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数智中医(闻)嗅诊研究进展

发表时间:2024年01月30日阅读:587次 下载:235次 下载 手机版

作者: 张玫 1, 2 钟瑞 1 魏旭煦 2 张晓雨 3 代倩倩 2 林家燕 1 赵晨 3 蒋寅 3 商洪才 2

作者单位: 1. 北京中医药大学中药学院(北京 102488) 2. 北京中医药大学东直门医院中医内科学教育部/北京市重点实验室(北京 100700) 3. 中国中医科学院中医临床基础医学研究所(北京 100700)

关键词: 数智中医 嗅诊 挥发性有机物 呼出气分析 中医诊疗仪器 疾病诊断

DOI: 10.12173/j.issn.1004-4337.202401029

基金项目: 国家重点研发计划“中医药现代化”重点专项(2022YFC3502300、2022YFC3502305);北京市自然科学基金项目(L222150)

引用格式: 张玫, 钟瑞, 魏旭煦, 张晓雨, 代倩倩, 林家燕, 赵晨, 蒋寅, 商洪才. 数智中医(闻)嗅诊研究进展[J]. 数理医药学杂志, 2024, 37(1): 2-21. DOI: 10.12173/j.issn.1004-4337.202401029

Zhang M, Zhong R, Wei XX, Zhang XY, Dai QQ, Lin JY, Zhao C, Jiang Y, Shang HC. Research progress on olfactory diagnosis of smart traditional Chinese medicine[J]. Journal of Mathematical Medicine, 2024, 37(1): 2-21. DOI: 10.12173/j.issn.1004-4337.202401029[Article in Chinese]

摘要| Abstract

嗅诊是中医“望、闻、问、切”四诊中“闻诊”的重要组成部分,通过辨气味诊察疾病、区分证型。虽然嗅诊在中医临床应用中有着悠久的历史,但其客观化、标准化仍是亟待解决的问题。近年来,随着分析化学、生物医学工程、人工智能等领域的迅猛发展,中医进入“数智化”发展新时代,这同时也促使嗅诊作为一种无创诊断方法愈发受到重视。本文对数智中医(闻)嗅诊的研究进展进行了综述,归纳了数智中医嗅诊研究对象、分析方法和科学仪器,概述了相关临床应用,总结了目前存在的挑战,并对中医智能(闻)嗅诊巨大的研究价值以及未来的发展进行了展望。

全文| Full-text

中医辨证是医家遣方用药的重要依据,“望、闻、问、切”四诊合参是中医基础诊断的核心方法[1]。四诊中的“闻诊”包括依靠听声音的“听诊”和依靠嗅气味的“嗅诊”,是指通过听声音和嗅气味以了解健康状况、诊察疾病的方法。其中“嗅诊”是指嗅辨患者身体气味与病室气味以诊察疾病的方法[2]。

古代医家以嗅诊指导临床有着悠久的历史[3]。最早关于“嗅诊”的记载可能是《黄帝内经·素问·金匮真言论》中提到:“肝……病之在筋,其臭臊;心……病之在脉,其臭焦;脾……病之在肉,其臭香;肺……病之在皮毛,其臭腥;肾……病之在骨,其臭腐”,提出了“五臭”的概念。《周礼·天官冢宰》中记载了西周时期“疾医掌养万民之疾病……以五气、五声、五色眡其死生”,这说明当时的医生就已经会根据病人的气味、声音、面色等判断其生死。《难经·十四难》中记载:“肝色青,其臭臊……心色赤, 其臭焦……脾色黄,其臭香……肺色白,其臭腥……肾色黑,其臭腐”,《难经·四十九难》中记载:“心主臭,自入为焦臭,入脾为香臭,入肝为臊臭,入肾为腐臭,入肺为腥臭。故知心病伤暑得之,当恶焦臭”,分别描述了五脏的“色”与“臭”,将嗅气味作为一种诊断方法。秦汉时期,中医药开始兴起,人们逐渐理解疾病、积累诊疗经验,《金匮要略·肺痿肺痈咳嗽上气病脉》中描述了气味“浊唾腥臭”,为肺中热壅毒蕴、血败肉腐,酿成痈脓之象。晋唐宋金元时期,中医药理论逐渐形成一套完整的体系,对闻诊的进一步重视使得嗅诊也随之发展起来。晋代王叔和的《脉经》中提到扁鹊推断病危的方法有“病患尸臭者,不可治”;以及“热病……身麻臭,伏毒伤肺”,认为黄疽病人出现臭气等气味变化为肺脾两脏气绝之死候。到明清时期,嗅诊的运用愈发频繁,渐成学说。清代戴天章在《广瘟疫论》中提出诊伤寒要五辨,首先辨气,“风寒气从外收敛入内,病无臭气触人,间有作臭气者,必待数日转阳明腑证之时,亦只作腐气,不作尸气。”在宏大的中医诊断史中,嗅诊的重要性可见一斑。

中医认为,人体的各种气味都是在脏腑生理活动和病理变化过程中产生的。在疾病情况下,由于邪气侵扰,气血运行失常,脏腑机能失调,秽浊排除不利,产生腐浊之气,可表现出体气、口气、分泌物、排泄物的气味异常[2]。因此,基于嗅诊辨别气味变化可以判断脏腑的生理和病理变化,为诊病、辨证提供依据。然而,嗅诊在中国古代多凭医者主观嗅觉而定,缺乏客观依据与标准,也导致难以传承。研究发现,人类嗅觉会受到衰老影响[4-5],也与性别有关。普遍来说,女性比男性嗅觉更加灵敏,这在非人灵长类动物中也得到证实[6-7]。人类对物质的敏感程度也有所不同,存在个体差异,可能存在对各自嗅觉较为敏感的物质[8]。而且,如果长期生活在某种气味中,人们对该气味辨识的阈值也会下降,可谓“入芝兰之室,久而不闻其香;入鲍鱼之肆,久而不闻其臭”[9]。此外,人类的嗅觉也会受到心理因素的影响[10]。上述因素都表明,嗅诊的标准化、客观化是中医药学领域亟待解决的问题。

近年来,随着分析化学、生物医学工程等理工科迅猛发展,特别是人工智能技术从20世纪中期发展至今日臻成熟,“数智中医”在医疗领域的应用场景亦愈发丰富[11-13]。而嗅诊作为一种无创诊断方法也更加受到重视,推进了中医嗅诊逐渐向数据化、标准化、客观化、智能化方向发展,目前已初步形成了数智中医闻嗅诊研究方向,这是对中医嗅诊的重要传承与创新。数智中医闻嗅诊的研究内容不仅包括通过分析患者的体味、口鼻气息,以及分泌物和排泄物等产生的气味来判断患者的健康状况和疾病类型,还包含发展对病人气味进行分析的分析方法、关键技术以及研发相关科学仪器,建立各种疾病气味数据库,健全人体气味学等,从而为临床诊断提供定性定量的数智化标准。本文综述了现阶段与数智中医嗅诊相关的研究对象、分析方法和科学仪器,概述了相关医学应用,总结了目前存在的挑战,并对中医智能嗅诊领域在未来的发展进行了展望。

1 数智中医嗅诊的分析对象

嗅诊的分析对象主要包括病体之气与病室之气,通过嗅辨患者身体气味、分泌物和排泄物气味,以及病室气味达到诊察疾病的目的。通过定性定量分析样品中的无机气体分子或挥发性有机物(volatile organic compounds, VOCs)等,再经过数据处理,对疾病及中医证型进行诊断。其中,病体之气是指病体散发的各种异常气味,主要包括口气、汗气、痰涕之气、呕吐物之气、排泄物之气等,分别来自患者皮肤、黏膜、呼吸道、胃肠道、呕吐物、排泄物、分泌物、脓液和血液等(图1)。不同个体年龄、性别、遗传基因、生理特征、新陈代谢产物均有很大差别,正常和病理状态下的人体代谢以及与微生物群的相互作用也会影响呼出气体中的化合物成分[14]。因此,病体之气为数智中医嗅诊研究提供了主要的分析对象。病室之气则因气味从病体发展到充斥病室,说明病情危重。临床上通过分析病室气味,也可作为推断病情及诊断特殊疾病的参考。

1.1 口气

在中医诊断学中,“口气”是指从口内呼出的秽浊臭气,又名口臭、口殠。中医认为口气源于五脏六腑功能失调,《诸病源候论》中写道:“五脏六腑不调,气上胸膈……蕴积胸膈之间,而发于热,冲发于口,故令臭也。”中国古代医家注意到多种类型的口气,如口酸,指口中自觉有酸味,甚者闻之有酸味[15]。《诸病源候论》中有云:“唁酸者,上焦有痰,脾胃有宿冷,故不能消谷,谷不消则胀,满而气逆,所以好隐而吞酸,气息醋息”,认为口酸是胃冷不能化食而致。又如口臭,元代朱震亨《丹溪手镜》中“妨于食(肝伤脾),病至先闻腥臊臭”,清代叶天士《临证指南医案》中“内应乎肝……口气皆臭”,均是在不同的肝病情况下对病人产生的肝臭及其辨证的详细叙述。口臭绝大多数情况都是由口腔内部疾病引起的,如牙龈炎、牙周炎、龋齿等[16-17],消化系统和呼吸系统疾病也可引起口臭,一些糖尿病患者在出现酮症酸中毒时呼出气会有烂苹果气味[18]。有些肝功能损害严重的患者呼出气中会带有特殊鼠臭味,俗称肝臭[19]。患者呼出的异味气体中被认为存在提示各种疾病的重要生物标志物。

口气的气味取决于呼出气中化合物的成分,成分特征也反映着人体各种生理和病理状况[20]。在过去几年中,呼出气的异常气味与呼出气分析引起了研究人员的极大兴趣。人体的呼出气主要包括无机气体分子,如氮气、氧气、二氧化碳、水蒸气、惰性气体和种类繁多的微量VOCs。人体呼出气中含有大量VOCs,既包括代谢活动产生的内源性VOCs,也包括通过饮食和环境摄入的外源性VOCs[21-24]。这些VOCs可溶解于血液中,随循环系统通过肺泡进入呼吸道。呼出气分析不仅被用于了解人体新陈代谢情况,还因其具有非侵入性和连续采样的可能性,因而具有巨大的临床潜力[25]。呼出气分析可用于疾病的早期诊断与筛查[26-29]、重症监护[30-31]、手术期间及手术前后的监测[32-35]等。但呼出气中VOCs含量低也为准确定性定量分析带来挑战,这就需要在样品采集、VOCs富集,以及提升仪器性能、提高检测灵敏度等方面不断突破创新。需要指出的是,近年来虽然不断有以呼出气为分析对象的研究发表[20, 36],与呼出气分析相关的关键技术、仪器研发、算法开发均受到关注,但以中医(闻)嗅诊为关注点的呼出气分析研究尚未见报道。

  • 图1 数智中医嗅诊中病体之气的来源
    Figure 1.The source of sickness smell in olflactory diagnosis of smart TCM

1.2 汗气

中医学理论认为汗液是由津液所化生,在《黄帝内经》中有“心在液为汗”的论述;《临证指南医案·汗》中用“阳加于阴,谓之汗。由是推之,是阳热加于阴,津散于外而为汗也”概括了出汗机理[37]。目前中医嗅诊对汗液气味的关注较少,已有的相关报道主要涉及腋臭。腋臭又称“胡臭”“体气”“狐臭”“腋气漏”等,最早记载于《肘后备急方》,其余中医著作对腋臭也有记载,如《诸病源候论》曰:“此亦是气血不和,为风邪所搏,津液蕴瘀,故气湿臭”;又如《三因方》有云:“夫胡臭者,多因劳逸汗渍,以手摸而嗅之,故清气道中受此宿秽,故传而为病。方论有天生臭之说,恐未必竟然[38]。”目前在中医学文献中,除了“腋臭”被认为是与汗出气味相关的描述之外,其余关于疾病、证型与汗气的关系鲜有文献报道。中医诊断学对病理性汗出的主要关注点集中在出汗量异常,以及基于有无汗出、汗出时间、部位做出对疾病的诊断。事实上,汗液能够传递的信息相当丰富,已知细胞外液是汗液的重要组成部分,因此,汗液中溶质的浓度被认为与该溶质在血液中的浓度直接相关。汗液中包含数百种化学成分,包括电解质、代谢物、激素、微量元素、药物等,此外,皮肤分泌汗液的速度和汗量均能够反映健康信息。因此,汗液/汗气分析有望在未来作为血液分析的非侵入性替代诊断方法。目前基于对汗液中VOCs的分析已被用于诊断癌症[39-40]、预警癫痫[41]、判断情绪压力[42]、法医学追踪犯罪[43]等,这些研究实例为未来智能中医嗅诊开展汗气分析提供了宝贵经验。

1.3 痰涕、呕吐物、排泄物之气

中医学所说的“痰涕之气”包括鼻腔和咳吐物的气味。痰液、鼻涕、呕吐物与排泄物的异味均属中医嗅诊关注的范畴,可在中医学典籍中发现对上述异常气味与疾病/证型关系的描述。近年来分析化学和临床检测等领域已有对痰液、呕吐物与排泄物中VOCs进行分析的应用,但以中医嗅诊为关注点的研究尚未见报道。

正常状态下,人体排出的少量痰和涕无异常气味。中医认为咳吐浊痰脓血,腥臭异常者,多为肺痈,是热毒炽盛所致;若咳痰黄稠味腥者,是肺热壅盛所致[44]。《本草纲目》曰:“脑崩臭秽,是下虚”,湿热内蕴,热移于脑,则会出现流涕黄浊,气味腥臭[15]。《证治要诀·诸嗽门》指出,劳咳患者咳痰气味:“劳咳有久嗽成劳者,有因久病劳咳者,其证往来寒热或独热无寒,咽干嗌痛,精神疲极,所嗽之痰或时有血腥臭异常。”目前痰液中VOCs分析已被用于辅助诊断严重哮喘[45]和肺结核[46],也被用于识别细菌定植与感染[47-49]。关于呕吐,中医学理论认为呕吐是胃气上逆所致,临床诊断时通常会结合呕吐物的形态、气味与病人呕吐时的表现做出诊断。中医嗅诊认为:呕吐物清稀,无臭味,多属胃寒;气味酸腐臭秽者,多属胃热;呕吐未消化食物,气味酸腐,为食积;呕吐脓血而腥臭,多为内有痈疡[2]。在实际应用中,呕吐物中的成分,包括VOCs,常被用于确定引起中毒的毒性物质[50-51]。在中医诊断学中,排泄物之气主要指尿液和粪便等散发的气味。《类证治裁·三消论治》曰:“小水不臭反甜,此脾气下脱症最重。”尿液气味恶臭是由于湿热内蕴膀胱。《景岳全书》中提到:“假寒者。火极似水也……以致下利纯清水,而其中仍有燥粪,及失气极臭者,察其六脉,必皆沉滑有力,此阳证也。”中医学理论认为大便酸臭难闻,为肠有积热;溏泻而腥者,多为脾胃虚寒;大便泄泻臭如败卵,夹有不消化食物、矢气酸臭者,为伤食。小便黄赤混浊,有臊臭气味,多属膀胱热;尿甜有烂苹果气味者,为消渴[2]。此外,经带之味也可指征疾病,《医宗金鉴·妇科心法要诀·调经门》曰:“凡血为热所化,则必稠粘臭秽;为寒所化则必清澈臭腥”“若形清腥秽,乃湿淤寒虚所化也”,即多因湿热、寒湿所致。已有多项研究表明,尿液和粪便VOCs可提供生物标志物用以诊断疾病,如新生儿筛查[52]、恶性胆道狭窄[53]、结直肠炎/癌[54-57]等,这些研究为未来中医智能嗅诊领域的发展提供了可靠的临床依据。

2 数智中医嗅诊的分析技术、方法与仪器

正所谓“工欲善其事,必先利其器”,自法国化学家Antoine Lavoisier建立了世界上第一套测量呼吸过程的实验装置以来,人类在分析化学与精密仪器制造领域不断取得进展,这也为大力推进数智中医嗅诊发展提供了可能[58]。本文以呼出气分析为代表,分类介绍了目前可用于数智中医嗅诊的主要分析技术,包括色谱、质谱(mass spectrometry, MS)、光谱、离子迁移谱(ion mobility spectroscopy, IMS)、电子鼻等,并对各种技术方法的优越性进行了总结。

2.1 色谱分析

常见的色质联用方法集成了色谱的优良分离能力和质谱的高灵敏度检测等优势,均可用于VOCs分析,包括气相色谱-质谱联用(gas chromatography-mass spectrometry, GC-MS)、液相色谱-质谱联用(liquid chromatography-mass spectrometry, LC-MS)和毛细管电泳-质谱联用(capillary electrophoresis-mass spectrometry, CE-MS)等。

GC-MS分析目前是VOCs检测的金标准,其主要优势在于GC具有强大的分离能力以及GC-MS分析具备标准谱库[59]。对于分析呼出气冷凝液、尿样、粪便等非气体样品中VOCs的需求,GC可提供顶空进样方式,因此,GC-MS是目前对VOCs分析使用最为广泛的方法。但采用GC-MS分析呼出气中VOCs也并非完美的解决方案,因为呼出气中VOCs含量非常低,在正常生理新陈代谢条件下,人体呼出气中VOCs浓度约为10-12~10-9 mol·L-1[60]。而GC-MS分析VOCs,尤其是采用顶空进样方式时,若VOCs水平低于百万分之一体积(parts per million by volume, ppmv),则很难准确定量。研究者通过对比实验证明了GC-MS更适合监测含有大量高浓度VOCs的样品[59]。当然,采用GC-MS方法分析VOCs也在不断被优化[61],建立了通过富集等方式提高检测灵敏度的解吸气质谱联用分析方法[62-63]、顶空固相微萃取气质谱联用分析方法[64-65]、二维GC-MS(GC×GC)分析方法[66]等。此外,GC-MS仪器硬件也在不断革新[67-69],图谱识别算法也变得对用户更加友好且功能强大,有学者建立了基于呼吸分析的智能COVID-19筛查平台[70]。值得一提的是GC-MS仪器的国产化和小型化,目前禾信仪器、聚光科技、皖仪科技、谱育科技等多家国内仪器公司均已在GC-MS领域具有一定影响力。便携GC和GC-MS也为VOCs样品的现场分析提供了可能[68-69, 71]。

相较于GC-MS,LC-MS更适合分析高沸点的VOCs[72-73];CE-MS的优点是适用于亲水性代谢物VOCs、分离效率高且分析耗时短[74-75]。但LC-MS和CE-MS均不是VOCs分析的首选方法,二者的一个共性缺点是没有标准谱库。近年来敞开式离子化技术迅猛发展,一系列质谱直接分析新方法被开发出来,因此采用LC-MS和CE-MS分析VOCs的研究就越来越少。

2.2 质谱分析

虽然GC-MS是目前应用最广泛的VOCs分析方法,但常规GC-MS分析往往局限于实验室环境,且分析时间相对较长。针对上述问题,研究者们开发了一系列质谱直接分析方法。这类方法无需对样品进行分离、富集、衍生化等前处理,使质谱分析过程更为便捷。此外,针对VOCs分析的微型质谱关键技术也不断取得突破,相应的数据处理算法也在蓬勃发展[76],这些都为即时呼出气现场检测的实现提供了可能,极具应用前景。

2.2.1 质子转移反应质谱

质子转移反应质谱(proton-transfer reaction mass spectrometry, PTR-MS)是目前实时检测气体样本中痕量VOCs最常用的方法[77-80]。PTR-MS应用了真空化学电离方法,常规的PTR-MS采用H3O+作为反应离子,因大多数VOCs的质子亲和性都高于水分子,因此在漂移管中H3O+会将质子传递给这些VOCs使其离子化。随后也有学者发展PTR-MS使其拥有了更多的反应离子种类,方法的适用范围得到了拓展[81-82]。PTR-MS可实现定量分析,这是由于漂移管长度固定,且特定种类的VOC从H3O+获得质子的反应动力学常数也恒定。但需注意呼出气中存在萜烯类VOCs,它们可能会在漂移管中发生碎裂,因而绝对定量更为复杂[83-85]。PTR-MS分析主要优势之一在于质子转移反应几乎不会使产物离子发生碎裂,这有利于从谱图中定性识别VOCs[86],此外,定性准确性也取决于质量分析器的种类,因此催生出PTR-TOF-MS[83, 87-88]、PTR-QiTOF-MS[89-91]等PTR-MS新仪器。

2.2.2 选择离子流管质谱

选择离子流管质谱(selected-ion flow-tube mass spectrometry, SIFT-MS)也采用真空条件下的化学电离方法,可实现对呼出气样品中VOCs待测物的直接质谱分析[92]。SIFT-MS是一种成熟方法,它首先通过电子轰击或微波放电产生H3O+、NO+或O2+试剂离子[93-96]。由于不像常规PTR-MS的试剂离子仅有H3O+一种,SIFT-MS先将试剂离子引入四极杆进行筛选,再导入氦缓冲漂移管中与待测VOCs分子发生电荷转移反应。在分析普通环境气体时,由于很多离子反应动力学已被研究得颇为透彻,研究人员可据此将质谱信号强度直接转化为待测物的绝对浓度。但在分析呼出气VOCs含量时情况变得较为复杂,这是由于样品湿度大[97],还需要考虑到可能形成水合离子等因素。早期SIFT-MS多采用四极杆质量分析器,近年来也出现了SIFT-TOF-MS新仪器[98],以及在漂移管中施加电场[99]等质谱硬件改进。

相较于常规PTR-MS,SIFT-MS在VOCs定性分析上可能更具优势,这是因为它可以通过改变试剂离子,使特定化合物的分析更具选择性[100]。PTR-MS灵敏度更高,因为样品气体本身在漂移管中充当了缓冲气体,从而避免了样品被稀释。而且PTR-MS不需要在漂移管前端放置四极杆,仪器构成也更加简单。此外,SIFT-MS和PTR-TOF-MS之间数据输出的可移植性也引起了关注[101]。

2.2.3 二次电喷雾电离质谱

二次电喷雾电离质谱(secondary electro-spray ionization mass spectrometry, SESI-MS)可以视作是常规电喷雾质谱在电离气态分析物时的特殊情况,如电离待测物蒸气。SESI-MS先通过纳升电喷雾产生反应物离子团簇(在呼出气分析中主要为H3O+),继而反应物离子与喷雾羽流中的待测物蒸气混合,产生的电离蒸气被吸入质谱仪进行分析。在分析一般气体样品时,SESI-MS的电离机制已被证明是基于气态分子-离子反应[102]。然而,呼出气样品湿度高,SESI-MS分析呼出气的电离机制可能更接近待测物蒸气与带电微液滴的相互作用。SESI-MS分析呼出气已被用于疾病诊断[103-105],包括睡眠呼吸暂停监测[106]、儿童哮喘的诊断与管理[107]、细菌感染[108]、肺囊性纤维化[109]等。与PTR-MS或SIFT-MS相比,SESI-MS中的电离发生在更高压力下(105 Pa相较于约102 Pa),这使得SESI-MS在分析较大分子时具有更高的离子化效率[110]。

2.2.4 电喷雾萃取电离质谱

电喷雾萃取电离质谱(extractive electrospray ionization, EESI-MS)是基于电喷雾的常温常压直接质谱分析技术。EESI-MS采用“Y形”的双喷雾形式,一支喷雾负责将电场能量转移到带电的溶剂微滴上,形成具有一定能量的初级试剂离子;另一支喷雾负责提供中性待测物微液滴。接下来初级试剂离子与中性待测物在三维空间中接触、碰撞,发生能量与电荷的传递,完成待测物的离子化过程[111]。EESI-MS与SESI-MS的相似之处在于二者都是中性待测物与带电初级试剂离子之间碰撞发生反应,实现了待测物离子化,主要区别在于待测物在EESI中是以微液滴的液体形态被提供,而在SESI中则是以待测物蒸汽等中性气体形式被提供。因此,SESI-MS适用于VOCs等气态样品的分析,而EESI可能样品范围更广,还包括液体样品等。近年来基于EESI-MS对呼出气进行分析也拓展了很多临床应用[112],如肺癌[113]和慢性肾病[114]患者的鉴别等。应当指出的是,SESI-MS与EESI-MS分析的定性、定量能力也与是否使用高分辨质量分析器密切相关。

2.2.5 等离子体质谱

等离子体质谱是一大类环境电离质谱技术,其电离机制通常涉及通过等离子体与环境空气中的大气水相互作用形成的H3O+簇对分析物进行质子化[115-116],因此所获得的质谱图通常不含有繁杂的碎片离子峰,而主要生成易于解释的质谱图。等离子体质谱离子源不依赖于高纯度溶剂,其普遍优势在于结构简单坚固且价格低廉。目前基于等离子体电离技术已经研发出多款离子源,都可以实现对呼出气的分析[117],如实时直接分析(direct analysis in real time, DART)[118-120]、大气压辉光放电(atmospheric-pressure glow discharge, APGD)[121-122]、流动大气压余辉电离(flowing atmospheric-pressure afterglow, FAPA)[121, 123-124]、介质阻挡放电电离(dielectric-barrier discharge ionization, DBDI)[125]、低温等离子体电离(low temperature plasma ionization, LTPI)[124, 126]等。

2.2.6 光致电离质谱

光致电离(photoionization, PI)是指光子与原子或分子相互作用形成离子的物理过程,其主要优点包括离子化效率高,生成的质谱图碎片离子峰少,易于解释。目前基于PI也已开发出许多质谱技术用于呼出气分析,如大气压光离子化(atmospheric pressure photoionization, APPI)[127]、大气压或中压激光离子化(atmospheric/medium pressure-laser ionization, APLI/MPLI)[128-129]等。此外,PI也是离子迁移谱检测呼出气常用的离子化方法[130]。

2.3 光谱分析

光谱分析方法是通过测量物质与辐射能作用时其内部发生量子化的能级间跃迁产生的发射、吸收或散射辐射的波长和强度来鉴别物质,以及确定其化学组成和相对含量的方法。目前光谱分析应用于临床呼出气检测主要使用近红外和中红外光源,主要优势在于可在非接触且无损伤条件下对样品进行测量,且操作简便,易对非专业人员推广普及[131]。

常见的呼出气光谱分析手段包括傅里叶变换红外光谱(Fourier transform infrared spectroscopy, FTIR)[132-137]、可调谐半导体激光吸收光谱(tunable diode laser absorption spectroscopy, TDLAS)[131, 138- 139]、光腔衰荡光谱(cavity ring-down spectroscopy, CRDS)[140-142]、光声光谱(photo acoustic spectroscopy, PAS)[143]等。光谱法分析呼出气样品的检测目标物通常是呼出气中的无机气体分子,其中FTIR是目前光谱法分析呼出气样品的主流技术,它利用不同物质在红外区不同波长下的吸收特征实现对物质的鉴别,具有快速稳定、技术成熟的特点,已有相应的市售产品[144-146]。

2.4 电子鼻

电子鼻也称人工嗅觉系统,其设计灵感源于对生物嗅觉系统的模仿[147]。生物嗅觉系统包含嗅上皮组织、嗅球和大脑皮层三部分,分别起到气味感知、气味信号处理传输和形成嗅觉的作用。因此,典型的电子鼻包括气敏传感器阵列、信号处理电路和模式识别单元三个组成部分。传感器是电子鼻最核心的组件单元,目前常见的传感器类型主要包括金属氧化物、导电聚合物、场效应晶体管和石英晶体微天平等,对这些结构和材料的不断优化提高了分析复杂气体混合物的能力。近年来,人工智能彻底改变了电子鼻领域,如人工神经网络、深度卷积神经网络、尖峰神经网络算法等。目前电子鼻已被广泛应用于哮喘[148]、感染[149-151]、肺癌[152]、胃肠道疾病[153]等多种疾病的诊断与监测。研究人员通常描述电子鼻能提供样品中挥发性成分的整体信息,即获得模拟嗅觉“指纹”数据的原因是将数据处理并入了电子鼻分析的定义之内。然而,可能由于历史习惯等,在描述色质联用、质谱或光谱分析时,往往用“分析”代表定性、定量检测样品中某(几)种成分的过程,但实际这些分析也必然是需要数据处理和算法支持的,依据测得的定性、定量结果,最终同样可以实现对样品的分类判别等。近年来随着电子鼻微型化的发展,也出现了微型化的传感器,如微机电系统(micro electro mechanical systems, MEMS)[154]。MEMS是自主的、毫米或微米级的独立智能系统,由传感器、执行器和微能源组成,通过芯片上的微电路和微机械技术集成。基于微机电系统的电子鼻(MEMS-based enose)也已被应用于分析呼出气辅助诊断疾病,如糖尿病 [155]等。

3 数智中医嗅诊的临床应用与潜力

目前VOCs分析已经越来越多地应用于临床样品的检测,主要应用场景包括对呼吸系统、消化系统、循环系统、神经系统疾病的区分与辨识等。用于VOCs分析的临床样品来源多数为呼出气,也有血液和粪便样品等。本文对目前已经进行到临床试验阶段的VOCs分析进行了归纳,见表1。

  • 表格1 进行VOCs分析的临床试验
    Table 1.Clinical trials involving VOCs analysis

在上述临床试验中,绝大多数试验均表明VOCs指纹谱可以表征人体代谢变化,特征VOCs的定性、定量分析已被明确可以辅助多种疾病的诊断,这些结论为中医嗅诊的客观化、数智化发展奠定了良好的先行基础。当然,上述临床研究也提出了亟待解决的问题,如呼出气湿度大、呼出气中VOCs含量低,需提高检测灵敏度等。在这些方向上进行技术提升将有助于大幅提高VOCs分析的准确性,可能的方法包括发展VOCs富集技术,以及提升检测仪器的性能等。

4 结语

中医诊断学的基本原理可以概括为“由表及里”。中医病证与人体气味变化密切相关,嗅诊正是基于这些相关性来“司外揣内”,用于辨别病证性质。本文系统梳理了中医嗅诊的历史渊源与发展、可用于嗅诊的样品来源、可服务于中医嗅诊的现代分析技术,并归纳总结了目前与嗅诊相关的临床试验实例。随着新技术方法的不断发展,大数据与人工智能的日臻成熟,基于国产精密仪器制造业与中医嗅诊理论深度融合的数智中医嗅诊即将迎来实现客观化、智能化、智慧化的时代,这不仅有利于中医诊断技术的传承,也必将促进中医现代化发展。

参考文献| References

[1] 赵文, 张佳, 徐佳君, 等. 四诊合参智能化发展现状及实现路径[J]. 中医杂志, 2020, 61(1): 58-62, 67. [Zhao W, Zhang J, Xu JJ, et al. Four diagnosis comprehensive analysis intellectualization: development status and pahts[J]. Journal of Traditional Chinese Medicine, 2020, 61(1): 58-62, 67.] DOI: 10.13288/j.11-2166/r.2020.01.013.

[2] 李灿东. 中医诊断学[M]. 北京: 中国中医药出版社, 2016. [Li CD. Diagnostics in Chinese Medicine[M]. Beijing: China Press of Traditional Chinese Medicine, 2016.]

[3] 于国东,高也陶. 五气参两:嗅诊的渊源、式微与复兴[J]. 医学与哲学, 2021, 42(13): 58-61, 72. [Yu GD, Gao YT. Consulting and contrasting FIVE-QI: the origin,decline and revival of olfactory diagnosis[J]. Medicine & Philosophy, 2021, 42(13): 58-61, 72.] DOI: 10.1204/j.issn.1002-0772.2021.13.13.

[4] Dan X, Wechter N, Gray S, et al. Olfactory dysfunction in aging and neurodegenerative diseases[J]. Ageing Res Rev, 2021, 70: 101416. DOI: 10.1016/j.arr.2021.101416.

[5] Schubert CR, Fischer ME, Pinto AA, et al. Odor detection thresholds in a population of older adults[J]. Laryngoscope, 2017, 127(6): 1257-1262. DOI: 10.1002/lary.26457.

[6] Pfabigan DM, Vezzani C, Thorsby PM, et al. Sex difference in human olfactory sensitivity is associated with plasma adiponectin[J]. Horm Behav, 2022, 145: 105235. DOI: 10.1016/j.yhbeh.2022.105235.

[7] Laska M, Wieser A, Hernandez Salazar LT. Sex-specific differences in olfactory sensitivity for putative human pheromones in nonhuman primates[J]. J Comp Psychol, 2006, 120(2): 106-112. DOI: 10.1037/0735-7036.120.2.106.

[8] Oleszkiewicz A, Alizadeh R, Altundag A, et al. Global study of variability in olfactory sensitivity[J]. Behav Neurosci, 2020, 134(5): 394-406. DOI: 10.1037/bne0000378.

[9] Mignot C, Schunke A, Sinding C, et al. Olfactory adaptation: recordings from the human olfactory epithelium[J]. Eur Arch Otorhinolaryngol, 2022, 279(7): 3503-3510. DOI: 10.1007/s00405-021-07170-0.

[10] Hoenen M, Wolf OT, Pause BM. The impact of stress on odor perception[J]. Perception, 2017, 46(3-4): 366-376. DOI: 10.1177/0301006616688707.

[11] 商洪才, 张晓维. 数智融合促进中医药传承创新发展[J]. 北京中医药, 2023, 42(5): 464-466. [Shang HC, Zhang XW. Integrating digital intelligence to promote the inheritance, innovation and development of traditional Chinese medicine[J]. Beijing Journal of Traditional Chinese Medicine, 2023, 42(5): 464-466.] DOI: 10.16025/j.1674-1307.2023.05.001.

[12] 商洪才. 临床“有毒”中药数智融合研究新模式:中药循证毒理学的提出[J].科学通报, 2022, 67(2): 118-124. [Shang HC. New mode of data-intelligence fusion research on clinical “toxic” Chinese medicines: the proposal of evidence-based Chinese medicine toxicology[J]. Chinese Science Bulletin, 2022, 67(2): 118-124.] DOI: 10.1360/TB-2021-1010.

[13] 陈昭, 郑蕊, 邱瑞瑾, 等. 基于数智融合的中西药并用代谢性药物肝损伤预警方法的构建[J]. 中华中 医药杂志, 2023, 38(4): 1413-1417. [Chen Z, Zheng Rui, Qiu RJ, et al. Construction of early warning methods of metabolic drug-induced liver injury with traditional Chinese medicine and Western medicine combination based on digital-intelligence fusion[J]. China Journal of Traditional Chinese Medicine and Pharmacy, 2023, 38(4): 1413-1417.] http://qikan.cqvip.com/Qikan/Article/Detail?id=7109629539&from=Qikan_Search_Index

[14] 李承木, 邬小萍. 呼出气体组分分析在临床实践中的应用进展[J]. 新发传染病电子杂志, 2023, 8(2): 78-81. [Li CM, Wu XP. Research progress in component analysis of exhaled breath[J]. Electronic Journal of Emerging Infectious Diseases, 2023, 8(2): 78-81.] DOI: 10.19871/j.cnki.xfcrbzz.2023.02.017.

[15] 刘莺. 闻气味的研究与展望[J]. 中医药信息, 1991(1): 9-12. [Liu Y. Research and prospects of smell and odor[J]. Information on Traditional Chinese Medicine, 1991(1): 9-12.] DOI: 10.19656/j.cnki.1002-2406.1991.01.005.

[16] Li Z, Li J, Fu R, et al. Halitosis: etiology, prevention, and the role of microbiota[J]. Clin Oral Investig, 2023, 27(11): 6383-6393. DOI: 310.1007/s00784-023-05292-9.

[17] Lowe H, Toyang N, Steele B, et al. The current and potential application of medicinal cannabis products in dentistry[J]. Dent J (Basel), 2021, 9(9): 106. DOI: 10.3390/dj9090106.

[18] Moldovanyi CP. Fruity breath odor: two major implications[J]. Nursing, 1988, 18(3): 65-69. DOI: 10.1097/00152193-198803000-00027.

[19] Van den Velde S, Nevens F, Van Hee P, et al. GC-MS analysis of breath odor compounds in liver patients[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2008, 875(2): 344-348. DOI: 10.1016/j.jchromb.2008.08.031.

[20] Zhang X, Frankevich V, Ding J, et al. Direct mass spectrometry analysis of exhaled human breath in real-time[J]. Mass Spectrom Rev, 2023. DOI: 10.1002/mas.21855.

[21] Amann A, Costello Bde L, Miekisch W, et al. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva[J]. J Breath Res, 2014, 8(3): 034001. DOI: 10.1088/1752-7155/8/3/034001.

[22] de Lacy Costello B, Amann A, Al-Kateb H, et al. A review of the volatiles from the healthy human body[J]. J Breath Res, 2014, 8(1): 014001. DOI: 10.1088/1752-7155/8/1/014001.

[23] Amann A, Mochalski P, Ruzsanyi V, et al. Assessment of the exhalation kinetics of volatile cancer biomarkers based on their physicochemical properties[J]. J Breath Res, 2014, 8(1): 016003. DOI: 10.1088/1752-7155/8/1/016003.

[24] Pleil JD, Stiegel MA, Risby TH. Clinical breath analysis: discriminating between human endogenous compounds and exogenous (environmental) chemical confounders[J]. J Breath Res, 2013, 7(1): 017107. DOI: 10.1088/1752-7155/7/1/017107.

[25] Amann A, Miekisch W, Schubert J, et al. Analysis of exhaled breath for disease detection[J]. Annu Rev Anal Chem (Palo Alto Calif), 2014, 7: 455-482. DOI: 10.1146/annurev-anchem-071213-020043.

[26] Mäkitie AA, Almangush A, Youssef O, et al. Exhaled breath analysis in the diagnosis of head and neck cancer[J]. Head Neck, 2020, 42(4): 787-793. DOI: 10.1002/hed.26043.

[27] Einoch Amor R, Nakhleh MK, Barash O, et al. Breath analysis of cancer in the present and the future[J]. Eur Respir Rev, 2019, 28(152): 190002. DOI: 10.1183/ 16000617.0002-2019.

[28] Kim C, Raja IS, Lee JM, et al. Recent trends in exhaled breath diagnosis using an artificial olfactory system[J]. Biosensors (Basel), 2021, 11(9): 337. DOI: 10.3390/bios11090337.

[29] Chung J, Akter S, Han S, et al. Diagnosis by volatile organic compounds in exhaled breath from patients with gastric and colorectal cancers[J]. Int J Mol Sci, 2022, 24(1): 129. DOI: 10.3390/ijms24010129.

[30] Douglas IS. New diagnostic methods for pneumonia in the ICU[J]. Curr Opin Infect Dis, 2016, 29(2): 197-204. DOI: 10.1097/QCO.0000000000000249.

[31] van Oort PM, de Bruin S, Weda H, et al. Exhaled breath metabolomics for the diagnosis of pneumonia in intubated and mechanically-ventilated intensive care unit (ICU)-patients[J]. Int J Mol Sci, 2017, 18(2): 449. DOI: 10.3390/ijms18020449.

[32] Mahairidou A, Rodopoulou S, Tomos I, et al. Exhaled breath condensate acidification occurs during surgery for abdominal cancer[J]. Anticancer Res, 2017, 37(6): 3315-3321. DOI: 10.21873/anticanres.11700.

[33] Pabst F, Miekisch W, Fuchs P, et al. Monitoring of oxidative and metabolic stress during cardiac surgery by means of breath biomarkers: an observational study[J]. J Cardiothorac Surg, 2007, 2: 37. DOI: 10.1186/1749-8090-2-37.

[34] Fernández Del Río R, O’Hara ME, Pemberton P, et al. Elimination characteristics of post-operative isoflurane levels in alveolar exhaled breath via PTR-MS analysis[J]. J Breath Res, 2016, 10(4): 046006. DOI: 10.1088/1752-7155/10/4/046006.

[35] Boshier PR, Mistry V, Cushnir JR, et al. Breath metabolite response to major upper gastrointestinal surgery[J]. J Surg Res, 2015, 193(2): 704-712. DOI: 10.1016/j.jss.2014.09.004.

[36] Bruderer T, Gaisl T, Gaugg MT, et al. On-line analysis of exhaled breath focus review[J]. Chem Rev, 2019, 119(19): 10803-10828. DOI: 10.1021/acs.chemrev.9b00005.

[37] 于晓飞, 王醊恩, 董正平, 等. 《黄帝内经》中“汗”的内涵简析[J]. 中国中医基础医学杂志, 2017, 23(9): 1190-1193. [Yu XF, Wang ZE, Dong ZP, et al. Connotation of sweating in the Inner Canon of Huang-di[J]. Journal of Basic Chinese Medicine, 2017, 23(9): 1190-1193.] DOI: 10.19945/j.cnki.issn.1006-3250.2017.09.003.

[38] 罗涛, 周创, 周继刚, 等. 狐臭外用古方用药分析 [J]. 中医学报, 2015, 30(3): 460-462. [Luo T, Zhou C, Zhou JG, et al. Medication analysis of external ancient prescriptions for the treatment of body odor[J]. Acta Chinese Medicine, 2015, 30(3): 460-462.] DOI: 10.16368/j.issn.1674-8999.2015.03.157.

[39] Monedeiro F, Dos Reis RB, Peria FM, et al. Investigation of sweat VOC profiles in assessment of cancer biomarkers using HS-GC-MS[J]. J Breath Res, 2020, 14(2): 026009. DOI: 10.1088/1752-7163/ab5b3c.

[40] Leemans M, Cuzuel V, Bauër P, et al. Screening of breast cancer from sweat samples analyzed by 2-dimensional gas chromatography-mass spectrometry: a preliminary study[J]. Cancers (Basel), 2023, 15(11): 2939. DOI: 10.3390/cancers15112939.

[41] Maa EH, Arnold J, Bush CK. Epilepsy and the smell of fear[J]. Epilepsy Behav, 2021, 121 (Pt A): 108078. DOI: 10.1016/j.yebeh.2021.108078.

[42] Zamkah A, Hui T, Andrews S, et al. Identification of suitable biomarkers for stress and emotion detection for future personal affective wearable sensors[J]. Biosensors (Basel), 2020, 10(4): 40. DOI: 10.3390/bios10040040.

[43] Choi MJ, Oh CH. 2nd dimensional GC-MS analysis of sweat volatile organic compounds prepared by solid phase micro-extraction[J]. Technol Health Care, 2014, 22(3): 481-488. DOI: 10.3233/THC-140807.

[44] 李文文. 中医症状性质特征的研究[D]. 济南:山东中医药大学, 2014. [Li WW. A research on the symptom attributes of Chinese medicine[D]. Jinan: Shandong University of Traditional Chinese Medicine, 2014.] https://cdmd.cnki.com.cn/article/cdmd-10441-1015506789.htm

[45] Peltrini R, Cordell RL, Ibrahim W, et al. Volatile organic compounds in a headspace sampling system and asthmatics sputum samples[J]. J Breath Res, 2021, 15(2): 027102. DOI: 10.1088/1752-7163/abcd2a.

[46] Phillips M, Cataneo RN, Condos R, et al. Volatile biomarkers of pulmonary tuberculosis in the breath[J]. Tuberculosis (Edinb), 2007, 87(1): 44-52. DOI: 10.1016/j.tube.2006.03.004.

[47] Suarez-Cuartin G, Giner J, Merino JL, et al. Identification of Pseudomonas aeruginosa and airway bacterial colonization by an electronic nose in bronchiectasis[J]. Respir Med, 2018, 136: 111-117. DOI: 10.1016/j.rmed.2018.02.008.

[48] Thompson R, Stephenson D, Sykes HE, et al. Detection of β-alanyl aminopeptidase as a biomarker for Pseudomonas aeruginosa in the sputum of patients with cystic fibrosis using exogenous volatile organic compound evolution[J]. RSC Adv, 2020, 10(18): 10634-10645. DOI: 10.1039/C9RA08386C.

[49] Nizio KD, Perrault KA, Troobnikoff AN, et al. In vitro volatile organic compound profiling using GC×GC-TOFMS to differentiate bacteria associated with lung infections: a proof-of-concept study[J]. J Breath Res, 2016, 10(2): 026008. DOI: 10.1088/1752-7155/10/2/026008.

[50] 吴邦华, 童映芳, 叶能权. GC/MS法检测呕吐物中灭多威[J]. 中国职业医学, 2001, 28(2): 48. [Wu BH, Tong YF, Ye NQ. Detection of methomyl in vomitus by GC/MS[J]. China Occupational Medicine, 2001, 28(2): 48.] DOI: 10.3969/j.issn.1000-6486.2001.02.029.

[51] 覃华开, 莫岳, 何伟仪, 等. GC-MS法快速检验食材及呕吐物中的氟乙酸钠[J]. 刑事技术, 2022, 47(2): 167-171. [Qin HK, Mo Y, He WY, et al. GC-MS rapidly determining sodium fluoroacetate in samples of food poisoning[J]. Forensic Science and Technology, 2022, 47(2): 167-171.] DOI: 10.16467/j.1008-3650.2021.0139.

[52] Course C, Watkins WJ, Müller CT, et al. Volatile organic compounds as disease predictors in newborn infants: a systematic review[J]. J Breath Res, 2021, 15(2): 024002. DOI: 10.1088/1752-7163/abe283.

[53] Navaneethan U, Parsi MA, Lourdusamy D, et al. Volatile organic compounds in urine for noninvasive diagnosis of malignant biliary strictures: a pilot study[J]. Dig Dis Sci, 2015, 60(7): 2150-2157. DOI: 10.1007/s10620-015-3596-x.

[54] Probert C, Greenwood R, Mayor A, et al. Faecal volatile organic compounds in preterm babies at risk of necrotising enterocolitis: the DOVE study[J]. Arch Dis Child Fetal Neonatal Ed, 2020, 105(5): 474-479. DOI: 10.1136/archdischild-2019-318221.

[55] Zygulska AL, Pierzchalski P. Novel diagnostic biomarkers in colorectal cancer[J]. Int J Mol Sci, 2022, 23(2): 852. DOI: 10.3390/ijms23020852.

[56] Vernia F, Valvano M, Fabiani S, et al. Are volatile organic compounds accurate markers in the assessment of colorectal cancer and inflammatory bowel diseases? A review[J]. Cancers (Basel), 2021, 13(10): 2361. DOI: 10.3390/cancers13102361.

[57] Chan DK, Leggett CL, Wang KK. Diagnosing gastrointestinal illnesses using fecal headspace volatile organic compounds[J]. World J Gastroentero, 2016, 22(4): 1639-1649. DOI: 10.3748/wjg.v22.i4.1639.

[58] Karamanou M, Androutsos G. Antoine-Laurent de Lavoisier (1743-1794) and the birth of respiratory physiology[J]. Thorax, 2013, 68(10): 978-979. DOI: 10.1136/thoraxjnl2013-203840.

[59] Langford VS, Graves I, McEwan MJ. Rapid monitoring of volatile organic compounds: a comparison between gas chromatography/mass spectrometry and selected ion flow tube mass spectrometry[J]. Rapid Commun Mass Spectrom, 2014, 28(1): 10-18. DOI: 10.1002/rcm.6747.

[60] Xiang L, Wu S, Hua Q, et al. Volatile organic compounds in human exhaled breath to diagnose gastrointestinal cancer: a meta-analysis[J]. Front Oncol, 2021, 11: 606915. DOI: 10.3389/fonc.2021.606915.

[61] El Manouni El Hassani S, Soers RJ, Berkhout DJC, et al. Optimized sample preparation for fecal volatile organic compound analysis by gas chromatography-mass spectrometry[J]. Metabolomics, 2020, 16(10): 112. DOI: 10.1007/s11306-020-01735-6.

[62] Seong SH, Kim HS, Lee YM, et al. Exploration of potential breath biomarkers of chronic kidney disease through thermal desorption gas chromatography mass spectrometry[J]. Metabolites, 2023, 13(7): 837. DOI: 10.3390/metabo13070837.

[63] Westphal K, Dudzik D, Waszczuk-Jankowska M, et al. Common strategies and factors affecting off-line breath sampling and volatile organic compounds analysis using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS)[J]. Metabolites, 2022, 13(1): 8. DOI: 10.3390/metabo13010008.

[64] Gherghel S, Morgan RM, Arrebola-Liébanas J, et al. Development of a HS-SPME/GC–MS method for the analysis of volatile organic compounds from fabrics for forensic reconstruction applications[J]. Forensic Sci Int, 2018, 290: 207-218. DOI: 10.1016/j.forsciint.2018.07.015.

[65] Poli D, Goldoni M, Corradi M, et al. Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2010, 878(27): 2643-2651. DOI: 10.1016/j.jchromb.2010.01.022.

[66] Pang X, Nan H, Zhong J, et al. Low-cost photoionization sensors as detectors in GC×GC systems designed for ambient VOC measurements[J]. Sci Total Environ, 2019, 664: 771-779. DOI: 10.1016/j.scitotenv.2019.01.348.

[67] Lourenço C, Bergin S, Hodgkinson J, et al. Instrumentation for quantitative analysis of volatile compounds emission at elevated temperatures. Part 1: Design and implementation[J]. Sci Rep, 2020, 10(1): 8700. DOI: 10.1038/s41598-020-65472-5.

[68] Manginell RP, Mowry CD, Pimentel AS, et al. Development of a mesoscale pulsed discharge helium ionization detector for portable gas chromatography[J]. Anal Sci, 2015, 31(11): 1183-1188. DOI: 10.2116/analsci.31.1183.

[69] Stierlin É, Michel T, Fernandez X. Field analyses of lavender volatile organic compounds: performance evaluation of a portable gas chromatography-mass spectrometry device[J]. Phytochem Anal, 2020, 31(6): 778-785. DOI: 10.1002/pca.2942.

[70] Xue C, Xu X, Liu Z, et al. Intelligent COVID-19 screening platform based on breath analysis[J]. J Breath Res, 2022, 17(1): 016005. DOI: 10.1088/1752-7163/aca119.

[71] Lam R, Lennard C, Kingsland G, et al. Rapid on-site identification of hazardous organic compounds at fire scenes using person-portable gas chromatography-mass spectrometry (GC-MS)-part 2: water sampling and analysis[J]. Forensic Sci Res, 2019, 5(2): 150-164. DOI: 10.1080/20961790.2019.1662648.

[72] Aksenov AA, Zamuruyev KO, Pasamontes A, et al. Analytical methodologies for broad metabolite coverage of exhaled breath condensate[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2017, 1061-1062: 17-25. DOI: 10.1016/j.jchromb.2017.06.038.

[73] Sani SN, Zhou W, Ismail BB, et al. LC-MS/MS based volatile organic compound biomarkers analysis for early detection of lung cancer[J]. Cancers (Basel), 2023, 15(4): 1186. DOI: 10.3390/cancers15041186.

[74] Hernández-Borges J, Rodríguez-Delgado MÁ, García-Montelongo FJ, et al. Highly sensitive analysis of multiple pesticides in foods combining solid-phase microextraction, capillary electrophoresis-mass spectrometry, and chemometrics[J]. Electrophoresis, 2004, 25(13): 2065-2076. DOI: 10.1002/elps.200405938.

[75] Kałużna-Czaplińska J. Current medical research with the application of coupled techniques with mass spectrometry[J]. Med Sci Monit, 2011, 17(5): RA117-RA123. DOI: 10.12659/msm.881756.

[76] Jiang Y, Huang D, Zhang H, et al. Smart miniature mass spectrometer enabled by machine learning[J]. Anal Chem, 2023, 95(14): 5976-5984. DOI: 10.1021/acs.analchem.2c05714.

[77] Lindinger W, Hansel A, Jordan A. On-line monitoring of volatile organic compounds at pptv levels by means of proton-transfer-reaction mass spectrometry (PTR-MS) medical applications, food control and environmental research[J]. Int J Mass Spectrom, 1998, 173(3): 191-241. DOI: 10.1016/S0168-1176(97)00281-4.

[78] Jung YJ, Seo HS, Kim JH, et al. Advanced diagnostic technology of volatile organic compounds real time analysis analysis from exhaled breath of gastric cancer patients using proton-transfer-reaction time-of-flight mass spectrometry[J]. Front Oncol, 2021, 11: 560591. DOI: 10.3389/fonc.2021.560591.

[79] Roquencourt C, Salvator H, Bardin E, et al. Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19[J]. ERJ Open Res, 2023, 9(5): 00206-2023. DOI: 10.1183/23120541.00206-2023.

[80] Zou X, Wang H, Ge D, et al. On-line monitoring human breath acetone during exercise and diet by proton transfer reaction mass spectrometry[J]. Bioanalysis, 2019, 11(1): 33-40. DOI: 10.4155/bio-2018-0258.

[81] Jordan A, Haidacher S, Hanel G, et al. An online ultra-high sensitivity proton-transfer-reaction mass-spectrometer combined with switchable reagent ion capability (PTR+SRI-MS)[J]. Int J Mass Spectrom, 2009, 286(1): 32-38. DOI: 10.1016/j.ijms.2009.06.006.

[82] Sulzer P, Edtbauer A, Hartungen E, et al. From conventional proton-transfer-reaction mass spectrometry (PTR-MS) to universal trace gas analysis[J]. Int J Mass Spectrom, 2012, 321: 66-70. DOI: 10.1016/j.ijms.2012.05.003.

[83] Kari E, Miettinen P, Yli-Pirilä P, et al. PTR-ToF-MS product ion distributions and humidity-dependence of biogenic volatile organic compounds[J]. Int J Mass Spectrom, 2018, 430: 87-97. DOI: 10.1016/j.ijms.2018.05.003.

[84] Mochalski P, King J, Mayhew CA, et al. A review on isoprene in human breath[J]. J Breath Res, 2023, 17(3): 037101. DOI: 10.1088/1752-7163/acc964.

[85] Pham YL, Holz O, Beauchamp J. Emissions and uptake of volatiles by sampling components in breath analysis[J]. J Breath Res, 2023, 17(3): 037102. DOI: 10.1088/1752-7163/acce34.

[86] Yuan B, Koss AR, Warneke C, et al. Proton-transfer-reaction mass spectrometry: applications in atmospheric sciences[J]. Chem Rev, 2017, 117(21): 13187-13229. DOI: 10.1021/acs.chemrev.7b00325.

[87] Roslund K, Uosukainen M, Järvik K, et al. Antibiotic treatment and supplemental hemin availability affect the volatile organic compounds produced by P. gingivalis in vitro[J]. Sci Rep, 2022, 12(1): 22534. DOI: 10.1038/s41598-022-26497-0.

[88] Liangou A, Tasoglou A, Huber HJ, et al. A method for the identification of COVID-19 biomarkers in human breath using proton transfer reaction time-of-flight mass spectrometry[J]. EClinicalMedicine, 2021, 42: 101207. DOI: 10.1016/j.eclinm.2021.101207.

[89] Acierno V, Fasciani G, Kiani S, et al. PTR-QiToF-MS and HSI for the characterization of fermented cocoa beans from different origins[J]. Food Chem, 2019, 289: 591-602. DOI: 10.1016/j.foodchem.2019.03.095.

[90] Ekpa O, Fogliano V, Linnemann A. Identification of the volatile profiles of 22 traditional and newly bred maize varieties and their porridges by PTR-QiTOF-MS and HS-SPME GC-MS[J]. J Sci Food Agric, 2021, 101(4): 1618-1628. DOI: 10.1002/jsfa.10781.

[91] Acierno V, Liu N, Alewijn M, et al. Which cocoa bean traits persist when eating chocolate? Real-time nosespace analysis by PTR-QiToF-MS[J]. Talanta, 2019, 195: 676-682. DOI: 10.1016/j.talanta.2018.11.100.

[92] Adams NG, Smith D. The selected ion flow tube (SIFT); a technique for studying ion-neutral reactions[J]. Int J Mass Spectrom Ion Phys, 1976, 21(3-4): 349-359. DOI: 10.1016/0020-7381(76)80133-7.

[93] Smith D, Španěl P, Demarais N, et al. Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS)[J]. Mass Spectrom Rev, 2023: e21835. DOI: 10.1002/mas.21835.

[94] Nakayama Y, Hanada M, Koda H, et al. Breast cancer detection using volatile compound profiles in exhaled breath via selected ion-flow tube mass spectrometry[J]. J Breath Res, 2022, 17(1): 016006. DOI: 10.1088/1752-7163/aca696.

[95] Segers K, Slosse A, Viaene J, et al. Feasibility study on exhaled-breath analysis by untargeted selected-ion flow-tube mass spectrometry in children with cystic fibrosis, asthma, and healthy controls: comparison of data pretreatment and classification techniques[J]. Talanta, 2021, 225: 122080. DOI: 10.1016/j.talanta.2021.122080.

[96] Tang WHW, Tranchito L, Albert C, et al. Exhaled breath analysis using selected ion flow tube mass spectrometry and disease severity in heart failure[J]. Metabolites, 2023, 13(10): 1049. DOI: 10.3390/metabo13101049.

[97] Spanĕl P, Smith D. On-line measurement of the absolute humidity of air, breath and liquid headspace samples by selected ion flow tube mass spectrometry[J]. Rapid Commun Mass Spectrom, 2001, 15(8): 563-569. DOI: 10.1002/rcm.265.

[98] Smith D, Španěl P. Status of selected ion flow tube MS: accomplishments and challenges in breath analysis and other areas[J]. Bioanalysis, 2016, 8(11): 1183-1201. DOI: 10.4155/bio-2016-0038.

[99] Spesyvyi A, Smith D, Španěl P. Selected ion flow-drift tube mass spectrometry: quantification of volatile compounds in air and breath[J]. Anal Chem, 2015, 87(24): 12151-12160. DOI: 10.1021/acs.analchem.5b02994.

[100] Allpress C, Crittenden D, Ma J, et al. Real-time differentiation of ethylbenzene and the xylenes using selected ion flow tube mass spectrometry[J]. Rapid Commun Mass Spectrom, 2019, 33(23): 1844-1849. DOI: 10.1002/rcm.8550.

[101] Lin GP, Vadhwana B, Belluomo I, et al. Cross platform analysis of volatile organic compounds using selected ion flow tube and proton-transfer-reaction mass spectrometry[J]. J Am Soc Mass Spectrom, 2021, 32(5): 1215-1223. DOI: 10.1021/jasms.1c00027.

[102] Rioseras AT, Gaugg MT, Sinues PML. Secondary electrospray ionization proceeds via gas-phase chemical ionization[J]. Anal Methods, 2017, 9(34): 5052-5057. DOI: 10.1039/c7ay01121k.

[103] Casas-Ferreira AM, Nogal-Sánchez MD, Pérez-Pavón JL, et al. Non-separative mass spectrometry methods for non-invasive medical diagnostics based on volatile organic compounds: a review[J]. Anal Chim Acta, 2019, 1045: 10-22. DOI: 10.1016/j.aca.2018.07.005.

[104] Li X, Huang DD, Du R, et al. Real-time breath analysis by using secondary nanoelectrospray ionization coupled to high resolution mass spectrometry[J]. J Vis Exp, 2018,  2018(133): e56465. DOI: 10.3791/56465.

[105] Gaugg MT. On-line breath metabolomics in respiratory diseases using secondary electrospray ionization-mass spectrometry[J]. Chimia (Aarau), 2018, 72(4): 184-188. DOI: 10.2533/chimia.2018.184.

[106] Nowak N, Engler A, Thiel S, et al. Validation of breath biomarkers for obstructive sleep apnea[J]. Sleep Med, 2021, 85: 75-86. DOI: 10.1016/j.sleep.2021.06.040.

[107] Weber R, Streckenbach B, Welti L, et al. Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma[J]. Front Mol Biosci, 2023, 10: 1154536. DOI: 10.3389/fmolb.2023.1154536.

[108] Gómez-Mejia A, Arnold K, Bär J, et al. Rapid detection of staphylococcus aureus and streptococcus pneumoniae by real-time analysis of volatile metabolites[J]. iScience, 2022, 25(10): 105080. DOI: 10.1016/j.isci.2022.105080.

[109] Weber R, Haas N, Baghdasaryan A, et al. Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS[J]. ERJ Open Res, 2020, 6(1): 00171-2019. DOI: 10.1183/23120541.00171-2019.

[110] Gisler A, Lan J, Singh KD, et al. Real-time breath analysis of exhaled compounds upon peppermint oil ingestion by secondary electrospray ionization-high resolution mass spectrometry: technical aspects[J]. J Breath Res, 2020, 14(4): 046001. DOI: 10.1088/1752-7163/ab9f8b.

[111] Wang R, Gröhn AJ, Zhu L, et al. On the mechanism of extractive electrospray ionization (EESI) in the dual-spray configuration[J]. Anal Bioanal Chem, 2012, 402(8): 2633-2643. DOI: 10.1007/s00216-011-5471-8.

[112] Ke M, Zhang H, Ding J, et al. Generating supercharged protein ions for breath analysis by extractive electrospray ionization mass spectrometry[J]. Anal Chem, 2019, 91(5): 3215-3220. DOI: 10.1021/acs.analchem.8b03114.

[113] Zuo W, Bai W, Gan X, et al. Detection of lung cancer by analysis of exhaled gas utilizing extractive electrospray ionization-mass spectroscopy[J]. J Biomed Nanotechnol, 2019, 15(4): 633-646. DOI: 10.1166/jbn.2019.2719.

[114] Zeng Q, Li P, Cai Y, et al. Detection of creatinine in exhaled breath of humans with chronic kidney disease by extractive electrospray ionization mass spectrometry[J]. J Breath Res, 2016, 10(1): 016008. DOI: 10.1088/1752-7155/10/1/016008.

[115] Chan GC, Shelley JT, Wiley JS, et al. Elucidation of reaction mechanisms responsible for afterglow and reagent-ion formation in the low-temperature plasma probe ambient ionization source[J]. Anal Chem, 2011, 83(10): 3675-3686. DOI: 10.1021/ac103224x.

[116] Olenici-Craciunescu SB, Michels A, Meyer C, et al. Characterization of a capillary dielectric barrier plasma jet for use as a soft ionization source by optical emission and ion mobility spectrometry[J]. Spectrochimica Acta Part B: Atomic Spectrocopy, 2009, 64(11-12): 1253-1258. DOI: 10.1016/j.sab.2009.10.001.

[117] Smoluch M, Mielczarek P, Silberring J. Plasma-based ambient ionization mass spectrometry in bioanalytical sciences[J]. Mass Spectrom Rev, 2016, 35(1): 22-34. DOI: 10.1002/mas.21460.

[118] Geng X, Zhang K, Li H, et al. Online mass spectrometry of exhaled breath with a modified ambient ion source[J]. Talanta, 2023, 255: 124254. DOI: 10.1016/j.talanta.2023.124254.

[119] Xu L, Zhang K, Geng X, et al. High-resolution mass spectrometry exhalome profiling with a modified direct analysis in real time ion source[J]. Rapid Commun Mass Spectrom, 2022, 36(24): e9406. DOI: 10.1002/rcm.9406.

[120] Li Y. Applications of a confined DART (direct analysis in real time) ion source for online in vivo analysis of human breath[J]. Anal Methods, 2013, 5(24): 6933-6940. DOI: 10.1039/c3ay41406j.

[121] Fandino J, Orejas J, Chauvet L, et al. Evaluation of a modified halo flowing atmospheric pressure afterglow ion source for the analysis of directly injected volatile organic compounds[J]. J Anal Atom Spectrom, 2020, 35(9): 2002-2010. DOI: 10.1039/d0ja00140f.

[122] Atutov SN, Galeyev AE, Plekhanov AI, et al. Universal sensor based on the spectroscopy of glow discharge for the detection of traces of atoms or molecules in air[J]. Rev Sci Instrum, 2018, 89(3): 033105. DOI: 10.1063/1.4989904.

[123] Zhang D, Latif M, Gamez G. Instantaneous differentiation of functional isomers via reactive flowing atmospheric pressure afterglow mass spectrometry[J]. Anal Chem, 2021, 93(29): 9986-9994. DOI: 10.1021/acs.analchem.0c04867.

[124] Gong X, Shi S, Zhang D, et al. Quantitative analysis of exhaled breath collected on filter substrates via low-temperature plasma desorption/ionization mass spectrometry[J]. J Am Soc Mass Spectrom, 2022, 33(8): 1518-1529. DOI: 10.1021/jasms.2c00109.

[125] Yang T, Gao DX, Yu YL, et al. Dielectric barrier discharge micro-plasma emission spectrometry for the detection of acetone in exhaled breath[J]. Talanta, 2016, 146: 603-608. DOI: 10.1016/j.talanta.2015.07.074.

[126] Gong X, Shi S, Gamez G. Real-time quantitative analysis of valproic acid in exhaled breath by low temperature plasma ionization mass spectrometry[J]. J Am Soc Mass Spectrom, 2017, 28(4): 678-687. DOI: 10.1007/s13361-016-1533-7.

[127] Liu Y, Li Q, Su G, et al. Photochemical conversion of toluene in simulated atmospheric matrix and characterization of large molecular weight products by  +APPI FT-ICR MS[J]. Sci Total Environ, 2019, 649: 111-119. DOI: 10.1016/j.scitotenv.2018.08.293.

[128] Kauppila TJ, Syage JA, Benter T. Recent developments in atmospheric pressure photoionization-mass spectrometry[J]. Mass Spectrom Rev, 2017, 36(3): 423-449. DOI: 10.1002/mas.21477.

[129] Appel MF, Short LC, Benter T. Development of medium pressure laser ionization, MPLI. Description of the MPLI ion source[J]. J Am Soc Mass Spectrom, 2004, 15(12): 1885-1896. DOI: 10.1016/j.jasms.2004.09.010.

[130] Chen C, Jiang D, Li H. UV photoionization ion mobility spectrometry: fundamentals and applications[J]. Anal Chim Acta, 2019, 1077: 1-13. DOI: 10.1016/j.aca.2019.05.018.

[131] Henderson B, Khodabakhsh A, Metsälä M, et al. Laser spectroscopy for breath analysis: towards clinical implementation[J]. Appl Phys B, 2018, 124(8): 161. DOI: 10.1007/s00340-018-7030-x.

[132] Seichter F, Tütüncü E, Hagemann LT, et al. Online monitoring of carbon dioxide and oxygen in exhaled mouse breath via substrate-integrated hollow waveguide Fourier-transform infrared-luminescence spectroscopy[J]. J Breath Res, 2018, 12(3): 036018. DOI: 10.1088/1752-7163/aabf98.

[133] Shlomo IB, Frankenthal H, Laor A, et al. Detection of SARS-CoV-2 infection by exhaled breath spectral analysis: introducing a ready-to-use point-of-care mass screening method[J]. EClinicalMedicine, 2022, 45: 101308. DOI: 10.1016/j.eclinm.2022.101308.

[134] Glöckler J, Mizaikoff B, Díaz de León-Martínez L. SARS CoV-2 infection screening via the exhaled breath fingerprint obtained by FTIR spectroscopic gas-phase analysis. a proof of concept[J]. Spectrochim Acta A Mol Biomol Spectrosc, 2023, 302: 123066. DOI: 10.1016/j.saa.2023.123066.

[135] Kalidoss R, Umapathy S, Anandan R, et al. Comparative study on the preparation and gas sensing properties of reduced graphene oxide/SnO2 binary nanocomposite for detection of acetone in exhaled breath[J]. Anal Chem, 2019, 91(8): 5116-5124. DOI: 10.1021/acs.analchem.8b05670.

[136] Seichter F, Vogt JA, Wachter U, et al. Strategies for 13C enrichment calculation in Fourier-transform infrared CO2 spectra containing spectral overlapping and nonlinear abundance-amount relations utilizing response surface fits[J]. Anal Chim Acta, 2020, 1095: 48-60. DOI: 10.1016/j.aca.2019.10.038.

[137] Hagemann LT, Repp S, Mizaikoff B. Hybrid analytical platform based on field-asymmetric ion mobility spectrometry, infrared sensing, and luminescence-based oxygen sensing for exhaled breath analysis[J]. Sensors(Basel), 2019, 19(12): 2653. DOI: 10.3390/s19122653.

[138] Roller C, Namjou K, Jeffers JD, et al. Nitric oxide breath testing by tunable-diode laser absorption spectroscopy: application in monitoring respiratory inflammation[J]. Appl Opt, 2002, 41(28): 6018-6029. DOI: 10.1364/ao.41.006018.

[139] Ghorbani R, Blomberg A, Schmidt FM. Impact of breath sampling on exhaled carbon monoxide[J]. J Breath Res, 2020, 14(4): 047105. DOI: 10.1088/1752-7163/abb479.

[140] Maithani S, Mandal S, Maity A, et al. High-resolution spectral analysis of ammonia near 6.2 μm using a cw EC-QCL coupled with cavity ring-down spectroscopy[J]. Analyst, 2018, 143(9): 2109-2114. DOI: 10.1039/c7an02008b.

[141] Larracy R, Phinyomark A, Scheme E. Infrared cavity ring-down spectroscopy for detecting non-small cell lung cancer in exhaled breath[J]. J Breath Res, 2022, 16(2): 026008. DOI: 10.1088/1752-7163/ac5e4f.

[142] Wang H, Wei X, Wu Y, et al. A combined screening study for evaluating the potential of exhaled acetone, isoprene, and nitric oxide as biomarkers of lung cancer[J]. RSC Adv, 2023, 13(45): 31835-31843. DOI: 10.1039/d3ra04522f.

[143] 刘静莎, 张健鹏. 细菌性肺炎患者呼出气与细菌培养顶空气体光声光谱的对比分析[J]. 当代医药论丛, 2023, 21(10): 12-16. [Liu JS, Zhang JP. Comparative analysis of photoacoustic spectra of exhaled air in patients with bacterial pneumonia and cultured aerosols[J]. Contemporary Medicine Forum, 2023, 21(10): 12-16.] DOI: 10.3969/j.issn.2095-7629.2023.10.004.

[144] Kibion. Kibion Dynamic [EB/OL]. (2017-06-14) [2024-01-05]. https://kibion.com/product-range/kibion-dynamic/.

[145] Bedfont Scientific Ltd. GastroCH4ECK [EB/OL]. (2019-07-26) [2024-01-05]. https://www.gastrolyzer.com/gastroch4eck/.

[146] Jiang C, Sun M, Wang Z, et al. A portable real-time ringdown breath acetone analyzer: toward potential diabetic screening and management[J]. Sensors (Basel), 2016, 16(8): 1199. DOI: 10.3390/s16081199.

[147] Chen H, Huo D, Zhang J. Gas recognition in E-nose system: a review[J]. IEEE Trans Biomed Circuits Syst, 2022, 16(2): 169-184. DOI: 10.1109/TBCAS.2022.3166530.

[148] Savito L, Scarlata S, Bikov A, et al. Exhaled volatile organic compounds for diagnosis and monitoring of asthma[J]. World J Clin Cases, 2023, 11(21): 4996-5013. DOI: 10.12998/wjcc.v11.i21.4996.

[149] Dospinescu VM, Tiele A, Covington JA. Sniffing out urinary tract infection-diagnosis based on volatile organic compounds and smell profile[J]. Biosensors (Basel), 2020, 10(8): 83. DOI: 10.3390/bios10080083.

[150] Lai SY, Deffenderfer OF, Hanson W, et al. Identification of upper respiratory bacterial pathogens with the electronic nose[J]. Laryngoscope, 2002, 112(6): 975-979. DOI: 10.1097/00005537-200206000-00007.

[151] Pavlou AK, Magan N, Sharp D, et al. An intelligent rapid odour recognition model in discrimination of Helicobacter pylori and other gastroesophageal isolates in vitro[J]. Biosens Bioelectron, 2000, 15(7-8): 333-342. DOI: 10.1016/S0956-5663(99)00035-4.

[152] Rocco G, Pennazza G, Santonico M, et al. Breathprinting and early diagnosis of lung cancer[J]. J Thorac Oncol, 2018, 13(7): 883-894. DOI: 10.1016/j.jtho.2018.02.026.

[153] Dalis C, Mesfin FM, Manohar K, et al. Volatile organic compound assessment as a screening tool for early detection of gastrointestinal diseases[J]. Microorganisms, 2023, 11(7): 1822. DOI: 10.3390/microorganisms11071822.

[154] Zhang T, Tan R, Shen W, et al. Inkjet-printed ZnO-based MEMS sensor array combined with feature selection algorithm for VOCs gas analysis[J]. Sens Actuators B Chem, 2023, 382: 133555. DOI: 10.1016/j.snb.2023.133555.

[155] Gupta A, Singh TS, Yadava RDS. MEMS sensor array-based electronic nose for breath analysis-a simulation study[J]. J Breath Res, 2018, 13(1): 016003. DOI: 10.1088/1752-7163/aad5f1.

[156] Poli D, Carbognani P, Corradi M, et al. Exhaled volatile organic compounds in patients with non-small cell lung cancer: cross sectional and nested short-term follow-up study[J]. Respir Res, 2005, 6(1): 71. DOI: 10.1186/1465-9921-6-71.

[157] Machado RF, Laskowski D, Deffenderfer O, et al. Detection of lung cancer by sensor array analyses of exhaled breath[J]. Am J Resp Crit Care Med, 2005, 171(11): 1286-1291. DOI: 10.1164/rccm.200409-1184OC.

[158] Mazzone PJ, Wang XF, Xu Y, et al. Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer[J]. J Thorac Oncol, 2012, 7(1): 137-142. DOI: 10.1097/JTO.0b013e318233d80f.

[159] Coronel Teixeira R, Rodríguez M, Jiménez de Romero N, et al. The potential of a portable, point-of-care electronic nose to diagnose tuberculosis[J]. J Infect, 2017, 75(5): 441-447. DOI: 10.1016/j.jinf.2017.08.003.

[160] Felton TW, Ahmed W, White IR, et al. Analysis of exhaled breath to identify critically ill patients with ventilator-associated pneumonia[J]. Anaesthesia, 2023, 78(6): 712-721. DOI: 10.1111/anae.15999.

[161] Suarez-Cuartin G, Giner J, Merino JL, et al. Identification of Pseudomonas aeruginosa and airway bacterial colonization by an electronic nose in bronchiectasis[J]. Respir Med, 2018, 136: 111-117. DOI: 10.1016/j.rmed.2018.02.008.

[162] van de Kant KD, van Berkel JJ, Jöbsis Q, et al. Exhaled breath profiling in diagnosing wheezy preschool children[J]. Eur Respir J, 2013, 41(1): 183-188. DOI: 10.1183/09031936.00122411.

[163] Zhang P, Ren T, Chen H, et al. A feasibility study of Covid-19 detection using breath analysis by high-pressure photon ionization time-of-flight mass spectrometry[J]. J Breath Res, 2022, 16(4): 046009. DOI: 10.1088/1752-7163/ac8ea1.

[164] Dragonieri S, van der Schee MP, Massaro T, et al. An electronic nose distinguishes exhaled breath of patients with malignant pleural mesothelioma from controls[J]. Lung cancer, 2012, 75(3): 326-331. DOI: 10.1016/j.lungcan.2011.08.009.

[165] Biller H, Holz O, Windt H, et al. Breath profiles by electronic nose correlate with systemic markers but not ozone response[J]. Respir Med, 2011, 105(9): 1352-1363. DOI: 10.1016/j.rmed.2011.03.002.

[166] Kumar S, Huang J, Abbassi-Ghadi N, et al. Mass spectrometric analysis of exhaled breath for the identification of volatile organic compound biomarkers in esophageal and gastric adenocarcinoma[J]. Ann Surg, 2015, 262(6): 981-990. DOI: 10.1097/SLA.0000000000001101.

[167] Dadamio J, Van den Velde S, Laleman W, et al. Breath biomarkers of liver cirrhosis[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2012, 905: 17-22. DOI: 10.1016/j.jchromb.2012.07.025.

[168] Peters AL, Gerritsen MG, Brinkman P, et al. Volatile organic compounds in exhaled breath are independent of systemic inflammatory syndrome caused by intravenous lipopolysaccharide infusion in humans: results from an experiment in healthy volunteers[J]. J Breath Res, 2017, 11(2): 026003. DOI: 10.1088/1752-7163/aa6545.

[169] van de Velde ME, El Hassani SEM, Kaspers GJL, et al. Prediction of bloodstream infection in pediatric acute leukemia by microbiota and volatile organic compounds analysis[J]. J Pediatr Hematol Oncol, 2022, 44(1): e152-e159. DOI: 10.1097/MPH.0000000000002210.

[170] Berna AZ, McCarthy JS, Wang XR, et al. Diurnal variation in expired breath volatiles in malaria-infected and healthy volunteers[J]. J Breath Res, 2018, 12(4): 046014. DOI: 10.1088/1752-7163/aadbbb.

[171] Broza YY, Har-Shai L, Jeries R, et al. Exhaled breath markers for nonimaging and noninvasive measures for detection of multiple sclerosis[J]. ACS Chem Neurosci, 2017, 8(11): 2402-2413. DOI: 10.1021/acschemneuro.7b00181.

[172] Nakhleh MK, Badarny S, Winer R, et al. Distinguishing idiopathic Parkinson's disease from other parkinsonian syndromes by breath test[J]. Parkinsonism Relat Disord, 2015, 21(2): 150-153. DOI: 10.1016/j.parkreldis. 2014.11.023.

[173] Mochalski P, King J, Haas M, et al. Blood and breath profiles of volatile organic compounds in patients with end-stage renal disease[J]. BMC Nephrol, 2014, 15: 43. DOI: 10.1186/1471-2369-15-43.

[174] Zou X, Zhou W, Shen C, et al. Online exhaled gas measurements for radiotherapy patients by proton transfer reaction mass spectrometry[J]. J Environ Radioact, 2016, 160: 135-140. DOI: 10.1016/j.jenvrad.2016.04.029.