Tissue Model Research Articles

Human 3D Lung Cancer Tissue Photothermal Therapy Using Zn- and Co-Doped Magnetite Nanoparticles.

Iron oxide-based nanoparticles are promising materials for cancer thermal therapy and immunotherapy. However, several proofs of concept reported data with murine tumor models that might have limitations for clinical translation. Magnetite is nowadays the most popular nanomaterial, but doping with distinct ions can enhance thermal therapy, namely, magnetic nanoparticle hyperthermia (MNH) and photothermal therapy (PTT). In this study, we used a 3D alveolar reconstructed A549 lung cancer tissue model and investigated the thermal properties, toxicity, and impact of the thermal dose on tissue viability and inflammatory response using magnetite codoped with 40% Zn and 2% Co divalent ions. The ZnCo-doped magnetite nanoparticles are not toxic up to an NP concentration of 30 mg/mL. PTT showed a better heat generation response than MNH under the evaluated conditions, while NP showed a high external photothermal conversion efficiency of ∼1.3 g·L-1·cm-1 at 808 nm. PTT study is carried out at different temperatures, 43 and 47 °C, for 15 min. Tissue viability decreased with increasing thermal dose, while intracelullar ROS levels increased, mitochondrial activity decreased, and active caspase-3 increased, suggesting cell death via apoptosis. Nanoparticles and PTT did not influence the cytokine TNF, IL-10, IL-1B, and IL-12p70. In contrast, IL-6 and IL-8 were triggered by NP and PTT. Increased expression of IL-6 and IL-8 with higher thermal doses is correlated with tissue injury results, suggesting the potential role in activating and attracting immune cells to the site of thermal-mediated tissue injury.

Comprehensive Analysis Reveals the Potential Diagnostic Value of Biomarkers Associated With Aging and Circadian Rhythm in Knee Osteoarthritis.

Knee osteoarthritis (KOA) is characterized by structural changes. Aging is a major risk factor for KOA. Therefore, the objective of this study was to examine the role of genes related to aging and circadian rhythms in KOA. This study identified differentially expressed genes (DEGs) by comparing gene expression levels between normal and KOA samples from the GEO database. Subsequently, we intersected the DEGs with aging-related circadian rhythm genes to obtain a set of aging-associated circadian rhythm genes differentially expressed in KOA. Next, we conducted Mendelian randomization (MR) analysis, using the differentially expressed aging-related circadian rhythm genes in KOA as the exposure factors, their SNPs as instrumental variables, and KOA as the outcome event, to explore the causal relationship between these genes and KOA. We then performed Gene Set Enrichment Analysis (GSEA) to investigate the pathways associated with the selected biomarkers, conducted immune infiltration analysis, built a competing endogenous RNA (ceRNA) network, and performed molecular docking studies. Additionally, the findings and functional roles of the biomarkers were further validated through experiments on human cartilage tissue and cell models. A total of 75 differentially expressed aging-circadian rhythm related genes between the normal group and the KOA group were identified by difference analysis, primarily enriched in the circadian rhythm pathway. Two biomarkers (PFKFB4 and DDIT4) were screened by MR analysis. Then, immune infiltration analysis showed significant differences in three types of immune cells (resting dendritic cells, resting mast cells, and M2 macrophages), between the normal and KOA groups. Drug prediction and molecular docking results indicated stable binding of PFKFB4 to estradiol and bisphenol_A, while DDIT4 binds stably to nortriptyline and trimipramine. Finally, cell lines with stable expression of the biomarkers were established by lentiviral infection and resistance screening, Gene expression was significantly elevated in overexpressing cells of PFKFB4 and DDIT4 and reversed the proliferation and migration ability of cells after IL-1β treatment. Two diagnostic and therapeutic biomarkers associated with aging-circadian rhythm in KOA were identified. Functional analysis, molecular mechanism exploration, and experimental validation further elucidated their roles in KOA, offering novel perspectives for the prevention and treatment of the disease.

PET Imaging of a Transgenic Tau Rat Model SHR24 with [18F]AV1451.

Positron Emission Tomography (PET) scans with radioligands targeting tau neurofibrillary tangles (NFT) have accelerated our understanding of the role of misfolded tau in neurodegeneration. While intended for human research, applying these radioligands to small animals establishes a vital translational link. Transgenic animal models of dementia, such as the tau rat SHR24, play a crucial role in enhancing our understanding of these disorders. This study aims to evaluate the utility of SHR24 rat model for PET studies. Dynamic PET scans were conducted in male SHR24 rats and their wild-type SHR (SHRwt) littermates using [18F]AV1451. Rapid blood sampling and metabolite analysis were performed to acquire input curves. Time activity curves were obtained from various brain regions over 60min. Blood-based, 2-Tissue Compartment Model (2-TCM) and Logan graphical analysis were used to obtain kinetic modelling parameters. The ability of reference tissue models to predict the binding potential (BPND) were assessed. Autoradiography studies were performed to corroborate the scan data. Total distribution volume (VT) was the best predicted parameter which revealed significantly higher uptake of [18F]AV1451 in the cortex (5.8 ± 1.1 vs 4.6 ± 0.7, P < 0.05) of SHR24 rats compared to SHRwt rats. Binding potential obtained from 2-TCM was variable, however BPND from reference tissue models detected significantly higher binding in cortex (0.28 ± 0.07 vs 0.20 ± 0.04, P < 0.01 by SRTM) and brainstem (0.14 ± 0.04 vs 0.08 ± 0.02, P < 0.01, by SRTM). With the ability to detect binding of established radioligand [18F]AV1451 in these rats, we have demonstrated the utility of this model for assessing aggregated tau neurobiology by PET, with reference tissue models providing potential for longitudinal studies.

Biofabricated tissue model for determining biocompatibility of metallic coatings.

Metallic biomaterials are extensively used in orthopedics and dentistry, either as implants or coatings. In both cases, metal ions come into contact with surrounding tissues causing a particular cell response. Here, we present a biofabricated in vitro tissue model, consisting of a hydrogel reinforced with a melt electrowritten mesh, to study the effects of bound and released metal ions on surrounding cells embedded in a hydrogel matrix. We evaluate the biocompatibility, bioactivity, and antibacterial properties of these metal coatings. Our approach involves integrating physical vapour deposition coating technology with 3D bioprinting methods. To produce tissue models, melt electrowritten (MEW) meshes composed of polycaprolactone (PCL) were printed and integrated into cell-laden methacrylated galatin (GelMa). The mouse embryonic fibroblast cell line (NIH3T3) was used. GelMa concentration and printing parameters for MEW were adjusted and mechanical analysis of the models was performed to find the optimal material composition. Optimized models were placed on the glass slide surfaces coated with typically non-toxic metals, i.e. titanium (Ti), tantalum (Ta), zirconium (Zr), silver (Ag), tungsten (W), and niobium (Nb). Except for W, all other coatings were stable in a physiological wet environment, as studied by SEM. The viability of the cells at different distances from the coated surface was analyzed. Antibacterial tests against pathogens Staphylococcus aureus and Escherichia coli were used to assess the models' resistance, important for infection control. While Ag coatings showed toxicity, Nb, Ta, Ti, and Zr coatings promoted fibroblast growth, with the highest cell viability after 14 days of culture revealed for Ta and Nb. The strongest antimicrobial effect against E. coli and S. aureus was observed for Ag and W, while Ta exhibited antibacterial activity only against S. aureus. From a broader perspective, our work offers an effective 3D in vitro model for an in-depth characterization of the biocompatibility of metals and metal coatings.

Structural constitutive models for soft biological tissues and biomaterials: the role of mechanical interactions

Structural constitutive models for soft biological tissues and biomaterials: the role of mechanical interactions

Utilizing Tissues Self-Assembled in Fiber Optic-Based "Chinese Guzheng Strings" for Contractility Sensing and Drug Efficacy Evaluation: A Practical Approach.

Recent advances in drug design and compound synthesis have highlighted the increasing need for effective methods of toxicity evaluation. A specialized force sensor, known as the light wavelength-encoded "Chinese guzheng" is developed. This innovative sensor is equipped with optical fiber strings and utilizes a wavelength-encoded fiber Bragg grating (FBG) that is chemically etched to reduce its diameter. This design allows the sensor to detect minimal forces as low as l µN. This sensor is successfully applied to monitor human-induced pluripotent stem cell-derived human-engineered heart tissue (hEHT) models that can self-assemble and contact optical fiber-based strings. The sensor detects micro newton contraction forces in real-time by measuring the wavelength drift resulting from hEHT contractions. In addition, the sensor is precise and durable, exhibiting a fatigue resistance of up to 800000 cycles, making it suitable for long-term monitoring. The device effectively measured the contractile force of the hEHTs under various physiological conditions, including natural contraction, electrical stimulation, and stretching. Moreover, multichannel detection enables the study and demonstration of short- and long-term effectiveness of multiple drugs. This breakthrough sensor addresses the critical need for high-precision real-time monitoring in drug evaluation and provides a solid foundation for screening drugs to treat cardiomyopathy.

A Hydrogel-Based Multiplex Coculture Platform for Retinal Component Cells.

There is growing interest in generating in vitro models of tissues and tissue-related diseases to mimic normal tissue organization and pathogenesis for different purposes. The retina is a highly complex multicellular tissue where the organization of the cellular components relative to each other is critical for retinal function. Many retinopathies arise due to the disruption of this order. In this study, we aimed to generate a coculture model of retina-derived cells, namely RPE and Müller cells, in multiplexed 3D hydrogels. Using methacrylated gelatin (GelMA)-based 3D hydrogels, we compared the behavior of RPE and Müller cells when they were cultured together. These patterned multiplex hydrogels containing cells were cultured for several days to reflect how cells would reorganize themselves in the presence of another cellular component derived from the same tissue. Here, we present a multicellular multiplex platform for the creation of cellular networks with cells of retinal tissue that can be easily adapted to create more complex tissue-like alternatives for large-scale tissue modeling and screening purposes. We also present an alternative method of coculture by generating spheroids from one of the components while keeping the other component free and motile in the hydrogel. The latter model predicts enhanced possibilities of cellular interactions by retarding the movement of one of the component cells.

Two- and Three-Dimensional Culture Systems: Respiratory In Vitro Tissue Models for Chemical Screening and Risk-Based Decision Making.

Risk of lung damage from inhaled chemicals or substances has long been assessed using animal models. However, New Approach Methodologies (NAMs) that replace, reduce, and/or refine the use of animals in safety testing such as 2D and 3D cultures are increasingly being used to understand human-relevant toxicity responses and for the assessment of hazard identification. Here we review 2D and 3D lung models in terms of their application for inhalation toxicity assessment. We highlight a key case study for the Organization for Economic Cooperation and Development (OECD), in which a 3D model was used to assess human toxicity and replace the requirement for a 90-day inhalation toxicity study in rats. Finally, we consider the regulatory guidelines for the application of NAMs and potential use of different lung models for aerosol toxicity studies depending on the regulatory requirement/context of use.

Robust estimation of skin physiological parameters from hyperspectral images using Bayesian neural networks.

Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte Carlo and inverse adding-doubling (IAD). We aim to develop a Bayesian neural network model for robust prediction of physiological parameters from hyperspectral images. We propose a two-component system for extracting physiological parameters from hyperspectral images. First, our system models the relationship between the measured spectra and the tissue parameters as a distribution rather than a point estimate and is thus able to generate multiple possible solutions. Second, the proposed tissue parameters are then refined using the neural network that approximates the biological tissue model. The proposed model was tested on simulated and in vivo data. It outperformed current models with an overall mean absolute error of 0.0141 and can be used as a faster alternative to the IAD algorithm. Results suggest that Bayesian neural networks coupled with the approximation of a biological tissue model can be used to reliably and accurately extract tissue properties from hyperspectral images on the fly.

Assessment of hard tissue changes after horizontal guided bone regeneration with the aid of deep learning CBCT segmentation.

To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes. The proposed SegResNet-based DL model was trained on 70 CBCT scans. It was tested on 10 pairs of pre- and post-operative CBCT scans of patients who underwent mandibular horizontal GBR. DL segmentations were compared to semi-automated (SA) segmentations of the same scans. Augmented hard tissue segmentation performance was evaluated by spatially aligning pre- and post-operative CBCT scans and subtracting preoperative segmentations obtained by DL and SA segmentations from the respective postoperative segmentations. The performance of DL compared to SA segmentation was evaluated based on the Dice similarity coefficient (DSC), intersection over the union (IoU), Hausdorff distance (HD95), and volume comparison. The mean DSC and IoU between DL and SA segmentations were 0.96 ± 0.01 and 0.92 ± 0.02 in both pre- and post-operative CBCT scans. While HD95 values between DL and SA segmentations were 0.62mm ± 0.16mm and 0.77mm ± 0.31mm for pre- and post-operative CBCTs respectively. The DSC, IoU and HD95 averaged 0.85 ± 0.08; 0.78 ± 0.07 and 0.91 ± 0.92mm for augmented hard tissue models respectively. Volumes mandible- and augmented hard tissue segmentations did not differ significantly between the DL and SA methods. The SegResNet-based DL model accurately segmented CBCT scans acquired before and after mandibular horizontal GBR. However, the training database must be further increased to increase the model's robustness. Automated DL segmentation could aid treatment planning for GBR and subsequent implant placement procedures and in evaluating hard tissue changes.

Underscoring long-term host-microbiome interactions in a physiologically relevant gingival tissue model

The human body houses many distinct and interconnecting microbial populations with long-lasting systemic effects, where the oral cavity serves as a pathogens’ reservoir. The correlation of different disease states strongly supports the need to understand the interplay between the oral tissue niche and microbiome. Despite efforts, the recapitulation of gingival architecture and physiological characteristics of the periodontal niche has yet to be accomplished by traditional cultural strategies. Here, we are showing for the first time the investigation of host–microbiome interactions in healthy conditions within a human oral tissue model over seven days. Our results indicated long-term host and microbiome viability, host barrier integrity, phenotypic functional response, and preservation of healthy microbial populations and interbacterial dialogs. This in vitro platform can maintain tissue homeostasis at the interface of the periodontal niche, thus, offering opportunities to identify predictive disease biomarkers and to develop intervention strategies to promote oral and overall health.

Construction of complex three-dimensional vascularized liver tissue model in vitro based on a biphasic cell-laden embedding medium

Construction of complex three-dimensional vascularized liver tissue model in vitro based on a biphasic cell-laden embedding medium

Monitoring of the Local Extracellular Environment Using Chiral Gold Nanoparticles.

In three-dimensional (3D)-printed tissue models, sensitive, noninvasive techniques are required to detect in situ changes in hydrogel structure caused by cellular remodeling. We demonstrate herein that circular dichroism (CD) spectroscopy provides a reliable method for detecting hydrogel structural variations. We probe directly the plasmonic optical activity of chiral gold nanorods (c-AuNRs) embedded within the hydrogel matrix, in response to variations in the local environment. Unlike extinction spectroscopy, we found that CD features such as zero-point crossings do not get masked by the strong scattering due to the porous hydrogel structure and are therefore sensitive to changes in the refractive index of the medium, reversible swelling and deswelling of the hydrogel, and other interactions between the hydrogel and the c-AuNR surface. By culturing metastatic breast cancer cells within the 3D hydrogel nanocomposite, we demonstrate that CD can noninvasively probe the restructuring of the hydrogel. This study highlights the potential of CD spectroscopy in combination with c-AuNRs to investigate complex changes in biological or polymeric systems.

Repetitive injury induces phenotypes associated with Alzheimer's disease by reactivating HSV-1 in a human brain tissue model.

Infection with herpes simplex virus type 1 (HSV-1) in the brains of APOE4 carriers increases the risk of Alzheimer's disease (AD). We previously found that latent HSV-1 in a three-dimensional in vitro model of APOE4-heterozygous human brain tissue was reactivated in response to neuroinflammation caused by exposure to other pathogens. Because traumatic brain injury also causes neuroinflammation, we surmised that brain injury might similarly reactivate latent HSV-1. Here, we examined the effects of one or more controlled blows to our human brain model in the absence or presence of latent HSV-1 infection. After repeated, mild controlled blows, latently infected tissues showed reactivation of HSV-1; the production and accumulation of β amyloid and phosphorylated tau (which promotes synaptic dysfunction and neurodegeneration); and activated gliosis, which is associated with destructive neuroinflammation. These effects are collectively associated with AD, dementia, and chronic traumatic encephalopathy (CTE) and were increased with additional injury but were absent in mock-infected tissue. Blocking the cytokine IL-1β prevented the induction of amyloid and gliosis in latently infected monolayer cultures after scratch wounding. We thus propose that after repeated mechanical injuries to the brain, such as from direct blows to the head or jarring motions of the head, the resulting reactivation of HSV-1 in the brain may contribute to the development of AD and related diseases in some individuals.

Rheological Characterization and Printability of Sodium Alginate-Gelatin Hydrogel for 3D Cultures and Bioprinting.

The development of biocompatible hydrogels for 3D bioprinting is essential for creating functional tissue models and advancing preclinical drug testing. This study investigates the formulation, printability, mechanical properties, and biocompatibility of a novel Alg-Gel hydrogel blend (alginate and gelatin) for use in extrusion-based 3D bioprinting. A range of hydrogel compositions were evaluated for their rheological behavior, including shear-thinning properties, storage modulus, and compressive modulus, which are crucial for maintaining structural integrity during printing and supporting cell viability. The printability assessment of the 7% alginate-8% gelatin hydrogel demonstrated that the 27T tapered needle achieved the highest normalized Printability Index (POInormalized = 1), offering the narrowest strand width (0.56 ± 0.02 mm) and the highest printing accuracy (97.2%) at the lowest printing pressure (30 psi). In contrast, the 30R needle, with the smallest inner diameter (0.152 mm) and highest printing pressure (80 psi), resulted in the widest strand width (0.70 ± 0.01 mm) and the lowest accuracy (88.8%), resulting in a POInormalized of 0.274. The 30T and 27R needles demonstrated moderate performance, with POInormalized values of 0.758 and 0.558, respectively. The optimized 7% alginate and 8% gelatin blend demonstrated favorable printability, mechanical strength, and cell compatibility with MDA-MB-213 breast cancer cells, exhibiting high cell proliferation rates and minimal cytotoxicity over a 2-week culture period. This formulation offers a balanced approach, providing sufficient viscosity for precision printing while minimizing shear stress to preserve cell health. This work lays the groundwork for future advancements in bioprinted cancer models, contributing to the development of more effective tools for drug screening and personalized medicine.

A probabilistic modeling framework for the prediction of spontaneous premature beats and reentry initiation.

Spontaneously occurring life-threatening reentrant arrhythmias result when a propagating premature beat encounters a region with significant dispersion of refractoriness. Although localized structural tissue heterogeneities and prescribed cell functional gradients have been incorporated into computational electrophysiologic models, a quantitative framework for the evolution from normal to abnormal behavior that occurs by disease is lacking. The purpose of this study was to develop a probabilistic modeling framework representing the complex interplay of cell function and tissue structure in health and disease that predicts the emergence of premature beats and the initiation of reentry. An action potential model of the rabbit was developed with data-driven uncertainty characterization as done previously. A novel tissue model using the discrete-cell monodomain equations was developed by implementing cellular uncertainty as a random spatial field. Cellular action potentials exhibited a wide range of duration and even a variety of behaviors, with 67% exhibiting normal repolarization, 27% displaying early afterdepolarizations, and 6% showing repolarization failure. Nevertheless, simulations in tissue resulted in localized synchronized repolarization. Thus, cellular variability provided "tissue-level robustness," and premature beats and reentry induction were never observed even with abnormalities in cell function (IKr block) or tissue structure (increased tissue resistance). Alterations of both cell function and tissue structure were necessary for the generation of premature beats and arrhythmia initiation. Once extended to whole hearts and validated for a specific context, this modeling framework provides a means to predict the probability of the initiation of life-threatening arrhythmias.

Proton dose deposition in heterogeneous media: A TOPAS Monte Carlo simulation study.

This study investigated the influence of tissue electron density on proton beam dose distribution using TOPAS Monte Carlo simulation. Heterogeneous tissue models composed of 14 materials were constructed to simulate the dose deposition process of a 169.23MeV proton beam. The study analyzed the relationships between electron density and key parameters such as maximum dose, total dose, and dose distribution. Results showed that increasing electron density led to higher local maximum dose, lower total dose, and decreased Bragg peak depth, range, penumbra width, and full width at half maximum (FWHM). High-density tissues caused a sharp, concentrated Bragg peak at shallower depths, while low-density tissues caused a backward shift and widening of the Bragg peak. Differences in proton energy deposition in various tissues were the fundamental reasons for dose distribution variations. This study quantified the relationship between electron density and proton beam dose distribution, providing a reference for accurate dose calculation and optimization in proton therapy.

Testing organ-specific responses to therapies in tissues differentiated from Cystic Fibrosis patient derived iPSCs.

Cystic Fibrosis (CF) is a life-shortening disease that is caused by mutations in the CFTR gene, a gene that is expressed in multiple organs. There are several primary tissue models of CF disease, including nasal epithelial cultures and rectal organoids, that are effective in reporting the potential efficacy of mutation-targeted therapies called CFTR modulators. However, there is the well-documented variation in tissue dependent, therapeutic response amongst CF patients, even those with the same CF-causing mutation. Hence, there is an interest in developing strategies for comparing therapeutic efficacy in different organs relative to isogenic controls. In this study, we evaluated the CFTR chloride channel response to the highly effective CFTR modulator: Trikafta, in CF patient specific, iPSC-derived colonic and airway cultures relative to mutation-corrected (non-CF) tissues from that same individual. We measured pharmacological rescue in both tissues. This proof-of-concept study provides a roadmap for future comparisons of patient-specific CF therapeutic responses in both pulmonary and extra-pulmonary systems.

Long-range directional growth of neurites induced by magnetic forces.

The ability to control the growth and orientation of neurites over long distances has significant implications for regenerative therapies and the development of physiologically relevant brain tissue models. In this study, the forces generated on magnetic nanoparticles internalised within intracellular endosomes are used to direct the orientation of neuronal outgrowth in cell cultures. Following differentiation, neurite orientation was observed after 3 days application of magnetic forces to human neuroblastoma (SH-SY5Y) cells, and after 4 days application to rat cortical primary neurons. The direction of neurite outgrowth was quantified using a 2D Fourier transform analysis, showing agreement with the derived magnetic force vectors. Orientation control was found to be effective over areas >1cm2 using modest forces of ∼10 fN per endosome, apparently limited only by the local confluence of the cells. A bioinformatics analysis of protein expression in cells exposed to magnetic forces revealed changes to cell signaling and metabolic pathways resulting in enhanced carbohydrate metabolism, as well as the perturbation of processes related to cellular organisation and proliferation. Additionally, in cell culture regions where the measured force vectors converged, large (∼100 µm) SH-SY5Y neuroclusters loaded with nanoparticles were found, connected by unusually thick linear neurite fibres. This could suggest a magnetically driven enhancement of neurocluster growth, with the clusters themselves contributing to the local forces that direct outgrowth. Such structures, which have not been previously observed, could provide new insights into the development and possible enhancement of neural circuitry. STATEMENT OF SIGNIFICANCE: A magnetic force approach for directing outgrowth in neuronal cells over macroscopic areas is successfully demonstrated. Cells were incubated with magnetic nanoparticles which were sequestered into intracellular compartments. Permanent magnet arrays created local intracellular magnetic force vectors mediated via the internalized nanoparticles, which were found to precisely guide neurite orientation. Analysis of cellular protein expression suggested the mechanism for directed growth involved specific cell signaling and metabolic pathways. In addition, highly unusual straight and thick neural fibers were observed that connected large 'magnetic' spherical cell clusters. The results reported will advance nanotechnology and cell therapy for neuro-regeneration where magnetic forces could help to reconnect damaged neurons, or even build artificial neuronal architectures.

Real-world outdoor air exposure effects in a model of the human airway epithelium - A comparison of healthy and asthmatic individuals using a mobile laboratory setting.

We developed a mobile laboratory allowing field exposure of lung tissue models to ambient air at localities with various pollution sources (Background, Industrial, Traffic, Urban) in different seasons (summer/fall/winter). In samples originating from healthy and asthmatic individuals, we assessed the parameters of toxicity, lipid peroxidation and immune response; we further performed comprehensive monitoring of air pollutants at sampling sites. We measured lactate dehydrogenase (LDH) and adenylate kinase (AK) production and transepithelial electrical resistance (TEER), analyzed 15-F2t-isopostane (IsoP) and a panel of 20 cytokines/chemokines/growth factors. In the ambient air, we detected particulate matter (PM), and other relevant chemicals (benzene, benzo[a]pyrene (BaP), NOx). In the Traffic locality, we found very high concentrations of ultrafine particles and NOx and observed low TEER values in the exposed samples, indicating significant traffic-related toxicity of the ambient air. In the Urban locality, sampled in winter, we observed high PM and BaP levels. We found lower AK levels in samples from healthy individuals exposed in this locality than in the asthmatic samples. In the samples from the Industrial locality, sampled in summer, we detected higher concentrations of TNFα, MIP-1α, Eotaxin, GROα, GM-CSF, IL-6 and IL-7 than in the Urban locality samples. We hypothesize that pollen or other plant-related components of the ambient air were responsible for this response. In conclusion, our data proved the feasibility of our mobile laboratory for field measurements of the biological response of lung tissue models exposed to ambient air, reflecting not only the levels of toxic compounds, but also season-specific parameters.