Nanomedicine: Nanotechnology, Biology, and Medicinexx (2014) xxx–xxx

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Sensor arrays based on nanoparticles for early detection of kidney injuryby breath samples

Morad K. Nakhleh, MSca, Haitham Amal, MSca, Hoda Awad, BScb, A'laa Gharra, BSca,Niroz Abu-Saleh, MScb, Raneen Jeries, BSca, Hossam Haick, PhDa,⁎, Zaid Abassi, PhDb,c

aDepartment of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion–Israel Institute of Technology, Haifa, IsraelbDepartment of Physiology and Biophysics, Faculty of Medicine, Technion–Israel Institute of Technology, Haifa, Israel

cResearch Unit, Rambam Health Campus, Hiafa, Israel

Received 24 December 2013; accepted 11 June 2014

Abstract

The outcomes of acute kidney injury (AKI) could be severe and even lethal, if not diagnosed in its early stages and treated appropriately.Blood and urine biomarkers, currently in use as indicators for kidney function, are either inaccurate in various cases or not timely. We report ondramatic changes in exhaled breath composition, associated with kidney dysfunction after ischemic insult in rat models. Gas chromatographylinked mass spectrometry examination of breath samples indicated significant elevations in the concentration of three exhaled volatile organiccompounds, two to six hours after AKI was surgically induced. Relying on these findings, we introduce an array of sensors, based on organic-layer capped gold nanoparticles, sensitive to odor changes. The ability of the array to detect AKI via breath testing was examined and scored asensitivity of 96%, only one hour after disease induction.© 2014 Elsevier Inc. All rights reserved.

Key words: Acute kidney injury; Detection; Gold nanoparticles; Breath test; Volatile organic compound

Acute kidney injury (AKI) is a common clinical problemaffecting about 2% to 7% of hospitalized patients and 5% to 10%of critically ill patients.1,2 AKI occurs in response to a largenumber of insults that damage the nephron with adversefunctional consequences such as metabolic acidosis, hyperkale-mia, abnormal body fluid balance and adverse effects on otherorgan systems.3,4 Renal ischemia/reperfusion (I/R) injury is theleading cause for intrinsic AKI.2–5 The mechanisms underlyingrenal I/R injury are complex, including, decreased oxygendelivery, depletion of cellular energy stores and accumulation oftoxic metabolites.2–4 However, reperfusion of ischemic tissue,being necessary as a reparative mechanism, has been shown toexacerbate acute ischemic injury through the generation of

Support: This study was supported by a NOFAR grant.Disclosure: No coauthor declares any conflict of interest.The authors acknowledge Dr. Yoav Broza and Dr. Ulrike Tisch (both

from Technion-IIT, Haifa, Israel) for helpful discussion and script review.The authors also acknowledge Dr. Viki Kloper for her assistance in thepreparation of the graphical images.

⁎Corresponding author.E-mail address: hhossam@technion.ac.il (H. Haick).

http://dx.doi.org/10.1016/j.nano.2014.06.0071549-9634/© 2014 Elsevier Inc. All rights reserved.

reactive oxygen and nitrogen species.2–4,6,7 Despite theadvances in medicine in general and critical care medicine inparticular, AKI is still associated with high morbidity, causing anoverall in-hospital mortality of approximately 20% and morethan 50% in Intensive Care Unit (ICU) patients.8,9

Urinalysis and urine volume are invaluable tools for thediagnosis of kidney dysfunction. However, both tools sufferfrom limited sensitivity and specificity.10 Specifically, areduction in urine output (oliguria) usually denotes moresignificant AKI than when urine output is maintained. However,preserved and even enhanced urine output is noted in AKI ofvarious etiologies including I/R AKI. Sodium excretion suffersfrom a few shortcomings, which could be altered by rhabdomy-losis, radio contrast or sepsis-induced AKI.10 Other criteria fordiagnosis and classification of AKI are highly dependent onchanges in serum creatinine (SCr).1,2 However, rapid, major lossof kidney function could be associated with small changes in SCrlevels, particularly in the early phases of AKI, so this could causea delay in the diagnosis and intervention.11 Biomarkers such asneutrophil gelatinase-associated lipocalin (NGAL) and kidneyinjury molecule-1 (KIM-1) were also suggested for AKIdetection.12–14 NGAL increased in urine very early after renal

FIGURE 1. Effect of ischemia–reperfusion injury (I/R) for 45 min on: (A) urine flow (V), (B) sodium excretion (UNaV), (C) fractional excretion of sodium(FENa), and (D) mean arterial blood pressure (MAP) at different time points: baseline (T0); and, one, two, three and four hours after I/R (T1-T4). (#) representsP-value b0.05 when comparing between the two groups at the same time point, whereas (*) represents P-value b0.05 when comparing the value at specific timepoint versus the baseline (T0) of the same group.

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ischemia in mouse and rat models,15,16 and in children with AKIafter cardiopulmonary bypass.12,14,17 However, NGAL levels inplasma and urine are known to rise in various clinical settingsincluding inflammatory and infective conditions.13,14 Therefore,there is an urgent need for alternative/complementary rapid andaccurate for early detection of AKI.

Several mass spectrometry studies over the past two decades haveshown that the spectrum of exhaled volatile organic compounds(VOCs) is remarkably altered as a result of disease,18–44 includingkidney dysfunction.35,36,44–47 This could be due to the accumulationof toxins in the blood, production of ischemic tissue and itssurrounding, or due to metabolic changes of disease pathwaybyproducts.34–36,38 A more innovative method in the field of breathtesting uses cross-reactive nanomaterial-based sensor arrays inconjugation with pattern-recognition algorithms.18–20,23,48 Thesenanomaterial-based sensor arrays are more likely to become aclinical and laboratory diagnostic tool because they are small in size,easy to use, and inexpensive. Furthermore, they respond rapidly anddifferently to small changes in concentration and provide a consistentoutput that is specific to a given exposure. When not in contact withthe analyte, these sensors return to their baseline state rapidly.

The advantages of these sensors have led to promising outcomesin several fields, including detection of cancer18–20,22,23,25–31,49–52

and various non-cancerous diseases.32–36,53–55 Recently, we havedemonstrated the ability of these sensor arrays to differentiatebetween healthy states and induced end stage renal disease (ESRD)in rats via breath samples with an accuracy of over 95%, using amodel of bilateral nephrectomy.36 Moreover, we have also showndiscrimination between various stages of kidney dysfunction inpatientswith chronic kidney disease (CKD)35 and that the efficacy ofhemodialysis treatment could be evaluated by gold nanoparticlesbased sensors.34 The present study is designed to examine whetherAKI-induced changes in theVOCconcentrations are detectable at anearly stage and whether these changes can be identified using ananoparticle-based sensor array.

Materials and methods

Study design

Studies were conducted on 16 male Sprague Dawley rats(Harlan Laboratories, Jerusalem), weighing 300-350 g, that were

FIGURE 2. Effect of ischemia-reperfusion injury (I/R) on: (A) glomerularfiltration rate (GFR) and (B) urine NGAL levels at the different time points:baseline (T0); and, one, two, three and four hours after I/R (T1-T4). (#)represents P-value b0.05 when comparing between the two groups at thesame time point, whereas (*) represents P-value b0.05 when comparing thevalue at specific time point versus the baseline (T0) of the same group.

FIGURE 3. Effect of I/R for 45 min on: (A) serumNGAL, (B) serum creatinine.(#) representsP-valueb0.05when comparing between the two groups at the sametime point, whereas (*) represents P-value b0.05 when comparing the value atspecific time point versus the baseline (T0) of the same group.

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maintained on standard rat chow (0.5% NaCl) and water adlibitum. The investigation was conducted according to theguidelines of the Animal Use and Care Committee, Technion–Israel Institute of Technology. AKI was surgically induced in 8of the animals, while the remaining 8 animals served as a shamoperated control group.

AKI induction, blood and urine sampling

All animals (n = 16) were housed under standardized condi-tions for 2–3 days. Following an overnight fast, the animals wereanaesthetized with inactin anesthesia (100 mg/kg, IP) and placedon a controlled heating (thermo-regulated) table (37 °C). Polyeth-ylene tubes (PE50) were jugular vein for blood sampling andinfusion of 0.9% normal saline (0.9% NaCl) at a 1.5 ml/h rate.After that, an upper abdominal midline incision was made andrenal blood vessels were isolated bilaterally. The area was coveredwith saline-soaked gauze to minimize dehydration. Baseline (T0)breath and blood samples were collected at this stage. Then, AKIwas surgically induced in only 8 of the animals. In this surgery, weremoved the right kidney (nephrectomy) and immediately afterthat, we occluded the left renal artery, occluded for 45 min. At the

end of the 45-min period, we allowed a reperfusion for 15 min(so called T1).

Breath and blood samples were obtained at T0 and T1 as wellas 2 h, 4 h, and 6 h after the nephrectomy process (denoted asT2, T4 and T6, respectively). Rats that underwent the sameprocedure with the exception of right nephrectomy and left renalischemia served as controls. Two rats (one AKI and the othersham operated) were examined per day. The experiments wereconducted over a period of 4 weeks. Blood samples werecentrifuged and the separated serum was stored at −20 °C.Serum samples were analyzed for NGAL and creatinine.

In an additional group of animals, a catheter (PE50) wasinserted into the bladder for urine collection; saline was infusedat a rate of 1% of body weight per hour (~3.0 ml/h) throughoutthe experiment. Urine samples were collected at T0, T1, T2, andT4. Blood and urine were chemically analyzed in order toevaluate kidney function using conventional biomarkers such asInulin clearance, urine NGAL, urine flow and sodium excretion.For further details regarding the sampling and analysisprocedure, see Supplementary Materials (Sections 1.1. and 1.2.).

Breath collection

Tracheo-tubes were inserted into all rats after anesthesia. Acustom-madeairwaysystemwasused(SupplementaryFigureS1-A),

Table 1Number of eligible samples contributed to GC/MS and sensor array analysis,after exculsion of damaged samples.

Analysismethod

Time point

Group Baseline T1 T2 T4 T6 Total

GC-MS AKI 7 7 8 5 8 35SHAM 6 6 7 5 3 27

Sensor Array AKI 8 7 8 7 7 37SHAM 7 6 7 6 6 32

The samples were collected from 8 AKI and 8 sham operated rats.Baseline: after abdominal insection.T1: one hour after nephrectomy and renal ischemia, T2, T4 andT6, respectively.

Table 2VOCs with significant change in concentration, at least at one time pointwhen compared to its baseline measurment.

VOC Retentiontime (min)

Main m/z Time ofsignificantchange

P-value forAKI group

P-value forSHAM group

Ethanol 2.499 31 T2 0.0253 0.2012Acetone 2.736 43 T6 0.0223 0.36252-Pentanone 7.006 43 T6 0.0009 0.4580

T2: 2 h after after nephrectomy and renal ischemia.T6: 6 h after nephrectomy and renal ischemia.

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consisting of two one-way valves. The first valve opens when therats applied negative chest pressure, as they attempt to inhale,directing ambient air into the lungs. The second valve remainsclosed during inhalation and is activated when the rats exhale,directing the exhaled breath into 1 liter Tedlar bags. Samples weresimultaneously collected from AKI and sham operated rats at T0,T1, T2, T4 and T6. Two bags were obtained at each time point and700 ml from the contents of each bag were pumped (100 ml/minflow rate) into a Tenax TA/Carboxen-1018 glass adsorbent tube(Sigma Aldrich Ltd.). All samples were analyzed within threemonths from collection. Ambient air samples (700 ml) were alsocollected on a daily basis, monitoring the environmental settingsduring the experiment.

Quantitative chemical analysis of breath samples

Gas chromatography linked with mass spectrometry (GC/MS) was used for the chemical analysis of the breath samples.Statistical analysis was performed for the identified compounds,described in the Supplementary Material (Section 1.3.).

Description of the nanoparticles-based sensor array

A sensor array is an artificial system that simulates thedifferent stages of the human olfactory system; it consists of anarray of chemical sensors for VOC detection, with amplificationof the sensor signal responses, and an algorithm for patternrecognition.18,19,48 The nanomaterial-based sensor array that wasused to analyze the breath samples contained cross-reactive,chemically diverse chemiresistors that were based on organicallystabilized spherical gold nanoparticles (GNPs, core diameter:3–4 nm). The chemical diversity of the sensors was achievedthrough three different organic functionalities: dodecanthiol,octadecanethiol, and 4-chlorobenzenemethanethiol. The organicligands of the GNPs provided broadly cross-selective absorptionsites for the breath VOCs.56,57 The GNPs were synthesizedas described in Refs. 58,59 and dispersed in chloroform.Chemiresistive layers were formed by drop casting the solutiononto semi-circular microelectronic transducers, until a resistanceof several MΩ was reached. The device was dried for 2 h atambient temperature and then baked overnight at 50 °C in avacuum oven. The microelectronic transducers consisted of tenpairs of circular interdigitated (ID) gold electrodes on silicon with300 nm thermal oxide (Silicon Quest International, Nevada, US).The outer diameter of the circular electrode area was 3 mm. Thegap between two adjacent electrodes as well as the width of each

electrode was 20 μm. The GNP sensors used in this studyresponded rapidly and reversibly when exposed to typical VOCs inthe breath.58,59 Additionally, we have confirmed that the GNPsensors have a very low response to water.60 Therefore, the effectof the high, varying air humidity in the room and the high, varyinghumidity levels in exhaled breath is insignificant. After fabricationof the devices, each sensor went through a characterizationprocedure, in which it was exposed to several concentrations ofcompounds, usually found in breath, (e.g. isopropyl alcohol, 2--ethyl-hexanol, water vapor and others), in a range of tens of partsper billion (ppbs)—several parts per million (ppms). Theinformation obtained in these experiments allowed us tochoose the most suitable sensors array to be used for breathsamples analysis.

Breath analysis using the sensor arrays

Breath samples were exposed to a reservoir of GNP-basedsensors. The exposure resulted in a fully reversible change inresistance of the sensors, which was recorded. Extracted sensingfeatures and used discriminant factor analysis (DFA) to choosethe minimal number of sensors required in order to achieve bestdiscrimination between two groups. The detailed procedure isdescribed in Supplementary Material (Sections 1.4. and 1.5.).

Statistical analysis

Statistical significance was assessed for repeated measure-ments by one-way analysis of variance (ANOVA) or by two-wayANOVA, as appropriate. The Dunnett test and Tukey's multiplecomparisons test were used for data point comparisons in eachgroup. P-values of b0.05 were considered statistically signifi-cant. Statistical tests were performed by SAS JMP, Version 10.0.

Results

Impact of I/R on kidney function and urine NGAL

The changes in urine flow, urinary sodium excretion,fractional sodium excretion, mean arterial pressure and GFRfollowing renal I/R are depicted in Figure 1 and 2, A. Rats thatwere subject to I/R exhibited a substantial increase in urine flowand in sodium excretion, both absolute and fractional, through-out the experiment. In parallel, GFR significantly declinedfollowing I/R, most remarkably at T1 and throughout the entireexperiment, although it gradually improved over time. Even 4 hafter I/R, the kidney continued to display significant

FIGURE 4. Breath VOCs affected by AKI progression. Average concentra-tion and SEM of (A) Ethanol, (B) acetone and (C) 2-pentanone, at differenttime point measurements. (*P b 0.05 single measurement vs. baseline).

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hypo-filtration in the AKI group. On the other hand, we noticed amild decline in GFR along with a slight increase in V and UNaVin the control group too, yet these changes did not reachstatistical significance (Figures 1 and 2, A). These alterations inkidney function of the sham operated rats may stem from

activation of vasoconstrictory neurohormonal systems, fluid lossfrom the open abdominal cavity, or insufficient saline infusion. Itshould be pointed out that the V and UNaV baseline values of thecontrols were lower than those obtained in AKI rats. However,the FENa, which is considered a better indicator of AKI thanUNaV or urine flow, was comparable for the two experimentalgroups (Figure 1). In line with the decrease in GFR, urinaryexcretion of NGAL was gradually enhanced in I/R and reachedstatistical significance within 2 h and lasted for 4 h after the renalinsult (Figure 2, B). In contrast, no significant change in urinaryNGAL was found in sham control rats.

Impact of I/R on serum NGAL and creatinine

As expected, rats that were subject to I/R exhibited a higherserum level of NGAL throughout the entire monitoring period.Although the increase was remarkable, starting one hour after I/Rinduction, statistical significance was observed in the first 4 hafter I/R induction (Figure 3, A). A mild increase in circulatoryNGAL was also noticed in sham control rats, where it reachedstatistical significance at T6. In addition, rats with I/R displayed agradual increase in SCr, which reached statistical significanceafter 2 h (Figure 3, B).

Chemical analysis of the breath samples by GC-MS

After excluding damaged tubes (shattered glass or leaky),a total of 62 breath samples, collected from AKI ratsand sham operated rats at five different time points duringthe procedure (Table 1), were analyzed. We tested12 identified VOCs that were present in at least 80% ofthe samples, including ethanol, acetone, 1-dodecyl-aziridine,2-pentanone, 1-butanol, 5-methyl 2-hexanone, 2,5-dimethyl-octane, 2,2,4,6,6-pentamethyl-heptane, hexanal, benzoic acid,1-eicosanol and 5-methyl-tridecane. We noticed significantchanges in the concentrations of three VOCs (P-value b0.05)in the AKI group. Ethanol levels, for instance, increased twohours after AKI induction, and then returned to normal levels atT4, followed by a significant increase at T6. The levels ofacetone and 2-pentonane increased significantly 6 h after I/R(Table 2 and Figure 4). We have carefully examined thepossibility that the changes observed were influenced byenvironmental effects: ambient air samples that were collectedtime of the experiments and were analyzed in the same way; weexamined the abundance of breath VOCs in them. While2-pentonane was not detected in any of the room samples,acetone appeared once. Ethanol was abundant in 4 of 8 samples,with average concentration of 187 ±165 ppb. Concerning2-pentanone and acetone concentrations, we observed aremarkable variation in the concentrations of one animal,affecting the average and standard deviation. This could bedue to several reasons: (i) an exogenous contamination duringthis animal specific procedure; (ii) metabolic reaction toanesthetic drug or surgical procedure; and/or (iii) technicaldefect during breath sampling of this specific animal.

Analysis of exhaled breath samples using sensor arrays

VOC patterns of AKI states were derived from the normalizedsensing features of three sensors of the sensor array as described in

FIGURE5. Statistical analysis for the responses of the sensors array. (A) First canonical value (CV1): DFAmodelwas built usingAKI group samples. (B) First canonicalvalue (CV1): DFAmodel was built applied on sham group samples. (C) Receiver operating characteristic (ROC) curve analysis for DFAmodel. (D)Receiver operatingcharacteristic (ROC) curve analysis for DFA model upon. Sham samples (E): average canonical value of each group at every time-point (error bars for SEM).(F) Individual responses of each sample. • (A and C) The boxes represent the 95% confidence intervals of the CV1 values, corresponding to 1.96 × SEM.

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the Supplementary Materials (Sections 1.4. and 1.5.). When usinga combination of three independent sensing features, extractedfrom a differentlymodified GNP sensor (Supplementary Figure S1and Supplementary Table S1), we could derive a powerful

discriminative model capable of sensing AKI and monitoring itsprogression, starting one hour post-surgery (T1). Figure 5, Ashows the first canonical value (CV1) of the DFA model for AKI.As seen in the Figure, the post-surgery states (T1–T6) formed a

Table 3Classification success of the DFA model estimated by leave-one-out cross validation.

Group Control Target group Sensitivity (TP) Specificity (TN) Accuracy ROC curve area

AKI (n = 37) Baseline (n = 8) T1-T6 (n = 29) 96% 75% 92% 89%(28) (6)

SHAM (n = 32) Baseline (n = 7) T1-T6 60% 42% 56% 60%(n = 25) (15) (3)

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well-defined cluster that was well-separated from the cluster of thepre-surgery baseline states (T0) of the same animals. Leave-one-out cross-validation showed that the model accurately classified 28of 29 breath samples from post-surgery AKI rats, scoring asensitivity of 96%, and 6 of 8 per-surgery (baseline) samples,setting a specificity of 75% and total diagnostic accuracy of 92%(Table 3). Moreover, a receiver operating characteristic (ROC)curve analysis was applied to the diagnostic model, examining thebinary state classification ability: the area under curve (AUC) was89% (Figure 5, C), showing high classification ability. Whenapplying the same model to the samples collected from the shamoperated rats before and after surgery, we observed that the DFAclusters overlapped completely (Figure 5, B). Leave-one-outcross-validation yielded a classification accuracy of only 56%(18 of 32), i.e., random classification, and an AUC of 60% wasobtained in the ROC curve analysis (Table 3 and Figure 5, D).These results confirm that the derived DFA model is indeedsensitive only to AKI, and not to other post-surgery injury, or toenvironmental fluctuations at the site of the breath samplecollection during the measurement period. Otherwise, similartrend would also be observed for the sham-operated rats, since oneach day of the experiment, one AKI and one sham-operated ratwere prepared and analyzed. Figure 5, E shows the average of theCV1 values that were obtained for all the breath samples from theAKI rats and the sham operated rats, and Figure 5, F displays theactual values for each sample. Prior to the procedure, at T0, all theanimals shared the same baseline; their CV1 values overlappedcompletely and no significant difference was observed between thetwo groups. The CV1 values of the AKI rats changed dramaticallyimmediately after I/R, whereas the CV1 values of the shamoperated controls show only a sub-significant shift towards lowernumbers. For all time-points after surgery up to T6, the differencein average CV1 between AKI rats and controls was significant.

Discussion

Blood and urine markers

Our findings suggest that the sensor array respondedimmediately to changes in the exhaled VOC profile that wereassociated with AKI, within not more than one hour from theoccurrence of the injury. The response of the sensor array to AKIstates was found to be faster than urinary and circulatory NGAL,which started to increase, only after 2 h and 6 h, respectively,from the AKI induction. Likewise, SCr was significantlyelevated only after 2 h from the AKI.

These findings are of special interest in light of the pooraccuracy of the classic biomarkers in detecting AKI.61–63

Kidney injury is usually diagnosed by laboratory analysis of

a patient's blood and urine, whereby elevated SCr andBUN, together with insufficient urinary output, are typicalcharacteristics.1,2 Despite its widespread use, SCr suffers fromnumerous limitations. Baseline values of SCr are not normallyavailable for patients suspected of having AKI. Moreover,changes in SCr usually lag behind the rapid alterations in GFRthat characterize AKI. Up to 60% of kidney function may be lostbefore SCr even begins to rise and can take several days to reacha new steady state.61–63 NGAL and KIM-1 are the mostprominent representatives of these biomarkers. Experimental andclinical studies revealed that circulatory and urinaryNGAL levels increased as early as 2 h after the developmentof AKI.12–17 In line with these findings, our results alsodemonstrated elevated urinary NGAL levels 2 h after the kidneyI/R insult. Concerning the serum levels of NGAL, we noticed agradual increase during the follow-up period; however, thedifference from the baseline reached statistical significance only6 h after the AKI induction. Despite NGAL superiority over SCr,NGAL measurements may be influenced by a number ofcoexisting variables, including chronic kidney disease, chronichypertension, systemic infections, inflammatory conditions,anemia, hypoxia and malignancies.64 Thus, the moderateincrease in serum and urinary NGAL in the control group afew hours after the initiation of the experiment could beattributed to possible systemic infection due to the surgicalprocedure. Alternatively, the increase in SCr even in the controlgroup might stem from inadequate fluid administration in theserelatively long experiments. Dehydration is known to causepre-renal failure, which is associated with mild to moderateincreases in SCr and urinary and Serum NGAL levels.65

Chemical analysis for AKI breath samples

While the effects of AKI on the body fluid and electrolytehomeostasis are well known, little is known about its impact onthe composition of the exhaled breath either in humans orexperimental models of the disease. This issue is interesting fortwo reasons: (i) It is well-established that CKD affects thecomposition of gases found in exhaled breath, and these VOCswere used to detect the disease in patients35,36,66 and rats36;(ii) AKI triggers a cascade of extra-renal abnormalities, includingcardiac, neuronal, hepatic dysfunctions along enhanced inflam-matory responses affecting lung homeostasis.67 AKI significant-ly affects lung physiology by altering the homeostasis of fluidbalance, acid–base balance, metabolism, vascular tone andthe status of the inflammatory/oxidative stress systems. Allthese are assumed to modify gaseous metabolites found in theexhaled breath during AKI. Indeed, chemical analysis of thebreath composition indicated a remarkable increase of three

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oxygen-containing compounds; acetone, 2-pentanone and etha-nol. Aldehydes, in general, and ethanol, in particular, mightoriginate by alcohol metabolism in the body. However, in ourcase, it is more likely to be produced by reduction ofhydroperoxide by cytochrome p-450, as secondary product oflipid peroxidation process in the kidney.21 As mentioned earlier,we have used an ischemic model to induce acute tubularnecrosis–ischemic AKI. Specifically, we blocked blood supplyfor 45 min to the remnant kidney, after removing the first one.During this period, cells suffer from a lack of oxygen andnutrients. However, with circulation restoration, we find anexcessive production of reactive oxygen species by inflamma-tory cells, stealing electrons from the lipids in cell membrane,damaging the surrounding tissue, all as part of the reperfusioninjury process.21,68

The ketones (acetone and 2-pentanoneare) are known to beelevated in ketonemic patients, for example, in the cases ofprolonged fasting or uncontrolled diabetes, in which an extremelipolysis process occurs. Similar conditions could be found insevere and rapid AKI, due to an imbalance of blood glucosehomeostasis. Moreover, it is well known that ketone-formationcould be secondary to lipid peroxidation and fatty acidsoxidation.21,68 However, further in-vitro studies are required inorder to determine the origin of these compounds. Moreover,blood glucose and insulin levels should also be monitored inorder to examine ketonomic effect of AKI. Although the ethanollevels change two hours after AKI, we don't suggest it as anoptimal biomarker for early detection of AKI, mainly becausethe multiple possible sources of ethanol, such as alcoholconsumption or production by GI tract bacteria.69 Consistentwith previous publications in the field of kidney failure, ethanol,acetone and 2-pentanone, were found in both breath and fecalsamples..38,40,66 Ethanol was found to be lower in both breathand feces of chronic kidney disease inducted in the rat model.Acetone was lower in the feces but higher in the breath of CKDrats when compared to control group. It was also reported that2-pentanone levels were higher in the breath of CKD rats.66

Sensor array for AKI detection

As indicated earlier in the introduction the GC/MS analysishas several disadvantages, including the complicity of operation,the high cost and the need of sample treatment prior to analysiswhich might insert a bias to it or cause a data loss.24Thedescribed sensor array constitutes a more robust and moresensitive detection system than GC/MS, mainly because thesensors monitor the collective changes in the overall breath-VOCcomposition, rather than examining each compounds' concen-tration. Moreover, it could be used for online point-of-careanalysis, which would be helpful especially among mechanicallyventilated patients.

Several types42,70,71 of chemical sensors were tested aspotential tools to monitor kidney function, and some scoredrelatively high correlation to GFR for accuracy of kidneydysfunction detection. However, some types require hightemperatures (N200 °C) in order to analyze the samples71;others use blood samples, which require invasive procedures andcould be hazardous.70 In few instances sensors39,43 were used for

the selective sensing of breath ammonia levels. Some of themshowed correlation between blood and breath ammonia levels;moreover, breath ammonia was significantly decreased afterhemodialysis.39 However, ammonia is not a stable biomarker forkidney diseases since ammonia levels are easily altered and notspecific to kidney disease. Ammoni was also found elevated inHelicobacter pylori infection,43 encephalopathy,43 and pulmo-nary artery hypertension.37 In contrast to these studies, ourapproach relies on the detection of a VOC mixtures for detectionof AKI conditions, thus decreasing the chances to find similarpatterns in other confounding diseases and/or environmentalconditions.

At present, physicians rely on ranges of healthy population asthe normal baseline. The same concept could be applied to oursystem, in which we establish a database of breath samples fromnumerous healthy subjects as a baseline reference for futurecomparisons when AKI is suspected. As a result, we are able totrack their behavior with regard to VOCs and normalize theresults in a way that prevents baseline and response drift. Themethod could also be translated to real world clinical conditionsby simple daily exposure of the sensors to specific mixtureof compounds.

Such an array of three sensors could be easily adapted as areusable kit for fast testing. The patient would breathe into anopening at one end of the device, after removing a sterile seal.Mounted on an electronic chip for signal readout and datastorage, the sensors' readout and the software for the dataanalysis could be loaded to any computer, and the data could beanalyzed on-site within few minutes.

Conclusions

The results of the current study show that AKI ischaracterized by very rapid metabolic alterations in bloodstream, as expressed in the concentrations of VOCs present inexhaled air, just one hour after disease induction. We present asimple, non-invasive breath test with a nanoparticle-based sensorarray that is capable of early detection of AKI. The sensor arraycan be used as a complementary tool for early diagnosis andmonitoring AKI progression. Further studies are needed toexplore whether this approach is reliable in early detection ofclinical AKI.

Appendix A. Supplementary data

Supplementary data to this article can be found online athttp://dx.doi.org/10.1016/j.nano.2014.06.007.

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