Smartphone-Enabled Paper-Based Hemoglobin Sensor for Extreme Point-of-Care Diagnostics

One-step copper deposition-induced signal amplification for multiplex bacterial infection diagnosis on a lateral flow immunoassay device

The lateral flow immunoassay (LFIA) is predominant in rapid diagnostic tests owing to its cost-effectiveness and operational simplicity. However, the conventional LFIA exhibits limited sensitivity and is susceptible to human variance for the result readout, impacting result interpretation. In this study, we introduced a novel one-step copper deposition-induced signal amplification lateral flow immunoassay (osa-LFIA) that markedly enhances the detection sensitivity for Staphylococcus aureus (protein A) and Pseudomonas aeruginosa (exotoxin A). Utilizing gold nanoparticles (AuNPs) as a catalyst, this approach employs ascorbic acid to reduce Cu2+ to Cu0, depositing on AuNPs at the test line and amplifying the signal. A user-friendly design features a three-dimensional paper structure incorporating pre-dried reagents, enabling a streamlined, efficient testing process. The osa-LFIA significantly lowers detection limits to 3 ng mL-1 for protein A and 10 ng mL-1 for exotoxin A, offering a tenfold improvement over conventional LFIA. Additionally, we developed a portable grayscale detection device, achieving less than 10% error in quantitative analysis compared to the data acquired and analyzed in the lab. This entire process, from detection to signal amplification, is completed in just 20 min. For the clinical trial, we utilized the osa-LFIA to test synovial fluid samples infected with Staphylococcus aureus. We also successfully detected different concentrations of the exotoxin A in parallel, with a recovery value of 96%-110%. Our findings demonstrate the osa-LFIA's potential as a rapid, highly sensitive, and simple-to-use diagnostic tool for detecting various pathogens, significantly advancing the field of rapid diagnostic testing.

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.

Recent advancements of smartphone-based sensing technology for diagnosis, food safety analysis, and environmental monitoring

The emergence of computationally powerful smartphones, relatively affordable high-resolution camera, drones, and robotic sensors have ushered in a new age of advanced sensible monitoring tools. The present review article investigates the burgeoning smartphone-based sensing paradigms, including surface plasmon resonance (SPR) biosensors, electrochemical biosensors, colorimetric biosensors, and other innovations for modern healthcare. Despite the significant advancements, there are still scarcity of commercially available smart biosensors and hence need to accelerate the rates of technology transfer, application, and user acceptability. The application/necessity of smartphone-based biosensors for Point of Care (POC) testing, such as prognosis, self-diagnosis, monitoring, and treatment selection, have brought remarkable innovations which eventually eliminate sample transportation, sample processing time, and result in rapid findings. Additionally, it articulates recent advances in various smartphone-based multiplexed bio sensors as affordable and portable sensing platforms for point-of-care devices, together with statistics for point-of-care health monitoring and their prospective commercial viability.

Asparagus officinalis Herb-Derived Carbon Quantum Dots: Luminescent Probe for Medical Diagnostics

The utilization of natural materials for the synthesis of highly fluorescent carbon quantum dots (CQDs) presents a sustainable approach to overcome the challenges associated with traditional chemical precursors. Here, we report the synthesis of novel S,N-self-doped CQDs (S,N@CQDs) derived from asparagus officinalis herb. These S,N@CQDs exhibit 16.7 % fluorescence quantum yield, demonstrating their potential in medical diagnostics. We demonstrate the efficacy of S,N@CQDs as luminescent probes for the detection of anti-pathogenic medications metronidazole (MTZ) and nitazoxanide (NTZ) over concentration ranges of 0.0-180.0 μM (with a limit of detection (LOD) of 0.064 μM) and 0.25-40.0 μM (LOD of 0.05 μM), respectively. The probes were successfully applied to determine MTZ and NTZ in medicinal samples, real samples, and spiked human plasma, with excellent recovery rates ranging from 99.82 % to 103.03 %. Additionally, S,N@CQDs demonstrate exceptional efficacy as diagnostic luminescent probes for hemoglobin (Hb) detection over a concentration range of 0-900 nM, with a minimal detectability of 9.24 nM, comparable to commercially available medical laboratory diagnostic tests. The eco-friendly synthesis and precise detection limits of S,N@CQDs meet necessary analytical requirements and hold promise for advancing diagnostic capabilities in clinical settings. This research signifies a significant step towards sustainable and efficient fluorescence-based medical diagnostics.

Smartphone-Based Techniques Using Carbon Dot Nanomaterials for Food Safety Analysis

The development of portable and efficient nanoprobes to realize the quantitative/qualitative onsite determination of food pollutants is of immense importance for safeguarding human health and food safety. With the advent of the smartphone, the digital imaging property causes it to be an ideal diagnostic substrate to point-of-care analysis probes. Besides, merging the versatility of carbon dots nanostructures and bioreceptor abilities has opened an innovative assortment of construction blocks to design advanced nanoprobes or improving those existing ones. On this ground, massive endeavors have been made to combine mobile phones with smart nanomaterials to produce portable (bio)sensors in a reliable, low cost, rapid, and even facile-to-implement area with inadequate resources. Herein, this work outlines the latest advancement of carbon dots nanostructures on smartphone for onsite detecting of agri-food pollutants. Particularly, we afford a summary of numerous approaches applied for target molecule diagnosis (pesticides, mycotoxins, pathogens, antibiotics, and metal ions), for instance microscopic imaging, fluorescence, colorimetric, and electrochemical techniques. Authors tried to list those scaffolds that are well-recognized in complex media or those using novel constructions/techniques. Lastly, we also point out some challenges and appealing prospects related to the enhancement of high-efficiency smartphone based carbon dots systems.

Quantification of Glycated Hemoglobin in Total Hemoglobin by a Simultaneous Dual-Signal Acquisition Approach

The glycated hemoglobin (HbA1c) level, which is defined as the ratio of HbA1c to total hemoglobin (tHb, including glycated and unglycated hemoglobin), is considered one of the preferred indicators for diabetes monitoring. Generally, assessment of the HbA1c level requires separate determination of tHb and HbA1c concentrations after a complex separation step. This undoubtedly increases the cost of the assay, and the loss or degradation of HbA1c during the separation process results in a decrease in the accuracy of the assay. Therefore, this study explored a dual-signal acquisition method for the one-step simultaneous evaluation of tHb and HbA1c. Quantification of tHb: graphene adsorbed carbon quantum dots and methylene blue were utilized as the substrate material and linked to the antibody. tHb was captured on the substrate by the antibody. The unique heme group on tHb catalyzed the production of •OH from H2O2 to degrade methylene blue on the substrate, and a quantitative relationship between the tHb concentration and the methylene blue oxidation current signal was constructed. Quantification of HbA1c: complex labels with HbA1c recognition were made of ZIF-8-ferrocene-gold nanoparticles-mercaptophenylboronic acid. The specific recognition of the boronic acid bond with the unique cis-diol structure of HbA1c establishes a quantitative relationship between the oxidation current of the label-loaded ferrocene and the concentration of HbA1c. Thus, the HbA1c level can be assessed with only one signal readout. The sensor exhibited extensive detection ranges (0.200-600 ng/mL for tHb and 0.100-300 ng/mL for HbA1c) and low detection limits (4.00 × 10-3 ng/mL for tHb and 1.03 × 10-2 ng/mL for HbA1c).

Microfluidics-Based Blood Typing Devices: An In-Depth Overview

Identification of correct blood types holds paramount importance in understanding the pathophysiological parameters of patients, therapeutic interventions, and blood transfusion. Considering the wide applications of blood typing, the requirement of centralized laboratory facilities is not well suited on many occasions. In this context, there has been a significant development of such blood typing devices on different microfluidic platforms. The advantages of these microfluidic devices offer easy, rapid test protocols, which could potentially be adapted in resource-limited settings and thereby can truly lead to the decentralization of testing facilities. The advantages of pump-free liquid transport (i.e., low power consumption) and biodegradability of paper substrates (e.g., reduction in medical wastes) make it a more preferred platform in comparison to other microfluidic devices. However, these devices are often coupled with some inherent challenges, which limit their potential to be used on a mass commercial scale. In this context, our Review offers a succinct summary of the recent development, especially to understand the importance of underlying facets for long-term sustainability. Our Review also delineates the role of integration with digital technologies to minimize errors in interpreting the readouts.

Diagnosis and screening of abnormal hemoglobins

Hemoglobin (Hb) abnormalities, such as thalassemia and structural Hb variants, are among the most prevalent inherited diseases and are associated with significant mortality and morbidity worldwide. However, there were not comprehensive reviews focusing on different clinical analytical techniques, research methods and artificial intelligence (AI) used in clinical screening and research on hemoglobinopathies. Hence the review offers a comprehensive summary of recent advancements and breakthroughs in the detection of aberrant Hbs, research methods and AI uses as well as the present restrictions anddifficulties in hemoglobinopathies. Recent advances in cation exchange high performance liquid chromatography (HPLC), capillary zone electrophoresis (CZE), isoelectric focusing (IEF), flow cytometry, mass spectrometry (MS) and polymerase chain reaction (PCR) etc have allowed for the definitive detection by using advanced AIand portable point of care tests (POCT) integrating with smartphone microscopic classification, machine learning (ML) model, complete blood counts (CBC), imaging-based method, speedy immunoassay, and electrochemical-, microfluidic- and sensing-related platforms. In addition, to confirm and validate unidentified and novel Hbs, highly specialized genetic based techniques like PCR, reverse transcribed (RT)-PCR, DNA microarray, sequencing of genomic DNA, and sequencing of RT-PCR amplified globin cDNA of the gene of interest have been used. Hence, adequate utilization and improvement of available diagnostic and screening technologies are important for the control and management of hemoglobinopathies.

Decorated DNA-Based Scaffolds as Lateral Flow Biosensors

Here we develop Lateral Flow Assays (LFAs) that employ as functional elements DNA-based structures decorated with reporter tags and recognition elements. We have rationally re-engineered tile-based DNA tubular structures that can act as scaffolds and can be decorated with recognition elements of different nature (i.e. antigens, aptamers or proteins) and with orthogonal fluorescent dyes. As a proof-of-principle we have developed sandwich and competitive multiplex lateral flow platforms for the detection of several targets, ranging from small molecules (digoxigenin, Dig and dinitrophenol, DNP), to antibodies (Anti-Dig, Anti-DNP and Anti-MUC1/EGFR bispecific antibodies) and proteins (thrombin). Coupling the advantages of functional DNA-based scaffolds together with the simplicity of LFAs, our approach offers the opportunity to detect a wide range of targets with nanomolar sensitivity and high specificity.

Predictive Framework Development for User-Friendly On-Site Glucose Detection

This study explores a smartphone-based spot detection framework for glucose in a rapid, simple, and affordable paper-based analytical device (PAD), which employs machine-learning algorithms to estimate various glucose concentrations. Herein, two different detection mixtures were chosen with chitosan (C) and without chitosan (WC) for the color change analysis. Being a biopolymer, chitosan improves the analytical performance of PADs when used with a chromogenic agent. Moreover, the influence of the illumination conditions and camera optics on the professed color of glucose strips was observed by choosing various illumination conditions and different smartphones. Hence, this study focuses on developing a framework for smartphone-based simple and user-friendly spot-based glucose detection (with a concentration range of 10-40 mM) at any illumination conditions and in any direction of illumination. Additionally, the combination of color spaces and machine-learning algorithms was applied for the signal enhancement. It was observed that the machine learning classifiers, cubic support vector machine (SVM) and narrow neutral network show higher accuracy for the WC samples, which are 92.7 and 92.3%, respectively. The samples with chitosan show higher accuracy for the linear discriminant and quadratic SVM classifiers, which are 94.1 and 93.9%, respectively. Simultaneously, cubic SVM shows ∼93% accuracy for both cases. In order to assess the performance of the devices, a blind test was also conducted. This study demonstrates the potential of the developed system for initial disease screening at the user end. By incorporating machine learning techniques, the platform can provide reliable and accurate results, thus paving the way for estimating the accuracy of the results for improved initial healthcare screening and diagnosis of any disease.

The NeoRoo mobile app: Initial design and prototyping of an Android-based digital health tool to support Kangaroo Mother Care in low/middle-income countries (LMICs)

Premature birth and neonatal mortality are significant global health challenges, with 15 million premature births annually and an estimated 2.5 million neonatal deaths. Approximately 90% of preterm births occur in low/middle income countries, particularly within the global regions of sub-Saharan Africa and South Asia. Neonatal hypothermia is a common and significant cause of morbidity and mortality among premature and low birth weight infants, particularly in low/middle-income countries where rates of premature delivery are high, and access to health workers, medical commodities, and other resources is limited. Kangaroo Mother Care/Skin-to-Skin care has been shown to significantly reduce the incidence of neonatal hypothermia and improve survival rates among premature infants, but there are significant barriers to its implementation, especially in low/middle-income countries (LMICs). The paper proposes the use of a multidisciplinary approach to develop an integrated mHealth solution to overcome the barriers and challenges to the implementation of Kangaroo Mother Care/Skin-to-skin care (KMC/STS) in LMICs. The innovation is an integrated mHealth platform that features a wearable biomedical device (NeoWarm) and an Android-based mobile application (NeoRoo) with customized user interfaces that are targeted specifically to parents/family stakeholders and healthcare providers, respectively. This publication describes the iterative, human-centered design and participatory development of a high-fidelity prototype of the NeoRoo mobile application. The aim of this study was to design and develop an initial ("A") version of the Android-based NeoRoo mobile app specifically to support the use case of KMC/STS in health facilities in Kenya. Key functions and features are highlighted. The proposed solution leverages the promise of digital health to overcome identified barriers and challenges to the implementation of KMC/STS in LMICs and aims to equip parents and healthcare providers of prematurely born infants with the tools and resources needed to improve the care provided to premature and low birthweight babies. It is hoped that, when implemented and scaled as part of a thoughtful, strategic, cross-disciplinary approach to reduction of global rates of neonatal mortality, NeoRoo will prove to be a useful tool within the toolkit of parents, health workers, and program implementors.

In-situ synthesis of ionic liquid-based-carbon quantum dots as fluorescence probe for hemoglobin detection

Carbon quantum dots (CQDs) have emerged as a potential fluorescent probe in bio/analytical chemistry in the present decade. The optical characteristics of CQDs may be tuned by their functional groups, which can also be used to selectively produce stable bonds with target molecules. Along with them, ionic liquids (ILs) are now demonstrating their important relevance in the field of pharmaceuticals for the creation of potent therapeutics. In the article, we have discussed the use of high fluorescent ILs-decorated-CQDs (CQDs-IM@OTf) as a straightforward and quick-acting fluorescence probe for sensitive and precise hemoglobin (Hb) determination with minimum detectability of 6.7 nM. The proposed mechanism behind this involves static mode of quenching which leads to the formation of a ground state complex [CQDs-IM@OTf-Hb complex] between the Hb protein and the drug. Despite the fact that Hb can quench the fluorescence of CQDs due to the inner filter effect (IFE) of the protein, which effects both the excitation and emission spectra of the CQDs, the addition of H₂O₂ improved the sensitivity of Hb detection. The present assay predicated on Hb interaction with H₂O₂, which produces reactive oxygen species such as hydroxyl (OH^.) and superoxide (O₂^.-) radicals under heme degradation and/or iron release from Hb. The subsequent reaction of hydroxyl radicals with CQDs, which acts as a strong oxidising agent, causes a high fluorescence quenching. The designed fluorescence probe was used to measure Hb in the concentration range of 3-90 nM with a precise detection limit of 0.33 nM. The quantification of hemoglobin (Hb) in diluted human blood samples is done using this observation.

Deep learning-assisted ultra-accurate smartphone testing of paper-based colorimetric ELISA assays

Smartphone has long been considered as one excellent platform for disease screening and diagnosis, especially when combined with microfluidic paper-based analytical devices (μPADs) that feature low cost, ease of use, and pump-free operations. In this paper, we report a deep learning-assisted smartphone platform for ultra-accurate testing of paper-based microfluidic colorimetric enzyme-linked immunosorbent assay (c-ELISA). Different from existing smartphone-based μPAD platforms, whose sensing reliability is suffered from uncontrolled ambient lighting conditions, our platform is able to eliminate those random lighting influences for enhanced sensing accuracy. We first constructed a dataset that contains c-ELISA results (n = 2048) of rabbit IgG as the model target on μPADs under eight controlled lighting conditions. Those images are then used to train four different mainstream deep learning algorithms. By training with these images, the deep learning algorithms can well eliminate the influences of lighting conditions. Among them, the GoogLeNet algorithm gives the highest accuracy (>97%) in quantitative rabbit IgG concentration classification/prediction, which also provides 4% higher area under curve (AUC) value than that of the traditional curve fitting results analysis method. In addition, we fully automate the whole sensing process and achieve the "image in, answer out" to maximize the convenience of the smartphone. A simple and user-friendly smartphone application has been developed that controls the whole process. This newly developed platform further enhances the sensing performance of μPADs for use by laypersons in low-resource areas and can be facilely adapted to the real disease protein biomarkers detection by c-ELISA on μPADs.

The air-gap PAD: a roll-to-roll-compatible fabrication method for paper microfluidics

Paper-based analytical devices (PADs) offer a low-cost, user-friendly platform for rapid point-of-use testing. Without scalable fabrication methods, however, few PADs make it out of the academic laboratory and into the hands of end users. Previously, wax printing was considered an ideal PAD fabrication method, but given that wax printers are no longer commercially available, alternatives are needed. Here, we present one such alternative: the air-gap PAD. Air-gap PADs consist of hydrophilic paper test zones, separated by "air gaps" and affixed to a hydrophobic backing with double-sided adhesive. The primary appeal of this design is its compatibility with roll-to-roll equipment for large-scale manufacturing. In this study, we examine design considerations for air-gap PADs, compare the performance of wax-printed and air-gap PADs, and report on a pilot-scale roll-to-roll production run of air-gap PADs in partnership with a commercial test-strip manufacturer. Air-gap devices performed comparably to their wax-printed counterparts in Washburn flow experiments, a paper-based titration, and a 12-lane pharmaceutical screening device. Using roll-to-roll manufacturing, we produced 2700 feet of air-gap PADs for as little as $0.03 per PAD.

A Plasmonic Fluor-Lightened Microneedle Array Enables Ultrasensitive Multitarget Whole Blood Diagnosis of Anemia in A Paper Origami-Based Device

This work reports a portable, origami-type paper device with a plasmonic fluor-labeled microneedle sensing module for the multiplexed quantification of anemia biomarkers in whole blood. Sequential steps, including serum separation, target enrichment, and multiplexed readout by a gel imager, are rapidly accomplished with the flexible and highly integrated device. The microneedle array enabled efficient sampling of trace targets from ng mL^-1 to pg mL^-1 level. Combined with the plasmonic fluor label, the signal is improved by ≈7.6 folds compared with the flat substrate-based assay. The device is applied to simultaneously quantify hemoglobin (Hb), ferritin, folic acid (FA), and vitamin B₁₂ (VB₁₂ ), which are four anemia biomarkers distributed in different environments with different concentration ranges. Featured by the small sample volume (150 µL), short assay time (20 min), low cost (2 $), robust stability, and user-friendliness, the device is promising for the rapid and accurate diagnosis of anemia in real practice.

Last Trends in Point-of-Care (POC) Diagnostics for the Management of Hematological Indices in Home Care Patients

Today, complete blood count (CBC) analyses are highly automated and allow for high throughput and accurate and reliable results. However, new analytical tools are in great demand to provide simple, rapid and cost-effective management of hematological indices in home care patients. Chronic disease monitoring at home has become a benefit for patients who are finding cost savings in programs designed to monitor/treat patients in offsite locations. This review reports the latest trends in point-of-care (POC) diagnostics useful for home testing of key hematological counts that may be affected during home therapy treatment.

Paper-based optical sensors paired with smartphones for biomedical analysis

The traditional analytical methods used for biomedical analysis are expensive and not easy to handle and require sophisticated instruments, thus their application is limited in resource-limited settings. Due to their portability, low cost, and ability to be applied to different analytical techniques, paper-based analytical devices are becoming valuable tools for biomedical analysis. The integration of smartphones into analytical devices has provided the ability to build portable, cost-effective, straightforward analytical devices for biomedical analysis and mobile health. The key aim of this review is to emphasize the recent applications of PADs combined with a smartphone for the optical analysis of biomedical species. We started this review by highlighting the type of papers and their modifications with different materials to prepare the PADs. After that, this review presents various detection methods including colorimetry, fluorescence, and luminescence where the smartphone is used for read-out. In the end, we provided the recent applications of the analysis of different biomedical compounds such as cancer and cardiovascular biomarkers, metal ions, glucose, viruses, etc. We believe that the present review will attract a wide scientific community in the areas of analytical chemistry, sensors, and clinical testing.

Cellular aggregation dictates universal spreading behaviour of a whole-blood drop on a paper strip

HYPOTHESIS

The complex spreading dynamics of blood on paper matrix is likely to be quantitatively altered with variations in the fractional occupancy of red blood cells in the whole blood (haematocrit). Here, we presented an apparently surprising observation that a finite volume blood drop undergoes a universal time-dependent spreading on a filter paper strip that is virtually invariant with its hematocrit level within physiologically healthy regime, though distinctively distinguishable from the spreading laws of blood plasma and water.

EXPERIMENTS

Our hypothesis was ascertained by performing controlled wicking experiments on filter papers of different grades. Spreading of human blood samples of different haematocrit levels ranging between 15% and 51% and the plasma separated from therein were traced by combined high-speed imaging and microscopy. These experiments were complemented with a semi-analytical theory to decipher the key physics of interest.

RESULTS

Our results unveiled the exclusive influence of the obstructing cellular aggregates in the randomly distributed hierarchically structured porous pathways and deciphered the role of the networked structures of the various plasma proteins that induced hindered diffusion. The resulting universal signatures of spontaneous dynamic spreading, delving centrally on the fractional reduction in the interlaced porous passages, provide novel design basis for paper-microfluidic kits in medical diagnostics and beyond.

Simultaneous quantitative detection of hematocrit and hemoglobin from whole blood using a multiplexed paper sensor with a smartphone interface

We report a highly accurate single-step label-free testing technology for simultaneous and independent hematocrit (Hct) and hemoglobin (Hb) level detection from a drop of whole blood by employing a disposable paper strip sensor interfaced with a portable impedimetric device. The paper strip is fabricated by in situ automated printing of a customized electrode template on the non-glossy side of a commercially available photo paper substrate followed by graphite deposition. The integrated platform device technology additionally includes a compact detection cum readout unit comprising a high precision impedance converter system that combines an on-board frequency generator with an analog-to-digital converter evaluation board, collectively interfaced with a central processor, calibration circuit, and smartphone. Employing a dispensed blood sample volume of 25 μL, the device is shown to have a sensitivity of 92 Ω/Hct and 287 Ω/Hb at an optimal frequency of 57 kHz. The respective linear response regimes appear to be wide enough to cover physiologically relevant limits, with excellent stability and reproducibility. Validation with clinical samples reveals limits of detection of Hct and Hb levels as low as 4.66% and 1.89 g dL^-1, respectively, which are beyond the quantitative capability of commonly used affordable point of care test kits. The envisaged paradigm of rapid, robust, highly accurate, energy-efficient, simple, user-friendly, multiplex portable detection, obviating any possible ambiguities in interpretation due to common artefacts of colorimetric detection technologies such as optical interference with the image analytical procedure due to the inherent redness of blood samples and background illumination, renders this ideal for deployment in resource-limited settings.

Novel Paraquat Detection Strategy Enabled by Carboxylatopillar[5]arene Confined in Nanochannels on a Paper-Based Sensor

Paper-based optical sensors have emerged as a promising technology for pesticide detection and attracted extensive attention. However, in practical analytical applications, it may suffer from limited sensitivity with traditional signal amplification strategies. Here, we developed a novel mesoporous silica-modified paper-based sensor for a sensitive capture and analysis of the pesticide paraquat. Carboxylatopillar[5]arene was covalently introduced into the nanochannels for the rapid capture of target paraquat molecules due to the mass transfer confinement effect within nanopores. In addition, the large specific surface area of mesoporous silica enabled high-abundance immobilization of the capture agent and promoted its binding efficiency, which, in turn, contributed to improving the sensitivity. This work highlights the great potential of nanochannels as a development platform for sensitive paper-based sensors that can be used to develop new systems for the detection of paraquat and even other pesticides.

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors

Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner. However, these sensors present low accuracy in practical use because it is difficult to distinguish color changes for a minute amount of analyte with the naked eye. Herein, we demonstrate that a machine learning (ML)-based paper sensor platform accurately determines the color changes. We fabricated a colorimetric paper sensor by adsorbing polyaniline nanoparticles (PAni-NPs), whose color changes from blue to green when the ambient pH decreases. Adding glucose oxidase (GOx) to the paper sensor enables colorimetric glucose detection. Target analytes (10 μL) were aliquoted onto the paper sensors, and their images were taken with a smartphone under the same conditions in a darkroom. The red-green-blue (RGB) data from the images were extracted and used to train and test three regression models: support vector regression (SVR), decision tree regression (DTR), and random forest regression (RFR). Of the three regression models, RFR performed the best at estimating pH levels (R² = 0.957) ranging from pH 2 to 10 and glucose concentrations (R² = 0.922) ranging from 0 to 10 mg mL^-1.

Instrument-free single-step direct estimation of the plasma glucose level from one drop of blood using smartphone-interfaced analytics on a paper strip

We demonstrated an instrument-free miniaturized adaptation of the laboratory gold standard methodology for the direct estimation of plasma glucose from a drop of whole blood using a low-cost single-user-step paper-strip sensor interfaced with a smartphone. Unlike a majority of the existing glucose meters that use whole blood-based indirect sensing technologies, our direct adaptation of the gold-standard laboratory benchmark could eliminate the possibilities of cross interference with other analytes present in the whole blood by facilitating an in situ plasma separation, capillary flow and colorimetric reaction occurring concomitantly, without incurring additional device complexity or embodiment. The test reagents were dispensed in lyophilized form, and the resulting paper strips were found to be stable over three months stored in a normal freezer, rendering easy adaptability commensurate with the constrained supply chains in extreme resource-poor settings. Quantitative results could be arrived at via a completely-automated mobile-app-based image analytics interface developed using dynamic machine learning, obviating manual interpretation. The tests were demonstrated to be of high efficacy, even when executed by minimally trained frontline personnel having no special skill of drawing precise volume of blood, on deployment at under-resourced community centres having no in-built or accessible healthcare infrastructure. Clinical validation using 220 numbers of human blood samples in a double-blinded manner evidenced sensitivity and specificity of 98.11% and 96.7%, respectively, as compared to the results obtained from a laboratory-benchmarked biochemistry analyser, establishing its efficacy for public health and community disease management in resource-limited settings without any quality compromise of the test outcome.

A Smartphone-Based Biosensor for Non-Invasive Monitoring of Total Hemoglobin Concentration in Humans with High Accuracy

In this paper, we propose a smartphone-based biosensor for detecting human total hemoglobin concentration in vivo with high accuracy. Compared to the existing biosensors used to measure hemoglobin concentration, the smartphone-based sensor utilizes the camera, memory, and computing power of the phone. Thus, the cost is largely reduced. Compared to existing smartphone-based sensors, we developed a highly integrated multi-wavelength LED module and a specially designed phone fixture to reduce spatial errors and motion artifacts, respectively. In addition, we embedded a new algorithm into our smartphone-based sensor to improve the measurement accuracy; an L*a*b* color space transformation and the “a” parameter were used to perform the final quantification. We collected 24 blood samples from normal and anemic populations. The adjusted R² of the prediction results obtained from the multiple linear regression method reached 0.880, and the RMSE reached 9.04, which met the accuracy requirements of non-invasive detection of hemoglobin concentration.

A portable smartphone-based hemoglobin point-of-care testing platform for accurate anemia diagnostics

Anemia affects over 2 billion people worldwide, with the heaviest burden borne by women and children. At present, anemia is diagnosed by measuring hemoglobin (Hb) levels, which must be done in hospitals or commercial laboratories by skilled operators. In this work, we report a portable, affordable ($3), easy-to-operate (1 min) and accurate smartphone-based Hb analyzer (SHbA) that uses a drop of finger-pricked blood for anemia point-of-care test (POCT) applications. POCT of Hb was achieved using a smartphone ambient light sensor (ALS) to accurately measure the absorbance of colorimetric Hb biochemical analysis reagents in a microcuvette, as well as an Android-based application for results analysis. SHbA validation results agreed well with those reported by a hematology analyzer, and the SHbA has an anemia diagnosis sensitivity of 95.4% and specificity of 96.3% for venous blood (n = 360) and a sensitivity of 96.39% and specificity of 95.58% for fingertip blood (n = 475). In addition, SHbA exhibits excellent performance in the diagnosis and treatment guidance of anemia high-risk populations, including tumor chemotherapy patients (n = 424), pregnant women (n = 214) and thalassemia patients (n = 208). Importantly, volunteer self-testing results (n = 20) indicate that SHbA can be used for home-based anemia diagnosis and monitoring. SHbA has the advantages of high sensitivity and specificity while being cheap and easy to operate, making it widely applicable for the diagnosis and treatment of anemia, especially for high-risk patients in areas with poor medical resources.

Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives

INTRODUCTION

Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites.

OBJECTIVES

The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021.

RESULTS

Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures.

CONCLUSION

Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.

Role of Paper-Based Sensors in Fight against Cancer for the Developing World

Cancer is one of the major killers across the globe. According to the WHO, more than 10 million people succumbed to cancer in the year 2020 alone. The early detection of cancer is key to reducing the mortality rate. In low- and medium-income countries, the screening facilities are limited due to a scarcity of resources and equipment. Paper-based microfluidics provide a platform for a low-cost, biodegradable micro-total analysis system (µTAS) that can be used for the detection of critical biomarkers for cancer screening. This work aims to review and provide a perspective on various available paper-based methods for cancer screening. The work includes an overview of paper-based sensors, the analytes that can be detected and the detection, and readout methods used.

Smartphone-Integrated Label-Free Rapid Screening of Anemia from the Pattern Formed by One Drop of Blood on a Wet Paper Strip

Screening of anemic patients poses demanding challenges in extreme point-of-care settings where the gold standard diagnostic technologies are not pragmatic and the alternative point-of-care technologies suffer from compromised accuracy, prohibitive cost, process complexity, or reagent stability issues. As a disruption to this paradigm, here, we report the development of a smartphone-based sensor for rapid screening of anemic patients by exploiting the patterns formed by a spreading drop of blood on a wet paper strip wherein blood attempts to displace a more viscous fluid, on the porous matrix of a paper, leading to "finger-like" projections at the interface. We analyze the topological features of the pattern via smartphone-enabled image analytics and map the same with the relative occupancy of the red blood cells in the blood sample, allowing for label-free screening and classification of blood samples corresponding to moderate to severe anemic conditions. The accuracy of detection is verified by comparing with gold standard reports of hematology analyzer, showing a strong correlation coefficient (R²) of 0.975. This technique is likely to provide a crucial decision-making tool that obviates delicate reagents and skilled technicians for supreme functionality in resource-limited settings.

Nano-Filamented Textile Sensor Platform with High Structure Sensitivity

A key challenge to the creation of chemically responsive electro-functionality of nonconductive, hydrophobic, and free-contacted textile or fibrous network materials is how to impart the 3D structure with functional filaments to enable responsive structure sensitivity, which is critical in establishing the fibrous platform technology for sensor applications. We demonstrate this capability using an electrospun polymeric fibrous substrate embedded with nano-filaments defined by size-tunable gold nanoparticles and structurally sensitive dendrons as crosslinkers. The resulting interparticle properties strongly depend on the assembly of the nano-filaments, enabling an interface with high structure sensitivity to molecular interactions. This is demonstrated with chemiresistive responses to vaporous alcohol molecules with different chain lengths and isomers, which is critical in breath and sweat sensing involving a high-moisture or -humidity background. The sensitivity scales with the chain length and varies with their isomers. This approach harnesses the multifunctional tunability of the nano-filaments in a sensor array format, showing high structure sensitivity to the alcohol molecules with different chain lengths and isomers. The high structure sensitivity and its implications for a paradigm shift in the design of textile sensor arrays for multiplexing human performance monitoring via breath or sweat sensing and environmental monitoring of air quality are also discussed.

Smartphone-Based Biosensor Devices for Healthcare: Technologies, Trends, and Adoption by End-Users

Smart biosensors are becoming an important support for modern healthcare, even more so in the current context. Numerous smartphone-based biosensor developments were published in recent years, some highly effective and sensitive. However, when patents and patent applications related to smart biosensors for healthcare applications are analyzed, it is surprising to note that, after significant growth in the first half of the decade, the number of applications filed has decreased considerably in recent years. There can be many causes of this effect. In this review, we present the state of the art of different types of smartphone-based biosensors, considering their stages of development. In the second part, a critical analysis of the possible reasons why many technologies do not reach the market is presented. Both technical and end-user adoption limitations were addressed. It was observed that smart biosensors on the commercial stage are still scarce despite the great evolution that these technologies have experienced, which shows the need to strengthen the stages of transfer, application, and adoption of technologies by end-users.

A survey of 3D printing technology applied to paper microfluidics

Paper microfluidics is a rapidly growing subfield of microfluidics in which paper-like porous materials are used to create analytical devices that are well-suited for use in field applications. 3D printing technology has the potential to positively affect paper microfluidic device development by enabling tools and methods for the creation of devices with well-defined and tunable fluidic networks of porous matrices for high performance signal generation. This critical review focuses on the progress that has been made in using 3D printing technologies to advance the development of paper microfluidic devices. We describe printing work in three general categories: (i) solid support structures for paper microfluidic device components; (ii) channel barrier definition in existing porous materials; and (iii) porous channels for capillary flow, and discuss their value in advancing paper microfluidic device development. Finally, we discuss major areas of focus for highest impact on the next generation of paper microfluidics devices.

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.