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Nowadays, analytical techniques are moving towards the development of smart biosensing strategies for the point-of-care accurate screening of disease biomarkers, such as human epididymis protein 4 (HE4), a recently discovered serum marker for early ovarian cancer diagnosis. In this context, the present work represents the first implementation of a competitive enzyme-labelled magneto-immunoassay exploiting a homemade IoT Wi-Fi cloud-based portable potentiostat for differential pulse voltammetry readout. The electrochemical device was specifically designed to be capable of autonomous calibration and data processing, switching between calibration, and measurement modes: in particular, firstly, a baseline estimation algorithm is applied for correct peak computation, then calibration function is built by interpolating data with a four-parameter logistic function. The calibration function parameters are stored on the cloud for inverse prediction to determine the concentration of unknown samples. Interpolation function calibration and concentration evaluation are performed directly on-board, thus reducing the power consumption. The analytical device was validated in human serum, demonstrating good sensing performance for analysis of HE4 with detection and quantitation limits in human serum of 3.5 and 29.2 pM, respectively, reaching the sensitivity that is required for diagnostic purposes, with high potential for applications as portable and smart diagnostic tool for point-of-care testing.

Vitamin C, an antioxidant in most fruits and vegetables, is highly sensitive to heat, pH, metals, light, and oxidation, making it a key marker for nutrient degradation in thermal processing. Research aimed at improving processing methods to maximize vitamin C retention is usually limited to expensive laboratory equipment, which does not reflect real-world conditions in the food industry. On the other hand, traditional methods are not suitable for on-line monitoring. This paper proposes bridging the gap in liquid food processing with a voltammetric sensor based on poly(3,4-ethylenedioxythiophene)-modified screen-printed carbon electrodes. The sensor showed excellent repeatability, with intra-sensor RSD below 5% and inter-sensor RSD below 10% at 250 mg/L of ascorbic acid. Detection and quantification limits were 0.7 and 2.1 mg/L, respectively. Trueness assessment in commercial orange juice with a declared vitamin C content yielded a recovery rate of 94 ± 1%. Selectivity tests with citric acid at concentrations equal to and 20 times higher than that of ascorbic acid showed no significant interference. Shelf-life studies confirmed the stability of the sensor for at least two months. This nanocomposite-based approach balances performance and cost with simple preparation, affordable materials, and a stable coating that allows long-term storage in uncontrolled environments.

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.

A new amperometric sandwich-format genosensor has been implemented on single-walled carbon nanotubes screen printed electrodes (SWCNT-SPEs) and compared in terms of performance with analogous genoassays developed using the same methodology on non-nanostructured glassy carbon platforms (GC-SPE). The working principle of the genosensors is based on the covalent immobilization of Peptide Nucleic Acid (PNA) capture probes (CP) on the electrode surface, carried out through the carboxylic functions present on SWCNT-SPEs (carboxylated SWCNT) or electrochemically induced on GC-SPEs. The sequence of the CP was complementary to a 20-mer portion of the target DNA; a second biotin-tagged PNA signalling probe (SP), with sequence complementary to a different contiguous portion of the target DNA, was used to obtain a sandwich hybrid with an Alkaline Phosphatase-streptavidin conjugate (ALP-Strp). Comparison of the responses obtained from the SWCNT-SPEs with those produced from the non-nanostructured substrates evidenced the remarkable enhancement effect given by the nanostructured electrode platforms, achieved both in terms of loading capability of PNA probes and amplification of the electron transfer phenomena exploited for the signal transduction, giving rise to more than four-fold higher sensitivity when using SWCNT-SPEs. The nanostructured substrate allowed to reach limit of detection (LOD) of 71 pM and limit of quantitation (LOQ) of 256 pM, while the corresponding values obtained with GC-SPEs were 430 pM and 1.43 nM, respectively.

For their great structural versatility, thiophene-based π-conjugated systems have been widely exploited in the preparation of low band gap materials. Here, we report the synthesis of a highly conjugated tetrathiophene system, namely 1,4-di([2,2′-bithiophen]-3-yl)buta-1,3-diyne (1), that presents two bithiophene units connected at position 3 by a butadiynylene spacer. Single-crystal X-ray diffraction (SC-XRD) analysis elucidated the structure of 1, confirming the planarity of the molecule. The molecule was then electropolymerized onto the surface of a gold-coated piezoelectric quartz crystal, showing a high reactivity that is ascribable to the extended conjugation. The frontier molecular orbital energies of 1 were obtained via DFT optimization performed on the crystal structure-derived molecular geometry. Finally, DFT was also used to estimate the polymer band gap.

Innovative and highly performing smart voltammetric immunosensors for rapid and effective serological tests aimed at the determination of SARS-CoV-2 antibodies were developed and validated in human serum matrix. Two immunosensors were developed for the determination of immunoglobulins directed against either the nucleocapsid or the spike viral antigen proteins. The immunosensors were realized using disposable screen-printed electrodes modified with nanostructured materials for the immobilization of the antigens. Fast quantitative detection was achieved, with analysis duration being around 1 h. Signal readout was carried out through a smart, compact and battery-powered potentiostat, based on a Wi-Fi protocol and devised for the Internet of Things (IoT) paradigm. This device is used for the acquisition, storage and sharing of clinical data. Outstanding immunosensors’ sensitivity, specificity and accuracy (100%) were assessed, according to the diagnostic guidelines for epidemiological data. The overall performance of the sensing devices, combined with the portability of the IoT-based device, enables their suitability as a high-throughput diagnostic tool. Both of the immunosensors were validated using clinical human serum specimens from SARS-CoV-2 infected patients, provided by IRCCS Ospedale San Raffaele.

An IoT-WiFi smart and portable electrochemical immunosensor for the quantification of SARS-CoV-2 spike protein was developed with integrated machine learning features. The immunoenzymatic sensor is based on the immobilization of monoclonal antibodies directed at the SARS-CoV-2 S1 subunit on Screen-Printed Electrodes functionalized with gold nanoparticles. The analytical protocol involves a single-step sample incubation. Immunosensor performance was validated in a viral transfer medium which is commonly used for the desorption of nasopharyngeal swabs. Remarkable specificity of the response was demonstrated by testing H1N1 Hemagglutinin from swine-origin influenza A virus and Spike Protein S1 from Middle East respiratory syndrome coronavirus. Machine learning was successfully used for data processing and analysis. Different support vector machine classifiers were evaluated, proving that algorithms affect the classifier accuracy. The test accuracy of the best classification model in terms of true positive/true negative sample classification was 97.3%. In addition, the ML algorithm can be easily integrated into cloud-based portable Wi-Fi devices. Finally, the immunosensor was successfully tested using a third generation replicating incompetent lentiviral vector pseudotyped with SARS-CoV-2 spike glycoprotein, thus proving the applicability of the immunosensor to whole virus detection.

An outlook on the current status of different strategies for magnetic micro- and nanosized bead functionalization with aptamers as prominent bioreceptors is given with a focus on electrochemical and optical apta-assays, as well as on aptamer-modified magnetic bead–based miniaturized extraction techniques in food control. Critical aspects that affect interaction of aptamers with target molecules, as well as the possible side effects caused by aptamer interaction with other molecules due to non-specific binding, are discussed. Challenges concerning the real potential and limitations of aptamers as bioreceptors when facing analytical problems in food control are addressed.

Traditional techniques for food analysis are based on off-line laboratory methods that are expensive and time-consuming and often require qualified personnel. Despite the high standards of accuracy and metrological traceability, these well-established methods do not facilitate real-time process monitoring and timely on-site decision-making as required for food safety and quality control. The future of food testing includes rapid, cost-effective, portable, and simple methods for both qualitative screening and quantification of food contaminants, as well as continuous, real-time measurement in production lines. Process automatization through process analytical technologies (PAT) is an increasing trend in the food industry as a way to achieve improved product quality, safety, and consistency, reduced production cycle times, minimal product waste or reworks, and the possibility for real-time product release. Novel methods of analysis for point-of-need (PON) screening could greatly improve food testing by allowing non-experts, such as consumers, to test in situ food products using portable instruments, smartphones, or even visual naked-eye inspections, or farmers and small producers to monitor products in the field. This requires the attention of the research community and devices manufacturers to ensure reliability of measurement results from PAT strategy and PON tests through the demonstration and critical evaluation of performance characteristics. The fitness for purpose of methods in real-life conditions is a priority that should not be overlooked in order to maintain an effective and harmonized food safety policy.

For their great structural versatility, thiophene-based π-conjugated systems have been widely exploited in the preparation of low band gap materials. Here, we report the synthesis of a highly conjugated tetrathiophene system, namely 1,4-di([2,2′-bithiophen]-3-yl)buta-1,3-diyne (1), that presents two bithiophene units connected at position 3 by a butadiynylene spacer. Single-crystal X-ray diffraction (SC-XRD) analysis elucidated the structure of 1, confirming the planarity of the molecule. The molecule was then electropolymerized onto the surface of a gold-coated piezoelectric quartz crystal, showing a high reactivity that is ascribable to the extended conjugation. The frontier molecular orbital energies of 1 were obtained via DFT optimization performed on the crystal structure-derived molecular geometry. Finally, DFT was also used to estimate the polymer band gap.