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            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Nathalie",	"last" : "Peters"},
            	{"first" : "Christian",	"last" : "Praetorius"},
            	{"first" : "Meike",	"last" : "Hutt"},
            	{"first" : "Oliver",	"last" : "Seifert"},
            	{"first" : "Friedegund",	"last" : "Meier"},
            	{"first" : "Roland",	"last" : "Kontermann"},
            	{"first" : "Dagmar",	"last" : "Kulms"},
            	{"first" : "Markus",	"last" : "Rehm"}
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            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Arman",	"last" : "Rahman"},
            	{"first" : "Claudia",	"last" : "Aura"},
            	{"first" : "Peter",	"last" : "Dynoodt"},
            	{"first" : "Emilie M.",	"last" : "Charles"},
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            	{"first" : "Joost J.",	"last" : "van den Oord"},
            	{"first" : "William M.",	"last" : "Gallagher"},
            	{"first" : "Markus",	"last" : "Rehm"}
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         "volume": "11","number": "2","pages": "124","abstract": "Despite the introduction of novel targeted therapies, chemotherapy still remains the primary treatment for metastatic melanoma in poorly funded healthcare environments or in case of disease relapse, with no reliable molecular markers for progression-free survival (PFS) available. As chemotherapy primarily eliminates cancer cells by apoptosis, we here evaluated if the expression of key apoptosis regulators (Bax, Bak, Bcl-2, Bcl-xL, Smac, Procaspase-9, Apaf-1, Procaspase-3 and XIAP) allows prognosticating PFS in stage III/IV melanoma patients. Following antibody validation, marker expression was determined by automated and manual scoring of immunohistochemically stained tissue microarrays (TMAs) constructed from treatment-naive metastatic melanoma biopsies. Interestingly and counter-intuitively, low expression of the pro-apoptotic proteins Bax, Bak and Smac indicated better prognosis (log-rank p\u2009\\textless\u20090.0001, p\u2009=\u20090.0301 and p\u2009=\u20090.0227 for automated and p\u2009=\u20090.0422, p\u2009=\u20090.0410 and p\u2009=\u20090.0073 for manual scoring). These findings were independently validated in the cancer genome atlas (TCGA) metastatic melanoma cohort (TCGA-SKCM) at transcript level (log-rank p\u2009=\u20090.0004, p\u2009=\u20090.0104 and p\u2009=\u20090.0377). Taking expression heterogeneity between the markers in individual tumour samples into account allowed defining combinatorial Bax, Bak, Smac signatures that were associated with significantly increased PFS (p\u2009=\u20090.0002 and p\u2009=\u20090.0028 at protein and transcript level, respectively). Furthermore, combined low expression of Bax, Bak and Smac allowed predicting prolonged PFS (\\textgreater\u200912 months) on a case-by-case basis (area under the receiver operating characteristic curve (ROC AUC)\u2009=\u20090.79). Taken together, our results therefore suggest that Bax, Bak and Smac jointly define a signature with potential clinical utility in chemotherapy-treated metastatic melanoma.",
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         "doi" : "10.1038/s41419-020-2309-3",
         
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         "label" : "Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities",
         "user" : "pumaizi",
         "description" : "",
         "date" : "2025-10-17 10:53:57",
         "changeDate" : "2025-10-17 10:53:57",
         "count" : 10,
         "pub-type": "article",
         "journal": "Scientific Reports","publisher":"Nature Publishing Group",
         "year": "2020", 
         "url": "http://www.nature.com/articles/s41598-020-60400-z", 
         
         "author": [ 
            "Karsten Kuritz","Daniela Stöhr","Daniela Simone Maichl","Nadine Pollak","Markus Rehm","Frank Allgöwer"
         ],
         "authors": [
         	
            	{"first" : "Karsten",	"last" : "Kuritz"},
            	{"first" : "Daniela",	"last" : "Stöhr"},
            	{"first" : "Daniela Simone",	"last" : "Maichl"},
            	{"first" : "Nadine",	"last" : "Pollak"},
            	{"first" : "Markus",	"last" : "Rehm"},
            	{"first" : "Frank",	"last" : "Allgöwer"}
         ],
         "volume": "10","number": "1","pages": "3619","abstract": "Modern cytometry methods allow collecting complex, multi-dimensional data sets from heterogeneous cell populations at single-cell resolution. While methods exist to describe the progression and order of cellular processes from snapshots of such populations, these descriptions are limited to arbitrary pseudotime scales. Here we describe MAPiT, an universal transformation method that recovers real-time dynamics of cellular processes from pseudotime scales by utilising knowledge of the distributions on the real scales. As use cases, we applied MAPiT to two prominent problems in the flow-cytometric analysis of heterogeneous cell populations: (1) recovering the kinetics of cell cycle progression in unsynchronised and thus unperturbed cell populations, and (2) recovering the spatial arrangement of cells within multi-cellular spheroids prior to spheroid dissociation for cytometric analysis. Since MAPiT provides a theoretic basis for the relation of pseudotime values to real temporal and spatial scales, it can be used broadly in the analysis of cellular processes with snapshot data from heterogeneous cell populations.",
         "issn" : "2045-2322",
         
         "doi" : "10.1038/s41598-020-60400-z",
         
         "bibtexKey": "Kuritz2020"

      }
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      {
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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2844f126bc266106c3bb8f413f6f8d7cc/pumaizi",         
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         "label" : "T-GAN-D: a GAN-based classifier for breast cancer \n                   prognostication",
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         "description" : "T-GAN-D: a GAN-based classifier for breast cancer prognostication | Zenodo",
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         "publisher":"Zenodo",
         "year": "2022", 
         "url": "https://doi.org/10.5281/zenodo.7151831", 
         
         "author": [ 
            "Cristiano Guttà","Christoph Morhard","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Christoph",	"last" : "Morhard"},
            	{"first" : "Markus",	"last" : "Rehm"}
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         "version" : "1.0",
         
         "doi" : "10.5281/zenodo.7151831",
         
         "bibtexKey": "gutta_cristiano_2022_7151831"

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      {
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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2056a5dc5d9f8aea47d25238d442d91b0/pumaizi",         
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         "label" : "Glioblastoma, from disease understanding towards optimal cell-based in vitro models",
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         "date" : "2025-10-17 10:53:57",
         "changeDate" : "2025-10-17 10:53:57",
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         "pub-type": "article",
         "journal": "Cellular Oncology",
         "year": "2022", 
         "url": "https://doi.org/10.1007/s13402-022-00684-7", 
         
         "author": [ 
            "Chiara Boccellato","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Chiara",	"last" : "Boccellato"},
            	{"first" : "Markus",	"last" : "Rehm"}
         ],
         
         "issn" : "2211-3436",
         
         "doi" : "10.1007/s13402-022-00684-7",
         
         "bibtexKey": "Boccellato2022"

      }
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      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/234725a3174a0dfbf8f016e29d2592615/pumaizi",         
         "tags" : [
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         ],
         
         "intraHash" : "34725a3174a0dfbf8f016e29d2592615",
         "interHash" : "e533a8ac4a472754b5689e94dce84773",
         "label" : "The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer",
         "user" : "pumaizi",
         "description" : "The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer | Cell Death & Differentiation",
         "date" : "2025-10-17 10:53:57",
         "changeDate" : "2025-10-17 10:53:57",
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         "journal": "Cell Death & Differentiation",
         "year": "2020", 
         "url": "https://doi.org/10.1038/s41418-020-0545-9", 
         
         "author": [ 
            "Gavin Fullstone","Tabea L. Bauer","Cristiano Guttà","Manuela Salvucci","Jochen H. M. Prehn","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Gavin",	"last" : "Fullstone"},
            	{"first" : "Tabea L.",	"last" : "Bauer"},
            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Manuela",	"last" : "Salvucci"},
            	{"first" : "Jochen H. M.",	"last" : "Prehn"},
            	{"first" : "Markus",	"last" : "Rehm"}
         ],
         
         "issn" : "14765403",
         
         "refid" : "Fullstone2020",
         
         "doi" : "10.1038/s41418-020-0545-9",
         
         "bibtexKey": "fullstone2020apoptosome"

      }
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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/24386f56655faa9b7cc13322ef28d8a24/kpluhackova",         
         "tags" : [
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         "intraHash" : "4386f56655faa9b7cc13322ef28d8a24",
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         "label" : "BCL-2 and BOK regulate apoptosis by interaction of their C-terminal transmembrane domains",
         "user" : "kpluhackova",
         "description" : "",
         "date" : "2025-02-04 15:38:44",
         "changeDate" : "2025-02-21 09:12:25",
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         "pub-type": "article",
         "journal": "EMBO Reports","publisher":"Springer Science and Business Media LLC",
         "year": "2024", 
         "url": "http://dx.doi.org/10.1038/s44319-024-00206-6", 
         
         "author": [ 
            "Tobias B Beigl","Alexander Paul","Thomas P Fellmeth","Dang Nguyen","Lynn Barber","Sandra Weller","Benjamin Schäfer","Bernhard F Gillissen","Walter E Aulitzky","Hans-Georg Kopp","Markus Rehm","David W Andrews","Kristyna Pluhackova","Frank Essmann"
         ],
         "authors": [
         	
            	{"first" : "Tobias B",	"last" : "Beigl"},
            	{"first" : "Alexander",	"last" : "Paul"},
            	{"first" : "Thomas P",	"last" : "Fellmeth"},
            	{"first" : "Dang",	"last" : "Nguyen"},
            	{"first" : "Lynn",	"last" : "Barber"},
            	{"first" : "Sandra",	"last" : "Weller"},
            	{"first" : "Benjamin",	"last" : "Schäfer"},
            	{"first" : "Bernhard F",	"last" : "Gillissen"},
            	{"first" : "Walter E",	"last" : "Aulitzky"},
            	{"first" : "Hans-Georg",	"last" : "Kopp"},
            	{"first" : "Markus",	"last" : "Rehm"},
            	{"first" : "David W",	"last" : "Andrews"},
            	{"first" : "Kristyna",	"last" : "Pluhackova"},
            	{"first" : "Frank",	"last" : "Essmann"}
         ],
         "volume": "25","number": "9","pages": "3896\u20133924",
         "issn" : "1469-3178",
         
         "doi" : "10.1038/s44319-024-00206-6",
         
         "bibtexKey": "Beigl_2024"

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         "label" : "Applying a GAN-based classifier to improve transcriptome-based prognostication in breast cancer",
         "user" : "fabian",
         "description" : "",
         "date" : "2023-06-29 13:07:55",
         "changeDate" : "2023-11-22 09:44:38",
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         "pub-type": "article",
         "journal": "PLOS Computational Biology","publisher":"Public Library of Science",
         "year": "2023", 
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         "author": [ 
            "Cristiano Guttà","Christoph Morhard","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Christoph",	"last" : "Morhard"},
            	{"first" : "Markus",	"last" : "Rehm"}
         ],
         "volume": "19","number": "4","pages": "1-20",
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         "bibtexKey": "10.1371/journal.pcbi.1011035"

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         "year": "2020", 
         "url": "https://onlinelibrary.wiley.com/doi/abs/10.1111/febs.15520", 
         
         "author": [ 
            "Daniela Stöhr","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Daniela",	"last" : "Stöhr"},
            	{"first" : "Markus",	"last" : "Rehm"}
         ],
         "pages": "febs.15520",
         "issn" : "1742-464X",
         
         "doi" : "10.1111/febs.15520",
         
         "bibtexKey": "Stohr2020"

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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2844f126bc266106c3bb8f413f6f8d7cc/fabian",         
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         "label" : "T-GAN-D: a GAN-based classifier for breast cancer \r\n                   prognostication",
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         "description" : "T-GAN-D: a GAN-based classifier for breast cancer prognostication | Zenodo",
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         "author": [ 
            "Cristiano Guttà","Christoph Morhard","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Cristiano",	"last" : "Guttà"},
            	{"first" : "Christoph",	"last" : "Morhard"},
            	{"first" : "Markus",	"last" : "Rehm"}
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         "version" : "1.0",
         
         "doi" : "10.5281/zenodo.7151831",
         
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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/21566fb51bbb18bad6a24331247d00bca/fabian",         
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         "author": [ 
            "Christian T. Hellwig","M. Eugenia Delgado","Josip Skoko","Lydia Dyck","Carol Hanna","Alexa Wentges","Claudia Langlais","Cathrin Hagenlocher","Alexandra Mack","David Dinsdale","Kelvin Cain","Marion MacFarlane","Markus Rehm"
         ],
         "authors": [
         	
            	{"first" : "Christian T.",	"last" : "Hellwig"},
            	{"first" : "M. Eugenia",	"last" : "Delgado"},
            	{"first" : "Josip",	"last" : "Skoko"},
            	{"first" : "Lydia",	"last" : "Dyck"},
            	{"first" : "Carol",	"last" : "Hanna"},
            	{"first" : "Alexa",	"last" : "Wentges"},
            	{"first" : "Claudia",	"last" : "Langlais"},
            	{"first" : "Cathrin",	"last" : "Hagenlocher"},
            	{"first" : "Alexandra",	"last" : "Mack"},
            	{"first" : "David",	"last" : "Dinsdale"},
            	{"first" : "Kelvin",	"last" : "Cain"},
            	{"first" : "Marion",	"last" : "MacFarlane"},
            	{"first" : "Markus",	"last" : "Rehm"}
         ],
         "pages": "1--9",
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   ]
}
