Mobile health (mHealth) promises a paradigm shift towards digital medicine where biomarkers in individuals are continuously monitored with wearable biosensors in decentralized locations to facilitate improved diagnosis and treatment of disease. Despite recent progress, the impact of wearables in health monitoring remains limited due to the lack of devices that measure meaningful health data and are accurate, minimally invasive, and unobtrusive. Therefore, next-generation biosensors must be developed to realize the vision of mHealth. To that end, in this dissertation, we develop wearable biochemical and biophysical sensors for health monitoring that can serve as platforms for future mHealth devices. First, we developed a skin patch biosensor for minimally invasive quantification of endogenous biochemical analytes in dermal interstitial fluid. The patch consisted of a polyacrylamide hydrogel microfilament array with covalently-tethered fluorescent aptamer sensors. Compared to prior approaches for hydrogel-based sensing, the microfilaments enable in situ sensing without invasive injection or removal. The patch was fabricated via replica molding with high-percentage polyacrylamide that provided high elastic modulus in the dehydrated state and optical transparency in the hydrated state. The microfilaments could penetrate the skin with low pain and without breaking, elicited minimal inflammation upon insertion, and were easily removed from the skin. To enable functional sensing, the polyacrylamide was co-polymerized with acrydite-modified aptamer sensors for phenylalanine that demonstrated reversible sensing with fast response time in vitro. In the future, hydrogel microfilaments could be integrated with a wearable fluorometer to serve as a platform for continuous, minimally invasive monitoring of intradermal biomarkers. Next, we shift focus to biophysical signals and the required signal processing, particularly towards the development of cuffless blood pressure (BP) monitors. Cuffless BP measurement could enable early detection and treatment of abnormal BP patterns and improved cardiovascular disease risk stratification. However, the accuracy of emerging cuffless monitoring methods is compromised by arm movement due to variations in hydrostatic pressure, limiting their clinical utility. To overcome this limitation, we developed a method to correct hydrostatic pressure errors in noninvasive BP measurements. The method tracks arm position using wearable inertial sensors at the wrist and a deep learning model that estimates parameterized arm-pose coordinates; arm position is then used for analytical hydrostatic pressure compensation. We demonstrated the approach with BP measurements derived from pulse transit time, one of the most well-studied modalities for cuffless BP measurement. Across hand heights of 25 cm above or below the heart, mean errors for diastolic and systolic BP were 0.7 ± 5.7 mmHg and 0.7 ± 4.9 mmHg, respectively, and did not differ significantly across arm positions. This method for correcting hydrostatic pressure may facilitate the development of cuffless devices that can passively monitor BP during everyday activities. Finally, towards a fully integrated device suitable for ambulatory BP monitoring, we developed a deep learning model for BP prediction from photoplethysmography waveforms acquired at a single measurement site. In contrast to competing methods that require thousands of measurements for adaptation to new users, our proposed approach enables accurate BP prediction following calibration with a single reference measurement. The model uses a convolutional neural network with temporal attention for feature extraction and a Siamese architecture for effective calibration. To prevent overfitting to person-specific variations that fail to generalize, we introduced an adversarial patient classification task to encourage the learning of patient-invariant features. Following calibration, the model accurately predicted diastolic and systolic BP over 24 hours, with mean errors of -0.07 ± 3.86 mmHg and -0.94 ± 7.32 mmHg, respectively, which meets the accuracy criteria for clinical validation. The proposed deep learning model could integrate with wearable photoplethysmography sensors, such as those in smartwatches, to enable cuffless ambulatory BP monitoring. Underlying this work is the development of minimally invasive biosensors that can integrate with wearable mHealth devices to facilitate passive monitoring of health parameters. The proliferation of mHealth wearables will enable the widespread collection of meaningful health data that provide actionable insights and a more comprehensive understanding of patient health. In a step towards this vision, we leveraged innovations in materials, multi-sensor fusion, and data-driven signal processing to develop sensors for measuring biochemical and biophysical markers. Overall, this work serves as an example of how the adoption of new technologies can facilitate the development of next-generation wearable biosensors.

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As science and medicine advance, it becomes ever more important to be able to control and analyze smaller and smaller bioparticles all the way down to single molecules. In this dissertation several studies aimed at improving our ability to manipulate and monitor single biomolecules will be discussed. First, we will discuss a study on developing a way to map dielectrophoresis with nanoscale resolution using a novel atomic force microscopy technique. Dielectrophoresis can be applied on nanoparticles through micron-scale electrodes to separate and control said particles. Therefore, this new method of mapping this force will greatly improve our ability to manipulate single biomolecules through dielectrophoresis. The next two studies discussed will be aimed at using carbon nanotube nanocircuits to monitor single protein kinetics in real time. Drug development and delivery methods rely on the precise understanding of protein interactions, thus creating the need for information on single protein dynamics that our techniques provides. The proteins studied in these sections are MMP1 and HDAC8, both of which are known targets of anti-cancer drugs. Finally, we developed a new strategy for diagnosing pancreatic cancer. Our strategy involves using graphene nanotransistors to detect exosomes released from the pancreatic tumor. The ability to reliably diagnose pancreatic cancer before it reaches metastasis would greatly improve the life expectancy of patients who develop this condition. We were able to test our technique on samples from a number of patients and were successfully able to distinguish patients with pancreatic cancer from noncancerous patients.

<p>This thesis has exploited the use of gold nanoparticles (AuNPs)/DNA conjugates towards 1) the development of simple colorimetric assays to monitor DNA functions and relevant biological processes, and 2) the control the nanoassembly of AuNPs using biomolecules and biological processes.</p> <p>DNA has a number of attractive functions including specific biorecognition, catalysis and being manipulated by protein enzymes, etc. These characteristics were exploited to permit nanoassembly to be responsive to a specific stimulus and also ensure the specificity and precision in the construction of well-defined 3D nanostructures. Meanwhile, the assembly or disassembly of AuNPs, which results in distinct color changes due to the localized surface plasmon resonance, provides an excellent platform for the colorimetrically monitoring the DNA functions and the relevant biological processes.</p> <p>We have specifically investigated how the surface charges, the length and conformations of surface-tethered DNA polymers affect the assembly of AuNPs. We found that the colloidal stability of AuNPs can be well-tuned by nucleotides (small charged molecules) with various binding affinity to AuNP surface and/or different number of negatively-charged phosphate groups. This relies on the fact that nucleotides can bind to AuNP surface via nucleobase-Au interaction, and negatively charged phosphates stabilize AuNPs via electrostatic repulsion. This investigation allowed us to monitor protein enzymatic reactions where nucleotides are modified by alkaline phosphatase and to control the growth of AuNPs using nucleotides as capping ligands.</p> <p>We then investigated the effect of the length of DNA polymers on AuNP surface on AuNP colloidal stability. DNA-modified AuNPs are stabilized electrosterically at a relatively high salt concentration; the removal (or shortening) of the DNA molecules by enzymatic cleavage or the dissociation of DNA aptamers from AuNP surface upon binding to their target destabilizes AuNPs and results in AuNP aggregation. We attribute this to the loss of negatively-charged polymeric DNA molecules that initially served as colloidal stabilizers. This has been applied to the monitoring of enzyme (both protein enzyme and DNA enzyme) cleavage of DNA molecules, and DNA aptamer binding event to its target, respectively.</p> <p> We also studied how DNA polymer conformational changes influence AuNP colloidal stability, which has been employed to monitor DNA aptamer folding events on the AuNP surfaces. We found that AuNPs to which folded aptamer/target complexes are attached are more stable towards salt induced aggregation than those tethered to unfolded aptamers. Experimental results suggested that the folded aptamers were more extended on the surface than the unfolded (but largely collapsed) aptamers in salt solution. The folded aptamers therefore provide higher stabilization effect on AuNPs from both the electrostatic and steric stabilization points of view.</p><p> Finally, we demonstrated the well-defined assembly of AuNPs using long (hundred nanometers to microns) single-stranded (ss) DNA molecules as template in a three-dimensional (3D) fashion. Specifically, these long ssDNA containing repeating units are generated by protein enzymatic reaction (DNA extension through rolling circle amplification) on AuNP surface. The resultant product provides a 3D-like scaffold that can be subsequently used for periodical assembly of complementary DNA-attached nanospecies. </p> <p> We also expect that the facile colorimetric biosensing assays developed in this thesis work provide an attractive means to study biomolecular behaviors (e.g, biorecognition and conformational changes) on the surface, and to investigate other common DNA (or RNA) structural (e.g., triplex, G-quadruplex, hairpin, i-motif) and protein structural transitions.</p> <p> Finally, this thesis work provides some novel and general strategies for the control of nanoassemblies by tuning surface charges and surface-tethered polymers. We expect these principles can also be applied in other AuNP-based sensing platforms that exploit interparticle interactions and in the construction of well-defined nanostructures which involves other types of nano-scaled materials (e.g., quantum dots, nanotubes, nanowires, etc).</p> / Thesis / Doctor of Philosophy (PhD)

The development of the in vitro selection technique permits the creation of synthetic DNA molecules with ligand-binding capabilities (DNA aptamers), or abilities to catalyze chemical reactions (DNAzymes), or both (aptazymes). Significant research efforts in this field over the past two decades have led to the creation of a large array of DNA aptamers and DNAzymes and ever-increasing interests in taking advantage of these molecular species for diverse applications. One area of remarkable potential and development is the exploration of functional DNA molecules for bioanalytical applications. The work described in this dissertation aims to pursue innovative concepts and technologies that expand utility of functional DNA molecules for biosensing applications. I have focused on two functional DNA species: RNA-cleaving DNAzymes and protein-binding DNA aptamers. My key interest is to develop simple but effective colorimetric assays that employ these functional DNA molecules and to establish an effective strategy that makes functional DNA biosensors highly functional in biological samples. / Thesis / Doctor of Philosophy (PhD)

Point-of-care DNA diagnostics for resource-limited settings require high sensitivity and low limits of detection but is constrained by a limitation on the complexity of instrumentation and resource consumption. To assist in the research and development of such technology, rapid-prototyping offers quick turnaround times from ideation to proof-of-concept testing at reduced costs. All-solution processed electrodes which exhibit micro/nano-scale wrinkling and porosity were rapidly-prototyped. Probe density was shown to be tunable with these electrodes and densities were greater than planar electrodes due to a surface area enhancement. Such electrodes also demonstrated favorable characteristics for the electrocatalytic detection of DNA hybridization. Characterization of hybridization efficiency for DNA biosensors often require the determination of probe and target DNA densities in separate experiments, relying on averaged measurements which lose device specificity. A new method to quantify hybridization efficiency was developed which allows the label-free, sequential determination of probe DNA and target DNA density in one experiment, allowing electrode-specific characterization of hybridization efficiency. / Thesis / Master of Applied Science (MASc)

Early-onset diagnostics, or the detection of disease before clinical symptoms arise, has gained traction for its potential to improve patient quality of life and health outcomes. Biosensors, found in point-of-care (POC) devices, facilitate early-onset diagnostics and disease monitoring by addressing the limitations of current diagnostics strategies, which include timeliness, cost-effectiveness, and accessibility. Biosensors often incorporate microarrays within their design to allow for the detection of disease-associated biomolecules, known as biomarkers. Microarrays are composed of capture biomolecules, such as monoclonal antibodies, that are immobilized through either contact or non-contact printing techniques. In the following thesis, we investigated microarray designs within novel biosensing platforms for diagnostic and disease monitoring applications. First, we highlighted the advantages and challenges of implementing different types of biosensors, detection methods, and biomolecule immobilization strategies. Additionally, we proposed a novel 3D microarray incorporating hydrogels composed purely of crosslinked bovine serum albumin (BSA) proteins decorated with capture antibodies (CAbs). Utilizing industry-standard inkjet printing, we developed and optimized a two-step fabrication protocol, by which BSA proteins and CAbs are printed first, followed by the crosslinking agent, 1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide (EDC). Characterization of the unique three-dimensional (3D) microstructure and hydrogel parameters and conducting comparisons with standard two-dimensional (2D) microdots, showed that increasing biosensor surface area led to a 3X increase in signal amplification. The limits of detection (LODs) for cytokine biomarkers were 0.3pg/mL for interleukin-6 (IL-6) and 1pg/mL for tumor necrosis factor receptor I (TNF RI), which were highly sensitive compared to reported LODs from literature. Alongside the investigation of novel printing protocols, proof-of-concepts for multiplex detection and distinguishing clinical patient samples from healthy donors were also presented. Overall, this thesis demonstrated the fabrication and optimization of microarray development shows promise in improving current biosensor designs, allowing for enhanced early-onset disease detection and monitoring. / Thesis / Master of Applied Science (MASc)

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