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

Naphthalimide Based Fluorophore for the Detection of Hazardous Volatile Organic Compounds (VOCs)

The naphthalimide molecule (NAP) was successfully synthesized and characterized by spectroscopy techniques. The NAP probe was exposed to a solvatochromic and aggregation-induced emission (AIE) probe using UV-visible and PL spectroscopy. In this case, the increased polarity of the solvent shows that it is red-shifted. The probe emission, a sky blue to yellow-green color at hexane to DCM, exhibited an excellent quantum yield. Meanwhile, the high-polar solvents of DMF and DMSO had poor quantum yields. This probe NAP showed the aggregation-induced emission property dramatically enhanced the emissions (at 540 nm) from fw = 80-90%. NAP was conducted with two polar solvent vapors in hexane and chloroform to investigate VOCs in a further solid-state study. A real-life test paper kit NAP probe was prepared and investigated VOCs detection against hexane and chloroform. When exposed to hexane vapors, the NAP probe test kit showed sky blue emission under UV light, which returned to greenish emission upon exposure to chloroform. Therefore, the results show that this NAP probe can be used for gas leak detection applications.

AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring

The steady progress in consumer electronics, together with improvement in microflow techniques, nanotechnology, and data processing, has led to implementation of cost-effective, user-friendly portable devices, which play the role of not only gadgets but also diagnostic tools. Moreover, numerous smart devices monitor patients' health, and some of them are applied in point-of-care (PoC) tests as a reliable source of evaluation of a patient's condition. Current diagnostic practices are still based on laboratory tests, preceded by the collection of biological samples, which are then tested in clinical conditions by trained personnel with specialistic equipment. In practice, collecting passive/active physiological and behavioral data from patients in real time and feeding them to artificial intelligence (AI) models can significantly improve the decision process regarding diagnosis and treatment procedures via the omission of conventional sampling and diagnostic procedures while also excluding the role of pathologists. A combination of conventional and novel methods of digital and traditional biomarker detection with portable, autonomous, and miniaturized devices can revolutionize medical diagnostics in the coming years. This article focuses on a comparison of traditional clinical practices with modern diagnostic techniques based on AI and machine learning (ML). The presented technologies will bypass laboratories and start being commercialized, which should lead to improvement or substitution of current diagnostic tools. Their application in PoC settings or as a consumer technology accessible to every patient appears to be a real possibility. Research in this field is expected to intensify in the coming years. Technological advancements in sensors and biosensors are anticipated to enable the continuous real-time analysis of various omics fields, fostering early disease detection and intervention strategies. The integration of AI with digital health platforms would enable predictive analysis and personalized healthcare, emphasizing the importance of interdisciplinary collaboration in related scientific fields.

Biosensors for Public Health and Environmental Monitoring: The Case for Sustainable Biosensing

Climate change is a profound crisis that affects every aspect of life, including public health. Changes in environmental conditions can promote the spread of pathogens and the development of new mutants and strains. Early detection is essential in managing and controlling this spread and improving overall health outcomes. This perspective article introduces basic biosensing concepts and various biosensors, including electrochemical, optical, mass-based, nano biosensors, and single-molecule biosensors, as important sustainability and public health preventive tools. The discussion also includes how the sustainability of a biosensor is crucial to minimizing environmental impacts and ensuring the long-term availability of vital technologies and resources for healthcare, environmental monitoring, and beyond. One promising avenue for pathogen screening could be the electrical detection of biomolecules at the single-molecule level, and some recent developments based on single-molecule bioelectronics using the Scanning Tunneling Microscopy-assisted break junctions (STM-BJ) technique are shown here. Using this technique, biomolecules can be detected with high sensitivity, eliminating the need for amplification and cell culture steps, thereby enhancing speed and efficiency. Furthermore, the STM-BJ technique demonstrates exceptional specificity, accurately detects single-base mismatches, and exhibits a detection limit essentially at the level of individual biomolecules. Finally, a case is made here for sustainable biosensors, how they can help, the paradigm shift needed to achieve them, and some potential applications.

Towards sustainable charcoal production: Designing an economical brick kiln with enhanced emission control technology

In this research, a brick kiln integrated with pollutant emission control technology was designed and applied in order to produce charcoal from Eucalyptus Globules wood. The batch operation carbonization of wood biomass was undertaken in a 1.25 m 3 volume brick kiln. A wet-packed scrubber was designed and constructed by filling gravels in a depth of 40 cm with aggregate sizes of 48-60 mm, 27-33 mm and 16-20 mm from the bottom to the top respectively aiming to treat emission from the charcoal-producing unit. The characteristics of the charcoal produced were determined to be composed of 9% moisture content, 1.5% ash content, 38% charcoal yield and a heating value of 27.53 MJ/kg. On the other hand, the wet scrubber integrated into a brick kiln was found to remove Hydrocarbons, C O 2 and CO by 97.8%, 98.5% and 99% respectively, which makes it efficient and practical way of controlling the gasses released during producing of charcoal.

Acetone Detection and Classification as Biomarker of Diabetes Mellitus Using a Quartz Crystal Microbalance Gas Sensor Array

A gas sensor array was developed and evaluated using four high-frequency quartz crystal microbalance devices (with a 30 MHz resonant frequency in fundamental mode). The QCM devices were coated with ethyl cellulose (EC), polymethylmethacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) sensing films, and deposited by the ultrasonic atomization method. The objective of this research was to propose a non-invasive technique for acetone biomarker detection, which is associated with diabetes mellitus disease. The gas sensor array was exposed to methanol, ethanol, isopropanol, and acetone biomarkers in four different concentrations, corresponding to 1, 5, 10, and 15 µL, at temperature of 22 °C and relative humidity of 20%. These samples were used because human breath contains them and they are used for disease detection. Moreover, the gas sensor responses were analyzed using principal component analysis and discriminant analysis, achieving the classification of the acetone biomarker with a 100% membership percentage when its concentration varies from 327 to 4908 ppm, and its identification from methanol, ethanol, and isopropanol.

Novel nanotechnological approaches for managing Phytophthora diseases of plants

Members of the Phytophthora genus are soil-dwelling pathogens responsible for diseases of several important plants. Among these, Phytophthora infestans causes late blight of potatoes, which was responsible for the Irish potato famine during the mid-19th century. Various strategies have been applied to control Phytophthora, including integrated management programs (IMPs) and quarantine, but without successful full management of the disease. Thus, there is a need to search for alternative tools. Here, we discuss the emerging role of nanomaterials in the detection and treatment of Phytophthora species, including slow delivery of agrochemicals (microbicides and pesticides). We propose integrating these tools into an IMP, which could lead to a reduction in pesticide use and provide more effective and sustainable control of Phytophthora pathogens.

Volatile Organic Compound Assessment as a Screening Tool for Early Detection of Gastrointestinal Diseases

Gastrointestinal (GI) diseases have a high prevalence throughout the United States. Screening and diagnostic modalities are often expensive and invasive, and therefore, people do not utilize them effectively. Lack of proper screening and diagnostic assessment may lead to delays in diagnosis, more advanced disease at the time of diagnosis, and higher morbidity and mortality rates. Research on the intestinal microbiome has demonstrated that dysbiosis, or unfavorable alteration of organismal composition, precedes the onset of clinical symptoms for various GI diseases. GI disease diagnostic research has led to a shift towards non-invasive methods for GI screening, including chemical-detection tests that measure changes in volatile organic compounds (VOCs), which are the byproducts of bacterial metabolism that result in the distinct smell of stool. Many of these tools are expensive, immobile benchtop instruments that require highly trained individuals to interpret the results. These attributes make them difficult to implement in clinical settings. Alternatively, electronic noses (E-noses) are relatively cheaper, handheld devices that utilize multi-sensor arrays and pattern recognition technology to analyze VOCs. The purpose of this review is to (1) highlight how dysbiosis impacts intestinal diseases and how VOC metabolites can be utilized to detect alterations in the microbiome, (2) summarize the available VOC analytical platforms that can be used to detect aberrancies in intestinal health, (3) define the current technological advancements and limitations of E-nose technology, and finally, (4) review the literature surrounding several intestinal diseases in which headspace VOCs can be used to detect or predict disease.

Sensitivity and specificity of in vivo COVID-19 screening by detection dogs: Results of the C19-Screendog multicenter study

Trained dogs can recognize the volatile organic compounds contained in biological samples of patients with COVID-19 infection. We assessed the sensitivity and specificity of in vivo SARS-CoV-2 screening by trained dogs. We recruited five dog-handler dyads. In the operant conditioning phase, the dogs were taught to distinguish between positive and negative sweat samples collected from volunteers' underarms in polymeric tubes. The conditioning was validated by tests involving 16 positive and 48 negative samples held or worn in such a way that the samples were invisible to the dog and handler. In the screening phase the dogs were led by their handlers to a drive-through facility for in vivo screening of volunteers who had just received a nasopharyngeal swab from nursing staff. Each volunteer who had already swabbed was subsequently tested by two dogs, whose responses were recorded as positive, negative, or inconclusive. The dogs' behavior was constantly monitored for attentiveness and wellbeing. All the dogs passed the conditioning phase, their responses showing a sensitivity of 83-100% and a specificity of 94-100%. The in vivo screening phase involved 1251 subjects, of whom 205 had a COVID-19 positive swab and two dogs per each subject to be screened. Screening sensitivity and specificity were respectively 91.6-97.6% and 96.3-100% when only one dog was involved, whereas combined screening by two dogs provided a higher sensitivity. Dog wellbeing was also analyzed: monitoring of stress and fatigue suggested that the screening activity did not adversely impact the dogs' wellbeing. This work, by screening a large number of subjects, strengthen recent findings that trained dogs can discriminate between COVID-19 infected and healthy human subjects and introduce two novel research aspects: i) assessement of signs of fatigue and stress in dogs during training and testing, and ii) combining screening by two dogs to improve detection sensitivity and specificity. Using some precautions to reduce the risk of infection and spillover, in vivo COVID-19 screening by a dog-handler dyad can be suitable to quickly screen large numbers of people: it is rapid, non-invasive and economical, since it does not involve actual sampling, lab resources or waste management, and is suitable to screen large numbers of people.

Advances in microbial analysis: based on volatile organic compounds of microorganisms in food

In recent years, microbial volatile organic compounds (mVOCs) produced by microbial metabolism have attracted more and more attention because they can be used to detect food early contamination and flaws. So far, many analytical methods have been reported for the determination of mVOCs in food, but few integrated review articles discussing these methods are published. Consequently, mVOCs as indicators of food microbiological contamination and their generation mechanism including carbohydrate, amino acid, and fatty acid metabolism are introduced. Meanwhile, a detailed summary of the mVOCs sampling methods such as headspace, purge trap, solid phase microextraction, and needle trap is presented, and a systematic and critical review of the analytical methods (ion mobility spectrometry, electronic nose, biosensor, and so on) of mVOCs and their application in the detection of food microbial contamination is highlighted. Finally, the future concepts that can help improve the detection of food mVOCs are prospected.

Synthesis, Characterization, and Soil Burial Degradation of Biobased Polyurethanes

There is an urgent need for developing degradable polymeric systems based on bio-derived and sustainable materials. In recent years, polyurethanes derived from castor oil have emerged due to the large availability and sustainable characteristics of castor oil. However, these polymers are normally prepared through tedious and/or energy-intensive procedures or using high volatile and/or toxic reagents such as volatile isocyanates or epoxides. Furthermore, poor investigation has been carried out to design castor oil derived polyurethanes with degradable characteristics or thorough specifically sustainable synthetic procedures. Herein, castor oil-derived polyurethane with more than 90% biomass-derived carbon content and enhanced degradable features was prepared through a simple, eco-friendly (E-factor: 0.2), and scalable procedure, employing a recently developed commercially available biomass-derived (61% bio-based carbon content) low-volatile polymeric isocyanate. The novel material was compared with a castor oil derived-polyurethane prepared with a commercially available fossil-based isocyanate counterpart. The different castor oil-derived polyurethanes were investigated by means of water uptake, soil burial degradation, and disintegration tests in compost. Characterization analyses, including thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) and scanning electron microscopy (SEM), were carried out both prior to and after degradation tests. The results suggest potential applications of the degradable castor oil-derived polyurethane in different fields, such as mulch films for agricultural purposes.

Strengthening Australia's Chemical Regulation

Humans are exposed to a myriad of chemicals every day, some of which have been established to have deleterious effects on human health. Regulatory frameworks play a vital role in safeguarding human health through the management of chemicals and their risks. For this review, we focused on agricultural and veterinary (Agvet) chemicals and industrial chemicals, which are regulated, respectively, by the Australian Pesticides and Veterinary Medicines Authority (APVMA), and the Australian Industrial Chemicals Introduction Scheme (AICIS). The current frameworks have been considered fragmented, inefficient, and most importantly, unsafe in prioritizing human health. We evaluated these frameworks, identified gaps, and suggested improvements that would help bring chemical regulation in Australia in line with comparative regulations in the EU, US, and Canada. Several weaknesses in the Australian frameworks include the lack of a national program to monitor chemical residues, slow pace in conducting chemical reviews, inconsistent risk management across states and territories, a paucity of research efforts on human health impacts, and inadequate framework assessment systems. Recommendations for Australia include establishing a national surveillance and chemical residue monitoring system, harmonizing risk assessment and management across jurisdictions, improving chemical review efficiency, and developing regular performance review mechanisms to ensure that human health is protected.

Development and Assessment of Regeneration Methods for Peptide-Based QCM Biosensors in VOCs Analysis Applications

Cleaning a quartz crystal microbalance (QCM) plays a crucial role in the regeneration of its biosensors for reuse. Imprecise removal of a receptor layer from a transducer’s surface can lead to unsteady operation during measurements. This article compares three approaches to regeneration of the piezoelectric transducers using the electrochemical, oxygen plasma and Piranha solution methods. Optimization of the cleaning method allowed for evaluation of the influence of cleaning on the surface of regenerated biosensors. The effectiveness of cleaning the QCM transducers with a receptor layer in the form of a peptide with the KLLFDSLTDLKKKMSEC-NH₂ sequence was described. Preliminary cleaning was tested for new electrodes to check the potential impact of the cleaning on deposition and the transducer’s operation parameters. The effectiveness of the cleaning was assessed via the measurement of a resonant frequency of the QCM transducers. Based on changes in the resonant frequency and the Sauerbrey equation, it was possible to evaluate the changes in mass adsorption on the transducer’s surface. Moreover, the morphology of the QCM transducer’s surface subjected to the selected cleaning techniques was presented with AFM imaging. The presented results confirm that each method is suitable for peptide-based biosensors cleaning. However, the most invasive seems to be the Piranha method, with the greatest decrease in performance after regeneration cycles (25% after three cycles). The presented techniques were evaluated for their efficiency with respect to a selected volatile compound, which in the future should allow reuse of the biosensors in particular applications, contributing to cost reduction and extension of the sensors’ lifetime.