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.

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.

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.

Detection of cardiovascular disease associated miR-29a using paper-based microfluidics and surface enhanced Raman scattering.

The development of viable point-of-care diagnostic formats is integral to achieving better patient care and improved outcomes. The need for robust and low-cost tests is especially important in under-resourced and rural settings. Perhaps the greatest challenge is ensuring that an untrained individual is capable of operating and interpreting the test, out with a care facility. Here we present a paper-based diagnostic device capable of sensing miR-29a using both colorimetric and surface enhanced Raman scattering (SERS) analysis. Rather, than carry out the two types of analyses in tandem, we envisage that the colorimetric output is easy enough to be interpreted by the untrained-individual administering the test to provide them with qualitative feedback. If deemed positive, the test can be further validated at a centralized care facility using a handheld-Raman spectrometer to provide a semi-quantitative result. Detection of miR-29a, a microRNA associated with myocardial infarction, was achieved at a level of pg µL-1 through the combination of three-dimensional paper-based microfluidics, colorimetric detection, and surface enhanced Raman scattering (SERS) analysis. RGB analysis of the colorimetric output generated from samples containing miR-29a at different concentrations (18-360 pg µL-1) showed differentiation from the control sample, however significant repeat variability indicated that it could not be used for quantifying miR-29a levels. However, the SERS analysis exhibited greater reproducibility at varying concentrations, achieving an LoD of 47 pg µL-1. The union of the paper-based device and the two analysis methods resulted in the production of a sensitive, reproducible and facile, point of care test (POCT), which paves the way for future implementation in the diagnosis of a range of diseases.

A self-cleaning, mechanically robust membrane for minimizing the foreign body reaction: towards extending the lifetime of sub-Q glucose biosensors.

Long-term, subcutaneously implanted continuous glucose biosensors have the potential to improve diabetes management and reduce associated complications. However, the innate foreign body reaction (FBR) both alters the local glucose concentrations in the surrounding tissues and compromises glucose diffusion to the biosensor due to the recruitment of high-metabolizing inflammatory cells and the formation of a dense, collagenous fibrous capsule. Minimizing the FBR has mainly focused on "passively antifouling" materials that reduce initial cellular attachment, including poly(ethylene glycol) (PEG). Instead, the membrane reported herein utilizes an "actively antifouling" or "self-cleaning" mechanism to inhibit cellular attachment through continuous, cyclic deswelling/reswelling in response to normal temperature fluctuations of the subcutaneous tissue. This thermoresponsive double network (DN) membrane is based on N-isopropylacrylamide (NIPAAm) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) (75:25 and 100:0 NIPAAm:AMPS in the 1st and 2nd networks, respectively; "DN-25%"). The extent of the FBR reaction of a subcutaneously implanted DN-25% cylindrical membrane was evaluated in rodents in parallel with a PEG-diacrylate (PEG-DA) hydrogel as an established benchmark biocompatible control. Notably, the DN-25% implants were more than 25× stronger and tougher than the PEG-DA implants while maintaining a modulus near that of subcutaneous tissue. From examining the FBR at 7, 30 and 90 days after implantation, the thermoresponsive DN-25% implants demonstrated a rapid healing response and a minimal fibrous capsule (~20-25 µm), similar to the PEG-DA implants. Thus, the dynamic self-cleaning mechanism of the DN-25% membranes represents a new approach to limit the FBR while achieving the durability necessary for long-term implantable glucose biosensors.

Collection Method of SERS Active Nanoparticles for Sensitive and Precise Measurements.

Developing surface-enhanced Raman spectroscopy (SERS) based biosensors requires not only synthesizing SERS active nanoparticles or nanoprobes that produce intense signal but also collecting them in a consistent manner to obtain sensitive and precise measurements. Nanoprobes are commonly measured in solution; however, this approach has several disadvantages that can reduce sensitivity, such as probing only a small percentage of the nanoprobes present in the sample. In this work, a novel collection device was designed, built, and tested which consistently concentrates nanoprobes in a specific area to yield highly sensitive (femtomolar) and repeatable measurements. A particular silica nanoprobe composed of aggregated silver nanoparticles with Raman reporters on them was synthesized and functionalized to measure it on the collection device. The collection device was assessed by collecting several concentrations of nanoprobes and comparing their SERS intensities to determine their limit of detection and the precision on the device. In addition, a competitive binding assay to detect cardiac Troponin I (cTnI) was used as an example to demonstrate the functionality of the nanoprobe and collection device. Nanoprobe samples (10 µL) were detected with less than 10% coefficient of variation (CV) across a range from nearly 27.4 fM to 1.7 pM using the described collection method. In the example assay, several cTnI concentrations ranging from 0 to 250 ng/mL were detected.

Rational design of a bisphenol A aptamer selective surface-enhanced Raman scattering nanoprobe.

Surface-enhanced Raman scattering (SERS) optical nanoprobes offer a number of advantages for ultrasensitive analyte detection. These functionalized colloidal nanoparticles are a multifunctional assay component. providing a platform for conjugation to spectral tags, stabilizing polymers, and biorecognition elements such as aptamers or antibodies. We demonstrate the design and characterization of a SERS-active nanoprobe and investigate the nanoparticles' biorecognition capabilities for use in a competitive binding assay. Specifically, the nanoprobe is designed for the quantification of bisphenol A (BPA) levels in the blood after human exposure to the toxin in food and beverage plastic packaging. The nanoprobes demonstrated specific affinity to a BPA aptamer with a dissociation constant Kd of 54 nM, and provided a dose-dependent SERS spectra with a limit of detection of 3 nM. Our conjugation approach shows the versatility of colloidal nanoparticles in assay development, acting as detectable spectral tagging elements and biologically active ligands concurrently.

PEGylation of concanavalin A to improve its stability for an in vivo glucose sensing assay.

Competitive binding assays utilizing concanavalin A (ConA) have the potential to be the basis of improved continuous glucose monitoring devices. However, the efficacy and lifetime of these assays have been limited, in part, by ConA's instability due to its thermal denaturation in the physiological environment (37 °C, pH 7.4, 0.15 M NaCl) and its electrostatic interaction with charged molecules or surfaces. These undesirable interactions change the constitution of the assay and the kinetics of its behavior over time, resulting in an unstable glucose response. In this work, poly(ethylene glycol) (PEG) chains are covalently attached to lysine groups on the surface of ConA (i.e., PEGylation) in an attempt to improve its stability in these environments. Dynamic light scattering measurements indicate that PEGylation significantly improved ConA's thermal stability at 37 °C, remaining stable for at least 30 days. Furthermore, after PEGylation, ConA's binding affinity to the fluorescent competing ligand previously designed for the assay was not significantly affected and remained at ~5.4 × 10(6) M(-1) even after incubation at 37 °C for 30 days. Moreover, PEGylated ConA maintained the ability to track glucose concentrations when implemented within a competitive binding assay system. Finally, PEGylation showed a reduction in electrostatic-induced aggregation of ConA with poly(allylamine), a positively charged polymer, by shielding ConA's charges. These results indicate that PEGylated ConA can overcome the instability issues from thermal denaturation and nonspecific electrostatic binding while maintaining the required sugar-binding characteristics. Therefore, the PEGylation of ConA can overcome major hurdles for ConA-based glucose sensing assays to be used for long-term continuous monitoring applications in vivo.

Lymph transport in rat mesenteric lymphatics experiencing edemagenic stress.

OBJECTIVE: To assess lymphatic flow adaptations to edema, we evaluated lymph transport function in rat mesenteric lymphatics under normal and increased fluid volume (edemagenic) conditions in situ. METHODS: Twelve rats were infused with saline (intravenous infusion, 0.2 mL/min/100 g body weight) to induce edema. We intravitally measured mesenteric lymphatic diameter and contraction frequency, as well as lymphocyte velocity and density before, during, and after infusion. RESULTS: A 10-fold increase in lymphocyte velocity (0.1-1 mm/s) and a sixfold increase in flow rate (0.1-0.6 µL/min), were observed post infusion, respectively. There were also increases in contraction frequency and fractional pump flow one minute post infusion. Time-averaged wall shear stress increased 10 fold post infusion to nearly 1.5 dynes/cm(2) . Similarly, maximum shear stress rose from 5 to 40 dynes/cm(2) . CONCLUSIONS: Lymphatic vessels adapted to edemagenic stress by increasing lymph transport. Specifically, the increases in lymphatic contraction frequency, lymphocyte velocity, and shear stress were significant. Lymph pumping increased post infusion, though changes in lymphatic diameter were not statistically significant. These results indicate that edemagenic conditions stimulate lymph transport via increases in lymphatic contraction frequency, lymphocyte velocity, and flow. These changes, consequently, resulted in large increases in wall shear stress, which could then activate NO pathways and modulate lymphatic transport function.

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.

Optimization of a Concanavalin A-based glucose sensor using fluorescence anisotropy.

To date, the dependent nature of the recognition and transduction mechanisms in optical glucose sensors based upon Concanavalin A (ConA) has tended to prevent the sensors' full potential from being realized. In this paper, these mechanisms are independently optimized for a given assay configuration in order to decrease the predictive error of a ConA-based glucose sensor and to give a more accurate demonstration of its potential. To this end, we used fluorescence anisotropy as the transduction mechanism to determine the binding of ConA to 4 kDa FITC-dextran by measuring the change in the rotational correlation lifetime between the bound and unbound populations. By tracking the fluorescence anisotropy of this ligand, the ranges of ConA and 4 kDa FITC-dextran concentrations capable of being explored were not limited by the transduction mechanism. Using predetermined association constants, the binding responses to physiological glucose concentrations were predicted for different assay configurations, and experimentally collected fluorescence anisotropy data displayed the predicted trends for these assay configurations. From the experimental results, a calibration fit was generated for the optimized assay configuration to predict the glucose concentrations using the fluorescence anisotropy. This optimized assay displayed a mean standard error of prediction of 7.5 mg/dL (0-300 mg/dL), and 100% of the data points fell within clinically acceptable zones (A and B) upon the Clarke Error Grid Analysis. This indicates that, by independently optimizing the recognition and transduction mechanisms for the final assay configuration, the sensitivity of a competitive binding chemistry using ConA can be appropriately configured for continuous glucose monitoring applications.

Design and characterization of a ferromagnetic, air gapped magneto-optic Faraday rotator.

A method has been developed to modulate the plane of polarized light through the use of a high permeability ferrite core design. A proof-of-principal, optical Faraday effect device has been constructed and tested. Magnetic fields were generated to provide up to 1 deg of rotation at frequencies of direct current up to 10 kHz using a terbium gallium garnet crystal rod.

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.

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.

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.

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.

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.

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.

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.

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.