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Repeated double cross validation (rdCV) is a strategy for (a) optimizing the complexity of regression models and (b) for a realistic estimation of prediction errors when the model is applied to new cases (that are within the population of the data used). This strategy is suited for small data sets and is a complementary method to bootstrap methods. rdCV is a formal, partly new combination of known procedures and methods, and has been implemented in a function for the programming environment R, providing several types of plots for model evaluation. The current version of the software is dedicated to regression models obtained by partial least-squares (PLS). The applied methods for repeated splits of the data into test sets and calibration sets, as well as for estimation of the optimum number of PLS components, are described. The relevance of some parameters (number of segments in CV, number of repetitions) is investigated. rdCV is applied to two data sets from chemistry: (1) determination of glucose concentrations from near infrared (NIR) data in mash samples from bioethanol production; (2) modeling the gas chromatographic retention indices of polycyclic aromatic compounds from molecular descriptors. Models using all original variables and models using a small subset of the variables, selected by a genetic algorithm (GA), are compared by rdCV.

Environmental pollution with microplastics (MPs) is a major and worldwide concern. Involuntary exposure to MPs by ingestion or inhalation is unavoidable. The effects on human health are still under debate, while in animals, cellular MP translocation and subsequent deleterious effects were shown. First reports indicate a potential intrauterine exposure with MPs, yet readouts are prone to contamination. Method: To establish a thorough protocol for the detection of MPs in human placenta and fetal meconium in a real-life clinical setting, a pilot study was set up to screen for MPs > 50 µm in placental tissue and meconium sampled during two cesarean sections for breech deliveries. After chemical digestion of non-plastic material, Fourier-transform infrared (FTIR) microspectroscopy was used to analyze the presence of 10 common types of microplastic in placenta and stool samples. Results: Human placenta and meconium samples were screened positive for polyethylene, polypropylene, polystyrene, and polyurethane, of which only the latter one was also detected as airborne fallout in the operating room—thus representing potential contamination. Conclusion: We found MPs > 50 µm in placenta and meconium acquired from cesarean delivery. Critical evaluation of potential contamination sources is pivotal and may guide future clinical studies to improve the correct detection of MPs in organ tissue. Studies investigating nano-sized plastics in human tissue are warranted.

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