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.

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.

Rationale: Pulmonary arterial hypertension is a severe lethal cardiopulmonary disease. Loss of function mutations in KCNK3 (potassium channel subfamily K member 3) gene, which encodes an outward rectifier K + channel, have been identified in pulmonary arterial hypertension patients. Objective: We have demonstrated that KCNK3 dysfunction is common to heritable and nonheritable pulmonary arterial hypertension and to experimental pulmonary hypertension (PH). Finally, KCNK3 is not functional in mouse pulmonary vasculature. Methods and Results: Using CRISPR/Cas9 technology, we generated a 94 bp out of frame deletion in exon 1 of Kcnk3 gene and characterized these rats at the electrophysiological, echocardiographic, hemodynamic, morphological, cellular, and molecular levels to decipher the cellular mechanisms associated with loss of KCNK3. Using patch-clamp technique, we validated our transgenic strategy by demonstrating the absence of KCNK3 current in freshly isolated pulmonary arterial smooth muscle cells from Kcnk3 -mutated rats. At 4 months of age, echocardiographic parameters revealed shortening of the pulmonary artery acceleration time associated with elevation of the right ventricular systolic pressure. Kcnk3 -mutated rats developed more severe PH than wild-type rats after monocrotaline exposure or chronic hypoxia exposure. Kcnk3 -mutation induced a lung distal neomuscularization and perivascular extracellular matrix activation. Lungs of Kcnk3 -mutated rats were characterized by overactivation of ERK1/2 (extracellular signal–regulated kinase1-/2), AKT (protein kinase B), SRC, and overexpression of HIF1-α (hypoxia-inducible factor-1 α), survivin, and VWF (Von Willebrand factor). Linked with plasma membrane depolarization, reduced endothelial-NOS expression and desensitization of endothelial-derived hyperpolarizing factor, Kcnk3 -mutated rats presented predisposition to vasoconstriction of pulmonary arteries and a severe loss of sildenafil-induced pulmonary arteries relaxation. Moreover, we showed strong alteration of right ventricular cardiomyocyte excitability. Finally, Kcnk3 -mutated rats developed age-dependent PH associated with low serum-albumin concentration. Conclusions: We established the first Kcnk3 -mutated rat model of PH. Our results confirm that KCNK3 loss of function is a key event in pulmonary arterial hypertension pathogenesis. This model presents new opportunities for understanding the initiating mechanisms of PH and testing biologically relevant therapeutic molecules in the context of PH.

The recognition of volatile organic compounds in breath samples is a promising approach for noninvasive safe diagnosis of disease. Spectrometry and spectroscopy methods used for breath analysis suffer from suboptimal accuracy, are expensive and are unsuitable for diagnostics. This article presents a concise review on arrays of monolayer-capped gold nanoparticle (GNP) sensors in conjugation with pattern recognition methods for cost-effective, fast and high-throughput point-of-care diagnostic results from exhaled breath samples. The article starts with a general introduction to the rationale and advantages of breath analysis as well as with a presentation of the utility of monolayer-capped GNP sensors in this field. The article continues with a presentation of the main fabrication and operation principles of these GNP sensors and concludes with selected examples regarding their utility in different fields of medicine, particularly in neurology, infectiology, respiratory medicine and oncology.

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These results reveal a dysregulation of the glutamate-NMDAR axis in the pulmonary arteries of patients with PAH and identify vascular NMDARs as targets for antiremodeling treatments in PAH.

The ante-mortem diagnosis of Parkinson's disease (PD) still relies on clinical symptoms. Biomarkers could in principle be used for the early detection of PD-related neuronal damage, but no validated, inexpensive, and simple biomarkers are available yet. Here we report on the breath-print of presymptomatic PD in rats, using a model with 50% lesion of dopaminergic neurons in substantia nigra. Exhaled breath was collected from 19 rats (10 lesioned and 9 sham operated) and analyzed using organically functionalized carbon nanotube sensors. Discriminant factor analysis detected statistically significant differences between the study groups and a classification accuracy of 90% was achieved using leave-one-out cross-validation. The sensors' breath-print was supported by determining statistically significant differences of several volatile organic compounds in the breath of the lesioned rats and the sham operated rats, using gas chromatography combined with mass spectrometry. The observed breath-print shows potential for cost-effective, fast, and reliable early PD detection.

Breath research has almost invariably focussed on the identification of endogenous volatile organic compounds (VOCs) as disease biomarkers. After five decades, a very limited number of breath tests measuring endogenous VOCs is applied to the clinic. In this perspective article, we explore some of the factors that may have contributed to the current lack of clinical applications of breath endogenous VOCs. We discuss potential pitfalls of experimental design, analytical challenges, as well as considerations regarding the biochemical pathways that may impinge on the application of endogenous VOCs as specific disease biomarkers. We point towards several lines of evidence showing that breath analysis based on administration of exogenous compounds has been a more successful strategy, with several tests currently applied to the clinic, compared to measurement of endogenous VOCs. Finally, we propose a novel approach, based on the use of exogenous VOC (EVOC) probes as potential strategy to measure the activity of metabolic enzymes in vivo, as well as the function of organs, through breath analysis. We present longitudinal data showing the potential of EVOC probe strategies in breath analysis. We also gathered important data showing that administration of EVOC probes induces significant changes compared to previous exposures to the same compounds. EVOC strategies could herald a new wave of substrate-based breath tests, potentially bridging the gap between research tools and clinical applications.