Monolayer-capped gold nanoparticles for disease detection from breath

Application of electronic nose technology in the diagnosis of gastrointestinal diseases: a review

Electronic noses (eNoses) are electronic bionic olfactory systems that use sensor arrays to produce response patterns to different odors, thereby enabling the identification of various scents. Gastrointestinal diseases have a high incidence rate and occur in 9 out of 10 people in China. Gastrointestinal diseases are characterized by a long course of symptoms and are associated with treatment difficulties and recurrence. This review offers a comprehensive overview of volatile organic compounds, with a specific emphasis on those detected via the eNose system. Furthermore, this review describes the application of bionic eNose technology in the diagnosis and screening of gastrointestinal diseases based on recent local and international research progress and advancements. Moreover, the prospects of bionic eNose technology in the field of gastrointestinal disease diagnostics are discussed.

An update on new-age potential biomarkers for Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that deals with dopaminergic deficiency in Substantia nigra pars compact (SNpc) region of the brain. Dopaminergic deficiency manifests into motor dysfunction. Alpha-synuclein protein aggregation is the source for inception of the pathology. Motor symptoms include rigidity, akinesia, tremor and gait dysfunction. Pre-motor symptoms are also seen in early stage of the disease; however, they are not distinguishable. Lack of early diagnosis in PD pathology poses a major challenge for development of disease modifying therapeutics. Substantial neuronal loss has already been occurred before the clinical manifestations appear and hence, it becomes impossible to halt the disease progression. Current diagnostics are majorly based on the clinical symptoms and thus fail to detect early progression of the disease. Thus, there is need for early diagnosis of PD, for detection of the disease at its inception. This will facilitate the effective use of therapies that halt the progression and will make remission possible. Many novel biomarkers are being developed that include blood-based biomarker, CSF biomarker. Other than that, there are non-invasive techniques that can detect biomarkers. We aim to discuss potential role of these new age biomarkers and their association with PD pathogenesis in this review.

An application of carbohydrate polymers-based surface-modified gold nanoparticles for improved target delivery to liver cancer therapy - A systemic review

Gold nanoparticles have been broadly investigated as cancer diagnostic and therapeutic agents. Gold nanoparticles are a favorable drug delivery vehicle with their unique subcellular size and good biocompatibility. Chitosan, agarose, fucoidan, porphyran, carrageenan, ulvan and alginate are all examples of biologically active macromolecules. Since they are biocompatible, biodegradable, and irritant-free, they find extensive application in biomedical and macromolecules. The versatility of these compounds is enhanced because they are amenable to modification by functional groups like sulfation, acetylation, and carboxylation. In an eco-friendly preparation process, the biocompatibility and targeting of GNPs can be improved by functionalizing them with polysaccharides. This article provides an update on using carbohydrate-based GNPs in liver cancer treatment, imaging, and drug administration. Selective surface modification of several carbohydrate types and further biological uses of GNPs are focused on.

The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis

Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.

Liquid Biopsy-Based Volatile Organic Compounds from Blood and Urine and Their Combined Data Sets for Highly Accurate Detection of Cancer

Liquid biopsy is seen as a prospective tool for cancer screening and tracking. However, the difficulty lies in effectively sieving, isolating, and overseeing cancer biomarkers from the backdrop of multiple disrupting cells and substances. The current study reports on the ability to perform liquid biopsy without the need to physically filter and/or isolate the cancer cells per se. This has been achieved through the detection and classification of volatile organic compounds (VOCs) emitted from the cancer cells found in the headspace of blood or urine samples or a combined data set of both. Spectrometric analysis shows that blood and urine contain complementary or overlapping VOC information on kidney cancer, gastric cancer, lung cancer, and fibrogastroscopy subjects. Based on this information, a nanomaterial-based chemical sensor array in conjugation with machine learning as well as data fusion of the signals achieved was carried out on various body fluids to assess the VOC profiles of cancer. The detection of VOC patterns by either Gas Chromatography-Mass Spectrometry (GC-MS) analysis or our sensor array achieved >90% accuracy, >80% sensitivity, and >80% specificity in different binary classification tasks. The hybrid approach, namely, analyzing the VOC datasets of blood and urine together, contributes an additional discrimination ability to the improvement (>3%) of the model's accuracy. The contribution of the hybrid approach for an additional discrimination ability to the improvement of the model's accuracy is examined and reported.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Biodiagnostics in an era of global pandemics-From biosensing materials to data management

The novel corona virus SARS-CoV-2 (COVID-19) has exposed the world to challenges never before seen in fast diagnostics, monitoring, and prevention of the outbreak. As a result, different approaches for fast diagnostic and screening are made and yet to find the ideal way. The current mini-review provides and examines evidence-based innovative and rapid chemical sensing and related biodiagnostic solutions to deal with infectious disease and related pandemic emergencies, which could offer the best possible care for the general population and improve the approachability of the pandemic information, insights, and surrounding contexts. The review discusses how integration of sensing devices with big data analysis, artificial Intelligence or machine learning, and clinical decision support system, could improve the accuracy of the recorded patterns of the disease conditions within an ocean of information. At the end, the mini-review provides a prospective on the requirements to improve our coping of the pandemic-related biodiagnostics as well as future opportunities.

In Situ Grown Gold Nanoisland-Based Chemiresistive Electronic Nose for Sniffing Distinct Odor Fingerprints

Chemiresistors based on metal-insulator-metal structures are attractive transducers for rapid tracing of a wide repertoire of (bio)chemical species in the vapor phase. However, current fabrication techniques suffer greatly from sensor-to-sensor variability, limiting their reproducible and reliable application in real-world settings. We demonstrate a novel, facile, and ubiquitously applicable strategy for fabricating highly reliable and reproducible organothiol-functionalized gold nanoisland-based chemiresistors. The novel fabrication technique involves iterative in situ seeding, growth, and surface functionalization of gold nanoislands on an interdigitated electrode, which in turn generates a multi-layered densely packed continuous gold nanoisland film. The chemiresistors fabricated using the proposed strategy exhibited high sensor-to-sensor reproducibility owing to the controlled iterative seeding and growth-based fabrication technique, long-term stability, and specificity for detection and identification of a wide variety of volatile organic compounds. Upon exposure to a specific odor, the chemiresistor ensemble comprised nine different chemical functionalities and produced a unique and discernable odor fingerprint that is reproducible for at least up to 90 days. Integrating these odor fingerprints with a simple linear classifier was found to be sufficient for discriminating between all six odors used in this study. We believe that the fabrication strategy presented here, which is agnostic to chemical functionality, enables fabrication of highly reliable and reproducible sensing elements, and thereby an adaptable electronic nose for a wide variety of real-world gas sensing applications.

Breath volatile organic compound analysis: an emerging method for gastric cancer detection

Gastric cancer is a common malignancy, being the fifth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide. Diagnosis of gastric cancer at the early stage is critical to effectively improve the survival rate. However, a substantial proportion of patients with gastric cancer in the early stages lack specific symptoms or are asymptomatic. Moreover, the imaging techniques currently used for gastric cancer screening, such as computed tomography and barium examination, are usually radioactive and have low sensitivity and specificity. Even though endoscopy has high accuracy for gastric cancer screening, its application is limited by the invasiveness of the technique. Breath analysis is an economic, effective, easy to perform, non-invasive detection method, and has no undesirable side effects on subjects. Extensive worldwide research has been conducted on breath volatile organic compounds (VOCs), which reveals its prospect as a potential method for gastric cancer detection. Many interesting results have been obtained and innovative methods have been introduced in this subject; hence, an extensive review would be beneficial. By providing a comprehensive list of breath VOCs identified by gastric cancer would promote further research in this field. This review summarizes the commonly used technologies for exhaled breath analysis, focusing on the application of analytical instruments in the detection of breath VOCs in gastric cancers, and the alterations in the profile of breath biomarkers in gastric cancer patients are discussed as well.

Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test.

Fabricating and printing chemiresistors based on monolayer-capped metal nanoparticles

Chemiresistors that are based on monolayer-capped metal nanoparticles (MCNPs) have been used in a wide variety of innovative sensing applications, including detection and monitoring of diagnostic markers in body fluids, explosive materials, environmental contaminations and food quality control. The sensing mechanism is based on reversible swelling or aggregation and/or changes in dielectric constant of the MCNPs. In this protocol, we describe a procedure for producing MCNP-based chemiresistive sensors that is reproducible from device to device and from batch to batch. The approach relies on three main steps: (i) controlled synthesis of gold MCNPs, (ii) fabrication of electrodes that are surrounded with a microbarrier ring to confine the deposited MCNP solution and (iii) a tailor-made drying process to enable evaporation of solvent residues from the MCNP sensing layer to prevent a coffee-ring effect. Application of this approach has been shown to produce devices with ±1.5% variance-a value consistent with the criterion for commercial sensors-as well as long shelf life and stability. Fabrication of chemical sensors based on dodecanethiol- or 2-ethylhexanethiol-capped MCNPs with this approach provides high sensitivity and accuracy in the detection of volatile organic compounds (e.g., octane and decane), toxic gaseous species (e.g., HCl and NH₃) in air and simulated mixtures of lung and gastric cancer from exhaled breath.

Non-invasive in vivo monitoring of transplanted stem cells in 3D-bioprinted constructs using near-infrared fluorescent imaging

Cell-based tissue engineering strategies have been widely established. However, the contributions of the transplanted cells within the tissue-engineered scaffolds to the process of tissue regeneration remain poorly understood. Near-infrared (NIR) fluorescence imaging systems have great potential to non-invasively monitor the transplanted cell-based tissue constructs. In this study, labeling mesenchymal stem cells (MSCs) using a lipophilic pentamethine indocyanine (CTNF127, emission at 700 nm) as a NIR fluorophore was optimized, and the CTNF127-labeled MSCs (NIR-MSCs) were printed embedding in gelatin methacryloyl bioink. The NIR-MSCs-loaded bioink showed excellent printability. In addition, NIR-MSCs in the 3D constructs showed high cell viability and signal stability for an extended period in vitro. Finally, we were able to non-invasively monitor the NIR-MSCs in constructs after implantation in a rat calvarial bone defect model, and the transplanted cells contributed to tissue formation without specific staining. This NIR-based imaging system for non-invasive cell monitoring in vivo could play an active role in validating the cell fate in cell-based tissue engineering applications.

Detection of Single Cancer Cells in Blood with Artificially Intelligent Nanoarray

Detection and monitoring of single cancer cells (SCCs), such as circulating tumor cells (CTCs), would be of aid in an efficient early detection of cancer, a tailored (personalized) therapy, and in a fast bedside assessment of treatment efficacy. Nevertheless, currently available techniques, which mostly rely on the isolation of SCCs based on their physical or biological properties, suffer from low sensitivity, complicated technical procedures, low cost-effectiveness, and being unsuitable for continuous monitoring. We report here on the design and use of an artificially intelligent nanoarray based on a heterogeneous set of chemisensitive nanostructured films for the detection of SCCs using volatile organic compounds emanating in the air trapped above blood samples containing SCCs. For demonstration purposes, we have focused on samples containing A549 lung cancer cells (hereafter, SCC^A549). The nanoarray developed to detect SCC^A549 has >90% accuracy, >85% sensitivity, and >95% specificity. Detection works irrespective of the medium and/or the environment. These results were validated by complementary mass spectrometry. The ability to continuously record, store, and preprocess the signals increases the chances that this nanotechnology might also be useful in the early detection of cancer cells in the blood and continuous monitoring of their possible progression.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Effect of Thiol Molecular Structure on the Sensitivity of Gold Nanoparticle-Based Chemiresistors toward Carbonyl Compounds

Increasing both the sensitivity and selectivity of thiol-functionalized gold nanoparticle chemiresistors remains a challenging issue in the quest to develop real-time gas sensors. The effects of thiol molecular structure on such sensor properties are not well understood. This study investigates the effects of steric as well as electronic effects in a panel of substituted thiol-urea compounds on the sensing properties of thiolate monolayer-protected gold nanoparticle chemiresistors. Three series of urea-substituted thiols with different peripheral end groups were synthesized for the study and used to prepare gold nanoparticle-based chemiresistors. The responses of the prepared sensors to trace volatile analytes were significantly affected by the urea functional motifs. The largest response for sensing acetone among the three series was observed for the thiol-urea sensor featuring a tert-butyl end group. Furthermore, the ligands fitted with N, N’-dialkyl urea moieties exhibit a much larger response to carbonyl analytes than the more acidic urea series containing N-alkoxy-N’-alkyl urea and N, N’-dialkoxy urea groups with the same peripheral end groups. The results show that the peripheral molecular structure of thiolate-coated gold nanoparticles plays a critical role in sensing target analytes.

Redispersion of cryoaggregated gold nanoparticle by means of laser irradiation and effect on biological interactions

Agglomeration/aggregation is an indispensable phenomenon observed by different nanoparticles. In the present study, commercial grade (50 nm) and chemically synthesized (40 nm) gold nanoparticles (AuNPs) were aggregated at sub-zero temperatures, followed by disruption of the AuNP aggregates via nanosecond laser-ablation and subsequent effect on biological interactions. AuNPs were characterized pre/post laser-ablation via UV-visible spectroscopy, transmission electron microscopy, atomic force microscopy, etc. The process of freezing (aggregation) and laser-ablation (dispersion) was performed multiple times, in order to compare the yield of nanoparticles after each cycle of laser-ablation. Further, AuNPs pre/post laser-ablation were assessed for cytotoxicity, protein-corona formation, and cell-uptake by in vitro studies using RAW264.7, Caco-2 and Neuro-2 a cell lines. Aggregates for both the types of AuNPs displayed fragmentation following first cycle of laser-ablation. In addition, AuNPs obtained after fragmentation of the aggregates showed reduction in diameter and reshaping, as compared to native AuNPs. The size and shape of the nanoparticles after second and third cycle of laser-ablation was same as that obtained after first cycle of ablation. Both laser-ablated and native AuNPs showed similar effects on viability of RAW 264.7 and Caco-2 cells, after 24 h and 48 h of exposure. Cell uptake of native and laser-ablated AuNPs was observed to be a size dependent phenomenon. Present findings showed that nanosecond laser ablation of cryoaggregated AuNPs lead to changes in the physical properties of AuNPs post ablation like size and shape, however, biological interaction with cells remained same. This work is first report on biological interactions of AuNPs generated via laser-ablation of cryoaggregated AuNPs.

Sniffing Out Urinary Tract Infection-Diagnosis Based on Volatile Organic Compounds and Smell Profile

Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1-2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24-72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography-mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent's resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

Enhancement of hydrophilicity, biocompatibility and biodegradability of poly(ε-caprolactone) electrospun nanofiber scaffolds using poly(ethylene glycol) and poly(L-lactide-co-ε-caprolactone-co-glycolide) as additives for soft tissue engineering

In this study, poly(ε-caprolactone) (PCL) has been blended with a more hydrophilic poly(ethylene glycol) (PEG) and with a biocompatible block-co-polymer: poly(L-lactide-co-ε-caprolactone-co-glycolide) (PLCG) in order to improve hydrophilicity, biocompatibility and biodegradability of PCL. PCL and the blend solutions were subjected to electrospinning to produce nanofiber scaffolds by the addition of only 1 wt% of PEG and PLCG either singly or in combination in PCL to retain the mechanical properties of the scaffolds. PCL-PEG-PLCG ternary and two binary (PCL-PEG and PCL-PLCG) blend nanofiber scaffolds have been prepared for comparison. The resulting nanofibers showed a smooth and flaw-free surface and the diameter of the nanofibers displayed a normal distribution. The PCL-PEG nanofiber scaffold showed improved hydrophilicity [water contact angle (WCA) ∼84°] over pristine PCL (WCA ∼127°); while PCL-PLCG and PCL-PEG-PLCG scaffolds exhibited absolute wetting by water, likely due to high porosity. In vitro biocompatibility studies using gingival mesenchymal stem cells (gMSCs) suggested that, both the PCL and the blend scaffolds were biocompatible supporting cell-viability and growth of gMSCs following their seeding on these scaffolds. Biodegradation studies in phosphate buffer solution showed that the addition of PEG and PLCG in PCL increased the weight loss of scaffolds with time, indicating higher extent of biodegradation in the blend scaffolds and the weight loss followed the power law curve with time.

Differential toxicity mechanism of gold nanoparticles in HK-2 renal proximal tubular cells and 786-0 carcinoma cells

Aim: To research the influence and mechanism of gold nanoparticles (AuNPs) with different size for HK-2 cells (kidney normal cells) and 786-0 cells (kidney cancer cells). Materials & methods: HK-2 cells and 786-0 cells were treated with 5 and 200 nm AuNPs at 1 and 10 μg/ml. The cell viability, intracellular reactive oxygen species levels, cell apoptosis, cell autophagy, and related cell signaling pathways were analyzed. Results: In HK-2 cells, AuNPs reduced the activity of Akt and mTOR and upregulated the expression of LC3 II. In 786-0 cells, the activity of p38 was upregulated, which leaded to the increase of caspase 3 and initiated apoptosis. Conclusion: AuNPs of 5 and 200 nm at 10 μg/ml exerted antitumor effect by prompting apoptosis and inhibiting proliferation, while autophagy was activated to protect HK-2 cells from AuNPs-induced cytotoxicity.

PLA-PCL-PEG-PCL-PLA based micelles for improving the ocular permeability of dexamethasone: development, characterization, and in vitro evaluation

The aim of the present research was to investigate the feasibility of developing polylactide-polycaprolactone-polyethylene glycol-polycaprolactone-polylactide (PLA-PCL-PEG-PCL-PLA) based micelles to improve ocular permeability of dexamethasone (DEX). PLA-PCL-PEG-PCL-PLA copolymers were synthesized by a ring-opening polymerization method. DEX was loaded into the developed copolymers. The DEX-loaded micelles were characterized using transmission electron microscopy (TEM) and dynamic light scattering (DLS) methods. Cytotoxicity of the micelles obtained was investigated on L929 cell line. Cellular uptake was followed by fluorescence microscopy and flow cytometry analyses. The release behavior of DEX from the micelles as well as the drug release kinetics was studied. Corneal permeability was also evaluated using an ex vivo bovine model. The pentablock copolymers were successfully synthesized. The TEM results verified the formation of spherical micelles, the sizes of which was approximately 65 nm. The micelles exhibited suitable compatibility on L929 cells. The release profile showed an initial burst release phase followed by a sustained release phase, the kinetic of which was close to the Weibull's distribution model. The micelles showed higher corneal permeability in comparison to a marketed DEX eye drop. Taken together, the results indicated that the PLA-PCL-PEG-PCL-PLA micelles could be appropriate candidates for the ocular delivery of DEX, and probably other hydrophobic drugs.

Quantitative Measures of Reliability and Sensitivity of Nanoparticle-Based Sensors in Detecting Volatile Organic Compounds

We herein provide quantitative measures of sensors' reliability and sensitivity as a function of the sensor's capacity (maximum detection signal or saturation state) in addition to other adsorption-desorption parameters that define the detection signals toward volatile organic compounds (VOCs). The measures we have developed show differentiation between irregular dispersed points of sensors with low and high capacities. We show that the sharpest capacity that separates between the two types of distribution points, viz the reliability limit (RL), is tightly linked with the desorption constant k _d. Less sharp RLs give interpretations of other reliability indicators. RL also provides information about the reliability of detecting signals of VOCs for a given sensor and sensors for a particular VOC. We show that sensors with high capacities are more reliable and sensitive to detecting signals of VOCs than sensors with lower capacities.

Breath analysis of cancer in the present and the future

Most of the currently used diagnostics for cancerous diseases have yet to meet the standards of screening, as they are insufficiently accurate and/or invasive and risky. In this review, we describe the rationale, the progress made to date, and the potential of analysing the exhaled volatile organic compounds as a pathway for enabling early diagnosis of cancer and, therefore, for achieving better clinical prognosis and survival rates. The review highlights the major advancements made in this field, from fundamentals, up to translational phases and clinical trials, with a special emphasis on sensing platforms based on nanomaterials. The prospects for breath analysis in early cancerous disease are presented and discussed.

Ligand-Capped Ultrapure Metal Nanoparticle Sensors for the Detection of Cutaneous Leishmaniasis Disease in Exhaled Breath

Human cutaneous leishmaniasis, although designated as one of the most neglected tropical diseases, remains underestimated due to its misdiagnosis. The diagnosis is mainly based on the microscopic detection of amastigote forms, isolation of the parasite, or the detection of Leishmania DNA, in addition to its differential clinical characterization; these tools are not always available in routine daily practice, and they are expensive and time-consuming. Here, we present a simple-to-use, noninvasive approach for human cutaneous leishmaniasis diagnosis, which is based on the analysis of volatile organic compounds in exhaled breath with an array of specifically designed chemical gas sensors. The study was realized on a group of n = 28 volunteers diagnosed with human cutaneous leishmaniasis and a group of n = 32 healthy controls, recruited in various sites from Tunisia, an endemic country of the disease. The classification success rate of human cutaneous leishmaniasis patients achieved by our sensors test was 98.2% accuracy, 96.4% sensitivity, and 100% specificity. Remarkably, one of the sensors, based on CuNPs functionalized with 2-mercaptobenzoxazole, yielded 100% accuracy, 100% sensitivity, and 100% specificity for human cutaneous leishmaniasis discrimination. While AuNPs have been the most extensively used in metal nanoparticle-ligand sensing films for breath sensing, our results demonstrate that chemical sensors based on ligand-capped CuNPs also hold great potential for breath volatile organic compounds detection. Additionally, the chemical analysis of the breath samples with gas chromatography coupled to mass spectrometry identified nine putative breath biomarkers for human cutaneous leishmaniasis.

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.

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.

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.

Highly-Selective Optoelectronic Nose Based on Surface Plasmon Resonance Imaging for Sensing Volatile Organic Compounds

Monitoring volatile organic compounds (VOCs) is an important issue, but difficult to achieve on a large scale and on the field using conventional analytical methods. Electronic noses (eNs), as promising alternatives, are still compromised by their performances due to the fact that most of them rely on a very limited number of sensors and use databases devoid of kinetic information. To narrow the performance gap between human and electronic noses, we developed a novel optoelectronic nose, which features a large sensor microarray that enables multiplexed monitoring of binding events in real-time with a temporal response. For the first time, surface plasmon resonance imaging is demonstrated as a promising novel analytical tool for VOC detection in the gas phase. By combining it with cross-reactive sensor microarrays, the obtained optoelectronic nose shows a remarkably high selectivity, capable of discriminating between homologous VOCs differing by only a single carbon atom. In addition, the optoelectronic nose has good repeatability and stability. Finally, the preliminary assays using VOC binary and ternary mixtures show that it is also very efficient for the analysis of more complex samples, opening up the exciting perspective of applying it to "real-world" samples in diverse domains.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

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.

Correlation analysis of respiratory signals by using parallel coordinate plots

BACKGROUND AND OBJECTIVES

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data.

METHODS

In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP.

RESULTS

The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals.

CONCLUSION

It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data.

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.

* Engineering Membranes for Bone Regeneration

This review is focused on the use of membranes for the specific application of bone regeneration. The first section focuses on the relevance of membranes in this context and what are the specifications that they should possess to improve the regeneration of bone. Afterward, several techniques to engineer bone membranes by using "bulk"-like methods are discussed, where different parameters to induce bone formation are disclosed in a way to have desirable structural and functional properties. Subsequently, the production of nanostructured membranes using a bottom-up approach is discussed by highlighting the main advances in the field of bone regeneration. Primordial importance is given to the promotion of osteoconductive and osteoinductive capability during the membrane design. Whenever possible, the films prepared using different techniques are compared in terms of handability, bone guiding ability, osteoinductivity, adequate mechanical properties, or biodegradability. A last chapter contemplates membranes only composed by cells, disclosing their potential to regenerate bone.

Advanced Materials for Health Monitoring with Skin-Based Wearable Devices

Skin-based wearable devices have a great potential that could result in a revolutionary approach to health monitoring and diagnosing disease. With continued innovation and intensive attention to the materials and fabrication technologies, development of these healthcare devices is progressively encouraged. This article gives a concise, although admittedly non-exhaustive, didactic review of some of the main concepts and approaches related to recent advances and developments in the scope of skin-based wearable devices (e.g. temperature, strain, biomarker-analysis werable devices, etc.), with an emphasis on emerging materials and fabrication techniques in the relevant fields. To give a comprehensive statement, part of the review presents and discusses different aspects of these advanced materials, such as the sensitivity, biocompatibility and durability as well as the major approaches proposed for enhancing their chemical and physical properties. A complementary section of the review linking these advanced materials with wearable device technologies is particularly specified. Some of the strong and weak points in development of each wearable material/device are highlighted and criticized. Several ideas regarding further improvement of skin-based wearable devices are also discussed.

Volatolomics of breath as an emerging frontier in pulmonary arterial hypertension

There is accumulating evidence in support of the significant improvement in survival rates and clinical outcomes when pulmonary arterial hypertension (PAH) is diagnosed at early stages. Nevertheless, it remains a major clinical challenge and the outcomes are dependent on invasive right heart catheterisation.

Resulting from pathophysiological processes and detectable in exhaled breath, volatile organic compounds (VOCs) have been proposed as noninvasive biomarkers for PAH. Studies have confirmed significant alterations of the exhaled VOCs among PAH patients when compared to controls and/or patients with other respiratory diseases. This suggests exhaled breath analysis as a potential noninvasive medical application in the field of PAH.

In this article, we review and discuss the progress made so far in the field of exhaled volatolomics (the omics of VOCs) as a potential noninvasive diagnostics of PAH. In addition, we propose a model including possible biochemical pathways on the level of the remodelled artery, in which specific VOCs could be detectable in exhaled breath during the early phases of PAH. We debate the different analytical approaches used and recommend a diagram including a “bottom–top” strategy, from basic to translational studies, required for promoting the field.

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

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

Programmed Nanoparticles for Tailoring the Detection of Inflammatory Bowel Diseases and Irritable Bowel Syndrome Disease via Breathprint

Chemical sensors based on programmable molecularly modified gold nanoparticles are tailored for the detection and discrimination between the breathprint of irritable bowel syndrome (IBS) and inflammatory bowel diseases (IBD). The sensors are examined in both lab- and real-world clinical conditions. The results reveal a discriminative power accuracy of 81% between IBD and IBS and 75% between Crohn's and Colitis states.

Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath

Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The best sensors obtained in the training set are then examined under real-world clinical conditions, using breath samples from 374 subjects. Analysis of the clinical samples show that the optimized SiNW FETs can detect and discriminate between almost all binary comparisons of the diseases under examination with >80% accuracy. Overall, this approach has the potential to support detection of many diseases in a direct harmless way, which can reassure patients and prevent numerous unpleasant investigations.

Self-Healable Sensors Based Nanoparticles for Detecting Physiological Markers via Skin and Breath: Toward Disease Prevention via Wearable Devices

Flexible and wearable electronic sensors are useful for the early diagnosis and monitoring of an individual's health state. Sampling of volatile organic compounds (VOCs) derived from human breath/skin or monitoring abrupt changes in heart-beat/breath rate should allow noninvasive monitoring of disease states at an early stage. Nevertheless, for many reported wearable sensing devices, interaction with the human body leads incidentally to unavoidable scratches and/or mechanical cuts and bring about malfunction of these devices. We now offer proof-of-concept of nanoparticle-based flexible sensor arrays with fascinating self-healing abilities. By integrating a self-healable polymer substrate with 5 kinds of functionalized gold nanoparticle films, a sensor array gives a fast self-healing (<3 h) and attractive healing efficiency in both the substrate and sensing films. The proposed platform was used in sensing pressure variation and 11 kinds of VOCs. The sensor array had satisfactory sensitivity, a low detection limit, and promising discrimination features in monitoring both of VOCs and pressure variation, even after full healing. These results presage a new type of smart sensing device, with a desirable performance in the possible detection and/or clinical application for a number of different purposes.

Exhaled Breath Analysis for Monitoring Response to Treatment in Advanced Lung Cancer

INTRODUCTION

The Response Evaluation Criteria in Solid Tumors (RECIST) serve as the accepted standard to monitor treatment efficacy in lung cancer. However, the time intervals between consecutive computerized tomography scans might be too long to allow early identification of treatment failure. This study examines the use of breath sampling to monitor responses to anticancer treatments in patients with advanced lung cancer.

METHODS

A total of 143 breath samples were collected from 39 patients with advanced lung cancer. The exhaled breath signature, determined by gas chromatography/mass spectrometry and a nanomaterial-based array of sensors, was correlated with the response to therapy assessed by RECIST: complete response, partial response, stable disease, or progressive disease.

RESULTS

Gas chromatography/mass spectrometry analysis identified three volatile organic compounds as significantly indicating disease control (PR/stable disease), with one of them also significantly discriminating PR/stable disease from progressive disease. The nanoarray had the ability to monitor changes in tumor response across therapy, also indicating any lack of further response to therapy. When one-sensor analysis was used, 59% of the follow-up samples were identified correctly. There was 85% success in monitoring disease control (stable disease/partial response).

CONCLUSION

Breath analysis, using mainly the nanoarray, may serve as a surrogate marker for the response to systemic therapy in lung cancer. As a monitoring tool, it can provide the oncologist with a quick bedside method of identifying a lack of response to an anticancer treatment. This may allow quicker recognition than does the current RECIST analysis. Early recognition of treatment failure could improve patient care.