@incollection{KochJacobsenOertel, author = {Koch, Marco and Jacobsen, Heike and Oertel, Britta}, title = {Einf{\"u}hrung}, series = {Dienstleistungen f{\"u}r die energieeffiziente Stadt}, booktitle = {Dienstleistungen f{\"u}r die energieeffiziente Stadt}, editor = {Koch, Marco and Jacobsen, Heike and Oertel, Britta}, publisher = {LIT}, address = {M{\"u}nster}, isbn = {978-3-643-13287-1}, pages = {IX -- XI}, language = {de} } @misc{HenzeHuettnerKochetal., author = {Henze, Henriette and H{\"u}ttner, S{\"o}ren S. and Koch, Philipp and Sch{\"u}ler, Svenja C. and Groth, Marco and von Eyss, Bj{\"o}rn and von Maltzahn, Julia}, title = {Denervation alters the secretome of myofibers and thereby affects muscle stem cell lineage progression and functionality}, series = {npj regenerative medicine}, volume = {9}, journal = {npj regenerative medicine}, number = {1}, publisher = {Nature Publishing Group UK}, address = {London}, issn = {2057-3995}, doi = {10.1038/s41536-024-00353-3}, pages = {1 -- 14}, abstract = {Skeletal muscle function crucially depends on innervation while repair of skeletal muscle relies on resident muscle stem cells (MuSCs). However, it is poorly understood how innervation affects MuSC properties and thereby regeneration of skeletal muscle. Here, we report that loss of innervation causes precocious activation of MuSCs concomitant with the expression of markers of myogenic differentiation. This aberrant activation of MuSCs after loss of innervation is accompanied by profound alterations on the mRNA and protein level. Combination of muscle injury with loss of innervation results in impaired regeneration of skeletal muscle including shifts in myogenic populations concomitant with delayed maturation of regenerating myofibers. We further demonstrate that loss of innervation leads to alterations in myofibers and their secretome, which then affect MuSC behavior. In particular, we identify an increased secretion of Osteopontin and transforming growth factor beta 1 (Tgfb1) by myofibers isolated from mice which had undergone sciatic nerve transection. The altered secretome results in the upregulation of early activating transcription factors, such as Junb , and their target genes in MuSCs. However, the combination of different secreted factors from myofibers after loss of innervation is required to cause the alterations observed in MuSCs after loss of innervation. These data demonstrate that loss of innervation first affects myofibers causing alterations in their secretome which then affect MuSCs underscoring the importance of proper innervation for MuSC functionality and regeneration of skeletal muscle.}, language = {en} } @misc{HeymanProniziusLewisetal., author = {Heyman, Tom and Pronizius, Ekaterina and Lewis, Savannah C. and Acar, Oguz A. and Adamkovič, Mat{\´u}š and Ambrosini, Ettore and Antfolk, Jan and Barzykowski, Krystian and Baskin, Ernest and Batres, Carlota and Boucher, Leanne and Boudesseul, Jordane and Brandst{\"a}tter, Eduard and Collins, W. Matthew and Filipović Ðurđević, Dušica and Egan, Ciara and Era, Vanessa and Ferreira, Paulo and Fini, Chiara and Garrido-V{\´a}squez, Patricia and Godbersen, Hendrik and Gomez, Pablo and Graton, Aurelien and Gurkan, Necdet and He, Zhiran and Johnson, Dave C. and Kačm{\´a}r, Pavol and Koch, Chris and Kowal, Marta and Kratochvil, Tomas and Marelli, Marco and Marmolejo-Ramos, Fernando and Mart{\´i}nez, Mart{\´i}n and Mattiassi, Alan and Maxwell, Nicholas P. and Montefinese, Maria and Morvinski, Coby and Neta, Maital and Nielsen, Yngwie A. and Ocklenburg, Sebastian and Onič, Jaš and Papadatou-Pastou, Marietta and Parker, Adam J. and Paruzel-Czachura, Mariola and Pavlov, Yuri G. and Perea, Manuel and Pfuhl, Gerit and Roembke, Tanja C. and R{\"o}er, Jan P. and Roettger, Timo B and Ruiz-Fernandez, Susana and Schmidt, Kathleen}, title = {Crowdsourcing multiverse analyses to explore the impact of different data-processing and analysis decisions : a tutorial}, series = {Psychological methods}, journal = {Psychological methods}, publisher = {American Psychological Association (APA)}, address = {Washington, DC}, issn = {1939-1463}, doi = {10.1037/met0000770}, abstract = {When processing and analyzing empirical data, researchers regularly face choices that may appear arbitrary (e.g., how to define and handle outliers). If one chooses to exclusively focus on a particular option and conduct a single analysis, its outcome might be of limited utility. That is, one remains agnostic regarding the generalizability of the results, because plausible alternative paths remain unexplored. A multiverse analysis offers a solution to this issue by exploring the various choices pertaining to data-processing and/or model building, and examining their impact on the conclusion of a study. However, even though multiverse analyses are arguably less susceptible to biases compared to the typical single-pathway approach, it is still possible to selectively add or omit pathways. To address this issue, we outline a novel, more principled approach to conducting multiverse analyses through crowdsourcing. The approach is detailed in a step-by-step tutorial to facilitate its implementation. We also provide a worked-out illustration featuring the Semantic Priming Across Many Languages project, thereby demonstrating its feasibility and its ability to increase objectivity and transparency. (PsycInfo Database Record (c) 2026 APA, all rights reserved).}, language = {en} }