A personalized food allergen testing platform on a cellphone

Domain-Agnostic Representation of Side-Channels

Side channels are unintended pathways within target systems that leak internal target information. Side-channel sensing (SCS) is the process of exploiting side channels to extract embedded target information. SCS is well established within the cybersecurity (CYB) domain, and has recently been proposed for medical diagnostics and monitoring (MDM). Remaining unrecognised is its applicability to human-computer interaction (HCI), among other domains (Misc). This article analyses literature demonstrating SCS examples across the MDM, HCI, Misc, and CYB domains. Despite their diversity, established fields of advanced sensing and signal processing underlie each example, enabling the unification of these currently otherwise isolated domains. Identified themes are collating under a proposed domain-agnostic SCS framework. This SCS framework enables a formalised and systematic approach to studying, detecting, and exploiting of side channels both within and between domains. Opportunities exist for modelling SCS as data structures, allowing for computation irrespective of domain. Future methodologies can take such data structures to enable cross- and intra-domain transferability of extraction techniques, perform side-channel leakage detection, and discover new side channels within target systems.

Smartphone-based colorimetric detection platform using color correction algorithms to reduce external interference

Smartphone-based digital image colorimetry is a powerful, fast, low-cost approach to detecting target analytes. However, lighting conditions and camera parameters easily affect the detection results, significantly curtailing its applicability in multiple scenarios. In this study, an Android-based mobile application (SMP-CC) is developed, which offers a comprehensive package that includes image acquisition, color correction, and colorimetric analysis functions. Using a custom color card, a built-in algorithm in SMP-CC can minimize the color difference between the standard color block image captured by different smartphones under different lighting conditions and the standard value by an LS171 colorimeter less than 4.36. The algorithm significantly eliminates the impacts of external lighting conditions and differences in cell phone models. Furthermore, the feasibility of SMP-CC was verified by successful colorimetric detection of urine pH, glucose, and protein, demonstrating its potential in smartphone-based digital image colorimetry.

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.

Advances and Opportunities of Mobile Health in the Postpandemic Era: Smartphonization of Wearable Devices and Wearable Deviceization of Smartphones

Mobile health (mHealth) with continuous real-time monitoring is leading the era of digital medical convergence. Wearable devices and smartphones optimized as personalized health management platforms enable disease prediction, prevention, diagnosis, and even treatment. Ubiquitous and accessible medical services offered through mHealth strengthen universal health coverage to facilitate service use without discrimination. This viewpoint investigates the latest trends in mHealth technology, which are comprehensive in terms of form factors and detection targets according to body attachment location and type. Insights and breakthroughs from the perspective of mHealth sensing through a new form factor and sensor-integrated display overcome the problems of existing mHealth by proposing a solution of smartphonization of wearable devices and the wearable deviceization of smartphones. This approach maximizes the infinite potential of stagnant mHealth technology and will present a new milestone leading to the popularization of mHealth. In the postpandemic era, innovative mHealth solutions through the smartphonization of wearable devices and the wearable deviceization of smartphones could become the standard for a new paradigm in the field of digital medicine.

Critical importance of RGB color space specificity for colorimetric bio/chemical sensing: A comprehensive study

The use of the RGB color model in colorimetric chemical sensing via imaging techniques is widely prevalent in the literature. However, the lack of specificity in the selection of RGB color space during capture and analysis presents a significant challenge in creating standardised methods for this field and possible discrepancies. In this study, we conducted a comprehensive comparison and contrast of a total of 68 RGB color spaces to evaluate their respective impacts on colorimetric bio/chemical sensing. We explore the impact of dynamic range, sensitivity, and limit of detection, and show that the lack of specificity in RGB color space selection can significantly impact colorimetric chemical sensing by 42-77%. We also explore the impact of underlying RGB comparisons and demonstrate a further 18.3% discrepancy between RGB color spaces. By emphasising the importance of proper RGB color space selection and handling, our findings contribute to a better understanding of this critical area and present valuable opportunities for future research. We further provide valuable insights for creating standardised methods in this field, which can be utilised to avoid discrepancies and ensure accurate and reliable analysis in colorimetric bio/chemical sensing.

Optical fiber speckle spectrometer based on reversed-lens smartphone microscope

Smartphones are a potentially powerful platform for scientific instruments. Here, we demonstrate speckle spectroscopy with smartphone-level hardware. This technique promises greater performance thresholds than traditional diffraction gratings. Light is injected into an optical fiber and the emergent speckle patterns are imaged by a reversed-lens smartphone camera. The smartphone then uses an algorithm, running on a mobile computing app, to determine, in less than one second, the (hitherto unknown) input spectrum. We reconstruct a variety of visible-wavelength (470-670 nm) single and multi-peaked spectra using a tunable source. The latter also include a metameric pair, i.e., two spectra that are different, yet represent colors that are indistinguishable to the human eye.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.

Analytical Chemistry: Tasks, Resolutions and Future Standpoints of the Quantitative Analyses of Environmental Complex Sample Matrices

Currently, the challenges that analytical chemistry has to face are ever greater and more complex both from the point of view of the selectivity of analytical methods and their sensitivity. This is especially true in quantitative analysis, where various methods must include the development and validation of new materials, strategies, and procedures to meet the growing need for rapid, sensitive, selective, and green methods. In this context, given the International Guidelines, which over time, are updated and which set up increasingly stringent “limits”, constant innovation is required both in the pre-treatment procedures and in the instrumental configurations to obtain reliable, accurate, and reproducible information. In addition, the environmental field certainly represents the greatest challenge, as analytes are often present at trace and ultra-trace levels. These samples containing analytes at ultra-low concentration levels, therefore, require very labor-intensive sample preparation procedures and involve the high consumption of organic solvents that may not be considered “green”. In the literature, in recent years, there has been a strong development of increasingly high-performing sample preparation techniques, often “solvent-free”, as well as the development of hyphenated instrumental configurations that allow for reaching previously unimaginable levels of sensitivity. This review aims to provide an update of the most recent developments currently in use in sample pre-treatment and instrument configurations in the environmental field, also evaluating the role and future developments of analytical chemistry in light of upcoming challenges and new goals yet to be achieved.

Smartphone-Based Quantitative Analysis of Protein Array Signals for Biomarker Detection in Lupus

Fluorescence-based microarray offers great potential in clinical diagnostics due to its high-throughput capability, multiplex capabilities, and requirement for a minimal volume of precious clinical samples. However, the technique relies on expensive and complex imaging systems for the analysis of signals. In the present study, we developed a smartphone-based application to analyze signals from protein microarrays to quantify disease biomarkers. The application adopted Android Studio open platform for its wide access to smartphones, and Python was used to design a graphical user interface with fast data processing. The application provides multiple user functions such as "Read", "Analyze", "Calculate" and "Report". For rapid and accurate results, we used ImageJ, Otsu thresholding, and local thresholding to quantify the fluorescent intensity of spots on the microarray. To verify the efficacy of the application, three antigens each with over 110 fluorescent spots were tested. Particularly, a positive correlation of over 0.97 was achieved when using this analytical tool compared to a standard test for detecting a potential biomarker in lupus nephritis. Collectively, this smartphone application tool shows promise for cheap, efficient, and portable on-site detection in point-of-care diagnostics.

Multi-Mode Compact Microscopy for High-Contrast and High-Resolution Imaging

We report a multi-mode compact microscope (MCM) for high-contrast and high-resolution imaging. The MCM consists of two LED illuminations, a magnification lens, a lift stage, and a housing with image processing and LED control boards. The MCM allows multi-modal imaging, including reflection, transmission, and higher magnification modes. The dual illuminations also provide high-contrast imaging of various targets such as biological samples and microcircuits. The high dynamic range (HDR) imaging reconstruction of MCM increases the dynamic range of the acquired images by 1.36 times. The microlens array (MLA)-assisted MCM also improves image resolution through the magnified virtual image of MLA. The MLA-assisted MCM successfully provides a clear, magnified image by integrating a pinhole mask to prevent image overlap without additional alignment. The magnification of MLA-assisted MCM was increased by 3.92 times compared with that of MCM, and the higher magnification mode demonstrates the image resolution of 2.46 μm. The compact portable microscope can provide a new platform for defect inspection or disease detection on site.

Quantitative pH Determination Based on the Dominant Wavelength Analysis of Commercial Test Strips

The determination of pH values is essential in many chemical, medical, and environmental monitoring processes, which has been relying on conventional pH meters (glass electrodes) for quantitation and pH test strips for qualitative (or semi-quantitative) assessment. In this work, we demonstrate a smartphone-based pH determination technique, which performs digital image analysis of commercial test strips, particularly the determination of either the dominant wavelength (λ_d) or complementary wavelength (λ_c) of the color image. In conjunction with a 3D-printed optical accessory (with a surface light source and a macro lens), the quality of captured images have been warranted, and the quantitation accuracy of 0.05 pH units has been achieved. More importantly, the performance of this smartphone-based pH reading system (namely "Smart-pH-Reader") was validated using multiple real-world samples, as the results are consistent with those determined with a standard pH meter. The Smart-pH-Reader is envisioned to be a simple, portable, and accurate tool for pH determination in the fields of environmental monitoring, medical diagnosis, and beyond.

How 3D printing can boost advances in analytical and bioanalytical chemistry

3D printing fabrication methods have received lately an enormous attention by the scientific community. Laboratories and research groups working on analytical chemistry applications, among others, have advantageously adopted 3D printing to fabricate a wide range of tools, from common laboratory hardware to fluidic systems, sample treatment platforms, sensing structures, and complete fully functional analytical devices. This technology is becoming more affordable over time and therefore preferred over the commonly used fabrication processes like hot embossing, soft lithography, injection molding and micromilling. However, to better exploit 3D printing fabrication methods, it is important to fully understand their benefits and limitations which are also directly associated to the properties of the materials used for printing. Costs, printing resolution, chemical and biological compatibility of the materials, design complexity, robustness of the printed object, and integration with commercially available systems represent important aspects to be weighted in relation to the intended task. In this review, a useful introductory summary of the most commonly used 3D printing systems and mechanisms is provided before the description of the most recent trends of the use of 3D printing for analytical and bioanalytical chemistry. Concluding remarks will be also given together with a brief discussion of possible future directions.

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.

Smartphone-based optical analysis systems

During the past few decades, there has been a growing trend towards the use of smartphone-based analysis systems. This is mainly due to its ubiquity, its increasing computing capacity, its relatively low cost and the ability to acquire and process data at the same time. Furthermore, there are many sensors integrated into a smartphone, for example a complementary metal-oxide semiconductor (CMOS) sensor. A CMOS sensor enables optical analysis for example by using it as a colorimeter, photometer or spectrometer. This review explores the current state-of-the-art smartphone-based optical analysis systems in various areas of application. It is organized into three sections, each of which investigates one class of smartphone-based devices: (i) smartphone-based colorimeters (ii) smartphone-based photo- and spectrometers and (iii) smartphone-based fluorimeters.

Smartphone biosensor for point-of-need chemiluminescence detection of ochratoxin A in wine and coffee

Exposure to mycotoxins, which may contaminate food and feed commodities, represents a serious health risk for consumers. Ochratoxin A (OTA) is one of the most abundant and toxic mycotoxins, thus specific regulations for fixing its maximum admissible levels in foodstuff have been established. Lateral Flow ImmunoAssay (LFIA)-based devices have been proposed as screening tools to avoid OTA contamination along the whole food chain. We report a portable, user-friendly smartphone-based biosensor for the detection and quantification of OTA in wine and instant coffee, which combines the LFIA approach with chemiluminescence (CL) detection. The device employs the smartphone camera as a light detector and uses low-cost, disposable analytical cartridges containing the LFIA strip and all the necessary reagents. The analysis can be carried out at the point of need by non-specialized operators through simple manual operations. The biosensor allows OTA quantitative detection in wine and coffee samples up to 25 μg L^-1 and with limits of detection of 0.3 and 0.1 μg L^-1, respectively, which are below the European law-fixed limits. These results demonstrate that the developed device can be used for routine monitoring of OTA contamination, enabling rapid and reliable identification of positive samples requiring confirmatory analysis.

A Portable Smartphone-based Platform with an Offline Image-processing Tool for the Rapid Paper-based Colorimetric Detection of Glucose in Artificial Saliva

In this study, a microfluidic paper-based analytical device (μPAD) was integrated with a smartphone app capable of offline (without internet access) image processing and analysis for the rapid colorimetric detection of glucose. A self-inking stamp was used to form hydrophobic channels on a piece of paper-towel due to its superior water absorption efficiency. As demonstrated, the developed sensor was employed for the colorimetric detection of glucose in artificial saliva in the linear scope of 0 - 1 mM with a calculated detection limit of 29.65 μM. The experimental results show that the quantitative analysis of glucose with the proposed smartphone platform could be completed in less than one minute. The app developed for the smartphone platform is capable of extracting the color-changing area with an embedded image processing tool which could address the problem of color uniformity in the detection zones of μPAD. The integrated platform has great potential to be used for non-invasive measurements of glucose in body fluids, like tears, sweat and saliva.

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.

A novel vertical flow assay for point of care measurement of iron from whole blood

Disorders in iron metabolism are endemic globally, affecting more than several hundred million individuals and often resulting in increased rates of mortality or general deterioration of quality of life. To both prevent and monitor treatment of iron related disorders, we present a point of care medical device which leverages a simple smartphone camera to measure total iron concentration from a finger-prick sample. The system consists of a smartphone and an in-house developed app, a 3D printed sensing chamber and a vertical flow membrane-based sensor strip designed to accommodate 50 μl of whole blood, filter out the cellular components and carry out a colorimetric chelation reaction producing a colour change which is detected by our smartphone device. The app's accuracy and precision were assessed via comparison of the mobile app's RGB output to a reference imaging software, ImageJ for the same colorimetric sensing strip. Correlation plots resulted in slopes of 0.99 and coefficient of determination (R² = 0.99). The device was determined to have a signal to noise ratio >40 and a mean bias of 2% which both indicate high analytical accuracy and precision (in terms of RGB measurement). The smartphone device's iron concentration readout was then studied using an extensively validated laboratory developed test (LDT) for iron detection, which is an optimized spectrophotometry-based technique (this is considered the gold standard for iron quantification among LDTs). In comparison of the smartphone-based technique with the gold standard LDT, a calibration slope of 0.0004 au μg^-1 dL^-1, a correlation plot with slope of 1.09 and coefficient of determination (R²) of 0.96 and a mean bias of 5.3%, our device can accurately measure iron levels in blood. With detection times of five minutes, fingerpick sample and sensor cost less than 10 cents, the device shows great promise in being developed as the first ever commercial device for iron quantification in blood.

Fabrication of a Smartphone-Based Spectrophotometer and Its Application in Monitoring Concentrations of Organic Dyes

In this study, an in-house constructed paper-based spectrophotometer is presented and demonstrated for detecting three organic dyes, namely, methylene blue, malachite green, and rhodamine B, and monitoring the efficiency of their removal from a wastewater sample with Sistan sand as a costless adsorbent. The compact design and light weight of this simple spectrophotometer delivered portability, with materials costing less than a dollar. Spectral analysis of the captured images was performed using free downloadable software from the Google Play store. The main experimental parameters affecting the efficiency of dye adsorption including pH, sorbent dosage, initial dye concentration, and contact time were investigated and optimized using the Taguchi design experimental method. Validation experiments were performed using a standard commercial bench-top spectrophotometer, and results were compared in terms of analytical performance, speed, and cost of analysis. The smartphone-based spectrometer was able to measure accurately, as confirmed using the commercial spectrometer, with enhanced sensitivity for methylene blue and rhodamine B. The combination of the high spectral accuracy of the paper-based spectrophotometer, together with sand as a readily accessible sorbent, enabled us to develop a powerful yet simple approach and tool for the removal and monitoring of dyes within wastewater samples, which is potentially available to everybody who owns a smartphone.

Microengineered poly(HEMA) hydrogels for wearable contact lens biosensing

Microchannels in hydrogels play an essential role in enabling a smart contact lens. However, microchannels have rarely been created in commercial hydrogel contact lenses due to their sensitivity to conventional microfabrication techniques. Here, we report the fabrication of microchannels in poly(2-hydroxyethyl methacrylate) (poly(HEMA)) hydrogels that are used in commercial contact lenses with a three-dimensional (3D) printed mold. We investigated the corresponding capillary flow behaviors in these microchannels. We observed different capillary flow regimes in these microchannels, depending on their hydration level. In particular, we found that a peristaltic pressure could reinstate flow in a dehydrated channel, indicating that the motion of eye-blinking may help tears flow in a microchannel-containing contact lens. Colorimetric pH and electrochemical Na+ sensing capabilities were demonstrated in these microchannels. This work paves the way for the development of microengineered poly(HEMA) hydrogels for various biomedical applications such as eye-care and wearable biosensing.

Application of smartphone-based spectroscopy to biosample analysis: A review

The emergence of the smartphones has brought extensive changes to our lifestyles, from communicating with one another, to shopping and enjoyment of entertainment, and from studying to functioning at the workplace (and in the field). At the same time, this portable device has also provided new possibilities in scientific research and applications. Based on the growing awareness of good health management, researchers have coupled health monitoring to smartphone sensing technologies. Along the way, there have been developed a variety of smartphone-based optical detection platforms for analyzing biological samples, including standalone smartphone units and integrated smartphone sensing systems. In this review, we outline the applications of smartphone-based optical sensors for biosamples. These applications focus mainly on three aspects: Microscopic imaging sensing, colorimetric sensing and luminescence sensing. We also discuss briefly some limitations of the current state of smartphone-based spectroscopy and present prospects of the future applicability of smartphone sensors.

A smartphone microscopic method for simultaneous detection of (oo)cysts of Cryptosporidium and Giardia

Background

Food and water-borne illness caused by ingestion of (oo)cysts of Cryptosporidium and Giardia is one of the major health problems globally. Several methods are available to detect Giardia cyst and Cryptosporidium oocyst in food and water. Most of the available methods require a good laboratory facility and well-trained manpower and are therefore costly. There is a need of affordable and reliable method that can be easily implemented in resource limited settings.

Methodology/Principle findings

We developed a smartphone based microscopic assay method to screen (oo)cysts of Cryptosporidium and Giardia contamination of vegetable and water samples. The method consisting of a ball lens of 1 mm diameter, white LED as illumination source and Lugols's iodine staining provided magnification and contrast capable of distinguishing (oo)cysts of Cryptosporidium and Giardia. The analytical performance of the method was tested by spike recovery experiments. The spike recovery experiments performed on cabbage, carrot, cucumber, radish, tomatoes, and water resulted in 26.8±10.3, 40.1±8.5, 44.4±7.3, 47.6±11.3, 49.2 ±10.9, and 30.2±7.9% recovery for Cryptosporidium, respectively and 10.2±4.0, 14.1±7.3, 24.2±12.1, 23.2±13.7, 17.1±13.9, and 37.6±2.4% recovery for Giardia, respectively. The spike recovery results are comparable with data obtained using commercial brightfield and fluorescence microscope methods. Finally, we tested the smartphone microscope system for detecting (oo)cysts on 7 types of vegetable (n = 196) and river water (n = 18) samples. Forty-two percent vegetable and thirty-nine percent water samples were found to be contaminated with Cryptosporidium oocyst. Similarly, thirty-one percent vegetable and thirty-three percent water samples were contaminated with Giardia cyst.

Conclusions

The newly developed smartphone microscopic method showed comparable performance to commercial microscopic methods. The new method can be a low-cost and easy to implement alternative method for simultaneous detection of (oo)cysts in vegetable and water samples in resource limited settings.

Food and water-borne illness arising from the consumption of contaminated food and water are serious health hazards globally. Cryptosporidium and Giardia are the major food and water‒borne parasites. The infection occurs mainly by (oo)cyst phase of the parasites. People in developing countries are more vulnerable to these parasites where infection is more likely underdiagnosed and underreported due to limited resources for detection. There is need of a method that is affordable and easy to implement. In this study, we developed and optimized a novel smartphone microscope method that can detect and quantify the (oo)cyst of the parasites in food and water samples. The developed method is easy to implement and affordable and provides similar performance to the other commercially available microscopic methods.

Precision medicine, bioanalytics and nanomaterials: toward a new generation of personalized portable diagnostics

The customization of disease treatment focused on genetic, environmental and lifestyle factors of individual patients, including tailored medical decisions and treatments, is identified as precision medicine. This approach involves the combination of various aspects such as the collection and processing of a large amount of data, the selection of optimized and personalized drug dosage for each patient and the development of selective and reliable analytical tools for the monitoring of clinical, genetic and environmental parameters. In this context, miniaturized, compact and ultrasensitive bioanalytical devices play a crucial role for achieving the goals of personalized medicine. In this review, the latest analytical technologies suitable for providing portable and easy-to-use diagnostic tools in clinical settings will be discussed, highlighting new opportunities arising from nanotechnologies, offering peculiar perspectives and opportunities for precision medicine.

The role of mobile health technologies in allergy care: An EAACI position paper

Mobile health (mHealth) uses mobile communication devices such as smartphones and tablet computers to support and improve health-related services, data and information flow, patient self-management, surveillance, and disease management from the moment of first diagnosis to an optimized treatment. The European Academy of Allergy and Clinical Immunology created a task force to assess the state of the art and future potential of mHealth in allergology. The task force endorsed the "Be He@lthy, Be Mobile" WHO initiative and debated the quality, usability, efficiency, advantages, limitations, and risks of mobile solutions for allergic diseases. The results are summarized in this position paper, analyzing also the regulatory background with regard to the "General Data Protection Regulation" and Medical Directives of the European Community. The task force assessed the design, user engagement, content, potential of inducing behavioral change, credibility/accountability, and privacy policies of mHealth products. The perspectives of healthcare professionals and allergic patients are discussed, underlining the need of thorough investigation for an effective design of mHealth technologies as auxiliary tools to improve quality of care. Within the context of precision medicine, these could facilitate the change in perspective from clinician- to patient-centered care. The current and future potential of mHealth is then examined for specific areas of allergology, including allergic rhinitis, aerobiology, allergen immunotherapy, asthma, dermatological diseases, food allergies, anaphylaxis, insect venom, and drug allergy. The impact of mobile technologies and associated big data sets are outlined. Facts and recommendations for future mHealth initiatives within EAACI are listed.

Recent advances in high-sensitivity detection methods for paper-based lateral-flow assay

Paper-based lateral-flow assays (LFAs) have achieved considerable commercial success and continue to have a significant impact on medical diagnostics and environmental monitoring. Conventional LFAs are typically performed by examining the color changes in the test bands by naked eye. However, for critical biochemical markers that are present in extremely small amounts in the clinical specimens, this readout method is not quantitative, and does not provide sufficient sensitivity or suitable detection limit for a reliable assay. Diverse technologies for high-sensitivity LFA detection have been developed and commercialization efforts are underway. In this review, we aim to provide a critical and objective overview of the recent progress in high-sensitivity LFA detection technologies, which involve the exploitation of the physical and chemical responses of transducing particles. The features and biomedical applications of the technologies, along with future prospects and challenges, are also discussed.

A Critical Comparison between Flow-through and Lateral Flow Immunoassay Formats for Visual and Smartphone-Based Multiplex Allergen Detection

(1) Background: The lack of globally standardized allergen labeling legislation necessitates consumer-focused multiplexed testing devices. These should be easy to operate, fast, sensitive and robust. (2) Methods: Herein, we describe the development of three different formats for multiplexed food allergen detection, namely active and passive flow-through assays, and lateral flow immunoassays with different test line configurations. (3) Results: The fastest assay time was 1 min, whereas even the slowest assay was within 10 min. With the passive flow approach, the limits of detection (LOD) of 0.1 and 0.5 ppm for total hazelnut protein (THP) and total peanut protein (TPP) in spiked buffer were reached, or 1 and 5 ppm of THP and TPP spiked into matrix. In comparison, the active flow approach reached LODs of 0.05 ppm for both analytes in buffer and 0.5 and 1 ppm of THP and TPP spiked into matrix. The optimized LFIA configuration reached LODs of 0.1 and 0.5 ppm of THP and TPP spiked into buffer or 0.5 ppm for both analytes spiked into matrix. The optimized LFIA was validated by testing in 20 different blank and spiked matrices. Using device-independent color space for smartphone analysis, two different smartphone models were used for the analysis of optimized assays.

Web-drive based source measure unit for automated evaluations of ionic liquid-gated MoS2 transistors

For reliable characterization of two-dimensional semiconducting devices and continuous monitoring in toxic environments, construction of an electrical characterization-based massive database using a portable source measure unit (SMU) with a WiFi connection is desirable. The web-drive based SMU using a microcontroller developed here exhibits superior voltage source performance (∼1 mV) and voltage/current measurement (∼0.15 mV/∼1 nA) capabilities, with automatic construction of a measurement database for online storage using web-drive based software, which can be applied for reliable electrical characterization. Electrical characterization of ionic liquid-gated MoS₂ transistors was achieved with the designed SMU and showed results comparable with those obtained using a commercial semiconductor characterization system. Ionic liquid-gated transistors only require a small gate bias (∼1.5 V) for on-state operation because of the high gate capacitance originating from the thin dielectric layer constructed of an electrical double layer, which makes the device a promising candidate for low power consumption applications. Finally, several electrical parameters of the ionic liquid-gated transistor were extracted from the datasets and uploaded to the web-drive.

Smartphone-integrated urinary CTX-II immunosensor based on wavelength filtering from chromogenic reaction

The integration of smart IT devices and biochemical assays with optical biosensing technology facilitates the development of efficacious optical biosensors for many practical diagnostic fields, owing to their minimized use of high-technical electronic components and simple operation. Herein, we introduced a simple optical biosensing system based on the specific wavelength filtering principle and count-based analysis method. The developed system uses a smartphone with a paper-based signal guide and a biosensing channel. The paper-based signal guide was prepared by printing red patterns of various brightness on a black background. Given that a blue product is generated as a result of horseradish peroxidase (HRP)-based enzymatic reaction in the biosensing channel, the channel could be used as a blue filter that absorbs red light. When red light reflected from the red pattern is absorbed by the channel, the pattern appears black. As such, the color of the patterns is assimilated with the black background, so it seems to disappear. Consequently, the amount of blue product relative to the concentration of the target analyte can be measured by counting the number of observed patterns on the paper-based signal guide. In this study, the concentration of urinary C-telopeptide fragment of type II collagen (uCTX-II, 0-10 ng/mL) was measured using the developed system without complicated equipment. In addition, the quantitative analysis of uCTX-II in the real urine sample was successfully performed. Therefore, we expect that the developed optical transducing system could be practically used for point-of-care testing (POCT) diagnosis under resource-limited environmental conditions.

The Efficiency of Color Space Channels to Quantify Color and Color Intensity Change in Liquids, pH Strips, and Lateral Flow Assays with Smartphones

Bottom-up, end-user based feed, and food analysis through smartphone quantification of lateral flow assays (LFA) has the potential to cause a paradigm shift in testing capabilities. However, most developed devices do not test the presence of and implications of inter-phone variation. Much discussion remains regarding optimum color space for smartphone colorimetric analyses and, an in-depth comparison of color space performance is missing. Moreover, a light-shielding box is often used to avoid variations caused by background illumination while the use of such a bulky add-on may be avoidable through image background correction. Here, quantification performance of individual channels of RGB, HSV, and LAB color space and ΔRGB was determined for color and color intensity variation using pH strips, filter paper with dropped nanoparticles, and colored solutions. LAB and HSV color space channels never outperformed the best RGB channels in any test. Background correction avoided measurement variation if no direct sunlight was used and functioned more efficiently outside a light-shielding box (prediction errors < 5%/35% for color/color intensity change). The system was validated using various phones for quantification of major allergens (i.e., gluten in buffer, bovine milk in goat milk and goat cheese), and, pH in soil extracts with commercial pH strips and LFA. Inter-phone variation was significant for LFA quantification but low using pH strips (prediction errors < 10% for all six phones compared). Thus, assays based on color change hold the strongest promise for end-user adapted smartphone diagnostics.

Spectrophotometric system based on a device created by 3D printing for the accommodation of a webcam chamber as a detection system

The development of a simple and economical spectrophotometric system based on the use of a device created by 3D printing and the electronics necessary to control the intensity of the radiation source was described. The measurements are made with a low-cost digital webcam. The entire system is only powered through the USB outputs of a computer, which makes the portable and really practical system for the measurements in the field. This method was applied to determine iron (II) in waters using o-phenanthroline as chromogenic reagent giving a red complex, and also to hypochlorite determination using tetramethylbenzidine as the reagent providing a yellow color. The calibration curves were built using a mathematical algorithm making a RGB deconvolution. The intense of colors obtained from a webcam in each concentration of analyte had a relationship with the absorbance values. In order to confirm the accuracy and precision of this method, a traditional spectrophotometer was used for validation.

Towards Lateral Flow Quantitative Assays: Detection Approaches

Point-of-care (POC) or bedside analysis is a global trend in modern diagnostics. Progress in POC testing has largely been provided by advanced manufacturing technology for lateral flow (immunochromatographic) test strips. They are widely used to rapidly and easily control a variety of biomarkers of infectious diseases and metabolic and functional disorders, as well as in consumer protection and environmental monitoring. However, traditional lateral flow tests rely on visual assessment and qualitative conclusion, which limit the objectivity and information output of the assays. Therefore, there is a need for approaches that retain the advantages of lateral flow assays and provide reliable quantitative information about the content of a target compound in a sample mixture. This review describes the main options for detecting, processing, and interpreting immunochromatographic analysis results. The possibilities of modern portable detectors that register colored, fluorescent, magnetic, and conductive labels are discussed. Prospects for further development in this direction are also examined.

Accessory-free quantitative smartphone imaging of colorimetric paper-based assays

The combination of smartphone technology and colorimetric paper-based microfluidics can enable simple, inexpensive diagnostics. However, imaging colorimetric diagnostic results via smartphones currently requires accessories to mitigate the influence of variability in surrounding lighting conditions. Here, we present an accessory-free smartphone-based colorimetric imaging method that enlists the built-in LED light source to dominate ambient lighting in combination with background and colour rescaling. This simple approach enables quantitative measurements from paper-based tests by compensating for different environmental lighting conditions and is universally applicable with respect to phone models and manufacturers. We demonstrate the method with three dominant phone makes and models in a cell counting application with a paper-based yeast detection device. The detection results are in good agreement with cell counting using automated cell counters. Eliminating the need for make/model specific accessories, this approach helps realize the potential for low-cost, broadly applicable paper-based diagnostics.

Filipe CD, Didar TF. Intelligent Food Packaging: A Review of Smart Sensing Technologies for Monitoring Food Quality

Food safety is a major factor affecting public health and the well-being of society. A possible solution to control food-borne illnesses is through real-time monitoring of the food quality throughout the food supply chain. The development of emerging technologies, such as active and intelligent packaging, has been greatly accelerated in recent years, with a focus on informing consumers about food quality. Advances in the fields of sensors and biosensors has enabled the development of new materials, devices, and multifunctional sensing systems to monitor the quality of food. In this Review, we place the focus on an in-depth summary of the recent technological advances that hold the potential for being incorporated into food packaging to ensure food quality, safety, or monitoring of spoilage. These advanced sensing systems usually target monitoring gas production, humidity, temperature, and microorganisms' growth within packaged food. The implementation of portable and simple-to-use hand-held devices is also discussed in this Review. We highlight the mechanical and optical properties of current materials and systems, along with various limitations associated with each device. The technologies discussed here hold great potential for applications in food packaging and bring us one step closer to enable real-time monitoring of food throughout the supply chain.

Detection platforms for point-of-care testing based on colorimetric, luminescent and magnetic assays: A review

Along with the considerable potential and increasing demand of the point-of-care testing (POCT), corresponding detection platforms have attracted great interest in both academic and practical fields. The first few generations of conventional detection devices tend to be costly, complicated to operate and hard to move on account of early limitations in the level of technological development and relatively high requirement of performance. Owing to the requirements for rapidity, simplicity, accuracy and cost controlling in the POCT, reader systems are urgently needed to be developed, upgraded and modified constantly, realizing on-site testing and healthcare management without a specific place or cumbersome operation. Accordingly, numerous rapid detection platforms with diverse size and performance have emerged such as bench-top apparatuses, handheld devices and intelligent detection devices. This review discusses various devices developed mainly for the detection of lateral flow test strips (LFTSs) or microfluidic strips in the POCT and summarizes these devices by size and portability. Furthermore, on the basis of various detection methods and diverse probes usually containing specific nanoparticles composites, three most common aspects of detection rationale in the POCT are selected to elaborate each kind of detection platforms in this paper: colorimetric assay, luminescent detection and magnetic signal detection. Herein, we focus on their structures, detection mechanisms and assay results, accompany with discussions and comments on the performances, costs and potential application, as well as advantages and limitations of each technique. In addition, perspectives on the future advances of detection platforms and some conclusions are proposed.

Using Colour Images for Online Yeast Growth Estimation

Automatisation and digitalisation of laboratory processes require adequate online measurement techniques. In this paper, we present affordable and simple means for non-invasive measurement of biomass concentrations during cultivation in shake flasks. Specifically, we investigate the following research questions. Can images of shake flasks and their content acquired with smartphone cameras be used to estimate biomass concentrations? Can machine vision be used to robustly determine the region of interest in the images such that the process can be automated? To answer these questions, 18 experiments were performed and more than 340 measurements taken. The relevant region in the images was selected automatically using K-means clustering. Statistical analysis shows high fidelity of the resulting model predictions of optical density values that were based on the information embedded in colour changes of the automatically selected region in the images.