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Neurodegenerative diseases show an increase in prevalence and incidence, with the most prominent example being Alzheimer's disease. DNA damage has been suggested to play a role in the pathogenesis, but the exact mechanisms remain elusive. We enrolled 425 participants with and without neurodegenerative diseases and analyzed DNA damage in the form of micronuclei in buccal mucosa samples. In addition, other parameters such as binucleated cells, karyolytic cells, and karyorrhectic cells were quantified. No relevant differences in DNA damage and cytotoxicity markers were observed in patients compared to healthy participants. Furthermore, other parameters such as lifestyle factors and diseases were also investigated. Overall, this study could not identify a direct link between changes in buccal cells and neurogenerative diseases, but highlights the influence of lifestyle factors and diseases on the human buccal cytome.
The use of inverse methods allow efficient model calibration. This study employs PEST to calibrate a large catchment scale transient flow model. Results are demonstrated by comparing manually calibrated approaches with the automated approach. An advanced Tikhonov regularization algorithm was employed for carrying out the automated pilot point (PP) method. The results indicate that automated PP is more flexible and robust as compared to other approaches. Different statistical indicators show that this method yields reliable calibration as values of coefficient of determination (R-2) range from 0.98 to 0.99, Nash Sutcliffe efficiency (ME) range from 0.964 to 0.976, and root mean square errors (RMSE) range from 1.68 m to 1.23 m, for manual and automated approaches, respectively. Validation results of automated PP show ME as 0.969 and RMSE as 1.31 m. The results of output sensitivity suggest that hydraulic conductivity is a more influential parameter. Considering the limitations of the current study, it is recommended to perform global sensitivity and linear uncertainty analysis for the better estimation of the modelling results.