Mapping of specialized metabolite terms onto a plant phylogeny using text mining and large language models.

Plants produce a staggering array of chemicals that are the basis for organismal function and important human nutrients and medicines. However, it is poorly defined how these compounds evolved and are distributed across the plant kingdom, hindering a systematic view and understanding of plant chemical diversity. Recent advances in plant genome/transcriptome sequencing have provided a well-defined molecular phylogeny of plants, on which the presence of diverse natural products can be mapped to systematically determine their phylogenetic distribution. Here, we built a proof-of-concept workflow where previously reported diverse tyrosine-derived plant natural products were mapped onto the plant tree of life. Plant chemical-species associations were mined from literature, filtered, evaluated through manual inspection of over 2500 scientific articles, and mapped onto the plant phylogeny. The resulting "phylochemical" map confirmed several highly lineage-specific compound class distributions, such as betalain pigments and Amaryllidaceae alkaloids. The map also highlighted several lineages enriched in dopamine-derived compounds, including the orders Caryophyllales, Liliales, and Fabales. Additionally, the application of large language models, using our manually curated data as a ground truth set, showed that post-mining processing can largely be automated with a low false-positive rate, critical for generating a reliable phylochemical map. Although a high false-negative rate remains a challenge, our study demonstrates that combining text mining with language model-based processing can generate broader phylochemical maps, which will serve as a valuable community resource to uncover key evolutionary events that underlie plant chemical diversity and enable system-level views of nature's millions of years of chemical experimentation.

DUF2285 is a novel helix-turn-helix domain variant that orchestrates both activation and antiactivation of conjugative element transfer in proteobacteria.

Horizontal gene transfer is tightly regulated in bacteria. Often only a fraction of cells become donors even when regulation of horizontal transfer is coordinated at the cell population level by quorum sensing. Here, we reveal the widespread 'domain of unknown function' DUF2285 represents an 'extended-turn' variant of the helix-turn-helix domain that participates in both transcriptional activation and antiactivation to initiate or inhibit horizontal gene transfer. Transfer of the integrative and conjugative element ICEMlSymR7A is controlled by the DUF2285-containing transcriptional activator FseA. One side of the DUF2285 domain of FseA has a positively charged surface which is required for DNA binding, while the opposite side makes critical interdomain contacts with the N-terminal FseA DUF6499 domain. The QseM protein is an antiactivator of FseA and is composed of a DUF2285 domain with a negative surface charge. While QseM lacks the DUF6499 domain, it can bind the FseA DUF6499 domain and prevent transcriptional activation by FseA. DUF2285-domain proteins are encoded on mobile elements throughout the proteobacteria, suggesting regulation of gene transfer by DUF2285 domains is a widespread phenomenon. These findings provide a striking example of how antagonistic domain paralogues have evolved to provide robust molecular control over the initiation of horizontal gene transfer.

Molecular electronics sensors on a scalable semiconductor chip: A platform for single-molecule measurement of binding kinetics and enzyme activity.

For nearly 50 years, the vision of using single molecules in circuits has been seen as providing the ultimate miniaturization of electronic chips. An advanced example of such a molecular electronics chip is presented here, with the important distinction that the molecular circuit elements play the role of general-purpose single-molecule sensors. The device consists of a semiconductor chip with a scalable array architecture. Each array element contains a synthetic molecular wire assembled to span nanoelectrodes in a current monitoring circuit. A central conjugation site is used to attach a single probe molecule that defines the target of the sensor. The chip digitizes the resulting picoamp-scale current-versus-time readout from each sensor element of the array at a rate of 1,000 frames per second. This provides detailed electrical signatures of the single-molecule interactions between the probe and targets present in a solution-phase test sample. This platform is used to measure the interaction kinetics of single molecules, without the use of labels, in a massively parallel fashion. To demonstrate broad applicability, examples are shown for probe molecule binding, including DNA oligos, aptamers, antibodies, and antigens, and the activity of enzymes relevant to diagnostics and sequencing, including a CRISPR/Cas enzyme binding a target DNA, and a DNA polymerase enzyme incorporating nucleotides as it copies a DNA template. All of these applications are accomplished with high sensitivity and resolution, on a manufacturable, scalable, all-electronic semiconductor chip device, thereby bringing the power of modern chips to these diverse areas of biosensing.

Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients.

We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.

J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum.

Proton nuclear magnetic resonance (NMR) N-acetyl signals (Glyc) from glycoproteins and supramolecular phospholipids composite peak (SPC) from phospholipid quaternary nitrogen methyls in subcompartments of lipoprotein particles) can give important systemic metabolic information, but their absolute quantification is compromised by overlap with interfering resonances from lipoprotein lipids themselves. We present a J-Edited DIffusional (JEDI) proton NMR spectroscopic approach to selectively augment signals from the inflammatory marker peaks Glyc and SPCs in blood serum NMR spectra, which enables direct integration of peaks associated with molecules found in specific compartments. We explore a range of pulse sequences that allow editing based on peak J-modulation, translational diffusion, and T2 relaxation time and validate them for untreated blood serum samples from SARS-CoV-2 infected patients (n = 116) as well as samples from healthy controls and pregnant women with physiological inflammation and hyperlipidemia (n = 631). The data show that JEDI is an improved approach to selectively investigate inflammatory signals in serum and may have widespread diagnostic applicability to disease states associated with systemic inflammation.

Exploration of Human Serum Lipoprotein Supramolecular Phospholipids Using Statistical Heterospectroscopy in n-Dimensions (SHY-n): Identification of Potential Cardiovascular Risk Biomarkers Related to SARS-CoV-2 Infection.

SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS).

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum.

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10-8 and 3.7 × 10-8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology.

Point-of-care human milk testing for maternal secretor status.

We present an electrochemical impedimetric-based biosensor for monitoring the variation in human milk oligosaccharide (HMO) composition. 2'-Fucosyllactose (2'FL) is an HMO associated with infant growth, cognitive development, and protection from infectious diarrhea, one of the major causes of infant death worldwide. Due to genetic variation, the milk of some women (non-secretors) contains no or very little 2'FL with potential implications for infant health and development. However, there is currently no technology to analyze the presence and concentration of HMOs in human milk at the point-of-care (POC). The lack of such technology represents a major impediment to advancing human milk research and improving maternal-infant health. Towards this unmet need, we report an impedimetric assay for HMOs with an α-1,2 linkage, the most abundant of which is 2'FL. The sensor uses a lectin for affinity, specifically Ulex europaeus agglutinin I (UEA), with electrochemical readout. In spiked studies, the sensor exhibited a high degree of linearity (R2 = 0.991) over 0.5 to 3.0 µM with a 330-nM detection limit. The sensor performance was clinically validated using banked human milk samples and correctly identified all secretor vs. non-secretor samples. Furthermore, despite the short 35-min assay time and low sample volume (25 µL), the assay was highly correlated with HPLC measurements. This bedside human milk testing assay enables POC, "sample-to-answer" quantitative HMO measurement, and will be a valuable tool to assess milk composition.

Integrative Modeling of Plasma Metabolic and Lipoprotein Biomarkers of SARS-CoV-2 Infection in Spanish and Australian COVID-19 Patient Cohorts.

Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.

Incomplete Systemic Recovery and Metabolic Phenoreversion in Post-Acute-Phase Nonhospitalized COVID-19 Patients: Implications for Assessment of Post-Acute COVID-19 Syndrome.

We present a multivariate metabotyping approach to assess the functional recovery of nonhospitalized COVID-19 patients and the possible biochemical sequelae of "Post-Acute COVID-19 Syndrome", colloquially known as long-COVID. Blood samples were taken from patients ca. 3 months after acute COVID-19 infection with further assessment of symptoms at 6 months. Some 57% of the patients had one or more persistent symptoms including respiratory-related symptoms like cough, dyspnea, and rhinorrhea or other nonrespiratory symptoms including chronic fatigue, anosmia, myalgia, or joint pain. Plasma samples were quantitatively analyzed for lipoproteins, glycoproteins, amino acids, biogenic amines, and tryptophan pathway intermediates using Nuclear Magnetic Resonance (NMR) spectroscopy and mass spectrometry. Metabolic data for the follow-up patients (n = 27) were compared with controls (n = 41) and hospitalized severe acute respiratory syndrome SARS-CoV-2 positive patients (n = 18, with multiple time-points). Univariate and multivariate statistics revealed variable patterns of functional recovery with many patients exhibiting residual COVID-19 biomarker signatures. Several parameters were persistently perturbed, e.g., elevated taurine (p = 3.6 × 10-3 versus controls) and reduced glutamine/glutamate ratio (p = 6.95 × 10-8 versus controls), indicative of possible liver and muscle damage and a high energy demand linked to more generalized tissue repair or immune function. Some parameters showed near-complete normalization, e.g., the plasma apolipoprotein B100/A1 ratio was similar to that of healthy controls but significantly lower (p = 4.2 × 10-3) than post-acute COVID-19 patients, reflecting partial reversion of the metabolic phenotype (phenoreversion) toward the healthy metabolic state. Plasma neopterin was normalized in all follow-up patients, indicative of a reduction in the adaptive immune activity that has been previously detected in active SARS-CoV-2 infection. Other systemic inflammatory biomarkers such as GlycA and the kynurenine/tryptophan ratio remained elevated in some, but not all, patients. Correlation analysis, principal component analysis (PCA), and orthogonal-partial least-squares discriminant analysis (O-PLS-DA) showed that the follow-up patients were, as a group, metabolically distinct from controls and partially comapped with the acute-phase patients. Significant systematic metabolic differences between asymptomatic and symptomatic follow-up patients were also observed for multiple metabolites. The overall metabolic variance of the symptomatic patients was significantly greater than that of nonsymptomatic patients for multiple parameters (χ2p = 0.014). Thus, asymptomatic follow-up patients including those with post-acute COVID-19 Syndrome displayed a spectrum of multiple persistent biochemical pathophysiology, suggesting that the metabolic phenotyping approach may be deployed for multisystem functional assessment of individual post-acute COVID-19 patients.

Plasmonic Sensing Studies of a Gas-Phase Cystic Fibrosis Marker in Moisture Laden Air.

A plasmonic sensing platform was developed as a noninvasive method to monitor gas-phase biomarkers related to cystic fibrosis (CF). The nanohole array (NHA) sensing platform is based on localized surface plasmon resonance (LSPR) and offers a rapid data acquisition capability. Among the numerous gas-phase biomarkers that can be used to assess the lung health of CF patients, acetaldehyde was selected for this investigation. Previous research with diverse types of sensing platforms, with materials ranging from metal oxides to 2-D materials, detected gas-phase acetaldehyde with the lowest detection limit at the µmol/mol (parts-per-million (ppm)) level. In contrast, this work presents a plasmonic sensing platform that can approach the nmol/mol (parts-per-billion (ppb)) level, which covers the required concentration range needed to monitor the status of lung infection and find pulmonary exacerbations. During the experimental measurements made by a spectrometer and by a smartphone, the sensing examination was initially performed in a dry air background and then with high relative humidity (RH) as an interferent, which is relevant to exhaled breath. At a room temperature of 23.1 °C, the lowest detection limit for the investigated plasmonic sensing platform under dry air and 72% RH conditions are 250 nmol/mol (ppb) and 1000 nmol/mol (ppb), respectively.

Wearable electrochemical glove-based sensor for rapid and on-site detection of fentanyl.

Rapid, on-site detection of fentanyl is of critical importance, as it is an extremely potent synthetic opioid that is prone to abuse. Here we describe a wearable glove-based sensor that can detect fentanyl electrochemically on the fingertips towards decentralized testing for opioids. The glove-based sensor consists of flexible screen-printed carbon electrodes modified with a mixture of multiwalled carbon nanotubes and a room temperature ionic liquid, 4-(3-butyl-1-imidazolio)-1-butanesulfonate). The sensor shows direct oxidation of fentanyl in both liquid and powder forms with a detection limit of 10 µM using square-wave voltammetry. The "Lab-on-a-Glove" sensors, combined with a portable electrochemical analyzer, provide wireless transmission of the measured data to a smartphone or tablet for further analysis. The integrated sampling and sensing methodology on the thumb and index fingers, respectively, enables rapid screening of fentanyl in the presence of a mixture of cutting agents and offers considerable promise for timely point-of-need screening for first responders. Such a glove-based "swipe, scan, sense, and alert" strategy brings chemical analytics directly to the user's fingertips and opens new possibilities for detecting substances of abuse in emergency situations.

High-Density Redox Amplified Coulostatic Discharge-Based Biosensor Array.

High-density biosensor arrays are essential for many cutting-edge biomedical applications including point-of-care vaccination screening to detect multiple highly-contagious diseases. Typical electrochemical biosensing techniques are based on the measurement of sub-pA currents for micron-sized sensors requiring highly-sensitive readout circuits. Such circuits are often too complex to scale down for high-density arrays. In this paper, a high-density 4,096-pixel electrochemical biosensor array in 180 nm CMOS is presented. It uses a coulostatic discharge sensing technique and interdigitated electrode geometry to reduce both the complexity and size of the readout circuitry. Each biopixel contains an interdigitated microelectrode with a 13 aA low-leakage readout circuit directly underneath. Compared to standard planar electrodes, the implemented interdigitated electrodes achieve a maximum amplification factor of 10.5× from redox cycling. The array's sensor density is comparable to state-of-the-art arrays, all without augmenting the sensors with complex post-processing. The detection of anti-Rubella and anti-Mumps antibodies in human serum is demonstrated.

Ribosomal frameshifting and dual-target antiactivation restrict quorum-sensing-activated transfer of a mobile genetic element.

Symbiosis islands are integrative and conjugative mobile genetic elements that convert nonsymbiotic rhizobia into nitrogen-fixing symbionts of leguminous plants. Excision of the Mesorhizobium loti symbiosis island ICEMlSym(R7A) is indirectly activated by quorum sensing through TraR-dependent activation of the excisionase gene rdfS. Here we show that a +1 programmed ribosomal frameshift (PRF) fuses the coding sequences of two TraR-activated genes, msi172 and msi171, producing an activator of rdfS expression named Frameshifted excision activator (FseA). Mass-spectrometry and mutational analyses indicated that the PRF occurred through +1 slippage of the tRNA(phe) from UUU to UUC within a conserved msi172-encoded motif. FseA activated rdfS expression in the absence of ICEMlSym(R7A), suggesting that it directly activated rdfS transcription, despite being unrelated to any characterized DNA-binding proteins. Bacterial two-hybrid and gene-reporter assays demonstrated that FseA was also bound and inhibited by the ICEMlSym(R7A)-encoded quorum-sensing antiactivator QseM. Thus, activation of ICEMlSym(R7A) excision is counteracted by TraR antiactivation, ribosomal frameshifting, and FseA antiactivation. This robust suppression likely dampens the inherent biological noise present in the quorum-sensing autoinduction circuit and ensures that ICEMlSym(R7A) transfer only occurs in a subpopulation of cells in which both qseM expression is repressed and FseA is translated. The architecture of the ICEMlSym(R7A) transfer regulatory system provides an example of how a set of modular components have assembled through evolution to form a robust genetic toggle that regulates gene transcription and translation at both single-cell and cell-population levels.

An Audio Jack-Based Electrochemical Impedance Spectroscopy Sensor for Point-of-Care Diagnostics.

Portable and easy-to-use point-of-care (POC) diagnostic devices hold high promise for dramatically improving public health and wellness. In this paper, we present a mobile health (mHealth) immunoassay platform based on audio jack embedded devices, such as smartphones and laptops, that uses electrochemical impedance spectroscopy (EIS) to detect binding of target biomolecules. Compared to other biomolecular detection tools, this platform is intended to be used as a plug-and-play peripheral that reuses existing hardware in the mobile device and does not require an external battery, thereby improving upon its convenience and portability. Experimental data using a passive circuit network to mimic an electrochemical cell demonstrate that the device performs comparably to laboratory grade instrumentation with 0.3% and 0.5° magnitude and phase error, respectively, over a 17 Hz to 17 kHz frequency range. The measured power consumption is 2.5 mW with a dynamic range of 60 dB. This platform was verified by monitoring the real-time formation of a NeutrAvidin self-assembled monolayer (SAM) on a gold electrode demonstrating the potential for POC diagnostics.

Smartphone-Based pH Sensor for Home Monitoring of Pulmonary Exacerbations in Cystic Fibrosis.

Currently, Cystic Fibrosis (CF) patients lack the ability to track their lung health at home, relying instead on doctor checkups leading to delayed treatment and lung damage. By leveraging the ubiquity of the smartphone to lower costs and increase portability, a smartphone-based peripheral pH measurement device was designed to attach directly to the headphone port to harvest power and communicate with a smartphone application. This platform was tested using prepared pH buffers and sputum samples from CF patients. The system matches within ~0.03 pH of a benchtop pH meter while fully powering itself and communicating with a Samsung Galaxy S3 smartphone paired with either a glass or Iridium Oxide (IrOx) electrode. The IrOx electrodes were found to have 25% higher sensitivity than the glass probes at the expense of larger drift and matrix sensitivity that can be addressed with proper calibration. The smartphone-based platform has been demonstrated as a portable replacement for laboratory pH meters, and supports both highly robust glass probes and the sensitive and miniature IrOx electrodes with calibration. This tool can enable more frequent pH sputum tracking for CF patients to help detect the onset of pulmonary exacerbation to provide timely and appropriate treatment before serious damage occurs.

An Efficient Power Harvesting Mobile Phone-Based Electrochemical Biosensor for Point-of-Care Health Monitoring.

Cellular phone penetration has grown continually over the past two decades with the number of connected devices rapidly approaching the total world population. Leveraging the worldwide ubiquity and connectivity of these devices, we developed a mobile phone-based electrochemical biosensor platform for point-of-care (POC) diagnostics and wellness tracking. The platform consists of an inexpensive electronic module (< $20) containing a low-power potentiostat that interfaces with and efficiently harvests power from a wide variety of phones through the audio jack. Active impedance matching improves the harvesting efficiency to 79%. Excluding loses from supply rectification and regulation, the module consumes 6.9 mW peak power and can measure < 1 nA bidirectional current. The prototype was shown to operate within the available power budget set by mobile devices and produce data that matches well with that of an expensive laboratory grade instrument. We demonstrate that the platform can be used to track the concentration of secretory leukocyte protease inhibitor (SLPI), a biomarker for monitoring lung infections in cystic fibrosis patients, in its physiological range via an electrochemical sandwich assay on disposable screen-printed electrodes with a 1 nM limit of detection.

Integration of Faradaic electrochemical impedance spectroscopy into a scalable surface plasmon biosensor for in tandem detection.

We present an integrated label-free biosensor based on surface plasmon resonance (SPR) and Faradaic electrochemical impedance spectroscopy (f-EIS) sensing modalities, for the simultaneous detection of biological analytes. Analyte detection is based on the angular spectroscopy of surface plasmon resonance and the extraction of charge transfer resistance values from reduction-oxidation reactions at the gold surface, as responses to functionalized surface binding events. To collocate the measurement areas and fully integrate the modalities, holographically exposed thin-film gold SPR-transducer gratings are patterned into coplanar electrodes for tandem impedance sensing. Mutual non-interference between plasmonic and electrochemical measurement processes is shown, and using our scalable and compact detection system, we experimentally demonstrate biotinylated surface capture of neutravidin concentrations as low as 10 nM detection, with a 5.5 nM limit of detection.

Mitigating Medication Tampering and Diversion via Real-time Intravenous Opioid Quantification.

Opioid tampering and diversion pose a serious problem for hospital patients with potentially life-threatening consequences. The ongoing opioid crisis has resulted in medications used for pain management and anesthesia, such as fentanyl and morphine, being stolen, substituted with a different substance, and abused. This work aims to mitigate tampering and diversion through analytical verification of the administered drug before it enters the patient. We present an electrochemical-based sensor and miniaturized wireless potentiostat that enable real-time intravenous (IV) monitoring of opioids, specifically fentanyl and morphine. The proposed system is connected to an IV drip system during surgery or post-operation recovery. Measurement results of two opioids are presented, including calibration curves and data on the sensor performance concerning pH, temperature, interference, reproducibility, and long-term stability. Finally, we demonstrate real-time fluidic measurements connected to a flow cell to simulate IV administration and a blind study classified using a machine-learning algorithm. The system achieves limits of detection (LODs) of 1.26 µg/mL and 2.75 µg/mL for fentanyl and morphine, respectively, while operating with >1-month battery lifetime due to an optimized ultra-low power 36 µA sleep mode.

A GMR enzymatic assay for quantifying nuclease and peptidase activity.

Hydrolytic enzymes play crucial roles in cellular processes, and dysregulation of their activities is implicated in various physiological and pathological conditions. These enzymes cleave substrates such as peptide bonds, phosphodiester bonds, glycosidic bonds, and other esters. Detecting aberrant hydrolase activity is vital for understanding disease mechanisms and developing targeted therapeutic interventions. This study introduces a novel approach to measuring hydrolase activity using giant magnetoresistive (GMR) spin valve sensors. These sensors change resistance in response to magnetic fields, and here, they are functionalized with specific substrates for hydrolases conjugated to magnetic nanoparticles (MNPs). When a hydrolase cleaves its substrate, the tethered magnetic nanoparticle detaches, causing a measurable shift in the sensor's resistance. This design translates hydrolase activity into a real-time, activity-dependent signal. The assay is simple, rapid, and requires no washing steps, making it ideal for point-of-care settings. Unlike fluorescent methods, it avoids issues like autofluorescence and photobleaching, broadening its applicability to diverse biofluids. Furthermore, the sensor array contains 80 individually addressable sensors, allowing for the simultaneous measurement of multiple hydrolases in a single reaction. The versatility of this method is demonstrated with substrates for nucleases, Bcu I and DNase I, and the peptidase, human neutrophil elastase. To demonstrate a clinical application, we show that neutrophil elastase in sputum from cystic fibrosis patients hydrolyze the peptide-GMR substrate, and the cleavage rate strongly correlates with a traditional fluorogenic substrate. This innovative assay addresses challenges associated with traditional enzyme measurement techniques, providing a promising tool for real-time quantification of hydrolase activities in diverse biological contexts.