@misc{LyuFuWilczoketal., author = {Lyu, Yu-Xuan and Fu, Qiang and Wilczok, Dominika and Ying, Kejun and King, Aaron and Antebi, Adam and Vojta, Aleksandar and Stolzing, Alexandra and Moskalev, Alexey and Georgievskaya, Anastasia and Maier, Andrea B. and Olsen, Andrea and Groth, Anja and Simon, Anna Katharina and Brunet, Anne and Jamil, Aisyah and Kulaga, Anton and Bhatti, Asif and Yaden, Benjamin and Pedersen, Bente Klarlund and Schumacher, Bj{\"o}rn and Djordjevic, Boris and Kennedy, Brian and Chen, Chieh and Huang, Christine Yuan and Correll, Christoph U. and Murphy, Coleen T. and Ewald, Collin Y. and Chen, Danica and Valenzano, Dario Riccardo and Sołdacki, Dariusz and Erritzoe, David and Meyer, David and Sinclair, David A. and Chini, Eduardo Nunes and Teeling, Emma C. and Morgen, Eric and Verdin, Eric and Vernet, Erik and Pinilla, Estefano and Fang, Evandro F. and Bischof, Evelyne and Mercken, Evi M. and Finger, Fabian and Kuipers, Folkert and Pun, Frank W. and Gy{\"u}lveszi, Gabor and Civiletto, Gabriele and Zmudze, Garri and Blander, Gil and Pincus, Harold A. and McClure, Joshua and Kirkland, James L. and Peyer, James and Justice, Jamie N. and Vijg, Jan and Gruhn, Jennifer R. and McLaughlin, Jerry and Mannick, Joan and Passos, Jo{\~a}o and Baur, Joseph A. and Betts-LaCroix, Joe and Sedivy, John M. and Speakman, John R. and Shlain, Jordan and Maltzahn, Julia von and Andreasson, Katrin I. and Moody, Kelsey and Palikaras, Konstantinos and Fortney, Kristen and Niedernhofer, Laura J. and Rasmussen, Lene Juel and Veenhoff, Liesbeth M. and Melton, Lisa and Ferrucci, Luigi and Quarta, Marco and Koval, Maria and Marinova, Maria and Hamalainen, Mark and Unfried, Maximilian and Ringel, Michael S. and Filipovic, Milos and Topors, Mourad and Mitin, Natalia and Roy, Nawal and Pintar, Nika and Barzilai, Nir and Binetti, Paolo and Singh, Parminder and Kohlhaas, Paul and Robbins, Paul D. and Rubin, Paul and Fedichev, Peter O. and Kamya, Petrina and Mu{\~n}oz-Canoves, Pura and de Cabo, Rafael and Faragher, Richard G. A. and Konrad, Rob and Ripa, Roberto and Mansukhani, Robin and B{\"u}ttner, Sabrina and Wickstr{\"o}m, Sara A. and Brunemeier, Sebastian and Jakimov, Sergey and Luo, Shan and Rosenzweig-Lipson, Sharon and Tsai, Shih-Yin and Dimmeler, Stefanie and Rando, Thomas A. and Peterson, Tim R. and Woods, Tina and Wyss-Coray, Tony and Finkel, Toren and Strauss, Tzipora and Gladyshev, Vadim N. and Longo, Valter D. and Dwaraka, Varun B. and Gorbunova, Vera and Acosta-Rodr{\´i}guez, Victoria A. and Sorrentino, Vincenzo and Sebastiano, Vittorio and Li, Wenbin and Suh, Yousin and Zhavoronkov, Alex and Scheibye-Knudsen, Morten and Bakula, Daniela}, title = {Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity}, series = {Aging}, volume = {16}, journal = {Aging}, number = {20}, publisher = {Impact Journals, LLC}, issn = {1945-4589}, doi = {10.18632/aging.206135}, pages = {12955 -- 12976}, language = {en} } @misc{SchulteHubbertKuepperThomasetal., author = {Schulte-Hubbert, Ruth and K{\"u}pper, Jan-Heiner and Thomas, Adam D. and Schrenk, Dieter}, title = {Estragole: DNA adduct formation in primary rat hepatocytes and genotoxic potential in HepG2-CYP1A2 cells}, series = {Toxicology}, volume = {444}, journal = {Toxicology}, issn = {0300-483X}, doi = {10.1016/j.tox.2020.152566}, pages = {8}, abstract = {Estragole is a natural constituent in herbs and spices and in products thereof such as essential oils or herbal teas. After cytochrome P450-catalyzed hydroxylation and subsequent sulfation, estragole acts as a genotoxic hepatocarcinogen forming DNA adducts in rodent liver. Because of the genotoxic mode of action and the widespread occurrence in food and phytomedicines a refined risk assessment for estragole is needed. We analyzed the time- and concentration-dependent levels of the DNA adducts N2-(isoestragole-3'-yl)-2'-desoxyguanosine (E3′N2dG) and N6-(isoestragole-3'-yl)-desoxyadenosine (E3′N6dA), reported to be the major adducts formed in rat liver, in rat hepatocytes (pRH) in primary culture after incubation with estragole. DNA adduct levels were measured via UHPLC-ESI-MS/MS using stable isotope dilution analysis. Both adducts were formed in pRH and could already be quantified after an incubation time of 1 h (E3′N6dA at 10 μM, E3′N2dG at 1μM estragole). E3′N2dG, the main adduct at all incubation times and concentrations, could be detected at estragole concentrations < 0.1 μM after 24 h and < 0.5 μM after 48 h. Adduct levels were highest after 6 h and showed a downward trend at later time-points, possibly due to DNA repair and/or apoptosis. While the concentration-response characteristics of adduct formation were apparently linear over the whole concentration range, strong indication for marked hypo-linearity was obtained when the modeling was based on concentrations < 1 μM only. In the micronucleus assay no mutagenic potential of estragole was found in HepG2 cells whereas in HepG2-CYP1A2 cells 1 μM estragole led to a 3.2 fold and 300 μM to a 7.1 fold increase in micronuclei counts. Our findings suggest the existence of a 'practical threshold' dose for DNA adduct formation as an initiating key event of the carcinogenicity of estragole indicating that the default assumption of concentration-response-linearity is questionable, at least for the two major adducts studied here.}, language = {en} } @misc{CouedelFalconnierAdametal., author = {Cou{\"e}del, Antoine and Falconnier, Gatien N. and Adam, Myriam and Cardinael, R{\´e}mi and Boote, Kenneth and Justes, Eric and Smith, Ward N. and Whitbread, Anthony Michael and Affholder, Fran{\c{c}}ois and Balkovic, Juraj and Basso, Bruno and Bhatia, Arti and Chakrabarti, Bidisha and Chikowo, Regis and Christina, Mathias and Faye, Babacar and Ferchaud, Fabien and Folberth, Christian and Akinseye, Folorunso M. and Gaiser, Thomas and Galdos, Marcelo V. and Gayler, Sebastian and Gorooei, Aram and Grant, Brian and Guibert, Herv{\´e} and Hoogenboom, Gerrit and Kamali, Bahareh and Laub, Moritz and Maureira, Fidel and Mequanint, Fasil and Nendel, Claas and Porter, Cheryl H. and Ripoche, Dominique and Ruane, Alex C. and Rusinamhodzi, Leonard and Sharma, Shikha and Singh, Upendra and Six, Johan and Srivastava, Amit Kumar and Vanlauwe, Bernard and Versini, Antoine and Vianna, Murilo and Webber, Heidi and Weber, Tobias K. D. and Zhang, Congmu and Corbeels, Marc}, title = {Long-term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa}, series = {European Journal of Agronomy}, volume = {155}, journal = {European Journal of Agronomy}, publisher = {Elsevier BV}, issn = {1161-0301}, doi = {10.1016/j.eja.2024.127109}, pages = {16}, abstract = {Food insecurity in sub-Saharan Africa is partly due to low staple crop yields, resulting from poor soil fertility and low nutrient inputs. Integrated soil fertility management (ISFM), which includes the combined use of mineral and organic fertilizers, can contribute to increasing yields and sustaining soil organic carbon (SOC) in the long term. Soil-crop simulation models can help assess the performance and trade-offs of a range of crop management practices including ISFM, under current and future climate. Yet, uncertainty in model simulations can be high, resulting from poor model calibration and/or inadequate model structure. Multi-model simulations have been shown to be more robust than those with single models and help understand and reduce modelling uncertainty. In this study, we aim to perform the first multi-model comparison for long-term simulations of crop yield and SOC and their feedbacks in SSA. We evaluated the performance of 16 soil-crop models using data from four long-term maize experiments at sites in SSA with contrasting climates and soils. Each experiment had four treatments: i) no exogenous inputs, ii) addition of mineral nitrogen (N) fertilizer, iii) use of organic amendments, and iv) combined use of mineral and organic inputs. We assessed model performance in two steps: through blind calibration involving a minimum level of experimental data provided to the modeling teams, and subsequently through full calibration, which included a more extensive set of observational data. Model ensemble accuracy was greater with full calibration than blind calibration. Improvement in model accuracy was larger for maize yields (nRMSE 48 vs 18\%) than for topsoil SOC (nRMSE 22 vs 14\%). Model ensemble uncertainty (defined as the coefficient of variation across the 16 models) increased over the duration of the long-term experiments. Uncertainty of SOC simulations increased when organic amendments were used, whilst uncertainty of yield predictions was largest when no inputs were applied. Our study revealed large discrepancies among the models in simulating i) crop-to-soil feedbacks due to uncertainties in simulated carbon coming from roots, and ii) soil-to-crop feedbacks due to large uncertainties in simulated crop N supply from soil organic matter decomposition. These discrepancies were largest when organic amendments were applied. The results highlight the need for long-term experiments in which root and soil N dynamics are monitored. This will provide the corresponding data to improve and calibrate soil-crop models, which will lead to more robust and reliable simulations of SOC and crop productivity, and their interactions.}, language = {en} }