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- ItemTofacitinib Loaded Squalenyl Nanoparticles for Targeted Follicular Delivery in Inflammatory Skin Diseases(Basel : MDPI, 2020) Christmann, Rebekka; Ho, Duy-Khiet; Wilzopolski, Jenny; Lee, Sangeun; Koch, Marcus; Loretz, Brigitta; Vogt, Thomas; Bäumer, Wolfgang; Schaefer, Ulrich F.; Lehr, Claus-MichaelTofacitinib (TFB), a Janus kinase inhibitor, has shown excellent success off-label in treating various dermatological diseases, especially alopecia areata (AA). However, TFB’s safe and targeted delivery into hair follicles (HFs) is highly desirable due to its systemic adverse effects. Nanoparticles (NPs) can enhance targeted follicular drug delivery and minimize interfollicular permeation and thereby reduce systemic drug exposure. In this study, we report a facile method to assemble the stable and uniform 240 nm TFB loaded squalenyl derivative (SqD) nanoparticles (TFB SqD NPs) in aqueous solution, which allowed an excellent loading capacity (LC) of 20%. The SqD NPs showed an enhanced TFB delivery into HFs compared to the aqueous formulations of plain drug in an ex vivo pig ear model. Furthermore, the therapeutic efficacy of the TFB SqD NPs was studied in a mouse model of allergic dermatitis by ear swelling reduction and compared to TFB dissolved in a non-aqueous mixture of acetone and DMSO (7:1 v/v). Whereas such formulation would not be acceptable for use in the clinic, the TFB SqD NPs dispersed in water illustrated a better reduction in inflammatory effects than plain TFB’s aqueous formulation, implying both encouraging good in vivo efficacy and safety. These findings support the potential of TFB SqD NPs for developing a long-term topical therapy of AA.
- ItemHuman displacements from Tropical Cyclone Idai attributable to climate change(Katlenburg-Lindau : European Geophysical Society, 2023) Mester, Benedikt; Vogt, Thomas; Bryant, Seth; Otto, Christian; Frieler, Katja; Schewe, JacobExtreme weather events, such as tropical cyclones, often trigger population displacement. The frequency and intensity of tropical cyclones are affected by anthropogenic climate change. However, the effect of historical climate change on displacement risk has so far not been quantified. Here, we show how displacement can be partially attributed to climate change using the example of the 2019 Tropical Cyclone Idai in Mozambique. We estimate the population exposed to high water levels following Idai's landfall using a combination of a 2D hydrodynamical storm surge model and a flood depth estimation algorithm to determine inland flood depths from remote sensing images, factual (climate change) and counterfactual (no climate change) mean sea level, and maximum wind speed conditions. Our main estimates indicate that climate change has increased displacement risk from this event by approximately 12 600-14 900 additional displaced persons, corresponding to about 2.7 % to 3.2 % of the observed displacements. The isolated effect of wind speed intensification is double that of sea level rise. These results are subject to important uncertainties related to both data and modeling assumptions, and we perform multiple sensitivity experiments to assess the range of uncertainty where possible. Besides highlighting the significant effects on humanitarian conditions already imparted by climate change, our study provides a blueprint for event-based displacement attribution.
- ItemIntercomparison of regional loss estimates from global synthetic tropical cyclone models([London] : Nature Publishing Group UK, 2022) Meiler, Simona; Vogt, Thomas; Bloemendaal, Nadia; Ciullo, Alessio; Lee, Chia-Ying; Camargo, Suzana J.; Emanuel, Kerry; Bresch, David N.Tropical cyclones (TCs) cause devastating damage to life and property. Historical TC data is scarce, complicating adequate TC risk assessments. Synthetic TC models are specifically designed to overcome this scarcity. While these models have been evaluated on their ability to simulate TC activity, no study to date has focused on model performance and applicability in TC risk assessments. This study performs the intercomparison of four different global-scale synthetic TC datasets in the impact space, comparing impact return period curves, probability of rare events, and hazard intensity distribution over land. We find that the model choice influences the costliest events, particularly in basins with limited TC activity. Modelled direct economic damages in the North Indian Ocean, for instance, range from 40 to 246 billion USD for the 100-yr event over the four hazard sets. We furthermore provide guidelines for the suitability of the different synthetic models for various research purposes.