Freeze-Driven Synthesis of DNA Hairpin-Conjugated Gold Nanoparticle Biosensors for Dual-Mode Detection.

Freeze-based immobilization of deoxyribonucleic acid (DNA) oligonucleotides on gold nanoparticles (AuNPs) is highly efficient for single-stranded oligonucleotides but typically does not accommodate structures such as snap-cooled DNA hairpins (Sc-HPs) and snap-cooled molecular beacons (Sc-MBs) frequently used for biorecognition applications. Recognizing this limitation, we have developed a modified, freeze-based technique specifically designed to enable the adsorption of such hairpin oligonucleotides onto AuNP surfaces while ensuring that they retain their biosensing capabilities. Successful hairpin oligonucleotide conjugation of varying lengths to a wide range of AuNP diameters was corroborated by dynamic light scattering, ζ-potential, and UV-vis spectrophotometry. Moreover, we conducted a thorough evaluation of this modified method, confirming the retention of the sensing functions of Sc-HPs and Sc-MBs. This advancement not only offers a more efficient route for DNA hairpin conjugation but also elucidates the underlying biorecognition functions, with implications for broader applications in molecular diagnostics.

Add-on soft electronic interfaces for continuous cuffless blood pressure monitoring.

Continuous monitoring of arterial blood pressure is clinically important for the diagnosis and management of cardiovascular diseases. Soft electronic devices with skin-like properties show promise in a wide range of applications, including the human-machine interface, the Internet of things, and health monitoring. Here, we report the use of add-on soft electronic interfaces to address the connection challenges between soft electrodes and rigid data acquisition circuitry for bioimpedance monitoring of cardiac signals, including heart rate and cuffless blood pressure. Nanocomposite films in add-on electrodes provide robust electrical and mechanical contact with the skin and the rigid circuitry. We demonstrate bioimpedance sensors composed of add-on electrodes for continuous blood pressure monitoring with high accuracy. Specifically, the bioimpedance collected with add-on nanocomposite electrodes shows a signal-to-noise ratio of 37.0 dB, higher than the ratio of 25.9 dB obtained with standard silver/silver chloride (Ag/AgCl gel) electrodes. Although the sample set is low, the continuously measured systolic and diastolic blood pressure offer accuracy of -2.0 ± 6.3 mmHg and -4.3 ± 3.9 mmHg, respectively, confirming the grade A performance based on the IEEE standard. These results show promise in bioimpedance measurements with add-on soft electrodes for cuffless blood pressure monitoring.

Geometry design for a fully insertable glucose biosensor with multimodal optical readout.

Significance: Insertable optical continuous glucose monitors (CGMs) with wearable readers are a strong option for monitoring individuals with diabetes. However, a fully insertable CGM requires a small form factor while still delivering sufficient signal to be read through tissue by an external device. Previous work has suggested that a multimodal repeating unit (barcode) approach may meet these requirements, but the biosensor geometry must be optimized to meet performance criteria. Aim: This work details in silico trials conducted to evaluate the geometry of a fully insertable multimodal optical biosensor with respect to both optical output and species diffusion in vivo. Approach: Monte Carlo modeling is used to evaluate the luminescent output of three presupposed biosensor designs based on size constraints for an injectable and logical placement of the bar code compartments. Specifically, the sensitivity of the luminescent output to displacement of the biosensor in the X and Y directions, overall size of the selected design, and size of an individual repeating unit are analyzed. Further, an experimentally validated multiphysics model is used to evaluate the diffusion and reaction of glucose and oxygen within the biosensor to estimate the occurrence of chemical crosstalk between the assay components. Results: A stacked cylinder multimodal biosensor 4.4 mm in length with repeating units 0.36 mm in length was found to yield a greater luminescent output than the current "barcode" biosensor design. In addition, it was found that a biosensor with enzymatic elements does not significantly deplete glucose locally and thus does not impact the diffusion profile of glucose in adjacent compartments containing nonenzymatic assays. Conclusions: Computational modeling was used to design the geometry of a multimodal, insertable, and optical CGM to ensure that the optical output and chemical diffusion profile are sufficient for this device to function in vivo.

Mid-Infrared Serial Microring Resonator Array for Real-Time Detection of Vapor-Phase Volatile Organic Compounds.

Chip-scale infrared spectrometers consisting of a microring resonator array (MRA) were developed for volatile organic compound (VOC) detection. The MRA is serially positioned to serve as a wavelength sorting element that enables wavelength demultiplexing. Unlike conventional devices operated by a single microring, our MRA can perform multiwavelength mid-infrared (mid-IR) sensing by routing the resonant wavelength light from a broadband mid-IR source into different sensing channels. Miniaturized spectrometer devices were fabricated on mid-IR transparent silicon-rich silicon nitride (SiNx) thin films through complementary metal-oxide-semiconductor (CMOS) processes, thus enabling wafer-level manufacturing and packaging. The spectral distribution of the resonance lines and the optimization of the microring structures were designed using finite-difference time-domain (FDTD) modeling and then verified by laser spectrum scanning. Using small microring structures, the spectrum showed a large free spectral range (FSR) of 100 nm and held four spectral channels without crosstalk. Unlike near-infrared microrings using refractive index sensing, our MRA can detect hexane and ethanol vapor pulses by monitoring the intensity variation at their characteristic mid-IR absorption bands, thus providing high specificity. Applying multiwavelength detection, the sensor module can discriminate among various VOC vapors. Hence, our mid-IR MRA could be an essential component to achieve a compact spectroscopic sensing module that has the potential for applications such as remote environmental monitoring and portable health care devices.

Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: ECG and Accelerometry.

BACKGROUND: Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes. METHODS: In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine-learning approaches to predict glycemic excursions: a classification model and a regression model. RESULTS: The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone. CONCLUSIONS: Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction.

A Computational Modeling and Simulation Workflow to Investigate the Impact of Patient-Specific and Device Factors on Hemodynamic Measurements from Non-Invasive Photoplethysmography.

Cardiovascular disease is the leading cause of death globally. To provide continuous monitoring of blood pressure (BP), a parameter which has shown to improve health outcomes when monitored closely, many groups are trying to measure blood pressure via noninvasive photoplethysmography (PPG). However, the PPG waveform is subject to variation as a function of patient-specific and device factors and thus a platform to enable the evaluation of these factors on the PPG waveform and subsequent hemodynamic parameter prediction would enable device development. Here, we present a computational workflow that combines Monte Carlo modeling (MC), gaussian combination, and additive noise to create synthetic dataset of volar fingertip PPG waveforms representative of a diverse cohort. First, MC is used to determine PPG amplitude across age, skin tone, and device wavelength. Then, gaussian combination generates accurate PPG waveforms, and signal processing enables data filtration and feature extraction. We improve the limitations of current synthetic PPG frameworks by enabling inclusion of physiological and anatomical effects from body site, skin tone, and age. We then show how the datasets can be used to examine effects of device characteristics such as wavelength, analog to digital converter specifications, filtering method, and feature extraction. Lastly, we demonstrate the use of this framework to show the insensitivity of a support vector machine predictive algorithm compared to a neural network and bagged trees algorithm.

Monte Carlo method for assessment of a multimodal insertable biosensor.

SIGNIFICANCE: Continuous glucose monitors (CGMs) are increasingly utilized as a way to provide healthcare to the over 10% of Americans that have diabetes. Fully insertable and optically transduced biosensors are poised to further improve CGMs by extending the device lifetime and reducing cost. However, optical modeling of light propagation in tissue is necessary to ascertain device performance. AIM: Monte Carlo modeling of photon transport through tissue was used to assess the luminescent output of a fully insertable glucose biosensor that uses a multimodal Förster resonance energy transfer competitive binding assay and a phosphorescence lifetime decay enzymatic assay. APPROACH: A Monte Carlo simulation framework of biosensor luminescence and tissue autofluorescence was built using MCmatlab. Simulations were first validated against previous research and then applied to predict the response of a biosensor in development. RESULTS: Our results suggest that a diode within the safety standards for light illumination on the skin, with far-red excitation, allows the luminescent biosensor to yield emission strong enough to be detectable by a common photodiode. CONCLUSIONS: The computational model showed that the expected fluorescent power output of a near-infrared light actuated barcode was five orders of magnitude greater than a visible spectrum excited counterpart biosensor.

Detection of volatile organic compounds using mid-infrared silicon nitride waveguide sensors.

Mid-infrared (mid-IR) sensors consisting of silicon nitride (SiN) waveguides were designed and tested to detect volatile organic compounds (VOCs). SiN thin films, prepared by low-pressure chemical vapor deposition (LPCVD), have a broad mid-IR transparent region and a lower refractive index (nSiN = 2.0) than conventional materials such as Si (nSi = 3.4), which leads to a stronger evanescent wave and therefore higher sensitivity, as confirmed by a finite-difference eigenmode (FDE) calculation. Further, in-situ monitoring of three VOCs (acetone, ethanol, and isoprene) was experimentally demonstrated through characteristic absorption measurements at wavelengths λ = 3.0-3.6 µm. The SiN waveguide showed a five-fold sensitivity improvement over the Si waveguide due to its stronger evanescent field. To our knowledge, this is the first time SiN waveguides are used to perform on-chip mid-IR spectral measurements for VOC detection. Thus, the developed waveguide sensor has the potential to be used as a compact device module capable of monitoring multiple gaseous analytes for health, agricultural and environmental applications.

A portable brightfield and fluorescence microscope toward automated malarial parasitemia quantification in thin blood smears.

Malaria is often most endemic in remote regions where diagnostic microscopy services are unavailable. In such regions, the use of rapid diagnostic tests fails to quantify parasitemia measurements which reflect the concentration of Plasmodium parasites in the bloodstream. Thus, novel diagnostic and monitoring technologies capable of providing such information could improve the quality of treatment, monitoring, and eradication efforts. A low-cost, portable microscope for gathering quantitative parasitemia data from fluorescently stained thin blood smears is presented. The system employs bimodal imaging using components optimized for cost savings, system robustness, and optical performance. The microscope is novel for its use of monochromatic visible illumination paired with a long working distance singlet aspheric objective lens that can image both traditionally mounted and cartridge-based blood smears. Eight dilutions of red blood cells containing laboratory cultured wild-type P. falciparum were used to create thin smears which were stained with SYBR Green-1 fluorescent dye. Two subsequent images are captured for each field-of-view, with brightfield images providing cell counts and fluorescence images providing parasite localization data. Results indicate the successful resolution of sub-micron sized parasites, and parasitemia measurements from the prototype microscope display linear correlation with measurements from a benchtop microscope with a limit of detection of 0.18 parasites per 100 red blood cells.

Skin optical properties in the obese and their relation to body mass index: a review.

SIGNIFICANCE: Obesity is a worldwide epidemic contributing directly to several cardiovascular risk factors including hypertension and type 2 diabetes. Wearable devices are becoming better at quantifying biomarkers relevant for the management of health and fitness. Unfortunately, both anecdotal evidence and recent studies indicate that some wearables have higher levels of error when utilized by populations with darker skin tones and high body mass index (BMI). There is an urgent need for a better evaluation of the limits of wearable health technologies when used by obese individuals. AIMS: (1) To review the current know-how on changes due to obesity in the skin epidermis, dermis, and subcutis that could affect the skin optical properties; (2) for the green wavelength range, to evaluate the difference in absorption and scattering coefficients from the abdominal skin between individuals with and without elevated BMI. The changes include alterations in layer thickness and cell size, as well as significant differences in chromophores and scatterer content, e.g., water, hemoglobin, collagen, and lipids. APPROACH: We have summarized literature pertaining to changes in skin and its components in obesity and report the results of our search using articles published between years 1971 and 2020. A linear model was used to demonstrate the absorption and reduced scattering coefficient of the abdominal skin of individuals with and without elevated BMI in the green wavelength range (530 to 550 nm) that is typically found in most wearables. RESULTS: The general trends indicate a decrease in absorption for both dermis and subcutis and an increase in reduced scattering for both epidermis and dermis. At 544-nm wavelength, a typical wavelength used for photoplethysmography (PPG), the absorption coefficient's relative percentage difference between high and low BMI skin, was 49% in the subcutis, 19% in the dermis, and negligible in the epidermis, whereas the reduced scattering coefficient relative difference was 21%, 29%, and 165% respectively. CONCLUSIONS: These findings suggest that there could be significant errors in the output of optical devices used for monitoring health and fitness if changes due to obesity are not accounted for in their design.

Spectrally multiplexed assay using gap enhanced nanoparticle for detection of a myocardial infarction biomarker panel.

Multiplexed assays are essential for the detection of biomarker panels. Differentiating signals from different biomarkers in a single test zone makes the detection more efficient. In this paper, a new method is designed for the synthesis of gap-enhanced nanoparticles (GeNPs) using Raman reporter molecules (RRM) and 6-amino-1-hexanethiol (6-AHT) as the spacer. The GeNPs show a nanometer-size gap, generate strong surface-enhanced Raman scattering (SERS) attributed to the gap, and exhibit discriminative spectral peaks. The strong Au-S bonds on both core and shell sides and the covalent bond between RRM and 6-AHT led to a stable structure, which ensured the stable SERS signal generation from the GeNPs. Using the GeNPs, a spectrally multiplexed assay for the detection of a biomarker panel is developed. The biomarker panel is composed of cardiac troponin I (cTnI), copeptin, and heart-type fatty acid-binding protein (h-FABP), which improves myocardial infarction (MI) diagnostic performance. A paper-based platform that is more amenable to point-of-care diagnostic analysis is used. The developed single biomarker assay achieves limits of detection of 0.01 ng mL-1, 0.86 ng mL-1, 0.004 ng mL-1 for cTnI, h-FABP, and copeptin in buffer solutions. The dynamic range of the assay in human serum samples also covers the clinically relevant range of the biomarkers. The cross interference in the multiplexed assay is low. These results show the strong potential of the developed GeNPs in multiplexed detection of biomarkers and the developed simple-to-use multiplexed assay in the diagnosis of MI at the point of care.

Predicting the Macronutrient Composition of Mixed Meals From Dietary Biomarkers in Blood.

Diet monitoring is an essential intervention component for a number of diseases, from type 2 diabetes to cardiovascular diseases. However, current methods for diet monitoring are burdensome and often inaccurate. In prior work, we showed that continuous glucose monitors (CGMs) may be used to predict meal macronutrients (e.g., carbohydrates, protein, fat) by analyzing the shape of the post-prandial glucose response. In this study, we examine a number of additional dietary biomarkers in blood by their ability to improve macronutrient prediction, compared to using CGMs alone. For this purpose, we conducted a nutritional study where (n = 10) participants consumed nine different mixed meals with varied but known macronutrient amounts, and we analyzed the concentration of 33 dietary biomarkers (including amino acids, insulin, triglycerides, and glucose) at various times post-prandially. Then, we built machine learning models to predict macronutrient amounts from (1) individual biomarkers and (2) their combinations. We find that the additional blood biomarkers provide complementary information, and more importantly, achieve lower normalized root mean squared error (NRMSE) for the three macronutrients (carbohydrates: 22.9%; protein: 23.4%; fat: 32.3%) than CGMs alone (carbohydrates: 28.9%, t(18) =1.64, p =0.060; protein: 46.4%, t(18) =5.38, p 0.001; fat: 40.0%, t(18) =2.09, p =0.025). Our main conclusion is that augmenting CGMs to measure these additional dietary biomarkers improves macronutrient prediction performance, and may ultimately lead to the development of automated methods to monitor nutritional intake. This work is significant to biomedical research as it provides a potential solution to the long-standing problem of diet monitoring, facilitating new interventions for a number of diseases.

Postprandial concentration of circulating branched chain amino acids are able to predict the carbohydrate content of the ingested mixed meal.

BACKGROUND: The amount of the macronutrients protein and carbohydrate (CHO) in a mixed meal is known to affect each other's digestion, absorption, and subsequent metabolism. While the effect of the amount of dietary protein and fat on the glycemic response is well studied, the ability of postprandial plasma amino acid patterns to predict the meal composition is unknown. OBJECTIVE: To study the postprandial plasma amino acid patterns in relation to the protein, CHO, and fat content of different mixed meals and to investigate if these patterns can predict the macronutrient meal composition. DESIGN: Ten older adults were given 9 meals with 3 different levels (low, medium, and high) of protein, CHO, and fat in different combinations, taking the medium content as that of a standardized western meal. We monitored the postprandial plasma response for amino acids, glucose, insulin, and triglycerides for 8 h and the areas under the curve (AUC) were subsequently calculated. Multiple regression analysis was performed to determine if amino acid patterns could predict the meal composition. RESULTS: Increasing meal CHO content reduced the postprandial plasma response of several amino acids including all branched chain amino acids (BCAA) (leucine; q < 0.0001, isoleucine; q = 0.0035, valine; q = 0.0022). The plasma BCAA patterns after the meal significantly predicted the meal's CHO content (leucine; p < 0.0001, isoleucine; p = 0.0003, valine; p = 0.0008) along with aspartate (p < 0.0001), tyrosine (p < 0.0001), methionine (p = 0.0159) and phenylalanine (p = 0.0332). Plasma citrulline predicted best the fat content of the meal (p = 0.0024). CONCLUSIONS: The postprandial plasma BCAA patterns are lower with increasing meal CHO content and are strong predictors of a mixed meal protein and CHO composition, as are plasma citrulline for the fat content. We hypothesize that postprandial plasma amino acid concentrations can be used to predict the meal's macronutrient composition.

Brightfield and fluorescence in-channel staining of thin blood smears generated in a pumpless microfluidic.

Effective staining of peripheral blood smears by increasing contrast of intracellular components and biomarkers is essential for the accurate characterization, diagnosis, and monitoring of various diseases such as malaria. To assess the potential for automation of stained whole human blood smears at the point-of-care (POC), brightfield and fluorescence staining protocols were adapted for smears generated in channels of pumpless microchannels and compared to a standard glass smear. A 3× concentration Giemsa brightfield staining solutions (10, 33, and 50% dilution), and Acridine Orange fluorescence staining solutions (12 µg mL-1) were evaluated with human blood smears containing malaria parasites within a microfluidic channel. Giemsa staining at 33% dilution showed an optimal combination of contrast and preservation of cellular morphology, while 50% dilutions showed significant cellular crenation and 10% dilutions did not show desired contrast in brightfield imaging. Fluorescence staining at 12 µg mL-1 using Acridine Orange showed clear separability between the fluorescent intensities of the malaria parasites and that of the red blood cells (RBCs) and background. However, compared to glass smears, these exhibited reduced signal intensity as well as inverted contrast of RBCs and background. These results demonstrate that peripheral thin blood smears generated in pumpless microfluidic can be successfully stained in-channel with a simple, one-step procedure to permit brightfield and fluorescence imaging.

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring.

Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

Paper Microfluidic Device with a Horizontal Motion Valve and a Localized Delay for Automatic Control of a Multistep Assay.

A microfluidic paper-based analytical device (µPAD) is a cost-effective platform to implement assays, especially for point-of-care testing. Developing µPADs with fluidic control is important to implement multistep assays and provide high sensitivities. However, current localized delays in µPADs made of sucrose have a limited ability to decrease the flow rate. In addition, existing µPADs for automatic multistep assays are limited by their need for auxiliary instruments, their false activation, or their unavoidable tradeoff between available fluid volumes and temporal differences between steps. Here, a novel µPAD composed of a localized dissolvable delay and a horizontal motion mechanical valve for use as an automatic multistep assay is reported. A mixture of fructose and sucrose was used in the localized dissolvable delay and it provided an effective decrease in the flow rate to ensure adequate sensitivity in an assay. The dissolvable delay effectively doubled the flow time. A mechanical valve using a horizontal movement was developed to automatically implement a multistep process. Two-step and four-step processes were enabled with the µPAD. Cardiac troponin I (cTnI), a gold-standard biomarker for myocardial infarction, was used as a model analyte to show the performance of the developed µPAD in an assay. The designed µPAD, with the simple-to-make localized dissolvable delay and the robust mechanical valve, provides the potential to automatically implement high-performance multistep assays toward a versatile platform for point-of-care diagnostics.

A review of biosensor technologies for blood biomarkers toward monitoring cardiovascular diseases at the point-of-care.

Cardiovascular diseases (CVDs) cause significant mortality globally. Notably, CVDs disproportionately negatively impact underserved populations, such as those that are economically disadvantaged and often located in remote regions. Devices to measure cardiac biomarkers have traditionally been focused on large instruments in a central laboratory but the development of affordable, portable devices that measure multiple cardiac biomarkers at the point-of-care (POC) are needed to improve clinical outcomes for patients, especially in underserved populations. Considering the enormity of the global CVD problem, complexity of CVDs, and the large candidate pool of biomarkers, it is of great interest to evaluate and compare biomarker performance and identify potential multiplexed panels that can be used in combination with affordable and robust biosensors at the POC toward improved patient care. This review focuses on describing the known and emerging CVD biosensing technologies for analysis of cardiac biomarkers from blood. Initially, the global burden of CVDs and the standard of care for the primary CVD categories, namely heart failure (HF) and acute coronary syndrome (ACS) including myocardial infarction (MI) are discussed. The latest United States, Canadian and European society guidelines recommended standalone, emerging, and add-on cardiac biomarkers, as well as their combinations are then described for the prognosis, diagnosis, and risk stratification of CVDs. Finally, both commercial in vitro biosensing devices and recent state-of-art techniques for detection of cardiac biomarkers are reviewed that leverage single and multiplexed panels of cardiac biomarkers with a view toward affordable, compact devices with excellent performance for POC diagnosis and monitoring.

All-nanoparticle layer-by-layer coatings for Mid-IR on-chip gas sensing.

Functionalization of optical waveguides with submicron coatings of zinc peroxide (ZnO2) and silica (SiO2) nanoparticles (NPs) is reported that enabled selective concentration of acetone vapors in the vicinity of the waveguide, boosting the sensitivity of a mid infrared (MIR) on-chip detector. Controlled thickness was achieved by introducing precise control of the substrate withdrawal speed to the layer-by-layer (LbL) deposition technique.

Aptamer-based surface-enhanced resonance Raman scattering assay on a paper fluidic platform for detection of cardiac troponin I.

SIGNIFICANCE: Cardiac troponin I (cTnI) is a primary biomarker for diagnosis of myocardial infarction (MI). In contrast to central laboratory tests for cTnI, point-of-care (POC) testing has the advantage of providing results when the patient is first encountered, which helps high-risk patients to be treated more rapidly and low-risk patients to be released in a timely fashion. A paper fluidic platform is good for POC testing because the paper is abundant, low cost, and disposable. However, current cTnI assays on paper platforms use antibodies as the recognition element, which has limitations due to the high cost of production and antibody stability issues at the POC. AIM: To develop an aptamer-based assay on a paper strip using surface-enhanced resonance Raman spectroscopy (SERRS) for detection of cTnI in the clinically relevant range at the POC. APPROACH: Gold nanoparticles (AuNPs) were functionalized with a Raman reporter molecule, malachite green isothiocyanate. The functionalized AuNPs were encapsulated in a silica shell and provided a SERRS signal using a handheld Raman system with a 638-nm excitation wavelength. A primary aptamer and a secondary aptamer of cTnI were used in a sandwich assay format to bind the cTnI on a test line of a paper fluidic platform. By measuring the SERRS signal from the test line, the concentration of cTnI was quantitatively determined. RESULTS: The aptamer-based SERRS assay on a paper strip had a detection range of 0.016 to 0.1 ng / ml for cTnI, had good selectivity for cTnI compared to three other markers, had good stability over 10 days, and had good performance in the more complex serum sample matrix. CONCLUSIONS: The aptamer-based SERRS assay on a paper strip has the potential to provide a sensitive, selective, stable, repeatable, and cost-effective platform for the detection of cTnI toward eventual use in diagnosis of MI at the POC.

Benzene Derivatives Analysis Using Aluminum Nitride Waveguide Raman Sensors.

Raman spectroscopy using aluminum nitride (AlN) optical waveguides was demonstrated for organic compound analysis. The AlN waveguide device was prepared by reactive sputtering deposition and complementary-metal-oxide semiconductor (CMOS) processes. A fundamental waveguide mode was observed over a broad visible spectrum and the waveguide evanescent wave was used to excite the Raman signals of the test analytes. The performance of the waveguide sensor was characterized by measuring the Raman spectra of the benzene derivative mixtures consisting of benzene, anisole, and toluene. The compositions and concentrations were resolved by correlating the obtained Raman spectrum with the characteristic Raman peaks associated with C-C, C-H, and C-O functional groups. With the advantages of real-time detection and enhanced Raman signal intensity, the AlN waveguides provided a sensor platform for nondestructive and online chemical compound monitoring.