Novel noninvasive identification of biomarkers by analytical profiling of chronic wounds using volatile organic compounds

No skin off your back: the sampling and extraction of sebum for metabolomics

INTRODUCTION

Sebum-based metabolomics (a subset of "sebomics") is a developing field that involves the sampling, identification, and quantification of metabolites found in human sebum. Sebum is a lipid-rich oily substance secreted by the sebaceous glands onto the skin surface for skin homeostasis, lubrication, thermoregulation, and environmental protection. Interest in sebomics has grown over the last decade due to its potential for rapid analysis following non-invasive sampling for a range of clinical and environmental applications.

OBJECTIVES

To provide an overview of various sebum sampling techniques with their associated challenges. To evaluate applications of sebum for clinical research, drug monitoring, and human biomonitoring. To provide a commentary of the opportunities of using sebum as a diagnostic biofluid in the future.

METHODS

Bibliometric analyses of selected keywords regarding skin surface analysis using the Scopus search engine from 1960 to 2022 was performed on 12th January 2023. The published literature was compartmentalised based on what the work contributed to in the following areas: the understanding about sebum, its composition, the analytical technologies used, or the purpose of use of sebum. The findings were summarised in this review.

RESULTS

Historically, about 15 methods of sampling have been used for sebum collection. The sample preparation approaches vary depending on the analytes of interest and are summarised. The use of sebum is not limited to just skin diseases or drug monitoring but also demonstrated for other systemic disease. Most of the work carried out for untargeted analysis of metabolites associated with sebum has been in the recent two decades.

CONCLUSION

Sebum has a huge potential beyond skin research and understanding how one's physiological state affects or reflects on the skin metabolome via the sebaceous glands itself or by interactions with sebaceous secretion, will open doors for simpler biomonitoring. Sebum acts as a sink to environmental metabolites and has applications awaiting to be explored, such as biosecurity, cross-border migration, localised exposure to harmful substances, and high-throughput population screening. These applications will be possible with rapid advances in volatile headspace and lipidomics method development as well as the ability of the metabolomics community to annotate unknown species better. A key issue with skin surface analysis that remains unsolved is attributing the source of the metabolites found on the skin surface before meaningful biological interpretation.

Non-invasive Sampling of Human Body Fluids Using In Vivo SPME

Noninvasive body fluids offer attractive sources to gain insights into human health. The in vivo solid-phase microextraction (SPME) technique is a fast and versatile sample preparation technique for the noninvasive sampling of human body fluids in various fields. This chapter summarizes the applications of SPME coupled with mass spectrometry (MS)-based approaches for noninvasive investigations of human body fluids, including urine, sweat, and saliva. New features of noninvasive SPME sampling and MS-based analysis are highlighted, and the prospects on their further development are also discussed.

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

Early detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization–high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient’s tailored treatment.

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Real-time mass spectrometry shows potential as a tool for microbiological diagnosis

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Bacterial volatile metabolites from 1 × 10³ CFUs are detected within minutes

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S. aureus and S. pneumoniae can be distinguished on species and even strain level

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Complex clinical samples cluster according to presence or absence of viable bacteria

Advances in non-invasive biosensing measures to monitor wound healing progression

Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed.

The Human Skin Volatolome: A Systematic Review of Untargeted Mass Spectrometry Analysis

The analysis of volatile organic compounds (VOCs) can provide important clinical information (entirely non-invasively); however, the exact extent to which VOCs from human skin can be signatures of health and disease is unknown. This systematic review summarises the published literature concerning the methodology, application, and volatile profiles of skin VOC studies. An online literature search was conducted in accordance with the preferred reporting items for systematic reviews and meta-analysis, to identify human skin VOC studies using untargeted mass spectrometry (MS) methods. The principal outcome was chemically verified VOCs detected from the skin. Each VOC was cross-referenced using the CAS number against the Human Metabolome and KEGG databases to evaluate biological origins. A total of 29 studies identified 822 skin VOCs from 935 participants. Skin VOCs were commonly sampled from the hand (n = 9) or forearm (n = 7) using an absorbent patch (n = 15) with analysis by gas chromatography MS (n = 23). Twenty-two studies profiled the skin VOCs of healthy subjects, demonstrating a volatolome consisting of aldehydes (18%), carboxylic acids (12%), alkanes (12%), fatty alcohols (9%), ketones (7%), benzenes and derivatives (6%), alkenes (2%), and menthane monoterpenoids (2%). Of the VOCs identified, 13% had putative endogenous origins, 46% had tentative exogenous origins, and 40% were metabolites from mixed metabolic pathways. This review has comprehensively profiled the human skin volatolome, demonstrating the presence of a distinct VOC signature of healthy skin, which can be used as a reference for future researchers seeking to unlock the clinical potential of skin volatolomics. As significant proportions of identified VOCs have putative exogenous origins, strategies to minimise their presence through methodological refinements and identifying confounding compounds are discussed.

Biting Innovations of Mosquito-Based Biomaterials and Medical Devices

Mosquitoes are commonly viewed as pests and deadly predators by humans. Despite this perception, investigations of their survival-based behaviors, select anatomical features, and biological composition have led to the creation of several beneficial technologies for medical applications. In this review, we briefly explore these mosquito-based innovations by discussing how unique characteristics and behaviors of mosquitoes drive the development of select biomaterials and medical devices. Mosquito-inspired microneedles have been fabricated from a variety of materials, including biocompatible metals and polymers, to mimic of the mouthparts that some mosquitoes use to bite a host with minimal injury during blood collection. The salivary components that these mosquitoes use to reduce the clotting of blood extracted during the biting process provide a rich source of anticoagulants that could potentially be integrated into blood-contacting biomaterials or administered in therapeutics to reduce the risk of thrombosis. Mosquito movement, vision, and olfaction are other behaviors that also have the potential for inspiring the development of medically relevant technologies. For instance, viscoelastic proteins that facilitate mosquito movement are being investigated for use in tissue engineering and drug delivery applications. Even the non-wetting nanostructure of a mosquito eye has inspired the creation of a robust superhydrophobic surface coating that shows promise for biomaterial and drug delivery applications. Additionally, biosensors incorporating mosquito olfactory receptors have been built to detect disease-specific volatile organic compounds. Advanced technologies derived from mosquitoes, and insects in general, form a research area that is ripe for exploration and can uncover potential in further dissecting mosquito features for the continued development of novel medical innovations.

Advanced Wound Diagnostics: Toward Transforming Wound Care into Precision Medicine

Significance: Nonhealing wounds are an ever-growing global pandemic, with mortality rates and management costs exceeding many common cancers. Although our understanding of the molecular and cellular factors driving wound healing continues to grow, standards for diagnosing and evaluating wounds remain largely subjective and experiential, whereas therapeutic strategies fail to consistently achieve closure and clinicians are challenged to deliver individualized care protocols. There is a need to apply precision medicine practices to wound care by developing evidence-based approaches, which are predictive, prescriptive, and personalized. Recent Advances: Recent developments in "advanced" wound diagnostics, namely biomarkers (proteases, acute phase reactants, volatile emissions, and more) and imaging systems (ultrasound, autofluorescence, spectral imaging, and optical coherence tomography), have begun to revolutionize our understanding of the molecular wound landscape and usher in a modern age of therapeutic strategies. Herein, biomarkers and imaging systems with the greatest evidence to support their potential clinical utility are reviewed. Critical Issues: Although many potential biomarkers have been identified and several imaging systems have been or are being developed, more high-quality randomized controlled trials are necessary to elucidate the currently questionable role that these tools are playing in altering healing dynamics or predicting wound closure within the clinical setting. Future Directions: The literature supports the need for the development of effective point-of-care wound assessment tools, such as a platform diagnostic array that is capable of measuring multiple biomarkers at once. These, along with advances in telemedicine, synthetic biology, and "smart" wearables, will pave the way for the transformation of wound care into a precision medicine. Clinical Trial Registration number: NCT03148977.

Superabsorbent charcoal dressing versus silver foam dressing in wound area reduction: a randomised controlled trial

AIM

This study aimed to compare the effect of a novel sterile polyacrylate wound pad with activated carbon cloth treatment with a standard non-adhesive hydrocellular foam dressing with silver in reducing wound area.

METHOD

A multicentre randomised controlled open-label wound-dressing trial was conducted in two wound care outpatient clinics in western Switzerland from November 2018 to March 2020.

RESULTS

A total of 77 successive patients were randomised to receive either a sterile polyacrylate wound pad with activated carbon cloth treatment (n=38) or the standard non-adhesive hydrocellular foam dressing with silver (n=39). Reduction in wound area was the primary outcome, whereas the application period of the dressing, odour, maceration and pain were the secondary outcomes. Wound area was measured at baseline and during each wound dressing change until the dressings were no longer indicated. Wound area reduced faster in the intervention group than in the control group (0.45cm² per day vs. 0.2cm² per day), although the application period was longer in the intervention group compared with the control group (9.5 days vs. 8.1 days). Maceration reduction was more pronounced in the intervention group (-2.07cm²) than in the control group (-0.71cm²). Odour, pain and infection were similar in both groups.

CONCLUSION

Sterile polyacrylate wound pad dressings with activated carbon cloth reduced the wound area, as well as the maceration area, faster than the non-adhesive hydrocellular foam dressing with silver.

Detecting bacterial infections in wounds: a review of biosensors and wearable sensors in comparison with conventional laboratory methods

Review on laboratory-based methods and biosensors and wearable sensors for detecting wound infection by aerobic and anaerobic bacteria.

Real-time detection of volatile metabolites enabling species-level discrimination of bacterial biofilms associated with wound infection

Aims

The main aim of this study was to investigate the real‐time detection of volatile metabolites for the species‐level discrimination of pathogens associated with clinically relevant wound infection, when grown in a collagen wound biofilm model.

Methods and Results

This work shows that Staphylococcus aureus, Pseudomonas aeruginosa and Streptococcus pyogenes produce a multitude of volatile compounds when grown as biofilms in a collagen‐based biofilm model. The real‐time detection of these complex volatile profiles using selected ion flow tube mass spectrometry and the use of multivariate statistical analysis on the resulting data can be used to successfully differentiate between the pathogens studied.

Conclusions

The range of bacterial volatile compounds detected between the species studied vary and are distinct. Discrimination between bacterial species using real‐time detection of volatile metabolites and multivariate statistical analysis was successfully demonstrated.

Significance and Impact of the Study

Development of rapid point‐of‐care diagnostics for wound infection would improve diagnosis and patient care. Such technological approaches would also facilitate the appropriate use of antimicrobials, minimizing the emergence of antimicrobial resistance. This study further develops the use of volatile metabolite detection as a new diagnostic approach for wound infection.

Validating Differential Volatilome Profiles in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that does not currently have a robust clinical diagnostic test. Nonmotor symptoms such as skin disorders have long since been associated with the disease, and more recently a characteristic odor emanating from the skin of people with Parkinson's has been identified. Here, dynamic head space (DHS) thermal desorption (TD) gas chromatography-mass spectrometry (GC-MS) is implemented to directly measure the volatile components of sebum on swabs sampled from people with Parkinson's-both drug naïve and those on PD medications (n = 100) and control subjects (n = 29). Supervised multivariate analyses of data showed 84.4% correct classification of PD cases using all detected volatile compounds. Variable importance in projection (VIP) scores were generated from these data, which revealed eight features with VIP > 1 and p < 0.05 which all presented a downregulation within the control cohorts. Purified standards based on previously annotated analytes of interest eicosane and octadecanal did not match to patient sample data, although multiple metabolite features are annotated with these compounds all with high spectral matches indicating the presence of a series of similar structured species. DHS-TD-GC-MS analysis of a range of lipid standards has revealed the presence of common hydrocarbon species rather than differentiated intact compounds which are hypothesized to be breakdown products of lipids. This replication study validates that a differential volatile profile between control and PD cohorts can be measured using an analytical method that measures volatile compounds directly from skin swabs.

Thriving Under Stress: Pseudomonas aeruginosa Outcompetes the Background Polymicrobial Community Under Treatment Conditions in a Novel Chronic Wound Model

In vitro infection models are important for studying the effects of antimicrobials on microbial growth and metabolism. However, many models lack important biological components that resemble the polymicrobial nature of chronic wounds or infections. In this study, we developed a perfused meat model that supports the growth of the human pathogen Pseudomonas aeruginosa in a native meat microbial background to investigate the impact of antibiotics and hydrogen peroxide on polymicrobial community growth and metabolism. P. aeruginosa plays an important role as an etiological agent involved in chronic infections and is a common opportunistic pathogen. Chemical stressors in the form of hydrogen peroxide, carbenicillin, and gentamicin were perfused through the meat with polymicrobial growth on the surface. The relative abundances of P. aeruginosa and the background microbial community were analyzed by cell viability assays, and metabolic changes of the entire community in response to different antimicrobial treatments were characterized by GC-MS analysis of volatile organic compounds. The meat background community was characterized by amplicon sequencing. Relative densities of P. aeruginosa and background microbiota were similar under control conditions. Antimicrobial stressors, even at sub-inhibitory, physiologically relevant concentrations, spurred P. aeruginosa dominance of the meat surface community. Volatile metabolite ion intensity levels showed that antibacterial treatments drive changes in microbial metabolism. The abundance of the P. aeruginosa-derived metabolite, acetophenone, remained stable with treatment, whereas the relative abundances of 2-butanone, 2-nonanone, and 2-aminoacetophenone changed in response to treatment, suggesting these could serve as biomarkers of infection. Our model recapitulates some of the physiological conditions of chronic wounds and facilitates high throughput experiments without the high cost of in vivo models. Expanded use of this perfusion model will contribute to the understanding of polymicrobial growth and metabolism in the context of chronic wounds and infections.

Volatile Cues Influence Host-Choice in Arthropod Pests

Many arthropod pests of humans and other animals select their preferred hosts by recognising volatile odour compounds contained in the hosts' 'volatilome'. Although there is prolific literature on chemical emissions from humans, published data on volatiles and vector attraction in other species are more sporadic. Despite several decades since the identification of a small number of critical volatiles underpinning specific host-vector relationships, synthetic chemicals or mixtures still largely fail to reproduce the attractiveness of natural hosts to their disease vectors. This review documents allelochemicals from non-human terrestrial animals and considers where challenges in collection and analysis have left shortfalls in animal volatilome research. A total of 1287 volatile organic compounds were identified from 141 species. Despite comparable diversity of entities in each compound class, no specific chemical is ubiquitous in all species reviewed, and over half are reported as unique to a single species. This review provides a rationale for future enquiries by highlighting research gaps, such as disregard for the contribution of breath volatiles to the whole animal volatilome and evaluating the role of allomones as vector deterrents. New opportunities to improve vector surveillance and disrupt disease transmission may be unveiled by understanding the host-associated stimuli that drive vector-host interactions.

The Detection of Wound Infection by Ion Mobility Chemical Analysis

Surgical site infection represents a large burden of care in the National Health Service. Current methods for diagnosis include a subjective clinical assessment and wound swab culture that may take several days to return a result. Both techniques are potentially unreliable and result in delays in using targeted antibiotics. Volatile organic compounds (VOCs) are produced by micro-organisms such as those present in an infected wound. This study describes the use of a device to differentiate VOCs produced by an infected wound vs. colonised wound. Malodourous wound dressings were collected from patients, these were a mix of post-operative wounds and vascular leg ulcers. Wound microbiology swabs were taken and antibiotics commenced as clinically appropriate. A control group of soiled, but not malodorous wound dressings were collected from patients who had a split skin graft (SSG) donor site. The analyser used was a G.A.S. GC-IMS. The results from the samples had a sensitivity of 100% and a specificity of 88%, with a positive predictive value of 90%. An area under the curve (AUC) of 91% demonstrates an excellent ability to discriminate those with an infected wound from those without. VOC detection using GC-IMS has the potential to serve as a diagnostic tool for the differentiation of infected and non-infected wounds and facilitate the treatment of wound infections that is cost effective, non-invasive, acceptable to patients, portable, and reliable.

A microbiome and metabolomic signature of phases of cutaneous healing identified by profiling sequential acute wounds of human skin: An exploratory study

Profiling skin microbiome and metabolome has been utilised to gain further insight into wound healing processes. The aims of this multi-part temporal study in 11 volunteers were to analytically profile the dynamic wound tissue and headspace metabolome and sequence microbial communities in acute wound healing at days 0, 7, 14, 21 and 28, and to investigate their relationship to wound healing, using non-invasive quantitative devices. Metabolites were obtained using tissue extraction, sorbent and polydimethylsiloxane patches and analysed using GCMS. PCA of wound tissue metabolome clearly separated time points with 10 metabolites of 346 being involved in separation. Analysis of variance-simultaneous component analysis identified a statistical difference between the wound headspace metabolome, sites (P = 0.0024) and time points (P<0.0001), with 10 out of the 129 metabolites measured involved with this separation between sites and time points. A reciprocal relationship between Staphylococcus spp. and Propionibacterium spp. was observed at day 21 (P<0.05) with a statistical correlation between collagen and Propionibacterium (r = 0.417; P = 0.038) and Staphylococcus (r = -0.434; P = 0.03). Procrustes analysis showed a statistically significant similarity between wound headspace and tissue metabolome with non-invasive wound devices. This exploratory study demonstrates the temporal and dynamic nature of acute wound metabolome and microbiome presenting a novel class of biomarkers that correspond to wound healing, with further confirmatory studies now necessary.

A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose

A medical electronic nose (e-nose) with 31 gas sensors is used for wound infection detection by analyzing the bacterial metabolites. In practical applications, the prediction accuracy drops dramatically when the prediction model established by laboratory data is directly used in human clinical samples. This is a key issue for medical e-nose which should be more worthy of attention. The host (carrier) of bacteria can be the culture solution, the animal wound, or the human wound. As well, the bacterial culture solution or animals (such as: mice, rabbits, etc.) obtained easily are usually used as experimental subjects to collect sufficient sensor array data to establish the robust predictive model, but it brings another serious interference problem at the same time. Different carriers have different background interferences, therefore the distribution of data collected under different carriers is different, which will make a certain impact on the recognition accuracy in the detection of human wound infection. This type of interference problem is called "transfer caused by different sample carriers". In this paper, a novel subspace alignment-based interference suppression (SAIS) method with domain correction capability is proposed to solve this interference problem. The subspace is the part of space whose dimension is smaller than the whole space, and it has some specific properties. In this method, first the subspaces of different data domains are gotten, and then one subspace is aligned to another subspace, thereby the problem of different distributions between two domains is solved. From experimental results, it can be found that the recognition accuracy of the infected rat samples increases from 29.18% (there is no interference suppression) to 82.55% (interference suppress by SAIS).

Factors influencing breath analysis results in patients with diabetes mellitus

Breath analysis is used to detect the composition of exhaled gas. As a quick and non-invasive detection method, breath analysis provides deep insights into the progression of various kinds of diseases, especially those with metabolism disorders. Abundant information on volatile compounds in diabetic patients has been studied in numerous articles in the literature. However, exhaled gas in diabetic patients can be altered by various complications. So far, little attention has been paid to this alteration. In our paper, we found that under air pollution conditions, diabetic patients exhale more nitric oxide. Diabetic patients with heart failure exhale more acetone than those without heart failure. After ¹³C-labeled glucose intake, patients infected with Helicobacter pylori exhaled more ¹³C and less ¹⁸O than those without infection. Exhalation with chronic kidney disease changes volatile organic compounds on a large scale. Diabetic patients with ketoacidosis exhale more acetone than those without ketoacidosis. Some specific volatile organic compounds also emanate from diabetic feet. By monitoring breath frequency, diabetic patients with obstructive sleep apnea syndrome exhibit a unique breath pattern and rhythm as compared with other diabetic patients, and sleep apnea is prevalent among diabetic patients. In addition to clinical findings, we analyzed the underlying mechanisms at the levels of molecules, cells and whole bodies, and provided suggestions for further studies.

A review of developments and applications of thin-film microextraction coupled to surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) greatly expands the applications of Raman spectroscopy and is a promising technique for food safety, environmental analysis, and public safety. Thin-film microextraction (TFME) provides an efficient sample preparation method for SERS to improve its selectivity and detection efficiency. This review comprehensively describes the development and applications of SERS and TFME, including the history, mechanisim, and active substrate of SERS and the theory, device, forms, and practical applications of TFME. The applications of TFME-SERS in food safety and environment monitoring are discussed, which could improve their advantages. TFME extracts and enriches the target analytes to eliminate the interfering substance, providing a facial way for SERS to analyze the target analytes in complex matrices. The development of TFME-SERS technology not only expands the application range of TFME, but greatly improves the anti-interference ability and detection sensitivity of SERS. Thus, the established methods are fast, convenient, and highly sensitive. This technology is potential to be applied in the on-site and real-time detection.

Use of voltammetric analysis for fast and objective discrimination of the etiology, evolution, and bacterial infection of lower limb ulcers

The timely recognition of leg ulcers (LU) etiology and infection is pivotal to optimize management and accelerate healing. The objective of this proof-of-concept study was to test the diagnostic performance of voltammetric analysis (VA) on ulcer exudate to identify LU etiology, infection, and predict clinical course. We enrolled 25 patients aged ≥60 years, affected by 42 venous/arterial LU. Clinical examination (Leg Ulcer Measurement Tool score, LUMT), swab culture, and VA were performed at baseline and 30 days. The ability of VA to predict outcomes was tested using partial least square-discrimination analysis. Mean age was 75 years (SD 11.1), 9/25 were male. The accuracy, sensitivity, and specificity vs. etiology were 97.4, 100%, and 94.1%, respectively; the corresponding figures were 95.2%, 100%, 88.9%, for infection and 94%, 84.6%, 100% for predicted objective LUMT worsening. VA is a promising diagnostic/prognostic tool for management of LU that may allow a more timely targeted therapy.

Wound odor: current methods of treatment and need for objective measures

Chronic wounds are an enormous burden to society, costing billions of dollars annually in the USA alone. Despite the extensive research into methods to heal chronic wounds, many remain unhealed for months to years. There is a need to focus on patient reported outcomes to improve quality of life in patients with non-healing wounds. Wound odor has a significant impact on patient quality of life; however, relatively little information is available on the management of wound odor. We review the current data available on wound odor and discuss the need for standardized objective measures of odor to improve research quality. An independent search of the PubMed and Embase databases was conducted using combinations of the following words or phrases: "wounds," "chronic wounds," "diabetic ulcers," "venous leg ulcers (VLUs)," "malignant ulcers," "odor," "odour," "smell," "malodor," "artificial olfaction," "electronic nose," and "e-nose." Article references were also searched for significance. There are few overall studies on wound odor, and fewer randomized controlled trials. Current trials on odor have consistent weaknesses such as subjective measures and poor methodology. No single odor treatment modality has been demonstrated to be widely effective for wound odor or superior to other methods. Future research should incorporate objective measures of odor such as electronic noses into clinical trials.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

Validation of biofilm formation on human skin wound models and demonstration of clinically translatable bacteria-specific volatile signatures

Biofilms are major contributors to delayed wound healing and there is a need for clinically relevant experimental models to assess theranostics. Microorganisms release volatile organic compounds (VOCs) and the ability to identify these in infected cutaneous wounds could lead to efficient non-invasive diagnosis. The aims here were to develop and assess bacterial biofilm formation and identify their VOC profiles in an in vitro model and validate in human ex vivo incisional and excisional cutaneous wound models. Biofilm development was assessed using multiple microscopy techniques with biofilm-forming deficient controls and quantified using metabolic and biomass assays; and VOC production measured by gas chromatography-mass spectrometry. The production of most VOCs was affected by biofilm development and model used. Some VOCs were specific either for planktonic or biofilm growth. The relative abundance of some VOCs was significantly increased or decreased by biofilm growth phase (P < 0.05). Some Staphylococcus aureus and Pseudomonas aeruginosa VOCs correlated with biofilm metabolic activity and biomass (R ≤ −0.5; ≥0.5). We present for the first time bacterial biofilm formation in human ex vivo cutaneous wound models and their specific VOC profiles. These models provide a vehicle for human skin-relevant biofilm studies and VOC detection has potential clinical translatability in efficient non-invasive diagnosis of wound infection.

Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection

For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning combined with sparse autoencoder and radial basis function (RBF) into the field. Self-taught learning is a kind of transfer learning that can transfer knowledge from other fields to target fields, can solve such problems that labeled data (target fields) and unlabeled data (other fields) do not share the same class labels, even if they are from entirely different distribution. In our paper, we obtain numerous cheap unlabeled pollutant gas samples (benzene, formaldehyde, acetone and ethylalcohol); however, labeled wound infection samples are hard to gain. Thus, we pose self-taught learning to utilize these gas samples, obtaining a basis vector θ. Then, using the basis vector θ, we reconstruct the new representation of wound infection samples under sparsity constraint, which is the input of classifiers. We compare RBF with partial least squares discriminant analysis (PLSDA), and reach a conclusion that the performance of RBF is superior to others. We also change the dimension of our data set and the quantity of unlabeled data to search the input matrix that produces the highest accuracy.

Development of sampling method and chromatographic analysis of volatile organic compounds emitted from human skin

Aim: The studies on volatile organic compounds emitted from skin are an interest for chemists, biologists and physicians due to their role in development of different scientific areas, including medical diagnostics, forensic medicine and the perfume design. This paper presents a proposal of two sampling methods applied to skin odor collection: the first one uses a bag of cellulose film, the second one, using cellulose sachets filled with active carbon. Materials & methods: Volatile organic compounds were adsorbed on carbon sorbent, removed via thermal desorption and analyzed using gas chromatograph with mass spectrometer. Results: The first sampling method allowed identification of more compounds (52) comparing to the second one (30). Quantitative analyses for acetone, butanal, pentanal and hexanal were done. Conclusion: The skin odor sampling method using a bag of cellulose film, allowed the identification of many more compounds when compared with the method using a sachet filled with active carbon.

A Comprehensive Review of Topical Odor-Controlling Treatment Options for Chronic Wounds

The process of wound healing is often accompanied by bacterial infection or critical colonization, resulting in protracted inflammation, delayed reepithelization, and production of pungent odors. The malodor produced by these wounds may lower health-related quality of life and produce psychological discomfort and social isolation. Current management focuses on reducing bacterial activity within the wound site and absorbing malodorous gases. For example, charcoal-based materials have been incorporated into dressing for direct adsorption of the responsible gases. In addition, multiple topical agents, including silver, iodine, honey, sugar, and essential oils, have been suggested for incorporation into dressings in an attempt to control the underlying bacterial infection. This review describes options for controlling malodor in chronic wounds, the benefits and drawbacks of each topical agent, and their mode of action. We also discuss the use of subjective odor evaluation techniques to assess the efficacy of odor-controlling therapies. The perspectives of employing novel biomaterials and technologies for wound odor management are also presented.

A correlated information removing based interference suppression technique in electronic nose for detection of bacteria

A sensor array with 30 gas sensors is used in the electronic nose (e-nose) for bacteria detection in wound infection. However, the interference is an urgent problem in e-nose, since it would impact on the detection of target due to the cross-sensitivity of gas sensors, especially the background interference caused by carrier gas. The related methods to suppress the background interference are independent component analysis and orthogonal signal correction algorithm which are unreasonable, because it is difficult to obtain the so-called reference vector in complex real-world scenario. Consider that the sampling process of pump suction is divided into three parts: baseline collecting, sample collecting and system purging. In the case of stabilized carrier gas, the information in baseline can be fully used to suppress the interference in sampling stage. Thus a novel and effective correlated information removing based interference suppression (CIRIS) method is proposed. Specifically, the principle of this method is to suppress the interference of the sampling stage by removing the information correlated with baseline samples. Experimental results show that the proposed method (CIRIS with principal component analysis used to calculate the projection matrix) is significantly effective for interference suppression in e-nose.

Analytical methodologies for broad metabolite coverage of exhaled breath condensate

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.

5th Congress of WUWHS Abstract book Florence, Italy September 25–29 2016

The abstract book contains the abstracts of keynote lectures, focus sessions, symposia, workshops, AIUC annual meeting, AISLEC annual meeting, EPUAP annual meeting, ETRS special session, sponsor symposia, oral presentations, poster presentations and the subject index.

A rabbit model for assessment of volatile metabolite changes observed from skin: a pressure ulcer case study

Human skin presents a large, easily accessible matrix that is potentially useful for diagnostic applications based on whole body metabolite changes-some of which will be volatile and detected using minimally invasive tools. Unfortunately, identifying skin biomarkers that can be reliably linked to a particular condition is challenging due to a large variability of genetics, dietary intake, and environmental exposures within human populations. This leads to a paucity of clinically validated volatile skin biomarker compounds. Animal models present a very convenient and attractive way to circumvent many of the variability issues. The rabbit (Leporidae) is a potentially logistically useful model to study the skin metabolome, but very limited knowledge of its skin metabolites exists. Here we present the first comprehensive assessment of the volatile fraction of rabbit skin metabolites using polydimethylsiloxane sorbent patch sampling in conjunction with gas chromatography/mass spectrometry. A collection of compounds that are secreted from rabbit skin was documented, and predominantly acyclic long-chain alkyls and alcohols were detected. We then utilized this animal model to study differences between intact skin and skin with early pressure ulcers, as the latter are a major problem in intensive care units. Four New Zealand female white rabbits underwent ulcer formation on one ear with the other ear as a control. Early-stage ulcers were created with neodymium magnets. Histologic analysis showed acute heterophilic dermatitis, edema, and micro-hemorrhage on the ulcerated ears with normal findings on the control ears. The metabolomic analysis revealed subtle but noticeable differences, with several compounds associated with the oxidative stress-related degradation of lipids found to be present in greater abundances in ulcerated ears. The metabolomic findings correlate with histologic evidence of early-stage ulcers. We postulate that the Leporidae model recapitulated the vascular changes associated with ulcer formation. This study illustrates the potential usefulness of the Leporidae model for skin metabolome studies. Additionally, skin metabolome analysis may enhance an understanding of non-skin sources such as urine or breath.

A Novel Pre-Processing Technique for Original Feature Matrix of Electronic Nose Based on Supervised Locality Preserving Projections

An electronic nose (E-nose) consisting of 14 metal oxide gas sensors and one electronic chemical gas sensor has been constructed to identify four different classes of wound infection. However, the classification results of the E-nose are not ideal if the original feature matrix containing the maximum steady-state response value of sensors is processed by the classifier directly, so a novel pre-processing technique based on supervised locality preserving projections (SLPP) is proposed in this paper to process the original feature matrix before it is put into the classifier to improve the performance of the E-nose. SLPP is good at finding and keeping the nonlinear structure of data; furthermore, it can provide an explicit mapping expression which is unreachable by the traditional manifold learning methods. Additionally, some effective optimization methods are found by us to optimize the parameters of SLPP and the classifier. Experimental results prove that the classification accuracy of support vector machine (SVM combined with the data pre-processed by SLPP outperforms other considered methods. All results make it clear that SLPP has a better performance in processing the original feature matrix of the E-nose.

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

The detection of many diseases is missed because of delayed diagnoses or the low efficacy of some treatments. This emphasizes the urgent need for inexpensive and minimally invasive technologies that would allow efficient early detection, stratifying the population for personalized therapy, and improving the efficacy of rapid bed-side assessment of treatment. An emerging approach that has a high potential to fulfill these needs is based on so-called "volatolomics", namely, chemical processes involving profiles of highly volatile organic compounds (VOCs) emitted from body fluids, including breath, skin, urine and blood. This article presents a didactic review of some of the main advances related to the use of nanomaterial-based solid-state and flexible sensors, and related artificially intelligent sensing arrays for the detection and monitoring of disease with volatolomics. The article attempts to review the technological gaps and confounding factors related to VOC testing. Different ways to choose nanomaterial-based sensors are discussed, while considering the profiles of targeted volatile markers and possible limitations of applying the sensing approach. Perspectives for taking volatolomics to a new level in the field of diagnostics are highlighted.

In vivo and ex vivo SPME: a low invasive sampling and sample preparation tool in clinical bioanalysis

Solid phase microextraction (SPME) is well-established technology in bioanalysis. Current review discusses the features of SPME, which determine the non- or low-invasiveness of the method in biomedical analysis. In the first section we analyze the factors, which have significant influence on the SPME sampling device performance in the view of sampling safety and efficiency. In the later sections applicability of various SPME approaches for analysis of easily accessible samples routinely used for analysis (e.g., urine, blood) as well as limited availability samples (tissues) is discussed. Moreover, the examples of sampling alternative matrices such as hair, saliva, sweat or breath are presented. The advantages and limitation of the technology in the view of future development of SPME are also reviewed.

Clinical application of volatile organic compound analysis for detecting infectious diseases

This review article introduces the significance of testing of volatile organic compounds (VOCs) in clinical samples and summarizes important features of some of the technologies. Compared to other human diseases such as cancer, studies on VOC analysis in cases of infectious diseases are limited. Here, we have described results of studies which have used some of the appropriate technologies to evaluate VOC biomarkers and biomarker profiles associated with infections. The publications reviewed include important infections of the respiratory tract, gastrointestinal tract, urinary tract, and nasal cavity. The results highlight the use of VOC biomarker profiles resulting from certain infectious diseases in discriminating between infected and healthy subjects. Infection-related VOC profiles measured in exhaled breath as well as from headspaces of feces or urine samples are a source of information with respect to disease detection. The volatiles emitted in clinical matrices may on the one hand represent metabolites of the infecting pathogen or on the other hand reflect pathogen-induced host responses or, indeed, a combination of both. Because exhaled-breath samples are easy to collect and online instruments are commercially available, VOC analysis in exhaled breath appears to be a promising tool for noninvasive detection and monitoring of infectious diseases.

High throughput volatile fatty acid skin metabolite profiling by thermal desorption secondary electrospray ionisation mass spectrometry

Global VOC skin metabolite profiling. Thermal desorption secondary electrospray ionisation time-of-flight mass spectrometry classifies skin odour phenotypes by targeted volatile fatty analysis. Examination of the mass spectra reveals the potential for global metabolic studies.

Noninvasive analysis of volatile biomarkers in human emanations for health and early disease diagnosis

Early disease diagnosis is crucial for human healthcare and successful therapy. Since any changes in homeostatic balance can alter human emanations, the components of breath exhalations and skin emissions may be diagnostic biomarkers for various diseases and metabolic disorders. Since hundreds of endogenous and exogenous volatile organic compounds (VOCs) are released from the human body, analysis of these VOCs may be a noninvasive, painless, and easy diagnostic tool. Sampling and preconcentration by sorbent tubes/traps and solid-phase microextraction, in combination with GC or GC–MS, are usually used to analyze VOCs. In addition, GC–MS-olfactometry is useful for simultaneous analysis of odorants and odor quality. Direct MS techniques are also useful for the online real-time detection of VOCs. This review focuses on recent developments in sampling and analysis of volatile biomarkers in human odors and/or emanations, and discusses future use of VOC analysis.

Cellular events and biomarkers of wound healing

Researchers have identified several of the cellular events associated with wound healing. Platelets, neutrophils, macrophages, and fibroblasts primarily contribute to the process. They release cytokines including interleukins (ILs) and TNF-α, and growth factors, of which platelet-derived growth factor (PDGF) is perhaps the most important. The cytokines and growth factors manipulate the inflammatory phase of healing. Cytokines are chemotactic for white cells and fibroblasts, while the growth factors initiate fibroblast and keratinocyte proliferation. Inflammation is followed by the proliferation of fibroblasts, which lay down the extracellular matrix. Simultaneously, various white cells and other connective tissue cells release both the matrix metalloproteinases (MMPs) and the tissue inhibitors of these metalloproteinases (TIMPs). MMPs remove damaged structural proteins such as collagen, while the fibroblasts lay down fresh extracellular matrix proteins. Fluid collected from acute, healing wounds contains growth factors, and stimulates fibroblast proliferation, but fluid collected from chronic, nonhealing wounds does not. Fibroblasts from chronic wounds do not respond to chronic wound fluid, probably because the fibroblasts of these wounds have lost the receptors that respond to cytokines and growth factors. Nonhealing wounds contain high levels of IL1, IL6, and MMPs, and an abnormally high MMP/TIMP ratio. Clinical examination of wounds inconsistently predicts which wounds will heal when procedures like secondary closure are planned. Surgeons therefore hope that these chemicals can be used as biomarkers of wounds which have impaired ability to heal. There is also evidence that the application of growth factors like PDGF will help the healing of chronic, nonhealing wounds.

In vivo solid-phase microextraction for tissue bioanalysis

Conventional in vitro or ex vivo bioanalytical quantitative sample preparation methods for the determination of compounds in biological tissues are often coupled with challenges in obtaining an assay representative of the system of interest. The rising interest in in vivo microsampling bioanalytical methods is due to the unique advantages they offer over their in vitro counterparts. In vivo solid-phase microextraction (SPME), a diffusion-based microsampling tool, has been successfully applied in recent studies to various biological systems. This review presents recent trends in tissue bioanalysis using in vivo SPME as a sample preparation tool. Efforts were made to discuss the various bioapplications of the method while highlighting possible strategies for improved sensitivity where needed. In vivo SPME devices currently employed for the various applications have also been described. In addition, we highlight selectivity of a new class of biocompatible coatings that can potentially improve the coverage of metabolites for untargeted metabolomics.