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Fluorometric sniff-cam (gas-imaging system) utilizing alcohol dehydrogenase for imaging concentration distribution of acetaldehyde in breath and transdermal vapor after drinking Kenta Iitani, Toshiyuki Sato, Munire Naisierding, Yuuki Hayakawa, Koji Toma, Takahiro Arakawa, and Kohji Mitsubayashi Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04474 • Publication Date (Web): 23 Jan 2018 Downloaded from http://pubs.acs.org on January 24, 2018

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Analytical Chemistry

1

Fluorometric sniff-cam (gas-imaging system) utilizing alcohol dehydrogenase for imaging

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concentration distribution of acetaldehyde in breath and transdermal vapor after drinking

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Kenta Iitania, Toshiyuki Satoa, Munire Naisierdinga, Yuuki Hayakawaa, Koji Tomab, Takahiro

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Arakawab and Kohji Mitsubayashia,b,*

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a

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5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan

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b

Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-

Department of Biomedical Devices and Instrumentation, Institute of Biomaterials and

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Bioengineering, Tokyo Medical and Dental University,2-3-10 Kanda-Surugadai, Chiyoda-ku,

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Tokyo 101-0062, Japan

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* Corresponding author. Tel.: +81 3 5280 8091, Fax: +81 3 5280 8094

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E-mail: [email protected]

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1 ACS Paragon Plus Environment

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Abstract

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Understanding concentration distributions, release sites and release dynamics of VOCs from

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the human is expected to lead to methods for noninvasive disease screening and assessment of

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metabolisms. In this study, we developed a visualization system (sniff-cam) that enabled to

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identify a spatiotemporal change of gaseous acetaldehyde (AcH) in real-time. AcH sniff-cam

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was composed of a camera, a UV-LED array sheet, and an alcohol dehydrogenase (ADH)-

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immobilized mesh. A reverse reaction of ADH was employed for detection of gaseous AcH

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where a relationship between fluorescence intensity from nicotinamide adenine dinucleotide

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and the concentration of AcH was inverse proportion; thus, the concentration distribution of

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AcH was measured by detecting the fluorescence decrease. Moreover, image differentiation

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method that calculated a fluorescence change rate was employed to visualize a real-time

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change in the concentration distribution of AcH. A dynamic range of the sniff-cam was 0.1–10

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ppm that encompassed breath AcH concentrations after drinking. Finally, the sniff-cam

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achieved to visualize concentration distribution of AcH in breath and skin gas. A clear

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difference of breath AcH concentration was observed between aldehyde dehydrogenase type 2

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active and inactive subjects, which was attributed to metabolic capacities of AcH. AcH in skin

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gas showed a similar time course of AcH concentration to the breath, and a variety of release

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concentration distribution. Using different NADH-dependent dehydrogenases in the sniff-cam

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could lead to a versatile method for noninvasive disease screening by acquiring

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spatiotemporal information of various VOCs in breath or skin gas.

38 human volatilome,

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Keywords:

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dehydrogenase, image differential

fluorescence, spatiotemporal, acetaldehyde, alcohol

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Introduction


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In the conventional and current diagnosis of diseases, the blood test has usually been 1,2

. At the same time, there has been growing interest in non-invasive

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commonly utilized

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diagnosis methods aiming at exhaled volatilome such as volatile organic compounds (VOCs)

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in breath or skin gas as the alternative or auxiliary in next-generation medicines

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VOCs are originally contained in blood as a result of specific diseases and metabolism, and

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then they are emanated directly from skin or breath after the exchange in the lungs 7,8.

3–6

. These

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Acetaldehyde (AcH), an intermediate of alcohol metabolism, is produced by ADH-

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mediated reaction in the liver after ingesting alcohol 9, and it has toxicity to DNA 10,11. For

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example, it was reported that AcH causes the mutational DNA damage in hematopoietic stem

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cells. 12 In this study, we used AcH as a model analyte since the contained in blood is released

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through breathing with a partition coefficient of breath : blood = 1 : 109

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Skin gas is constantly released and can be easily collected without a mental and physical

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burden; therefore, skin gas is considered to be more suitable for monitoring of VOCs than

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exhaled breath. However, measurement of VOCs in skin gas is challenging since their

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concentrations are usually much lower than the breath, e.g., ppb or sub-ppb level 15; a highly

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sensitive system is strongly required for the detection. Conventionally, skin gas sample is

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collected by a hermetically container such as a sample bag and measured by analytical

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devices such as a gas chromatograph (GC) and a mass spectrometer (MS). For example,

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Tsuda et al. and Turner et al. measured ethanol, acetone and etc. in skin gas that were released

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from a forearm, hand, and finger and collected by a sample bag

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ionization detector or selected ion flow tube MS. Mochalski et al. developed a room-type skin

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gas collection system which a subject was in, and collected only emanated skin gas by

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discharging exhaled breath out of the room; the VOCs contained in skin gas was measured

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using a proton transfer reaction MS

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drawbacks including complicated processes of measurement and requirement of highly skilled

16,17

13

and skin gas

14

.

using GC and flame

18

. Despite the advantages of these methods, some



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personnel made them unsuitable for simple disease screening and metabolism evaluation.

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Besides, it is difficult to investigate release sites and dynamics in detail because these

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methods measured the total amount of released VOCs and are unable to focus on a spot. It is

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known that VOCs’ concentration in exhaled breath and skin gas shows temporal fluctuation

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19–21

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important to deepen the understanding of a correlation between skin gas and physiological

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conditions: (i) Direct emanation from blood through the dermis and the epidermis, (ii)

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vaporization of sweat secreted from glands in a skin and (iii) production by metabolism of

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resident bacteria on a skin surface 22–25.

, and elucidating following potential release pathways for each VOC is considered to be

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Up to now, we have introduced a fiber optic gas sensor “bio-sniffer” that showed high

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sensitivity and selectivity due to the substrate specificity of an enzyme, and it allowed

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continuous measurement of VOCs 26–30. Also, applying the bio-sniffer’s technique to imaging,

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a biofluorometric gas imaging system (sniff-cam) was developed

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AcH sniff-cam employing a reverse reaction of ADH

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accurately display a temporal change of AcH concentration by measuring the fluorescence

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intensity of β-nicotinamide adenine dinucleotide (NADH) because the fluorescence

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reached a plateau after initial decrease and did not return to a baseline although the gas

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injection was stopped. This was attributed to measurement principle in which consumed

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NADH has not filled up again throughout the measurement. In this study, we further advanced

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the AcH sniff-cam to improve the responses and to enable visualize a spatiotemporal change

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of AcH concentration in real-time. The response was improved by employing an image

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differential method that utilized a slope of fluorescence intensity change instead. Since the

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slope kept changing while the fluorescence intensity increased and approached plateau, the

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slope output showed a clear peak and returned to a baseline when the gas injection was

31

. Recently, we reported

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. However, it was difficult to


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stopped. Afterwards, the advanced AcH sniff-cam was applied to real-time visualization of

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spatiotemporal change of AcH contained in exhaled breath and skin gas after drinking.

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Experimental

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Materials and reagents

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Tris-HCl buffer solution (Tris, pH6.5, 0.1 M) that was used in all of the

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experiment was made by 2-amino-2-hydroxymethyl-1,3-propanediol (99.9%, Cat. No.

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013-16385, Wako), hydrochloric acid (35%, Cat. No. 083-03485, Wako) and ultra-pure

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water that was generated by a Mill-Q purification system. Reagents for fabrication of

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an ADH-immobilized mesh were ADH (EC 1.1.1.1, 369 units/mg solid, Cat. No.

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A7011, from Saccharomyces cerevisiae, Sigma-Aldrich, USA), phosphate buffer (PB,

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pH6.5, 0.1 M), bovine serum albumin (BSA, Cat. No. 306-13383, Wako, Japan) and

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glutaraldehyde (GA, 25%, Cat. No. 079-00533, Wako Pure Chemical Wako, Japan). A

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cotton mesh (100% cotton, the thickness of 1 mm, the interval of 1 mm) that was used

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as a substrate for enzyme immobilization was purchased from Ohki Healthcare

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Holdings (Japan). Reduced form of β-nicotinamide adenine dinucleotide (NADH, Cat.

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No. 44326000) was purchased from Oriental Yeast (Japan). Standard gaseous AcH was

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generated using a permeation tube (Cat. No. P-92-1, Gastec, Japan) with a standard gas

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generator (Cat. No. PD-1B-2, Gastec, Japan). For selectivity assessment, some VOCs

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including ethanol (99.5 %, Cat. No. 14033-00. Wako), methanol (99.8%, Cat. No. 21926-95,

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nacalai tesque), 2-propanol (99.7, Cat. No. 166-04836, Wako), acetone (99.5%, Cat. No.

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016-00346, Wako) were generated by a diffusion tube (No.3200, Gastec, Japan), and the other

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such as methyl mercaptan that was done by a permeation tube (Cat. No. P-71-5, Gastec,

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Japan). An alcohol beverage (concentration of 20%, distilled liquor) for breath and skin gas

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experiments was purchased at a local store.



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Construction of the AcH sniff-cam

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Figure 1a shows a visualization principle of gaseous AcH distribution employed

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in an AcH sniff-cam. AcH was detected as a fluorescence decrease from NADH

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consumption which occurs through an ADH-mediated reverse reaction. In our previous

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work, we investigated the reduction/oxidation reaction of ADH can be controlled by

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pH condition. Also, unwanted interfere between forward and reverse reaction could not

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occur under optimal conditions.33 NADH has an autofluorescence property that

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exhibits absorption of excitation light at 340 nm wavelength and emission of

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fluorescence at 490 nm wavelength. Since NADH and AcH concentrations are

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correlated, AcH concentration can be determined by detecting fluorescence decrease of

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NADH. The AcH sniff-cam was composed of a UV-LED array (λ of 340 nm, 9×9

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array, 340X081SFN, Dowa, Japan), an ADH-immobilized mesh and a high-sensitive

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camera (HEED-HARP, Pioneer, Japan) (Figure 1b). The UV-LED array and the

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camera were aligned in the same optical, and 5 mm and 110 mm apart from the ADH-

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immobilized mesh, respectively. The UV-LED array was connected to a power source

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(KX-100H, Takasago, Japan) that supplied constant current 540 mA to the LED, and

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enabled to excite NADH uniformly in the ADH-immobilized mesh. The gain

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parameter of the high-sensitive camera was fixed at 15 in all of the experiments, and

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video signal that was conforming to National Television System Committee (NTSC)

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was out from composite connector of a camera controller. An analog video signal was

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converted to a digital video format by a video encoder (Intensity shuttle USB3.0, Black

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Magic Design, Australia). Two bandpass filters placed in front of the UV-LED array

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(BPFex, λ of 340 ± 42.5 nm, Edmund Optics, USA) and the high-sensitive camera

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(BPFfl, λ of 490 ± 10 nm, Asahi Spectra, Japan) excluded unwanted light to improve a 6 ACS Paragon Plus Environment

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signal to noise ratio. The ADH-immobilized mesh was fabricated by the following

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process. First, 0.65 mg of ADH and 1.5 mg of BSA were dissolved in PB (200 µL, 0.1

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M at pH 6.5). Then, 200 µL of the mixture was dropped and spread uniformly on a 20

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× 20 mm2 cotton mesh substrate, and then the mesh was left in a refrigerator for 60

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minutes. Subsequently, 10-fold diluted GA solution (32 µL, 2.5 v/v% in PB, 0.1 M at

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pH 7.0) was dropped onto the mesh for cross-linking and left in the refrigerator for 90

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minutes. Finally, the ADH-immobilized mesh was rinsed with 300 µL of Tris and then

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used immediately. Standard gaseous AcH was generated by a standard gas generator

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with a permeation tube. Clean carrier air that was compressed and filtered by a

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compressor and air filters was supplied to the standard gas generator through

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polytetrafluoroethylene tubes (F-8006-017, the outer diameter of 6 mm, the inner

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diameter of 4 mm, FLON industry, Japan) with excellent chemical and adsorption

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resistance. Flow rates of generated standard gaseous AcH and clean carrier air were

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controlled at 40 mL/min by mass flow controllers (MFC, RK1250, KOFLOC, Japan),

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and gas was introduced to the AcH-immobilized mesh. A glass gas outlet was placed

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on a backside of the ADH-immobilized mesh. Incidentally, it is reported that the

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environmental temperature affects enzyme activity and fluorescence intensity of

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NADH34. Thus, environmental temperature was kept at 25 ± 1.5 ºC of all experiment

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using an air conditioner. Thus, the temperature did not affect the enzyme activity and

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fluorescence intensity of NADH.

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(Figure 1 comes here)

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Differential method for visualization of spatiotemporal changes of AcH



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In the previous report, visualization of gaseous AcH spatial distribution was achieved

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using AcH sniff-cam that employed a reverse reaction of ADH. However, there was a problem

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in temporal resolution. After a decrease of fluorescence intensity on the ADH-immobilized

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mesh, the intensity reached a plateau and did not recover to the initial value even though

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injection of AcH was stopped. This was because there was no NADH supply once it was

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consumed. This problem made it difficult for previous AcH sniff-cam to be used for the study

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of gaseous AcH release dynamics. In order to solve this problem, an image differential

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method that utilized slope of fluorescence intensity change instead of the intensity itself was

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adopted. Application of the differential method to a video taken by the AcH sniff-cam was as

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follows. First, an original video that showed fluorescence decrease as a result of NADH

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consumption was converted to one in which florescence increased by subtracting a subsequent

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frame from the first frame of the video. This process is described by the following equation: = − ( > 0),

Eq.1

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wherei i is a frame index number; FI and FD are fluorescence increasing and decreasing

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images, respectively. Next, a simple moving average (SMA) filter described in equation 2 was

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used to remove high-frequency noise from FI that was caused by an image sensor of the

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camera. 1 =

()

( ≥ ),

Eq.2

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where n is the number of the frames in the SMA filter; FIk is a kth frame in the fluorescence

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increasing video; SFI is smoothed fluorescence increasing images. Then, a differential video

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that was composed of slopes of fluorescence intensity changes was created by differential

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method described in equation 3. =

− (×∆)) ∆ = ( ∆ = 2, !"# = 30, > 60), ∆ ∆

Eq.3


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where i is a frame index number; fps is frame per s that was of 30; ∆t is a time step that was of

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2 sec; SFI is a smoothed fluorescence increasing image; DI is a differential image.

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Finally, high-frequency noise remaining in the DI was removed by the SMA filter. The

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SMA filter had a trade-off relationship between noise reduction performance and response

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time. When the n in the SMA filter increased, noises were decreasing but response time

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became longer. Thus, an influence of the n to noise and response time was investigated with

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various conditions (n = 0, 10, 30, 100, 300, and 600 frames) of the SMA filter. In the

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experiment, 10 ppm of gaseous AcH was applied to the ADH-immobilized mesh wetted by

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NADH solution (500 µM, in 300 µL of Tris at pH 6.5, 0.1 M). After creating DI, that was

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smoothed by various conditions of SMA filters. Then, noise and response time at each

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condition were evaluated.

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In order to confirm the applicability of the AcH sniff-cam to the measurement of

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breath and skin gas, sensitivity and selectivity of the AcH sniff-cam were investigated. Each

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experiment was performed using 500 µM NADH dissolved in 0.1 M Tris at pH 6.5. For

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evaluation of the sensitivity of the AcH sniff-cam, various concentrations of gaseous AcH

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generated by the standard gas generator were applied to the ADH-immobilized mesh at a flow

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rate of 40 mL/min. In the experiment, initially clean carrier air was applied for 20 s, and then

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gaseous AcH was applied for 20 s. Finally, clean carrier air was applied again for 80 s. For

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investigation of selectivity, typical VOCs produced by the standard gas generator were

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applied to the AcH sniff-cam in the same procedure with the above-mentioned sensitivity

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study, and concentrations of the gas samples were set to be those after drinking: AcH (5 ppm),

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ethanol (100 ppm), methanol (0.1 ppm), 2-propanol (0.1 ppm), acetone (0.6 ppm), methyl

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mercaptan (0.007 ppm), and mixture of AcH (5 ppm) and ethanol (100 ppm) were used 35,36.



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Note that all of the numerical data of mean intensity and differential value were

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calculated at the region of interest (ROI, 80 pixels × 80 pixels) that was set at the center of

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frames in each video.

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Visualization of spatiotemporal change of the AcH concentration in breath

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Visualization of AcH in exhaled breath after drinking was taken place with subjects

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with a different phenotype of aldehyde dehydrogenase type-2 (ALDH2). A subject with lower

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activity of ALDH2 (ALDH2[-]) cannot catalyze AcH efficiently. In general, blood AcH

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concentration of ALDH2[-] subject becomes higher after drinking than that of the subject with

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high activity of ALDH2 (ALDH2[+]), thus breath AcH concentration is also expected to be

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higher than the ALDH2[+] 37–39. These breath and skin gas experiments were conducted based

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on the authorization of the Human Investigations Committee of Institute of Biomaterials and

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Bioengineering, Tokyo Medical and Dental University (authorization code of 2012-6) that

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acted up to Declaration of Helsinki. The subjects had been prohibited to smoke, take medicine

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and alcohols since 72 hours before the experiment. The most important of the experiment with

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a drinking was unified concentration of blood ethanol in all subject. Concentration of ethanol

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in blood fluctuates by volume of blood that almost correlates to body weight. Therefore, each

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subject who had been fasting for 4 hours administrated alcoholic beverage with an ethanol

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concentration of 0.4 g/kg body weight within 15 minutes by refer to previous research.

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the experiment, exhaled breath was directory applied to the ADH-immobilized mesh that was

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soaked with 500 µM NADH solution (in 300 µL, 0.1 M of Tris at pH 6.5) through a breath

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flow controller 41 that made a flow rate of the breath constant (40 mL/min). The measurement

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was taken place at -15, 0, 15, 30, 45, 60, 90, 120, and 180 minutes after drinking. In order to

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validate results by the AcH sniff-cam, the identical breath sample collected in a sample bag

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(Cat. No. 2-0081-03, As One, Japan) was measured simultaneously by a gas detection tube as

40

In


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a standard comparison. The concentration of breath AcH measured by the AcH sniff-cam was

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calculated using a calibration curve, and its spatial distribution was visualized using the image

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differential method.

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Visualization of distribution of the AcH released from palm skin

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For skin gas visualization, a palm was chosen due to convenience for the

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measurement. Taking an average size of palm into consideration, a larger (90 × 90 mm2)

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ADH-immobilized mesh than that used in breath AcH visualization was prepared. Preparation

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of this larger mesh was the same as the one for the breath experiment except for a point where

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a total amount of chemicals was increased proportionally to the size. Briefly, a mixture of

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13.17 mg of ADH, 20.0 mg of BSA and 1800 µL of PB was dropped and spread uniformly

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onto the cotton mesh, then left for 60 minutes in a refrigerator. Afterwards, ADH was cross-

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linked by 648 µL of GA in the refrigerator for 90 minutes. The mesh was then rinsed by 5000

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µL of Tris at pH 6.5 and wetted by 500 µM NADH solution (in 0.1 M of Tris at pH 6.5, 6075

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µL), followed by being placed in front of the camera. Figure 1d shows a skin gas injector with

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a thickness of 3 mm was composed of a polymethylmethacrylate (PMMA) frame and a

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honeycomb spacer for adequate imaging of spatiotemporal change of skin gas. Because it was

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used to keep the constant distance between the ADH-immobilized mesh and the palm skin

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contour surface. Imaging of transdermal AcH after drinking was performed by the following

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steps. First, a background image without skin gas was recorded for 60 s, and then skin gas

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was applied to the ADH-immobilized mesh by attaching a subject’s palm on the spacer for 20

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s. Afterwards, resultant fluorescence on the mesh was recorded by the camera for 60 s. An

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image of transdermal AcH distribution was made by subtracting the background image from

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the skin gas. The measurement was taken place at -15, 30, 60, and 90 minutes after drinking,



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and alcohol administration conditions were same with the above-mentioned breath

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experiment.

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Results and discussion

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Responsivity, quantitativity, and selectivity of the AcH sniff-cam

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Figure S-1a and S-1b show time courses of the mean intensity of the ROI and

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differential value. An SMA filter was applied to the intensity of the ROI at different frame

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numbers (n = 0, 4, 8, 16 and 32), and the differential values were obtained from the filtered

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intensity. The result indicated that the response time was almost the same among the frame

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number of 0–32. The relationship between noise and the number of frames in the SMA filter

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is shown in Figure S-1c. The standard deviation of the baseline (time from -20 to 0 s) was

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defined as a noise. The noises of both mean intensities of the ROI and differential value

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decreased as increasing the number of frames. However, the performance of SMA’s high-

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frequency noise reduction was saturated over 16 frames; thus, we used 16 frames for the SMA

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filter to the mean intensity of the ROI in subsequent experiments. We further investigate the

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influence of the frame number of the SMA filter on the differential value. As Figure S-2a

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shows, the time course of the differential values becomes smoother as increasing the frame

275

numbers. Figure S-2b summarizes response time and noise as a function of the number of

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frames. When 300 frames were used in the SMA filter, significantly small background noise

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was obtained as well as a good response time; therefore, we decided to use 300 frames in the

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SMA filter that was applied to the differential value.

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Figure 2a shows fluorescence and differential images 0, 20 and 120 s after applying 10

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ppm standard gaseous AcH to the ADH-immobilized mesh. Originally the fluorescence image

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at 0 second was uniformly bright image due to the presence of NADH on the mesh. The

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images in Figure 2a are the ones converted by equation 1. As a result of image differential


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method, observation of both spatial and temporal change of AcH concentration on the ADH-

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immobilized mesh surface was achieved (supplemental movie 1). Figure 2b shows temporal

285

changes of mean intensity of the ROI and differential value. The ROI intensity has reached a

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plateau after the initial increase and did not recover to the baseline even after AcH application

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was stopped. In contrast, the differential value exhibited a clear peak 20 s after applying AcH

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and returned to the baseline immediately after stopping AcH gas. Mean intensity of the ROI

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between 90–100 s after applying the AcH was defined as a signal output (∆I); the peak of the

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differential value was defined as a signal output of the differential value (∆D). The response

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time of mean intensity of the ROI T90 was defined as a time which took for signal to reach

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90% of ∆I; the response time of differential value TR was the time to reach peak maximum of

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∆D. It was revealed that the response time was improved by 15 s (T90 = 35 s and TR = 20 s for

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10 ppm AcH) using the image differential method. Changing of fluorescence intensity

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continued for a while even after stopping AcH gas since a little amount of AcH remained on

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the ADH-immobilized mesh. In contrast, a reaction speed was decreasing immediately

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because that of ADH was sensitive to the concentration of AcH. The differential value

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indicated the reaction speed of ADH reverse reaction. Therefore, the image differential

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method enabled to improve response time by accurately detect changing of concentration on

300

the ADH-immobilized mesh. Note that a speed of enzymatic reaction is proportional to

301

substrate concentration only in the first-order reaction region. Thus, an improvement of

302

reaction time may not be occured for high concentration of AcH.. However, this need not be

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taken into account in our experiment because AcH concentration in breath and skin gas are

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lower than 10 ppm.

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307 13 ACS Paragon Plus Environment


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Figure 3a shows temporal changes of a differential value to various concentrations of

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standard gaseous AcH, a calibration curve and differential images that were obtained 20 s

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after applying 1, 5 and 10 ppm AcH. Each plot in the calibration curve was taken from the

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peak of each differential value. As a result, the AcH sniff-cam showed a wide dynamic range

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(0.1–10 ppm) that encompasses a concentration range of breath AcH after drinking (0.4–9.0

313

ppm). The ADH-immobilized mesh was designed for disposable by concerning sanitary of the

314

system because the sniff-cam supposed to use in medical fields. Thus, note that each plot of

315

the calibration curve in figure 3a was measured by a different ADH-immobilized mesh that

316

was prepared at the same time. The coefficient of variation of ∆D among three deferent ADH-

317

immobilized mesh was 1.5% as shown in figure S-3. Plots were fitted by the following

318

equation with a correlation coefficient of 0.997:

∆ = 0.02 × [()* (""+)]- + 0.07 × [()*(""+)] + 0.08

Eq.4

319

Figure 3b displays relative outputs ∆D to investigate selectivity of the AcH sniff-cam

320

to gaseous AcH. The relative output was obtained by normalizing the output for each VOC by

321

that for 5 ppm AcH. It was observed that the AcH sniff-cam showed output signals only from

322

samples containing AcH, which validated a high selectivity of the AcH sniff-cam due to a

323

high substrate specificity of the enzyme.

324


325 326

Visualization of breath AcH

327

Figure 4a shows differential images of 0, 20 and 120 s after applying breath samples

328

from ALDH2[+] and ALDH2[-] subjects 30 minutes after drinking. The spatiotemporal

329

change of breath AcH could be visualized similarly to standard gaseous AcH. Figure 4b

330

displays time course of those differential values. Both peaked at about the same timing and

331

returned to the baseline, and breath AcH concentration of the ALDH2[-] subject was about 3-


Page 15 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


332

fold higher (8.4 ppm) than that of the ALDH2[+] (2.8 ppm). Stagnation of recovering to initial

333

value in differentiation value at around 10 s after differentiation value reaching peak was

334

observed unlike a result of standard gaseous AcH that was shown in Figure 2. This

335

phenomenon seems originated of humidity of exhaled breath. When the breath was loaded in

336

PTFE tube, the breath was cooled immediately, and then amount of saturated water vapor was

337

decreased, finally condensation was caused on wall of the PTFE tube. After that when

338

applying the breath was stopped and starting the applying dry carrier air, AcH remaining in

339

the PTFE tube as condensation was applying to ADH-immobilized mesh again. Therefore, the

340

stagnation of decrease of differentiation value was occurred. The differential analysis was

341

very sensitive to concentration change of AcH on ADH-immobilized mesh surface. As a

342

result, unexpected influence of humidity in breath was realized. Note that this little disorder

343

on response caused by the humidity of breath did not influenced quantifying the AcH in the

344

breath as described in following discussion.

345 346


347 348

Time courses of breath AcH concentrations for ALDH2[+] and ALDH2[-] are shown

349

in Figure 5. In the graphs, vertical bar graphs represent values of the standard comparison by

350

AcH detector tubes. The AcH sniff-cam revealed that AcH concentration in exhaled breath

351

initially increased and peaked 30 minutes after drinking, and then gradually decreased with

352

time. It was reported that the concentration of AcH in blood showed a maximum 15–30

353

minutes after drinking

354

concentration was related to ethanol metabolism, and it reflected AcH blood concentration.

355

Obtained peak breath AcH concentrations for ALDH2[+] and ALDH2[-] subjects were 2.75 ±

356

0.39 ppm and 8.64 ± 0.32 ppm, respectively; these values were in good agreement with

42

. Therefore, it was considered that the change of breath AcH



Page 16 of 30

13,43

. Also, AcH

357

reported results (ALDH2[+], 1.2 ± 1.0 ppm; ALDH2[-], 6.9 ± 2.5 ppm)

358

concentrations measured by detector tubes showed similar values and the same trend to the

359

AcH sniff-cam. These results and evidence demonstrated the sniff-cam’s capability of

360

accurate and quantitative visualization of the spatiotemporal distribution of breath AcH.

361 362


363 364

Distribution of AcH released from a palm skin

365

Figure 6a shows top and 30-degree tilted views of transdermal AcH distribution

366

released from a palm skin. Fluorescence intensity changed when applying skin gas, and this

367

image was created by merging pictures of a hand and a fluorescence distribution profile. From

368

the image, higher output was observed at around the metacarpal phalangeal joint of a second

369

finger and the thenar eminence than the other parts probably due to different emanation rate

370

over a palm skin as observed in our previous results of skin emanated ethanol that was

371

obtained by chemiluminescent sniff-cam

372

visualizing a concentration distribution of ethanol emanated from palm skin 31. More clearly

373

distribution image compared to previous one was obtained in this study. The difference was

374

seemingly made by an improvement of skin gas injector shown in figure 1d. Previously, skin

375

gas was applied to an enzyme immobilized mesh only using PMMA frame that had a 90 × 90

376

mm2 square hole. There was a possibility of touching an enzyme immobilized mesh when the

377

skin gas injector with a square hole was used; thus, skin surface had to fix in the air. Such a

378

situation, dilution, and agitation of skin gas could occur easily. In contrast, a honeycomb

379

spacer that allows fitting with skin surface at all position certainly without the possibility of

380

touching the ADH-immobilized mesh was newly added in this study. Thus, skin gas could be

381

applied to ADH-immobilized mesh directly without dilution and agitation. As the result, clear

44

. Fluorometric ethanol sniff-cam also achieved


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382

distribution image might have been obtained because of skin gas that reaching to the ADH-

383

immobilized mesh more increased than the previous system. However, the current AcH sniff-

384

cam cannot measure skin gas in real-time because a hand blocked the excitation light from the

385

UV-LED array when subject applied skin gas to the ADH-immobilized mesh. Therefore, the

386

image differential method could not be applied to the AcH sniff-cam. Figure 6b shows a time

387

course of mean intensity difference of the ROI ∆I from the 15 minutes before drinking. The

388

temporal change of ∆I showed a similar trend to the breath concentration. The concentration

389

of skin gas AcH was calculated by calibration curve based on difference of fluorescence

390

intensity between before and after exposure of AcH ∆I

391

exhaled breath. The results suggest that the measurement conditions of the calibration curve

392

were not fit to the measurement conditions of the skin gas. For example, standard gaseous

393

AcH has the flow-rate of 40 mL/min although flow-rate of skin gas was not constant.

32

showed higher than the one in the

394

Besides, parameters for formation of concentration distribution of AcH from palm skin

395

are still unclear. Perspiration is closely related to the release pathway of skin gas, and it is

396

reported that there is much number of sweat gland on palm skin than the other part of the

397

body.

398

occurs by measuring several biological information such as sweat rate, skin temperature and

399

concentration distribution of skin gas, simultaneously in the future.

45

Therefore, we expect to investigate mechanism in which concentration distribution

400 401


402 403

Conclusions

404

In this research, we developed the AcH sniff-cam using a reverse reaction of ADH and

405

an image differential method that allowed spatiotemporal visualization of gaseous AcH

406

concentration. After the system construction, the image differential method that calculated 17 ACS Paragon Plus Environment


Page 18 of 30

407

reaction speed of the reverse reaction was developed in order to improve temporal response of

408

the system. Characterization of the AcH sniff-cam revealed that the AcH sniff-cam had a

409

suitable dynamic range (100–10000 ppb) and selectivity for measurement of AcH in breath

410

and skin gas. Also, the image differential method allowed to improve temporal response by 15

411

s. Finally, spatiotemporal changes of AcH concentration in exhaled breath and distribution of

412

AcH in skin gas were visualized by the AcH sniff-cam. Breath AcH concentration peaked 30

413

minutes after drinking, and it was 3-fold higher for ALDH2[-] subject than that for the

414

ALDH2[+]. The difference in AcH release rate was also clearly visualized over a palm, which

415

also peaked 30 minutes after drinking. These results demonstrated that the sniff-cam holds a

416

huge potential for deployment in simple and noninvasive metabolism evaluation and disease

417

screening by acquiring spatiotemporal information of various VOCs in breath and skin gas.

418 419

Acknowledgement

420

This work was supported by the JSPS KAKENHI Grant Numbers JP17H01759,

421

JP16J09604, and JP15H04013, the Japan Science and Technology Agency (JST), and the

422

Ministry of Education, Culture, Sports, Science and Technology (MEXT) Special Funds for

423

Education and Research “Advanced Research Program in Neo-Biology”.

424 425

Supporting Information. Brief statement in nonsentence format listing the contents of the

426

material supplied as Supporting Information.

427

171208-AcH-vis-breath-skingas.docx Graphs about optimization of image analysis

428

parameter, reproducibility of the ADH-immobilized mesh

429

supplemental movie 1.avi Video of spatiotemporal change of AcH on the ADH-immobilized

430

mesh

431


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515


Graphics and captions

516 517

Figure 1. (a) Detection principle of AcH sniff-cam that employs a reverse reaction of ADH.

518

NADH absorbs UV light (λ = 340 nm) and emits fluorescence (λ = 490 nm). (b) Schematic

519

illustration of the experimental setup for characterization of the AcH sniff-cam. In

520

measurement of the exhaled breath, breath flow controller shown in (c) was used instead of

521

gas generator and MFCAcH in (b). In order to keep spaces between a palm skin surface and the

522

ADH-immobilized mesh constant, (d) PMMA frame and honeycomb spacer were used for

523

visualization of transdermal AcH.

524 23 ACS Paragon Plus Environment


Page 24 of 30

525 526

Figure 2. (a) Fluorescence (upper) and differential images (lower) obtained by AcH sniff-cam

527

0, 20 and 120 s after applying 10 ppm AcH. The differential images were created by applying

528

an image differential method to the fluorescence images. (b) Comparison of the signal

529

responses of fluorescence intensity and differential value. The average of the mean intensity

530

of the ROI between 90–100 s after applying the AcH was defined as a signal output (∆I); the

531

peak of differential value was defined as a signal output (∆D).

532


Page 25 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


533 534

Figure 3. (a) Calibration curve of the AcH sniff-cam to gaseous AcH. The dynamic range was

535

0.1–10 ppm with the correlation coefficient of 0.997. The inset shows time course of the

536

differential value with various concentration of AcH (0.1, 0.5, 1, 3, 5, 8 and 10 ppm). The

537

upper images are differential images 20 s after applying 1, 5 and 10 ppm of AcH. (b) The

538

selectivity of the AcH sniff-cam against typical chemical components in breath. The output of

539

each sample was normalized by that of AcH.

540 541



Page 26 of 30

542 543

Figure 4. (a)Differential images 0, 20 and 120 s after applying exhaled breath of ALDH2[+]

544

and ALDH2[-] subject 30 minutes after drinking. (b) Time course of the corresponding

545

differential values.

546


Page 27 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


547 548

Figure 5. Time course of concentration of breath AcH after drinking obtained from (a)

549

ALDH2[+] subjects and (b) ALDH2[-] subjects. As a comparison, the concentration was

550

measured by gas detection tubes simultaneously (vertical bar).

551



Page 28 of 30

552 553

Figure 6. (a) Distribution of transdermal AcH over a palm of ALDH2[+] subject 30 minutes

554

after drinking. (b) Time course of fluorescence intensity ∆I, differences from the intensity 15

555

minutes before drinking.

556


Page 29 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

557


for TOC only ADH

acetaldehyde

CH3CHO +

NADH

Ex. 340 nm

+

H+

pH6.5

ethanol

CH3CH2OH + NAD+

pH10.0 Fl. 490 nm

distribution of acetaldehyde UV-LED array

ADH-immobilized mesh

camera BPF

558


ADH


acetaldehyde

1 3 2 3 4 Ex. 340 nm 5 6 7 8 UV-LED array 9 10 11 12 13 14 15 16 17 18 19 20 ADH-immobilized mesh 21 22 23

CH CHO +

NADH

+

H+

pH6.5 pH10.0

Page 30 of 30

ethanol

CH3CH2OH + NAD+

Fl. 490 nm

distribution of acetaldehyde

camera BPF

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