Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Advancements in Cerebrospinal Fluid Biosensors: Bridging the Gap from Early Diagnosis to the Detection of Rare Diseases

Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of central nervous system (CNS) damage or neurodegenerative disease, regardless of their age range. Hence, this can be a very painful procedure, especially in infants and elderly patients. On the other hand, the detection of disease biomarkers in CSF makes diagnoses as accurate as possible. This review aims to explore novel electrochemical biosensing platforms that have impacted biomedical science. Biosensors have emerged as techniques to accelerate the detection of known biomarkers in body fluids such as CSF. Biosensors can be designed and modified in various ways and shapes according to their ultimate applications to detect and quantify biomarkers of interest. This process can also significantly influence the detection and diagnosis of CSF. Hence, it is important to understand the role of this technology in the rapidly progressing field of biomedical science.

Nanoporous MoS2 Field-Effect Transistor Based Artificial Olfaction: Achieving Enhanced Volatile Organic Compound Detection Inspired by the Drosophila Olfactory System

Olfaction, a primal and effective sense, profoundly impacts our emotions and instincts. This sensory system plays a crucial role in detecting volatile organic compounds (VOCs) and realizing the chemical environment. Animals possess superior olfactory systems compared to humans. Thus, taking inspiration from nature, artificial olfaction aims to achieve a similar level of excellence in VOC detection. In this study, we present the development of an artificial olfaction sensor utilizing a nanostructured bio-field-effect transistor (bio-FET) based on transition metal dichalcogenides and the Drosophila odor-binding protein LUSH. To create an effective sensing platform, we prepared a hexagonal nanoporous structure of molybdenum disulfide (MoS2) using block copolymer lithography and selective etching techniques. This structure provides plenty of active sites for the integration of the LUSH protein, enabling enhanced binding with ethanol (EtOH) for detection purposes. The coupling of the biomolecule with EtOH influences the bio-FETs potential, which generates indicative electrical signals. By mimicking the sniffing techniques observed in Drosophila, these bio-FETs exhibit an impressive limit of detection of 10-6% for EtOH, with high selectivity, sensitivity, and detection ability even in realistic environments. This bioelectric sensor demonstrates substantial potential in the field of artificial olfaction, offering advancements in VOC detection.

Volatile organic compounds from human skin as biomarkers of menstruation phase and severity of premenstrual syndrome: An exploratory pilot study

Background and aim

Numerous women of reproductive age experience physical or mental discomfort during their natural menstrual cycle due to paramenstrual symptoms, such as premenstrual syndrome (PMS). To date, there is no established biomarker for the diagnosis of PMS. This study investigated the relationship between skin gas composition and menstruation cycles, and evaluated the possibility of skin gas composition as a biomarker of paramenstrual symptoms.

Methods

We conducted an exploratory pilot study. Healthy Japanese women (aged 20-29 years) underwent blood and skin gas analyses on 1 day corresponding to menstruation, preovulatory, middle luteal, and late luteal phases. Skin gas was collected from the cubital fossa and armpit using a Passive Flux Sampler; samples were analyzed for 65 volatile organic compounds (VOCs) by gas chromatography-mass spectrometry (GC-MS). Non-parametric statistical analysis was performed to identify VOCs related to the menstrual cycle, levels of female hormones, and severity of PMS.

Results

Fourteen women participated; of those, 12 completed the study. Regarding the relationship with the menstrual cycles, seven and four VOCs were significantly and marginally changed, respectively, at the cubital fossa during menstruation. Of those 11 compounds, 10 were also correlated with the levels of serum female hormones. At the armpit, five and three compounds were significantly and marginally changed, respectively, during menstruation. Of those eight compounds, five were also correlated with the levels of serum female hormones. In the study of PMS severity, analysis of the changes in VOCs suggested that ketones and fatty acids are increased during menstruation in the severe PMS group versus the mild PMS group.

Conclusions

The results of this study suggest that certain VOCs emitted in skin gas related to the menstrual cycle, levels of female hormones, and severity of PMS. These findings may advance the metabolic understanding and development of diagnostic biomarkers for menstruation-related symptoms.

Raman spectroscopy-based biomarker screening by studying the fingerprint and lipid characteristics of Polycythemıa Vera cases blood serum

This study aimed to develop a novel approach for diagnosing Polycythemia Vera (PV), a stem cell-derived neoplasm of the myeloid lineage. The approach utilized Raman spectroscopy coupled with multivariate analysis to analyze blood serum samples collected from PV patients. The results showed that PV serum exhibited lower protein and lipid levels and structural changes in the functional groups that comprise proteins and lipids. The study also demonstrated differences in lipid biosynthesis and protein levels in PV serum. Using the Partial Least Square Discriminant Analysis (PLS-DA) model, Raman-based multivariate analysis achieved high accuracy rates of 96.49% and 93.04% in the training sets and 93.10% and 89.66% in the test sets for the 800-1800 cm-1 and 2700-3000 cm-1 ranges, respectively. The area under the curve (AUC) values of the test datasets were calculated as 0.92 and 0.89 in the 800-1800 cm-1 and 2700-3000 cm-1 spectral regions, respectively, demonstrating the effectiveness of the PLS-DA models for the diagnosis of PV. This study highlights the potential of Raman spectroscopy-based analysis in the early and accurate diagnosis of PV, enabling the application of effective treatment strategies.

Electronic Nose and Tongue for Assessing Human Microbiota

The technological developments of recent times have allowed the use of innovative approaches to support the diagnosis of various diseases. Many of such clinical conditions are often associated with metabolic unbalance, in turn producing an alteration of the gut microbiota even during asymptomatic stages. As such, studies regarding the microbiota composition in biological fluids obtained by humans are continuously growing, and the methodologies for their investigation are rapidly changing, making it less invasive and more affordable. To this extent, Electronic Nose and Electronic Tongue tools are gaining importance in the relevant field, making them a useful alternative—or support—to traditional analytical methods. In light of this, the present manuscript seeks to investigate the development and use of such tools in the gut microbiota assessment according to the current literature. Significant gaps are still present, particularly concerning the Electronic Tongue systems, however the current evidence highlights the strong potential such tools own to enter the daily clinical practice, with significant advancement concerning the patients’ acceptability and cost saving for healthcare providers.

Electrical and Electrochemical Sensors Based on Carbon Nanotubes for the Monitoring of Chemicals in Water-A Review

Carbon nanotubes (CNTs) combine high electrical conductivity with high surface area and chemical stability, which makes them very promising for chemical sensing. While water quality monitoring has particularly strong societal and environmental impacts, a lot of critical sensing needs remain unmet by commercial technologies. In the present review, we show across 20 water monitoring analytes and 90 references that carbon nanotube-based electrochemical sensors, chemistors and field-effect transistors (chemFET) can meet these needs. A set of 126 additional references provide context and supporting information. After introducing water quality monitoring challenges, the general operation and fabrication principles of CNT water quality sensors are summarized. They are sorted by target analytes (pH, micronutrients and metal ions, nitrogen, hardness, dissolved oxygen, disinfectants, sulfur and miscellaneous) and compared in terms of performances (limit of detection, sensitivity and detection range) and functionalization strategies. For each analyte, the references with best performances are discussed. Overall, the most frequently investigated analytes are H+ (pH) and lead (with 18% of references each), then cadmium (14%) and nitrite (11%). Micronutrients and toxic metals cover 40% of all references. Electrochemical sensors (73%) have been more investigated than chemistors (14%) or FETs (12%). Limits of detection in the ppt range have been reached, for instance Cu(II) detection with a liquid-gated chemFET using SWCNT functionalized with peptide-enhanced polyaniline or Pb(II) detection with stripping voltammetry using MWCNT functionalized with ionic liquid-dithizone based bucky-gel. The large majority of reports address functionalized CNTs (82%) instead of pristine or carboxyl-functionalized CNTs. For analytes where comparison is possible, FET-based and electrochemical transduction yield better performances than chemistors (Cu(II), Hg(II), Ca(II), H2O2); non-functionalized CNTs may yield better performances than functionalized ones (Zn(II), pH and chlorine).

Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring

Collecting and analyzing data from sensors embedded in the context of daily life has been widely employed for the monitoring of mental health. Variations in parameters such as movement, sleep duration, heart rate, electrocardiogram, skin temperature, etc., are often associated with psychiatric disorders. Namely, accelerometer data, microphone, and call logs can be utilized to identify voice features and social activities indicative of depressive symptoms, and physiological factors such as heart rate and skin conductance can be used to detect stress and anxiety disorders. Therefore, a wide range of devices comprising a variety of sensors have been developed to capture these physiological and behavioral data and translate them into phenotypes and states related to mental health. Such systems aim to identify behaviors that are the consequence of an underlying physiological alteration, and hence, the raw sensor data are captured and converted into features that are used to define behavioral markers, often through machine learning. However, due to the complexity of passive data, these relationships are not simple and need to be well-established. Furthermore, parameters such as intrapersonal and interpersonal differences need to be considered when interpreting the data. Altogether, combining practical mobile and wearable systems with the right data analysis algorithms can provide a useful tool for the monitoring and management of mental disorders. The current review aims to comprehensively present and critically discuss all available smartphone-based, wearable, and environmental sensors for detecting such parameters in relation to the treatment and/or management of the most common mental health conditions.

An Update on the Use of Exhaled Breath Analysis for the Early Detection of Lung Cancer

Lung cancer has historically been the main responsible for cancer associated deaths. Owing to this is our current inability to screen for and diagnose early pathological findings, preventing us from a timely intervention when cure is still achievable. Over the last decade, together with the extraordinary progress in therapeutical alternatives in the field, there has been an ongoing search for a biomarker that would allow for this. Numerous technologies have been developed but their clinical application is yet to come. In this review, we provide an update on volatile organic compounds, a non-invasive method that can hold the key for detecting early metabolic pathway changes in carcinogenesis. For its compilation, web-based search engines of scientific literature such as PubMed were explored and reviewed, using articles, research, and papers deemed meaningful by authors discretion. After a brief description, we depict how this technique can complement current methods and present the value of electronic noses in the identification of the “breathprint”. Lastly, we bring some of the latest updates in the field together with the current limitations and final remarks.

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.

Volatile organic compounds as disease predictors in newborn infants: a systematic review

Volatile organic compounds (VOC) detected in human breath, urine, stool, sweat, saliva, and blood result from metabolic processes in the body during health or disease. Using sophisticated measurement systems, small amounts of these compounds can be detected in the above bodily fluids. Multiple studies in adults and children have shown the potential of these compounds to differentiate between healthy individuals and patients by detecting profiles of compounds in non-invasively collected samples. However, the detection of biomarkers in VOCs from neonates is particularly attractive due to the non-invasive nature of its approach, and its ability to track disease progress by longitudinal sampling. In this work we have reviewed the literature on the use of VOCs in neonates and identified areas for future work.

Multisensor Systems and Arrays for Medical Applications Employing Naturally-Occurring Compounds and Materials

The significant improvement of quality of life achieved over the last decades has stimulated the development of new approaches in medicine to take into account the personal needs of each patient. Precision medicine, providing healthcare customization, opens new horizons in the diagnosis, treatment and prevention of numerous diseases. As a consequence, there is a growing demand for novel analytical devices and methods capable of addressing the challenges of precision medicine. For example, various types of sensors or their arrays are highly suitable for simultaneous monitoring of multiple analytes in complex biological media in order to obtain more information about the health status of a patient or to follow the treatment process. Besides, the development of sustainable sensors based on natural chemicals allows reducing their environmental impact. This review is concerned with the application of such analytical platforms in various areas of medicine: analysis of body fluids, wearable sensors, drug manufacturing and screening. The importance and role of naturally-occurring compounds in the development of electrochemical multisensor systems and arrays are discussed.

Cross-Reactive, Self-Encoded Polymer Film Arrays for Sensor Applications

The development of chemical sensors continues to be an active area of research, especially the development of a practical electronic nose. Here, we present a spectroscopic chemical sensor based on an array of 64 self-encoded polymer films deposited on a microfabricated silicon substrate. The polymer arrays were analyzed by FTIR and Raman spectroscopy before and after exposure to a series of organic volatiles to monitor changes in their vibrational fingerprints. We show here that the spectroscopic changes of self-encoded polymer films can be used to distinguish between volatile organic analytes. Changes induced in the sensor arrays by the analyte vapor were denoted by a spectroscopic response of the self-encoded polymer sensors and transformed into a response pattern by multivariate data analysis using partial least squares regression. The results indicated that the polymer sensors provide a unique and reproducible pattern for each analyte vapor and can potentially be used in the fabrication of a novel electronic nose device.

A review of breath analysis techniques in head and neck cancer

Cancers of the head and neck region are a severely disabling group of diseases with no method for early detection. Analysis of exhaled breath volatile organic compounds shows promise as biomarkers for early detection and disease monitoring. This article reviews breath analysis in the setting of head and neck cancer, with a practical focus on breath sampling techniques, detection technologies and valid data analysis methods. Title and abstract keyword searches were conducted on PubMed and Embase databases to identify English language studies without a time-period limitation. The main inclusion criteria were human studies comparing head and neck cancer patients to healthy controls using exhaled breath analysis. Multiple breath collection techniques, three major detection technologies and multiple data analysis methods were identified. However, the variability in techniques and lack of methodological standardization does not allow for adequate study replication or data pooling. Twenty-two volatile organic compounds identified in five studies have been reported to discriminate head and neck cancer patients from healthy controls. Breath analysis for detection of head and neck cancer shows promise as a non-invasive detection tool. However, methodological standardization is paramount for future research study design to provide the potential for translating these techniques into routine clinical use.

Critical Evaluation of Laboratory Potentiometric Electronic Tongues for Pharmaceutical Analysis-An Overview

Electronic tongue systems equipped with cross-sensitive potentiometric sensors have been applied to pharmaceutical analysis, due to the possibility of various applications and developing new formulations. Many studies already proved the complementarity between the electronic tongue and classical analysis such as dissolution tests indicated by Pharmacopeias. However, as a new approach to study pharmaceuticals, electronic tongues lack strict testing protocols and specification limits; therefore, their results can be improperly interpreted and inconsistent with the reference studies. Therefore, all aspects of the development, measurement conditions, data analysis, and interpretation of electronic tongue results were discussed in this overview. The critical evaluation of the effectiveness and reliability of constructed devices may be helpful for a better understanding of electronic tongue systems development and for providing strict testing protocols.

Differentiation between infected and non-infected wounds using an electronic nose

OBJECTIVES

The aim of this study was to explore whether an electronic nose, Aetholab, is able to discriminate between infected versus non-infected wounds, based on headspace analyses from wound swabs.

METHODS

A total of 77 patients participated in this pilot study. Each wound was assessed for infection based on clinical judgment. Additionally, two wound swabs were taken, one for microbiological culture and one for measurement with Aetholab. Diagnostic properties with 95% confidence intervals (95%CIs) of Aetholab were calculated with clinical judgment and microbiological culture results as reference standards.

RESULTS

With clinical judgment as reference standard, Aetholab had a sensitivity of 91% (95%CI 76-98) and a specificity of 71% (95%CI 55-84). Diagnostic properties were somewhat lower when microbiological culture results were used as reference standard: sensitivity 81% (95%CI 64-91), specificity 63% (95%CI 46-77).

CONCLUSIONS

Aetholab seems a promising diagnostic tool for wound infection given the diagnostic properties presented in this pilot study. A larger study is needed to confirm our results.

Integration of a field effect transistor-based aptasensor under a hydrophobic membrane for bioelectronic nose applications

A new bioelectronic nose based on a field effect transistor coupled with an aptamer as the sensing element was developed. The gas-to-liquid extraction interface required for appropriate aptamer function was integrated into standard CMOS technology. It was developed with the use of a sacrificial aluminium etching technique combined with surface modifications by silanes for wettability control. As a proof of concept, aptamer Van74 for vanillin was immobilized on the sensitive surface of the ISFET. The developed microsystem can selectively detect vanillin vapor in a concentration range from 2.7 ppt to 0.3 ppm, with a detection limit of 2.7 ppt. The sensor was able to detect vanillin in a gas sample obtained from roasted coffee beans. This outcome provides a foundation for developing a new generation of bioelectronic noses for the detection and discrimination of volatile compounds.

Thermally Driven Selective Nanocomposite PS-PHB/MGC Nanofibrous Conductive Sensor for Air Pollutant Detection

The potentials to use the working temperature to tune both the sensitivity and the selectivity of a chemical sensor based on a nanostructured and nanocomposite polymer layer have been investigated and described. Thus, in a single step, a peculiar chemical layer was grown up onto IDE (Interdigitated Electrode) microtransducers by electrospinning deposition and using a single-needle strategy. The 3-component nanofibers, obtained from a mixture of polystyrene and polyhydroxibutyrate (insulating thermoplastics) and a known concentration of mesoporous graphitized carbon nanopowder, appeared highly rough on the surface and decorated with jagged islands but homogeneous in shape and diameter, with the nanofillers aggregated into clusters more or less densely packed through the fibers. The resulting sensor was conductive at room temperature and could work between 40 and 80°C without any apparent degradation. As the fibrous sensing layer was heated, the current increased and the sensitivity to some classes of VOCs such as an oxidizing gas drastically changed depending on the working temperature. More in detail, the sensor resulted highly sensitive and selective to acetic acid at 40°C but the sensitivity fell down, decreasing by 96%, when the sensor operated at 80°C. On the other hand, although an increase in temperature caused a general decrease in sensitivity to the tested VOCs (with a maximum of 14, 81, and 78% for amine, acetone and toluene, respectively) and water vapors (with a maximum of 55%), higher temperature affected only slightly the amine permeation, thus modifying the partial selectivity of the sensor to these chemicals. Conversely, when the operating temperature increased, the sensitivity to the detected gas, NO2, increased too, reporting a ~2 ppb limit of detection (LOD), thus confirming that the temperature was able to drive the selectivity of nanocomposite polymeric sensors.

Protein- and Peptide-Based Biosensors in Artificial Olfaction

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.