Silicon Nanosensor for Diagnosis of Cardiovascular Proteomic Markers

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460038 ournal of Laboratory AutomationPrasad et al. 2012

JLAXXX10.1177/2211068212460038J

Original Report

Silicon Nanosensor for Diagnosis of Cardiovascular Proteomic Markers

Journal of Laboratory Automation 18(2) 143­–151 © 2012 Society for Laboratory Automation and Screening DOI: 10.1177/2211068212460038 jala.sagepub.com

Shalini Prasad1, Anjan Panneer Selvam1, Ravikiran K. Reddy2, and Adrian Love3

Abstract A silicon nanosensor technology based on electrical impedance measurements has been developed for the detection of proteins. The nanosensor miniaturizes the high-density, low-volume multiwell plate concept. The scientific core of this technology lies in integrating nanoporous membranes with microfabricated chip platforms.This results in the conversion of individual pores into nanowells of picoliter volume. Monoclonal antibodies were localized and isolated into individual wells. Detection of two cardiac proteomic biomarkers has been demonstrated with this technology.The two proteins, C-reactive protein and NT-pro–brain natriuretic peptide (BNP), are associated with adverse cardiac outcomes in clinical samples when detected in the pg/mL concentration.The formation of the antibody-antigen binding complex occurs in individual wells.The membrane allows for robust separation among individual wells. This technology has the capability to achieve near real-time detection with improved sensitivity at 1 ag/mL for BNP and 1 fg/mL for CRP from human serum. Keywords cardiac protein biomarkers, clinical diagnostics assay, impedance measurements, electrical protein sensor

Introduction One hundred thousand patients undergo surgery daily in the United States, 33 million annually, at a cost of $450 billion.1 C-reactive protein (CRP) and NT-pro–brain natriuretic peptide (BNP) have been associated with increased mortality after vascular surgery.2–7 Several large-scale population studies have demonstrated that CRP profiling has improved the prediction of the first cardiovascular event.8–10 The use of proteomic tools to create molecular signatures of disease is a recent development in the domain of disease diagnostics. Enzyme-linked immunosorbent assay (ELISA) is the gold standard in protein-based diagnostics.11,12 In recent times, the sensitivity of ELISA assays has been enhanced by attaching the antibodies that are necessary for a sandwich immunoassay to microbeads instead of microplate wells. Since microbeads offer a large spherical surface area, antibodies immobilized on this surface are more clustered than the same concentration of antibodies attached to a 2D plate well. In addition, recent research has indicated that to enhance the sensitivity of a proteomic assay, in vitro detection systems must mimic the protein microenvironment within a cell. Inside the cell, the correct folding of many proteins depends on the preexisting protein machinery called molecular chaperones.13 This provides a certain level of spatial confinement, providing the former with a “cage” structure

with confined volume. Crowding prevents the self-assembly of partly folded polypeptide chains; this is characterized as aggregation in the in vitro studies.14–16 Confinement appears to stabilize proteins and accelerate their folding significantly.17 Thus, it would slow down the unfolding of proteins that are known to cause denaturization of the protein structures and cause them to lose their functionality.18–22 From the above discussion, it would seem useful to provide a very small confined area in which the proteins could be detected. For this purpose, a nanoporous alumina membrane was chosen to be embedded on the surface of the metal electrodes. These small wells of 200 nm diameter would provide small reaction wells and improve the stability of the reactions.

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Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA 2 Department of Electrical Engineering, Portland State University, Portland, OR, USA 3 Department of Electrical Engineering, Wichita State University, Wichita, KS, USA Received Jun 18, 2012. Corresponding Author: Shalini Prasad, PhD, Department of Bioengineering, University of Texas at Dallas, 800 W Campbell Road, EC 39, Richardson, TX 75080, USA. Email: [email protected]

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New diagnostics technologies leveraging the concept of nanoconfinement detect protein biomolecules with electrical signal transduction mechanisms to quantify the biomolecular recognition event. Electrical detection is usually based on the interaction of a biomolecule recognition element with the analyte target, resulting in a measurable change in a solution property, such as the formation of a measurable product or consumption of a measurable reactant. The transducer converts this change in solution property into a quantifiable electrical signal. In electrical detection achieved through impedance spectrometry,23,24 an alternating current (AC) potential is applied at a range of frequencies, and the resulting current and phase shift are used to calculate the circuit impedance. Electrical impedance spectroscopy (EIS) can provide great sensitivity and has the potential to be used in a label-free manner. Impedance biosensors measure the electrical impedance of an interface in AC steady state by imposing a small sinusoidal voltage at a particular frequency and measuring the resulting current. The impedance that is given by the resulting current is to the voltage ratio, which, when repeated at different frequencies, is called AC impedance EIS. This form of EIS has been used to study electrochemical phenomena (mostly affinity) of various biological interactions.24 Changes in the amplitude and phase of the sinusoidal signal measured at a particular frequency reflect binding of a particular target-molecular recognition element pair,25 which reduces the number of reagents required for detection, simplifies the sample processing, and allows for a more rapid detection of the analyte of interest. EIS is a rapid, sensitive technique that has been heavily employed for biosensor signal transduction. Hence, in this article, EIS has been implemented onto the nanosensor platform for labelfree detection of C-reactive protein and NT-pro–BNP. CRP and BNP are primarily quantified in lab-on-a chip devices through fluorescence-based immunoassays. These devices are used for point-of-care testing and have a limit of detection at 500 ng/mL.26 Other nanoscale label-based methods such as quantum dot–based quantification have lower detection limits at 200 pg/mL and require approximately 2 h for detection.27 Micro- and nanoscale methods for label-free detection reduce reagent use and dependence on labels. A piezoresistive self-sensing micro-cantilever has demonstrated the detection of CRP at 100 ng/mL, but the system showed a significant amount of background noise and signal fluctuation.28 Surface plasmon resonance and nanobeads have been used in conjunction to detect BNP at concentrations of 25 pg/mL using primary and secondary antibodies.29 Use of micro-magnetic particles for detection of BNP has been demonstrated using biotin-streptavidin chemistry, and these systems have shown lower detection limits of 10 pg/mL.30,31 Label-free impedance biosensors offer ease of miniaturization and are best suitable for pointof-care diagnostic devices.32 The demonstrated impedancebased nanosensor in this study performs detection of BNP

and CRP at concentrations of 1 fg/mL and 1 ag/mL, much lower than previously demonstrated methods. Detection of these proteins at less than 100 pg/mL is essential for predicting cardiac event effects and to be of clinical relevance.33 Hence, the nanosensor technique demonstrated in this article has the potential for technological adoption as a clinical point-of-care assay. The goal of this article is to demonstrate the design of a diagnostic device that leverages the symmetry, reproducibility, and periodicity of nanoporous alumina manufactured through electrochemical oxidation processes and integrates it with silicon microelectronics to generate robust ultra-porous devices suitable for rapid proteomic diagnostics of clinical samples. These diagnostics devices have been applied for detection of CRP and NT-pro–BNP from human serum samples.

Materials and Methods Design of the Nanosensor Device The nanosensor comprised two parts. The first was the silicon micro-fabricated platform; the second was the nanoporous membrane implanted on the platform with a polymer manifold encapsulant. Micro-fabricated platform. The fabrication process required four steps and used one optical mask. (1) A polished silicon wafer (4-inch diameter and 500 µm thick) with a thermally deposited oxide that functioned as the dielectric was used as the base platform. The dielectric provided electrical isolation among sensing sites. (2) Sensing sites were defined using standard mask-based photolithography techniques. (3) By thin-film deposition techniques, a chrome (20-nm) adhesion layer and a gold (150-nm) measurement layer were deposited. The gold layer was laid over the chrome layer. (4) Finally, using wet etching techniques, the sensing sites were physically isolated. This formed the base of the nanosensor. Figure 1 is the representation of the base micro-fabricated platform. Nanoporous membrane. The nanoporous alumina is the second part of the nanosensor. The gold surface was first protected with a 20-nm-thick etch stop layer of silicon nitride that protected the gold from the acid etch that was used for the electrochemical anodization of aluminum. A 250-nmthick layer of aluminum film was thermally evaporated onto the microelectrode platform. This acted as the anode for the two-step anodization process required for fabricating the nanopores. The cathode was a platinum wire. Both the anode and cathode were immersed in an electrochemical bath. A constant voltage of 45V and a constant current density of 20 mA/cm2 were applied across the electrodes. A mixture of 0.1M sulfuric acid and 0.4M oxalic acid was used as the electrolyte to obtain a uniform structure of the pores. The conditions for the electrochemical bath were optimized to get a

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Figure 1. (A) Schematic representation of the physical isolation of the eight sensing sites. (B) Optical micrograph of the micro-fabricated platform. (C) Schematic representation of the geometry of the electrode leads from each sensing site. (D) Optical micrograph indicating the working and counter electrode on a single sensing site. The counter electrode is 10 times larger than the working electrode. (E) Schematic showing the polydimethylsiloxane chamber enclosing the nanosensor.

uniform pore size of 200 nm.34 The anodization process parameters were optimized to ensure that anodization was stopped at the etch stop layer. The etch stop layer was then selectively removed using deep reactive ion etching (Alcatel 601 DRIE, Alcatel Micro Machining Systems, Annecy, France) to expose the gold surface. Hence, the alumina pores were designed such that the base of each pore comprised the gold substrate. These pores formed the nanowells of the nanosensor. The entire sensor surface was encapsulated with a polydimethylsiloxane manifold with a single inlet and outlet holding a sample volume of 150 µL. Hence, physically the nanosensor was a miniaturized microwell plate that contained picoliter volume per well.

Principle of Operation The nanosensor (Fig. 2) worked on the principle of doublelayer capacitance measurement. In other electrochemical methods of measurement, such as transconductance and conductance methods, the measurements are limited by the need for redox reactions at the surface for optimal charge

transfer. This makes the reactions hard to control and regulate. The nonfaradic impedance due to the capacitance of the electrical double layer formed at the electrode surface is sensitive to reactions and is the basis of nanosensor measurement. This technique is advantageous since it does not require addition of any redox probes. Furthermore, impedance measurements at different bias voltages and frequencies can reveal much information about dielectric and charge environment at the interface. The nanosensors comprised multiple sensing sites with each sensing site containing approximately a quarter million nanowells. The physical dimensions of the nanowell (200 nm wide and 250 nm deep) were controlled during the fabrication process such that a select amount of antibody was trapped in an individual nanowell. So, theoretically, at antibody saturation, a high density of antibodies is trapped on a single sensing site.35 In the nanowells, inoculated antibodies (size: 1–10 nm) flowed to the bottom of the well due to capillary forces and fell within the inner Helmholtz layer of the double layer, thereby causing a perturbation and producing a change in

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Figure 2. (A) Optical micrograph of the nanomonitor. (B) Combination image of a single sensing site: the base is an optical micrograph and the nanoporous membrane is a scanning electron micrograph (SEM). (C) SEM image of the trapped protein within a nanopore. (D) Schematic representation of the immunocomplex formation on the combination image.

the capacitance. The charge associated with the antibody modified the double layer. When the antigen was added to the sensing site, this further modified the interface, and the formation of the immunocomplex changed the charge distribution, causing a change in the capacitance at the interface (Fig. 3). Each nanowell was located on the precharged sensing site. Since so many wells were interrogated simultaneously, this would improve the signal-to-noise ratio. Individual nanowells with trapped biomolecules are electrically equivalent to multiple capacitors connected in parallel. Hence, the equivalent impedance obtained from a single sensing site was the sum of the individual capacitors associated with each nanowell. This resulted in signal amplification, which was relevant during the detection of lower concentration (less than 10 ng/mL), which in turn improved the limit of detection. In addition, as the capacitance was averaged over multiple nanowells, this reduced the variability in measurement during the testing of replicates, thus improving the robustness of the nanosensor technology. The impedance was measured from each sensing site. Each site comprised a counter and working electrode, and the capacitance change was translated into an impedance change as measured from the working electrode with respect to the counter electrode. The two electrodes were connected to an impedance analyzer (Ref 600 Potentiostat; Gamry, Warminster, PA) that directly

measured the capacitance values, which have been represented as impedance changes.

Assay Samples To establish the validity of the nanosensor technology, two types of samples for CRP and NT-pro–BNP were investigated. The samples used antibodies in their purified form at 10 µg/mL, which has been identified as the saturation concentration of the nanosensor device. The antigen was added to sterile and filtered human serum obtained from human plasma (Sigma-Aldrich, St. Louis, MO). The aliquots were spiked with the protein corresponding to the individual points of the dose-response curve. Immobilization of proteins (antigens) was done using specific protein receptors (antibodies). This biosensor used the affinity of these antigens to the antibodies to detect the presence of the antigens. Commercially available human serum CRP (hs-CRP), NT-pro–BNP (BNP), and anti-CRP and anti-BNP were purchased from Abcam (Cambridge, UK; ab32412 and ab19646). The antibodies were aliquoted into a range of dilutions using phosphate-buffered saline (PBS), which was purchased from Pierce (Rockford, IL; 0028372). Dithiobis succinimidyl propionate (DSP) from Pierce (22585) was used to immobilize the antibodies within the nanowells. DSP was mixed with

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capacitance, which was translated into impedance changes as obtained from the EIS measurement setup. To provide a better understanding of the magnitude of capacitance changes in the electrical double layer associated with biomolecule binding, we have represented one set of results as capacitance changes. All experimental data were obtained from three independent chips. Five replicates were measured on each chip, and three independent chips were evaluated for each experiment. Hence, the data set represented has been obtained from 15 separate measurements. The coefficient of variance for the sensor response has been represented as standard error of the mean in all the data plots.

Results Figure 3. Schematic representation of the principle of electrochemical capacitance measurement from an individual nanowell. The covalent linker chemistry explained in experimental design has been represented as shown above. DSP, dithiobis succinimidyl propionate.

DMSO to obtain a 10-mM concentration. DMSO was used as a solvent to cleave the S-S bond in DSP and enabled the binding of the thiol group to the gold surface and left the amine end for the antibody-linker covalent interaction. The assembled biosensor was washed using 150 µL PBS to obtain the initial wet test readings to establish the electrical impedance baseline. The sensing site was then incubated for 30 min with the 10-mM DSP linker diluted in DMSO. Three times (3×) PBS wash was followed to extract the unbounded linker from the sensing surface. Then, 150 µL of 10 µg/mL antibody (either anti-CRP or anti-BNP) was used to incubate the biosensor for 15 min; this concentration was identified as the dose that saturated the sensing site.36 The 3× PBS wash step was carried out to extract the unbound antibody. Blocking agent (SuperBlock, Thermo Scientific Protein Research Products, Rockford, IL; 150 µL) was then injected onto the electrode surface to prevent the nonspecific binding of the antigen. The sensing site was then washed using 3× PBS after the 15-min blocking agent incubation. Finally, the protein concentrations for NT-pro–BNP (ranging from 1 ag/mL to 1 µg/mL) and for CRP (ranging from 1 fg/mL to 100 pg/mL) were tested. Each concentration was incubated for 15 min and followed by the 3× PBS wash step. Figure 3 shows the schematic flow of the antibody-antigen binding interaction along with the presence of the DSP linker chemistry, in the presence of PBS solution. The double-layer capacitance was characterized using EIS. The data were acquired using Reference 600 (Gamry) with an input AC voltage at 10 mV swept from 50 Hz to 5 kHz, and the effective change in the impedance was plotted against the frequency range.36 The antigen dose response was obtained by measuring the changes to the double-layer

In this section, the sensor performance in detecting NT-pro– BNP and CRP is demonstrated. Two sets of data are represented in this section. The first data set demonstrates the identification of the antibody saturation dose for anti-BNP and anti-CRP. The second set of data shows the sensor dose response in detecting a range of doses of the two target proteins from human serum. The sensor performance metrics were identified based on the sensor performance.

Control Experiments Control experiments were performed to electrically establish surface functionalization of the nanosensor for protein detection. Baseline impedance measurements were obtained for the electrochemical impedance spectroscopy operation parameters from (a) the dry nanosensor, (b) the nanosensor incubated with 0.15M phosphate-buffered saline in the absence of DSP functionalization, and (c) the nanosensor after DSP functionalization and (d) after incubation with SuperBlock. A stepwise decrease in impedance was obtained, which demonstrated the functionalization of the nanosensor surface for protein detection. Figure 4 shows the impedance changes measured from the nanosensor surface for each of the preparation steps detailed above.

Antibody Saturation Study The antibody saturation study is a critical experiment in priming the sensor surface. The assay for measuring the presence of the two target proteins was achieved in an electrical immunoassay format. This format entailed the immobilization of the antibody onto the sensor surface. The antibody receptors enabled the antigen-antibody interactions resulting in protein detection. Saturating the sensor surface with the antibody was critical to minimize nonspecific binding of other biomolecules onto the sensor. Antibody saturation dose was determined empirically by testing varying doses of the antibody ranging from 10 pg/ mL to 100 µg/mL onto the sensor surface in a serial manner.

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Figure 4. Control study demonstrating the changes to the impedance of the nanosensor for the various preparatory steps of the immunoassay. The changes to the impedance values observed at different points of the assay prior to antigen dose-response study have been shown. BNP, brain natriuretic peptide; DSP, dithiobis succinimidyl propionate.

The impedance changes from the PBS baseline were measured after each dose of the antibody was incubated onto the sensor chip. A sequential increase to the percentage change in the impedance was measured. Impedance changes saturated for NT-pro–BNP antibodies for doses >1 µg/mL. The NT-pro–BNP antibody saturation graph is shown in Figure 5A. Impedance changes ranged from 0% to 40% from the PBS baseline over the dose range. The measured

impedance changes ranged from 135 to 90 ohms. The R2 value was 0.93, indicating linearity in the response. For CRP antibody, doses from 1 ng/mL to100 µg/mL were tested in a serial manner on the sensor surface. The impedance changes from the PBS baseline were measured after each dose of the antibody was incubated onto the sensor chip. A sequential increase to the percentage change in the impedance was measured. Impedance changes saturated for CRP antibodies for doses >10 µg/mL. Although saturation in the measured impedance values was not obtained at doses greater than 10 µg/mL, the rate of change in impedance was significantly minimized and hence was found suitable for antibody saturation. The CRP antibody saturation graph is shown in Figure 5B. Impedance changes ranged from 0% to 45% from the PBS baseline over the dose range. The measured impedance changes ranged from 146 to 78 ohms. The R2 value was 0.98, indicating linearity in the response over the dose range.

NT-Pro–BNP and CRP Dose-Response Study The next step was to determine the lowest concentration of the specific antigen that could be detected accurately in replicates. The parameter that was monitored in the measurement technique was the electrochemical impedance. Using the nanosensor immunoassay technique, we were able to detect BNP and CRP with the present lower limit of detection at 1 ag/mL and 1 fg/mL, respectively. The data presented in this section were obtained from three independent interassay measurements. The variability in the measurement is statistically insignificant; error has been

Figure 5. Antibody saturation study. Impedance decreases (percent change increases) as the concentration of antibody increases, implying nanowell saturation with antibody. (A) Anti–brain natriuretic peptide (BNP) saturation study; impedance value decreases significantly for doses >1 µg/mL, after which saturation is observed. (B) Ab saturation concentration for anti–C-reactive protein (CRP); impedance decreases through all concentrations in the study.The percentage change in impedance is significantly less at 10 µg/mL, and this is chosen as the saturating concentration.

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Figure 6. Representation of the antigen dose-response studies of brain natriuretic peptide (BNP) and C-reactive protein (CRP) with their respective antibodies. The dynamic range of detection of antigens has been demonstrated. Enhanced sensitivity in detection is due to nanoconfinement offered by the nanoporous alumina membrane. Graph indicates lower limit of detection for the nanosensor as (A) 1 ag/mL for BNP and (B) 1 fg/mL for CRP.

represented as the standard error of mean and is less than 1%. The dynamic range was 1 ag/mL to 10 µg/mL for BNP and 1 fg/mL to 100 pg/mL for CRP. The impedance change for BNP over the dose range was from 125.35 to 47.49 ohms. This resulted in a percentage change in impedance from the antibody saturation base line (at 149.25 ohms) from 25% to 68% with an R2 value of 0.91. The impedance change for CRP over the dose range was from 97.31 to 59.77 ohms, resulting in a percentage change from the antibody saturation base line (108.73 ohms) from 27% to 55% with an R2 value of 0.96. Each sensing site consisted of the working and counter electrode and supported 2 million nanowells. The variation of the impedance was measured across these two electrodes. Antigen aliquots at varying concentrations in commercial human serum were inoculated onto separate antibody-saturated sensing sites. After an incubation period of 15 min to enable antigen adsorption and the formation of the immunocomplex, the change in the conductance was measured with respect to the conductance associated with antibody saturation. Due to the formation of the immunocomplex, the charges at the solid-liquid interface were modulated, and this resulted in a change in the measured impedance. The lower limit of detection is the concentration value at which there is either zero or almost negligible change in the impedance from the baseline. Figure 6A,B demonstrates the dynamic range for the two study antigens (BNP and CRP) in human serum.

Discussion The overall outcome from the silicon nanosensor technology is the demonstration of a technology with improved speed in

detection with performance metrics that indicate its potential application in the clinical environment for protein biomarker detection. The improved performance is attributed to the effect of spatial confinement of proteins similar to in vitro cell environments. We have previously shown how this effect can help in effective signal amplification and detection.35 Protein immunoassays are inherently limited in terms of the number of proteins that can be simultaneously detected from one assay due to the issue of nonspecific binding. This problem can only be minimized but not totally overcome. This, in turn, limits the number of protein biomarkers that can be simultaneously detected from a multiplexed assay. In the current application, we are using monoclonal antibodies to eliminate cross-reactivity among the study protein biomarkers: BNP and CRP. We have not observed any crossreactivity among the two study proteins. The future focus will be on the design of cost-effective multiplexed electrical proteomic immunoassays, leveraging the principle of nanoconfinement as offered by the architecture of the nanosensor technology. In conclusion, a highly sensitive device for protein detection was designed and fabricated. This nanosensor has several advantages over the existing electrical immunoassays: (a) It is label free without the use of a redox probe, and hence risk of contamination is reduced, and (b) it has a high potential for being developed into a portable device. The novelty is the design of the nanosensor that demonstrates successful heterogeneous integration of nanoporous material with microelectronic platforms. The nanosensor has demonstrated sensitivity in detecting two cardiac protein biomarkers, CRP at 1 fg/mL and BNP at 1 ag/mL sensitivity. Linearity in the sensor dose response has been achieved

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over the dose regimes evaluated. The nanosensor technology has potential applicability in low-resource settings as a screening/diagnostics tool for disease diagnosis based on quantitatively evaluating test protein biomarkers. Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this project was through the Office of Naval Research (grant number: N00014-07-1-0457).

References 1. Mangano, D. T. Perioperative Medicine: NHLBI Working Group Deliberations and Recommendations. J. Cardiothorac. Vasc. Anesth. 2004, 18(1), 1–6. 2. Goei, D.; Hoeks, S. E.; Boersma, E.; Winkel, T. A.; Dunkelgrun, M.; Flu, W.-J.; Schouten, O.; Bax, J. J.; Poldermans, D. Incremental Value of High-Sensitivity C-reactive Protein and N-terminal Pro-B-type Natriuretic Peptide for the Prediction of Postoperative Cardiac Events in Noncardiac Vascular Surgery Patients. Coronary Artery Dis. 2009, 20(3), 219–224. 3. Landesberg, G.; Shatz, V.; Akopnik, I.; Wolf, Y. G.; Mayer, M.; Berlatzky, Y.; Weissman, C.; Mosseri, M. Association of Cardiac Troponin, CK-MB, and Postoperative Myocardial Ischemia with Long-Term Survival after Major Vascular Surgery. J. Am. Coll. Cardiol. 2003, 42(9), 1547–1554. 4. Levy, M.; Heels-Ansdell, D.; Hiralal, R.; Bhandari, M.; Guyatt, G.; Yusuf, S.; Cook, D.; Villar, J. C.; McQueen, M.; McFalls, E.; et al. Prognostic Value of Troponin and Creatine Kinase Muscle and Brain Isoenzyme Measurement after Noncardiac Surgery: A Systematic Review and Meta-analysis. Anesthesiology 2011, 114(4), 796–806. 5. Padayachee, L.; Rodseth, R. N.; Biccard, B. M. A Meta-analysis of the Utility of C-reactive Protein in Predicting Early, Intermediate-Term and Long Term Mortality and Major Adverse Cardiac Events in Vascular Surgical Patients. Anaesthesia 2009, 64(4), 416–424. 6. Redfern, G.; Rodseth, R. N.; Biccard, B. M. Outcomes in Vascular Surgical Patients with Isolated Postoperative Troponin Leak: A Meta-analysis. Anaesthesia 2011, 66(7), 604–610. 7. Rodseth, R. N.; Lurati Buse, G. A.; Bolliger, D.; Burkhart, C. S.; Cuthbertson, B. H.; Gibson, S. C.; Mahla, E.; Leibowitz, D. W.; Biccard, B. M. The Predictive Ability of Pre-operative B-type Natriuretic Peptide in Vascular Patients for Major Adverse Cardiac Events: An Individual Patient Data MetaAnalysis. J. Am. Coll. Cardiol. 2011, 58(5), 522–529. 8. Griffee, M.; Brambrink, A.; Barrett, T. Preoperative Biomarkers of Inflammation, Ischemia, and Heart Failure and Outcomes

of Vascular Surgery. Cleveland Clin. J. Med. 2009, 76(Electronic Suppl 1), eS19. 9. Fleisher, L. A.; Beckman, J. A.; Brown, K. A.; Calkins, H.; Chaikof, E. L.; Fleischmann, K. E.; Freeman, W. K.; Froehlich, J. B.; Kasper, E. K.; Kersten, J. R.; et al. ACC/AHA 2007 Guidelines on Perioperative Cardiovascular Evaluation and Care for Noncardiac Surgery: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 2002 Guidelines on Perioperative Cardiovascular Evaluation for Noncardiac Surgery) Developed in Collaboration with the American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Rhythm Society, Society of Cardiovascular Anesthesiologists, Society for Cardiovascular Angiography and Interventions, Society for Vascular Medicine and Biology, and Society for Vascular Surgery. J. Am. Coll. Cardiol. 2007, 50(17), e159–e242. 10. Back, M. R.; Schmacht, D. C.; Bowser, A. N.; Stordahl, N.; Cuthbertson, D.; Johnson, B. L.; Bandyk, D. F. Critical Appraisal of Cardiac Risk Stratification Before Elective Vascular Surgery. Vasc. Endovasc. Surg. 2003, 37(6), 387–397. 11. Favaloro, E. J.; Grispo, L.; Exner, T.; Koutts, J. Development of a Simple Collagen Based ELISA Assay Aids in the Diagnosis of, and Permits Sensitive Discrimination between Type I and Type II, von Willebrand’s Disease. Blood Coagu. Fibrinolysis 1991, 2(2), 285–291. 12. Tsarev, S. A.; Tsareva, T. S.; Emerson, S. U.; Kapikian, A. Z.; Ticehurst, J.; London, W.; Purcell, R. H. ELISA for Antibody to Hepatitis E Virus (HEV) Based on Complete Open-Reading Frame-2 Protein Expressed in Insect Cells: Identification of HEV Infection in Primates. J. Infect. Dis. 1993, 168(2), 369–378. 13. Hall, D.; Minton, A. P. Macromolecular Crowding: Qualitative and Semiquantitative Successes, Quantitative Challenges. Biochim. Biophys. Acta 2003, 1649(2), 127–139. 14. Hartl, F. U. Molecular Chaperones in Cellular Protein Folding. Nature 1996, 381(6583), 571–580. 15. Minton, A. P. Models for Excluded Volume Interaction between an Unfolded Protein and Rigid Macromolecular Cosolutes: Macromolecular Crowding and Protein Stability Revisited. Biophys. J. 2005, 88(2), 971–985. 16. Minton, A. P. Macromolecular Crowding. Curr. Biol. 2006, 16(8), R269–R271. 17. van den Berg, B.; Ellis, R. J.; Dobson, C. M. Effects of Macromolecular Crowding on Protein Folding and Aggregation. EMBO J. 1999, 18(24), 6927–6933. 18. Dobson, C. M. Chemical Space and Biology. Nature 2004, 432(7019), 824–828. 19. Ellis, R. J. Macromolecular Crowding: Obvious but Underappreciated. Trends Biochem. Sci. 2001, 26(10), 597–604. 20. Ellis, R. J. Molecular Chaperones: Assisting Assembly in Addition to Folding. Trends Biochem. Sci. 2006, 31(7), 395–401. 21. Ellis, R. J.; Minton, A. P. Cell Biology: Join the Crowd. Nature 2003, 425(6953), 27–28.

Downloaded from jla.sagepub.com by guest on March 24, 2016

151

Prasad et al. 22. Ellis, R. J.; Pinheiro, T. J. T. Medicine: Danger—Misfolding Proteins. Nature 2002, 416(6880), 483–484. 23. Heinisch, R. H.; Barbieri, C. F.; Nunes Filho, J. R.; Oliveira, G. L. d.; Heinisch, L. M. M. Prospective Assessment of Different Indices of Cardiac Risk for Patients Undergoing Noncardiac Surgeries. Arq. Bras. Cardiol. 2002, 79, 333–338. 24. Kumar, R.; McKinney, W. P.; Raj, G.; Heudebert, G. R.; Heller, H. J.; Koetting, M.; McIntire, D. D. Adverse Cardiac Events after Surgery. J. Gen. Intern. Med. 2001, 16(8), 507–518. 25. Ford, M. K.; Beattie, W. S.; Wijeysundera, D. N. Systematic Review: Prediction of Perioperative Cardiac Complications and Mortality by the Revised Cardiac Risk Index. Ann. Intern. Med. 2010, 152(1), 26–35. 26. Oh, S. W.; Moon, J. D.; Park, S. Y.; Jang, H. J.; Kim, J. H.; Nahm, K. B.; Choi, E. Y. Evaluation of Fluorescence hs-CRP Immunoassay for Point-of-Care Testing. Clin. Chim. Acta 2005, 356(1–2), 172–177. 27. Luo, Y.; Zhang, B.; Chen, M.; Jiang, T.; Zhou, D.; Huang, J.; Fu, W. Sensitive and Rapid Quantification of C-reactive Protein Using Quantum Dot-Labeled Microplate Immunoassay. J. Transl. Med. 2012, 10, 24. 28. Wee, K. W.; Kang, G. Y.; Park, J.; Kang, J. Y.; Yoon, D. S.; Park, J. H.; Kim, T. S. Novel Electrical Detection of LabelFree Disease Marker Proteins Using Piezoresistive SelfSensing Micro-Cantilevers. Biosensors Bioelectronics 2005, 20(10), 1932–1938. 29. Teramura, Y.; Arima, Y.; Iwata, H. Surface Plasmon Resonance–Based Highly Sensitive Immunosensing for Brain

Natriuretic Peptide Using Nanobeads for Signal Amplification. Anal. Biochem. 2006, 357(2), 208–215. 30. Liu, R.; Liu, J.; Xie, L.; Wang, M.; Luo, J.; Cai, X. A Fast and Sensitive Enzyme Immunoassay for Brain Natriuretic Peptide Based on Micro-Magnetic Probes Strategy. Talanta 2010, 81(3), 1016–1021. 31. Sandhu, A.; Handa, H.; Abe, M. Synthesis and Applications of Magnetic Nanoparticles for Biorecognition and Point of Care Medical Diagnostics. Nanotechnology 2010, 21(44), 442001. 32. Daniels, J. S.; Pourmand, N. Label-Free Impedance Biosensors: Opportunities and Challenges. Electroanalysis 2007, 19(12), 1239–1257. 33. Castellanos, L. R.; Bhalla, V.; Isakson, S.; Daniels, L. B.; Bhalla, M. A.; Lin, J. P.; Clopton, P.; Gardetto, N.; Hoshino, M.; Chiu, A.; et al. B-type Natriuretic Peptide and Impedance Cardiography at the Time of Routine Echocardiography Predict Subsequent Heart Failure Events. J. Card. Fail. 2009, 15(1), 41–47. 34. Vattipalli, K.; Feikert, P.; Brandigampala, S.; Prasad, S. Study of Nanoporous Membranes with Applications in the Enhanced Detection of Cardiovascular Biomarker Proteins. Nano LIFE 2010, 01(03n04), 175–183. 35. Bothara, M.; Venkatraman, V.; Reddy, R. K.; Barrett, T.; Carruthers, J.; Prasad, S. Nanomonitors: Electrical Immunoassays for Protein Biomarker Profiling. Nanomedicine 2008, 3(4), 423–436. 36. Reddy, R. K.; Bothara, M. G.; Barrett, T. W.; Carruthers, J.; Prasad, S. Nanomonitors: Protein Biosensors for Rapid Analyte Analysis. Sensors J. IEEE 2008, 8(6), 720–723.

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