Bioelectronic tongue: Current status and perspectives

A novel biomimetic electrochemical taste-biosensor based on conformational changes of the taste receptor

Taste sensor, a useful tool which could detect and identify thousands of different chemical substances in liquid environments, has attracted continuous concern from beverage and foodstuff industry and its consumers. Although many taste sensing methods have been extensively developed, the assessment of tastant content remains challenging due to the limitations of sensor selectivity and sensitivity. Here we present a novel biomimetic electrochemical taste-biosensor based on bioactive sensing elements and immune amplification with nanomaterials carrier to address above concerns, while taking sweet taste perception as a model. The proposed biosensor based on ligand binding domain (T1R2 VFT) of human sweet taste receptor protein showed human mimicking character and initiated the application of immune recognition in gustation biosensor, which can precisely and sensitively distinguish sweet substances against other related gustation substances with detection limit of 5.1 pM, far less than that of taste sensors without immune amplification whose detection limit was 0.48 nM. The performance test demonstrated the biosensor has the capacity of monitoring the response of sweet substances in real food environments, which is crucial in practical. This biomimetic electrochemical taste-biosensor can work as a new screening platform for newly developed tastants and disclose sweet perception mechanism.

Advances in Electrochemical Biosensors for the Detection of Common Oral Diseases

Limiting and preventing oral diseases remains a major challenge to the health of populations around the world, so finding ways to detect early-stage diseases (e.g., caries, periodontal disease, and oral cancer) and aiding in their prevention has always been an important clinical treatment concept. The development and application of electrochemical detection technology can provide important support for the early detection and non-invasive diagnosis of oral diseases and make up for the shortcomings of traditional diagnostic methods, which are highly sensitive, non-invasive, cost-effective, and less labor-intensive. It detects specific disease markers in body fluids through electrochemical reactions, discovers early warning signals of diseases, and realizes rapid and reliable diagnosis. This paper comprehensively summarizes the development and application of electrochemical biosensors in the detection and diagnosis of common oral diseases in terms of application platforms, sensing types, and disease detection, and discusses the challenges faced by electrochemical biosensors in the detection of oral diseases as well as the great prospects for future applications, in the hope of providing important insights for the future development of electrochemical biosensors for the early detection of oral diseases.

Gustation-Inspired Dual-Responsive Hydrogels for Taste Sensing Enabled by Machine Learning

Human gustatory system recognizes salty/sour or sweet tastants based on their different ionic or nonionic natures using two different signaling pathways. This suggests that evolution has selected this detection dualism favorably. Analogically, this work constructs herein bioinspired stimulus-responsive hydrogels to recognize model salty/sour or sweet tastes based on two different responses, that is, electrical and volumetric responsivities. Different compositions of zwitter-ionic sulfobetainic N-(3-sulfopropyl)-N-(methacryloxyethyl)-N,N-dimethylammonium betaine (DMAPS) and nonionic 2-hydroxyethyl methacrylate (HEMA) are co-polymerized to explore conditions for gelation. The hydrogel responses upon adding model tastant molecules are explored using electrical and visual de-swelling observations. Beyond challenging electrochemical impedance spectroscopy measurements, naive multimeter electrical characterizations are performed, toward facile applicability. Ionic model molecules, for example, sodium chloride and acetic acid, interact electrostatically with DMAPS groups, whereas nonionic molecules, for example, D(-)fructose, interact by hydrogen bonding with HEMA. The model tastants induce complex combinations of electrical and volumetric responses, which are then introduced as inputs for machine learning algorithms. The fidelity of such a trained dual response approach is tested for a more general taste identification. This work envisages that the facile dual electric/volumetric hydrogel responses combined with machine learning proposes a generic bioinspired avenue for future bionic designs of artificial taste recognition, amply needed in applications.

Bacteria-Infected Artificial Urine Characterization Based on a Combined Approach Using an Electronic Tongue Complemented with 1H-NMR and Flow Cytometry

The prevailing form of bacterial infection is within the urinary tract, encompassing a wide array of bacteria that harness the urinary metabolome for their growth. Through their metabolic actions, the chemical composition of the growth medium undergoes modifications as the bacteria metabolize urine compounds, leading to the subsequent release of metabolites. These changes can indirectly indicate the existence and proliferation of bacterial organisms. Here, we investigate the use of an electronic tongue, a powerful analytical instrument based on a combination of non-selective chemical sensors with a partial specificity for data gathering combined with principal component analysis, to distinguish between infected and non-infected artificial urine samples. Three prevalent bacteria found in urinary tract infections were investigated, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. Furthermore, the electronic tongue analysis was supplemented with 1H NMR spectroscopy and flow cytometry. Bacteria-specific changes in compound consumption allowed for a qualitative differentiation between artificial urine medium and bacterial growth.

Mimicking the Biological Sense of Taste In Vitro Using a Taste Organoids-on-a-Chip System

Thanks to the gustatory system, humans can experience the flavors in foods and drinks while avoiding the intake of some harmful substances. Although great advances in the fields of biotechnology, microfluidics, and nanotechnologies have been made in recent years, this astonishing recognition system can hardly be replaced by any artificial sensors designed so far. Here, taste organoids are coupled with an extracellular potential sensor array to form a novel bioelectronic organoid and developed a taste organoids-on-a-chip system (TOS) for highly mimicking the biological sense of taste ex vivo with high stability and repeatability. The taste organoids maintain key taste receptors expression after the third passage and high cell viability during 7 days of on-chip culture. Most importantly, the TOS not only distinguishs sour, sweet, bitter, and salt stimuli with great specificity, but also recognizes varying concentrations of the stimuli through an analytical method based on the extraction of signal features and principal component analysis. It is hoped that this bioelectronic tongue can facilitate studies in food quality controls, disease modelling, and drug screening.

Analysis of urine using electronic tongue towards non-invasive cancer diagnosis

Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.

Bioelectronic Tongues Mimicking Insect Taste Systems for Real-Time Discrimination between Natural and Artificial Sweeteners

A bioelectronic tongue (B-ET) mimicking insect taste systems is developed for the real-time detection and discrimination of natural and artificial sweeteners. Here, a carbon nanotube field-effect transistor (CNT-FET) was hybridized with nanovesicles including the honeybee sugar taste receptor, gustatory receptor 1 of Apis mellifera (AmGr1). This strategy allowed us to detect glucose, a major component of nectar, down to 100 fM in real time and identify sweet tastants from other tastants. It could also be utilized for the detection of glucose in dextrose tablet solutions. Importantly, we demonstrated the discrimination between natural and artificial sweeteners down to 10 pM even in real beverages such as decaffeinated coffee using our hybrid platform. In this respect, our B-ET mimicking insect taste systems can be a powerful tool for various applications such as food screening and basic studies on insect taste systems.

A Sensor Array Based on Molecularly Imprinted Polymers and Machine Learning for the Analysis of Fluoroquinolone Antibiotics

Fluoroquinolones (FQs) are one of the most important types of antibiotics in the clinical, poultry, and aquaculture industries, and their monitoring is required as the abuse has led to severe issues, such as antibiotic residues and antimicrobial resistance. In this study, we report a voltammetric electronic tongue (ET) for the simultaneous determination of ciprofloxacin, levofloxacin, and moxifloxacin in both pharmaceutical and biological samples. The ET comprises four sensors modified with three different customized molecularly imprinted polymers (MIPs) and a nonimprinted polymer integrated with Au nanoparticle-decorated multiwall carbon nanotubes (Au-fMWCNTs). MWCNTs were first functionalized to serve as a supporting substrate, while the anchored Au nanoparticles acted as a catalyst. Subsequently, MIP films were obtained by electropolymerization of pyrrole in the presence of the different target FQs. The sensors' morphology was characterized by scanning electron microscopy and transmission electron microscopy, while the modification process was followed electrochemically step by step employing [Fe(CN)₆]^3-/4- as the redox probe. Under the optimal conditions, the MIP(FQs)@Au-fMWCNT sensors exhibited different responses, limits of detection of ca. 1 μM, and a wide detection range up to 300 μM for the three FQs. Lastly, the developed ET presents satisfactory agreement between the expected and obtained values when used for the simultaneous determination of mixtures of the three FQs (R² ≥0.960, testing subset), which was also applied to the analysis of FQs in commercial pharmaceuticals and spiked human urine samples.

Antarctic aldehyde dehydrogenase from Flavobacterium PL002 as a potent catalyst for acetaldehyde determination in wine

Latest solutions in biotechnologies and biosensing targeted cold-active extremozymes. Analysis of acetaldehyde as a relevant quality indicator of wine is one example of application that could benefit from using low-temperatures operating catalysts. In search of novel aldehyde dehydrogenases (ALDH) with high stability and activity at low temperatures, the recombinant S2-ALDH from the Antarctic Flavobacterium PL002 was obtained by cloning and expression in Escherichia coli BL21(DE3). Structural and phylogenetic analyses revealed strong protein similarities (95%) with psychrophilic homologs, conserved active residues and structural elements conferring enzyme flexibility. Arrhenius plot revealed a conformational shift at 30 °C, favoring catalysis (low activation energy) at lower temperatures. In addition to a broad substrate specificity with preference for acetaldehyde (Km = 1.88 mM), this enzyme showed a high tolerance for ethanol (15%) and several salts and chelators (an advantage for wine analysis), while being sensitive to mercury (I₅₀ = 1.21 µM). The neutral optimal pH (7.5) and the stability up to 40 °C and after lyophilization represent major assets for developing S2-ALDH-based sensors. An enzymatic electrochemical assay was developed for acetaldehyde detection in wines with proven accuracy in comparison with the reference spectrophotometric method, thus evidencing the potential of S2-ALDH as effective biocatalyst for industry and biosensing.

Progress in the Development of Detection Strategies Based on Olfactory and Gustatory Biomimetic Biosensors

The biomimetic olfactory and gustatory biosensing devices have broad applications in many fields, such as industry, security, and biomedicine. The development of these biosensors was inspired by the organization of biological olfactory and gustatory systems. In this review, we summarized the most recent advances in the development of detection strategies for chemical sensing based on olfactory and gustatory biomimetic biosensors. First, sensing mechanisms and principles of olfaction and gustation are briefly introduced. Then, different biomimetic sensing detection strategies are outlined based on different sensing devices functionalized with various molecular and cellular components originating from natural olfactory and gustatory systems. Thereafter, various biomimetic olfactory and gustatory biosensors are introduced in detail by classifying and summarizing the detection strategies based on different sensing devices. Finally, the future directions and challenges of biomimetic biosensing development are proposed and discussed.

Electrochemical Signal Amplification Strategies and Their Use in Olfactory and Taste Evaluation

Biosensors are powerful analytical tools used to identify and detect target molecules. Electrochemical biosensors, which combine biosensing with electrochemical analysis techniques, are efficient analytical instruments that translate concentration signals into electrical signals, enabling the quantitative and qualitative analysis of target molecules. Electrochemical biosensors have been widely used in various fields of detection and analysis due to their high sensitivity, superior selectivity, quick reaction time, and inexpensive cost. However, the signal changes caused by interactions between a biological probe and a target molecule are very weak and difficult to capture directly by using detection instruments. Therefore, various signal amplification strategies have been proposed and developed to increase the accuracy and sensitivity of detection systems. This review serves as a reference for biosensor and detector research, as it introduces the research progress of electrochemical signal amplification strategies in olfactory and taste evaluation. It also discusses the latest signal amplification strategies currently being employed in electrochemical biosensors for nanomaterial development, enzyme labeling, and nucleic acid amplification techniques, and highlights the most recent work in using cell tissues as biosensitive elements.

Application and Progress of Chemometrics in Voltammetric Biosensing

The voltammetric electrochemical sensing method combined with biosensors and multi-sensor systems can quickly, accurately, and reliably analyze the concentration of the main analyte and the overall characteristics of complex samples. Simultaneously, the high-dimensional voltammogram contains the rich electrochemical features of the detected substances. Chemometric methods are important tools for mining valuable information from voltammetric data. Chemometrics can aid voltammetric biosensor calibration and multi-element detection in complex matrix conditions. This review introduces the voltammetric analysis techniques commonly used in the research of voltammetric biosensor and electronic tongues. Then, the research on optimizing voltammetric biosensor results using classical chemometrics is summarized. At the same time, the incorporation of machine learning and deep learning has brought new opportunities to further improve the detection performance of biosensors in complex samples. Finally, smartphones connected with miniaturized voltammetric biosensors and chemometric methods provide a high-quality portable analysis platform that shows great potential in point-of-care testing.

Current Advances and Future Aspects of Sweetener Synergy: Properties, Evaluation Methods and Molecular Mechanisms

Sweetener synergy is the phenomenon in which certain combinations of sweeteners work more effectively than the theoretical sum of the effects of each components. It provides benefits in reducing sweetener dosages and improving their sweetness. Many mixtures of sweeteners with synergistic effects have been reported up to now. Both artificial high-intensity sweeteners and natural sweeteners are popularly used in sweetener mixtures for synergism, although the former seem to display more potential to exhibit synergy than the latter. Furthermore, several evaluation methods to investigate sweetener synergy have been applied, which could lead to discrepancies in results. Moreover, structurally dissimilar sweeteners could cooperatively bind at the different sites in the sweet taste receptor T1R2/T1R3 to activate the receptor, and their hydration characters/packing characteristics in solvents could affect their interaction with the receptor, providing the preliminary explanations for the molecular basis of sweetener synergy. In this article, we firstly present a systematic review, analysis and comment on the properties, evaluation methods and molecular mechanisms of sweetener synergy. Secondly, challenges of sweetener synergy in both theory and practice and possible strategies to overcome these limitations are comprehensively discussed. Finally, future perspectives for this important performance in human sweet taste perception are proposed.

Biohybrid Tongue for Evaluation of Taste Interaction between Sweetness and Sourness

The past decade has witnessed tremendous progress achieved in taste research, while few studies focus on interactions among taste compounds. Indeed, sweeteners and acidulants are commonly used food additives, and sweet-sour mixtures always provide improved tastes. For example, sensory studies have shown that sourness suppresses sweetness. However, the degree of sweetness suppression by sourness is difficult to evaluate quantitatively and objectively. Therefore, we propose a biohybrid tongue that is constructed by integrating mammalian gustatory epithelium with a microelectrode array chip. The taste quality and intensity information is coded in time-frequency patterns of local field potential. Different response patterns evoked by sweet and sour stimuli are observed, and the response is dose-dependent. Then, interaction effects of sourness against sweetness are quantified. The results indicate that suppression of sweetness by sourness occurs by increasing sourness concentrations. In summary, this study provides a powerful new tool for quantitative evaluation of sweet, sour, and their binary taste interactions that mimic the mammalian taste system.

Self-healable and anti-freezing ion conducting hydrogel-based artificial bioelectronic tongue sensing toward astringent and bitter tastes

Numerous efforts have been attempted to mimic human tongue since years. However, they still have limitations because of damages, temperature effects, detection ranges etc. Herein, a self-healable hydrogel-based artificial bioelectronic tongue (E-tongue) containing mucin as a secreted protein, sodium chloride as an ion transporting electrolyte, and chitosan/poly(acrylamide-co-acrylic acid) as the main 3D structure holding hydrogel network is synthesized. This E-tongue is introduced to mimic astringent and bitter mouth feel based on cyclic voltammetry (CV) measurements subjected to target substances, which permits astringent tannic acid (TA) and bitter quinine sulfate (QS) to be detected over wide corresponding ranges of 29.3 mM-0.59 μM and 63.8 mM-6.38 μM with remarkable respective sensitivities of 0.2 and 0.12 wt%^-1. Besides, the taste selectivity of this E-tongue is performed in the presence of various mixed-taste chemicals to show its high selective behavior toward bitter and astringent chemicals. The electrical self-healability is shown via CV responses to illustrate electrical recovery within a short time span. In addition, cytotoxicity tests using HeLa cells are performed, where a clear viability of ≥95% verified its biocompatibility. The anti-freezing sensing of E-tongue tastes at -5 °C also makes this work to be useful at sub-zero environments. Real time degrees of tastes are detected using beverages and fruits to confirm future potential applications in food taste detections and humanoid robots.

Neurosensory Prosthetics: An Integral Neuromodulation Part of Bioelectronic Device

Bioelectronic medicines (BEMs) constitute a branch of bioelectronic devices (BEDs), which are a class of therapeutics that combine neuroscience with molecular biology, immunology, and engineering technologies. Thus, BEMs are the culmination of thought processes of scientists of varied fields and herald a new era in the treatment of chronic diseases. BEMs work on the principle of neuromodulation of nerve stimulation. Examples of BEMs based on neuromodulation are those that modify neural circuits through deep brain stimulation, vagal nerve stimulation, spinal nerve stimulation, and retinal and auditory implants. BEDs may also serve as diagnostic tools by mimicking human sensory systems. Two examples of in vitro BEDs used as diagnostic agents in biomedical applications based on in vivo neurosensory circuits are the bioelectronic nose and bioelectronic tongue. The review discusses the ever-growing application of BEDs to a wide variety of health conditions and practices to improve the quality of life.

Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.

Artificial Taste Buds: Bioorthogonally Ligated Gustatory-Neuronal Multicellular Hybrids Enabling Intercellular Taste Signal Transmission

Heterogeneous tissue models require the assembly and co-culture of multiple types of cells. Our recent work demonstrated taste signal transmission from gustatory cells to neurons by grafting single-stranded DNA into the cell membrane to construct multicellular assemblies. However, the weak DNA linkage and low grafting density allowed the formation of large gustatory cell self-aggregates that cannot communicate with neurons efficiently. This article presents the construction of artificial taste buds exhibiting active intercellular taste signal transmission through the hybridization of gustatory-neuronal multicellular interfaces using bioorthogonal click chemistry. Hybrid cell clusters were formed by the self-assembly of neonatal gustatory cells displaying tetrazine with a precultured embryonic hippocampal neuronal network displaying trans-cyclooctene. A bitter taste signal transduction was provoked in gustatory cells using denatonium benzoate and transmitted to neurons as monitored by intracellular calcium ion sensing. In the multicellular hybrids, the average number of signal transmissions was five to six peaks per cell, and the signal transmission lasted for ∼5 min with a signal-to-signal gap time of 10-40 s. The frequent and extended intercellular signal transmission suggests that the cell surface modification by the bioorthogonal click chemistry is a promising approach to fabricating functional multicellular hybrid clusters potentially useful for cell-based biosensors, toxicity assays, and tissue regeneration.

Hybrid Integrated Cardiomyocyte Biosensors for Bitter Detection and Cardiotoxicity Assessment

Among basic taste sensations, bitter taste is vital to the survival of mammals due to its indispensable role in toxin prediction or identification, so the identification of bitter compounds is of great value in the pharmaceutical and food industry. Recently, bitter taste receptor (T2Rs)-based biosensors have been developed for specific bitter detection. However, the taste biosensors based on taste cells/tissues suffer from simple function, low sensitivity, low content, and limited parameters. Here, to establish a high-content, highly sensitive, and multifunctional taste biosensor, we developed a multifunctional hybrid integrated cardiomyocyte biosensor (HICB) for bitter detection. Due to the expression of bitter taste receptors in cardiomyocytes, the HICB can recognize the specific bitter agonists by synchronously recording the extracellular field potential (EFP) and mechanical beating (MB) signals from the cultured cardiomyocytes in vitro. Multiple feature parameters were defined and extracted from the electromechanical signals of cardiomyocytes to analyze the specific responses to four typical bitter compounds. The radar map, heat map, and principal component analysis (PCA) were used to visualize and classify the specific responses. Moreover, bitter-induced cardiotoxicity also was chronically evaluated, and these bitter compounds presented an inhibition effect on the electrophysiological and contractile activities of cardiomyocytes. This high-content HICB offers an alternative platform for both bitter detection and cardiotoxicity assessment, showing promising applications in the fields of taste detection and toxicity screening.

Addressing the Selectivity of Enzyme Biosensors: Solutions and Perspectives

Enzymatic biosensors enjoy commercial success and are the subject of continued research efforts to widen their range of practical application. For these biosensors to reach their full potential, their selectivity challenges need to be addressed by comprehensive, solid approaches. This review discusses the status of enzymatic biosensors in achieving accurate and selective measurements via direct biocatalytic and inhibition-based detection, with a focus on electrochemical enzyme biosensors. Examples of practical solutions for tackling the activity and selectivity problems and preventing interferences from co-existing electroactive compounds in the samples are provided such as the use of permselective membranes, sentinel sensors and coupled multi-enzyme systems. The effect of activators, inhibitors or enzymatic substrates are also addressed by coupled enzymatic reactions and multi-sensor arrays combined with data interpretation via chemometrics. In addition to these more traditional approaches, the review discusses some ingenious recent approaches, detailing also on possible solutions involving the use of nanomaterials to ensuring the biosensors' selectivity. Overall, the examples presented illustrate the various tools available when developing enzyme biosensors for new applications and stress the necessity to more comprehensively investigate their selectivity and validate the biosensors versus standard analytical methods.

Bitter taste in silico: A review on virtual ligand screening and characterization methods for TAS2R-bitterant interactions

The growing pharmaceutical interest in the human bitter taste receptors (hTAS2Rs) has two dimensions; i) evaluation of the bitterness of active pharmaceutical compounds, in order to develop strategies for improving patients' adherence to medication, and ii) application of ligands for extra-cellular hTAS2Rs for potential preventive therapeutic achievements. The result is an increasing demand on robust tools for bitterness assessment and screening the receptor-ligand affinity. In silico tools are useful for aiding experimental-screening, as well as to elucide ligand-receptor interactions. In this review, the ligand-based and structure-based approaches are described as the two main in silico tools for bitter taste analysis. The strengths and weaknesses of each approach are discussed. Both approaches provide key tools for understanding and exploiting bitter taste for human health applications.

Cryopreservation of a cell-based biosensor chip modified with elastic polymer fibers enabling ready-to-use on-site applications

An efficient preservation of a cell-based biosensor chip to achieve a ready-to-use on-site system is still very challenging as the chip contains a living component such as adherent mammalian cells. Herein, we propose a strategy called on-sensor cryopreservation (OSC), which enables the adherent cells to be preserved by freezing (-80 °C) on a biosensor surface, such as the light-addressable potentiometric sensor (LAPS). Adherent cells on rigid surfaces are prone to cryo-injury; thus, the surface was modified to enhance the cell recovery for OSC. It relies on i) the integration of elastic electrospun fibers composed of polyethylene vinyl acetate (PEVA), which has a high thermal expansion coefficient and low glass-transition temperature, and ii) the treatment with O₂ plasma. The modified sensor is integrated into a microfluidic chip system not only to decrease the thermal mass, which is critical for fast thawing, but also to provide a precisely controlled micro-environment. This novel cryo-chip system is effective for keeping cells viable during OSC. As a proof-of-concept for the applicability of a ready-to-use format, the extracellular acidification of cancer cells (CHO-K1) was evaluated by differential LAPS measurements after thawing. Results show, for the first time, that the OSC strategy using the cryo-chip allows label-free and quantitative measurements directly after thawing, which eliminates additional post-thaw culturing steps. The freezing of the chips containing cells at the manufacturing stage and sending them via a cold-chain transport could open up a new possibility for a ready-to-use on-site system.

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.

Sensing Senses: Optical Biosensors to Study Gustation

The five basic taste modalities, sweet, bitter, umami, salty and sour induce changes of Ca²⁺ levels, pH and/or membrane potential in taste cells of the tongue and/or in neurons that convey and decode gustatory signals to the brain. Optical biosensors, which can be either synthetic dyes or genetically encoded proteins whose fluorescence spectra depend on levels of Ca²⁺, pH or membrane potential, have been used in primary cells/tissues or in recombinant systems to study taste-related intra- and intercellular signaling mechanisms or to discover new ligands. Taste-evoked responses were measured by microscopy achieving high spatial and temporal resolution, while plate readers were employed for higher throughput screening. Here, these approaches making use of fluorescent optical biosensors to investigate specific taste-related questions or to screen new agonists/antagonists for the different taste modalities were reviewed systematically. Furthermore, in the context of recent developments in genetically encoded sensors, 3D cultures and imaging technologies, we propose new feasible approaches for studying taste physiology and for compound screening.