Advances in the Electronics for Cyclic Voltammetry: the Case of Gas Detection by Using Microfabricated Electrodes

Cortisol Monitoring Devices toward Implementation for Clinically Relevant Biosensing In Vivo

Cortisol is a steroid hormone that regulates energy metabolism, stress reactions, and immune response. Cortisol is produced in the kidneys' adrenal cortex. Its levels in the circulatory system are regulated by the neuroendocrine system with a negative feedback loop of the hypothalamic-pituitary-adrenal axis (HPA-axis) following circadian rhythm. Conditions associated with HPA-axis disruption cause deteriorative effects on human life quality in numerous ways. Psychiatric, cardiovascular, and metabolic disorders as well as a variety of inflammatory processes accompanying age-related, orphan, and many other conditions are associated with altered cortisol secretion rates and inadequate responses. Laboratory measurements of cortisol are well-developed and based mainly on the enzyme linked immunosorbent assay (ELISA). There is a great demand for a continuous real-time cortisol sensor that is yet to be developed. Recent advances in approaches that will eventually culminate in such sensors have been summarized in several reviews. This review compares different platforms for direct cortisol measurements in biological fluids. The ways to achieve continuous cortisol measurements are discussed. A cortisol monitoring device will be essential for personified pharmacological correction of the HPA-axis toward normal cortisol levels through a 24-h cycle.

Microsystem Nodes for Soil Monitoring via an Energy Mapping Network: A Proof-of-Concept Preliminary Study

The need for accurate information and the availability of novel tool and technological advances in agriculture have given rise to innovative autonomous systems. The aim is to monitor key parameters for optimal water and fertilizer management. A key issue in precision agriculture is the in situ monitoring of soil macronutrients. Here, a proof-of-concept study was conducted that tested two types of sensors capable of capturing both the electrochemical response of the soil and the electrical potential generated by the interaction between the soil and plants. These two sensors can be used to monitor large areas using a network approach, due to their small size and low power consumption. The voltammetric sensor (BIONOTE-L) proved to be able to characterize different soil samples. It was able, indeed, to provide a reproducible voltammetric fingerprint specific for each soil type, and to monitor the concentration of CaCl2 and NaCl in the soil. BIONOTE-L can be coupled to a device capable of capturing the energy produced by interactions between plants and soil. As a consequence, the functionality of the microsystem node when applied in a large-area monitoring network can be extended. Additional calibrations will be performed to fully characterize the instrument node, to implement the network, and to specialize it for a particular application in the field.

Biosensors for Detection and Monitoring of Joint Infections

The aim of this review is to assess the use of biosensors in the diagnosis and monitoring of joint infection (JI). JI is worldwide considered a significant cause of morbidity and mortality in developed countries. Due to the progressive ageing of the global population, the request for joint replacement increases, with a significant rise in the risk of periprosthetic joint infection (PJI). Nowadays, the diagnosis of JI is based on clinical and radiological findings. Nuclear imaging studies are an option but are not cost-effective. Serum inflammatory markers and the analysis of the aspirated synovial fluid are required to confirm the diagnosis. However, a quick and accurate diagnosis of JI may remain elusive as no rapid and highly accurate diagnostic method was validated. A comprehensive search on Medline, EMBASE, Scopus, CINAH, CENTRAL, Google Scholar, and Web of Science was conducted from the inception to June 2021. The PRISMA guidelines were used to improve the reporting of the review. The MINORS was used for quality assessment. From a total of 155 studies identified, only four articles were eligible for this study. The main advantages of biosensors reported were accuracy and capability to detect bacteria also in negative culture cases. Otherwise, due to the few studies and the low level of evidence of the papers included, it was impossible to find significant results. Therefore, further high-quality studies are required.

Design of an Innovative Methodology for Cerebrospinal Fluid Analysis: Preliminary Results

Cerebrospinal fluid (CSF) analysis supports diagnosis of neurodegenerative diseases (NDs), however a number of issues limits its potentialities in clinical practice. Here, a newly developed technique for fluid voltammetry, relying on a simple sensor (BIOsensor-based multisensorial system for mimicking Nose, Tongue and Eyes, BIONOTE), was used to test the applicability for CSF analysis. BIONOTE was initially calibrated on an artificial CSF-like solution and then applied on human CSF, either immediately after collection or after refrigerated storage. Following optimization, it was used to evaluate 11 CSF samples correlating the electrochemical dataset with CSF routine parameters and biomarkers of neurodegeneration. Multivariate data analysis was performed for model elaboration and calibration using principal component analysis and partial least squares discriminant analysis. BIONOTE presented a high capacity to predict both physiological and pathological constituents of artificial CSF. It differentiated distinct fresh human CSF samples well but lost accuracy after refrigerated storage. The electrochemical analysis-derived data correlated with either CSF routine cytochemical indexes or a biomarker of neurodegeneration. BIONOTE resulted as being a reliable system for electrochemical analysis of CSF. The CSF fingerprint provided by the sensor has shown itself to be sensitive to CSF modification, thus it is potentially representative of CSF alteration. This result opens the way to its testing in further study addressed at assessing the clinical relevance of the methodology. Because of its advantages due to the ease and rapidity of the methodology, a validation study is now required to translate the technique into clinical practice and improve diagnostic workup of NDs.

A Wearable Low-Power Sensing Platform for Environmental and Health Monitoring: The Convergence Project

The low-power sensing platform proposed by the Convergence project is foreseen as a wireless, low-power and multifunctional wearable system empowered by energy-efficient technologies. This will allow meeting the strict demands of life-style and healthcare applications in terms of autonomy for quasi-continuous collection of data for early-detection strategies. The system is compatible with different kinds of sensors, able to monitor not only health indicators of individual person (physical activity, core body temperature and biomarkers) but also the environment with chemical composition of the ambient air (NOx, COx, NHx particles) returning meaningful information on his/her exposure to dangerous (safety) or pollutant agents. In this article, we introduce the specifications and the design of the low-power sensing platform and the different sensors developed in the project, with a particular focus on pollutant sensing capabilities and specifically on NO2 sensor based on graphene and CO sensor based on polyaniline ink.

A Second-Generation Voltage-Conveyor-Based Interface for Ultrasonic PVDF Sensors

Exploiting the transmission and reception of low frequency ultrasounds in air is often associated with the innate echolocating abilities of some mammals, later emulated with sophisticated electronic systems, to obtain information about unstructured environments. Here, we present a novel approach for the reception of ultrasounds in air, which exploits a piezopolymer broadband sensor and an electronic interface based on a second-generation voltage conveyor (VCII). Taking advantage of its capability to manipulate both voltage and current signals, in this paper, we propose an extremely simple interface that presents a sensitivity level of about −100 dB, which is in line with commercially available references. The presented results are obtained without any filtration stage. The second-generation voltage conveyor active device is implemented through a commercially available AD844, with a supply voltage of ±15 V.

Voltammetric analysis for distinguishing portal hypertension-related from malignancy-related ascites: A proof of concept study

Background

Serum-ascites albumin gradient (SAAG) remains the most sensitive and specific marker for the differentiation of ascites due to portal hypertension from ascites due to other causes. SAAG has some limitations and may fail in selected conditions. Voltammetric analysis (VA) has been used for the detection of electroactive species of biological significance and has proven effective for detection infections in biological fluids.

Aims

In this study, we compared the accuracy of voltammetric analysis (VA) with that of SAAG to differentiate ascites due to portal hypertension from that having a different origin.

Methods

80 ascites samples were obtained from patients undergoing paracentesis at the Campus Bio-Medico Hospital of Rome. VA was performed using the BIONOTE device. The ability of VA to discriminate ascitic fluid etiology and biochemical parameters was evaluated using Partial Least Square Discriminant Analysis (PLS-DA), with ten-fold cross-validations.

Results

Mean age was 68.6 years (SD 12.5), 58% were male. Ascites was secondary to only portal hypertension in 72.5% of cases (58 subjects) and it was secondary to a baseline neoplastic disease in 27.5% of cases (22 subjects). Compared to SAAG≥1.1, e-tongue predicted ascites from portal hypertension with a better accuracy (92.5% Vs 87.5%); sensitivity (98.3% Vs 94.8%); specificity (77.3% Vs 68.2%); predictive values (PPV 91.9% Vs 88.7% and NPV 94.4% Vs 83.3%). VA correctly classified ascites etiology in 57/58 (98.2%) of cases with portal hypertension and in 17/22 (77.2%) of cases with malignancy. Instead, VA showed poor predictive capacities towards total white blood count and polymorphonuclear cell count.

Conclusions

According to this proof of concept study, VA qualifies as a promising low-cost and easy method to discriminate between ascites secondary to portal hypertension and ascites due to malignancy.

A Sensor Platform for Athletes' Training Supervision: A Proof of Concept Study

One of the basic needs of professional athletes is the real-time and non-invasive monitoring of their activities. The use of these kind of data is necessary to develop strategies for specific tailored training in order to improve performances. The sensor system presented in this work has the aim to adopt a novel approach for the monitoring of physiological parameters, and athletes' performances, during their training. The anaerobic threshold is herein identified with the monitoring of the lactate concentration and the respiratory parameters. The data collected by the sensor are used to build a model using a supervised method (based on the partial least squares method, PLS) to predict the values of the parameters of interest. The sensor is able to measure the lactate concentration from a sample of saliva and it can estimate a respiratory parameter, such as maximal oxygen consumption, maximal carbon dioxide production and respiratory rate from a sample of exhaled breath. The main advantages of the device are the low power; the wireless communication; and the non-invasive sampling method, which allow its use in a real context of sport practice.