Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

Exhaled-breath Testing for Prostate Cancer Based on Volatile Organic Compound Profiling Using an Electronic Nose Device (Aeonose™): A Preliminary Report

BACKGROUND

Prostate biopsy, an invasive examination, is the gold standard for diagnosing prostate cancer (PCa). There is a need for a novel noninvasive diagnostic tool that achieves a significantly high pretest probability for PCa, reducing unnecessary biopsy numbers. Recent studies have shown that volatile organic compounds (VOCs) in exhaled breath can be used to detect different types of cancers via training of an artificial neural network (ANN).

OBJECTIVE

To determine whether exhaled-breath analysis using a handheld electronic nose device can be used to discriminate between VOC patterns between PCa patients and healthy individuals.

DESIGN, SETTING, AND PARTICIPANTS

This prospective pilot study was conducted in the outpatient urology clinic of the Maastricht University Medical Center, the Netherlands. Patients with histologically proven PCa were already included before initial biopsy or during follow-up, with no prior treatment for their PCa. Urological patients with negative biopsies in the past year or patients with prostate enlargement (PE) with low or stable serum prostate-specific antigen were used as controls. Exhaled breath was probed from 85 patients: 32 with PCa and 53 controls (30 having negative biopsies and 23 PE).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient characteristics were statistically analyzed using independent sample t test and Pearson's chi-square test. Data analysis was performed by Aethena software after data compression using the TUCKER3 algorithm. ANN models were trained and evaluated using the leave-10%-out cross-validation method.

RESULTS AND LIMITATIONS

Our trained ANN showed an accuracy of 0.75, with an area under the curve of 0.79 with sensitivity and specificity of 0.84 (95% confidence interval [CI] 0.66-0.94) and 0.70 (95% CI 0.55-0.81) respectively, comparing PCa with control individuals. The negative predictive value was found to be 0.88. The main limitation is the relatively small sample size.

CONCLUSIONS

Our findings imply that the Aeonose allows us to discriminate between patients with untreated, histologically proven primary PCa and control patients based on exhaled-breath analysis.

PATIENT SUMMARY

We explored the possibility of exhaled-breath analysis using an electronic nose, to be used as a noninvasive tool in clinical practice, as a pretest for diagnosing prostate cancer. We found that the electronic nose was able to discriminate between prostate cancer patients and control individuals.

Sensor Array for Detection of Early Stage Parkinson's Disease before Medication

Early diagnosis of Parkinson's disease (PD) is important because it affects the choice of therapy and is subject to a relatively high degree of error. In addition, early detection of PD can potentially enable the start of neuroprotective therapy before extensive loss of dopaminergic neurons of the substantia nigra occurs. However, until now, studies for early detection of PD using volatile biomarkers sampled only treated and medicated patients. Therefore, there is a great need to evaluate untreated patients for establishing a real world screening and diagnostic technology. Here we describe for the first time a clinical trial to distinguish between de novo PD and control subjects using an electronic system for detection of volatile molecules in exhaled breath (sensor array). We further determine for the first time the association to other common tests for PD diagnostics as smell, ultrasound, and nonmotor symptoms. The test group consisted of 29 PD patients after initial diagnosis by an experienced neurologist, compared with 19 control subjects of similar age. The sensitivity, specificity, and accuracy values of the sensor array to detect PD from controls were 79%, 84%, and 81% respectively, in comparison with midbrain ultrasonography (93%, 90%, 92%) and smell detection (62%, 89%, 73%). The results confirm previous data showing the potential of sensor arrays to detect PD.

Identification of volatile metabolites in human saliva from patients with oral squamous cell carcinoma via zeolite-based thin-film microextraction coupled with GC-MS

In recent years, volatile organic compounds (VOCs) discharged from the human body, of which some compounds exhibit strong correlations with pathological conditions, have attracted attention as a new means of disease diagnosis technology. The aim of this study was to establish the salivary metabolomic profiles of oral squamous cell carcinoma (OSCC) patients and healthy volunteers (control group) and to investigate VOCs as potential biomarkers in the diagnosis of oral cancer. We have demonstrated a method combining thin-film microextraction based on a ZSM-5/polydimethylsiloxane hybrid film coupled with gas chromatography-mass spectrometry and carried out a comparative analysis of salivary VOC profiles between OSCC patients and healthy controls. The results depicted that 42 and 73 VOCs were detected and identified in samples from the healthy control group (n = 50) and oral cancer group (n = 24), respectively. Among them, twenty-seven VOCs (ten were decreased, seven disappeared, and ten were newly produced in the oral cancer group) depict significant differences between both the sample groups, and they have relevance as candidate biomarkers for OSCC. Twelve salivary VOCs that were characteristic of oral cancer patients were finally extracted and used for pattern recognition analyses for oral cancer diagnosis. The proposed TFME approach for analyzing human saliva on the basis of a ZSM-5-loaded PDMS hybrid thin film has been performed for the very first time in the field of dentistry.

Methodological considerations for large-scale breath analysis studies: lessons from the U-BIOPRED severe asthma project

Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies.

Microhotplates for Metal Oxide Semiconductor Gas Sensor Applications-Towards the CMOS-MEMS Monolithic Approach

The recent development of the Internet of Things (IoT) in healthcare and indoor air quality monitoring expands the market for miniaturized gas sensors. Metal oxide gas sensors based on microhotplates fabricated with micro-electro-mechanical system (MEMS) technology dominate the market due to their balance in performance and cost. Integrating sensors with signal conditioning circuits on a single chip can significantly reduce the noise and package size. However, the fabrication process of MEMS sensors must be compatible with the complementary metal oxide semiconductor (CMOS) circuits, which imposes restrictions on the materials and design. In this paper, the sensing mechanism, design and operation of these sensors are reviewed, with focuses on the approaches towards performance improvement and CMOS compatibility.

Ultrasensitive Detection of 2,4-Dinitrophenol Using Nanowire Biosensor

The method for the detection of 2,4-dinitrophenol (DNP) in solution is proposed. This method employs the sensors based on silicon nanowire field-effect transistors with protective layers of high-k dielectrics, whose surface is functionalized with an amino silane. Direct highly sensitive detection of DNP has been demonstrated, and the lowest detectable concentration of DNP was determined to be 10−14 M. Silicon-on-insulator nanowire (SOI-NW) sensors can well be employed for the rapid detection of a wide range of toxic and explosive compounds by selection of sensor surface modification techniques.

Orthogonal Ambipolar Semiconductors with Inherently Multi-Dimensional Responses for the Discriminative Sensing of Chemical Vapors

Numerous examples of field-effect transistor (FET) biosensors and chemical sensors with good sensitivity and selectivity have now been developed. However, effectively discriminating between analytes has required either the use of receptors that selectively bind specific analytes or the fabrication of an array of sensors with varying but nonspecific responses. Both approaches exhibit significant limitations. In the first case, it can be difficult to design sufficiently specific receptors for many compounds, whereas the number of receptors required scales with the number of analytes to be detected, making it impractical to recognize many different compounds. In the second case, existing approaches to FET sensor arrays are generally material-inefficient and provide modest sensitivity. Here, we demonstrate that orthogonal ambipolar semiconductors consisting of semiconducting p-type polymers and n-type small-molecule nanowires with perpendicular in-plane orientations provide a platform with high sensitivity and inherently multi-dimensional response. This allows for discrimination between even closely related derivatives such as aromatic isomers and n-alkyl alcohols varying in length by a single carbon atom resolution using only a single sensor element.

Materials and Wearable Devices for Autonomous Monitoring of Physiological Markers

Wearable devices are gaining considerable attention owing to the ease with which they can collect crucial information in real-time, both continuously and noninvasively, regarding a wearer's health. A concise summary is given of the three main elements that enable autonomous detection and monitoring of the likelihood or the existence of a health-risk state in continuous and real-time modes, with an emphasis on emerging materials and fabrication techniques in the relevant fields. The first element is the sensing technology used in the noninvasive detection of physiological markers relevant to the state of health. The second element is self-powered devices for longer periods of use by drawing energy from bodily movement and temperature. The third element is the self-healing properties of the materials used in the wearable devices to extended usage if they become scratched or cut. Promises and challenges of the separately reviewed parts and the combined parts are presented and discussed. Ideas regarding further improvement of skin-based wearable devices are also presented and discussed.

Inorganic-Organic Hybrid Tongue-Mimic for Time-Resolved Luminescent Noninvasive Pattern and Chiral Recognition of Thiols in Biofluids toward Healthcare Monitoring

In this work, manganese(II)-doped zinc/germanium oxide nanoparticles (Mn@ZGNPs) have been hydrothermally synthesized to equip with appealing time-resolved luminescence (TRL). Interestingly, we reveal that they can be readily quenched ("turn off") via a facile surface coating with bioinspired polydopamine (PDA) polymerized from dopamine (DA), resulting from PDA-triggered TRL resonance energy transfer (TRL-RET). By integrated with the thiol-induced inhibition of PDA formation, an ingenious inorganic-organic hybrid tongue-mimic sensor array is thus unveiled for noninvasive pattern recognition of thiols in biofluids in a TRL-RET-reversed "turn on" format toward healthcare monitoring. The sensing principle is based on the new finding that there are differential inhibitions from thiols against the polymerization of DA with various concentrations. Furthermore, density function theory (DFT) studies excellently prove our sensing principle and experimental results, reinforcing the power of the presented system. More importantly, chiral recognition of varied concentrations and mixtures of cysteine enantiomers using our platform are also been demonstrated, promising its practical usage. This is a novel concept of inorganic-organic hybrid-based pattern and chiral recognition platform for TRL background-free sensing and would sprout more novel relevant strategies toward broader applications.

Confounding effect of benign pulmonary diseases in selecting volatile organic compounds as markers of lung cancer

Lung cancer (LC) is a leading cause of cancer-related morbidity and mortality globally, and exhaled breath testing has been considered as a fast, convenient and non-invasive way to diagnose LC in its early stages. Volatile organic compounds (VOCs), as markers of LC in exhaled breath, have been widely investigated for cancer diagnosis. However, few studies have reported on the interference of benign pulmonary diseases (BPD) in the selection of VOC markers for LC. During this study, 207 samples were analyzed using thermal desorption instrumentation/gas chromatography/mass spectrometry (TD-GCMS) to detect C₆-C₃₀ VOCs, and all samples were divided into four groups: LC group, BPD group, lung disease (LD) group (including LC group and BPD group) and healthy group. To make up for the deficiency of detecting low carbon hydrocarbons (<C₆), 277 samples were analyzed using solid-phase micro-extraction/gas chromatography/mass spectrometry (SPME-GCMS), divided among the four groups. VOC markers were selected by reference to the receiver operating characteristics curve. With the comparisons among the LC group, BPD group and healthy group from TD-GCMS and SPME-GCMS results, we found that exhaled VOCs are capable of discriminating LC group versus healthy group and BPD group versus healthy group with a consistency of 70%-80%. However, no VOCs can be selected with good discrimination capability between the LC group and BPD group, indicating that BPD interferes significantly in VOC marker selection for LC. To discriminate breath samples from the LD group and healthy group, 11 VOCs, including ten selected from TD-GCMS and one from SPME-GCMS, were chosen as markers for LD diagnosis. The sensitivity, specificity and overall accuracy of the diagnostic model established using ten VOCs were 80.8%, 84% and 82.7%, and those of the model established by using one VOC were 75.6%, 78.9% and 76.7%. These results validate that LD patients can be effectively discriminated and diagnosed using exhaled VOC analysis. (Clinical trial registration number: ChiCTR-DCD-15007106.).

A Future with Ubiquitous Sensing and Intelligent Systems

In this paper, we discuss the relevance of sensing and biosensing for the ongoing revolution in science and technology as a product of the merging of machine learning and Big Data into affordable technologies and accessible everyday products. Possible scenarios for the next decades are described with examples of intelligent systems for various areas, most of which will rely on ubiquitous sensing. The technological and societal challenges for developing the full potential of such intelligent systems are also addressed.

Breath volatolomics for diagnosing chronic rhinosinusitis

Purpose

Chronic rhinosinusitis (CRS) is one of the most common chronic diseases treated by primary care physicians. It is increasingly recognized that CRS and nasal polyposis (NP) comprise several disease processes with diverse causes. Hence, subgroups of sinusitis need to be differentiated so that patients can be screened appropriately and personalized medical treatment provided.

Patients and methods

To address this need, we use a cross-reactive nanoarray based on either molecularly modified gold nanoparticles or molecularly modified single-walled carbon nanotubes, combined with pattern recognition for analyzing breath samples. Breath samples were collected from three groups of volunteers (total 71) at the Hillel Yaffe Medical Center: CRS, NP, and control.

Results

Nanoarray results discriminated between patients with sinusitis and the control group with 87% sensitivity, 83% specificity, and 85% accuracy. The system also discriminated well between the subpopulations: 1) CRS vs control (76% sensitivity, 90% specificity); 2) CRS vs NP (82% sensitivity, 71% specificity); and 3) NP vs control (71% sensitivity, 90% specificity).

Conclusion

This preliminary study shows that a nanoarray-based breath test for screening population for sinusitis-related conditions is feasible.

Chemically Modified Polyaniline for the Detection of Volatile Biomarkers of Minimal Sensitivity to Humidity and Bending

Flexible sensors can be widely used in future wearable devices to monitor people's health states. However, most of the sensors are sensitive to humidity and bending effects, limiting their application in a real-world environment. A new strategy is proposed for obtaining flexible sensors with good tolerance to humidity. By integrating a hydrophobic layer on the surface of doped polyaniline, a flexible sensor that can resist water response with a concentration up to 350 ppm is developed. Good resilience against mechanical bending is also achieved in this flexible sensor. These results may trigger a renaissance in flexible sensor applications for disease diagnosing by wearable devices.

Nanosensors for water quality monitoring

Nanomaterial-enabled sensors are being designed for high-efficiency, multiplex-functionality and high-flexibility sensing applications. Many existing nanosensors have the inherent capacity to achieve such goals; however, they require further development into consumer- and operator-friendly tools with the ability to detect analytes in previously inaccessible locations, as well as at a greater scale than heretofore possible. Here, I discuss how nanotechnology-enabled sensors have great, as yet unmet, promise to provide widespread and potentially low-cost monitoring of chemicals, microbes and other analytes in drinking water.

Ex vivo emission of volatile organic compounds from gastric cancer and non-cancerous tissue

The presence of certain volatile organic compounds (VOCs) in the breath of patients with gastric cancer has been reported by a number of research groups; however, the source of these compounds remains controversial. Comparison of VOCs emitted from gastric cancer tissue to those emitted from non-cancerous tissue would help in understanding which of the VOCs are associated with gastric cancer and provide a deeper knowledge on their generation. Gas chromatography with mass spectrometric detection (GC-MS) coupled with head-space needle trap extraction (HS-NTE) as the pre-concentration technique, was used to identify and quantify VOCs released by gastric cancer and non-cancerous tissue samples collected from 41 patients during surgery. Excluding contaminants, a total of 32 VOCs were liberated by the tissue samples. The emission of four of them (carbon disulfide, pyridine, 3-methyl-2-butanone and 2-pentanone) was significantly higher from cancer tissue, whereas three compounds (isoprene, γ-butyrolactone and dimethyl sulfide) were in greater concentration from the non-cancerous tissues (Wilcoxon signed-rank test, p < 0.05). Furthermore, the levels of three VOCs (2-methyl-1-propene, 2-propenenitrile and pyrrole) were correlated with the occurrence of H. pylori; and four compounds (acetonitrile, pyridine, toluene and 3-methylpyridine) were associated with tobacco smoking. Ex vivo analysis of VOCs emitted by human tissue samples provides a unique opportunity to identify chemical patterns associated with a cancerous state and can be considered as a complementary source of information on volatile biomarkers found in breath, blood or urine.

Natural menstrual rhythm and oral contraception diversely affect exhaled breath compositions

Natural menstrual cycle and/or oral contraception diversely affect women metabolites. Longitudinal metabolic profiling under constant experimental conditions is thereby realistic to understand such effects. Thus, we investigated volatile organic compounds (VOCs) exhalation throughout menstrual cycles in 24 young and healthy women with- and without oral contraception. Exhaled VOCs were identified and quantified in trace concentrations via high-resolution real-time mass-spectrometry, starting from a menstruation and then repeated follow-up with six intervals including the next bleeding. Repeated measurements within biologically comparable groups were employed under optimized measurement setup. We observed pronounced and substance specific changes in exhaled VOC concentrations throughout all cycles with low intra-individual variations. Certain blood-borne volatiles changed significantly during follicular and luteal phases. Most prominent changes in endogenous VOCs were observed at the ovulation phase with respect to initial menstruation. Here, the absolute median abundances of alveolar ammonia, acetone, isoprene and dimethyl sulphide changed significantly (P-value ≤ 0.005) by 18.22↓, 13.41↓, 18.02↑ and 9.40↓%, respectively. These VOCs behaved in contrast under the presence of combined oral contraception; e.g. isoprene decreased significantly by 30.25↓%. All changes returned to initial range once the second bleeding phase was repeated. Changes in exogenous benzene, isopropanol, limonene etc. and smoking related furan, acetonitrile and orally originated hydrogen sulphide were rather nonspecific and mainly exposure dependent. Our observations could apprehend a number of known/pre-investigated metabolic effects induced by monthly endocrine regulations. Potential in vivo origins (e.g. metabolic processes) of VOCs are crucial to realize such effects. Despite ubiquitous confounders, we demonstrated the true strength of volatolomics for metabolic monitoring of menstrual cycle and contraceptives. These outcomes may warrant further studies in this direction to enhance our fundamental and clinical understanding on menstrual metabolomics and endocrinology. Counter-effects of contraception can be deployed for future noninvasive assessment of birth control pills. Our findings could be translated toward metabolomics of pregnancy, menopause and post-menopausal complications via breath analysis.

A Rapid and Robust Diagnostic for Liver Fibrosis Using a Multichannel Polymer Sensor Array

Liver disease is the fifth most common cause of premature death in the Western world, with the irreversible damage caused by fibrosis, and ultimately cirrhosis, a primary driver of mortality. Early detection of fibrosis would facilitate treatment of the underlying liver disease to limit progression. Unfortunately, most cases of liver disease are diagnosed late, with current strategies reliant on invasive biopsy or fragile lab-based antibody technologies. A robust, fully synthetic fluorescent-polymer sensor array is reported, which, rapidly (in 45 minutes), detects liver fibrosis from low-volume serum samples with clinically relevant specificity and accuracy, using an easily readable diagnostic output. The simplicity, rapidity, and robustness of this method make it a promising platform for point-of-care diagnostics for detecting and monitoring liver disease.

Bioinspired Cocatalysts Decorated WO3 Nanotube Toward Unparalleled Hydrogen Sulfide Chemiresistor

Herein, we incorporated dual biotemplates, i.e., cellulose nanocrystals (CNC) and apoferritin, into electrospinning solution to achieve three distinct benefits, i.e., (i) facile synthesis of a WO₃ nanotube by utilizing the self-agglomerating nature of CNC in the core of as-spun nanofibers, (ii) effective sensitization by partial phase transition from WO₃ to Na₂W₄O₁₃ induced by interaction between sodium-doped CNC and WO₃ during calcination, and (iii) uniform functionalization with monodispersive apoferritin-derived Pt catalytic nanoparticles (2.22 ± 0.42 nm). Interestingly, the sensitization effect of Na₂W₄O₁₃ on WO₃ resulted in highly selective H₂S sensing characteristics against seven different interfering molecules. Furthermore, synergistic effects with a bioinspired Pt catalyst induced a remarkably enhanced H₂S response ( R_air/ R_gas = 203.5), unparalleled selectivity ( R_air/ R_gas < 1.3 for the interfering molecules), and rapid response (<10 s)/recovery (<30 s) time at 1 ppm of H₂S under 95% relative humidity level. This work paves the way for a new class of cosensitization routes to overcome critical shortcomings of SMO-based chemical sensors, thus providing a potential platform for diagnosis of halitosis.

Optimized Sampling Conditions for Fecal Volatile Organic Compound Analysis by Means of Field Asymmetric Ion Mobility Spectrometry

Fecal volatile organic compounds (VOCs) are increasingly considered to be potential noninvasive, diagnostic biomarkers for various gastrointestinal diseases. Knowledge of the influence of sampling conditions on VOC outcomes is limited. We aimed to evaluate the effects of sampling conditions on fecal VOC profiles and to assess under which conditions an optimal diagnostic accuracy in the discrimination between pediatric inflammatory bowel disease (IBD) and controls could be obtained. Fecal samples from de novo treatment-naïve pediatric IBD patients and healthy controls (HC) were used to assess the effects of sampling conditions compared to the standard operating procedure (reference standard), defined as 500 mg of sample mass diluted with 10 mL tap water, using field asymmetric ion mobility spectrometry (FAIMS). A total of 17 IBD (15 CD (Crohn's disease) and 2 UC (ulcerative colitis)) and 25 HC were included. IBD and HC could be discriminated with high accuracy (accuracy = 0.93, AUC = 0.99, p < 0.0001). A smaller fecal sample mass resulted in a decreased diagnostic accuracy (300 mg accuracy = 0.77, AUC = 0.69, p = 0.02; 100 mg accuracy = 0.70, AUC = 0.74, p = 0.003). A loss of diagnostic accuracy was seen toward increased numbers of thaw–freeze cycles (one cycle, accuracy = 0.61, AUC = 0.80, p = 0.0004; two cycles, accuracy = 0.64, AUC = 0.56, p = 0.753; and three cycles, accuracy = 0.57, AUC = 0.50, p = 0.5101) and when samples were kept at room temperature for 180 min prior to analysis (accuracy = 0.60, AUC = 0.51, p = 0.46). Diagnostic accuracy of VOC profiles was not significantly influenced by storage duration differences of 20 months. The application of a 500 mg sample mass analyzed after one thaw–freeze cycle showed the best discriminative accuracy for the differentiation of IBD and HC. VOC profiles and diagnostic accuracy were significantly affected by sampling conditions, underlining the need for the implementation of standardized protocols in fecal VOC analysis.

Bioinspired Copolymers Based Nose/Tongue-Mimic Chemosensor for Label-Free Fluorescent Pattern Discrimination of Metal Ions in Biofluids

There is a close correlation between body health and the level of biofluid-derived metal ions, which makes it an attractive model analyte for noninvasive health monitoring. The present work has developed a novel nose/tongue-mimic chemosensor array based on bioinspired polydopamine/polyethylenimine copolymers (PDA/PEI _n) for label-free fluorescent determination of metal ions in biofluids. Three types of PDA/PEI _n (PDA/PEI₆, PDA/PEI₁₈, and PDA/PEI₄₈) were prepared by using different concentrations of PEI to construct the proposed sensor array, which would lead to unique fluorescence response patterns upon challenged with metal ions for their pattern discrimination. The results show that as few as 3 PDA/PEI _n sensors can successfully realize the largescale sensitive detection of metal ions in biofluids. Moreover, we have demonstrated that PDA/PEI _n sensors are qualified for lifetime-based pattern discrimination application. Furthermore, the sensors can distinguish between different concentrations of metal ions, as well as a mixture of different metal ions in biofluids, even the mixtures with different valence states. The method promises the simple, rapid, sensitive, and powerful discrimination of metal ions in accessible biofluids, showing the potential applications in the diagnosis of metal ion-involved diseases.

Current and Emerging Trends in Point-of-Care Technology and Strategies for Clinical Validation and Implementation

BACKGROUND

Point-of-care technology (POCT) provides actionable information at the site of care to allow rapid clinical decision-making. With healthcare emphasis shifting toward precision medicine, population health, and chronic disease management, the potential impact of POCT continues to grow, and several prominent POCT trends have emerged or strengthened in the last decade.

CONTENT

This review summarizes current and emerging trends in POCT, including technologies approved or cleared by the Food and Drug Administration or in development. Technologies included have either impacted existing clinical diagnostics applications (e.g., continuous monitoring and targeted nucleic acid testing) or are likely to impact diagnostics delivery in the near future. The focus is limited to in vitro diagnostics applications, although in some sections, technologies beyond in vitro diagnostics are also included given the commonalities (e.g., ultrasound plug-ins for smart phones). For technologies in development (e.g., wearables, noninvasive testing, mass spectrometry and nuclear magnetic resonance, paper-based diagnostics, nanopore-based devices, and digital microfluidics), we also discuss their potential clinical applications and provide perspectives on strategies beyond technological and analytical proof of concept, with the end goal of clinical implementation and impact.

SUMMARY

The field of POCT has witnessed strong growth over the past decade, as evidenced by new clinical or consumer products or research and development directions. Combined with the appropriate strategies for clinical needs assessment, validation, and implementation, these and future POCTs may significantly impact care delivery and associated outcomes and costs.

Detection of Lung Cancer: Concomitant Volatile Organic Compounds and Metabolomic Profiling of Six Cancer Cell Lines of Different Histological Origins

In recent years, there has been an extensive search for a non-invasive screening technique for early detection of lung cancer. Volatile organic compound (VOC) analysis in exhaled breath is one such promising technique. This approach is based on the fact that tumor growth is accompanied by unique oncogenesis, leading to detectable changes in VOC emitting profile. Here, we conducted a comprehensive profiling of VOCs and metabolites from six different lung cancer cell lines and one normal lung cell line using mass spectrometry. The concomitant VOCs and metabolite profiling allowed significant discrimination between lung cancer and normal cell, nonsmall cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as well as between different subtypes of NSCLC. It was found that a combination of benzaldehyde, 2-ethylhexanol, and 2,4-decadien-1-ol could serve as potential volatile biomarkers for lung cancer. A detailed correlation between nonvolatile metabolites and VOCs can demonstrate possible biochemical pathways for VOC production by the cancer cells, thus enabling further optimization of VOCs as biomarkers. These findings could eventually lead to noninvasive early detection of lung cancer and differential diagnosis of lung cancer subtypes, thus revolutionizing lung cancer treatment.

Long-term monitoring of breath methane

In recent years, methane as a component of exhaled human breath has been considered as a potential bioindicator providing information on microbial activity in the intestinal tract. Several studies indicated a relationship between breath methane status and specific gastrointestinal disease. So far, almost no attention has been given to the temporal variability of breath methane production by individual persons. Thus here, for the first time, long-term monitoring was carried out measuring breath methane of three volunteers over periods between 196 and 1002days. Results were evaluated taking into consideration the health status and specific medical intervention events for each individual during the monitoring period, and included a gastroscopy procedure, a vaccination, a dietary change, and chelate therapy. As a major outcome, breath methane mixing ratios show considerable variability within a person-specific range of values. Interestingly, decreased breath methane production often coincided with gastrointestinal complaints whereas influenza infections were mostly accompanied by increased breath methane production. A gastroscopic examination as well as a change to a low-fructose diet led to a dramatic shift of methane mixing ratios from high to low methane production. In contrast, a typhus vaccination as well as single chelate injections resulted in significant short-term methane peaks. Thus, this study clearly shows that humans can change from high to low methane emitters and vice versa within relatively short time periods. In the case of low to medium methane emitters the increase observed in methane mixing ratios, likely resulting from immune reactions and inflammatory processes, might indicate non-microbial methane formation under aerobic conditions. Although detailed reaction pathways are not yet known, aerobic methane formation might be related to cellular oxidative-reductive stress reactions. However, a detailed understanding of the pathways involved in human methane formation is necessary to enable comprehensive interpretation of methane breath levels.

Exploring the potential of needle trap microextraction combined with chromatographic and statistical data to discriminate different types of cancer based on urinary volatomic biosignature

The worldwide high cancer incidence and mortality demands for more effective and specific diagnostic strategies. In this study, we evaluated the efficiency of an innovative methodology, Needle Trap Microextraction (NTME), combined with gas chromatography-mass spectrometry (GC-MS), for the establishment of the urinary volatomic biosignature from breast (BC), and colon (CC) cancer patients as well as healthy individuals (CTL). To achieve this, 40 mL of the headspace of acidified urine (4 mL, 20% NaCl, pH = 2), equilibrated at 50 °C during 40 min, were loaded through the DVB/Car1000/CarX sorbent inside the NTD, and subjected to a GC-MS analysis. This allowed the identification of 130 VOMs from different chemical families that were further processed using discriminant analysis through the partial least squares method (PLS-DA). Several pathways are over activated in cancer patients, being phenylalanine pathway in BC and limonene and pinene degradation pathway in CC the most relevant. Butanoate metabolism is also highly activated in both cancers, as well as tyrosine metabolism in a lesser extension. In BC the xenobiotics metabolism by cytochrome P450 and fatty acid biosynthesis are also differentially activated. Different clusters corresponding to the groups recruited allowed to define sets of volatile organic metabolites (VOMs fingerprints) that exhibit high classification rates, sensitivity and specificity in the discrimination of the selected cancers. As far as we are aware, this is the first time that NTME is used for isolation urinary volatile metabolites, being the obtained results very promising.

Breathprinting Reveals Malaria-Associated Biomarkers and Mosquito Attractants

Current evidence suggests that malarial infection could alter metabolites in the breath of patients, a phenomenon that could be exploited to create a breath-based diagnostic test. However, no study has explored this in a clinical setting. To investigate whether natural human malarial infection leads to a characteristic breath profile, we performed a field study in Malawi. Breath volatiles from children with and those without uncomplicated falciparum malaria were analyzed by thermal desorption-gas chromatography/mass spectrometry. Using an unbiased, correlation-based analysis, we found that children with malaria have a distinct shift in overall breath composition. Highly accurate classification of infection status was achieved with a suite of 6 compounds. In addition, we found that infection correlates with significantly higher breath levels of 2 mosquito-attractant terpenes, α-pinene and 3-carene. These findings attest to the viability of breath analysis for malaria diagnosis, identify candidate biomarkers, and identify plausible chemical mediators for increased mosquito attraction to patients infected with malaria parasites.

Breathprinting and Early Diagnosis of Lung Cancer

The electronic nose (e-nose) is a promising technology as a useful addition to the currently available modalities to achieve lung cancer diagnosis. The e-nose can assess the volatile organic compounds detected in the breath and derived from the cellular metabolism. Volatile organic compounds can be analyzed to identify the individual chemical elements as well as their pattern of expression to reproduce a sensorial combination similar to a fingerprint (breathprint). The e-nose can be used alone, mimicking the combinatorial selectivity of the human olfactory system, or as part of a multisensorial platform. This review analyzes the progress made by investigators interested in this technology as well as the perspectives for its future utilization.

Nitrogen-Doped Single Graphene Fiber with Platinum Water Dissociation Catalyst for Wearable Humidity Sensor

Humidity sensors are essential components in wearable electronics for monitoring of environmental condition and physical state. In this work, a unique humidity sensing layer composed of nitrogen-doped reduced graphene oxide (nRGO) fiber on colorless polyimide film is proposed. Ultralong graphene oxide (GO) fibers are synthesized by solution assembly of large GO sheets assisted by lyotropic liquid crystal behavior. Chemical modification by nitrogen-doping is carried out under thermal annealing in H₂ (4%)/N₂ (96%) ambient to obtain highly conductive nRGO fiber. Very small (≈2 nm) Pt nanoparticles are tightly anchored on the surface of the nRGO fiber as water dissociation catalysts by an optical sintering process. As a result, nRGO fiber can effectively detect wide humidity levels in the range of 6.1-66.4% relative humidity (RH). Furthermore, a 1.36-fold higher sensitivity (4.51%) at 66.4% RH is achieved using a Pt functionalized nRGO fiber (i.e., Pt-nRGO fiber) compared with the sensitivity (3.53% at 66.4% RH) of pure nRGO fiber. Real-time and portable humidity sensing characteristics are successfully demonstrated toward exhaled breath using Pt-nRGO fiber integrated on a portable sensing module. The Pt-nRGO fiber with high sensitivity and wide range of humidity detection levels offers a new sensing platform for wearable humidity sensors.

Altered Volatile Organic Compound Profile in Transgenic Rats Bearing A53T Mutation of Human α-Synuclein: Comparison with Dopaminergic and Serotonergic Denervation

Early diagnosis of Parkinson's disease (PD) is of great importance due its progressive phenotype. Neuroprotective drugs could potentially slow down disease progression if used at early stages. Previously, we have reported an altered content of volatile organic compounds (VOCs) in the breath of rats following a 50% reduction in striatal dopamine (DA) content induced by 6-hydroxydopamine. We now report on the difference in the breath-print and content of VOCs between rats with mild and severe lesions of DA neurons, serotonergic neuronal lesions, and transgenic (Tg) rats carrying the PD-producing A53T mutation of the SNCA (α-synuclein) gene. The Tg rats had an increased content of 3-octen-1-ol and 4-chloro-3-methyl phenol in blood, while in brain tissue, hexanal, hexanol, and 2,3-octanedione were present in controls but absent in Tg rats. Levels of 1-heptyl-2-methyl cyclopropane were increased in brain tissue of Tg rats. The data confirm the potential of breath analysis for detection of human idiosyncratic as well as autosomal dominant PD.

Machine learning for the meta-analyses of microbial pathogens' volatile signatures

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications

The paper deals with a functional instability of electronic nose (e-nose) units which significantly limits their real-life applications. Here we demonstrate how to approach this issue with example of an e-nose based on a metal oxide sensor array developed at the Karlsruhe Institute of Technology (Germany). We consider the instability of e-nose operation at different time scales ranging from minutes to many years. To test the e-nose we employ open-air and headspace sampling of analyte odors. The multivariate recognition algorithm to process the multisensor array signals is based on the linear discriminant analysis method. Accounting for the received results, we argue that the stability of device operation is mostly affected by accidental changes in the ambient air composition. To overcome instabilities, we introduce the add-training procedure which is found to successfully manage both the temporal changes of ambient and the drift of multisensor array properties, even long-term. The method can be easily implemented in practical applications of e-noses and improve prospects for device marketing.

Dual-Mode Gas Sensor Composed of a Silicon Nanoribbon Field Effect Transistor and a Bulk Acoustic Wave Resonator: A Case Study in Freons

In this paper, we develop a novel dual-mode gas sensor system which comprises a silicon nanoribbon field effect transistor (Si-NR FET) and a film bulk acoustic resonator (FBAR). We investigate their sensing characteristics using polar and nonpolar organic compounds, and demonstrate that polarity has a significant effect on the response of the Si-NR FET sensor, and only a minor effect on the FBAR sensor. In this dual-mode system, qualitative discrimination can be achieved by analyzing polarity with the Si-NR FET and quantitative concentration information can be obtained using a polymer-coated FBAR with a detection limit at the ppm level. The complementary performance of the sensing elements provides higher analytical efficiency. Additionally, a dual mixture of two types of freons (CFC-113 and HCFC-141b) is further analyzed with the dual-mode gas sensor. Owing to the small size and complementary metal-oxide semiconductor (CMOS)-compatibility of the system, the dual-mode gas sensor shows potential as a portable integrated sensing system for the analysis of gas mixtures in the future.

Non-invasive lung disease diagnostics from exhaled microdroplets of lung fluid: perspectives and technical challenges

The combination of ultra-sensitive assay techniques and recent improvements in the instrumentation used to collect microdroplets of lung fluid (MLF) from exhaled breath has enabled the development of non-invasive lung disease diagnostics that are based on MLF analysis. In one example of this approach, electrospun nylon filters were used to collect MLFs from patients with pulmonary tuberculosis. The filters were washed to obtain liquid probes, which were then tested for human immunoglobulin A (h-IgA) and fractions of h-IgA specific to ESAT-6 and Psts-1, two antigens secreted by Mycobacterium tuberculosis. Probes collected for 10 min contained 100-1500 fg of h-IgA and, in patients with pulmonary tuberculosis, a portion of these h-IgA molecules showed specificity to the secreted antigens. Separate MLFs and their dry residues were successfully collected using an electrostatic collector and impactor developed especially for this purpose. Visualization of MLF dry residues by atomic force microscopy made it possible to estimate the lipid content in each MLF and revealed mucin molecules in some MLFs. This exciting new approach will likely make it possible to detect biomarkers in individual MLFs. MLFs emerging from an infection site ('hot' microdroplets) are expected to be enriched with infection biomarkers. This paper discusses possible experimental approaches to detecting biomarkers in single MLFs, as well as certain technological problems that need to be resolved in order to develop new non-invasive diagnostics based on analysing biomarkers in separate MLFs.

Exhaled Breath Markers for Nonimaging and Noninvasive Measures for Detection of Multiple Sclerosis

Multiple sclerosis (MS) is the most common chronic neurological disease affecting young adults. MS diagnosis is based on clinical characteristics and confirmed by examination of the cerebrospinal fluids (CSF) or by magnetic resonance imaging (MRI) of the brain or spinal cord or both. However, neither of the current diagnostic procedures are adequate as a routine tool to determine disease state. Thus, diagnostic biomarkers are needed. In the current study, a novel approach that could meet these expectations is presented. The approach is based on noninvasive analysis of volatile organic compounds (VOCs) in breath. Exhaled breath was collected from 204 participants, 146 MS and 58 healthy control individuals. Analysis was performed by gas-chromatography mass-spectrometry (GC-MS) and nanomaterial-based sensor array. Predictive models were derived from the sensors, using artificial neural networks (ANNs). GC-MS analysis revealed significant differences in VOC abundance between MS patients and controls. Sensor data analysis on training sets was able to discriminate in binary comparisons between MS patients and controls with accuracies up to 90%. Blinded sets showed 95% positive predictive value (PPV) between MS-remission and control, 100% sensitivity with 100% negative predictive value (NPV) between MS not-treated (NT) and control, and 86% NPV between relapse and control. Possible links between VOC biomarkers and the MS pathogenesis were established. Preliminary results suggest the applicability of a new nanotechnology-based method for MS diagnostics.

The 150 most important questions in cancer research and clinical oncology series: questions 67-75 : Edited by Chinese Journal of Cancer

Since the beginning of 2017, Chinese Journal of Cancer has published a series of important questions in cancer research and clinical oncology, which sparkle diverse thoughts, interesting communications, and potential collaborations among researchers all over the world. In this article, 9 more questions are presented as followed. Question 67. How could we overcome the resistance of hepatocellular carcinoma against chemotherapeutics? Question 68. Is pursuit of non-covalent small-molecule binders of RAS proteins viable as a strategy of cancer drug discovery? Question 69. In what oligomeric structures do RAS proteins signal? Question 70. How can we achieve non-invasive early detection and diagnosis of lung cancer? Question 71. Does genetic information influence the volatolome enabling diagnosis of lung cancer with genetic mutations via cell headspace or breath analysis? Question 72. Is heavy ion beam radiotherapy effective to kill cancer stem cells? Question 73. Is there any diversity among different types of cancer in terms of sensitivity to heavy ion beam radiotherapy? Question 74. Can targeted alpha-particle therapy augment the effect of carbon ion radiotherapy on malignancies? Question 75. How does chromosomal instability drive tumor progression?

Toward breath analysis on a chip for disease diagnosis using semiconductor-based chemiresistors: recent progress and future perspectives

Semiconductor gas sensors using metal oxides, carbon nanotubes, graphene-based materials, and metal chalcogenides have been reviewed from the viewpoint of the sensitive, selective, and reliable detection of exhaled biomarker gases, and perspectives/strategies to realize breath analysis on a chip for disease diagnosis are discussed based on the concurrent design of high-performance sensing materials and miniaturized pretreatment components. Carbon-based sensing materials that show relatively high responses to NO and NH₃ at low or mildly raised temperatures can be applied to the diagnosis of asthma and renal disease. Halitosis can be diagnosed by employing sensing or additive materials such as CuO and Mo that have high chemical affinities for H₂S, while catalyst-loaded metal oxide nanostructure sensors or their arrays have been used to diagnose diabetes via the selective detection of acetone or by pattern recognition of sensor signals. For the ultimate miniaturization of a breath-analysis system into a tiny chip, preconditioning that includes preconcentration, dehumidification, and flow sensing needs to be either improved through the design of gas/moisture adsorbents or removed/simplified through the design of highly sensitive sensing materials that are less impervious to interference from humidity and temperature. Moreover, an abundant sensing library needs to be provided for the diagnosis of diseases (e.g. lung cancer) that are associated with multiple biomarker gases and for finding new methods to diagnose other diseases. For this aim, p-type oxide semiconductors with high catalytic activities, as well as combinatorial approaches, can be considered for the development of sensing materials that detect less-reactive large molecules, and high-throughput screening, respectively. Selectivity for a specific biomarker gas will simplify the system further. Breath analysis on a tiny chip using semiconductor chemiresistors with ultralow power consumption that is connected to the 'Internet of Things' will pave new roads for disease diagnosis and patient monitoring.

Exhaled Volatile Organic Compounds of Infection: A Systematic Review

With heightened global concern of microbial drug resistance, advanced methods for early and accurate diagnosis of infection are urgently needed. Analysis of exhaled breath volatile organic compounds (VOCs) toward detecting microbial infection potentially allows a highly informative and noninvasive alternative to current genomics and culture-based methods. We performed a systematic review of research literature reporting human and animal exhaled breath VOCs related to microbial infections. In this Review, we find that a wide range of breath sampling and analysis methods are used by researchers, which significantly affects interstudy method comparability. Studies either perform targeted analysis of known VOCs relating to an infection, or non-targeted analysis to obtain a global profile of volatile metabolites. In general, the field of breath analysis is still relatively immature, and there is much to be understood about the metabolic production of breath VOCs, particularly in a host where both commensal microflora as well as pathogenic microorganisms may be manifested in the airways. We anticipate that measures to standardize high throughput sampling and analysis, together with an increase in large scale collaborative international trials, will bring routine breath VOC analysis to improve diagnosis of infection closer to reality.

Drawing Sensors with Ball-Milled Blends of Metal-Organic Frameworks and Graphite

The synthetically tunable properties and intrinsic porosity of conductive metal-organic frameworks (MOFs) make them promising materials for transducing selective interactions with gaseous analytes in an electrically addressable platform. Consequently, conductive MOFs are valuable functional materials with high potential utility in chemical detection. The implementation of these materials, however, is limited by the available methods for device incorporation due to their poor solubility and moderate electrical conductivity. This manuscript describes a straightforward method for the integration of moderately conductive MOFs into chemiresistive sensors by mechanical abrasion. To improve electrical contacts, blends of MOFs with graphite were generated using a solvent-free ball-milling procedure. While most bulk powders of pure conductive MOFs were difficult to integrate into devices directly via mechanical abrasion, the compressed solid-state MOF/graphite blends were easily abraded onto the surface of paper substrates equipped with gold electrodes to generate functional sensors. This method was used to prepare an array of chemiresistors, from four conductive MOFs, capable of detecting and differentiating NH₃, H₂S and NO at parts-per-million concentrations.

Inhalation exposure to three-dimensional printer emissions stimulates acute hypertension and microvascular dysfunction

Fused deposition modeling (FDM™), or three-dimensional (3D) printing has become routine in industrial, occupational and domestic environments. We have recently reported that 3D printing emissions (3DPE) are complex mixtures, with a large ultrafine particulate matter component. Additionally, we and others have reported that inhalation of xenobiotic particles in this size range is associated with an array of cardiovascular dysfunctions. Sprague-Dawley rats were exposed to 3DPE aerosols via nose-only exposure for ~3h. Twenty-four hours later, intravital microscopy was performed to assess microvascular function in the spinotrapezius muscle. Endothelium-dependent and -independent arteriolar dilation were stimulated by local microiontophoresis of acetylcholine (ACh) and sodium nitroprusside (SNP). At the time of experiments, animals exposed to 3DPE inhalation presented with a mean arterial pressure of 125±4mmHg, and this was significantly higher than that for the sham-control group (94±3mmHg). Consistent with this pressor response in the 3DPE group, was an elevation of ~12% in resting arteriolar tone. Endothelium-dependent arteriolar dilation was significantly impaired after 3DPE inhalation across all iontophoretic ejection currents (0-27±15%, compared to sham-control: 15-120±21%). Endothelium-independent dilation was not affected by 3DPE inhalation. These alterations in peripheral microvascular resistance and reactivity are consistent with elevations in arterial pressure that follow 3DPE inhalation. Future studies must identify the specific toxicants generated by FDM™ that drive this acute pressor response.

Integrating exhaled breath diagnostics by disease-sniffing dogs with instrumental laboratory analysis

Dogs have been studied for many years as a medical diagnostic tool to detect a pre-clinical disease state by sniffing emissions directly from a human or an in vitro biological sample. Some of the studies report high sensitivity and specificity in blinded case-control studies. However, in these studies it is completely unknown as to which suites of chemicals the dogs detect and how they ultimately interpret this information amidst confounding background odors. Herein, we consider the advantages and challenges of canine olfaction for early (meaningful) detection of cancer, and propose an experimental concept to narrow the molecular signals used by the dog for sample classification to laboratory-based instrumental analysis. This serves two purposes; first, in contrast to dogs, analytical methods could be quickly up-scaled for high throughput sampling. Second, the knowledge gained from identifying probative chemicals could be helpful in learning more about biochemical pathways and disease progression. We focus on exhaled breath aerosol, arguing that the semi-volatile fraction should be given more attention. Ultimately, we conclude that the interaction between dog-based and instrument-based research will be mutually beneficial and accelerate progress towards early detection of cancer by breath analysis.

High-Definition Medicine

The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution-what we refer to as high-definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging, and behavioral tracking. Our ability to understand and act upon these observations at equally high precision is driven by advances in genome editing, cellular reprogramming, tissue engineering, and information technologies, especially artificial intelligence. In this review, we will examine the core disciplines that enable high-definition medicine and project how these technologies will alter the future of medicine.

Nanoelectronic Discrimination of Nonmalignant and Malignant Cells Using Nanotube Field-Effect Transistors

Detection of malignant cells in tissue is a difficult hurdle in medical diagnostics and screening. Carbon nanotubes are extremely sensitive to their local environments, and nanotube-based field-effect transistors (NTFETs) provide a plethora of information regarding the mechanism of interaction with target analytes. Herein, we use a series of functionalized metal nanoparticle-decorated NTFET devices forming an array with multiple nonselective sensor units as the electronic "tongue", sensing all five basic tastes. By extraction of selected NTFET characteristics and using linear discriminant analysis, we have successfully detected and discriminated between malignant and nonmalignant tissues and cells. We also studied the sensing mechanism and what NTFET characteristics are responsible for the variation of response between cell types, allowing for the design of future studies such as detection of malignant cells in a biopsy or the effects of malignant cells on healthy tissue.

Innovative Nanosensor for Disease Diagnosis

As a futuristic diagnosis platform, breath analysis is gaining much attention because it is a noninvasive, simple, and low cost diagnostic method. Very promising clinical applications have been demonstrated for diagnostic purposes by correlation analysis between exhaled breath components and specific diseases. In addition, diverse breath molecules, which serve as biomarkers for specific diseases, are precisely identified by statistical pattern recognition studies. To further improve the accuracy of breath analysis as a diagnostic tool, breath sampling, biomarker sensing, and data analysis should be optimized. In particular, development of high performance breath sensors, which can detect biomarkers at the ppb-level in exhaled breath, is one of the most critical challenges. Due to the presence of numerous interfering gas species in exhaled breath, selective detection of specific biomarkers is also important. This Account focuses on chemiresistive type breath sensors with exceptionally high sensitivity and selectivity that were developed by combining hollow protein templated nanocatalysts with electrospun metal oxide nanostructures. Nanostructures with high surface areas are advantageous in achieving high sensitivity because the sensing signal is dominated by the surface reaction between the sensing layers and the target biomarkers. Furthermore, macroscale pores between one-dimensional (1D) nanostructures can facilitate fast gas diffusion into the sensing layers. To further enhance the selectivity, catalytic functionalization of the 1D metal oxide nanostructure is essential. However, the majority of conventional techniques for catalytic functionalization have failed to achieve a high degree of dispersion of nanoscale catalysts due to aggregation on the surface of the metal oxide, which severely deteriorates the sensing properties by lowering catalytic activity. This issue has led to extensive studies on monolithically dispersed nanoscale particles on metal oxides to maximize the catalytic performances. As a pioneering technique, a bioinspired templating route using apoferritin, that is, a hollow protein cage, has been proposed to obtain nanoscale (∼2 nm) catalyst particles with high dispersity. Nanocatalysts encapsulated by a protein shell were first used in chemiresistive type breath sensors for catalyst functionalization on 1D metal oxide structures. We discuss the robustness and versatility of the apoferrtin templating route for creating highly dispersive catalytic NPs including single components (Au, Pt, Pd, Rh, Ag, Ru, Cu, and La) and bimetallic catalysts (PtY and PtCo), as well as the core-shell structure of Au-Pd (Au-core@Pd-shell). The use of these catalysts is essential to establish high performance sensors arrays for the pattern recognition of biomarkers. In addition, novel multicomponent catalysts provide unprecedented sensitivity and selectivity. With this in mind, we discuss diverse synthetic routes for nanocatalysts using apoferritin and the formation of various catalyst-1D metal oxide composite nanostructures. Furthermore, we discuss detection capability of a simulated biomarker gas using the breath sensor arrays and principal component analysis. Finally, future prospects with the portable breath analysis platform are presented by demonstrating the potential feasibility of real-time and on-site breath analysis using chemiresistive sensors.

Smelling, Seeing, Tasting-Old Senses for New Sensing

The senses are the physiological mechanisms of perception that enable an organism to interact with the surrounding media. For centuries, humans have utilized these senses in science; vision and olfaction have been used the most extensively in laboratories followed by gustation and somatosensation, whereas audition has only rarely been employed. Most of these applications of senses were developed spontaneously based on the natural behavior of the chemistry of the reactants producing changes in scent, taste, or color. In recent years, by exploiting the outstanding properties of nanoparticles, many groups have demonstrated alternative sensing scenarios where the detection limits are remarkably improved, enabling the recognition of hazardous substances by mere sight, smell, or taste. Such alternative sensing approaches can be divided into two main groups: (i) methods that identify a single analyte by engineering a reaction that promotes a change in color or the generation of a characteristic scent, and (ii) methods that emulate or even improve mammalian senses, especially those related to taste and smell. In this Perspective, we discuss the context of each technology, present prominent examples, and evaluate the complexities, potential pitfalls, and opportunities presented by different re-engineering strategies.