BackgroundQuantifying morphologic changes is critical to our understanding of the pathophysiology of the lung. Mean linear intercept (MLI) measures are important in the assessment of clinically relevant pathology, such as emphysema. However, qualitative measures are prone to error and bias, while quantitative methods such as mean linear intercept (MLI) are manually time consuming. Furthermore, a fully automated, reliable method of assessment is nontrivial and resource-intensive.MethodsWe propose a semi-automated method to quantify MLI that does not require specialized computer knowledge and uses a free, open-source image-processor (Fiji). We tested the method with a computer-generated, idealized dataset, derived an MLI usage guide, and successfully applied this method to a murine model of particulate matter (PM) exposure. Fields of randomly placed, uniform-radius circles were analyzed. Optimal numbers of chords to assess based on MLI were found via receiver-operator-characteristic (ROC)-area under the curve (AUC) analysis. Intraclass correlation coefficient (ICC) measured reliability.ResultsWe demonstrate high accuracy (AUCROC > 0.8 for MLIactual > 63.83 pixels) and excellent reliability (ICC = 0.9998, p < 0.0001). We provide a guide to optimize the number of chords to sample based on MLI. Processing time was 0.03 s/image. We showed elevated MLI in PM-exposed mice compared to PBS-exposed controls. We have also provided the macros that were used and have made an ImageJ plugin available free for academic research use at https://med.nyu.edu/nolanlab.ConclusionsOur semi-automated method is reliable, equally fast as fully automated methods, and uses free, open-source software. Additionally, we quantified the optimal number of chords that should be measured per lung field.Electronic supplementary materialThe online version of this article (10.1186/s12890-019-0915-6) contains supplementary material, which is available to authorized users.

Diclofenac is a frequently prescribed drug for rheumatic diseases and muscle pain. In rare cases, it may be associated with a severe hepatotoxicity. In literature, it is discussed whether this toxicity is related to the oxidative phase I metabolism, resulting in electrophilic quinone imines, which can subsequently react with nucleophiles present in the liver in form of glutathione or proteins. In this work, electrochemistry coupled to mass spectrometry is used as a tool for the simulation of the oxidative pathway of diclofenac. Using this purely instrumental approach, diclofenac was oxidized in a thin layer cell equipped with a boron doped diamond working electrode. Sum formulae of generated oxidation products were calculated based on accurate mass measurements with deviations below 2 ppm. Quinone imines from diclofenac were detected using this approach. It could be shown for the first time that these quinone imines do not react with glutathione exclusively but also with larger molecules such as the model protein β-lactoglobulin A. A tryptic digest of the generated drug-protein adduct confirms that the protein is modified at the only free thiol-containing peptide. This simple and purely instrumental set-up offers the possibility of generating reactive metabolites of diclofenac and to assess their reactivity rapidly and easily.

During the development of new materials demonstrating biological activity, prediction and identification of reactive intermediates generated in the course of drug metabolism in the human liver is of great importance. We present a rapid and purely instrumental method for the structure elucidation of possible phase I metabolites. With electrochemical (EC) conversion adopting the oxidative function of liver-inherent enzymes and nuclear magnetic resonance (NMR) spectroscopy enabling structure elucidation, comprehensive knowledge on potential metabolites can be gained. Paracetamol (APAP) has been known to induce hepatotoxicity when exceeding therapeutic doses and was therefore selected as the test compound. The reactive metabolite N-acetyl-p-benzoquinone imine has long been proven to be responsible for the toxic side effects of APAP and can easily be generated by EC. EC coupled online to NMR is a straightforward technique for structure elucidation of reactive drug intermediates at an early stage in drug discovery.

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