Paper-based devices as new smart analytical tools for sustainable detection of environmental pollutants

The use of paper as a multifunctional material in electrochemical sensing has been intensively explored over the last decade. The combination among different kinds of paper as well as their coupling with different electro chemical cell configurations have been demonstrated, disclosing innovative sensing performances and features that are still to be fully investigated. This ongoing research has found applications in a variety of fields, including the biomedical, agri-food, security, and environmental ones, thanks to the high versatility and adaptability of the paper material. In this review, we report a critical and comparative analysis of electrochemical devices based on paper published within 2010–2021 and applied for the detection of pollutants of environmental interest in fresh water, seawater, and other real environmental matrices. Several paper types, from common office paper to Whatman filter paper with different filtering grades, were proved to be useful in this field. In detail, the multifarious roles played by the paper are discussed, highlighting how the paper can be a suitable material for electrochemical sensing while being capable of simplifying the measurement of complex real matrices or real izing programmable origami-like structures. Among the most important pollutants, a special focus is dedicated to the emerging pollutants. Furthermore, the unique advantages achieved by the paper have been analyzed and highlighted, reporting the future perspectives regarding the use of this surprising material

Experimental comparison in sensing breast cancer mutations by signal on and signal off paper-based electroanalytical strips

Altres ajuts: the ICN2 is funded by the CERCA Programme/Generalitat de Catalunya.The development of paper-based electroanalytical strips as powerful diagnostic tools has gained a lot of attention within the sensor community. In particular, the detection of nucleic acids in complex matrices represents a trending topic, especially when focused toward the development of emerging technologies, such as liquid biopsy. DNA-based biosensors have been largely applied in this direction, and currently, there are two main approaches based on target/probe hybridization reported in the literature, namely Signal ON and Signal OFF. In this technical note, the two approaches are evaluated in combination with paper-based electrodes, using a single strand DNA relative to H1047R (A3140G) missense mutation in exon 20 in breast cancer as the model target. A detailed comparison among the analytical performances, detection protocol, and cost associated with the two systems is provided, highlighting the advantages and drawbacks depending on the application. The present work is aimed to a wide audience, particularly for those in the field of point-of-care, and it is intended to provide the know-how to manage with the design and development stages, and to optimize the platform for the sensing of nucleic acids using a paper-based detection method

State of the art on the SARS-CoV-2 toolkit for antigen detection: one year later

The recent global events of COVID-19 in 2020 have alerted the world to the risk of viruses and their impacts on human health, including their impacts in the social and economic sectors. Rapid tests are urgently required to enable antigen detection and thus to facilitate rapid and simple evaluations of contagious individuals, with the overriding goal to delimitate spread of the virus among the population. Many efforts have been achieved in recent months through the realization of novel diagnostic tools for rapid, affordable, and accurate analysis, thereby enabling prompt responses to the pandemic infection. This review reports the latest results on electrochemical and optical biosensors realized for the specific detection of SARS-CoV-2 antigens, thus providing an overview of the available diagnostics tested and marketed for SARS-CoV-2 antigens as well as their pros and cons

Liquid biopsy beyond cancer: a miRNA detection in serum with electrochemical chip for non-invasive coeliac disease diagnosis

Coeliac disease is a very common autoimmune disease estimated to affect 1 in 100 people worldwide. It occurs in genetically predisposed people where the ingestion of gluten leads to damage in the small intestine, and it is accurately diagnosticated through duodenal biopsy, an invasive diagnostic method. The liquid biopsy, generally used for monitoring cancer, is an appealing alternative even for autoimmune pathology such as coeliac disease, allowing for detecting disease progression or resistance to treatment. For this reason, an electrochemical peptide nucleic acid (PNA) device combined with a smartphone-assisted potentiostat for non-invasive coeliac disease diagnosis is proposed, by measuring the selected overexpressed miRNA-486-5p in serum, enlarging the application of liquid biopsy in nontumor pathologies. For highly sensitive detection, the polyester-based printed sensor is nanomodified with gold nanoparticles and a synthetic customized PNA probe. The designed sensor can detect the target analyte in the range of 10–100 nM with a limit of detection of 0.7 nM by measuring the variation of the response of the electrochemical mediator hexaammineruthenium in the presence of PNA–miRNA duplex on the nanostructured working electrode surface. The analyses testing serum samples are found in agreement with ones obtained by realxtime quantitative polymerase chain reaction (RT-qPCR), demonstrating the reliability of this innovative electrochemical chip developed

Imported arboviral infections in Italy, July 2014-October 2015: A National Reference Laboratory report

BACKGROUND: Imported cases of infections due to Dengue (DENV) and Chikungunya (CHIKV) viruses and, more recently, Zika virus (ZIKV) are commonly reported among travelers returning from endemic regions. In areas where potentially competent vectors are present, the risk of autochthonous transmission of these vector-borne pathogens is relatively high. Laboratory surveillance is crucial to rapidly detect imported cases in order to reduce the risk of transmission. This study describes the laboratory activity performed by the National Reference Laboratory for Arboviruses (NRLA) at the Italian National Institute of Health in the period from July 2014 to October 2015. METHODS: Samples from 180 patients visited/hospitalized with a suspected DENV/CHIKV/ZIKV infection were sent to the NRLA from several Italian Hospitals and from Regional Reference Laboratories for Arboviruses, in agreement with the National Plan on human surveillance of vector-borne diseases. Both serological (ELISA IgM test and Plaque Reduction Neutralization Test-PRNT) and molecular assays (Real Time PCR tests, RT-PCR plus nested PCR and sequencing of positive samples) were performed. RESULTS: DENV infection was the most frequently diagnosed (80 confirmed/probable cases), and all four genotypes were detected. However, an increase in imported CHIKV cases (41 confirmed/probable cases) was observed, along with the detection of the first ZIKV cases (4 confirmed cases), as a consequence of the recent spread of both CHIKV and ZIKV in the Americas. CONCLUSIONS: Main diagnostic issues highlighted in our study are sensitivity limitations of molecular tests, and the importance of PRNT to confirm serological results for differential diagnosis of Arboviruses. The continuous evaluation of diagnostic strategy, and the implementation of laboratories networks involved in surveillance activities is essential to ensure correct diagnosis, and to improve the preparedness for a rapid and proper identification of viral threats

Paper-based electrochemical peptide sensor for on-site detection of botulinum neurotoxin serotype A and C

Botulinum neurotoxins (BoNTs) produced by soil bacterium Clostridium botulinum are cause of botulism and listed as biohazard agents, thus rapid screening assays are needed for taking the correct countermeasures in a timely fashion. The gold standard method relies on the mouse lethality assay with a lengthy analysis time, i.e., 2?5 days, hindering the prompt management of food safety and medical diagnosis. Herein, we propose the first paperbased antibody-free sensor for reliable and rapid detection of BoNT/A and BoNT/C, exploiting their cleavage capability toward a synthetic peptide able to mimic the natural substrate SNAP-25. The peptide is labelled with the electroactive molecule methylene blue and immobilized on the paper-based electrode modified with gold nanoparticles. Because BoNT/A and BoNT/C can cleave the peptide with the removal of methylene blue from electrode surface, the presence of these neurotoxins in the sample leads to a signal decrease proportional to BoNT amount. The biosensor developed with the selected peptide and combined with smartphone assisted potentiostat is able to detect both BoNT/A and BoNT/C with a linearity up to 1 nM and a detection limit equal to 10 pM. The applicability of this biosensor was evaluated with spiked samples of orange juice, obtaining recovery values equal to 104 ? 6% and 98 ? 9% for 1 nM and 0.5 nM of BoNT/A, respectively

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype