiveness of drugs and siRNAs, and to control cell behavior. However, commonly used quantification methods are label-dependent, and end-point assays. As an alternative, using our lensfree video microscopy platform to perform high-throughput real-time monitoring of cell culture, we introduce specifically devised metrics that are capable of non-invasive quantification of cell functions such as cell-substrate adhesion, cell spreading, cell division, cell division orientation and cell death. Unlike existing methods, our platform and associated metrics embrace entire population of thousands of cells whilst monitoring the fate of every single cell within the population. This results in a high content description of cell functions that typically contains 25,000 – 900,000 measurements per experiment depending on cell density and period of observation. As proof of concept, we monitored cell-substrate adhesion and spreading kinetics of human Mesenchymal Stem Cells (hMSCs) and primary human fibroblasts, we determined the cell division orientation of hMSCs, and we observed the effect of transfection of siCellDeath (siRNA known to induce cell death) on hMSCs and human Osteo Sarcoma (U2OS) Cells.