Inflammatory Biomarkers in Exhaled Breath Condensate: A Systematic Review

Worse pulmonary function in association with cumulative exposure to nanomaterials. Hints of a mediation effect via pulmonary inflammation

BACKGROUND

Today, nanomaterials are broadly used in a wide range of industrial applications. Such large utilization and the limited knowledge on to the possible health effects have raised concerns about potential consequences on human health and safety, beyond the environmental burden. Given that inhalation is the main exposure route, workers exposed to nanomaterials might be at risk of occurrence of respiratory morbidity and/or reduced pulmonary function. However, epidemiological evidence regarding the association between cumulative exposure to nanomaterials and respiratory health is still scarce. This study focused on the association between cumulative exposure to nanomaterials and pulmonary function among 136 workers enrolled in the framework of the European multicentric NanoExplore project.

RESULTS

Our findings suggest that, independently of lifelong tobacco smoking, ethnicity, age, sex, body mass index and physical activity habits, 10-year cumulative exposure to nanomaterials is associated to worse FEV1 and FEF25 - 75%, which might be consistent with the involvement of both large and small airway components and early signs of airflow obstruction. We further explored the hypothesis of a mediating effect via airway inflammation, assessed by interleukin (IL-)10, IL-1β and Tumor Necrosis Factor alpha (TNF-α), all quantified in the Exhaled Breath Condensate of workers. The mediation analysis results suggest that IL-10, TNF-α and their ratio (i.e., anti-pro inflammatory ratio) may fully mediate the negative association between cumulative exposure to nanomaterials and the FEV1/FVC ratio. This pattern was not observed for other pulmonary function parameters.

CONCLUSIONS

Safeguarding the respiratory health of workers exposed to nanomaterials should be of primary importance. The observed association between cumulative exposure to nanomaterials and worse pulmonary function parameters underscores the importance of implementing adequate protective measures in the nanocomposite sector. The mitigation of harmful exposures may ensure that workers can continue to contribute productively to their workplaces while preserving their respiratory health over time.

Assessing the inhaled dose of nanomaterials by nanoparticle tracking analysis (NTA) of exhaled breath condensate (EBC) and its relationship with lung inflammatory biomarkers

The widespread and increasing use of nanomaterials has resulted in a higher likelihood of exposure by inhalation for nanotechnology workers. However, tracking the internal dose of nanoparticles deposited at the airways level, is still challenging. To assess the suitability of particle number concentration determination as biomarker of internal dose, we carried out a cross sectional investigation involving 80 workers handling nanomaterials. External exposure was characterized by portable counters of particles DISCminiTM (Testo, DE), allowing to categorize 51 workers as exposed and 29 as non-exposed (NE) to nanoparticles. Each subject filled in a questionnaire reporting working practices and health status. Exhaled breath condensate was collected and analysed for the number of particles/ml as well as for inflammatory biomarkers. A clear-cut relationship between the number of airborne particles in the nano-size range determined by the particle counters and the particle concentration in exhaled breath condensate (EBC) was apparent. Moreover, inflammatory cytokines (IL-1β, IL-10, and TNF-α) measured in EBC, were significantly higher in the exposed subjects as compared to not exposed. Finally, significant correlations were found between external exposure, the number concentration of particles measured by the nanoparticle tracking analysis (NTA) and inflammatory cytokines. As a whole, the present study, suggests that NTA can be regarded as a reliable tool to assess the inhaled dose of particles and that this dose can effectively elicit inflammatory effects.

Occupational Exposure to Metal-Based Nanomaterials: A Possible Relationship between Chemical Composition and Oxidative Stress Biomarkers

Nanomaterials (NMs) are in high demand for a wide range of practical applications; however, comprehensively understanding the toxicity of these materials is a complex challenge, due to the limited availability of epidemiological evidence on the human health effects arising from workplace exposures. The aim of this work is to assess whether and how urinary metal concentrations could be reliable and useful in NM biomonitoring. In the framework of "NanoExplore Project" [EU LIFE17 Grant ENV/GR/000285], 43 not-exposed subjects and 40 exposed workers were recruited to measure exposure to NMs (PCN and LDSA) in the proximity of the workstations and biological biomarkers (urinary metal concentrations-Aluminum (Al), Silica (Si), Titanium (Ti), and Chromium (Cr); urinary OS biomarkers-TAP, Isop, and MDA). The results showed that Si and Ti were directly associated with NM exposure (both PCN and LDSA), as well as with OS biomarkers, especially in exposed workers. Moreover, the mediation analyses showed that Si could account for about 2.8% in the relationship between LDSA and OS biomarkers, possibly by decreasing OS antioxidant defenses in exposed people. In conclusion, our study provides evidence that occupational exposure to mixtures containing NMs can represent an underestimated hazard for exposed people, increasing the body burden and the oxidative balance.

Intranasal PAMAM-G3 scavenges cell-free DNA attenuating the allergic airway inflammation

Allergic airway inflammation (AAI), including allergic rhinitis (AR) and allergic asthma, is driven by epithelial barrier dysfunction and type 2 inflammation. However, the underlying mechanism remains uncertain and available treatments are constrained. Consequently, we aim to explore the role of cell-free DNA (cfDNA) in AAI and assess the potential alleviating effects of cationic polymers (CPs) through cfDNA elimination. Levels of cfDNA were evaluated in AR patients, allergen-stimulated human bronchial epithelium (BEAS-2B cells) and primary human nasal epithelium from both AR and healthy control (HC), and AAI murine model. Polyamidoamine dendrimers-generation 3 (PAMAM-G3), a classic type of cationic polymers, were applied to investigate whether the clearance of cfDNA could ameliorate airway epithelial dysfunction and inhibit AAI. The levels of cfDNA in the plasma and nasal secretion from AR were higher than those from HC (P < 0.05). Additionally, cfDNA levels in the exhaled breath condensate (EBC) were positively correlated with Interleukin (IL)-5 levels in EBC (R = 0.4191, P = 0.0001). Plasma cfDNA levels negatively correlated with the duration of allergen immunotherapy treatment (R = -0.4297, P = 0.006). Allergen stimulated cfDNA secretion in vitro (P < 0.001) and in vivo (P < 0.0001), which could be effectively scavenged with PAMAM-G3. The application of PAMAM-G3 inhibited epithelial barrier dysfunction in vitro and attenuated the development of AAI in vivo. This study elucidates that cfDNA, a promising biomarker for monitoring disease severity, aggravates AAI and the application of intranasal PAMAM-G3 could potentially be a novel therapeutic intervention for AAI. Allergen stimulates the secretion of cell-free DNA (cfDNA) in both human and mouse airway. Intranasal polyamidoamine dendrimers-generation 3 (PAMAM-G3) scavenges cfDNA and alleviates allergic airway inflammation.

New perspectives on 'Breathomics': metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS

Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. "Breathomics" as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath.

Noninvasive Diabetes Detection through Human Breath Using TinyML-Powered E-Nose

Volatile organic compounds (VOCs) in exhaled human breath serve as pivotal biomarkers for disease identification and medical diagnostics. In the context of diabetes mellitus, the noninvasive detection of acetone, a primary biomarker using electronic noses (e-noses), has gained significant attention. However, employing e-noses requires pre-trained algorithms for precise diabetes detection, often requiring a computer with a programming environment to classify newly acquired data. This study focuses on the development of an embedded system integrating Tiny Machine Learning (TinyML) and an e-nose equipped with Metal Oxide Semiconductor (MOS) sensors for real-time diabetes detection. The study encompassed 44 individuals, comprising 22 healthy individuals and 22 diagnosed with various types of diabetes mellitus. Test results highlight the XGBoost Machine Learning algorithm's achievement of 95% detection accuracy. Additionally, the integration of deep learning algorithms, particularly deep neural networks (DNNs) and one-dimensional convolutional neural network (1D-CNN), yielded a detection efficacy of 94.44%. These outcomes underscore the potency of combining e-noses with TinyML in embedded systems, offering a noninvasive approach for diabetes mellitus detection.

Phospholipid chlorohydrins as chlorine exposure biomarkers in a large animal model

Chlorine is a toxic industrial chemical that has been used as a chemical weapon in recent armed conflicts. Confirming human exposure to chlorine has proven challenging, and there is currently no established method for analyzing human biomedical samples to unambiguously verify chlorine exposure. In this study, two chlorine-specific biomarkers: palmitoyl-oleoyl phosphatidylglycerol chlorohydrin (POPG-HOCl) and the lipid derivative oleoyl ethanolamide chlorohydrin (OEA-HOCl) are shown in bronchoalveolar lavage fluid (BALF) samples from spontaneously breathing pigs after chlorine exposure. These biomarkers are formed by the chemical reaction of chlorine with unsaturated phospholipids found in the pulmonary surfactant, which is present at the gas-liquid interface within the lung alveoli. Our results strongly suggest that lipid chlorohydrins are promising candidate biomarkers in the development of a verification method for chlorine exposure. The establishment of verified methods capable of confirming the illicit use of toxic industrial chemicals is crucial for upholding the principles of the Chemical Weapons Convention (CWC) and enforcing the ban on chemical weapons. This study represents the first published dataset in BALF revealing chlorine biomarkers detected in a large animal. Furthermore, these biomarkers are distinct in that they originate from molecular chlorine rather than hypochlorous acid.

Biomarkers of oxidative stress, inflammation, and genotoxicity to assess exposure to micro- and nanoplastics. A literature review

The increased awareness about possible health effects arising from micro- and nanoplastics (MNPs) pollution is driving a huge amount of studies. Many international efforts are in place to better understand and characterize the hazard of MNPs present in the environment. The literature search was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology in two different databases (PubMed and Embase). The selection of articles was carried out blind, screening titles and abstracts according to inclusion and exclusion criteria. In general, these studies rely on the methodology already in use for assessing hazard from nanomaterials and particles of concern. However, only a limited number of studies have so far directly measured human exposure to MNPs and examined the relationship between such exposure and its impact on human health. This review aims to provide an overview of the current state of research on biomarkers of oxidative stress, inflammation, and genotoxicity that have been explored in relation to MNPs exposure, using human, cellular, animal, and plant models. Both in-vitro and in-vivo models suggest an increased level of oxidative stress and inflammation as the main mechanism of action (MOA) leading to adverse effects such as chronic inflammation, immunotoxicity and genotoxicity. With the identification of such biological endpoints, representing critical key initiating events (KIEs) towards adaptive or adverse outcomes, it is possible to identify a panel of surrogate biomarkers to be applied and validated especially in occupational settings, where higher levels of exposure may occur.

MEASURE: Multiplex Exhaled Breath Condensate - Scanning Using Rapid Electro-Analytics

Exhaled breath condensate is an emerging source of inflammatory biomarkers suitable for the noninvasive detection of respiratory disorders. Current gold standard methods are highly invasive and pose challenges in sample collection during airway inflammation monitoring. Cytokine biomarkers are detectable in EBC at increased or decreased concentrations. IL-6, IL-1β, IL-8, and hs-CRP are characteristic biomarkers identified in respiratory disorders. We have demonstrated the promising outcomes of a 16-plexed electrochemical platform - READ 2.0 for the multiplexed detection of characteristic biomarkers in EBC. The sensor demonstrates dynamic ranges of 1-243 pg/mL with a lower detection limit of 1 pg/mL for IL-6 and IL-1β, while the detection range and limit of detection for IL-8 and hs-CRP is 1-150 pg/mL and 3 pg/mL, respectively. The detection accuracies for the biomarkers are in the range of ∼85 ± 15% to ∼100 ± 10%. The sensor shows a nonspecific response to similar cross-reacting biomarkers. Analytical validation of the sensor with ELISA as the standard reference generated a correlation of R2 > 0.96 and mean biases of 10.9, 3.5, 17.4, and 3.9 pg/mL between the two methods for IL-6, IL-1β, IL-8, and hs-CRP, respectively. The precision of the sensor in detecting low biomarker concentrations yields a %CV of <7%. The variation in the sensor's response on repeat EBC sample measurements and within a 6 h duration is less than 10%. The READ 2.0 platform shows a promise that EBC-based biomarker detection can prove to be vital in predicting the severity and survival rates of respiratory disorders and serve as a reference point for monitoring EBC-based biomarkers.

Biomarkers of nitrosative stress in exhaled breath condensate and serum among patients with cystic fibrosis

PURPOSE

The measurement of biomarkers in exhaled breath condensate (EBC) offers a non-invasive way to assess airway disease and can be easily done in a clinical setting among patients with cystic fibrosis (CF). The role of oxidative and nitrosative stress in the complex pathophysiology of CF is widely accepted and biomarkers of oxidative and nitrosative stress can be measured in the serum and EBC. To our knowledge, this is the first study to assess markers of nitrosative stress in EBC and serum, collected simultaneously from the CF patients.

PATIENTS AND METHODS

Paired EBC and serum samples were collected from 36 stable patients with CF and 14 healthy controls. Markers of nitrosative stress ‒ 3-nitrotyrosine and nitrate/nitrite were measured in the EBC and serum using an enzyme-linked immunosorbent assay.

RESULTS

We found no differences in 3-nitrotyrosine and nitrate/nitrite in the EBC of patients with CF as compared to healthy controls (125.37 ​± ​3.29 vs. 126.24 ​± ​2.21 ​nmol/L, p ​= ​0.218; 12.66 ​± ​7.23 vs. 8.79 ​± ​4.83 ​μmol/L, p ​= ​0.133, respectively). Furthermore, 3-nitrotyrosine and nitrate/nitrite were significantly higher in the serum of patients with CF as compared to the healthy controls (0.13 ​± ​0.02 vs. 0.11 ​± ​0.01 ​nmol/mg protein, p ​= ​0.003; 70.78 ​± ​22.55 vs. 53.08 ​± ​8.5 ​μmol/L, p ​= ​0.009, respectively). No correlations were found between the markers determined in the EBC and serum.

CONCLUSIONS

The results of the EBC nitrosative stress biomarkers should be interpreted with caution, especially in patients with stable disease, as the EBC values may be independent on levels of circulating markers that are elevated in the serum of patients with stable CF.

Beta-Lactam Antibiotics Can Be Measured in the Exhaled Breath Condensate in Mechanically Ventilated Patients: A Pilot Study

Different techniques have been proposed to measure antibiotic levels within the lung parenchyma; however, their use is limited because they are invasive and associated with adverse effects. We explore whether beta-lactam antibiotics could be measured in exhaled breath condensate collected from heat and moisture exchange filters (HMEFs) and correlated with the concentration of antibiotics measured from bronchoalveolar lavage (BAL). We designed an observational study in patients undergoing mechanical ventilation, which required a BAL to confirm or discard the diagnosis of pneumonia. We measured and correlated the concentration of beta-lactam antibiotics in plasma, epithelial lining fluid (ELF), and exhaled breath condensate collected from HMEFs. We studied 12 patients, and we detected the presence of antibiotics in plasma, ELF, and HMEFs from every patient studied. The concentrations of antibiotics were very heterogeneous over the population studied. The mean antibiotic concentration was 293.5 (715) ng/mL in plasma, 12.3 (31) ng/mL in ELF, and 0.5 (0.9) ng/mL in HMEF. We found no significant correlation between the concentration of antibiotics in plasma and ELF (R² = 0.02, p = 0.64), between plasma and HMEF (R² = 0.02, p = 0.63), or between ELF and HMEF (R² = 0.02, p = 0.66). We conclude that beta-lactam antibiotics can be detected and measured from the exhaled breath condensate accumulated in the HMEF from mechanically ventilated patients. However, no correlations were observed between the antibiotic concentrations in HMEF with either plasma or ELF.

Synthesis and Biological Activities of Dehydrodiisoeugenol: A Review

Dehydrodiisoeugenol (DHIE) is a neolignan found in more than 17 plant species, including herbs, fruit, and root. DHIE was, for the first time, isolated from Myristica fragrans bark in 1973. Since then, many methodologies have been used for the obtention of DHIE, including classical chemistry synthesis using metal catalysts and biocatalytic synthesis; employing horseradish peroxidase; peroxidase from Cocos nucifera; laccase; culture cells of plants; and microorganisms. Increasing evidence has indicated that DHIE has a wide range of biological activities: anti-inflammatory, anti-oxidant, anti-cancerogenic, and anti-microbial properties. However, evidence in vivo and in human beings is still lacking to support the usefulness potential of DHIE as a therapeutic agent. This study's review was created by searching for relevant DHIE material on websites such as Google Scholar, PubMed, SciFinder, Scholar, Science Direct, and others. This reviews the current state of knowledge regarding the different synthetical routes and biological applications of DHIE.