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The European Registration, Evaluation, Authorization and Restriction of Chemical Substances Regulation, requires marketed chemicals to be evaluated for Ready Biodegradability (RB), considering in silico prediction as valid alternative to experimental testing. However, currently available models may not be relevant to predict compounds of industrial interest, due to accuracy and applicability domain restriction issues. In this work, we present a new and extended RB dataset (2830 compounds), issued by the merging of several public data sources. It was used to train classification models, which were externally validated and benchmarked against already-existing tools on a set of 316 compounds coming from the industrial context. New models showed good performances in terms of predictive power (Balance Accuracy (BA) = 0.74-0.79) and data coverage (83-91%). The Generative Topographic Mapping approach identified several chemotypes and structural motifs unique to the industrial dataset, highlighting for which chemical classes currently available models may have less reliable predictions. Finally, public and industrial data were merged into global dataset containing 3146 compounds. This is the biggest dataset reported in the literature so far, covering some chemotypes absent in the public data. Thus, predictive model developed on the Global dataset has larger applicability domain than the existing ones.

BackgroundClara cell protein (CC16), the main secretory product of bronchiolar Clara cells, plays an important protective role in the respiratory tract against oxidative stress and inflammation. The purpose of the study was to investigate the role of elemental carbon ultrafine particles (EC-UFP)-induced oxidative stress on Clara cells and CC16 in a mouse model of allergic lung inflammation.MethodsOvalbumin (OVA)-sensitized mice were exposed to EC-UFP (507 μg/m3 for 24 h) or filtered air immediately prior to allergen challenge and systemically treated with N-acetylcysteine (NAC) or vehicle prior and during EC-UFP inhalation. CC16 was measured up to one week after allergen challenge in bronchoalveolar lavage fluid (BALF) and in serum. The relative expression of CC16 and TNF-α mRNA were measured in lung homogenates. A morphometrical analysis of mucus hypersecretion and electron microscopy served to investigate goblet cell metaplasia and Clara cell morphological alterations.ResultsIn non sensitized mice EC-UFP inhalation caused alterations in CC16 concentration, both at protein and mRNA level, and induced Clara cell hyperplasia. In sensitized mice, inhalation of EC-UFP prior to OVA challenge caused most significant alterations of BALF and serum CC16 concentration, BALF total protein and TNF-α relative expression compared to relevant controls; their Clara cells displayed the strongest morphological alterations and strongest goblet cell metaplasia occurred in the small airways. NAC strongly reduced both functional and morphological alterations of Clara cells.ConclusionOur findings demonstrate that oxidative stress plays an important role in EC-UFP-induced augmentation of functional and morphological alterations of Clara cells in allergic lung inflammation.