Enhancing the compatibility of BioCaRGOS silica sol-gel technology with ctDNA extraction and droplet digital PCR (ddPCR) analysis.

Previously, our group had demonstrated long term stabilization of protein biomarkers using BioCaRGOS, a silica sol-gel technology. Herein, we describe workflow modifications to allow for extraction of cell free DNA (cfDNA) from primary samples containing working concentrations of BioCaRGOS, as well as the compatibility of BioCaRGOS with droplet digital PCR (ddPCR) analysis for pancreatic cancer biomarkers i.e., KRAS circulating tumor DNA (ctDNA). Preliminary attempts to extract ctDNA from BioCaRGOS containing samples demonstrated interference in the extraction of primary samples and the interference with ddPCR analysis when BioCaRGOS was directly introduced to stabilize sample extracts. In our modified technique, we have minimized the interference caused by methanol with ddPCR by complete removal of methanol from the activated BioCaRGOS formulation prior to addition to the biospecimen or ctDNA extract. Interference of the silica matrix present in BioCaRGOS with ctDNA extraction was eliminated through the introduction of invert filtration of the sample prior to extraction. These modifications to the workflow of BioCaRGOS containing samples allow for use of BioCaRGOS for stabilization of trace quantities of nucleic acid biomarkers such as plasma ctDNA, while retaining the capability to extract the biomarker and quantify based on ddPCR.

Adsorption Properties and Electron-transfer Rates of a Redox Probe at Different Interfaces of an Immunoassay Assembled on an Electro-active Photonic Platform.

Physical and chemical properties of a redox protein adsorbed to different interfaces of a multilayer immunoassay assembly were studied using a single-mode, electro-active, integrated optical waveguide (SM-EA-IOW) platform. For each interface of the immunoassay assembly (indium tin oxide, 3-aminopropyl triethoxysilane, recombinant protein G, antibody, and bovine serum albumin) the surface density, the adsorption kinetics, and the electron-transfer rate of bound species of the redox-active cytochrome c (Cyt-C) protein were accurately quantified at very low surface concentrations of redox species (from 0.4 to 4% of a full monolayer) using a highly sensitive optical impedance spectroscopy (OIS) technique based on measurements obtained with the SM-EA-IOW platform. The technique is shown here to provide quantitative insights into an important immunoassay assembly for characterization and understanding of the mechanisms of electron transfer rate, the affinity strength of molecular binding, and the associated bio-selectivity. Such methodology and acquired knowledge are crucial for the development of novel and advanced immuno-biosensors.

Long term storage of miRNA at room and elevated temperatures in a silica sol-gel matrix.

Storage of biospecimens in their near native environment at room temperature can have a transformative global impact, however, this remains an arduous challenge to date due to the rapid degradation of biospecimens over time. Currently, most isolated biospecimens are refrigerated for short-term storage and frozen (-20 °C, -80 °C, liquid nitrogen) for long-term storage. Recent advances in room temperature storage of purified biomolecules utilize anhydrobiosis. However, a near aqueous storage solution that can preserve the biospecimen nearly "as is" has not yet been achieved by any current technology. Here, we demonstrate an aqueous silica sol-gel matrix for optimized storage of biospecimens. Our technique is facile, reproducible, and has previously demonstrated stabilization of DNA and proteins, within a few minutes using a standard benchtop microwave. Herein, we demonstrate complete integrity of miRNA 21, a highly sensitive molecule at 4, 25, and 40 °C over a period of ∼3 months. In contrast, the control samples completely degrade in less than 1 week. We attribute excellent stability to entrapment of miRNA within silica-gel matrices.

Bio-CaRGOS: capture and release gels for optimized storage of hemoglobin.

Room temperature biospecimen storage for prolonged periods is essential to eliminate energy consumption by ultra-low freezing or refrigeration-based storage techniques. State of the art practices that sufficiently minimize the direct or hidden costs associated with cold-chain logistics include ambient temperature storage of biospecimens (i.e., DNA, RNA, proteins, lipids) in the dry state. However, the biospecimens are still well-exposed to the stress associated with drying and reconstitution cycles, which augments the pre-analytical degradation of biospecimens prior to their downstream processing. An aqueous storage solution that can eliminate these stresses which are correlated to several cycles of drying/rehydration or freezing of biospecimens, is yet to be achieved by any current technology. In our study, we have addressed this room temperature biospecimen-protection challenge using aqueous capture and release gels for optimized storage (Bio-CaRGOS) of biospecimens. Herein, we have demonstrated a single-step ∼95% recovery of a metalloprotein hemoglobin at room temperature using a cost-effective standard microwave-based aqueous formulation of Bio-CaRGOS. Although hemoglobin samples are currently stored at sub-zero or under refrigeration (4 °C) conditions to avoid loss of integrity and an unpredictable diagnosis during their downstream assays, our results have displayed an unprecedented room temperature integrity preservation of hemoglobin. Bio-CaRGOS formulations efficiently preserve hemoglobin in its native state, with single-step protein recovery of ∼95% at ambient conditions (1 month) and ∼96% (7 months) under refrigeration conditions. In contrast, two-thirds of the control samples degrade under ambient (1 month) and refrigeration (7 months) settings.

Radiation-induced curcumin release from curcumin-chitosan polymer films.

The probability of human exposure to damaging radiation is increased in activities associated with long-term space flight, medical radiation therapies, and responses to nuclear accidents. However, the development of responsive countermeasures to combat radiation damage to biological tissue is lagging behind rates of human exposure. Herein, we report a radiation-responsive drug delivery system that releases doses of curcumin from a chitosan polymer/film in response to low level gamma radiation exposure. As a fibrous chitosan-curcumin polymer, 1 Gy gamma irradiation (137Cs) released 5 ± 1% of conjugated curcumin, while 6 Gy exposure releases 98 ± 1% of conjugated curcumin. The same polymer was formed into a film through solvent casting. The films showed similar, albeit attenuated behavior in water (100% released) and isopropyl alcohol (32% released) with statistically significant drug release following 2 Gy irradiation. ATR FT-IR studies confirmed glycosidic bond cleavage in the chitosan-curcumin polymer in response to gamma radiation exposure. Similar behavior was noted upon exposure of the polymer to 20 cGy (1 GeV amu-1, at 20 cGy min-1) high linear energy transfer (LET) 56Fe radiation based on FTIR studies. Density Functional Theory calculations indicate homolytic bond scission as the primary mechanism for polymer disintegration upon radiation exposure. Films did not change in thickness during the course of radiation exposure. The successful demonstration of radiation-triggered drug release may lead to new classes of radio-protective platforms for developing countermeasures to biological damage from ionizing radiation.

Dataset for dose and time-dependent transcriptional response to ionizing radiation exposure.

Exposure to ionizing radiation associated with highly energetic and charged heavy particles is an inherent risk astronauts face in long duration space missions. We have previously considered the transcriptional effects that three levels of radiation (0.3 Gy, 1.5 Gy, and 3.0 Gy) have at an immediate time point (1 hr) post-exposure [1]. Our analysis of these results suggest effects on transcript levels that could be modulated at lower radiation doses [2]. In addition, a time dependent effect is likely to be present. Therefore, in order to develop a lab-on-a-chip approach for detection of radiation exposure in terms of both radiation level and time since exposure, we developed a time- and dose-course study to determine appropriate sensitive and specific transcript biomarkers that are detectable in blood samples. The data described herein was developed from a study measuring exposure to 0.15 Gy, 0.30 Gy, and 1.5 Gy of radiation at 1 hr, 2 hr, and 6 hr post-exposure using Affymetrix® GeneChip® PrimeView™ microarrays. This report includes raw gene expression data files from the resulting microarray experiments representing typical radiation exposure levels an astronaut may experience as part of a long duration space mission. The data described here is available in NCBI's Gene Expression Omnibus (GEO), accession GSE63952.

Targeted Gold Nanoparticle⁻Oligonucleotide Contrast Agents in Combination with a New Local Voxel-Wise MRI Analysis Algorithm for In Vitro Imaging of Triple-Negative Breast Cancer.

Gold nanoparticles (GNPs) have tremendous potential as cancer-targeted contrast agents for diagnostic imaging. The ability to modify the particle surface with both disease-targeting molecules (such as the cancer-specific aptamer AS1411) and contrast agents (such as the gadolinium chelate Gd(III)-DO3A-SH) enables tailoring the particles for specific cancer-imaging and diagnosis. While the amount of image contrast generated by nanoparticle contrast agents is often low, it can be augmented with the assistance of computer image analysis algorithms. In this work, the ability of cancer-targeted gold nanoparticle-oligonucleotide conjugates to distinguish between malignant (MDA-MB-231) and healthy cells (MCF-10A) is tested using a T1-weighted image analysis algorithm based on three-dimensional, deformable model-based segmentation to extract the Volume of Interest (VOI). The gold nanoparticle/algorithm tandem was tested using contrast agent GNP-Gd(III)-DO3A-SH-AS1411) and nontargeted c-rich oligonucleotide (CRO) analogs and control (CTR) counterparts (GNP-Gd(III)-DO3A-SH-CRO/CTR) via in vitro studies. Remarkably, the cancer cells were notably distinguished from the nonmalignant cells, especially at nanomolar contrast agent concentrations. The T1-weighted image analysis algorithm provided similar results to the industry standard Varian software interface (VNMRJ) analysis of T1 maps at micromolar contrast agent concentrations, in which the VNMRJ produced a 19.5% better MRI contrast enhancement. However, our algorithm provided more sensitive and consistent results at nanomolar contrast agent concentrations, where our algorithm produced ~500% better MRI contrast enhancement.

Detection of influenza virus by electrochemical surface plasmon resonance under potential modulation.

In this study we report the development of a novel viral pathogen immunosensor technology based on the electrochemical modulation of the optical signal from a surface plasmon wave interacting with a redox dye reporter. The device is formed by incorporating a sandwich immunoassay onto the surface of a plasmonic device mounted in a micro-electrochemical flow cell, where it is functionalized with a monoclonal antibody aimed to a specific target pathogen antigen. Once the target antigen is bound to the surface, it promotes the capturing of a secondary polyclonal antibody that has been conjugated with a redox-active methylene blue dye. The methylene blue displays a reversible change in the complex refractive index throughout a reduction-oxidation transition, which generates an optical signal that can be electrochemically modulated and detected at high sensitivity. For proof-of-principle measurements, we have targeted the hemagglutinin protein from the H5N1 avian influenza A virus to demonstrate the capabilities of our device for detection and quantification of a critical influenza antigen. Our experimental results of the EC-SPR-based immunosensor under potential modulation showed a 300 pM limit of detection for the H5N1 antigen.

Computer-Aided Diagnostic System for Early Detection of Acute Renal Transplant Rejection Using Diffusion-Weighted MRI.

OBJECTIVE: Early diagnosis of acute renal transplant rejection (ARTR) is critical for accurate treatment. Although the current gold standard, diagnostic technique is renal biopsy, it is not preferred due to its invasiveness, long recovery time (1-2 weeks), and potential for complications, e.g., bleeding and/or infection. METHODS: This paper presents a computer-aided diagnostic (CAD) system for early ARTR detection using (3D + b-value) diffusion-weighted (DW) magnetic resonance imaging (MRI) data. The CAD process starts from kidney tissue segmentation with an evolving geometric (level-set-based) deformable model. The evolution is guided by a voxel-wise stochastic speed function, which follows from a joint kidney-background Markov-Gibbs random field model accounting for an adaptive kidney shape prior and on-going kidney-background visual appearances. A B-spline-based three-dimensional data alignment is employed to handle local deviations due to breathing and heart beating. Then, empirical cumulative distribution functions of apparent diffusion coefficients of the segmented DW-MRI at different b-values are collected as discriminatory transplant status features. Finally, a deep-learning-based classifier with stacked nonnegative constrained autoencoders is employed to distinguish between rejected and nonrejected renal transplants. RESULTS: In our initial "leave-one-subject-out" experiment on 100 subjects, [Formula: see text] of the subjects were correctly classified. The subsequent four-fold and ten-fold cross-validations gave the average accuracy of [Formula: see text] and [Formula: see text], respectively. CONCLUSION: These results demonstrate the promise of this new CAD system to reliably diagnose renal transplant rejection. SIGNIFICANCE: The technology presented here can significantly impact the quality of care of renal transplant patients since it has the potential to replace the gold standard in kidney diagnosis, biopsy.

Automated Diagnosis and Grading of Diabetic Retinopathy Using Optical Coherence Tomography.

Purpose: We determine the feasibility and accuracy of a computer-assisted diagnostic (CAD) system to diagnose and grade nonproliferative diabetic retinopathy (NPDR) from optical coherence tomography (OCT) images. Methods: A cross-sectional, single-center study was done of type II diabetics who presented for routine screening and/or monitoring exams. Inclusion criteria were age 18 or older, diagnosis of diabetes mellitus type II, and clear media allowing for OCT imaging. Exclusion criteria were inability to image the macula, posterior staphylomas, proliferative diabetic retinopathy, and concurrent retinovascular disease. All patients underwent a full dilated eye exam and spectral-domain OCT of a 6 × 6 mm area of the macula in both eyes. These images then were analyzed by a novel CAD system that segments the retina into 12 layers; quantifies the reflectivity, curvature, and thickness of each layer; and ultimately uses this information to train a neural network that classifies images as either normal or having NPDR, and then further grades the level of retinopathy. A first dataset was tested by "leave-one-subject-out" (LOSO) methods and by 2- and 4-fold cross-validation. The system then was tested on a second, independent dataset. Results: Using LOSO experiments on a dataset of images from 80 patients, the proposed CAD system distinguished normal from NPDR subjects with 93.8% accuracy (sensitivity = 92.5%, specificity = 95%) and achieved 97.4% correct classification between subclinical and mild/moderate DR. When tested on an independent dataset of 40 patients, the proposed system distinguished between normal and NPDR subjects with 92.5% accuracy and between subclinical and mild/moderate NPDR with 95% accuracy. Conclusions: A CAD system for automated diagnosis of NPDR based on macular OCT images from type II diabetics is feasible, reliable, and accurate.

A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury.

Voluntary movements and the standing of spinal cord injured patients have been facilitated using lumbosacral spinal cord epidural stimulation (scES). Identifying the appropriate stimulation parameters (intensity, frequency and anode/cathode assignment) is an arduous task and requires extensive mapping of the spinal cord using evoked potentials. Effective visualization and detection of muscle evoked potentials induced by scES from the recorded electromyography (EMG) signals is critical to identify the optimal configurations and the effects of specific scES parameters on muscle activation. The purpose of this work was to develop a novel approach to automatically detect the occurrence of evoked potentials, quantify the attributes of the signal and visualize the effects across a high number of scES parameters. This new method is designed to automate the current process for performing this task, which has been accomplished manually by data analysts through observation of raw EMG signals, a process that is laborious and time-consuming as well as prone to human errors. The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. In comparing the automatic method vs. manual detection on 700 EMG signals from five individuals, the new approach decreased the processing time from several hours to less than 15 seconds for each set of data, and demonstrated an average accuracy of 98.28% based on the combined false positive and false negative error rates. The sensitivity of this method to the signal-to-noise ratio (SNR) was tested using simulated EMG signals and compared to two existing methods, where the novel technique showed much lower sensitivity to the SNR.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey.

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Transcriptional profile of immediate response to ionizing radiation exposure.

Astronauts participating in long duration space missions are likely to be exposed to ionizing radiation associated with highly energetic and charged heavy particles. Previously proposed gene biomarkers for radiation exposure include phosphorylated H2A Histone Family, Member X (γH2AX), Tumor Protein 53 (TP53), and Cyclin-Dependent Kinase Inhibitor 1A (CDKN1A). However, transcripts of these genes may not be the most suitable biomarkers for radiation exposure due to a lack of sensitivity or specificity. As part of a larger effort to develop lab-on-a-chip methods for detecting radiation exposure events using blood samples, we designed a dose-course microarray study in order to determine coding and non-coding RNA transcripts undergoing differential expression immediately following radiation exposure. The main goal was to elicit a small set of sensitive and specific radiation exposure biomarkers at low, medium, and high levels of ionizing radiation exposure. Four separate levels of radiation were considered: 0 Gray (Gy) control; 0.3 Gy; 1.5 Gy; and 3.0 Gy with four replicates at each radiation level. This report includes raw gene expression data files from the resulting microarray experiments from all three radiation levels ranging from a lower, typical exposure than an astronaut might see (0.3 Gy) to high, potentially lethal, levels of radiation (3.0 Gy). The data described here is available in NCBI's Gene Expression Omnibus (GEO), accession GSE64375.

Release-Modulated Antioxidant Activity of a Composite Curcumin-Chitosan Polymer.

Curcumin is known to have immense therapeutic potential but is hindered by poor solubility and rapid degradation in solution. To overcome these shortcomings, curcumin has been conjugated to chitosan through a pendant glutaric anhydride linker using amide bond coupling chemistry. The hybrid polymer has been characterized by UV-visible, fluorescence, and infrared spectroscopies as well as zeta potential measurements and SEM imaging. The conjugation reactivity was confirmed through gel permeation chromatography and quantification of unconjugated curcumin. An analogous reaction of curcumin with glucosamine, a small molecule analogue for chitosan, was performed and the purified product characterized by mass spectrometry, UV-visible, fluorescence, and infrared spectroscopies. Conjugation of curcumin to chitosan has greatly improved curcumin aqueous solubility and stability, with no significant curcumin degradation detected after one month in solution. The absorbance and fluorescence properties of curcumin are minimally perturbed (λmax shifts of 2 and 5 nm, respectively) by the conjugation reaction. This conjugation strategy required use of one out of two curcumin phenols (one of the main antioxidant functional groups) for covalent linkage to chitosan, thus temporarily attenuating its antioxidant capacity. Hydrolysis-based release of curcumin from the polymer, however, is accompanied by full restoration of curcumin's antioxidant potential. Antioxidant assays show that curcumin radical scavenging potential is reduced by 40% after conjugation, but that full antioxidant potential is restored upon hydrolytic release from chitosan. Release studies show that curcumin is released over 19 days from the polymer and maintains a concentration of 0.23 ± 0.12 µM curcumin/mg polymer/mL solution based on 1% curcumin loading on the polymer. Release studies in the presence of carbonic anhydrase, an enzyme with known phenolic esterase activity, show no significant difference from nonenzymatic release studies, implying that simple ester hydrolysis is the dominant release mechanism. Conjugation of curcumin to chitosan through a phenol ester modification provides improved stability and solubility to curcumin, with ester hydrolysis restoring the full antioxidant potential of curcumin.

An orbital shear platform for real-time, in vitro endothelium characterization.

Electrical impedance techniques have been used to characterize endothelium morphology, permeability, and motility in vitro. However, these impedance platforms have been limited to either static endothelium studies and/or induced laminar fluid flow at a constant, single shear stress value. In this work, we present a microfabricated impedance sensor for real-time, in vitro characterization of human umbilical vein endothelial cells (HUVECs) undergoing oscillatory hydrodynamic shear. Oscillatory shear was applied with an orbital shaker and the electrical impedance was measured by a microfabricated impedance chip with discrete electrodes positioned at radial locations of 0, 2.5, 5.0, 7.5, 10.0, and 12.5 mm from the center of the chip. Depending on their radial position within the circular orbital platform, HUVECs were exposed to shear values ranging between 0.6 and 6.71 dyne/cm(2) (according to numerical simulations) for 22 h. Impedance spectra were fit to an equivalent circuit model and the trans-endothelial resistance and monolayer's capacitance were extracted. Results demonstrated that, compared to measurements acquired before the onset of shear, cells at the center of the platform that experienced low steady shear stress (∼2.2 dyne/cm(2) ) had an average change in trans-endothelial resistance of 6.99 ± 4.06% and 1.78 ± 2.40% change in cell capacitance after 22 hours of shear exposure; cells near the periphery of the well (r = 12.5 mm) experienced transient shears (2.5-6.7 dyne/cm(2) ) and exhibited a greater change in trans-endothelial resistance (24.2 ± 10.8%) and cell capacitance (4.57 ± 5.39%). This study, demonstrates that the orbital shear platform provides a simple system that can capture and quantify the real-time cellular morphology as a result of induced shear stress. The orbital shear platform presented in this work, compared to traditional laminar platforms, subjects cells to more physiologically relevant oscillatory shear as well as exposes the sample to several shear values simultaneously. Biotechnol. Bioeng. 2016;113: 1336-1344. © 2015 Wiley Periodicals, Inc.

Prescribed 3-D Direct Writing of Suspended Micron/Sub-micron Scale Fiber Structures via a Robotic Dispensing System.

A 3-axis dispensing system is utilized to control the initiating and terminating fiber positions and trajectory via the dispensing software. The polymer fiber length and orientation is defined by the spatial positioning of the dispensing system 3-axis stages. The fiber diameter is defined by the prescribed dispense time of the dispensing system valve, the feed rate (the speed at which the stage traverses from an initiating to a terminating position), the gauge diameter of the dispensing tip, the viscosity and surface tension of the polymer solution, and the programmed drawing length. The stage feed rate affects the polymer solution's evaporation rate and capillary breakup of the filaments. The dispensing system consists of a pneumatic valve controller, a droplet-dispensing valve and a dispensing tip. Characterization of the direct write process to determine the optimum combination of factors leads to repeatedly acquiring the desired range of fiber diameters. The advantage of this robotic dispensing system is the ease of obtaining a precise range of micron/sub-micron fibers onto a desired, programmed location via automated process control. Here, the discussed self-assembled micron/sub-micron scale 3D structures have been employed to fabricate suspended structures to create micron/sub-micron fluidic devices and bioengineered scaffolds.

A high yield, one-pot dialysis-based process for self-assembly of near infrared absorbing gold nanoparticles.

HYPOTHESIS: A facile, dialysis-based synthesis of stable near infrared (nIR) absorbing plasmonic gold nanoparticles (λmax=650-1000 nm) will increase the yield of nIR particles and reduce the amount of gold colloid contaminant in the product mixture. EXPERIMENTS: Chloroauric acid and sodium thiosulfate were reacted using a dialysis membrane as a reaction vessel. Product yield and composition was determined and compared to traditional synthesis methods. The product particle distribution, yield, and partitioning of gold between dispersed product and membrane-adsorbed gold were determined. FINDINGS: The synthesis results in polydisperse particle suspensions comprised of 70% spheroid-like particles, 27% triangular plates, and 3% rod-like structures with a 3% batch-to-batch variation and a prominent nIR absorption band with λmax=650-1000 nm. The amount of small gold colloid (λmax=530 nm; d<10 nm) in the isolated product was reduced by 96% compared to traditional methods. Additionally, 91.1% of the gold starting material is retained in the solution-based nanoparticle mixture while 8.2% is found on the dialysis membrane. The synthesis results in a quality ratio (QR=Abs(nIR)/Abs(530)) of 1.7-2.4 (twice that of previous techniques) and 14.3 times greater OD∗ml yield of the nIR-absorbing nanoparticle fraction.

Electrochemical dissolved oxygen removal from microfluidic streams for LOC sample pretreatment.

Current water quality monitoring for heavy metal contaminants largely results in analytical snapshots at a particular time and place. Therefore, we have been interested in miniaturized and inexpensive sensors suitable for long-term, real-time monitoring of the drinking water distribution grid, industrial wastewater effluents, and even rivers and lakes. Among the biggest challenges for such sensors are the issues of in-field device calibration and sample pretreatment. Previously, we have demonstrated use of coulometric stripping analysis for calibration-free determination of copper and mercury. For more negatively reduced metals, O2 reduction interferes with stripping analysis; hence, most electroanalysis techniques rely on pretreatments to remove dissolved oxygen (DO). Current strategies for portable DO removal offer limited practicality, because of their complexity, and often cause inadvertent sample alterations. Therefore, we have designed an indirect in-line electrochemical DO removal device (EDOR), utilizing a silver cathode to reduce DO in a chamber that is fluidically isolated from the sample stream by an O2-permeable membrane. The resulting concentration gradient supports passive DO diffusion from the sample stream into the deoxygenation chamber. The DO levels in the sample stream were determined by cyclic voltammetry (CV) and amperometry at a custom thin-layer cell (TLC) detector. Results show removal of 98% of the DO in a test sample at flow rates approaching 50 µL/min and power consumption as low as 165 mW h L(-1) at steady state. Besides our specific stripping application, this device is well-suited for LOC applications where miniaturized DO removal and/or regulation are desirable.

Electrochemical and microfabrication strategies for remotely operated smart chemical sensors: application of anodic stripping coulometry to calibration-free measurements of copper and mercury.

Remote unattended sensor networks are increasingly sought after to monitor the drinking water distribution grid, industrial wastewater effluents, and even rivers and lakes. One of the biggest challenges for application of such sensors is the issue of in-field device calibration. With this challenge in mind, we report here the use of anodic stripping coulometry (ASC) as the basis of a calibration-free micro-fabricated electrochemical sensor (CF-MES) for heavy metal determinations. The sensor platform consisted of a photo-lithographically patterned gold working electrode on SiO2 substrate, which was housed within a custom stopped-flow thin-layer cell, with a total volume of 2-4 µL. The behavior of this platform was characterized by fluorescent particle microscopy and electrochemical studies utilizing Fe(CN)6(3-/4-) as a model analyte. The average charge obtained for oxidation of 500 µM ferrocyanide after 60s over a 10 month period was 176 µC, corresponding to a volume of 3.65 µL (RSD = 2.4%). The response of the platform to copper concentrations ranging from 50 to 7500 ppb was evaluated, and the ASC results showed a linear dependence of charge on copper concentrations with excellent reproducibility (RSD ≤ 2.5%) and accuracy for most concentrations (≤ 5-10% error). The platform was also used to determine copper and mercury mixtures, where the total metallic content was measurable with excellent reproducibility (RSD ≤ 4%) and accuracy (≤ 6% error).

Enhanced drug delivery via hyperthermal membrane disruption using targeted gold nanoparticles with PEGylated Protein-G as a cofactor.

Gold nanoparticles (GNPs) with near infrared (NIR) plasmon resonance have been promisingly used in photothermal cancer therapy as a less invasive treatment. Recombinant Protein-G (ProG) was PEGylated to act as a cofactor to immobilize immunoglobulins (IgGs) on GNPs by the Fc region, resulting in optimal orientation of IgGs for efficient cancer targeting. In-vitro studies showed that HER-2 overexpressing breast cancer cells, SK-BR-3, were efficiently targeted and ablated at a laser power of 900 J/cm(2) (5 W/cm(2) for 3 min). However, as a means of enhancing treatment efficacy by increasing cellular sensitivity to chemotherapeutic agents, we showed that GNP exposure to lower power laser resulted in small disruptions of cell membrane due to localized hyperthermia. This did not lead to cell death but provided a mechanism for killing cancer cells by providing enhanced uptake of drug molecules thus leading to a new avenue for hyperthermia-anticancer drug combined cancer therapeutics. FROM THE CLINICAL EDITOR: PEGylated recombinant Protein-G was used as a cofactor to optimize the orientation of IgGs providing "target seeking" properties to gold nanoparticles used in photothermal cancer therapy. The system demonstrated excellent properties in cancer therapy, with the hope and expectation of future clinical translation.