Maximizing Electrochemical Information: A Perspective on Background-Inclusive Fast Voltammetry.

This perspective encompasses a focused review of the literature leading to a tipping point in electroanalytical chemistry. We tie together the threads of a "revolution" quietly in the making for years through the work of many authors. Long-held misconceptions about the use of background subtraction in fast voltammetry are addressed. We lay out future advantages that accompany background-inclusive voltammetry, particularly when paired with modern machine-learning algorithms for data analysis.

Developmental framework for a desktop hydrogeomorphic wetland functional assessment derived from field-based data.

With loss of wetlands and their associated ecosystem services within landscapes, it is imperative to be able to understand the change in ecological functions underlying these services. Field-based functional assessments can produce a range of specific scores among a robust set of functions but are time and cost prohibitive as the number of wetlands assessed increases. Remote-based functional assessments are an alternative for broad scale assessments, but trade-off cost for limitations in scoring and functional assemblage. To address these concerns, we created a framework for the development of the Hydrogeomorphic Remote Assessment of Wetland Function (HGM-RAWF). Rooted in the hydrogeomorphic approach of an existing field-based functional assessment and its underlying models, this remote functional assessment substitutes field-based assessment methods with remotely assessed proxies. As potential remote proxies were determined through literature review and statistically screened for use in the remote assessment, a field-based reference wetland database of 222 freshwater wetlands in the Mid-Atlantic Region provided a baseline by which remote data could be compared and calibrated. The resulting HGM-RAWF protocol remotely assesses seven hydrology and biogeochemistry functions in the Mid-Atlantic with assessment scores similar to its field-based counterparts. With noted limitations, the HGM-RAWF framework provides the means to create desktop functional assessments across broad geographic scales with the diversity and specificity of field-based assessments at the reduced costs associated with remote assessments. Its basis in the HGM approach and use of public spatial datasets allows the framework to be adopted regionally and can be used as a model for national wetland functional assessment.

Untapped Potential: Real-Time Measurements of Opioid Exocytosis at Single Cells.

The endogenous opioid system is commonly targeted in pain treatment, but the fundamental nature of neuropeptide release remains poorly understood due to a lack of methods for direct detection of specific opioid neuropeptides in situ. These peptides are concentrated in, and released from, large dense-core vesicles in chromaffin cells. Although catecholamine release from these neuroendocrine cells is well characterized, the direct quantification of opioid peptide exocytosis events has not previously been achieved. In this work, a planar carbon-fiber microelectrode served as a "postsynaptic" sensor for probing catecholamine and neuropeptide release dynamics via amperometric monitoring. A constant potential of 500 mV was employed for quantification of catecholamine release, and a higher potential of 1000 mV was used to drive oxidation of tyrosine, the N-terminal amino acid in the opioid neuropeptides released from chromaffin cells. By discriminating the results collected at the two potentials, the data reveal unique kinetics for these two neurochemical classes at the single-vesicle level. The amplitude of the peptidergic signals decreased with repeat stimulation, as the halfwidth of these signals simultaneously increased. By contrast, the amplitude of catecholamine release events increased with repeat stimulation, but the halfwidth of each event did not vary. The chromogranin dense core was identified as an important mechanistic handle by which separate classes of transmitter can be kinetically modulated when released from the same population of vesicles. Overall, the data provide unprecedented insight into key differences between catecholamine and opioid neuropeptide release from isolated chromaffin cells.

Exploring Electrochemistry: A Hydrogen Peroxide Sensor Based on a Screen-Printed Carbon Electrode Modified with Prussian Blue.

There is an increasing need for fundamental electrochemistry concepts to be taught in the undergraduate curriculum, given the broad applicability of electrochemical technologies in addressing a wide range of global issues from critical energy shortages to real-time medical diagnostics. However, many electrochemical concepts are often taught in disparate laboratory experiments, spread out through the curriculum, which can be intimidating to students (and instructors). This experiment, which has been tested and optimized in the undergraduate classroom over multiple semesters, covers a wide range of electrochemistry topics in realizing the construction of a hydrogen peroxide (H2O2) sensor that is based on Prussian blue electrochemistry. The experiment introduces the fundamentals of cyclic voltammetry by prompting students to distinguish faradaic and capacitive components of voltammograms and to investigate their relationship with scan rate as per electrochemical theory. Students also evaluate electrocatalysis through electrodeposition of a thin film of Prussian blue on the sensor surface and the effects of this modification on electron transfer and sensor performance. Finally, students combine amperometric measurements with the method of standard additions to determine H2O2 concentrations in an unknown sample. Overall, this experiment offers an integrated and cohesive experience that connects many important electroanalytical concepts that are often taught individually into one 3 h, hands-on laboratory experiment that requires minimal resources.

Neurotransmitter Readily Escapes Detection at the Opposing Microelectrode Surface in Typical Amperometric Measurements of Exocytosis at Single Cells.

For decades, carbon-fiber microelectrodes have been used in amperometric measurements of neurotransmitter release at a wide variety of cell types, providing a tremendous amount of valuable information on the mechanisms involved in dense-core vesicle fusion. The electroactive molecules that are released can be detected at the opposing microelectrode surface, allowing for precise quantification as well as detailed kinetic information on the stages of neurotransmitter release. However, it remains unclear how much of the catecholamine that is released into the artificial synapse escapes detection. This work examines two separate mechanisms by which released neurotransmitter goes undetected in a typical amperometric measurement. First, diffusional loss is assessed by monitoring exocytosis at single bovine chromaffin cells using carbon-fiber microelectrodes fabricated in a recessed (cavity) geometry. This creates a microsampling vial that minimizes diffusional loss of analyte prior to detection. More molecules were detected per exocytotic release event when using a recessed cavity sensor as compared to the conventional configuration. In addition, pharmacological inhibition of the norepinephrine transporter (NET), which serves to remove catecholamine from the extracellular space, increased both the size and the time course of individual amperometric events. Overall, this study characterizes distinct physical and biological mechanisms by which released neurotransmitter escapes detection at the opposing microelectrode surface, while also revealing an important role for the NET in "presynaptic" modulation of neurotransmitter release.

Interpreting Dynamic Interfacial Changes at Carbon Fiber Microelectrodes Using Electrochemical Impedance Spectroscopy.

Carbon-fiber microelectrodes are instrumental tools in neuroscience used for the electroanalysis of neurochemical dynamics and recordings of neural activity. However, performance is variable and dependent on fabrication strategies, the biological response to implantation, and the physical and chemical composition of the recording environment. This presents an analytical challenge, as electrode performance is difficult to quantitatively assess in situ, especially when electrodes are permanently implanted or cemented in place. We previously reported that electrode impedance directly impacts electrochemical performance for molecular sensing. In this work, we investigate the impacts of individual components of the electrochemical system on impedance. Equivalent circuit models for glass- and silica-insulated carbon-fiber microelectrodes were determined using electrochemical impedance spectroscopy (EIS). The models were validated based on the ability to assign individual circuit elements to physical properties of the electrochemical system. Investigations were performed to evaluate the utility of the models in providing feedback on how changes in ionic strength and carbon fiber material alter impedance properties. Finally, EIS measurements were used to investigate the electrode/solution interface prior to, during, and following implantation in live brain tissue. A significant increase in impedance and decrease in capacitance occur during tissue exposure and persist following implantation. Electrochemical conditioning, which occurs continually during fast-scan cyclic voltammetry recordings, etches and renews the carbon surface, mitigating these effects. Overall, the results establish EIS as a powerful method for characterization of carbon-fiber microelectrodes, providing unprecedented insight into how real-world factors affect the electrode/solution interface.

Drift Subtraction for Fast-Scan Cyclic Voltammetry Using Double-Waveform Partial-Least-Squares Regression.

Background-subtracted fast-scan cyclic voltammetry (FSCV) provides a method for detecting molecular fluctuations with high spatiotemporal resolution in the brain of awake and behaving animals. The rapid scan rates generate large background currents that are subtracted to reveal changes in analyte concentration. Although these background currents are relatively stable, small changes do occur over time. These changes, referred to as electrochemical drift, result in background-subtraction artifacts that constrain the utility of FSCV, particularly when quantifying chemical changes that gradually occur over long measurement times (minutes). The voltammetric features of electrochemical drift are varied and can span the entire potential window, potentially obscuring the signal from any targeted analyte. We present a straightforward method for extending the duration of a single FSCV recording window. First, we have implemented voltammetric waveforms in pairs that consist of a smaller triangular sweep followed by a conventional voltammetric scan. The initial, abbreviated waveform is used to capture drift information that can serve as a predictor for the contribution of electrochemical drift to the subsequent full voltammetric scan using partial-least-squares regression (PLSR). This double-waveform partial-least-squares regression (DW-PLSR) paradigm permits reliable subtraction of the drift component to the voltammetric data. Here, DW-PLSR is used to improve quantification of adenosine, dopamine, and hydrogen peroxide fluctuations occurring >10 min from the initial background position, both in vitro and in vivo. The results demonstrate that DW-PLSR is a powerful tool for evaluating and interpreting both rapid (seconds) and gradual (minutes) chemical changes captured in FSCV recordings over extended durations.

Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate Fluctuations in Brain Tissue Using Fast-Scan Cyclic Voltammetry.

Recent studies have described a role for lactate in brain energy metabolism and energy formation, challenging the conventional view that glucose is the principle energy source for brain function. To date, lactate dynamics in the brain are largely unknown, limiting insight into function. We addressed this by developing and characterizing a lactate oxidase-modified carbon-fiber microelectrode coupled with fast-scan cyclic voltammetry. This new tool boasts a sensitivity for lactate of 22 ± 1 nA·mM-1 and LOD of 7.0 ± 0.7 µM. The approach has enabled detection of rapid lactate fluctuations with unprecedented spatiotemporal resolution as well as excellent stability, selectivity, and sensitivity. The technology was characterized both in vitro and in vivo at discrete recording sites in rat striatum. We provide evidence that striatal lactate availability increases biphasically in response to electrical stimulation of the dopaminergic midbrain in the anesthetized rat. This new tool for real-time detection of lactate dynamics promises to improve understanding of how lactate availability underscores neuronal function and dysfunction.

Electrochemical Selectivity Achieved Using a Double Voltammetric Waveform and Partial Least Squares Regression: Differentiating Endogenous Hydrogen Peroxide Fluctuations from Shifts in pH.

Hydrogen peroxide (H2O2) is a reactive oxygen species that serves as an important signaling molecule in normal brain function. At the same time, excessive H2O2 concentrations contribute to myriad pathological consequences resulting from oxidative stress. Studies to elucidate the diverse roles that H2O2 plays in complex biological environments have been hindered by the lack of robust methods for probing dynamic H2O2 fluctuations in living systems with molecular specificity. Background-subtracted fast-scan cyclic voltammetry at carbon-fiber microelectrodes provides a method of detecting rapid H2O2 fluctuations with high temporal and spatial resolution in brain tissue. However, H2O2 fluctuations can be masked by local changes in pH (ΔpH), because the voltammograms for these species can have significant peak overlap, hindering quantification. We present a method for removing ΔpH-related contributions from complex voltammetric data. By employing two distinct potential waveforms per scan, one in which H2O2 is electrochemically silent and a second in which both ΔpH and H2O2 are redox active, a clear distinction between H2O2 and ΔpH signals is established. A partial least-squares regression (PLSR) model is used to predict the ΔpH signal and subtract it from the voltammetric data. The model has been validated both in vitro and in vivo using k-fold cross-validation. The data demonstrate that the double waveform PLSR model is a powerful tool that can be used to disambiguate and evaluate naturally occurring H2O2 fluctuations in vivo.

Quantitative Comparison of Enzyme Immobilization Strategies for Glucose Biosensing in Real-Time Using Fast-Scan Cyclic Voltammetry Coupled with Carbon-Fiber Microelectrodes.

Electrochemical monitoring of non-electroactive species requires a biosensor that is stable and selective, with sensitivity to physiological concentrations of targeted analytes. We have combined glucose oxidase-modified carbon-fiber microelectrodes with fast-scan cyclic voltammetry for real-time measurements of glucose fluctuations in brain tissue. Work presented herein quantitatively compares three approaches to enzyme immobilization on the microelectrode surface-physical adsorption, hydrogel entrapment, and entrapment in electrospun nanofibers. The data suggest that each of these methods can be used to create functional microbiosensors. Immobilization of glucose oxidase by physical adsorption generates a biosensor with poor sensitivity to glucose and unstable performance. Entrapment of glucose oxidase in poly(vinyl alcohol) nanofibers generates microbiosensors that are effective for glucose measurements over a large linear range, and that may be particularly useful when targeting glucose concentrations in excess of 3 mm, such as in blood. Hydrogel entrapment is the most effective in terms of sensitivity and stability. These microbiosensors can be used for simultaneous monitoring of glucose and dopamine in real time. The findings outlined herein should be applicable to other oxidase enzymes, and thus they are broadly important for the development of new tools for real-time measurements of fluctuating molecules that are not inherently electroactive.

Spectroelectrochemical Characterization of the Dynamic Carbon-Fiber Surface in Response to Electrochemical Conditioning.

The effects of electrochemical preconditioning of P-55 pitch-based carbon-fiber microelectrodes were quantitatively examined in this study. Microstructural characterization of the electrode surface was done using Raman spectroscopy and scanning electron microscopy. Electrochemical performance was evaluated using cyclic voltammetry. The data show that application of positive potentials provides beneficial structural modifications to the electrode surface. Electrodes that were preconditioned using a static potential of +1.0 V exhibited enhanced sensitivity and electron transfer properties when compared to electrodes conditioned for the same amount of time with dynamic (triangular) waveforms reaching +1.0 V. Conditioning elicited microstructural changes to the electrode surface that were dependent on the amount of time spent at potentials greater than ∼1.0 V. Importantly, the data demonstrate that the carbon-fiber microstructure is dynamic. It is able to quickly and continuously undergo rapid structural reorganization as potential is applied, repeatedly alternating between a relatively ordered state and one that exhibits greater disorder in response to applied electrochemical potentials that span the range commonly used in voltammetric experiments.

Highly personalized detection of minimal Ewing sarcoma disease burden from plasma tumor DNA.

BACKGROUND: Even though virtually all patients with Ewing sarcoma achieve a radiographic complete response, up to 30% of patients who present with localized disease and up to 90% of those who present with metastases experience a metastatic disease recurrence, highlighting the inability to identify patients with residual disease at the end of therapy. Up to 95% of Ewing sarcomas carry a driving EWS-ETS translocation that has an intronic breakpoint that is specific to each tumor, and the authors developed a system to quantitatively detect the specific breakpoint DNA fragment in patient plasma. METHODS: The authors used a long-range multiplex polymerase chain reaction (PCR) technique to identify tumor-specific EWS-ETS breakpoints in Ewing sarcoma cell lines, patient-derived xenografts, and patient tumors, and this sequence was used to design tumor-specific primer sets to detect plasma tumor DNA (ptDNA) by droplet digital PCR in xenograft-bearing mice and patients. RESULTS: Tumor-specific breakpoint DNA fragments were detected in the plasma of xenograft-bearing mice, and the signal correlated with tumor burden during primary tumor growth, after surgical resection, and at the time of metastatic disease recurrence. Furthermore, the authors were able to detect the specific breakpoint in plasma DNA obtained from 3 patients with Ewing sarcoma and in 2 patients the authors were able to detect ptDNA when there was radiographically undetectable disease present. CONCLUSIONS: The use of droplet digital PCR to detect tumor-specific EWS-ETS fusion gene breakpoint ptDNA fragments can be developed into a highly personalized biomarker of disease recurrence that can be optimized in animal studies for ultimate use in patients. Cancer 2016;122:3015-3023. © 2016 American Cancer Society.

Microfabricated Collector-Generator Electrode Sensor for Measuring Absolute pH and Oxygen Concentrations.

Fast-scan cyclic voltammetry (FSCV) has attracted attention for studying in vivo neurotransmission due to its subsecond temporal resolution, selectivity, and sensitivity. Traditional FSCV measurements use background subtraction to isolate changes in the local electrochemical environment, providing detailed information on fluctuations in the concentration of electroactive species. This background subtraction removes information about constant or slowly changing concentrations. However, determination of background concentrations is still important for understanding functioning brain tissue. For example, neural activity is known to consume oxygen and produce carbon dioxide which affects local levels of oxygen and pH. Here, we present a microfabricated microelectrode array which uses FSCV to detect the absolute levels of oxygen and pH in vitro. The sensor is a collector-generator electrode array with carbon microelectrodes spaced 5 µm apart. In this work, a periodic potential step is applied at the generator producing transient local changes in the electrochemical environment. The collector electrode continuously performs FSCV enabling these induced changes in concentration to be recorded with the sensitivity and selectivity of FSCV. A negative potential step applied at the generator produces a transient local pH shift at the collector. The generator-induced pH signal is detected using FSCV at the collector and correlated to absolute solution pH by postcalibration of the anodic peak position. In addition, in oxygenated solutions a negative potential step at the generator produces hydrogen peroxide by reducing oxygen. Hydrogen peroxide is detected with FSCV at the collector electrode, and the magnitude of the oxidative peak is proportional to absolute oxygen concentrations. Oxygen interference on the pH signal is minimal and can be accounted for with a postcalibration.

Multiple scan rate voltammetry for selective quantification of real-time enkephalin dynamics.

Methionine-enkephalin (M-ENK) and leucine-enkephalin (L-ENK) are small endogenous opioid peptides that have been implicated in a wide variety of complex physiological functions, including nociception, reward processing, and motivation. However, our understanding of the role that these molecules play in modulating specific brain circuits remains limited, largely due to challenges in determining where, when, and how specific neuropeptides are released in tissue. Background-subtracted fast-scan cyclic voltammetry coupled with carbon-fiber microelectrodes has proven to be sensitive and selective for detecting rapidly fluctuating neurochemicals in vivo; however, many challenges exist for applying this approach to the detection of neuropeptides. We have developed and characterized a novel voltammetric waveform for the selective quantification of small tyrosine-containing peptides, such as the ENKs, with rapid temporal (subsecond) and precise spatial (10s of micrometers) resolution. We have established that the main contributor to the electrochemical signal inherent to M-ENK is tyrosine and that conventional waveforms provide poor peak resolution and lead to fouling of the electrode surface. By employing two distinct scan rates in each anodic sweep of this analyte-specific waveform, we have selectively distinguished M-ENK from common endogenous interfering agents, such as ascorbic acid, pH shifts, and even L-ENK. Finally, we have used this approach to simultaneously quantify catecholamine and M-ENK fluctuations in live tissue. This work provides a foundation for real-time measurements of endogenous ENK fluctuations in biological locations, and the underlying concept of using multiple scan rates is adaptable to the voltammetric detection of other tyrosine-containing neuropeptides.

Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget.

Estimating lateral carbon fluxes in agroecosystems presents challenges due to intricate anthropogenic and biophysical interactions. We used a modeling technique to enhance our comprehension of the determinants influencing lateral carbon fluxes and their significance in agroecosystem carbon budgets. The SWAT-C model was refined by incorporating a dynamic dissolved inorganic carbon (DIC) module, enhancing our ability to accurately quantify total lateral carbon fluxes. This improved model was calibrated using observed data on riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) fluxes, as well as net ecosystem exchange (NEE) data monitored by a flux tower situated in a representative agricultural watershed, the Tuckahoe Watershed (TW) of the Chesapeake Bay's coastal plain. We assessed the losses of POC, DOC, and DIC across five primary rotation types: C (continuous carbon), CS (corn-soybean), CSS (corn-soybean-soybean), CWS (corn-wheat-soybean), and CWSCS (corn-wheat-soybean-corn-soybean). Our study revealed notable variations in the average annual fluxes of POC (ranging between 152 and 198 kg ha-1), DOC (74-85 kg ha-1), and DIC (93-156 kg ha-1) across the five rotation types. The primary influencing factor for annual POC fluxes was identified as sediment yield. While both annual DOC and DIC fluxes displayed a marked correlation with surface runoff across all crop rotation schemes, soil respiration also significantly influenced annual DIC fluxes. Total lateral carbon fluxes (POC + DOC+DIC) constituted roughly 11 % of both net ecosystem production (NEP) and NEE, yet they represented a striking 95 % of net biome production (NBP) in the TW's agroecosystem. Grain yield carbon accounted for 80 % of both NEP and NEE and was nearly seven times that of NBP. Our findings suggest that introducing soybeans into cornfields tends to reduce NEP, NEE, and also NBP. Conversely, integrating winter wheat into the corn-soybean rotation significantly boosted NEP, NEE, and NBP values, with NBP even surpassing the levels in continuous corn cultivation.

Optimized Fabrication of Carbon-Fiber Microbiosensors for Codetection of Glucose and Dopamine in Brain Tissue.

Dopamine (DA) signaling is critically important in striatal function, and this metabolically demanding process is fueled largely by glucose. However, DA and glucose are typically studied independently and, as such, the precise relationship between DA release and glucose availability remains unclear. Fast-scan cyclic voltammetry (FSCV) is commonly coupled with carbon-fiber microelectrodes to study DA transients. These microelectrodes can be modified with glucose oxidase (GOx) to generate microbiosensors capable of simultaneously quantifying real-time and physiologically relevant fluctuations of glucose, a nonelectrochemically active substrate, and DA, which is readily oxidized and reduced at the electrode surface. A chitosan hydrogel can be electrodeposited to entrap the oxidase enzyme on the sensor surface for stable, sensitive, and selective codetection of glucose and DA using FSCV. This strategy can also be used to entrap lactate oxidase on the carbon-fiber surface for codetection of lactate and DA. However, these custom probes are individually fabricated by hand, and performance is variable. This study characterizes the physical nature of the hydrogel and its effects on the acquired electrochemical data in the detection of glucose (2.6 mM) and DA (1 µM). The results demonstrate that the electrodeposition of the hydrogel membrane is improved using a linear potential sweep rather than a direct step to the target potential. Electrochemical impedance spectroscopy data relate information on the physical nature of the electrode/solution interface to the electrochemical performance of bare and enzyme-modified carbon-fiber microelectrodes. The electrodeposition waveform and scan rate were characterized for optimal membrane formation and performance. Finally, codetection of both DA/glucose and DA/lactate was demonstrated in intact rat striatum using probes fabricated according to the optimized protocol. Overall, this work improves the reliable fabrication of carbon-fiber microbiosensors for codetection of DA and important energetic substrates that are locally delivered to the recording site to meet metabolic demand.

Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data.

Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intra-watershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

In situ electrode calibration strategy for voltammetric measurements in vivo.

Technological advances have allowed background-subtracted fast-scan cyclic voltammetry to emerge as a powerful tool for monitoring molecular fluctuations in living brain tissue; however, there has been little progress to date in advancing electrode calibration procedures. Variability in the performance of these handmade electrodes renders calibration necessary for accurate quantification; however, experimental protocol makes standard postcalibration difficult or in some cases impossible. We have developed a model that utilizes information contained in the background charging current to predict electrode sensitivity to dopamine, ascorbic acid, hydrogen peroxide, and pH shifts at any point in an electrochemical experiment. Analysis determined a high correlation between predicted sensitivity and values obtained using the traditional postcalibration method, across all analytes. To validate this approach in vivo, calibration factors obtained with this model at electrodes in brain tissue were compared to values obtained at these electrodes using a traditional ex vivo calibration. Both demonstrated equal power of predictability for dopamine concentrations. This advance enables in situ electrode calibration, allowing researchers to track changes in electrode sensitivity over time and eliminating the need to generalize calibration factors between electrodes or across multiple days in an experiment.

Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping.

The hydrologic connectivity of non-floodplain wetlands (NFWs) with downstream water (DW) has gained increased importance, but connectivity via groundwater (GW) is largely unknown owing to the high complexity of hydrological processes and climatic seasonality. In this study, a causal inference method, convergent cross mapping (CCM), was applied to detect the hydrologic causality between upland NFW and DW through GW. CCM is a nonlinear inference method for detecting causal relationships among environmental variables with weak or moderate coupling in nonlinear dynamical systems. We assumed that causation would exist when the following conditions were observed: (1) the presence of two direct causal (NFW → GW and GW → DW) and one indirect causal (NFW → DW) relationship; (2) a nonexistent opposite causal relationship (DW → NFW); (3) the two direct causations with shorter lag times relative to indirect causation; and (4) similar patterns not observed with pseudo DW. The water levels monitored by a well and piezometer represented NFW and GW measurements, respectively, and the DW was indicated by the baseflow at the outlet of the drainage area, including NFW. To elucidate causality, the DW taken at the adjacent drainage area with similar climatic seasonality was also tested as pseudo DW. The CCM results showed that the water flow from NFW to GW and then DW was only present, and any opposite flows did not exist. In addition, direct causations had shorter lag time than indirect causation, and 3-day lag time was shown between NFW and DW. Interestingly, the results with pseudo DW did not show any lagged interactions, indicating non-causation. These results provide the signals for the hydrologic connectivity of NFW and DW with GW. Therefore, this study would support the importance of NFW protection and management.

Exploiting Microelectrode Geometry for Comprehensive Detection of Individual Exocytosis Events at Single Cells.

Carbon fiber microelectrodes are commonly used for real-time monitoring of individual exocytosis events at single cells. Since the nature of an electrochemical signal is fundamentally governed by mass transport to the electrode surface, microelectrode geometry can be exploited to achieve precise and accurate measurements. Researchers traditionally pair amperometric measurements of exocytosis with a ∼10-µm diameter, disk microelectrode in an "artificial synapse" configuration to directly monitor individual release events from single cells. Exocytosis is triggered, and released molecules diffuse to the "post-synaptic" electrode for oxidation. This results in a series of distinct current spikes corresponding to individual exocytosis events. However, it remains unclear how much of the material escapes detection. In this work, the performance of 10- and 34-µm diameter carbon fiber disk microelectrodes was directly compared in monitoring exocytosis at single chromaffin cells. The 34-µm diameter electrode was more sensitive to catecholamines and enkephalins than its traditional, 10-µm diameter counterpart, and it more effectively covered the entire cell. As such, the larger sensor detected more exocytosis events overall, as well as a larger quantal size, suggesting that the traditional tools underestimate the above measurements. Both sensors reliably measured l-DOPA-evoked changes in quantal size, and both exhibited diffusional loss upon adjustment of cell-electrode spacing. Finite element simulations using COMSOL support the improved collection efficiency observed using the larger sensor. Overall, this work demonstrates how electrode geometry can be exploited for improved detection of exocytosis events by addressing diffusional loss─an often-overlooked source of inaccuracy in single-cell measurements.