Electrochemical sensors modified with iron oxide nanoparticles/nanocomposites for voltammetric detection of Pb (II) in water: A review.

Permissible limits of Pb2+ in drinking water are being reduced from 10 µgL-1 to 5 µgL-1, which calls for rapid, and highly reliable detection techniques. Electrochemical sensors have garnered attention in detection of heavy metal ions in environmental samples due to their ease of operation, low cost, and rapid detection responses. Selectivity, sensitivity and detection capabilities of these sensors, can be enhanced by modifying their working electrodes (WEs) with iron oxide nanoparticles (IONPs) and/or their composites. Therefore, this review is an in-depth analysis of the deployment of IONPs/nanocomposites in modification of electrochemical sensors for detection of Pb2+ in drinking water over the past decade. From the analyzed studies (n = 23), the optimal solution pH, deposition potential, and deposition time ranged between 3 and 5.6, -0.7 to -1.4 V vs Ag/AgCl, and 100-400 s, respectively. Majority of the studies employed square wave anodic stripping voltammetry (n = 16), in 0.1 M acetate buffer solution (n = 19) for detection of Pb2+. Limits of detection obtained (2.5 x 10-9 - 4.5 µg/L) were below the permissible levels which indicated good sensitivities of the modified electrodes. Despite the great performance of these modified electrodes, the primary source of IONPs has always been commercial iron-based salts in addition to the use of so many materials as modifying agents of these IONPs. This may limit reproducibility and sustainability of the WEs due to lengthy and costly preparation protocols. Steel and/or iron industrial wastes can be alternatively employed in generation of IONPs for modification of electrochemical sensors. Additionally, biomass-based activated carbons enriched with surface functional groups are also used in modification of bare IONPs, and subsequently bare electrodes. However, these two areas still need to be fully explored.

A Wearable Real-Time System for Simultaneous Wireless Power and Data Transmission to Cortical Visual Prosthesis.

Wireless, miniaturised and distributed neural interfaces are emerging neurotechnologies. Although extensive research efforts contribute to their technological advancement, the need for real-time systems enabling simultaneous wireless information and power transfer toward distributed neural implants remains crucial. Here we present a complete wearable system including a software for real-time image capturing, processing and digital data transfer; an hardware for high radiofrequency generation and modulation via amplitude shift keying; and a 3-coil inductive link adapt to operate with multiple miniaturised receivers. The system operates in real-time with a maximum frame rate of 20 Hz, reconstructing each frame with a matrix of 32 × 32 pixels. The device generates a carrier frequency of 433.92 MHz. It transmits the highest power of 32 dBm with a data rate of 6 Mbps and a variable modulation index as low as 8 %, thus potentially enabling wireless communication with 1024 miniaturised and distributed intracortical microstimulators. The system is primarily conceived as an external wearable device for distributed cortical visual prosthesis covering a visual field of 20 °. At the same time, it is modular and versatile, being suitable for multiple applications requiring simultaneous wireless information and power transfer to large-scale neural interfaces.

A Frequency-Switching Inductive Power Transfer System for Wireless, Miniaturised and Large-Scale Neural Interfaces.

Three-coil inductive power transfer is the state-of-the-art solution to power multiple miniaturised neural implants. However, the maximum delivered power is limited by the efficiency of the powering link and safety constrains. Here we propose a frequency-switching inductive link, where the passive resonator normally used in a three-coil link is replaced by an active resonator. It receives power from the external transmitter via a two-coil inductive link at the low frequency of 13.56 MHz. Then, it switches the operating frequency to the higher frequency of 433.92 MHz through a dedicated circuitry. Last, it transmits power to 1024 miniaturised implants via a three-coil inductive link using an array of 37 focusing resonators for a brain coverage of 163.84 mm 2. Our simulations reported a power transfer efficiency of 0.013 % and a maximum power delivered to the load of 1970 µW under safety-constrains, which are respectively two orders of magnitude and more than six decades higher compared to an equivalent passive three-coil link. The frequency-switching inductive system is a scalable and highly versatile solution for wireless, miniaturised and large-scale neural interfaces.

In-Memory Sensing and Computing for Cancer Diagnostics: A Perspective Paper.

During the past two decades, a number of two-terminal switching devices have been demonstrated in the literature. They typically exhibit hysteric behavior in the current-to-voltage characteristics. These devices have often been also referred to as memristive devices. Their capacity to switch and exhibit electrical hysteresis has made them well-suited for applications such as data storage, in-memory computing, and in-sensor computing or in-memory sensing. The aim of this perspective paper is to is twofold. Firstly, it seeks to provide a comprehensive examination of the existing research findings in the field and engage in a critical discussion regarding the potential for the development of new non-Von-Neumann computing machines that can seamlessly integrate sensing and computing within memory units. Secondly, this paper aims to demonstrate the practical application of such an innovative approach in the realm of cancer medicine. Specifically, it explores the modern concept of employing multiple cancer markers simultaneously to enhance the efficiency of diagnostic processes in cancer medicine.

Portable impedance-sensing device for microorganism characterization in the field.

A variety of biosensors have been proposed to quickly detect and measure the properties of individual microorganisms among heterogeneous populations, but challenges related to cost, portability, stability, sensitivity, and power consumption limit their applicability. This study proposes a portable microfluidic device based on impedance flow-cytometry and electrical impedance spectroscopy that can detect and quantify the size of microparticles larger than 45 µm, such as algae and microplastics. The system is low cost ($300), portable (5 cm [Formula: see text] 5 cm), low-power (1.2 W), and easily fabricated utilizing a 3D-printer and industrial printed circuit board technology. The main novelty we demonstrate is the use of square wave excitation signal for impedance measurements with quadrature phase-sensitive detectors. A linked algorithm removes the errors associated to higher order harmonics. After validating the performance of the device for complex impedance models, we used it to detect and differentiate between polyethylene microbeads of sizes between 63 and 83 µm, and buccal cells between 45 and 70 µm. A precision of 3% is reported for the measured impedance and a minimum size of 45 µm is reported for the particle characterization.

Changes Over Time in the Electrode/Brain Interface Impedance: An Ex-Vivo Study.

Closed-loop neural implants based on continuous brain activity recording and intracortical microstimulation are extremely effective and promising devices to monitor and address many neurodegenerative diseases. The efficiency of these devices depends on the robustness of the designed circuits which rely on precise electrical equivalent models of the electrode/brain interface. This is true in the case of amplifiers for differential recording, voltage or current drivers for neurostimulation, and potentiostats for electrochemical bio-sensing. This is of paramount importance, especially for the next generation of wireless and ultra-miniaturised CMOS neural implants. Circuits are usually designed and optimized considering the electrode/brain impedance with a simple electrical equivalent model whose parameters are stationary over time. However, the electrode/brain interfacial impedance varies simultaneously in frequency and in time after implantation. The aim of this study is to monitor the impedance changes occurring on microelectrodes inserted in ex-vivo porcine brains to derive an opportune electrode/brain model describing the system and its evolution in time. In particular, impedance spectroscopy measurements have been performed for 144 hours to characterise the evolution of the electrochemical behaviour in two different setups analysing both the neural recording and the chronic stimulation scenarios. Then, different equivalent electrical circuit models have been proposed to describe the system. Results showed a decrease in the resistance to charge transfer, attributed to the interaction between biological material and the electrode surface. These findings are crucial to support circuit designers in the field of neural implants.

Biocompatible and Biodegradable 3D Printing from Bioplastics: A Review.

There has been a lot of interest in developing and producing biodegradable polymers to address the current environmental problem caused by the continued usage of synthetic polymers derived from petroleum products. Bioplastics have been identified as a possible alternative to the use of conventional plastics since they are biodegradable and/or derived from renewable resources. Additive manufacturing, also referred to as 3D printing, is a field of growing interest and can contribute towards a sustainable and circular economy. The manufacturing technology also provides a wide material selection with design flexibility increasing its usage in the manufacture of parts from bioplastics. With this material flexibility, efforts have been directed towards developing 3D printing filaments from bioplastics such as Poly (lactic acid) to substitute the common fossil- based conventional plastic filaments such as Acrylonitrile butadiene styrene. Plant biomass is now utilized in the development of biocomposite materials. A lot of literature presents work done toward improving the biodegradability of printing filaments. However, additive manufacture of biocomposites from plant biomass is faced with printing challenges such as warping, low agglomeration between layers and poor mechanical properties of the printed parts. The aim of this paper is to review the technology of 3D printing using bioplastics, study the materials that have been utilized in this technology and how challenges of working with biocomposites in additive manufacture have been addressed.

Iron oxide nanoparticles/nanocomposites derived from steel and iron wastes for water treatment: A review.

Iron oxide nanoparticles (IONPs) are characterized by superior magnetic properties, high surface area to volume ratio, and active surface functional groups. These properties aid in removal of pollutants from water, through adsorption and/or photocatalysis, justifying the choice of IONPs in water treatment systems. IONPs are usually developed from commercial chemicals of ferric and ferrous salts alongside other reagents, a procedure that is costly, environmentally unfriendly and limits their mass production. On the other hand, steel and iron industries produce both solid and liquid wastes which in most cases are piled, discharged into water streams or landfilled as strategies to dispose them off. Such practices are detrimental to environmental ecosystems. Given the high content of iron present in these wastes, they can be used to generate IONPs. This work reviewed published literature through selected key words on the deployment of steel and/or iron-based wastes as IONPs precursors for water treatment. The findings reveal that steel waste-derived IONPs have properties such as specific surface area, particle sizes, saturation magnetization, and surface functional groups that are comparable or sometimes better than those synthesized from commercial salts. Furthermore, the steel waste-derived IONPs have high removal efficacy for heavy metals and dyes from water with possibilities of being regenerated. The performance of steel waste-derived IONPs can be enhanced by functionalization with different reagents such as chitosan, graphene, and biomass based activated carbons. Nonetheless, there is need to explore the potential of steel waste-based IONPs in removing contaminants of emerging concern, modifying pollutant detection sensors, their techno-economic feasibility in large treatment plants, toxicity of these nanoparticles when ingested into the human body, among other areas.

Precision Oncology by Point-of-Care Therapeutic Drug Monitoring and Dosage Adjustment of Conventional Cytotoxic Chemotherapies: A Perspective.

Therapeutic drug monitoring (TDM) of conventional cytotoxic chemotherapies is strongly supported yet poorly implemented in daily practice in hospitals. Analytical methods for the quantification of cytotoxic drugs are instead widely presented in the scientific literature, while the use of these therapeutics is expected to keep going for longer. There are two main issues hindering the implementation of TDM: turnaround time, which is incompatible with the dosage profiles of these drugs, and exposure surrogate marker, namely total area under the curve (AUC). Therefore, this perspective article aims to define the adjustment needed from current to efficient TDM practice for cytotoxics, namely point-of-care (POC) TDM. For real-time dose adjustment, which is required for chemotherapies, such POC TDM is only achievable with analytical methods that match the sensitivity and selectivity of current methods, such as chromatography, as well as model-informed precision dosing platforms to assist the oncologist with dose fine-tuning based on quantification results and targeted intervals.

Electrochemiluminescent immunosensor for detection of carcinoembryonic antigen using luminol-coated silver nanoparticles.

Recently, electrochemiluminescent (ECL) immunosensors have received much attention in the field of biomarker detection. Here, a highly enhanced ECL immunosensing platform was designed for ultrasensitive detection of carcinoembryonic antigen (CEA). The surface of the glassy carbon electrode was enhanced by applying functional nanostructures such as thiolated graphene oxide (S-GO) and streptavidin-coated gold nanoparticles (SA-AuNPs). The selectivity and sensitivity of the designed immunosensor were improved by entrapping CEA biomolecules using a sandwich approach. Luminol/silver nanoparticles (Lu-SNPs) were applied as the main core of the signaling probe, which were then coated with streptavidin to provide overloading of the secondary antibody. The highly ECL signal enhancement was obtained due to the presence of horseradish peroxidase (HRP) in the signaling probe, in which the presence of H2O2 further amplified the intensity of the signals. The engineered immunosensor presented excellent sensitivity for CEA detection, with limit of detection (LOD) and linear detection range (LDR) values of 58 fg mL-1 and 0.1 pg mL-1 to 5 pg mL-1 (R2 = 0.9944), respectively. Besides its sensitivity, the fabricated ECL immunosensor presented outstanding selectivity for the detection of CEA in the presence of various similar agents. Additionally, the developed immunosensor showed an appropriate repeatability (RSD 3.8%) and proper stability (2 weeks). Having indicated a robust performance in the real human serum with stated LOD and LDR, the engineered immunosensor can be considered for the detection and monitoring of CEA in the clinic.

Soft Epidermal Paperfluidics for Sweat Analysis by Ratiometric Raman Spectroscopy.

The expanding interest in digital biomarker analysis focused on non-invasive human bodily fluids, such as sweat, highlights the pressing need for easily manufactured and highly efficient soft lab-on-skin solutions. Here, we report, for the first time, the integration of microfluidic paper-based devices (µPAD) and non-enhanced Raman-scattering-enabled optical biochemical sensing (Raman biosensing). Their integration merges the enormous benefits of µPAD, with high potential for commercialization and use in resource-limited settings, with biorecognition-element-free (but highly selective) optical Raman biosensing. The introduced thin (0.36 mm), ultra-lightweight (0.19 g), and compact footprint (3 cm2) opto-paperfluidic sweat patch is flexible, stretchable, and conforms, irritation-free, to hairless or minimally haired body regions to enable swift sweat collection. As a great advantage, this new bio-chemical sensory system excels through its absence of onboard biorecognition elements (bioreceptor-free) and omission of plasmonic nanomaterials. The proposed easy fabrication process is adaptable to mass production by following a fully sustainable and cost-effective process utilizing only basic tools by avoiding typically employed printing or laser patterning. Furthermore, efficient collection and transportation of precise sweat volumes, driven exclusively by the wicking properties of porous materials, shows high efficiency in liquid transportation and reduces biosensing latency by a factor of 5 compared to state-of-the-art epidermal microfluidics. The proposed unit enables electronic chip-free and imaging-less visual sweat loss quantification as well as optical biochemical analysis when coupled with Raman spectroscopy. We investigated the multimodal quantification of sweat urea and lactate levels ex vivo (with syntactic sweat including +30 sweat analytes on porcine skin) and achieved a linear dynamic range from 0 to 100 mmol/L during fully dynamic continuous flow characterization.

Real-Time Multi-Ion-Monitoring Front-End With Interference Compensation by Multi-Output Support Vector Regressor.

Ion-sensors play a major role in physiology and healthcare monitoring since they are capable of continuously collecting biological data from body fluids. Nevertheless, ion interference from background electrolytes present in the sample is a paramount challenge for a precise multi-ion-monitoring. In this work, we propose the first system combining a battery-powered portable multi-channel electronic front-end, and an embedded Multi-output Support Vector Regressor (M-SVR), that supplies an accurate, continuous, and real-time monitoring of sodium, potassium, ammonium, and calcium ions. These are typical analytes tracked during physical exercise. The front-end interface was characterized through a sensor array built with screen-printed electrodes. Nernstian sensitivity and limit of detection comparable to a bulky laboratory potentiometer were achieved in both water and artificial sweat. The multivariate calibration model was deployed on a Raspberry Pi where the activity of the target ions were locally computed. The M-SVR model was trained, optimized, and tested on an experimental dataset acquired following a design of experiments. We demonstrate that the proposed multivariate regressor is a compact, low-complexity, accurate, and unbiased estimator of sodium and potassium ions activity. A global normalized root mean-squared error improvement of 6.97%, and global mean relative error improvement of 10.26%, were achieved with respect to a standard Multiple Linear Regressor (MLR). Within a real-time multi-ion-monitoring task, the overall system enabled the continuous monitoring and accurate determination of the four target ions activity, with an average accuracy improvement of 27.73% compared to a simple MLR, and a prediction latency of [Formula: see text].

Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning.

Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anaesthesiologist and patient with continuous drug monitoring. Direct detection of drugs is achieved with electrochemical techniques, and several options are present in literature to measure propofol (widely used anaesthetics). Still, the sensors proposed do not enable in-situ detection, they do not provide this information continuously, and they are based on bulky and costly lab equipment. In this paper, we present a novel smart pen-shaped electronic system for continuous monitoring of propofol in human serum. The system consists of a needle-shaped sensor, a quasi digital front-end, a smart machine learning data processing, in a single wireless battery-operated embedded device featuring Bluetooth Low Energy (BLE) communication. The system has been tested and characterized in real, undiluted human serum, at 37  °C. The device features a limit of detection of 3.8  µM, meeting the requirement of the target application, with an electronics system 59% smaller and 81% less power consuming w.r.t. the state-of-the-art, using a smart machine learning classification for data processing, which guarantees up to twenty continuous measure.

The Michelangelo step: removing scalloping and tapering effects in high aspect ratio through silicon vias.

We present here, for the first time, a fabrication technique that allows manufacturing scallop free,non-tapered, high aspect ratio in through-silicon vias (TSVs) on silicon wafers. TSVs are among major technology players in modern high-volume manufacturing as they enable 3D chip integration. However, the usual standardized TSV fabrication process has to deal with scalloping, an imperfection in the sidewalls caused by the deep reactive ion etching. The presence of scalloping causes stress and field concentration in the dielectric barrier, thereby dramatically impacting the following TSV filling step, which is performed by means of electrochemical plating. So, we propose here a new scallop free and non-tapered approach to overcome this challenge by adding a new step to the standard TSV procedure exploiting the crystalline orientation of silicon wafers. Thank to this new step, that we called "Michelangelo", we obtained an extremely well polishing of the TSV holes, by reaching atomic-level smoothness and a record aspect ratio of 28:1. The Michelangelo step will thus drastically reduce the footprint of 3D structures and will allow unprecedented efficiency in 3D chip integration.

Electrochemical Sensing of Adenosin Triphosphate by Specific Binding to Dipicolylamine Group in Cyclodextrin Supramolecular Complex.

Electrochemical detection based on cyclodextrin supramolecular complexes is founded on the competitive binding between electroactive probes and target molecules. This limits their versatility to be used for sensing a broad range of metabolites. In this work, we demonstrate the significant role of zinc ions as well as of ß-cyclodextrins modified with dipicolylamine and of a phenylboronic acid-modified ferrocene probe to address a selective electrochemical detection of adenosin triphosphate (ATP). Our findings will definitively have an impact in oncological point-of-care systems, since a high level of extracellular ATP reveals the inflammatory response due to chemotherapeutic treatments.

Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier.

We present a new method for electrochemical sensing, which compensates the fouling effect of propofol through machine learning (ML) model. Direct and continuous monitoring of propofol is crucial in the development of automatic systems for control of drug infusion in anaesthesiology. The fouling effect on electrodes discourages the possibility of continuous online monitoring of propofol since polymerization of the surface produces sensor drift. Several approaches have been proposed to limit the phenomenon at the biochemical interface; instead, here, we present a novel ML-based calibration procedure. In this paper, we analyse a dataset of 600 samples acquired through staircase cyclic voltammetry (SCV), resembling the scenario of continuous monitoring of propofol, both in PBS and in undiluted human serum, to demonstrate that ML-based model solves electrode fouling of anaesthetics. The proposed calibration approach is based on Gaussian radial basis function support vector classifier (RBF-SVC) that achieves classification accuracy of 98.9% in PBS, and 100% in undiluted human serum. The results prove the ability of the ML-based model to correctly classify propofol concentration in the therapeutic range between 1µM and 60µM with levels of 10µM, continuously up to ten minutes, with one sample every 30s.

Miniaturised Wireless Power Transfer Systems for Neurostimulation: A Review.

In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulators: ultrasound coupling, inductive coupling and capacitive coupling. For each powering method, the discussion starts describing the physical working principle. In particular, we focus on the challenges given by the miniaturisation of the implanted integrated circuits and the related ad-hoc solutions for wireless power transfer. Then, we present recent developments and progresses in wireless power transfer for biomedical applications. Last, we compare each technique based on key performance indicators to highlight the most relevant and innovative solutions suitable for neurostimulation, with the gaze turned towards miniaturisation.

Electrochemical Assay for Extremely Selective Recognition of Fructose Based on 4-Ferrocene-Phenylboronic Acid Probe and ß-Cyclodextrins Supramolecular Complex.

The aim of the present paper is to highlight a novel electrochemical assay for an extremely-selective detection of fructose thanks to the use of a supramolecular complex between ß-cyclodextrins (ß-CDs) and a chemically modified ferrocene with boronic acid named 4-Fc-PB/natural-ß-CDs. Another kind of ß-CDs, the 4-Fc-PB/3-phenylboronic-ß-CDs, is proposed for the detection of glucose. The novel electrochemical probe is fully characterized by 1 H nuclear magnetic resonance, mass spectroscopy, and elemental analysis, while the superior electrochemical performance is assessed in terms of sensitivity and detection limit. The novelty of the present work consists in the role of CDs that for the first time are employed in electrochemistry with a unique detection mechanism based on specific chemical interactions with the target molecule by the introduction of proper binding groups. A highly selective detection of fructose is obtained and it is believed that the proposed mechanism of detection represents a new way to electrochemically sense other molecules by varying the combination of specific groups of the supramolecular complex. The findings are of impactful importance since a quick, easy, cheap, and extremely selective detection of fructose is not yet available in the market, here achieved by using electrochemical methods which are a very growing field.

Microfluidics by Additive Manufacturing for Wearable Biosensors: A Review.

Wearable devices are nowadays at the edge-front in both academic research as well as in industry, and several wearable devices have been already introduced in the market. One of the most recent advancements in wearable technologies for biosensing is in the area of the remote monitoring of human health by detection on-the-skin. However, almost all the wearable devices present in the market nowadays are still providing information not related to human 'metabolites and/or disease' biomarkers, excluding the well-known case of the continuous monitoring of glucose in diabetic patients. Moreover, even in this last case, the glycaemic level is acquired under-the-skin and not on-the-skin. On the other hand, it has been proven that human sweat is very rich in molecules and other biomarkers (e.g., ions), which makes sweat a quite interesting human liquid with regards to gathering medical information at the molecular level in a totally non-invasive manner. Of course, a proper collection of sweat as it is emerging on top of the skin is required to correctly convey such liquid to the molecular biosensors on board of the wearable system. Microfluidic systems have efficiently come to the aid of wearable sensors, in this case. These devices were originally built using methods such as photolithographic and chemical etching techniques with rigid materials. Nowadays, fabrication methods of microfluidic systems are moving towards three-dimensional (3D) printing methods. These methods overcome some of the limitations of the previous method, including expensiveness and non-flexibility. The 3D printing methods have a high speed and according to the application, can control the textures and mechanical properties of an object by using multiple materials in a cheaper way. Therefore, the aim of this paper is to review all the most recent advancements in the methods for 3D printing to fabricate wearable fluidics and provide a critical frame for the future developments of a wearable device for the remote monitoring of the human metabolism directly on-the-skin.