Mobile phones democratize and cultivate next-generation imaging, diagnostics and measurement tools

Highly Sensitive and Selective Fluorescence and Smartphone-Based Sensor for Detection of Rutin Using Boron Nitrogen Co-doped Graphene Quantum Dots

This research explores the fluorescence properties and photostability of boron nitrogen co-doped graphene quantum dots (BN-GQDs), evaluating their effectiveness as sensors for rutin (RU). BN-GQDs are biocompatible and exhibit notable absorbance and fluorescence characteristics, making them suitable for sensing applications. The study utilized various analytical techniques to investigate the chemical composition, structure, morphology, optical attributes, elemental composition, and particle size of BN-GQDs. Techniques included X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM). The average particle size of the BN-GQDs was determined to be approximately 3.5 ± 0.3 nm. A clear correlation between the emission intensity ratio and RU concentration was identified across the range of 0.42 to 4.1 μM, featuring an impressively low detection limit (LOD) of 1.23 nM. The application of BN-GQDs as fluorescent probes has facilitated the development of a highly sensitive and selective RU detection method based on Förster resonance energy transfer (FRET) principles. This technique leverages emission at 465 nm. Density Functional Theory (DFT) analyses confirm that FRET is the primary mechanism behind fluorescence quenching, as indicated by the energy levels of the lowest unoccupied molecular orbitals (LUMOs) of BN-GQDs and RU. The method's effectiveness has been validated by measuring RU concentrations in human serum samples, showing a recovery range between 97.8% and 103.31%. Additionally, a smartphone-based detection method utilizing BN-GQDs has been successfully implemented, achieving a detection limit (LOD) of 49 nM.

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

A digital image colorimetry system based on smart devices for immediate and simultaneous determination of enzyme-linked immunosorbent assays

Standard enzyme-linked immunosorbent assays based on microplates are frequently utilized for various molecular sensing, disease screening, and nanomedicine applications. Comparing this multi-well plate batched analysis to non-batched or non-standard testing, the diagnosis expenses per patient are drastically reduced. However, the requirement for rather big and pricey readout instruments prevents their application in environments with limited resources, especially in the field. In this work, a handheld cellphone-based colorimetric microplate reader for quick, credible, and novel analysis of digital images of human cancer cell lines at a reasonable price was developed. Using our in-house-developed app, images of the plates are captured and sent to our servers, where they are processed using a machine learning algorithm to produce diagnostic results. Using FDA-approved human epididymis protein of ovary IgG (HE4), prostate cancer cell line (PC3), and bladder cancer cell line (5637) ELISA tests, we successfully examined this mobile platform. The accuracies for the HE4, PC3, and 5637 tests were 93%, 97.5%, and 97.2%, respectively. By contrasting the findings with the measurements made using optical absorption EPOCH microplate readers and optical absorption Tecan microplate readers, this approach was found to be accurate and effective. As a result, digital image colorimetry on smart devices offered a practical, user-friendly, affordable, precise, and effective method for quickly identifying human cancer cell lines. Thus, healthcare providers might use this portable device to carry out high-throughput illness screening, epidemiological investigations or monitor vaccination campaigns.

Ratiometric fluorescent sensing of melatonin based on inner filter effect and smartphone established detection

Melatonin (MLT) is a crucial neurohormone having inhibitory effects over various types of cancer. In this work, 3,6-Diaminocarbazole (DAC), a fluorescent probe is utilized to detect MLT in a highly sensitive, selective and facile way. The unique feature of present work is that MLT is sensed by ratiometric fluorescent technique based on the inner filter effect (IFE) using DAC at an emission wavelength of 310 nm. As a result, a noticeable change in color from red to cyan is observed and the quantitative analysis of fluorescence signals at these wavelengths are used to detect MLT observing a linear relationship between the ratio of emission intensities and the concentration of MLT over a linear range of 0 to 78 μM. DAC can accurately measure the detailed quantity of MLT with a limit of detection of 30 nM and has proved to be an efficient sensing probe due to its excellent molar absorptivity and high photoluminescence quantum yield (PLQY). Sensing characterization was carried out UV-Vis, steady-state, and time- resolved fluorescence spectroscopic techniques. The smartphone app "RGB colour detector" value has been successfully linked with the considerable detectable color changes of DAC on addition of MLT. HOMO-LUMO have been calculated using DFT with B3LYP/6-31G(d,p) level and band gaps of 3.77 eV and 4.91 eV were found for DAC and MLT, respectively. Electrons are not allowed energetically to transfer from MLT to DAC, as is evident from their band gaps. Therefore, IFE can be considered the foremost method in fluorescence quenching of present investigation. The developed sensor was verified by spiking of MLT in human serum.

Estimation of planar angles from non-orthogonal imaging

Photogrammetry-based methods are traditionally used to estimate the geometrical parameters using optical images. These methods employ specific equipment, computationally sophisticated and expensive algorithms, and utilize projective geometry to reconstruct real-life scenes up to a scale. In this work, we used a computationally less-expensive method for sparse reconstruction to estimate the planar angles using two-view geometry and linear algorithms from non-orthogonal images acquired by a smartphone camera. First, intrinsic camera parameters were determined. Next, scale-invariant feature transform was used to identify the correspondence points from each pair of images. Epipolar constraint was applied on all these points to determine the essential matrix using the eight-point algorithm. Thereafter, extrinsic camera parameters were estimated from the essential matrix and combined with the intrinsic matrix to get the camera projection matrix. Finally, linear triangulation was used to get the sparse point cloud representing the scene. Planar angles were estimated by backprojecting the chosen image points and applying simple vector algebra on the obtained 3D points. The method was successful in estimating the planar angles in less than 10 s on non-curved edges with an average error of 3% by using only ten images. Given the simplicity of methods used, this technique can be integrated into a smartphone for on-site measurements as well as large deformations.

Molecular point-of-care devices for the diagnosis of infectious diseases in resource-limited settings - A review of the current landscape, technical challenges, and clinical impact

Molecular point-of-care (POC) tests offer high sensitivity, rapid turnaround times, relative ease of use, and the convenience of laboratory-grade testing in the absence of formal laboratory spaces and equipment, making them appealing options for infectious disease diagnosis in resource-limited settings. In this review, we discuss the role and potential of molecular POC tests in resource-limited settings and their associated logistical challenges. We discuss U.S. Food and Drug Administration approval, Clinical Laboratory Improvement Amendments complexity levels, and the REASSURED criteria as a starting point for assessing options currently available inside and outside of the United States. We then present POC tests currently in research and development phases that have potential for commercialization and implementation in limited-resource settings. Finally, we review published studies that have assessed the clinical impact of molecular POC testing in limited- and moderate-resource settings.

Nanobiosensing Based on Electro-Optically Modulated Technology

At the nanoscale, metals exhibit special electrochemical and optical properties, which play an important role in nanobiosensing. In particular, surface plasmon resonance (SPR) based on precious metal nanoparticles, as a kind of tag-free biosensor technology, has brought high sensitivity, high reliability, and convenient operation to sensor detection. By applying an electrochemical excitation signal to the nanoplasma device, modulating its surface electron density, and realizing electrochemical coupling SPR, it can effectively complete the joint transmission of electrical and optical signals, increase the resonance shift of the spectrum, and further improve the sensitivity of the designed biosensor. In addition, smartphones are playing an increasingly important role in portable mobile sensor detection systems. These systems typically connect sensing devices to smartphones to perceive different types of information, from optical signals to electrochemical signals, providing ideas for the portability and low-cost design of these sensing systems. Among them, electrochemiluminescence (ECL), as a special electrochemically coupled optical technology, has good application prospects in mobile sensing detection due to its strong anti-interference ability, which is not affected by background light. In this review, the SPR is introduced using nanoparticles, and its response process is analyzed theoretically. Then, the mechanism and sensing application of electrochemistry coupled with SPR and ECL are emphatically introduced. Finally, it extends to the relevant research on electrochemically coupled optical sensing on mobile detection platforms.

A paper-based chemical tongue based on the charge transfer complex of ninhydrin with an array of metal-doped carbon dots discriminates natural amino acids and several of their enantiomers

Simultaneous detection of multiple amino acids (AAs) instead of individual AAs is inherently worthwhile for improving diagnostic accuracy in clinical applications. Here, a facile and reliable colorimetric microfluidic paper-based analytical device (μPAD) using carbon dots doped with transition metals (Cr3+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+, and Zn2+) has been provided to detect and discriminate 20 natural amino acids. To make the colourless metal-doped carbon dots suitable for colorimetric assays, they were mixed with ninhydrin to form a charge transfer complex. This optical tongue system, which was constructed by dropping mixtures of ninhydrin with a series of metal-doped carbon dots on a paper substrate in an array format, represented obvious but different colorimetric signatures for every examined amino acid. Since bovine serum albumin was used as a chiral selector reagent for synthesizing the CDs, the sensor device represented excellent selectivity to identify enantiomeric species of AAs. This is the first optical array device that can simultaneously discriminate AAs and several of their enantiomers. We employed various statistical and chemometric methods to analyze the digital data library collected by Image J software, including principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA). Twenty AAs could be well distinguished at various concentrations (10.00, 5.00, 2.50, and 1.25 mM). The colorimetric patterns were highly repeatable and were characteristic of individual AAs. Besides qualitative analysis, the designed μPAD-based optical tongue represented quantitative analysis ability, e.g., for lysine in the concentration ranges of 0.005-20.0 mM with a detection limit of 1.0 × 10-6 M and for arginine in the concentration range of 0.12-20.00 mM with a detection limit of 80.0 × 10-6 M. In addition, the binary, ternary, and quaternary mixtures of AAs could also be well recognized with this sensor.

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.

Micropatterning of functional lipid bilayer assays for quantitative bioanalysis

Interactions of the cell with its environment are mediated by the cell membrane and membrane-localized molecules. Supported lipid bilayers have enabled the recapitulation of the basic properties of cell membranes and have been broadly used to further our understanding of cellular behavior. Coupled with micropatterning techniques, lipid bilayer platforms have allowed for high throughput assays capable of performing quantitative analysis at a high spatiotemporal resolution. Here, an overview of the current methods of the lipid membrane patterning is presented. The fabrication and pattern characteristics are briefly described to present an idea of the quality and notable features of the methods, their utilizations for quantitative bioanalysis, as well as to highlight possible directions for the advanced micropatterning lipid membrane assays.

Sensitive fluorescence assay for the detection of glyphosate with NACCu2+ complex

Glyphosate is widely used as an herbicide in weed control. However, the excessive use and residue of glyphosate adversely affect the environment. Thus, a rapid and highly sensitive system must be developed for glyphosate detection. Herein, a novel turn-on fluorescent probe was designed and synthesized for glyphosate, that is N-butyl-1,8-naphthalimide-4-hydrazino-6-isopropyl-chromone (NAC). The fluorescence of NAC was quenched by the addition of Cu²⁺ to form NACCu²⁺ complex in dimethyl sulfoxide/2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid (DMSO/HEPES, 9/1, v/v, pH = 7.0). Upon the addition of glyphosate, the fluorescence of NACCu²⁺ was recovered through chelation between Cu²⁺ and glyphosate. The NACCu²⁺ complex exhibited the desired linearity of glyphosate concentration under optimum conditions in the range of 0-40 μM with a low detection limit of 36 nM. Based on competitive coordination, NACCu²⁺ exhibited good sensitivity and selectivity for glyphosate. Moreover, NAC was successfully utilized to detect glyphosate in tap water, local water from Songhua River, soil, maize, and soybean with convenient operations, indicating a promising application in pesticide residue detection.

Smartphone-based corona virus detection using saliva: A mini-review

During the ongoing worldwide epidemic, SARS-CoV-2 has infected millions of individuals and taken the lives of numerous victims. It is clear that early detection of infected individuals, especially asymptomatic carriers, is possible with the development of innovative analytical tools for rapid identification of COVID-19 present in nasopharyngeal swabs, serum, and saliva. The saliva, as a diagnostic sample, can be easily collected by the patient with almost no discomfort and needs specialized healthcare personnel to manage, which reduces the risks for the operator. Moreover, smartphone-based sensing systems are one of the most attractive techniques that can speed up the detection time of COVID-19 agents without the need for professional staff and clinical centers. In this review, recent advances in precise salivary-based SARS-CoV-2 diagnosis using smartphones via viral RNA detection, antibody identification, and viral antigen identification were summarized. Finally, the conclusion and future perspective of this field are described in brief.

Acoustofluidics - changing paradigm in tissue engineering, therapeutics development, and biosensing

For more than 70 years, acoustic waves have been used to screen, diagnose, and treat patients in hundreds of medical devices. The biocompatible nature of acoustic waves, their non-invasive and contactless operation, and their compatibility with wide visualization techniques are just a few of the many features that lead to the clinical success of sound-powered devices. The development of microelectromechanical systems and fabrication technologies in the past two decades reignited the spark of acoustics in the discovery of unique microscale bio applications. Acoustofluidics, the combination of acoustic waves and fluid mechanics in the nano and micro-realm, allowed researchers to access high-resolution and controllable manipulation and sensing tools for particle separation, isolation and enrichment, patterning of cells and bioparticles, fluid handling, and point of care biosensing strategies. This versatility and attractiveness of acoustofluidics have led to the rapid expansion of platforms and methods, making it also challenging for users to select the best acoustic technology. Depending on the setup, acoustic devices can offer a diverse level of biocompatibility, throughput, versatility, and sensitivity, where each of these considerations can become the design priority based on the application. In this paper, we aim to overview the recent advancements of acoustofluidics in the multifaceted fields of regenerative medicine, therapeutic development, and diagnosis and provide researchers with the necessary information needed to choose the best-suited acoustic technology for their application. Moreover, the effect of acoustofluidic systems on phenotypic behavior of living organisms are investigated. The review starts with a brief explanation of acoustofluidic principles, the different working mechanisms, and the advantages or challenges of commonly used platforms based on the state-of-the-art design features of acoustofluidic technologies. Finally, we present an outlook of potential trends, the areas to be explored, and the challenges that need to be overcome in developing acoustofluidic platforms that can echo the clinical success of conventional ultrasound-based devices.

Portable, low-cost, Raspberry Pi-based optical sensor (PiSENS): continuous monitoring of atmospheric nitrogen dioxide

We have developed a sensing system that utilizes a low-cost computer (Raspberry Pi) and its imaging camera as an optical sensing core for the continuous detection of NO₂ in the air (PiSENS-A). The sensor is based on colour development as a consequence of the interaction of the gas with an absorbing solution. The PiSENS-A is thoroughly calibrated over the hourly mean which is used as one of the key metrics in evaluating air quality. The calibration was performed in the range of 0 < [NO₂] < 476 μg m^-3 chosen to contain the threshold used to determine compliance to the UK's Air Quality Standard Regulations (2010) expressed as a maximum of 18 permitted exceedances of [NO₂]_{hourly mean} = 200 μg per m³ per year. Lab-based measurements were evaluated against UV-vis. The average precision expressed as a relative standard deviation was: RSD% = 2.8%, while the correlation of mock samples was excellent (Pearson's r = 1.000). Field-based measurements were evaluated against chemiluminescence-based instrument exhibiting a correlation coefficient of R² = 0.993. The PiSENS-A was also deployed as an independent air quality analyser at the Keele University campus.

Non-Destructive Detection of Meat Quality Based on Multiple Spectral Dimension Reduction Methods by Near-Infrared Spectroscopy

The potential of four dimension reduction methods for near-infrared spectroscopy was investigated, in terms of predicting the protein, fat, and moisture contents in lamb meat. With visible/near-infrared spectroscopy at 400-1050 nm and 900-1700 nm, respectively, calibration models using partial least squares regression (PLSR) or multiple linear regression (MLR) between spectra and quality parameters were established and compared. The MLR prediction models for all three quality parameters based on the wavelengths selected by stepwise regression achieved the best results in the spectral region of 400-1050 nm. As for the spectral region of 900-1700 nm, the PLSR prediction model based on the raw spectra or high-correlation spectra achieved better results. The results of this study indicate that sampling interval shortening and of peak-to-trough jump features are worthy of further study, due to their great potential in explaining the quality parameters.

Portable, Automated and Deep-Learning-Enabled Microscopy for Smartphone-Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review

Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone-based portable diagnostic devices are significantly efficient tools to user-friendly connect personalized health conditions and collect valuable optical information for rapid diagnosis and biomedical research through at-home screening. Deep learning algorithms for portable microscopes also help to enhance diagnostic accuracy by reducing the imaging resolution gap between benchtop and portable microscopes. This review highlighted recent progress and continued efforts in a smartphone-tethered optical platform through portable, automated, and deep-learning-enabled microscopy for personalized diagnostics and remote monitoring. In detail, the optical platforms through smartphone-based microscopes and lens-free holographic microscopy are introduced, and deep learning-based portable microscopic imaging is explained to improve the image resolution and accuracy of diagnostics. The challenges and prospects of portable optical systems with microfluidic channels and a compact microscope to screen COVID-19 in the current pandemic are also discussed. It has been believed that this review offers a novel guide for rapid diagnosis, biomedical imaging, and digital healthcare with low cost and portability.

Performance evaluation of Hipee S2 point-of-care testing urine dipstick analyser: a cross-sectional study

OBJECTIVE

With advances in mobile technology, smartphone-based point-of-care testing (POCT) urinalysis hold great potential for disease screening and health management for clinicians and individual users. The purpose of this study is to evaluate the analytical performance of Hipee S2 POCT urine dipstick analyser.

DESIGN

A multicentre, hospital-based, cross-sectional study.

SETTING

Analytical performance of the POCT analyser was conducted at a clinical laboratory, and method comparison was performed at three clinical laboratories in China.

PARTICIPANTS

Urine samples were collected from 1603 outpatients and inpatients at three hospitals, and 5 health check-up population at one of the hospitals.

OUTCOME MEASURES

All tests were performed by clinical laboratory technicians. Precision, drift, carry-over, interference and method comparison of Hipee S2 were evaluated. Diagnostic accuracy of semiquantitative albumin-to-creatinine ratio (ACR) for albuminuria was carried out using quantitative ACR as the standard.

RESULTS

The precision for each parameter, assessed by control materials, was acceptable. No sample carry-over or drift was observed. Ascorbate solution with 1 g/L had an inhibitory effect for the haemoglobin test. Agreement for specific gravity (SG) varied between moderate to substantial (κ values 0.496-0.687), for pH was moderate (κ values 0.423-0.569) and for other parameters varied between substantial to excellent (κ values 0.669-0.991), on comparing the Hipee S2 with laboratory analysers. The semiquantitative microalbumin and creatinine were highly correlated with the quantitative results. The sensitivity of semiquantitative ACR to detect albuminuria was 87.2%-90.7%, specificity was 70.7%-78.4%, negative predictive value was 85.3%-87.9% and positive predictive value was 73.9%-83%.

CONCLUSIONS

Hipee S2 POCT urine analyser showed acceptable analytical performance as a semiquantitative method. It serves as a convenient alternate device for clinicians and individual users for urinalysis and health management. In addition, the POCT semiquantitative ACR would be useful in screening for albuminuria.

Toward Next Generation Lateral Flow Assays: Integration of Nanomaterials

Lateral flow assays (LFAs) are currently the most used point-of-care sensors for both diagnostic (e.g., pregnancy test, COVID-19 monitoring) and environmental (e.g., pesticides and bacterial monitoring) applications. Although the core of LFA technology was developed several decades ago, in recent years the integration of novel nanomaterials as signal transducers or receptor immobilization platforms has brought improved analytical capabilities. In this Review, we present how nanomaterial-based LFAs can address the inherent challenges of point-of-care (PoC) diagnostics such as sensitivity enhancement, lowering of detection limits, multiplexing, and quantification of analytes in complex samples. Specifically, we highlight the strategies that can synergistically solve the limitations of current LFAs and that have proven commercial feasibility. Finally, we discuss the barriers toward commercialization and the next generation of LFAs.

A visual portable microfluidic experimental device with multiple electric field regulation functions

High portability and miniaturization are two of the most important objectives pursued by microfluidic methods. However, there remain many challenges for the design of portable and visual microfluidic devices (e.g., electrokinetic experiments) due to the use of a microscope and power supply. To this end, we report a visual portable microfluidic experimental device (PMED) with multiple electric field regulation functions, which can realize the electric field regulation functions of various basic microfluidic experiments through modular design. The internal reaction process of the microfluidic chip is displayed by a smartphone, and the experimental results are analyzed using a mobile phone application (APP). Taking the induced-charge electroosmosis (ICEO) particle focusing phenomenon as an example, we carried out detailed experiments on PMED and obtained conclusions consistent with numerical simulations. In addition to ICEO experiments, other functions such as alternating electroosmosis (ACEO), thermal buoyancy convection, and dielectrophoresis (DEP) can be realized by replacing module-specific covers. The device expands the application of microfluidic experiments and provides a certain reference for the further integration and portability of subsequent microfluidic experiment devices.

A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm

Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system-related diseases are diagnosed by the differential count of white blood cells, which is one of the common laboratory tests. Data is one of the most important ingredients in the development and testing of many commercial and successful automatic or semi-automatic systems. To this end, this study introduces a free access dataset of normal peripheral white blood cells called Raabin-WBC containing about 40,000 images of white blood cells and color spots. For ensuring the validity of the data, a significant number of cells were labeled by two experts. Also, the ground truths of the nuclei and cytoplasm are extracted for 1145 selected cells. To provide the necessary diversity, various smears have been imaged, and two different cameras and two different microscopes were used. We did some preliminary deep learning experiments on Raabin-WBC to demonstrate how the generalization power of machine learning methods, especially deep neural networks, can be affected by the mentioned diversity. Raabin-WBC as a public data in the field of health can be used for the model development and testing in different machine learning tasks including classification, detection, segmentation, and localization.

Assessment of a Smartphone-Based Loop-Mediated Isothermal Amplification Assay for Detection of SARS-CoV-2 and Influenza Viruses

Importance

A critical need exists in low-income and middle-income countries for low-cost, low-tech, yet highly reliable and scalable testing for SARS-CoV-2 virus that is robust against circulating variants.

Objective

To assess whether a smartphone-based assay is suitable for SARS-CoV-2 and influenza virus testing without requiring specialized equipment, accessory devices, or custom reagents.

Design, Setting, and Participants

This cohort study enrolled 2 subgroups of participants (symptomatic and asymptomatic) at Santa Barbara Cottage Hospital. The symptomatic group consisted of 20 recruited patients who tested positive for SARS-CoV-2 with symptoms; 30 asymptomatic patients were recruited from the same community, through negative admission screening tests for SARS-CoV-2. The smartphone-based real-time loop-mediated isothermal amplification (smaRT-LAMP) was first optimized for analysis of human saliva samples spiked with either SARS-CoV-2 or influenza A or B virus; these results then were compared with those obtained by side-by-side analysis of spiked samples using the Centers for Disease Control and Prevention (CDC) criterion-standard reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) assay. Next, both assays were used to test for SARS-CoV-2 and influenza viruses present in blinded clinical saliva samples obtained from 50 hospitalized patients. Statistical analysis was performed from May to June 2021.

Exposures

Testing for SARS-CoV-2 and influenza A and B viruses.

Main Outcomes and Measures

SARS-CoV-2 and influenza infection status and quantitative viral load were determined.

Results

Among the 50 eligible participants with no prior SARS-CoV-2 infection included in the study, 29 were men. The mean age was 57 years (range, 21 to 93 years). SmaRT-LAMP exhibited 100% concordance (50 of 50 patient samples) with the CDC criterion-standard diagnostic for SARS-CoV-2 sensitivity (20 of 20 positive and 30 of 30 negative) and for quantitative detection of viral load. This platform also met the CDC criterion standard for detection of clinically similar influenza A and B viruses in spiked saliva samples (n = 20), and in saliva samples from hospitalized patients (50 of 50 negative). The smartphone-based LAMP assay was rapid (25 minutes), sensitive (1000 copies/mL), low-cost (<$7/test), and scalable (96 samples/phone).

Conclusions and Relevance

In this cohort study of saliva samples from patients, the smartphone-based LAMP assay detected SARS-CoV-2 infection and exhibited concordance with RT-qPCR tests. These findings suggest that this tool could be adapted in response to novel CoV-2 variants and other pathogens with pandemic potential including influenza and may be useful in settings with limited resources.

An affordable, handheld multimodal microscopic system with onboard cell morphology and counting features on a mobile device

A simple yet effective, handheld and flexible bright-field and fluorescence microscopic platform on a smartphone with varying optical magnifications is reported for morphological analysis and onboard cell counting features.

Honey bee sHSP are responsive to diverse proteostatic stresses and potentially promising biomarkers of honey bee stress

The pollination services provided by the honey bee are critical in both natural and agricultural ecosystems. Honey bee colonies in the United States have suffered from an increased rate of die-off in recent years, stemming from a complex set of interacting stresses that remain poorly described. Defining specific common cellular processes and cellular stress responses impacted by multiple stressors represent a key step in understanding these synergies. Proteotoxic stresses negatively impact protein synthesis, folding, and degradation. Diverse proteotoxic stresses induce expression of genes encoding small heat shock proteins (sHSP) of the expanded lethal (2) essential for life (l(2)efl) gene family. In addition to upregulation by the Integrated Stress Response (ISR), the Heat Shock Response (HSR), and the Oxidative Stress Response (OSR), our data provide first evidence that sHSP genes are upregulated by the Unfolded Protein Response (UPR). As these genes appear to be part of a core stress response that could serve as a useful biomarker for cellular stress in honey bees, we designed and tested an RT-LAMP assay to detect increased l(2)efl gene expression in response to heat-stress. While this assay provides a powerful proof of principle, further work will be necessary to link changes in sHSP gene expression to colony-level outcomes, to adapt our preliminary assay into a Point of Care Testing (POCT) assay appropriate for use as a diagnostic tool for use in the field, and to couple assay results to management recommendations.

Paper-based analytical devices for virus detection: Recent strategies for current and future pandemics

The importance of user-friendly, inexpensive, sensitive, and selective detection of viruses has been highlighted again due to the recent Coronavirus disease 2019 (COVID-19) pandemic. Among the analytical tools, paper-based devices (PADs) have become a leading alternative for point-of-care (POC) testing. In this review, we discuss the recent development strategies and applications in nucleic acid-based, antibody/antigen-based and other affinity-based PADs using optical and electrochemical detection methods for sensing viruses. In addition, advantages and drawbacks of presented PADs are identified. Current state and insights towards future perspectives are presented regarding developing POC diagnosis platform for COVID-19. This review considers state-of-the-art technologies for further development and improvement in PADs performance for virus detection.

Exploring the use of upconversion nanoparticles in chemical and biological sensors: from surface modifications to point-of-care devices

Upconversion nanoparticles (UCNPs) have emerged as promising luminescent nanomaterials due to their unique features that allow the overcoming of several problems associated with conventional fluorescent probes. Although UCNPs have been used in a broad range of applications, it is probably in the field of sensing where they best evidence their potential. UCNP-based sensors have been designed with high sensitivity and selectivity, for detection and quantification of multiple analytes ranging from metal ions to biomolecules. In this review, we deeply explore the use of UCNPs in sensing systems emphasizing the most relevant and recent studies on the topic and explaining how these platforms are constructed. Before diving into UCNP-based sensing platforms it is important to understand the unique characteristics of these nanoparticles, why they are attracting so much attention, and the most significant interactions occurring between UCNPs and additional probes. These points are covered over the first two sections of the article and then we explore the types of fluorescent responses, the possible analytes, and the UCNPs' integration with various material types such as gold nanostructures, quantum dots and dyes. All the topics are supported by analysis of recently reported sensors, focusing on how they are built, the materials' interactions, the involved synthesis and functionalization mechanisms, and the conjugation strategies. Finally, we explore the use of UCNPs in paper-based sensors and how these platforms are paving the way for the development of new point-of-care devices.

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning

Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sample that potentially contains the target antigen, as a result of which the particles form clusters, with a size that is a function of the antigen concentration and the reaction time. Here, we present a quantitative particle agglutination assay that combines mobile lens-free microscopy and deep learning for rapidly measuring the concentration of a target analyte; as its proof-of-concept, we demonstrate high-sensitivity C-reactive protein (hs-CRP) testing using human serum samples. A dual-channel capillary lateral flow device is designed to host the agglutination reaction using 4 μL of serum sample with a material cost of 1.79 cents per test. A mobile lens-free microscope records time-lapsed inline holograms of the lateral flow device, monitoring the agglutination process over 3 min. These captured holograms are processed, and at each frame the number and area of the particle clusters are automatically extracted and fed into shallow neural networks to predict the CRP concentration. 189 measurements using 88 unique patient serum samples were utilized to train, validate and blindly test our platform, which matched the corresponding ground truth concentrations in the hs-CRP range (0-10 μg mL^-1) with an R² value of 0.912. This computational sensing platform was also able to successfully differentiate very high CRP concentrations (e.g., >10-500 μg mL^-1) from the hs-CRP range. This mobile, cost-effective and quantitative particle agglutination assay can be useful for various point-of-care sensing needs and global health related applications.

Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging

Research related to the development and application of luminescent nanoparticles (LNPs) for chemical and biological analysis and imaging is flourishing. Novel materials and new applications continue to be reported after two decades of research. This review provides a comprehensive and heuristic overview of this field. It is targeted to both newcomers and experts who are interested in a critical assessment of LNP materials, their properties, strengths and weaknesses, and prospective applications. Numerous LNP materials are cataloged by fundamental descriptions of their chemical identities and physical morphology, quantitative photoluminescence (PL) properties, PL mechanisms, and surface chemistry. These materials include various semiconductor quantum dots, carbon nanotubes, graphene derivatives, carbon dots, nanodiamonds, luminescent metal nanoclusters, lanthanide-doped upconversion nanoparticles and downshifting nanoparticles, triplet-triplet annihilation nanoparticles, persistent-luminescence nanoparticles, conjugated polymer nanoparticles and semiconducting polymer dots, multi-nanoparticle assemblies, and doped and labeled nanoparticles, including but not limited to those based on polymers and silica. As an exercise in the critical assessment of LNP properties, these materials are ranked by several application-related functional criteria. Additional sections highlight recent examples of advances in chemical and biological analysis, point-of-care diagnostics, and cellular, tissue, and in vivo imaging and theranostics. These examples are drawn from the recent literature and organized by both LNP material and the particular properties that are leveraged to an advantage. Finally, a perspective on what comes next for the field is offered.

A multispectral-sensor-based colorimetric reader for biological assays

Tests that depend on changes in color are commonly used in biosensing. Here, we report on a colorimetric reader for such applications. The device is simple to construct and operate, making it ideal for research laboratories with limited resources or skilled personnel. It consists of a commercial multispectral sensor interfaced with a Raspberry Pi and a touchscreen. Unlike camera-based readers, this instrument requires no calibration of wavelengths by the user or extensive image processing to obtain results. We demonstrate its potential for colorimetric biosensing by applying it to the birefringent enzyme-linked immunosorbent assay. It was able to prevent certain false positives that the assay is susceptible to and lowered its limit of detection for glucose by an order of magnitude.

Development and Application of Mobile Apps for Molecular Sensing: A Review

Modern smartphone-based sensing devices are generally standalone detection platforms that can transduce signals (via the built-in USB port, audio jack, or camera), perform analysis through mobile applications (apps), and display results on the screen/user interface. The advancement toward this ultimate form of on-site chemical analysis and point-of-care diagnosis is tied closely with the evolution of mobile technology. Previous reviews in the field mainly focused on the physical platforms while overlooking the role of mobile apps in such devices. There exist three general stages throughout the development: (1) early generation telemedicine, (2) mobile phone-assisted clinical diagnosis (without apps), and (3) mobile app-based sensing devices for various analytes. This review presents the key breakthroughs during each stage, recent development, remaining challenges, and future perspectives of the field. Representative examples, spanning from the pioneering point-of-care testing to the latest devices with integrated mobile apps, are classified by their sensing mechanisms. The review also discusses the scarcity of open-source apps dedicated to molecular sensing. With the introduction of more open-source and commercial apps, the mobile app-based detection system is anticipated to dominate point-of-care diagnosis and on-site molecular sensing in our opinion.

Sensing Optimum in the Raw: Leveraging the Raw-Data Imaging Capabilities of Raspberry Pi for Diagnostics Applications

Single-board computers (SBCs) and microcontroller boards (MCBs) are extensively used nowadays as prototyping platforms to accomplish innovative tasks. Very recently, implementations of these devices for diagnostics applications are rapidly gaining ground for research and educational purposes. Among the available solutions, Raspberry Pi represents one of the most used SBCs. In the present work, two setups based on Raspberry Pi and its CMOS-based camera (a 3D-printed device and an adaptation of a commercial product named We-Lab) were investigated as diagnostic instruments. Different camera elaboration processes were investigated, showing how direct access to the 10-bit raw data acquired from the sensor before downstream imaging processes could be beneficial for photometric applications. The developed solution was successfully applied to the evaluation of the oxidative stress using two commercial kits (d-ROM Fast; PAT). We suggest the analysis of raw data applied to SBC and MCB platforms in order to improve results.

Recent trends in smartphone-based detection for biomedical applications: a review

Smartphone-based imaging devices (SIDs) have shown to be versatile and have a wide range of biomedical applications. With the increasing demand for high-quality medical services, technological interventions such as portable devices that can be used in remote and resource-less conditions and have an impact on quantity and quality of care. Additionally, smartphone-based devices have shown their application in the field of teleimaging, food technology, education, etc. Depending on the application and imaging capability required, the optical arrangement of the SID varies which enables them to be used in multiple setups like bright-field, fluorescence, dark-field, and multiple arrays with certain changes in their optics and illumination. This comprehensive review discusses the numerous applications and development of SIDs towards histopathological examination, detection of bacteria and viruses, food technology, and routine diagnosis. Smartphone-based devices are complemented with deep learning methods to further increase the efficiency of the devices. Graphical Abstract.

Addressable nanoantennas with cleared hotspots for single-molecule detection on a portable smartphone microscope

The advent of highly sensitive photodetectors and the development of photostabilization strategies made detecting the fluorescence of single molecules a routine task in many labs around the world. However, to this day, this process requires cost-intensive optical instruments due to the truly nanoscopic signal of a single emitter. Simplifying single-molecule detection would enable many exciting applications, e.g., in point-of-care diagnostic settings, where costly equipment would be prohibitive. Here, we introduce addressable NanoAntennas with Cleared HOtSpots (NACHOS) that are scaffolded by DNA origami nanostructures and can be specifically tailored for the incorporation of bioassays. Single emitters placed in NACHOS emit up to 461-fold (average of 89 ± 7-fold) brighter enabling their detection with a customary smartphone camera and an 8-US-dollar objective lens. To prove the applicability of our system, we built a portable, battery-powered smartphone microscope and successfully carried out an exemplary single-molecule detection assay for DNA specific to antibiotic-resistant Klebsiella pneumonia on the road.

Single-molecule fluorescence currently requires specialized imaging equipment due to the low signal of a single emitter. Here the authors introduce NanoAntennas with Cleared HOtSpots (NACHOS) to boost the signal sufficient for detection of a single emitter by a smartphone, opening the door to point-of-care applications.

User-friendly lab-on-paper optical sensor for the rapid detection of bacterial spoilage in packaged meat products

A lab-on-paper colorimetric sensor for detection and quantification of bacterial meat spoilage is reported.

Smart phone assisted quinoline-hemicyanine based fluorescent probe for the selective detection of glutathione and the application in living cells

Quinoline appended hemicyanine 6MIM with strong ICT character was successfully synthesized through simple condensation reaction of 6-methoxy-2-chloro-3-formyl quinoline with 2-benzothiazolinium iodide. The photophysical characteristics of synthesized probe revealed that it would selectively detect glutathione (GSH) when it compared with different amino acids including biothiols and the detection limit is found to be 100 nM. The turn off sensor is due to thiol-halogen S_NAr nucleophilic substitution between 6MIM and thiol group in glutathione. More importantly, the biosensor 6MIM was effectively applied in the fluorescence bioimaging of GSH in living cells with low cell toxicity. The colorimetric detectable color change of 6MIM-GSH has been effectively integrated with smartphone assisted RGB color value application with lowest detection value of 120 nM.

C3-symmetric triaminoguanidine based colorimetric and fluorometric chemosensor: Sequential detection of Zn2+/PPi, its RGB performance for detection of Zn2+ ion and construction of IMPLICATION logic gate

In this work, new ethyl(E)-2-cyano-3-(1H-pyrrol-2-yl)acrylate appended C₃-symmetric star-shape triaminoguanidine based Schiff base (LH₃) was designed and synthesized from simple synthons. New probe, LH₃ was completely analyzed by ¹H NMR, ¹³C NMR and mass spectrum. In the present probe LH₃, effective π-conjugated ethyl(E)-2-cyano-acrylate unit was introduced on the periphery of the pyrrole-triaminoquanidine conjugates by using carefully chosen building units. The probe LH₃ shows high selectivity and sensitivity towards Zn²⁺ ion via colorimetric and fluorometric changes. The yellowish orange color of LH₃ solution turned to wine red color upon addition of Zn²⁺ solution, along with red shifted absorption maxima from 450 nm to 550 nm, this indicates the formation of LH₃-Zn²⁺ species. Job's plot and mass spectrum analysis confirms the formation of 1:3 stoichiometric complex between the LH₃ and Zn²⁺ ions. Further this ensemble shows selective detection towards PPi anion over the other anions based on displacement metal ion approach. Hence, reversible colorimetric/emission response of LH₃ towards Zn²⁺ and PPi ions via "on-off-on" manner could allow the construction of IMPLICATION logic gate functions. The practical efficacy of the probe LH₃ was established by utilization of the probe for the detection of Zn²⁺ ions in real water sample analysis. Further, the significant noticeable colorimetric changes of the probe LH₃ upon addition of Zn²⁺ ion have been successfully integrated with a smartphone app RGB color value to construct a real-time analysis of Zn²⁺ ions.

Measurement of serum phosphate levels using a mobile sensor

The measurement of serum phosphate concentration is crucial for patients with advanced chronic kidney disease (CKD) and those on maintenance dialysis, as abnormal phosphate levels may be associated with severe health risks. It is important to monitor serum phosphate levels on a regular basis in these patients; however, such measurements are generally limited to every 0.5-3 months, depending on the severity of CKD. This is due to the fact that serum phosphate measurements can only be performed at regular clinic visits, in addition to cost considerations. Here we present a portable and cost-effective point-of-care device capable of measuring serum phosphate levels using a single drop of blood (<60 μl). This is achieved by integrating a paper-based microfluidic platform with a custom-designed smartphone reader. This mobile sensor was tested on patients undergoing dialysis, where whole blood samples were acquired before starting the hemodialysis and during the three-hour treatment. This sampling during the hemodialysis, under patient consent, allowed us to test blood samples with a wide range of phosphate concentrations, and our results showed a strong correlation with the ground truth laboratory tests performed on the same patient samples (Pearson coefficient r = 0.95 and p < 0.001). Our 3D-printed smartphone attachment weighs about 400 g and costs less than 80 USD, whereas the material cost for the disposable test is <3.5 USD (under low volume manufacturing). This low-cost and easy-to-operate system can be used to measure serum phosphate levels at the point-of-care in about 45 min and can potentially be used on a daily basis by patients at home.

Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer

We report a field-portable and cost-effective imaging flow cytometer that uses deep learning and holography to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput of 100 mL h-1. This flow cytometer uses lens free color holographic imaging to capture and reconstruct phase and intensity images of microscopic objects in a continuously flowing sample, and automatically identifies Giardia lamblia cysts in real-time without the use of any labels or fluorophores. The imaging flow cytometer is housed in an environmentally-sealed enclosure with dimensions of 19 cm × 19 cm × 16 cm and weighs 1.6 kg. We demonstrate that this portable imaging flow cytometer coupled to a laptop computer can detect and quantify, in real-time, low levels of Giardia contamination (e.g., <10 cysts per 50 mL) in both freshwater and seawater samples. The field-portable and label-free nature of this method has the potential to allow rapid and automated screening of drinking water supplies in resource limited settings in order to detect waterborne parasites and monitor the integrity of the filters used for water treatment.

Automated screening of sickle cells using a smartphone-based microscope and deep learning

Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited settings, SCD is not consistently diagnosed. In Africa, where the majority of SCD patients reside, more than 50% of the 0.2-0.3 million children born with SCD each year will die from it; many of these deaths are in fact preventable with correct diagnosis and treatment. Here, we present a deep learning framework which can perform automatic screening of sickle cells in blood smears using a smartphone microscope. This framework uses two distinct, complementary deep neural networks. The first neural network enhances and standardizes the blood smear images captured by the smartphone microscope, spatially and spectrally matching the image quality of a laboratory-grade benchtop microscope. The second network acts on the output of the first image enhancement neural network and is used to perform the semantic segmentation between healthy and sickle cells within a blood smear. These segmented images are then used to rapidly determine the SCD diagnosis per patient. We blindly tested this mobile sickle cell detection method using blood smears from 96 unique patients (including 32 SCD patients) that were imaged by our smartphone microscope, and achieved ~98% accuracy, with an area-under-the-curve of 0.998. With its high accuracy, this mobile and cost-effective method has the potential to be used as a screening tool for SCD and other blood cell disorders in resource-limited settings.

Deep learning-enabled point-of-care sensing using multiplexed paper-based sensors

We present a deep learning-based framework to design and quantify point-of-care sensors. As a use-case, we demonstrated a low-cost and rapid paper-based vertical flow assay (VFA) for high sensitivity C-Reactive Protein (hsCRP) testing, commonly used for assessing risk of cardio-vascular disease (CVD). A machine learning-based framework was developed to (1) determine an optimal configuration of immunoreaction spots and conditions, spatially-multiplexed on a sensing membrane, and (2) to accurately infer target analyte concentration. Using a custom-designed handheld VFA reader, a clinical study with 85 human samples showed a competitive coefficient-of-variation of 11.2% and linearity of R 2 = 0.95 among blindly-tested VFAs in the hsCRP range (i.e., 0-10 mg/L). We also demonstrated a mitigation of the hook-effect due to the multiplexed immunoreactions on the sensing membrane. This paper-based computational VFA could expand access to CVD testing, and the presented framework can be broadly used to design cost-effective and mobile point-of-care sensors.

Clinical evaluation of smartphone-based fluorescence imaging for guidance and monitoring of ALA-PDT treatment of early oral cancer

SIGNIFICANCE

India has one of the highest rates of oral cancer incidence in the world, accounting for 30% of reported cancers. In rural areas, a lack of adequate medical infrastructure contributes to unchecked disease progression and dismal mortality rates. Photodynamic therapy (PDT) has emerged as an effective modality with potential for treating early stage disease in resource-limited settings, while photosensitizer fluorescence can be leveraged for treatment guidance.

AIM

Our aim was to assess the capability of a simple smartphone-based device for imaging 5-aminolevulinic acid (ALA)-induced protoporphyrin IX (PpIX) fluorescence for treatment guidance and monitoring as part of an ongoing clinical study evaluating low-cost technology for ALA-based PDT treatment of early oral cancer.

APPROACH

A total of 29 subjects with <2  cm diameter moderately/well-differentiated microinvasive (  <  5  mm depth) oral squamous cell carcinoma lesions (33 lesions total, mean area ∼1.23  cm2) were administered 60  mg  /  kg ALA in oral solution and imaged before and after delivery of 100  J  /  cm2 total light dose to the lesion surface. Smartphone-based fluorescence and white light (WL) images were analyzed and compared with ultrasound (US) imaging of the same lesions.

RESULTS

We present a comparative analysis of pre- and post-treatment fluorescence, WL, and US images of oral lesions. There was no significant difference in the distribution of lesion widths measured by fluorescence and US (mean widths of 14.5 and 15.3 mm, respectively) and linear regression shows good agreement (R2  =  0.91). In general, PpIX fluorescence images obtained prior to therapeutic light delivery are able to resolve lesion margins while dramatic photobleaching (∼42  %  ) is visible post-treatment. Segmentation of the photobleached area confirms the boundaries of the irradiated zone.

CONCLUSIONS

A simple smartphone-based approach for imaging oral lesions is shown to agree in most cases with US, suggesting that this approach may be a useful tool to aid in PDT treatment guidance and monitoring photobleaching as part of a low-cost platform for intraoral PDT.