Development of Organic-Inorganic Hybrid Optical Gas Sensors for the Non-Invasive Monitoring of Pathogenic Bacteria

Volatile organic compounds (VOCs) detection for the identification of bacterial infections in clinical wound samples

Early detection of wound infections is critical for timely intervention and prevention of possible complications since prompt treatment can help lower pathogen spread and enhance faster healing. Early detection also helps reduce the risk of serious infections requiring extensive medical interventions or life-threatening diseases such as sepsis. Culture-based approaches currently used for bacterial identification have limited sensitivity and specificity. At the same time, they are time-consuming, resulting in delays in therapy and, therefore, having a negative impact on the treatment outcomes. Quantifying the volatile organic compounds (VOCs) released by bacteria residing in wounds is a promising, non-invasive option for detecting infections at early stages. This method allows for continuous monitoring without requiring invasive procedures, thereby reducing patient discomfort and the risk of further complications. Spectroscopy methods and sensors are the primary VOC detection and quantification approaches, but sensors are more rapid, cost-effective, non-invasive, and precise. This review highlights the significance of the early detection of wound infection to enable timely intervention and prevent complications, emphasizing the limitations of culture-based approaches. It also explores the potential of quantifying VOCs using different methods and discusses the correlation between their levels and the rate of bacterial infections in wounds. Additionally, the review evaluates current VOC-based monitoring methods for wound management, identifies gaps in the field, and advocates for further research to advance wound care and enhance patient outcomes.

Microfluidic integrated gas sensors for smart analyte detection: a comprehensive review

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.

A Novel Packaging of the MEMS Gas Sensors Used for Harsh Outdoor and Human Exhale Sampling Applications

Dust or condensed water present in harsh outdoor or high-humidity human breath samples are one of the key sources that cause false detection in Micro Electro-Mechanical System (MEMS) gas sensors. This paper proposes a novel packaging mechanism for MEMS gas sensors that utilizes a self-anchoring mechanism to embed a hydrophobic polytetrafluoroethylene (PTFE) filter into the upper cover of the gas sensor packaging. This approach is distinct from the current method of external pasting. The proposed packaging mechanism is successfully demonstrated in this study. The test results indicate that the innovative packaging with the PTFE filter reduced the average response value of the sensor to the humidity range of 75~95% RH by 60.6% compared to the packaging without the PTFE filter. Additionally, the packaging passed the High-Accelerated Temperature and Humidity Stress (HAST) reliability test. With a similar sensing mechanism, the proposed packaging embedded with a PTFE filter can be further employed for the application of exhalation-related, such as coronavirus disease 2019 (COVID-19), breath screening.

A Lab-Made E-Nose-MOS Device for Assessing the Bacterial Growth in a Solid Culture Medium

The detection and level assessment of microorganisms is a practical quality/contamination indicator of food and water samples. Conventional analytical procedures (e.g., culture methods, immunological techniques, and polymerase chain reactions), while accurate and widely used, are time-consuming, costly, and generate a large amount of waste. Electronic noses (E-noses), combined with chemometrics, provide a direct, green, and non-invasive assessment of the volatile fraction without the need for sample pre-treatments. The unique olfactory fingerprint generated during each microorganism's growth can be a vehicle for its detection using gas sensors. A lab-made E-nose, comprising metal oxide semiconductor sensors was applied, to analyze solid medium containing Gram-positive (Enterococcus faecalis and Staphylococcus aureus) or Gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The electrical-resistance signals generated by the E-nose coupled with linear discriminant analysis allowed the discrimination of the four bacteria (90% of correct classifications for leave-one-out cross-validation). Furthermore, multiple linear regression models were also established allowing quantifying the number of colony-forming units (CFU) (0.9428 ≤ R² ≤ 0.9946), with maximum root mean square errors lower than 4 CFU. Overall, the E-nose showed to be a powerful qualitative-quantitative device for bacteria preliminary analysis, being envisaged its possible application in solid food matrices.

Recent Progress in Electronic Noses for Fermented Foods and Beverages Applications

Fermented foods and beverages have become a part of daily diets in several societies around the world. Emitted volatile organic compounds play an important role in the determination of the chemical composition and other information of fermented foods and beverages. Electronic nose (E-nose) technologies enable non-destructive measurement and fast analysis, have low operating costs and simplicity, and have been employed for this purpose over the past decades. In this work, a comprehensive review of the recent progress in E-noses is presented according to the end products of the main fermentation types, including alcohol fermentation, lactic acid fermentation, acetic acid fermentation and alkaline fermentation. The benefits, research directions, limitations and challenges of current E-nose systems are investigated and highlighted for fermented foods and beverage applications.

Carbon Dots in the Detection of Pathogenic Bacteria and Viruses

Bacterial and viruses pathogens are a significant hazard to human safety and health. In the imaging and detection of pathogenic microorganisms, the application of fluorescent nanoparticles is very useful. Carbon dots and quantum dots are preferred in this regard as labels, amplifiers, and/or electrode modifiers because of their outstanding features. However, precise diagnostics to identify numerous harmful bacteria simultaneously still face considerable hurdles, yet it is an inevitable issue. With the growing development of biosensors, nanoproduct-based bio-sensing has recently become one of the most promising methods for accurately identifying and quantifying various pathogens at low cost, high sensitivity, and selectivity, with time savings. The most recent applications of carbon dots in optical and electrochemical-based sensors are discussed in this review, along with some examples of pathogen sensors.HighlightsSimultaneous and early detection of pathogens is a critical issue in the management of readily spread to prevent epidemics.Carbon dots-based biosensors are more preferred in detection of pathogens due to high selectivity and sensitivity, as well as quick and cheap point-of-care platform.Summary of recent advances in the design of optical and electrochemical biosensors for the detection of pathogens.

Sniffing Bacteria with a Carbon-Dot Artificial Nose

HIGHLIGHTS

Novel artificial nose based upon electrode-deposited carbon dots (C-dots). Significant selectivity and sensitivity determined by "polarity matching" between the C-dots and gas molecules. The C-dot artificial nose facilitates, for the first time, real-time, continuous monitoring of bacterial proliferation and discrimination among bacterial species, both between Gram-positive and Gram-negative bacteria and between specific strains. Machine learning algorithm furnishes excellent predictability both in the case of individual gases and for complex gas mixtures. Continuous, real-time monitoring and identification of bacteria through detection of microbially emitted volatile molecules are highly sought albeit elusive goals. We introduce an artificial nose for sensing and distinguishing vapor molecules, based upon recording the capacitance of interdigitated electrodes (IDEs) coated with carbon dots (C-dots) exhibiting different polarities. Exposure of the C-dot-IDEs to volatile molecules induced rapid capacitance changes that were intimately dependent upon the polarities of both gas molecules and the electrode-deposited C-dots. We deciphered the mechanism of capacitance transformations, specifically substitution of electrode-adsorbed water by gas molecules, with concomitant changes in capacitance related to both the polarity and dielectric constants of the vapor molecules tested. The C-dot-IDE gas sensor exhibited excellent selectivity, aided by application of machine learning algorithms. The capacitive C-dot-IDE sensor was employed to continuously monitor microbial proliferation, discriminating among bacteria through detection of distinctive "volatile compound fingerprint" for each bacterial species. The C-dot-IDE platform is robust, reusable, readily assembled from inexpensive building blocks and constitutes a versatile and powerful vehicle for gas sensing in general, bacterial monitoring in particular.

A hybrid electronic nose system for discrimination of pathogenic bacterial volatile compounds

A hybrid electronic nose comprising an array of three organic-inorganic nanocomposite gas sensors [zinc tetra tert-butyl phthalocyanine (ZnTTBPc), zinc tetra-phenyl porphyrin (ZnTPP), and cobalt tetraphenyl-porphyrin (CoTPP)] coupled with three commercial metal-oxide semiconductor gas sensors (TGS 2444, TGS 2603 and TGS 2620) was developed to discriminate bacterial volatile compounds. Each type of gas sensor had its own strengths and weaknesses in terms of its capability to detect complex odors from the five different bacterial species tested. Bacterial samples were controlled at a fixed initial bacterial concentration by measuring the optical density at 600 nm of the culture suspensions. A comparative evaluation of the volatile compound fingerprints from five bacterial species grown in Luria-Bertani medium was conducted to identify the optimal incubation time for detection of volatile biomarkers to discriminate among bacteria. The results suggest that the hybrid electronic nose was indeed able to discriminate among the bacterial species and culture media, with a variance based on contributions of 92.4% from PC1 and 7.2% from PC2, at an incubation time of 6 hours. Furthermore, the results of hierarchical cluster analysis showed that bacterial odor data formed two major bacterial groups, with the maximum cluster distance close to 25. Intra-group similarity was demonstrated as the two bacterial species (E. cloacae and P. aeruginosa) from among the Gram-negative bacteria had a greater similarity with a cluster distance close to 4. Finally, the minimum distance between E. cloacae and S. Typhi was approximately 1, at an equal distance from E. coli and S. aureus.

Development of a Colorimetric Sensor for Autonomous, Networked, Real-Time Application

This review describes an ongoing effort intended to develop wireless sensor networks for real-time monitoring of airborne targets across a broad area. The goal is to apply the spectrophotometric characteristics of porphyrins and metalloporphyrins in a colorimetric array for detection and discrimination of changes in the chemical composition of environmental air samples. The work includes hardware, software, and firmware design as well as development of algorithms for identification of event occurrence and discrimination of targets. Here, we describe the prototype devices and algorithms related to this effort as well as work directed at selection of indicator arrays for use with the system. Finally, we review the field trials completed with the prototype devices and discuss the outlook for further development.

Special Issue "Advanced Nanomaterials Based Gas Sensors"

During the last several years, according to the works published in research journals, many nanostructured materials have been tested as sensing materials for gas-sensing applications. This trend has been observed for both metal oxides as well as carbon-based nanomaterials. More recently, it has also been extended to other materials based on chalcogenides. The field of applications for these sensors is very wide, including air quality, industrial safety and medical diagnosis, using different transducing mechanisms. Therefore, in this Special Issue, we have put together recent advances in this area.

A phthalocyanine sensor array based on sensitivity and current changes for highly sensitive identification of three toxic gases at ppb levels

The first phthalocyanine-based sensor array by the combination of two parameters, namely current change direction and sensitivity, for accurate discrimination and wide range of detection of three toxic gases at ppb levels.

Fabrication of Hybrid Membranes Containing Nylon-11 and Organic Semiconductor Particles with Potential Applications in Molecular Electronics

Chemical degradation is a major disadvantage in the development of organic semiconductors. This work proposes the manufacture and characterization of organic semiconductor membranes in order to prevent semiconductor properties decreasing. Semiconductor membranes consisting of Nylon-11 and particles of π-conjugated molecular semiconductors were manufactured by high-vacuum evaporation followed by thermal relaxation. Initially, and with the aim of obtaining semiconductor particles, bulk heterojunction (BHJ) was carried out using green chemistry techniques between the zinc phthalocyanine (ZnPc) and the zinc hexadecafluoro-phthalocyanine (F₁₆ZnPc) as n-type molecular semiconductors with the p-type molecular semiconductor dibenzotetrathiafulvalene (DBTTF). Consequently, the π-conjugated semiconductors particles were embedded in a Nylon-11 matrix and characterized, both structurally and considering their optical and electrical properties. Thin films of these materials were manufactured in order to comparatively study the membranes and precursor semiconductor particles. The membranes presented bandgap (E_g) values that were lower than those obtained in the films, which is an indicator of an improvement in their semiconductor capacity. Finally, the membranes were subjected to accelerated lighting conditions, to determine the stability of the polymer and the operating capacity of the membrane. After fatigue conditions, the electrical behavior of the proposed semiconductor membranes remained practically unaltered; therefore, they could have potential applications in molecular electronics. The chemical stability of membranes, which did not degrade in their polymer compound, nor in the semiconductor, was monitored by IR spectroscopy.

Yeast Smell Like What They Eat: Analysis of Volatile Organic Compounds of Malassezia furfur in Growth Media Supplemented with Different Lipids

Malassezia furfur is part of the human skin microbiota. Its volatile organic compounds (VOCs) possibly contribute to the characteristic odour in humans, as well as to microbiota interaction. The aim of this study was to investigate how the lipid composition of the liquid medium influences the production of VOCs. Growth was performed in four media: (1) mDixon, (2) oleic acid (OA), (3) oleic acid + palmitic acid (OA+PA), and (4) palmitic acid (PA). The profiles of the VOCs were characterized by HS-SPME/GC-MS in the exponential and stationary phases. A total number of 61 VOCs was found in M. furfur, among which alkanes, alcohols, ketones, and furanic compounds were the most abundant. Some compounds previously reported for Malassezia (γ-dodecalactone, 3-methylbutan-1-ol, and hexan-1-ol) were also found. Through our experiments, using univariate and multivariate unsupervised (Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA)) and supervised (Projection to Latent Structures Discriminant Analysis (PLS-DA)) statistical techniques, we have proven that each tested growth medium stimulates the production of a different volatiles profile in M. furfur. Carbon dioxide, hexan-1-ol, pentyl acetate, isomer5 of methyldecane, dimethyl sulphide, undec-5-ene, isomer2 of methylundecane, isomer1 of methyldecane, and 2-methyltetrahydrofuran were established as differentiating compounds among treatments by all the techniques. The significance of our findings deserves future research to investigate if certain volatile profiles could be related to the beneficial or pathogenic role of this yeast.