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This work implemented a non-invasive volatile organic compounds (VOCs) monitoring approach to study how food components are metabolised by the gut microbiota in-vitro. The fermentability of a model food matrix rich in dietary fibre (oat bran), and a pure prebiotic (inulin), added to a minimal gut medium was compared by looking at global changes in the volatilome. The substrates were incubated with a stabilised human faecal inoculum over a 24-h period, and VOCs were monitored without interfering with biological processes. The fermentation was performed in nitrogen-filled vials, with controlled temperature, and tracked by automated headspace-solid-phase microextraction coupled with gas chromatography-mass spectrometry. To understand the molecular patterns over time, we applied a multivariate longitudinal statistical framework: repeated measurements-ANOVA simultaneous component analysis. The methodology was able to discriminate the studied groups by looking at VOCs temporal profiles. The volatilome showed a time-dependency that was more distinct after 12 h. Short to medium-chain fatty acids showed increased peak intensities, mainly for oat bran and for inulin, but with different kinetics. At the same time, alcohols, aldehydes, and esters showed distinct trends with discriminatory power. The proposed approach can be applied to study the intertwined pathways of gut microbiota food components interaction in-vitro.

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In this study, we synthesized hybrid systems based on manganese oxide@zinc oxide (Mn3O4@ZnO), using sol gel and hydrothermal methods. The hybrid materials exhibited hierarchical morphologies and structures characterized by the hexagonal phase of ZnO and the tetragonal phase of Mn3O4. The hybrid materials were tested for degradation of methylene blue (MB), methyl orange (MO), and malachite green (MG) under ultraviolet (UV) light illumination. The aim of this work was to observe the effect of various amounts of Mn3O4 in enhancing the photocatalytic properties of ZnO-based hybrid structures towards the degradation of MB, MO and MG. The ZnO photocatalyst showed better performance with an increasing amount of Mn3O4, and the degradation efficiency for the hybrid material containing the maximum amount of Mn3O4 was found to be 94.59%, 89.99%, and 97.40% for MB, MO and MG, respectively. The improvement in the performance of hybrid materials can be attributed to the high charge separation rate of electron-hole pairs, the co-catalytic role, the large number of catalytic sites, and the synergy for the production of high quantities of oxidizing radicals. The performance obtained from the various Mn3O4@ZnO hybrid materials suggest that Mn3O4 can be considered an effective co-catalyst for a wide range of photocatalytic materials such as titanium dioxide, tin oxide, and carbon-based materials, in developing practical hybrid photocatalysts for the degradation of dyes and for wastewater treatment.

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Thermal modification of wood is a well-known industrial process performed to increase the durability and dimensional stability or to change the colour of natural wood. The treatment influences many other properties of wood including the emission of volatile organic compounds (VOCs). VOC release ultimately affects the quality of indoor air and the capability of having low VOC emission is often included as a key parameter for the attribution of quality labels. In the present work, wood from six tree species was subjected to different types of treatment and VOC profiling was carried out on both treated and untreated samples by means of PTR-ToF-MS. Different types of thermal treatment were tested, involving either overpressure or vacuum and the effect of different temperature profiles was evaluated. Hardwood and softwood showed different release profiles under all tested conditions: the headspace of softwood was richer in several VOCs, such as terpenes, phenols and C6-C9 aldehydes and carboxylic acids. Upon thermal treatment, terpene emissions decreased, whereas several other VOCs, such as formic acid, formaldehyde, furfural and acetic acid, were released in higher amounts. With its high sensitivity and throughput, PTR-ToF-MS appears to be a very powerful analytical tool, useful in supporting the selection of wood materials for different end uses.

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The present study is focused on yogurt as a simple, inexpensive, abundant, and green source for the preparation of luminescent carbon material for enhancing the photodegradation of methylene blue (MB). It introduces an ecological and sustainable approach for the large-scale production of carbon material using the direct thermal annealing of yogurt in a muffle furnace. The size of the as-prepared carbon material is about 200-300 nm, with average particle size distribution of 355 nm. The material exhibits clear luminescence under illumination with ultraviolet light. The synthesized carbon material shows an outstanding degradation functionality of MB under the irradiation of ultraviolet (UV) light in aqueous media. Various dye degradation parameters such as initial dye concentration, catalyst dose, pH of dye solution, and scavenger effects have been investigated. The optimum MB concentration was found to be 2.3 × 10-5 M with a degradation efficiency of 94.8%. The degradation was highly enhanced at pH 11 with a degradation efficiency of 98.11%. The degradation of MB under highly alkaline conditions was mainly governed by the high amount of hydroxyl radicals. Furthermore, the scavenger study confirmed that the hydroxyl radicals were mainly involved in the degradation process. The degradation kinetics of MB followed first order kinetics with large values of rate constant. The reusability was also studied to ensure the stability of the as-prepared carbon material during the degradation of MB. The preparation of carbon materials with efficient photosensitivity for the degradation of organic dyes from yogurt shows a green and innovative methodology. Therefore, it can be of great interest for future studies related to energy and environmental applications.

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Methanol, naturally present in small quantities in the distillation of alcoholic beverages, can lead to serious health problems. When it exceeds a certain concentration, it causes blindness, organ failure, and even death if not recognized in time. Analytical techniques such as chromatography are used to detect dangerous concentrations of methanol, which are very accurate but also expensive, cumbersome, and time-consuming. Therefore, a gas sensor that is inexpensive and portable and capable of distinguishing methanol from ethanol would be very useful. Here, we present a resistive gas sensor, based on tin oxide nanowires, that works in a thermal gradient. By combining responses at various temperatures and using machine learning algorithms (PCA, SVM, LDA), the device can distinguish methanol from ethanol in a wide range of concentrations (1-100 ppm) in both dry air and under different humidity conditions (25-75% RH). The proposed sensor, which is small and inexpensive, demonstrates the ability to distinguish methanol from ethanol at different concentrations and could be developed both to detect the adulteration of alcoholic beverages and to quickly recognize methanol poisoning.

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Gas sensors play an important role in many areas of human life, including the monitoring of production processes, occupational safety, food quality assessment, and air pollution monitoring. Therefore, the need for gas sensors to monitor hazardous gases, such as ammonia, at low operating temperatures has become increasingly important in many fields. Sensitivity, selectivity, low cost, and ease of production are crucial characteristics for creating a capillary network of sensors for the protection of the environment and human health. However, developing gas sensors that are not only efficient but also small and inexpensive and therefore integrable into everyday life is a difficult challenge. In this paper, we report on a resistive sensor for ammonia detection based on thin V2O5 nanosheets operating at room temperature. The small thickness and porosity of the V2O5 nanosheets give the sensors good performance for sensing ammonia at room temperature (RT), with a relative change of resistance of 9.4% to 5 ppm ammonia (NH3) and an estimated detection limit of 0.4 ppm. The sensor is selective with respect to the seven interferents tested; it is repeatable and stable over the long term (four months). Although V2O5 is generally an n-type semiconductor, in this case the nanosheets show a p-type semiconductor behavior, and thus a possible sensing mechanism is proposed. The device's performance, along with its size, low cost, and low power consumption, makes it a good candidate for monitoring freshness and spoilage along the food supply chain.

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In recent times, an increasing number of applications in different fields need gas sensors that are miniaturized but also capable of distinguishing different gases and volatiles. Thermal electronic noses are new devices that meet this need, but their performance is still under study. In this work, we compare the performance of two thermal electronic noses based on SnO2 and ZnO nanowires. Using five different target gases (acetone, ammonia, ethanol, hydrogen and nitrogen dioxide), we investigated the ability of the systems to distinguish individual gases and estimate their concentration. SnO2 nanowires proved to be more suitable for this purpose with a detection limit of 32 parts per billion, an always correct classification (100%) and a mean absolute error of 7 parts per million.

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The response of a single tin oxide nanowire was collected at different temperatures to create a virtual array of sensors working as a nano-electronic nose. The single nanowire, acting as a chemiresistor, was first tested with pure ammonia and then used to determine the freshness status of trout fish (Oncorhynchus mykiss) in a rapid and non-invasive way. The gas sensor reacts to total volatile basic nitrogen, detecting the freshness status of the fish samples in less than 30 s. The sensor response at different temperatures correlates well with the total viable count (TVC), demonstrating that it is a good (albeit indirect) way of measuring the bacterial population in the sample. The nano-electronic nose is not only able to classify the samples according to their degree of freshness but also to quantitatively estimate the concentration of microorganisms present. The system was tested with samples stored at different temperatures and classified them perfectly (100%), estimating their log(TVC) with an error lower than 5%.

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In this work, four identical micro sensors on the same chip with noble metal decorated tin oxide nanowires as gas sensing material were located at different distances from an integrated heater to work at different temperatures. Their responses are combined in highly informative 4D points that can qualitatively (gas recognition) and quantitatively (concentration estimate) discriminate all the tested gases. Two identical chips were fabricated with tin oxide (SnO2) nanowires decorated with different metal nanoparticles: one decorated with Ag nanoparticles and one with Pt nanoparticles. Support Vector Machine was used as the "brain" of the sensing system. The results show that the systems using these multisensor chips were capable of achieving perfect classification (100%) and good estimation of the concentration of tested gases (errors in the range 8-28%). The Ag decorated sensors did not have a preferential gas, while Pt decorated sensors showed a lower error towards acetone, hydrogen and ammonia. Combination of the two sensor chips improved the overall estimation of gas concentrations, but the individual sensor chips were better for some specific target gases.

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BACKGROUND: Silver nanoparticles (AgNPs) are well-known as a promising antimicrobial material; they have been widely used in many commercial products against pathogenic agents. Despite a growing concern regarding the cytotoxicity, AgNPs still have attracted considerable interest worldwide to develop a new generation of diagnostic tool and effective treatment solution for cancer cells. OBJECTIVE: This paper aims to review the advances of AgNPs applied for cancer diagnosis and treatment. METHODS: The database has been collected, screened and analysed through up-to-date scientific articles published from 2007 to May 2019 in peer-reviewed international journals. RESULTS: The findings of the database have been analysed and divided into three parts of the text that deal with AgNPs in cancer diagnosis, their cytotoxicity, and the role as carrier systems for cancer treatment. Thanks to their optical properties, high conductivity and small size, AgNPs have been demonstrated to play an essential role in enhancing signals and sensitivity in various biosensing platforms. Furthermore, AgNPs also can be used directly or developed as a drug delivery system for cancer treatment. CONCLUSION: The review paper will help readers understand more clearly and systematically the role and advances of AgNPs in cancer diagnosis and treatment.

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Multisensor systems with low-power consumption are emerging for the Internet of Things. In this work, we demonstrate the use of self-heated networked Ag-decorated SnO2 NW sensors integrated into a portable module for selective detection of H2S gas at low power consumption, and the integrated system is simulated as a virtual multisensor under varying heating powers for identifying and quantifying different reducing gases. The H2S gas-sensing characterisations at the different self-heating powers of 2-10 mW showed that the gas response significantly increased with the increase in Ag density decoration and the heated power strongly affected the gas-sensing performance and sensor stability. Excellent response of 21.2 to 0.5 ppm H2S gas was obtained at a low heating power of 2 mW with an acceptable response/recovery time of 18/980 s. The increase of the heating power over 20 mW can destroy the devices. The integrated system could selectively detect H2S at the heating power below 4 mW and H2, C2H5OH and NH3 gases at the heating power upon 4 mW. The virtual multisensor could discriminate qualitatively (with an accuracy of 100%) and quantitatively H2S, H2, NH3, C2H5OH (Ethanol) and CH3COCH3 (Aceton) gases with average errors of 13.5%, 14.7%, 16.8%, 16.9%, and 14.8%, respectively. The proposed sensing platform is a promising candidate for selective detection of H2S gas and virtual multisensor with low power consumption for mobile or wireless network devices.

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In this work we have grown particular zinc oxide two-dimensional nanostructures which are essentially a series of hexagonal very thin sheets. The hexagonal wurtzite crystal structure gives them their peculiar shape, whose dimensions are few microns wide, with a thickness in the order of 25 nm. Such kind of nanostructure, grown by thermal oxidation of evaporated metallic zinc on a silica substrate, has been used to fabricate conductometric gas sensors, investigated then for hydrogen gas detection. The "depletion layer sensing mechanism" is clarified, explaining how the geometrical factors of one- and two-dimensional nanostructures affect their sensing parameters. The comparison with one-dimensional ZnO nanowires based structures shows that two-dimensional nanostructures are ideal for gas sensing, due to their tiny thickness, which is comparable to the depletion-layer thickness, and their large cross-section, which increases the base current, thus lowering the limit of detection. The response to H2 has been found good even to sub-ppm concentrations, with response and recovery times shorter than 18s in the whole range of H2 concentrations investigated (500 ppb-10 ppm). The limit of detection has been found around 200 ppb for H2 gas even at relatively low working temperature (175 °C).

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