Detection of liver dysfunction using a wearable electronic nose system based on semiconductor metal oxide sensors

The purpose of this exploratory study was to determine whether liver dysfunction can be generally classified using a wearable electronic nose based on semiconductor metal oxide (MOx) gas sensors, and whether the extent of this dysfunction can be quantified. MOx gas sensors are attractive because of their simplicity, high sensitivity, low cost, and stability. A total of 30 participants were enrolled, 10 of them being healthy controls, 10 with compensated cirrhosis, and 10 with decompensated cirrhosis. We used three sensor modules with a total of nine different MOx layers to detect reducible, easily oxidizable, and highly oxidizable gases. The complex data analysis in the time and non-linear dynamics domains is based on the extraction of 10 features from the sensor time series of the extracted breathing gas measurement cycles. The sensitivity, specificity, and accuracy for distinguishing compensated and decompensated cirrhosis patients from healthy controls was 1.00. Patients with compensated and decompensated cirrhosis could be separated with a sensitivity of 0.90 (correctly classified decompensated cirrhosis), a specificity of 1.00 (correctly classified compensated cirrhosis), and an accuracy of 0.95. Our wearable, non-invasive system provides a promising tool to detect liver dysfunctions on a functional basis. Therefore, it could provide valuable support in preoperative examinations or for initial diagnosis by the general practitioner, as it provides non-invasive, rapid, and cost-effective analysis results

Total ion chromatogram and total ion mass spectrum as alternative tools for detection and discrimination (A review)

Gas chromatography (GC) and mass spectrometry (MS) are widely used techniques in the analysis of complex mixtures due to their various advantages, such as high selectivity, reproducibility, precision, and sensitivity. However, the data processing is often complex and time-consuming and requires a great deal of experience, which might be a serious drawback in certain areas, such as quality control, or regarding research in the field of medicine or forensic sciences, where time plays a crucial role. For these reasons, some authors have proposed the use of alternative data processing approaches, such as the total ion chromatogram or total mass spectrum, allowing these techniques to be treated as sensors where each retention time or ratio m/z acts as a sensor collecting total intensities. In this way, the main advantages associated with both techniques are maintained, but the outcomes from the analysis can be reached in a faster, simpler, and an almost automated way. In this review, the main features of the GC- and MS-based analysis methodologies and the ways in which to apply them are highlighted. Moreover, their implementation in different fields, such as agri-food, forensics, environmental sciences, or medicine is discussed, highlighting important advantages as well as limitations.info:eu-repo/semantics/publishedVersio

Cocaine by-product detection with metal oxide semiconductor sensor arrays

A range of n-type and p-type metal oxide semiconductor gas sensors based on SnO2 and Cr2O3 materials have been modified with zeolites H-ZSM-5, Na-A and H–Y to create a gas sensor array able to successfully detect a cocaine by-product, methyl benzoate, which is commonly targeted by detection dogs. Exposure to vapours was carried out with eleven sensors. Upon data analysis, four of these that offered promising qualities for detection were subsequently selected to understand whether machine learning methods would enable successful and accurate classification of gases. The capability of discrimination of the four sensor array was assessed against nine different vapours of interest; methyl benzoate, ethane, ethanol, nitrogen dioxide, ammonia, acetone, propane, butane, and toluene. When using the polykernel function (C = 200) in the Weka software – and just five seconds into the gas injection – the model was 94.1% accurate in successfully classifying the data. Although further work is necessary to bring the sensors to a standard of detection that is competitive with that of dogs, these results are very encouraging because they show the potential of metal oxide semiconductor sensors to rapidly detect a cocaine by-product in an inexpensive way

Cocaine by-product detection with metal oxide semiconductor sensor arrays

A range of n-type and p-type metal oxide semiconductor gas sensors based on SnO2 and Cr2O3 materials have been modified with zeolites H-ZSM-5, Na-A and H–Y to create a gas sensor array able to successfully detect a cocaine by-product, methyl benzoate, which is commonly targeted by detection dogs. Exposure to vapours was carried out with eleven sensors. Upon data analysis, four of these that offered promising qualities for detection were subsequently selected to understand whether machine learning methods would enable successful and accurate classification of gases. The capability of discrimination of the four sensor array was assessed against nine different vapours of interest; methyl benzoate, ethane, ethanol, nitrogen dioxide, ammonia, acetone, propane, butane, and toluene. When using the polykernel function (C = 200) in the Weka software – and just five seconds into the gas injection – the model was 94.1% accurate in successfully classifying the data. Although further work is necessary to bring the sensors to a standard of detection that is competitive with that of dogs, these results are very encouraging because they show the potential of metal oxide semiconductor sensors to rapidly detect a cocaine by-product in an inexpensive way

Paving the Way for a Green Transition in the Design of Sensors and Biosensors for the Detection of Volatile Organic Compounds (VOCs)

The efficient and selective detection of volatile organic compounds (VOCs) provides key information for various purposes ranging from the toxicological analysis of indoor/outdoor environments to the diagnosis of diseases or to the investigation of biological processes. In the last decade, different sensors and biosensors providing reliable, rapid, and economic responses in the detection of VOCs have been successfully conceived and applied in numerous practical cases; however, the global necessity of a sustainable development, has driven the design of devices for the detection of VOCs to greener methods. In this review, the most recent and innovative VOC sensors and biosensors with sustainable features are presented. The sensors are grouped into three of the main industrial sectors of daily life, including environmental analysis, highly important for toxicity issues, food packaging tools, especially aimed at avoiding the spoilage of meat and fish, and the diagnosis of diseases, crucial for the early detection of relevant pathological conditions such as cancer and diabetes. The research outcomes presented in the review underly the necessity of preparing sensors with higher efficiency, lower detection limits, improved selectivity, and enhanced sustainable characteristics to fully address the sustainable manufacturing of VOC sensors and biosensors

Recent Changes in Drug Abuse Scenario: The Novel Psychoactive Substances (NPS) Phenomenon

copyright 2019 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND.Final Published versio

Combating substance abuse with the potential of geographic information system combining multivariate analysis

Substance abuse problems have been a growing concern for people from all over the world. The objective of this study is to demonstrate the usefulness of a combination between a geographic information system and a multivariate analysis in substance abuse research. However, due to the limited studies on a combination of both these methods in the substance abuse field, we review some other studies in various fields indicating the potential of this method in future substance abuse studies. As the expertise of GIS lies in spatial analysis and the multivariate analysis lies in analyzing huge data thus being capable of interpreting the results very well, we hope this method will attract researchers to applying it in their studies and can consequently and indirectly help in combating substance abuse problems.Keywords: substance abuse; geographic information system; multivariate analysis;  spatial analysis; comba

The relationship between chemical concentration and odor activity value explains the inconsistency in making a comprehensive surrogate scent training tool representative of illicit drugs

This report highlights the importance of an individual chemical\u27s odor impact in the olfactory identification of marijuana, cocaine, and heroin. There are small amounts of highly odorous compounds present in headspace of these drugs, with very low odor detection thresholds, that are more likely responsible for contributing to the overall odor of these drugs. Previous reports of the most abundant compounds in headspace can mislead researchers when dealing with whole odor of these drugs. Surrogate scent formulations, therefore, must match the odor impact of key compounds and not just the chemical abundance of compounds. The objective of this study was to compare odorous volatile organic compounds (VOCs) emitted from illicit drug samples of marijuana, cocaine, and heroin to surrogate smell formulations using simultaneous sensory (via human olfaction) and chemical analyses. Use of solid phase microextraction (SPME) allowed VOCs in drug headspace to be extracted and pre-concentrated on site, and analyzed by multidimensional gas chromatography–mass spectrometry–olfactometry (MDGC–MS-O). Use of MDGC–MS-O allowed for further separation of odorous compounds and simultaneous detection by the human nose of the separate odor parts that make up the total aroma of these drugs. The compounds most abundant in headspace were not the most odor impactful when ranked by odor activity values (OAVs) (defined as ratio of concentration to odor detection threshold, ODT). There were no apparent correlations between concentrations and OAVs. A 1 g marijuana surrogate lacked in odor active acids, aldehydes, ethers, hydrocarbons, N-containing, and S-containing VOCs and was overabundant in odor active alcohols and aromatics compared with real marijuana. A 1 g cocaine surrogate was overabundant in odor active alcohols, aldehydes, aromatics, esters, ethers, halogenates, hydrocarbons, ketones and N-containing compounds compared with real. A 1 g heroin surrogate should contain less odor active acids, alcohols, aromatics, esters, ketones, and N-containing compounds. Drug quantity, age and adulterants can affect VOC emissions and their odor impact. The concept of odor activity value, then, is useful to researchers without access to more sophisticated instrumentation. Odor activity values can be calculated from published odor detection thresholds. More research is warranted to expand the database, and determine odor detection thresholds for compounds of interest. Additional information could be obtained from establishing ODTs of key odorants for canines