@article{RedlichZhangBenjaminetal.2022,
  author    = {Redlich, Sarah and Zhang, Jie and Benjamin, Caryl and Dhillon, Maninder Singh and Englmeier, Jana and Ewald, J{\"o}rg and Fricke, Ute and Ganuza, Cristina and Haensel, Maria and Hovestadt, Thomas and Kollmann, Johannes and Koellner, Thomas and K{\"u}bert-Flock, Carina and Kunstmann, Harald and Menzel, Annette and Moning, Christoph and Peters, Wibke and Riebl, Rebekka and Rummler, Thomas and Rojas-Botero, Sandra and Tobisch, Cynthia and Uhler, Johannes and Uphus, Lars and M{\"u}ller, J{\"o}rg and Steffan-Dewenter, Ingolf},
  title     = {Disentangling effects of climate and land use on biodiversity and ecosystem services—A multi-scale experimental design},
  series = {Methods in Ecology and Evolution},
  volume    = {13},
  journal   = {Methods in Ecology and Evolution},
  number    = {2},
  doi       = {10.1111/2041-210X.13759},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-258270},
  pages     = {514-527},
  year      = {2022},
  abstract  = {Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales. Stratifying the state of Bavaria into five climate zones (reference period 1981-2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6-9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5-10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.},
  language  = {en}
}
@article{BousquetAntoBachertetal.2021,
  author    = {Bousquet, Jean and Anto, Josep M. and Bachert, Claus and Haahtela, Tari and Zuberbier, Torsten and Czarlewski, Wienczyslawa and Bedbrook, Anna and Bosnic-Anticevich, Sinthia and Walter Canonica, G. and Cardona, Victoria and Costa, Elisio and Cruz, Alvaro A. and Erhola, Marina and Fokkens, Wytske J. and Fonseca, Joao A. and Illario, Maddalena and Ivancevich, Juan-Carlos and Jutel, Marek and Klimek, Ludger and Kuna, Piotr and Kvedariene, Violeta and Le, LTT and Larenas-Linnemann, D{\´e}sir{\´e}e E. and Laune, Daniel and Louren{\c{c}}o, Olga M. and Mel{\´e}n, Erik and Mullol, Joaquim and Niedoszytko, Marek and Odemyr, Mika{\"e}la and Okamoto, Yoshitaka and Papadopoulos, Nikos G. and Patella, Vincenzo and Pfaar, Oliver and Pham-Thi, Nh{\^a}n and Rolland, Christine and Samolinski, Boleslaw and Sheikh, Aziz and Sofiev, Mikhail and Suppli Ulrik, Charlotte and Todo-Bom, Ana and Tomazic, Peter-Valentin and Toppila-Salmi, Sanna and Tsiligianni, Ioanna and Valiulis, Arunas and Valovirta, Erkka and Ventura, Maria-Teresa and Walker, Samantha and Williams, Sian and Yorgancioglu, Arzu and Agache, Ioana and Akdis, Cezmi A. and Almeida, Rute and Ansotegui, Ignacio J. and Annesi-Maesano, Isabella and Arnavielhe, Sylvie and Basaga{\~n}a, Xavier and D. Bateman, Eric and B{\´e}dard, Annabelle and Bedolla-Barajas, Martin and Becker, Sven and Bennoor, Kazi S. and Benveniste, Samuel and Bergmann, Karl C. and Bewick, Michael and Bialek, Slawomir and E. Billo, Nils and Bindslev-Jensen, Carsten and Bjermer, Leif and Blain, Hubert and Bonini, Matteo and Bonniaud, Philippe and Bosse, Isabelle and Bouchard, Jacques and Boulet, Louis-Philippe and Bourret, Rodolphe and Boussery, Koen and Braido, Fluvio and Briedis, Vitalis and Briggs, Andrew and Brightling, Christopher E. and Brozek, Jan and Brusselle, Guy and Brussino, Luisa and Buhl, Roland and Buonaiuto, Roland and Calderon, Moises A. and Camargos, Paulo and Camuzat, Thierry and Caraballo, Luis and Carriazo, Ana-Maria and Carr, Warner and Cartier, Christine and Casale, Thomas and Cecchi, Lorenzo and Cepeda Sarabia, Alfonso M. and H. Chavannes, Niels and Chkhartishvili, Ekaterine and Chu, Derek K. and Cingi, Cemal and Correia de Sousa, Jaime and Costa, David J. and Courbis, Anne-Lise and Custovic, Adnan and Cvetkosvki, Biljana and D'Amato, Gennaro and da Silva, Jane and Dantas, Carina and Dokic, Dejan and Dauvilliers, Yves and De Feo, Giulia and De Vries, Govert and Devillier, Philippe and Di Capua, Stefania and Dray, Gerard and Dubakiene, Ruta and Durham, Stephen R. and Dykewicz, Mark and Ebisawa, Motohiro and Gaga, Mina and El-Gamal, Yehia and Heffler, Enrico and Emuzyte, Regina and Farrell, John and Fauquert, Jean-Luc and Fiocchi, Alessandro and Fink-Wagner, Antje and Fontaine, Jean-Fran{\c{c}}ois and Fuentes Perez, Jos{\´e} M. and Gemicioğlu, Bilun and Gamkrelidze, Amiran and Garcia-Aymerich, Judith and Gevaert, Philippe and Gomez, Ren{\´e} Maximiliano and Gonz{\´a}lez Diaz, Sandra and Gotua, Maia and Guldemond, Nick A. and Guzm{\´a}n, Maria-Antonieta and Hajjam, Jawad and Huerta Villalobos, Yunuen R. and Humbert, Marc and Iaccarino, Guido and Ierodiakonou, Despo and Iinuma, Tomohisa and Jassem, Ewa and Joos, Guy and Jung, Ki-Suck and Kaidashev, Igor and Kalayci, Omer and Kardas, Przemyslaw and Keil, Thomas and Khaitov, Musa and Khaltaev, Nikolai and Kleine-Tebbe, Jorg and Kouznetsov, Rostislav and Kowalski, Marek L. and Kritikos, Vicky and Kull, Inger and La Grutta, Stefania and Leonardini, Lisa and Ljungberg, Henrik and Lieberman, Philip and Lipworth, Brian and Lodrup Carlsen, Karin C. and Lopes-Pereira, Catarina and Loureiro, Claudia C. and Louis, Renaud and Mair, Alpana and Mahboub, Bassam and Makris, Micha{\"e}l and Malva, Joao and Manning, Patrick and Marshall, Gailen D. and Masjedi, Mohamed R. and Maspero, Jorge F. and Carreiro-Martins, Pedro and Makela, Mika and Mathieu-Dupas, Eve and Maurer, Marcus and De Manuel Keenoy, Esteban and Melo-Gomes, Elisabete and Meltzer, Eli O. and Menditto, Enrica and Mercier, Jacques and Micheli, Yann and Miculinic, Neven and Mihaltan, Florin and Milenkovic, Branislava and Mitsias, Dimitirios I. and Moda, Giuliana and Mogica-Martinez, Maria-Dolores and Mohammad, Yousser and Montefort, Steve and Monti, Ricardo and Morais-Almeida, Mario and M{\"o}sges, Ralph and M{\"u}nter, Lars and Muraro, Antonella and Murray, Ruth and Naclerio, Robert and Napoli, Luigi and Namazova-Baranova, Leyla and Neffen, Hugo and Nekam, Kristoff and Neou, Angelo and Nordlund, Bj{\"o}rn and Novellino, Ettore and Nyembue, Dieudonn{\´e} and O'Hehir, Robyn and Ohta, Ken and Okubo, Kimi and Onorato, Gabrielle L. and Orlando, Valentina and Ouedraogo, Solange and Palamarchuk, Julia and Pali-Sch{\"o}ll, Isabella and Panzner, Peter and Park, Hae-Sim and Passalacqua, Gianni and P{\´e}pin, Jean-Louis and Paulino, Ema and Pawankar, Ruby and Phillips, Jim and Picard, Robert and Pinnock, Hilary and Plavec, Davor and Popov, Todor A. and Portejoie, Fabienne and Price, David and Prokopakis, Emmanuel P. and Psarros, Fotis and Pugin, Benoit and Puggioni, Francesca and Quinones-Delgado, Pablo and Raciborski, Filip and Rajabian-S{\"o}derlund, Rojin and Regateiro, Frederico S. and Reitsma, Sietze and Rivero-Yeverino, Daniela and Roberts, Graham and Roche, Nicolas and Rodriguez-Zagal, Erendira and Rolland, Christine and Roller-Wirnsberger, Regina E. and Rosario, Nelson and Romano, Antonino and Rottem, Menachem and Ryan, Dermot and Salim{\"a}ki, Johanna and Sanchez-Borges, Mario M. and Sastre, Joaquin and Scadding, Glenis K. and Scheire, Sophie and Schmid-Grendelmeier, Peter and Sch{\"u}nemann, Holger J. and Sarquis Serpa, Faradiba and Shamji, Mohamed and Sisul, Juan-Carlos and Sofiev, Mikhail and Sol{\´e}, Dirceu and Somekh, David and Sooronbaev, Talant and Sova, Milan and Spertini, Fran{\c{c}}ois and Spranger, Otto and Stellato, Cristiana and Stelmach, Rafael and Thibaudon, Michel and To, Teresa and Toumi, Mondher and Usmani, Omar and Valero, Antonio A. and Valenta, Rudolph and Valentin-Rostan, Marylin and Pereira, Marilyn Urrutia and van der Kleij, Rianne and Van Eerd, Michiel and Vandenplas, Olivier and Vasankari, Tuula and Vaz Carneiro, Antonio and Vezzani, Giorgio and Viart, Fr{\´e}d{\´e}ric and Viegi, Giovanni and Wallace, Dana and Wagenmann, Martin and Wang, De Yun and Waserman, Susan and Wickman, Magnus and Williams, Dennis M. and Wong, Gary and Wroczynski, Piotr and Yiallouros, Panayiotis K. and Yusuf, Osman M. and Zar, Heather J. and Zeng, St{\´e}phane and Zernotti, Mario E. and Zhang, Luo and Shan Zhong, Nan and Zidarn, Mihaela},
  title     = {ARIA digital anamorphosis: Digital transformation of health and care in airway diseases from research to practice},
  series = {Allergy},
  volume    = {76},
  journal   = {Allergy},
  number    = {1},
  doi       = {10.1111/all.14422},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-228339},
  pages     = {168 -- 190},
  year      = {2021},
  abstract  = {Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.},
  language  = {en}
}
@article{ChopraBiehlSteinfattetal.2016,
  author    = {Chopra, Martin and Biehl, Marlene and Steinfatt, Tim and Brandl, Andreas and Kums, Juliane and Amich, Jorge and Vaeth, Martin and Kuen, Janina and Holtappels, Rafaela and Podlech, J{\"u}rgen and Mottok, Anja and Kraus, Sabrina and Jord{\´a}n-Garotte, Ana-Laura and B{\"a}uerlein, Carina A. and Brede, Christian and Ribechini, Eliana and Fick, Andrea and Seher, Axel and Polz, Johannes and Ottmueller, Katja J. and Baker, Jeannette and Nishikii, Hidekazu and Ritz, Miriam and Mattenheimer, Katharina and Schwinn, Stefanie and Winter, Thorsten and Sch{\"a}fer, Viktoria and Krappmann, Sven and Einsele, Hermann and M{\"u}ller, Thomas D. and Reddehase, Matthias J. and Lutz, Manfred B. and M{\"a}nnel, Daniela N. and Berberich-Siebelt, Friederike and Wajant, Harald and Beilhack, Andreas},
  title     = {Exogenous TNFR2 activation protects from acute GvHD via host T reg cell expansion},
  series = {Journal of Experimental Medicine},
  volume    = {213},
  journal   = {Journal of Experimental Medicine},
  number    = {9},
  doi       = {10.1084/jem.20151563},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-187640},
  pages     = {1881-1900},
  year      = {2016},
  abstract  = {Donor CD4\(^+\)Foxp3\(^+\) regulatory T cells (T reg cells) suppress graft-versus-host disease (GvHD) after allogeneic hematopoietic stem cell transplantation (HCT allo-HCT]). Current clinical study protocols rely on the ex vivo expansion of donor T reg cells and their infusion in high numbers. In this study, we present a novel strategy for inhibiting GvHD that is based on the in vivo expansion of recipient T reg cells before allo-HCT, exploiting the crucial role of tumor necrosis factor receptor 2 (TNFR2) in T reg cell biology. Expanding radiation-resistant host T reg cells in recipient mice using a mouse TNFR2-selective agonist before allo-HCT significantly prolonged survival and reduced GvHD severity in a TNFR2-and T reg cell-dependent manner. The beneficial effects of transplanted T cells against leukemia cells and infectious pathogens remained unaffected. A corresponding human TNFR2-specific agonist expanded human T reg cells in vitro. These observations indicate the potential of our strategy to protect allo-HCT patients from acute GvHD by expanding T reg cells via selective TNFR2 activation in vivo.},
  language  = {en}
}
@article{CecilRikanovicOhlsenetal.2011,
  author    = {Cecil, Alexander and Rikanovic, Carina and Ohlsen, Knut and Liang, Chunguang and Bernhardt, Jorg and Oelschlaeger, Tobias A. and Gulder, Tanja and Bringmann, Gerd and Holzgrabe, Ulrike and Unger, Matthias and Dandekar, Thomas},
  title     = {Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-68802},
  year      = {2011},
  abstract  = {Background: Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results: Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions: The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics.},
  subject      = {Staphylococcus aureus},
  language  = {en}
}
@article{PietroGarciaHartmannReisslandetal.2022,
  author    = {Pietro-Garcia, Christian and Hartmann, Oliver and Reissland, Michaela and Fischer, Thomas and Maier, Carina R. and Rosenfeldt, Mathias and Sch{\"u}lein-V{\"o}lk, Christina and Klann, Kevin and Kalb, Reinhard and Dikic, Ivan and M{\"u}nch, Christian and Diefenbacher, Markus E.},
  title     = {Inhibition of USP28 overcomes Cisplatin-resistance of squamous tumors by suppression of the Fanconi anemia pathway},
  series = {Cell Death and Differentiation},
  volume    = {29},
  journal   = {Cell Death and Differentiation},
  number    = {3},
  issn      = {1476-5403},
  doi       = {10.1038/s41418-021-00875-z},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-273014},
  pages     = {568-584},
  year      = {2022},
  abstract  = {Squamous cell carcinomas (SCC) frequently have an exceptionally high mutational burden. As consequence, they rapidly develop resistance to platinum-based chemotherapy and overall survival is limited. Novel therapeutic strategies are therefore urgently required. SCC express ∆Np63, which regulates the Fanconi Anemia (FA) DNA-damage response in cancer cells, thereby contributing to chemotherapy-resistance. Here we report that the deubiquitylase USP28 is recruited to sites of DNA damage in cisplatin-treated cells. ATR phosphorylates USP28 and increases its enzymatic activity. This phosphorylation event is required to positively regulate the DNA damage repair in SCC by stabilizing ∆Np63. Knock-down or inhibition of USP28 by a specific inhibitor weakens the ability of SCC to cope with DNA damage during platin-based chemotherapy. Hence, our study presents a novel mechanism by which ∆Np63 expressing SCC can be targeted to overcome chemotherapy resistance. Limited treatment options and low response rates to chemotherapy are particularly common in patients with squamous cancer. The SCC specific transcription factor ∆Np63 enhances the expression of Fanconi Anemia genes, thereby contributing to recombinational DNA repair and Cisplatin resistance. Targeting the USP28-∆Np63 axis in SCC tones down this DNA damage response pathways, thereby sensitizing SCC cells to cisplatin treatment.},
  language  = {en}
}
@article{HartmannReisslandMaieretal.2021,
  author    = {Hartmann, Oliver and Reissland, Michaela and Maier, Carina R. and Fischer, Thomas and Prieto-Garcia, Cristian and Baluapuri, Apoorva and Schwarz, Jessica and Schmitz, Werner and Garrido-Rodriguez, Martin and Pahor, Nikolett and Davies, Clare C. and Bassermann, Florian and Orian, Amir and Wolf, Elmar and Schulze, Almut and Calzado, Marco A. and Rosenfeldt, Mathias T. and Diefenbacher, Markus E.},
  title     = {Implementation of CRISPR/Cas9 Genome Editing to Generate Murine Lung Cancer Models That Depict the Mutational Landscape of Human Disease},
  series = {Frontiers in Cell and Developmental Biology},
  volume    = {9},
  journal   = {Frontiers in Cell and Developmental Biology},
  issn      = {2296-634X},
  doi       = {10.3389/fcell.2021.641618},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-230949},
  year      = {2021},
  abstract  = {Lung cancer is the most common cancer worldwide and the leading cause of cancer-related deaths in both men and women. Despite the development of novel therapeutic interventions, the 5-year survival rate for non-small cell lung cancer (NSCLC) patients remains low, demonstrating the necessity for novel treatments. One strategy to improve translational research is the development of surrogate models reflecting somatic mutations identified in lung cancer patients as these impact treatment responses. With the advent of CRISPR-mediated genome editing, gene deletion as well as site-directed integration of point mutations enabled us to model human malignancies in more detail than ever before. Here, we report that by using CRISPR/Cas9-mediated targeting of Trp53 and KRas, we recapitulated the classic murine NSCLC model Trp53fl/fl:lsl-KRasG12D/wt. Developing tumors were indistinguishable from Trp53fl/fl:lsl-KRasG12D/wt-derived tumors with regard to morphology, marker expression, and transcriptional profiles. We demonstrate the applicability of CRISPR for tumor modeling in vivo and ameliorating the need to use conventional genetically engineered mouse models. Furthermore, tumor onset was not only achieved in constitutive Cas9 expression but also in wild-type animals via infection of lung epithelial cells with two discrete AAVs encoding different parts of the CRISPR machinery. While conventional mouse models require extensive husbandry to integrate new genetic features allowing for gene targeting, basic molecular methods suffice to inflict the desired genetic alterations in vivo. Utilizing the CRISPR toolbox, in vivo cancer research and modeling is rapidly evolving and enables researchers to swiftly develop new, clinically relevant surrogate models for translational research.},
  language  = {en}
}
@article{DhillonDahmsKuebertFlocketal.2023,
  author    = {Dhillon, Maninder Singh and Dahms, Thorsten and Kuebert-Flock, Carina and Rummler, Thomas and Arnault, Joel and Steffan-Dewenter, Ingolf and Ullmann, Tobias},
  title     = {Integrating random forest and crop modeling improves the crop yield prediction of winter wheat and oil seed rape},
  series = {Frontiers in Remote Sensing},
  volume    = {3},
  journal   = {Frontiers in Remote Sensing},
  issn      = {2673-6187},
  doi       = {10.3389/frsen.2022.1010978},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-301462},
  year      = {2023},
  abstract  = {The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security. However, the consistency and reliability of suitable methodologies that provide accurate crop yield outcomes still need to be explored. The study investigates the coupling of crop modeling and machine learning (ML) to improve the yield prediction of winter wheat (WW) and oil seed rape (OSR) and provides examples for the Free State of Bavaria (70,550 km2), Germany, in 2019. The main objectives are to find whether a coupling approach [Light Use Efficiency (LUE) + Random Forest (RF)] would result in better and more accurate yield predictions compared to results provided with other models not using the LUE. Four different RF models [RF1 (input: Normalized Difference Vegetation Index (NDVI)), RF2 (input: climate variables), RF3 (input: NDVI + climate variables), RF4 (input: LUE generated biomass + climate variables)], and one semi-empiric LUE model were designed with different input requirements to find the best predictors of crop monitoring. The results indicate that the individual use of the NDVI (in RF1) and the climate variables (in RF2) could not be the most accurate, reliable, and precise solution for crop monitoring; however, their combined use (in RF3) resulted in higher accuracies. Notably, the study suggested the coupling of the LUE model variables to the RF4 model can reduce the relative root mean square error (RRMSE) from -8\% (WW) and -1.6\% (OSR) and increase the R 2 by 14.3\% (for both WW and OSR), compared to results just relying on LUE. Moreover, the research compares models yield outputs by inputting three different spatial inputs: Sentinel-2(S)-MOD13Q1 (10 m), Landsat (L)-MOD13Q1 (30 m), and MOD13Q1 (MODIS) (250 m). The S-MOD13Q1 data has relatively improved the performance of models with higher mean R 2 [0.80 (WW), 0.69 (OSR)], and lower RRMSE (\%) (9.18, 10.21) compared to L-MOD13Q1 (30 m) and MOD13Q1 (250 m). Satellite-based crop biomass, solar radiation, and temperature are found to be the most influential variables in the yield prediction of both crops.},
  language  = {en}
}
@article{DhillonKuebertFlockDahmsetal.2023,
  author    = {Dhillon, Maninder Singh and K{\"u}bert-Flock, Carina and Dahms, Thorsten and Rummler, Thomas and Arnault, Joel and Steffan-Dewenter, Ingolf and Ullmann, Tobias},
  title     = {Evaluation of MODIS, Landsat 8 and Sentinel-2 data for accurate crop yield predictions: a case study using STARFM NDVI in Bavaria, Germany},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {7},
  issn      = {2072-4292},
  doi       = {10.3390/rs15071830},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311132},
  year      = {2023},
  abstract  = {The increasing availability and variety of global satellite products and the rapid development of new algorithms has provided great potential to generate a new level of data with different spatial, temporal, and spectral resolutions. However, the ability of these synthetic spatiotemporal datasets to accurately map and monitor our planet on a field or regional scale remains underexplored. This study aimed to support future research efforts in estimating crop yields by identifying the optimal spatial (10 m, 30 m, or 250 m) and temporal (8 or 16 days) resolutions on a regional scale. The current study explored and discussed the suitability of four different synthetic (Landsat (L)-MOD13Q1 (30 m, 8 and 16 days) and Sentinel-2 (S)-MOD13Q1 (10 m, 8 and 16 days)) and two real (MOD13Q1 (250 m, 8 and 16 days)) NDVI products combined separately to two widely used crop growth models (CGMs) (World Food Studies (WOFOST), and the semi-empiric Light Use Efficiency approach (LUE)) for winter wheat (WW) and oil seed rape (OSR) yield forecasts in Bavaria (70,550 km\(^2\)) for the year 2019. For WW and OSR, the synthetic products' high spatial and temporal resolution resulted in higher yield accuracies using LUE and WOFOST. The observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 played a significant role in accurately measuring the yield of WW and OSR. For example, L- and S-MOD13Q1 resulted in an R\(^2\) = 0.82 and 0.85, RMSE = 5.46 and 5.01 dt/ha for WW, R\(^2\) = 0.89 and 0.82, and RMSE = 2.23 and 2.11 dt/ha for OSR using the LUE model, respectively. Similarly, for the 8- and 16-day products, the simple LUE model (R\(^2\) = 0.77 and relative RMSE (RRMSE) = 8.17\%) required fewer input parameters to simulate crop yield and was highly accurate, reliable, and more precise than the complex WOFOST model (R\(^2\) = 0.66 and RRMSE = 11.35\%) with higher input parameters. Conclusively, both S-MOD13Q1 and L-MOD13Q1, in combination with LUE, were more prominent for predicting crop yields on a regional scale than the 16-day products; however, L-MOD13Q1 was advantageous for generating and exploring the long-term yield time series due to the availability of Landsat data since 1982, with a maximum resolution of 30 m. In addition, this study recommended the further use of its findings for implementing and validating the long-term crop yield time series in different regions of the world.},
  language  = {en}
}
@article{MartinRommelThomasetal.2022,
  author    = {Martin, Tamara and Rommel, Kathrin and Thomas, Carina and Eymann, Jutta and Kretschmer, Tanita and Berner, Reinhard and Lee-Kirsch, Min Ae and Hebestreit, Helge},
  title     = {Seltene Erkrankungen in den Daten sichtbar machen - Kodierung},
  series = {Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz},
  volume    = {65},
  journal   = {Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz},
  number    = {11},
  doi       = {10.1007/s00103-022-03598-9},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324275},
  pages     = {1133-1142},
  year      = {2022},
  abstract  = {Seltene Erkrankungen (SE) werden durch die im deutschen Gesundheitssystem verwendete Diagnosenklassifikation ICD-10-GM (International Statistical Classification of Diseases and Related Health problems, 10th Revision, German Modification) nur zu einem kleinen Teil eindeutig erfasst. Daher sind Aussagen zur H{\"a}ufigkeit von SE sowie zum speziellen Versorgungs- und Finanzierungsbedarf nicht m{\"o}glich, was zu einer l{\"u}ckenhaften Datenlage als Entscheidungsgrundlage f{\"u}r Krankenkassen, Leistungserbringer und Gesundheitspolitik f{\"u}hrt. Das Fehlen exakter Informationen behindert auch die wissenschaftliche Arbeit. Daher wird deutschlandweit ab 2023 die Verwendung der Alpha-ID-SE-Datei und der ORPHAcodes f{\"u}r die spezifische Erfassung von SE bei station{\"a}ren F{\"a}llen verpflichtend. Die Alpha-ID-SE-Datei verkn{\"u}pft die ICD-10-GM-Kodes mit den international anerkannten ORPHAcodes f{\"u}r die Diagnose von SE. Kommerzielle Anbieter stellen zunehmend die ben{\"o}tigten IT-Tools zur Kodierung von SE zur Verf{\"u}gung. An mehreren Universit{\"a}tskliniken mit Zentren f{\"u}r SE wurden L{\"o}sungen etabliert, die eine vollst{\"a}ndige Kodierung gew{\"a}hrleisten sollen. Hierzu geh{\"o}ren finanzielle Anreize f{\"u}r die kodierenden Bereiche, konkrete Nachfragen nach dem Vorliegen einer SE beim Kodiervorgang und eine semiautomatische Kodierung bei Patient*innen, die schon einmal mit einer SE an der Einrichtung betreut worden waren. Eine Kombination der verschiedenen Ans{\"a}tze verspricht die h{\"o}chste Wahrscheinlichkeit einer vollst{\"a}ndigen Kodierung. F{\"u}r ein umf{\"a}ngliches Bild der SE im Gesundheitssystem und um dem speziellen Versorgungs- und Finanzierungsbedarf besser Rechnung tragen zu k{\"o}nnen, w{\"a}re auch im ambulanten Bereich eine m{\"o}glichst spezifische und eindeutige Kodierung w{\"u}nschenswert. F{\"u}r komplexe SE und bisher undiagnostizierte Patient*innen wird zus{\"a}tzlich eine strukturierte Erfassung des Ph{\"a}notyps ben{\"o}tigt.},
  language  = {de}
}
@article{DhillonDahmsKuebertFlocketal.2023,
  author    = {Dhillon, Maninder Singh and Dahms, Thorsten and K{\"u}bert-Flock, Carina and Liepa, Adomas and Rummler, Thomas and Arnault, Joel and Steffan-Dewenter, Ingolf and Ullmann, Tobias},
  title     = {Impact of STARFM on crop yield predictions: fusing MODIS with Landsat 5, 7, and 8 NDVIs in Bavaria Germany},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {6},
  issn      = {2072-4292},
  doi       = {10.3390/rs15061651},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311092},
  year      = {2023},
  abstract  = {Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km\(^2\)), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R\(^2\) of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R\(^2\) of yearly synthetic NDVIs and N) and -0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R\(^2\) of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R\(^2\) = 0.88) and OSR (R\(^2\) = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R\(^2\) of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.},
  language  = {en}
}