The use of low-cost and ecofriendly adsorbent was investigated as an ideal alternative to the current expensive methods of removing dyes from wastewater. In this study, activated carbon from olive-tree wood was used as an adsorbent for the removal of Congo red dye from aqueous solutions. Acidic and basic functional groups and surface structure of the obtained activated carbon were analyzed by Bohem titration, pH of point of zero charge (pH_PZC) and scanning electron microscopy (SEM). Langmuir and Freundlich adsorption models were employed to provide a description of the equilibrium isotherm. Furthermore, the pseudo-first-order and pseudo-second-order kinetic models were used to study the mechanism of dye adsorption by the activated carbon. The thermodynamic studies indicated that the adsorption of Murexide occurs in a spontaneous and exothermic process. The fitness of the Langmuir model to the adsorption process points that the Congo red dye was adsorbed on specific monolayer onto activated carbon. According to the obtained findings, activated carbon, produced by the chemical activation of olive waste wood, could be used as an effective and low-cost adsorbent to decrease the concentrations of dyes in wastewater. The results of this research highlight the importance of recycling agricultural waste to decrease environmental contamination and conserve natural resources. This encourages researchers to conduct further investigations in this area.

Ultrasound-assisted extraction (UAE) is a technique that belongs to the group of novel extraction methods belonging to green chemistry, like microwave assisted extraction (MAE), enzyme assisted extraction (EAE) or high-pressure assisted extraction (HPAE), because it promotes the extraction of compounds of interest, with a decrease in the consumption of resources, such as solvent and energy, and achieving remarkably higher extraction yields [1]. UAE has been mainly used to plant matrices to obtain extracts rich in bioactive compounds, such as phenolic compounds, pigments, polysaccharides, amino acids, among others. This methodology is based on the principle of cavitation, which leads to cell collapse of the matrix and allows the release of their inner substances. Several variables are relevant for the performance of UAE, including the solid-liquid ratio, the type of solvents used, the extraction time and the ultrasound power applied [2]. Besides, power and extraction time are closely linked to a fifth important factor: temperature. In practical terms, a correct optimization of these variables is essential to obtain an excellent performance, resulting in a maximal extraction yield. In addition, temperature is very important, as it can affect the integrity ofbioactive compounds, since most of them are thermolabile. Thus, large amounts of power linked to long extraction periods may lead to sample damage, so temperature control is essential for acorrect design of the cooling reactor and the optimization of of UAE extraction protocols. Keeping all this in mind, this critical review is focused on the influence of all the variables that affect ultrasound-assisted extraction, in order to analyze the critical factors involved in the optimization of this technique.

Acknowledgments

The research leading to these results was supported by MICINN supporting the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891) and the FPU grant for Anxo Carreira Casais (FPU2016/06135); by Xunta de Galicia for supporting the program EXCELENCIA-ED431F 2020/12, the pre-doctoral grant of A.G. Pereira (ED481A-2019/0228) and the program BENEFICIOS DO CONSUMO DAS ESPECIES TINTORERA- CO-0019-2021 that supports the work of F. Chamorro; by University of Vigo for supporting the predoctoral grant of M. Carpena (Uvigo-00VI 131H 6410211); and by the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019) that supports the work of P. Otero and P. Garcia-Perez. The authors are grateful to Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003). The JU receives support from the European Union’s Horizon 2020 research and innovation program and the Bio Based Industries Consortium. The project SYSTEMIC Knowledge hub on Nutrition and Food Security, has received funding from national research funding parties in Belgium (FWO), France (INRA), Germany (BLE), Italy (MIPAAF), Latvia (IZM), Norway (RCN), Portugal (FCT), and Spain (AEI) in a joint action of JPI HDHL, JPI-OCEANS and FACCE-JPI launched in 2019 under the ERA-NET ERA-HDHL (n° 696295).

References

1. Chemat, F.; Zill-E-Huma; Khan, M.K. Applications of Ultrasound in Food Technology: Processing, Preservation and Extraction. Ultrason. Sonochem. 2011, 18, 813–835, doi:10.1016/j.ultsonch.2010.11.023.
2. Chemat, F.; Abert Vian, M.; Fabiano-Tixier, A.S.; Nutrizio, M.; Režek Jambrak, A.; Munekata, P.E.S.; Lorenzo, J.M.; Barba, F.J.; Binello, A.; Cravotto, G. A Review of Sustainable and Intensified Techniques for Extraction of Food and Natural Products. Green Chem. 2020, 22, 2325–2353, doi:10.1039/c9gc03878g.

Nowadays, numerous diseases still have no cure or there is no effective treatment against them (some cancers, antibiotics-resistant bacterial infections, viruses, among others). To find new treatments for these diseases it is necessary to search for compounds with associated bioactivities of interest. Secondary metabolites from natural sources, such as plants, constitute one of the most relevant pools of molecules with pharmacological potential. In this sense, extracts derived from different species belonging to Amaranthaceae family show relevant effectiveness against several cancer cell lines and pathogenic bacteria under in vitro conditions. In this study, the chemical and nutritional composition of three Amaranthaceae species (Alternanthera sessilis (L.) R.Br. ex Dc, Dicliptera chinensis (L.) Juss., and Dysphania ambrosioides (L.) Mosyakin & Clemants), largely used in Asiatic traditional medicine for the treatment of several diseases, due to its antimicrobial, wound-healing, anti-inflammatory, and antioxidant properties, were studied. Results showed a differential flavonoid content in the three species: A. sessilis and D. ambrosioides showed similar flavonoid contents (15.1 ± 0.6 mg/g extract and 15.1 ± 0.1 mg/g extract, respectively), followed by D. chinensis (11.4 ± 0.1 mg/g extract); however, the principal flavonoids identified in A. sessilis were luteolin derivatives (luteolin-8-C-(rhamnosyl)ketodeoxihexoside and luteolin-6-C-glucoside), in the case of D. ambrosioides were isorhamnetin derivatives (mostly, isorhamnetin-3-O-rutinoside and isorhamnetin-3-O-neohesperidoside), and in D. chinensis were apigenin derivatives (apigenin-6-C-glucoside-8-C-arabinoside and apigenin-2"-O-xyloside-8-C-hexoside). These flavonoids have been reported to have significant bioactive properties, such as anti-inflammatory, anti-proliferative and antioxidant activity in previous studies [1]. On the other hand, the nutritional results showed a high protein content in all the species studied (16.9-13.9 ± 0.1 g/100g dw) and they also revealed the presence of organic acids, such as oxalic and succinic acid. Therefore, the bioactive compounds found in the extracts from Amaranthaceae species could be responsible for the bioactivities attributed to these plants, together with their protein and organic acid content, which could be highly valuable for pharmaceutical, nutraceutical and cosmetic industries.

References

1. Williamson, G.; Kay, C.D.; Crozier, A. The Bioavailability, Transport, and Bioactivity of Dietary Flavonoids: A Review from a Historical Perspective. Compr. Rev. Food Sci. Food Saf. 2018, 17, 1054–1112, doi:10.1111/1541-4337.12351.

Acknowledgments

The research leading to these results was supported by MICINN supporting the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891); by University of Vigo for supporting the predoctoral grant of M. Carpena (Uvigo-00VI 131H 6410211); by EcoChestnut Project (Erasmus+ KA202) that supports the work of B. Nuñez-Estevez, by Grupos de Referencia Competitiva de la Xunta that supports the work of M. Barral-Martínez (GRUPO AA1-GRC 2018) and by the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019) that supports the work of P. Otero and P. Garcia-Perez. The research leading to these results was funded by Xunta de Galicia supporting the program EXCELENCIA-ED431F 2020/12; to Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003). The JU receives support from the European Union’s Horizon 2020 research and innovation program and the Bio Based Industries Consortium. The project SYSTEMIC Knowledge hub on Nutrition and Food Security, has received funding from national research funding parties in Belgium (FWO), France (INRA), Germany (BLE), Italy (MIPAAF), Latvia (IZM), Norway (RCN), Portugal (FCT), and Spain (AEI) in a joint action of JPI HDHL, JPI-OCEANS and FACCE-JPI launched in 2019 under the ERA-NET ERA-HDHL (n° 696295). The authors are also gratefull to FCT, Portugal for financial support through national funds FCT/MCTES to the CIMO (UIDB/00690/2020); and L. Barros and R. Calhelha thank the national funding by FCT, P.I., through the institutional and individual scientific employment program-contract for their contracts.

Artificial Neural Networks have emerged as the one of the leading algorithmic approaches to solve modern healthcare challenges such as biomarker detection, disease diagnosis and medical imaging.

The relatively large success of Artificial Neural Networks within this field can be attributed to the neural networks ability to identify underlying trends and abstract relevant details from a given dataset.

This paper presents a comprehensive review of Artificial Neural Networks by identifying the key working components of any Artificial Neuron starting from an external input to its corresponding output received from an activation function, it analyses the different methodologies to network construction such as Supervised Learning, Unsupervised Learning and Reinforcement Learning, while also comparatively reviewing popular network topologies used within neural network based healthcare solutions such as Convolutional Neural Networks and Auto Encoders.

Finally, this paper summarizes the current state of Artificial Neural Networks within Medico-Diagnostics, predicts future trends, and identifies upcoming areas of challenges such as overtraining of small datasets, a difficulty in obtaining large medical datasets owing to the amount of time it takes medical professionals to label data and a general lack in the availability of high-quality data.

The need to control pesticide residues in foodstuffs in a fast and straightforward analysis for the field scale is required. Therefore, this research develops a transducer-based biosensor with a small device potentiometer (SDP) to produce a fast and accurate pesticide detection tool. The biosensor based on Pt/Au electrodes by immobilizing the acetylcholinesterase (AChE) enzyme coated membrane cellulose acetate (CA) 15% (w/v) cross-linked glutaraldehyde (GA) 25% (v/v) and SDP as a transducer that produces a potential value. The biosensor testing results on the organophosphate pesticide class, namely diazinon and profenofos, in which they showed the sensitivity of 21.204 and 21.035 mV.decade^-1, Limit of Detection (LoD) 10^-8 mg.L^-1, selectivity coefficient K_i,j < 1 and accuracy of 99.497 and 94.765 %, respectively. The results showed that the biosensor connected to an SDP transducer had an excellent performance in determining the presence of organophosphate pesticides.

Recently, low-dimensional (1D, 2D) nanostructured materials are attracting more and more interest as building blocks for innovative systems. Metal oxide nanowires are one of the most widely used materials for solid state gas sensors, as they are simple to make, inexpensive, and sensitive to a wide range of gases and volatiles.

Unfortunately, their broad sensitivity has a price to pay: very low selectivity. Fortunately, this flaw is not a problem for all applications. Where the boundary conditions are defined and "simple", a simple chemiresistor may be the best choice, while in cases where the variables are many, it is better to use an intelligent system.

In this paper we will show different systems based on metal oxide nanowires: single nanowire, many nanowires and on-chip systems, both traditional and smart. We will show that the performance of these nanostructures is excellent and can be used in various applications, including agri-food quality monitoring. We will demonstrate that the combination of different sensors of the same material positioned in a thermal gradient can act as an electronic nose, with excellent performance (100% classification and <15% average error on gas concentration) thanks to machine learning algorithms.

The integration of such tiny (less than one square mm) and cheap devices into the food supply chains would greatly reduce waste and the frequency of food poisoning.

Sensors are considered the future monitoring tools since compared to traditional sampling and analysis techniques, provide fast response on the output data in a timely, continuous, safe, and cost-effective fashion. Within sensors, the electronic tongue (e-tongue) devices are gaining special attention for liquid matrices. The use of nanomaterials to perform the analysis as sensor’s layers improves the device’s sensitivity and performance, due to their unique physical and chemical properties, such as more conductivity and/or resistivity to the changes in the target analyte, high relative surface area and size versatility.

Thus, the aim of the present work was to explore the potential of the e-tongue concept to monitor Clarithromycin (10 ng/L to 10 ug/L) by various nanostructures ( e.g. polyethyleneimine (PEI) and poly(sodium 4-styrenesulfonate) (PSS), MWCNTs) for coating, in order to find the best combination to detect and quantify the target contaminants in different matrices. Two thin-film deposition techniques were performed: layer-by-layer and sputtering techniques. The detection of the target antibiotics was achieved by measuring the impedance spectra of thin-films when immersed in mineral and river water matrices. The impedance spectra will be accessed with a Solartron 1260 Impedance Analyzer in the frequency range of 1 Hz to 1 MHz, by applying 25 mV. The sensor devices array forming the e-tongue concept, consist of ceramic/glass BK7 solid support with deposited gold interdigitate electrodes, coated with the thin films aforementioned.

The development of portable and inexpensive analyzers allowing fast determination of the integral sample characteristics is a current trend in analytical chemistry. Optical spectroscopy in visible and near infrared (NIR) range has a great potential due to the advances of modern optical engineering. Optical multisensor systems (OMS) are devices working on the principle of optical spectroscopy, but optimized for a specific analytical task and composed of cheaper elements: light-emitting diodes (LEDs), optical fibers, 3D-printed parts, stamped optics, and etc. Such specialization enables essential reduction of analyzers’ price, size and weight, thus, making the analysis widely available for both real-time application and field measurements.

In the present work, a novel platform for construction of OMS was suggested. The idea is to use a combination of molecular emitters as a multichannel light source with tunable intensity and wavelength range. Cyclometalated Ir(III) complexes [1] and Cu(II)-based complexes were synthetized and tested in order to obtain such a light source. Each individual complex has its own emission spectrum in the visible range. This enables selection and optimization of the light source for a specific analytical application. Several optical setup designs of OMS were developed. The proposed prototype was applied to analyze the metal ions in aqueous mixtures. The practical application of the OMS was demonstrated for the quantification of fluoride and phosphate in real surface and tap waters.

The proposed approach to OMS development allows reducing analysis time and does not require additional sample preparation. Moreover, OMS based on molecular emitters can be adopted for the particular analytical task by selecting the appropriate wavelength region. Despite the relative technical simplicity of OMS, its application in combination with modern chemometric methods provides high accuracy of analysis, comparable with that of full-featured spectrometers.

This study was supported by the RSF project #19-79-00076.

References

[1] Gitlina A.Yu., Surkova A., Ivonina M.V., Sizov V.V., Petrovskii S.K., Legin A., Starova G.L., Koshevoy I.O., Grachova E.V., Kirsanov D.O. Dyes and Pigments, 180 (2020) 108428.

Illicit drug consumption is posing critical concerns in our society causing health issues, crime-related activities, and the disruption of the border trade. The smuggling of illicit drugs such as cocaine and heroin in Europe urges the development of new tools for rapid on-site identification in cargos. Besides, the production of synthetic drugs increases internal trafficking, thus demanding simple and straightforward devices to detect illicit drugs in the field. Current methods used by law enforcement offices rely on presumptive color tests and portable spectroscopic techniques. However, these methods sometimes exhibit inaccurate results due to commonly used cutting agents or because the drugs are smuggled (hidden or mixed) in colored samples. Interestingly, electrochemical sensors can deal with these specific problems and can provide more reliable results in comparison to commercially available devices. Herein, it is presented an electrochemical device that uses low-cost screen-printed electrodes for the electrochemical detection of illicit drugs by square-wave voltammetry (SWV) profiling. A dual pH strategy based on a screening and a confirmatory test allows detecting the most encountered illicit drugs (i.e. cocaine, MDMA, heroin, amphetamine, and methamphetamine). The electrochemical interrogation of the illicit drugs exhibits the oxidation of the electroactive moieties in each drug at a certain potential, with the exception of amphetamine that uses an in situ derivatization to unravel its oxidation peak. A library of electrochemical profiles is built upon pure and mixtures of illicit drugs with common cutting agents. This library allows the design of a tailor-made script that shows the identification of each drug through a user-friendly interface. Finally, the results obtained from the analysis of different samples from confiscated cargos at different end-users sites present a promising alternative to current methods offering low-cost and rapid analysis in the field.

The sensors reproducibility is an important issue to ensure the reliability of the final instrument, such as electronic noses, in which individual sensors are implemented. The core of the electronic nose is made by sensors array, which may work in isothermal and/or temperature modulation mode. For the commercial applications (medical, food, environmental) three different aspects are important to develop an effective electronic nose: the system must guarantee good performance in order to sensitivity and specificity; the database and the pattern recognition software should work on different nominally identical electronic noses with minimal adaptation work; sensors should be interchangeable with nominally identical ones in case of failure. For these reasons, in this work the reproducibility of nominally identical sensors was tested comparing the features extrapolated with sensors working in the two modes: isothermal and temperature modulation. For the modulation of temperature we used a squared voltage wave (3 and 4 volts) and for constant temperature we applied the same average voltage (3.5 volts) in order to have the same average temperature for both modes during a single thermal period. The experiments were carried out with 4 commercial sensor (TGS 2620873TF- Figaro Sensor) tested by 2 different standard compounds (lactic acid and water). The experiments carried out with temperature modulation show that: i) it is not necessary to normalize features to a reference atmosphere; ii) some extracted features are more concrete and stable than others, even if from the PCA it is possible to deduce that also the latter ones provide important information. For the constant temperature: i) normalization to the reference air is necessary; ii) the normalized feature may be more or less repeatable than those extrapolated from the other mode depending on individual features.