Predictive performance for human skin sensitizing potential of the human cell line activation test (h-CLAT)

Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds

Background

To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine learning applications.

Methods

Following chemical exposure, cell cytotoxicity was assessed using CCK-8 to determine appropriate stimulation concentrations. RNA-Seq was subsequently employed to analyze THP-1 cells, followed by differential expression gene (DEG) analysis and weighted gene co-expression net-work analysis (WGCNA). Using two data preprocessing methods and three feature extraction techniques, we constructed and validated models with eight machine learning algorithms.

Results

Our results demonstrated the effectiveness of this integrated approach. The best performing models were random forest (RF) and voom-based diagonal quadratic discriminant analysis (voomDQDA), both achieving 100% accuracy. Support vector machine (SVM) and voom based nearest shrunken centroids (voomNSC) showed excellent performance with 96.7% test accuracy, followed by voom-based diagonal linear discriminant analysis (voomDLDA) at 95.2%. Nearest shrunken centroids (NSC), Poisson linear discriminant analysis (PLDA) and negative binomial linear discriminant analysis (NBLDA) achieved 90.5% and 90.2% accuracy, respectively. K-nearest neighbors (KNN) showed the lowest accuracy at 85.7%.

Conclusion

This study highlights the potential of integrating co-culture systems, RNA-Seq, and machine learning to develop more accurate and comprehensive in vitro methods for skin sensitization testing. Our findings contribute to the advancement of cosmetic safety assessments, potentially reducing the reliance on animal testing.

The Monocytic Cell Line THP-1 as a Validated and Robust Surrogate Model for Human Dendritic Cells

We have implemented an improved, cost-effective, and highly reproducible protocol for a simple and rapid differentiation of the human leukemia monocytic cell line THP-1 into surrogates for immature dendritic cells (iDCs) or mature dendritic cells (mDCs). The successful differentiation of THP-1 cells into iDCs was determined by high numbers of cells expressing the DC activation markers CD54 (88%) and CD86 (61%), and the absence of the maturation marker CD83. The THP-1-derived mDCs are characterized by high numbers of cells expressing CD54 (99%), CD86 (73%), and the phagocytosis marker CD11b (49%) and, in contrast to THP-1-derived iDCs, CD83 (35%) and the migration marker CXCR4 (70%). Treatment of iDCs with sensitizers, such as NiSO4 and DNCB, led to high expression of CD54 (97%/98%; GMFI, 3.0/3.2-fold induction) and CD86 (64%/96%; GMFI, 4.3/3.2-fold induction) compared to undifferentiated sensitizer-treated THP-1 (CD54, 98%/98%; CD86, 55%/96%). Thus, our iDCs are highly suitable for toxicological studies identifying potential sensitizing or inflammatory compounds. Furthermore, the expression of CD11b, CD83, and CXCR4 on our iDC and mDC surrogates could allow studies investigating the molecular mechanisms of dendritic cell maturation, phagocytosis, migration, and their use as therapeutic targets in various disorders, such as sensitization, inflammation, and cancer.

Lessons learned from immunological characterization of nanomaterials at the Nanotechnology Characterization Laboratory

Nanotechnology carriers have become common in pharmaceutical products because of their benefits to drug delivery, including reduced toxicities and improved efficacy of active pharmaceutical ingredients due to targeted delivery, prolonged circulation time, and controlled payload release. While available examples of reduced drug toxicity through formulation using a nanocarrier are encouraging, current data also demonstrate that nanoparticles may change a drug’s biodistribution and alter its toxicity profile. Moreover, individual components of nanoparticles and excipients commonly used in formulations are often not immunologically inert and contribute to the overall immune responses to nanotechnology-formulated products. Said immune responses may be beneficial or adverse depending on the indication, dose, dose regimen, and route of administration. Therefore, comprehensive toxicology studies are of paramount importance even when previously known drugs, components, and excipients are used in nanoformulations. Recent data also suggest that, despite decades of research directed at hiding nanocarriers from the immune recognition, the immune system’s inherent property of clearing particulate materials can be leveraged to improve the therapeutic efficacy of drugs formulated using nanoparticles. Herein, I review current knowledge about nanoparticles’ interaction with the immune system and how these interactions contribute to nanotechnology-formulated drug products’ safety and efficacy through the lens of over a decade of nanoparticle characterization at the Nanotechnology Characterization Laboratory.

Weight of Evidence Approach for Skin Sensitization Potency Categorization of Fragrance Ingredients

Reliable human potency data are necessary for conducting quantitative risk assessments, as well as development and validation of new nonanimal methods for skin sensitization assessments. Previously, human skin sensitization potency of fragrance materials was derived primarily from human data or the local lymph node assay.

In silico Prediction of Skin Sensitization: Quo vadis?

Skin direct contact with chemical or physical substances is predisposed to allergic contact dermatitis (ACD), producing various allergic reactions, namely rash, blister, or itchy, in the contacted skin area. ACD can be triggered by various extremely complicated adverse outcome pathways (AOPs) remains to be causal for biosafety warrant. As such, commercial products such as ointments or cosmetics can fulfill the topically safe requirements in animal and non-animal models including allergy. Europe, nevertheless, has banned animal tests for the safety evaluations of cosmetic ingredients since 2013, followed by other countries. A variety of non-animal in vitro tests addressing different key events of the AOP, the direct peptide reactivity assay (DPRA), KeratinoSens™, LuSens and human cell line activation test h-CLAT and U-SENS™ have been developed and were adopted in OECD test guideline to identify the skin sensitizers. Other methods, such as the SENS-IS are not yet fully validated and regulatorily accepted. A broad spectrum of in silico models, alternatively, to predict skin sensitization have emerged based on various animal and non-animal data using assorted modeling schemes. In this article, we extensively summarize a number of skin sensitization predictive models that can be used in the biopharmaceutics and cosmeceuticals industries as well as their future perspectives, and the underlined challenges are also discussed.

Skin sensitization in silico protocol

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

Immunostimulatory effects on THP-1 cells by peptide or protein pharmaceuticals associated with injection site reactions

Injection site reaction (ISR) is a common side-effect associated with the use of peptide or protein pharmaceuticals. These types of pharmaceuticals-induced activation of antigen-presenting cells is assumed to be a key step in the pathogenesis of immune-mediated ISR. The present study was designed to evaluate the immunostimulatory properties of peptide or protein pharmaceuticals using human monocytic THP-1 cells. Here, THP-1 cells, with or without phorbol-12-myristate-13-acetate (PMA) pretreatment, were exposed to enfuvirtide and glatiramer acetate (positive controls) or evolocumab (negative control) for 6 or 24 h. PMA treatment differentiated non-adherent monocytic THP-1 (nTHP-1) cells into adherent macrophagic THP-1 (pTHP-1) cells that highly express CD11b and CD36. Enfuvirtide increased the release of cytokines, e.g. TNFα, MIP-1β, and MCP-1, and expression of CD86 and CD54 on nTHP-1 cells at 24 h. Similar immunostimulatory properties of glatiramer acetate were observed both in the nTHP-1 and pTHP-1 cells at 6 h, but the responses were very weak in the pTHP-1 cells. Evolocumab did not affect cytokine secretion or cell surface marker expression in either cell type. Taken together, these in vitro THP-1 cell assays revealed the immunostimulatory properties of enfuvirtide and glatiramer acetate. This assay platform thus could serve as a powerful tool in evaluating potential immune-related ISR risks of peptide or protein pharmaceuticals in humans.

The Overt and Hidden Use of Animal-Derived Products in Alternative Methods for Skin Sensitisation: A Systematic Review

In vitro methods that can replace animal testing in the identification of skin sensitisers are now a reality. However, as cell culture and related techniques usually rely on animal-derived products, these methods may be failing to address the complete replacement of animals in safety assessment. The objective of this study was to identify the animal-derived products that are used as part of in vitro methods for skin sensitisation testing. Thus, a systematic review of 156 articles featuring 83 different in vitro methods was carried out and, from this review, the use of several animal-derived products from different species was identified, with the use of fetal bovine serum being cited in most of the methods (78%). The use of sera from other animals, monoclonal antibodies and animal proteins were also variously mentioned. While non-animal alternatives are available and methods free of animal-derived products are emerging, most of the current methods reported used at least one animal-derived product, which raises ethical and technical concerns. Therefore, to deliver technically and ethically better in vitro methods for the safety assessment of chemicals, more effort should be made to replace products of animal origin in existing methods and to avoid their use in the development of new method protocols.

[Toxicological risk assessment using the example of potential contact sensitization to resorcinol]

Resorcinol is a frequently used hair dye, whose quantitative risk assessment (QRA) for hair color products is presented in this review as an example to assess its skin sensitization risk after topical application. Its purpose is to determine the maximum concentration that can be used without expecting skin sensitization to occur. The focus is to prevent the de novo development of a contact allergy. Epidemiological data which are provided via dermatological surveillance, e.g., by the IVDK (Information Network of Departments of Dermatology) in Germany, are an important source of information that help to assess the quality and the effectivity of the QRA.

The THP-1 cell toolbox: a new concept integrating the key events of skin sensitization

According to the current scientific consensus, one in vitro test is insufficient to cover the key events (KE) defined by the adverse outcome pathway (AOP) for skin sensitization. To address this issue we combined different end points in the same cell line to cover all KEs defined by the skin sensitization AOP. Since dendritic cells (DC) play a key role in the sensitization phase leading to the development of allergic contact dermatitis (ACD), we used THP-1 cells as a surrogate for DC. We measured ROS production and GSH depletion for KE1 (binding to proteins), Nrf2 activation pathway and gene expressions for KE2 (keratinocyte response), phenotype modifications using cell-surface markers and cytokine production for KE3 (DC activation), and T-cell proliferation for KE4 (T-cell activation). These measurements were performed using the THP-1 cell line and an original THP-1/T-cell co-culture system following exposure to a variety of chemicals, including irritant, non-sensitizers, and chemicals sensitizers (pro/prehaptens). Results showed that treatment with sensitizers such as cinnamaldehyde (100 µM) or methylisothiazolinone (150 µM) was able to trigger the three main key events (KE1, KE2, and KE3) of the sensitization phase of ACD in THP-1 cells. In addition, all sensitizers were able to induce T lymphocyte proliferation (KE4), while non-sensitizers and irritants did not. Our study shows for the first time that addressing the four main KE of skin sensitization AOP in a single cell line is an achievable task.

Development and utilization of a unique in vitro antigen presentation co-culture model for detection of immunomodulating substances

Current regulatory immunotoxicity studies require the use of animal models. However, evolving regulatory requirements, the need to evaluate large numbers of chemicals efficiently and societal pressures are driving the development and utilization of alternative in vitro methods for identifying potential immunotoxicants. In line with these efforts, we developed a novel in vitro cell-based assay to evaluate effects on antigen presentation - a key step in successful immunization. In this assay, Ch27 B cells acquire and present hen egg lysozyme peptides to antigen-restricted 3A9 T cells, causing them to produce and secrete IL-2. IL-2 levels in the culture medium may be monitored to identify effects of immunotoxicant exposure on antigen uptake, processing or presentation by the Ch27 cells and on antigen recognition and IL-2 production and secretion by the 3A9 cells. IL-2 production was reduced in response to treatment with well-known immunotoxicants cyclosporin A (CYA), dexamethasone (DEX), azathioprine (AZPR), methotrexate (MOT) and benzo(a)pyrene (BAP) but was not affected by treatment with cyclophosphamide (CYPH). A negative control compound mannitol (MANN) altered neither cell viability nor IL-2 levels whereas the lysosomotrophic compound ammonium chloride (AMCL) reduced IL-2 production. This novel in vitro assay of immune function may be suitable for integration into a tiered testing battery for screening and prioritization of potential immunosuppressants.

Improvement of human cell line activation test (h-CLAT) using short-time exposure methods for prevention of false-negative results

Recently, animal testing has been affected by increasing ethical, social, and political concerns regarding animal welfare. Several in vitro safety tests for evaluating skin sensitization, such as the human cell line activation test (h-CLAT), have been proposed. However, similar to other tests, the h-CLAT has produced false-negative results, including in tests for acid anhydride and water-insoluble chemicals. In a previous study, we demonstrated that the cause of false-negative results from phthalic anhydride was hydrolysis by an aqueous vehicle, with IL-8 release from THP-1 cells, and that short-time exposure to liquid paraffin (LP) dispersion medium could reduce false-negative results from acid anhydrides. In the present study, we modified the h-CLAT by applying this exposure method. We found that the modified h-CLAT is a promising method for reducing false-negative results obtained from acid anhydrides and chemicals with octanol-water partition coefficients (LogK_ow) greater than 3.5. Based on the outcomes from the present study, a combination of the original and the modified h-CLAT is suggested for reducing false-negative results. Notably, the combination method provided a sensitivity of 95% (overall chemicals) or 93% (chemicals with LogK_ow > 2.0), and an accuracy of 88% (overall chemicals) or 81% (chemicals with LogK_ow > 2.0). We found that the combined method is a promising evaluation scheme for reducing false-negative results seen in existing in vitro skin-sensitization tests. In the future, we expect a combination of original and modified h-CLAT to be applied in a newly developed in vitro test for evaluating skin sensitization.

Lipopolysaccharide interferes with the use of the human Cell Line Activation Test to determine the allergic potential of proteins

It was believed that high molecular weight molecules including proteins cannot penetrate the skin. However, protein penetration through disrupted/ruptured skin has been reported recently, thus carrying the potential for inducing an allergic response. We used the human Cell Line Activation Test (h-CLAT), an in vitro skin sensitization test, to assess the allergic potential of proteins by measuring levels of CD86 and CD54 in the human monocytic leukemia cell line THP-1. Six allergens including ovalbumin (OVA) and human serum albumin (HSA; negative control) upregulated CD86 and/or CD54; a false-positive result was obtained using HSA. This was caused by lipopolysaccharide (LPS) contamination. Naturally derived materials often include LPS at various concentrations and may influence protein induction of CD86 and CD54. Additionally, polymyxin B, an LPS inhibitor, could not completely overcome the effect of LPS. Therefore, if test proteins contain ≥0.1 EU/mL LPS, their allergenic potency will not be assessed accurately using h-CLAT. These data show that naturally occurring materials or those derived from living organisms should be evaluated for their LPS content. It is important to confirm the applicability of in vitro methods such as h-CLAT for assessing the allergenic potency of naturally occurring proteins; our findings can be a foundation for future studies.

Predicting skin sensitizers with confidence - Using conformal prediction to determine applicability domain of GARD

GARD - Genomic Allergen Rapid Detection is a cell based alternative to animal testing for identification of skin sensitizers. The assay is based on a biomarker signature comprising 200 genes measured in an in vitro model of dendritic cells following chemical stimulations, and consistently reports predictive performances ~90% for classification of external test sets. Within the field of in vitro skin sensitization testing, definition of applicability domain is often neglected by test developers, and assays are often considered applicable across the entire chemical space. This study complements previous assessments of model performance with an estimate of confidence in individual classifications, as well as a statistically valid determination of the applicability domain for the GARD assay. Conformal prediction was implemented into current GARD protocols, and a large external test dataset (n = 70) was classified at a confidence level of 85%, to generate a valid model with a balanced accuracy of 88%, with none of the tested chemical reactivity domains identified as outside the applicability domain of the assay. In conclusion, results presented in this study complement previously reported predictive performances of GARD with a statistically valid assessment of uncertainty in each individual prediction, thus allowing for classification of skin sensitizers with confidence.

Predicting Chemically Induced Skin Sensitization by Using In Chemico / In Vitro Methods

Over the recent years development toward assessing skin sensitization hazard has moved toward non-animal testing methods. These methods are based on the key events as described in the OECD Adverse Outcome Pathway (AOP) for skin sensitization initiated by covalent binding to proteins. As these individual methods address mainly one mechanistic event (key event) in the initiation of skin sensitization, combination of different methods are needed to conclude on the skin sensitization hazard. Validated and regulatory adopted (EU and OECD) in chemico/in vitro methods are available for KEs 1-3 and are presented here. This chapter also illustrates how individual test methods can be combined by providing two examples of defined approaches to testing and assessment for skin sensitization hazard identification and assessment.

Prediction of skin sensitization potency using machine learning approaches

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd.

State of the art in non-animal approaches for skin sensitization testing: from individual test methods towards testing strategies

The hazard assessment of skin sensitizers relies mainly on animal testing, but much progress is made in the development, validation and regulatory acceptance and implementation of non-animal predictive approaches. In this review, we provide an update on the available computational tools and animal-free test methods for the prediction of skin sensitization hazard. These individual test methods address mostly one mechanistic step of the process of skin sensitization induction. The adverse outcome pathway (AOP) for skin sensitization describes the key events (KEs) that lead to skin sensitization. In our review, we have clustered the available test methods according to the KE they inform: the molecular initiating event (MIE/KE1)-protein binding, KE2-keratinocyte activation, KE3-dendritic cell activation and KE4-T cell activation and proliferation. In recent years, most progress has been made in the development and validation of in vitro assays that address KE2 and KE3. No standardized in vitro assays for T cell activation are available; thus, KE4 cannot be measured in vitro. Three non-animal test methods, addressing either the MIE, KE2 or KE3, are accepted as OECD test guidelines, and this has accelerated the development of integrated or defined approaches for testing and assessment (e.g. testing strategies). The majority of these approaches are mechanism-based, since they combine results from multiple test methods and/or computational tools that address different KEs of the AOP to estimate skin sensitization potential and sometimes potency. Other approaches are based on statistical tools. Until now, eleven different testing strategies have been published, the majority using the same individual information sources. Our review shows that some of the defined approaches to testing and assessment are able to accurately predict skin sensitization hazard, sometimes even more accurate than the currently used animal test. A few defined approaches are developed to provide an estimate of the potency sub-category of a skin sensitizer as well, but these approaches need further independent evaluation with a new dataset of chemicals. To conclude, this update shows that the field of non-animal approaches for skin sensitization has evolved greatly in recent years and that it is possible to predict skin sensitization hazard without animal testing.

Integrated decision strategies for skin sensitization hazard

One of the top priorities of the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by the Organisation for Economic Co-operation and Development (OECD). Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens assay. Data for six physicochemical properties, which may affect skin penetration, were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89-96% for the test set and 96-99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Multivariate models for prediction of human skin sensitization hazard

One of the Interagency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens™ assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy 88%), any of the alternative methods alone (accuracy 63-79%) or test batteries combining data from the individual methods (accuracy 75%). These results suggest that computational methods are promising tools to identify effectively the potential human skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Prediction of chemical respiratory sensitizers using GARD, a novel in vitro assay based on a genomic biomarker signature

Background

Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers.

Results

Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers.

Conclusions

We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample.