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1,340 results on '"Goebeler, Matthias"'

1. Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study

Author

Chanda, Tirtha, Haggenmueller, Sarah, Bucher, Tabea-Clara, Holland-Letz, Tim, Kittler, Harald, Tschandl, Philipp, Heppt, Markus V., Berking, Carola, Utikal, Jochen S., Schilling, Bastian, Buerger, Claudia, Navarrete-Dechent, Cristian, Goebeler, Matthias, Kather, Jakob Nikolas, Schneider, Carolin V., Durani, Benjamin, Durani, Hendrike, Jansen, Martin, Wacker, Juliane, Wacker, Joerg, Consortium, Reader Study, and Brinker, Titus J.

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction
Abstract

Artificial intelligence (AI) systems have substantially improved dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing clinicians' confidence and trust in AI-driven decisions. Despite these advancements, there remains a critical need for objective evaluation of how dermatologists engage with both AI and XAI tools. In this study, 76 dermatologists participated in a reader study, diagnosing 16 dermoscopic images of melanomas and nevi using an XAI system that provides detailed, domain-specific explanations. Eye-tracking technology was employed to assess their interactions. Diagnostic performance was compared with that of a standard AI system lacking explanatory features. Our findings reveal that XAI systems improved balanced diagnostic accuracy by 2.8 percentage points relative to standard AI. Moreover, diagnostic disagreements with AI/XAI systems and complex lesions were associated with elevated cognitive load, as evidenced by increased ocular fixations. These insights have significant implications for clinical practice, the design of AI tools for visual tasks, and the broader development of XAI in medical diagnostics.

Published
2024

2. Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study

Author

Heinlein, Lukas, Maron, Roman C., Hekler, Achim, Haggenmüller, Sarah, Wies, Christoph, Utikal, Jochen S., Meier, Friedegund, Hobelsberger, Sarah, Gellrich, Frank F., Sergon, Mildred, Hauschild, Axel, French, Lars E., Heinzerling, Lucie, Schlager, Justin G., Ghoreschi, Kamran, Schlaak, Max, Hilke, Franz J., Poch, Gabriela, Korsing, Sören, Berking, Carola, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Schadendorf, Dirk, Sondermann, Wiebke, Goebeler, Matthias, Schilling, Bastian, Krieghoff-Henning, Eva, and Brinker, Titus J.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Statistics - Applications
Abstract

Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence (AI) has proven to be helpful for enhancing melanoma detection. However, there are few prospective studies confirming these promising results. Existing studies are limited by low sample sizes, too homogenous datasets, or lack of inclusion of rare melanoma subtypes, preventing a fair and thorough evaluation of AI and its generalizability, a crucial aspect for its application in the clinical setting. Therefore, we assessed 'All Data are Ext' (ADAE), an established open-source ensemble algorithm for detecting melanomas, by comparing its diagnostic accuracy to that of dermatologists on a prospectively collected, external, heterogeneous test set comprising eight distinct hospitals, four different camera setups, rare melanoma subtypes, and special anatomical sites. We advanced the algorithm with real test-time augmentation (R-TTA, i.e. providing real photographs of lesions taken from multiple angles and averaging the predictions), and evaluated its generalization capabilities. Overall, the AI showed higher balanced accuracy than dermatologists (0.798, 95% confidence interval (CI) 0.779-0.814 vs. 0.781, 95% CI 0.760-0.802; p<0.001), obtaining a higher sensitivity (0.921, 95% CI 0.900- 0.942 vs. 0.734, 95% CI 0.701-0.770; p<0.001) at the cost of a lower specificity (0.673, 95% CI 0.641-0.702 vs. 0.828, 95% CI 0.804-0.852; p<0.001). As the algorithm exhibited a significant performance advantage on our heterogeneous dataset exclusively comprising melanoma-suspicious lesions, AI may offer the potential to support dermatologists particularly in diagnosing challenging cases.

Published
2024

3. Prospective multicenter study using artificial intelligence to improve dermoscopic melanoma diagnosis in patient care

Author

Heinlein, Lukas, Maron, Roman C., Hekler, Achim, Haggenmüller, Sarah, Wies, Christoph, Utikal, Jochen S., Meier, Friedegund, Hobelsberger, Sarah, Gellrich, Frank F., Sergon, Mildred, Hauschild, Axel, French, Lars E., Heinzerling, Lucie, Schlager, Justin G., Ghoreschi, Kamran, Schlaak, Max, Hilke, Franz J., Poch, Gabriela, Korsing, Sören, Berking, Carola, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Schadendorf, Dirk, Sondermann, Wiebke, Goebeler, Matthias, Schilling, Bastian, Krieghoff-Henning, Eva, and Brinker, Titus J.

Published
2024
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4. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Author

Chanda, Tirtha, Hauser, Katja, Hobelsberger, Sarah, Bucher, Tabea-Clara, Garcia, Carina Nogueira, Wies, Christoph, Kittler, Harald, Tschandl, Philipp, Navarrete-Dechent, Cristian, Podlipnik, Sebastian, Chousakos, Emmanouil, Crnaric, Iva, Majstorovic, Jovana, Alhajwan, Linda, Foreman, Tanya, Peternel, Sandra, Sarap, Sergei, Özdemir, İrem, Barnhill, Raymond L., Llamas-Velasco, Mar, Poch, Gabriela, Korsing, Sören, Sondermann, Wiebke, Gellrich, Frank Friedrich, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Goebeler, Matthias, Schilling, Bastian, Utikal, Jochen S., Ghoreschi, Kamran, Fröhling, Stefan, Krieghoff-Henning, Eva, and Brinker, Titus J.

Published
2024
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5. Klinische Fälle

Author

Dege, Tassilo, Fleißner, Janik, Herz, Corinna, Ickrath, Franziska, Mohme, Sophia, Reichel, Alexandra, Riedmiller-Schraven, Anna-Liisa, Schulmeyer, Lena, Hamm, Henning, Goebeler, Matthias, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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8. Lösungen zu den Übungsfragen

Author

Dege, Tassilo, Fleißner, Janik, Herz, Corinna, Ickrath, Franziska, Mohme, Sophia, Reichel, Alexandra, Riedmiller-Schraven, Anna-Liisa, Schulmeyer, Lena, Hamm, Henning, Goebeler, Matthias, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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9. Psychodermatosen

Author

Mohme, Sophia, Herz, Corinna, Goebeler, Matthias, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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11. Konsultationsanlässe

Author

Dege, Tassilo, Fleißner, Janik, Mohme, Sophia, Schulmeyer, Lena, Goebeler, Matthias, Hamm, Henning, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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14. Angiopathien

Author

Schulmeyer, Lena, Reichel, Alexandra, Goebeler, Matthias, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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16. Maligne Hauttumoren

Author

Dege, Tassilo, Riedmiller-Schraven, Anna-Liisa, Hamm, Henning, Goebeler, Matthias, Goebeler, Matthias, editor, and Hamm, Henning, editor

Published
2024
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18. Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study

Author

Hekler, Achim, Maron, Roman C., Haggenmüller, Sarah, Schmitt, Max, Wies, Christoph, Utikal, Jochen S., Meier, Friedegund, Hobelsberger, Sarah, Gellrich, Frank F., Sergon, Mildred, Hauschild, Axel, French, Lars E., Heinzerling, Lucie, Schlager, Justin G., Ghoreschi, Kamran, Schlaak, Max, Hilke, Franz J., Poch, Gabriela, Korsing, Sören, Berking, Carola, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Schadendorf, Dirk, Sondermann, Wiebke, Goebeler, Matthias, Schilling, Bastian, Kather, Jakob N., Krieghoff-Henning, Eva, and Brinker, Titus J.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Background: Convolutional neural network (CNN)-based melanoma classifiers face several challenges that limit their usefulness in clinical practice. Objective: To investigate the impact of multiple real-world dermoscopic views of a single lesion of interest on a CNN-based melanoma classifier. Methods: This study evaluated 656 suspected melanoma lesions. Classifier performance was measured using area under the receiver operating characteristic curve (AUROC), expected calibration error (ECE) and maximum confidence change (MCC) for (I) a single-view scenario, (II) a multiview scenario using multiple artificially modified images per lesion and (III) a multiview scenario with multiple real-world images per lesion. Results: The multiview approach with real-world images significantly increased the AUROC from 0.905 (95% CI, 0.879-0.929) in the single-view approach to 0.930 (95% CI, 0.909-0.951). ECE and MCC also improved significantly from 0.131 (95% CI, 0.105-0.159) to 0.072 (95% CI: 0.052-0.093) and from 0.149 (95% CI, 0.125-0.171) to 0.115 (95% CI: 0.099-0.131), respectively. Comparing multiview real-world to artificially modified images showed comparable diagnostic accuracy and uncertainty estimation, but significantly worse robustness for the latter. Conclusion: Using multiple real-world images is an inexpensive method to positively impact the performance of a CNN-based melanoma classifier.

Published
2023
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19. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Author

Chanda, Tirtha, Hauser, Katja, Hobelsberger, Sarah, Bucher, Tabea-Clara, Garcia, Carina Nogueira, Wies, Christoph, Kittler, Harald, Tschandl, Philipp, Navarrete-Dechent, Cristian, Podlipnik, Sebastian, Chousakos, Emmanouil, Crnaric, Iva, Majstorovic, Jovana, Alhajwan, Linda, Foreman, Tanya, Peternel, Sandra, Sarap, Sergei, Özdemir, İrem, Barnhill, Raymond L., Velasco, Mar Llamas, Poch, Gabriela, Korsing, Sören, Sondermann, Wiebke, Gellrich, Frank Friedrich, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Goebeler, Matthias, Schilling, Bastian, Utikal, Jochen S., Ghoreschi, Kamran, Fröhling, Stefan, Krieghoff-Henning, Eva, and Brinker, Titus J.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma poses severe obstacles to user acceptance. Explainable artificial intelligence (XAI) methods can help to increase transparency, but most XAI methods are unable to produce precisely located domain-specific explanations, making the explanations difficult to interpret. Moreover, the impact of XAI methods on dermatologists has not yet been evaluated. Extending on two existing classifiers, we developed an XAI system that produces text and region based explanations that are easily interpretable by dermatologists alongside its differential diagnoses of melanomas and nevi. To evaluate this system, we conducted a three-part reader study to assess its impact on clinicians' diagnostic accuracy, confidence, and trust in the XAI-support. We showed that our XAI's explanations were highly aligned with clinicians' explanations and that both the clinicians' trust in the support system and their confidence in their diagnoses were significantly increased when using our XAI compared to using a conventional AI system. The clinicians' diagnostic accuracy was numerically, albeit not significantly, increased. This work demonstrates that clinicians are willing to adopt such an XAI system, motivating their future use in the clinic.

Published
2023
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20. S2k guidelines on the management of paraneoplastic pemphigus/paraneoplastic autoimmune multiorgan syndrome initiated by the European Academy of Dermatology and Venereology (EADV)

Author

Antiga, Emiliano, Bech, Rikke, Maglie, Roberto, Genovese, Giovanni, Borradori, Luca, Bockle, Barbara, Caproni, Marzia, Caux, Frédéric, Chandran, Nisha Suyien, Corrà, Alberto, D'Amore, Francesco, Daneshpazhooh, Maryam, De, Dipankar, Didona, Dario, Dmochowski, Marian, Drenovska, Kossara, Ehrchen, Jan, Feliciani, Claudio, Goebeler, Matthias, Groves, Richard, Günther, Claudia, Handa, Sanjeev, Hofmann, Silke C, Horvath, Barbara, Ioannidis, Dimitrios, Jedlickova, Hana, Kowalewski, Cezary, Kridin, Khalaf, Joly, Pascal, Lim, Yen Loo, Marinovic, Branka, Maverakis, Emanual, Meijer, Joost, Patsatsi, Aikaterini, Pincelli, Carlo, Prost, Catherine, Setterfield, Jane, Sprecher, Eli, Skiljevic, Dusan, Tasanen, Kaisa, Uzun, Soner, Van Beek, Nina, Vassileva, Snejina, Vorobyev, Artem, Vujic, Igor, Wang, Gang, Wang, Mingyue, Wozniak, Katarzyna, Yayli, Savas, Zambruno, Giovanna, Hashimoto, Takashi, Schmidt, Enno, Mascarò, José Manuel, and Marzano, Angelo Valerio

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Hematology, Autoimmune Disease, Animals, Rats, Autoimmune Diseases, Neoplasms, Paraneoplastic Syndromes, Paraneoplastic Syndromes, Nervous System, Societies, Medical, Dermatology & Venereal Diseases, Clinical sciences
Abstract

BackgroundParaneoplastic pemphigus (PNP), also called paraneoplastic autoimmune multiorgan syndrome (PAMS), is a rare autoimmune disease with mucocutaneous and multi-organ involvement. PNP/PAMS is typically associated with lymphoproliferative or haematological malignancies, and less frequently with solid malignancies. The mortality rate of PNP/PAMS is elevated owing to the increased risk of severe infections and disease-associated complications, such as bronchiolitis obliterans.ObjectivesThese guidelines summarize evidence-based and expert-based recommendations (S2k level) for the clinical characterization, diagnosis and management of PNP/PAMS. They have been initiated by the Task Force Autoimmune Blistering Diseases of the European Academy of Dermatology and Venereology with the contribution of physicians from all relevant disciplines. The degree of consent among all task force members was included.ResultsChronic severe mucositis and polymorphic skin lesions are clue clinical characteristics of PNP/PAMS. A complete assessment of the patient with suspected PNP/PAMS, requiring histopathological study and immunopathological investigations, including direct and indirect immunofluorescence, ELISA and, where available, immunoblotting/immunoprecipitation, is recommended to achieve a diagnosis of PNP/PAMS. Detection of anti-envoplakin antibodies and/or circulating antibodies binding to the rat bladder epithelium at indirect immunofluorescence is the most specific tool for the diagnosis of PNP/PAMS in a patient with compatible clinical and anamnestic features. Treatment of PNP/PAMS is highly challenging. Systemic steroids up to 1.5 mg/kg/day are recommended as first-line option. Rituximab is also recommended in patients with PNP/PAMS secondary to lymphoproliferative conditions but might also be considered in cases of PNP/PAMS associated with solid tumours. A multidisciplinary approach involving pneumologists, ophthalmologists and onco-haematologists is recommended for optimal management of the patients.ConclusionsThese are the first European guidelines for the diagnosis and management of PNP/PAMS. Diagnostic criteria and therapeutic recommendations will require further validation by prospective studies.

Published
2023

21. Approach to Mycosis Fungoides in children: Consensus-based recommendations

Author

Zvulunov, Alex, Neale, Holly, Stern, Jonah, Santaguida, Pasqualina, Stein, Amy Buros, Koh, Mark, Eichenfield, Lawrence F., Guitart, Joan, Goebeler, Matthias, Scarisbrick, Julia, Willemze, Rein, Coughlin, Carrie C., George, Renu, Brazzelli, Valeria, Marschalkó, Márta, Belousova, Irena, Querfeld, Christiane, Bagot, Martine, Szepietowski, Jacek C., Papadavid, Evangelina, Quaglino, Pietro, Hoeger, Peter, Ortiz-Romero, Pablo L., Nikolaou, Vasiliki, Dummer, Reinhard, Aung, Phyu P., Lawley, Leslie, Morel, Kimberly D., Ngan, Bo, Wain, Mary, Gameiro, Ana, Lacy-Niebla, Rosa María, and Pope, Elena

Published
2024
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24. Tumor-derived GDF-15 blocks LFA-1 dependent T cell recruitment and suppresses responses to anti-PD-1 treatment

Author

Haake, Markus, Haack, Beatrice, Schäfer, Tina, Harter, Patrick N., Mattavelli, Greta, Eiring, Patrick, Vashist, Neha, Wedekink, Florian, Genssler, Sabrina, Fischer, Birgitt, Dahlhoff, Julia, Mokhtari, Fatemeh, Kuzkina, Anastasia, Welters, Marij J. P., Benz, Tamara M., Sorger, Lena, Thiemann, Vincent, Almanzar, Giovanni, Selle, Martina, Thein, Klara, Späth, Jacob, Gonzalez, Maria Cecilia, Reitinger, Carmen, Ipsen-Escobedo, Andrea, Wistuba-Hamprecht, Kilian, Eichler, Kristin, Filipski, Katharina, Zeiner, Pia S., Beschorner, Rudi, Goedemans, Renske, Gogolla, Falk Hagen, Hackl, Hubert, Rooswinkel, Rogier W., Thiem, Alexander, Roche, Paula Romer, Joshi, Hemant, Pühringer, Dirk, Wöckel, Achim, Diessner, Joachim E., Rüdiger, Manfred, Leo, Eugen, Cheng, Phil F., Levesque, Mitchell P., Goebeler, Matthias, Sauer, Markus, Nimmerjahn, Falk, Schuberth-Wagner, Christine, von Felten, Stefanie, Mittelbronn, Michel, Mehling, Matthias, Beilhack, Andreas, van der Burg, Sjoerd H., Riedel, Angela, Weide, Benjamin, Dummer, Reinhard, and Wischhusen, Jörg

Published
2023
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27. Characterization of the skin microbiota in bullous pemphigoid patients and controls reveals novel microbial indicators of disease

Author

Belheouane, Meriem, Hermes, Britt M., Van Beek, Nina, Benoit, Sandrine, Bernard, Philippe, Drenovska, Kossara, Gerdes, Sascha, Gläser, Regine, Goebeler, Matthias, Günther, Claudia, von Georg, Anabelle, Hammers, Christoph M., Holtsche, Maike M., Homey, Bernhard, Horváth, Orsolya N., Hübner, Franziska, Linnemann, Beke, Joly, Pascal, Márton, Dalma, Patsatsi, Aikaterini, Pföhler, Claudia, Sárdy, Miklós, Huilaja, Laura, Vassileva, Snejina, Zillikens, Detlef, Ibrahim, Saleh, Sadik, Christian D., Schmidt, Enno, and Baines, John F.

Published
2023
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29. Model soups improve performance of dermoscopic skin cancer classifiers

Author

Maron, Roman C., Hekler, Achim, Haggenmüller, Sarah, von Kalle, Christof, Utikal, Jochen S., Müller, Verena, Gaiser, Maria, Meier, Friedegund, Hobelsberger, Sarah, Gellrich, Frank F., Sergon, Mildred, Hauschild, Axel, French, Lars E., Heinzerling, Lucie, Schlager, Justin G., Ghoreschi, Kamran, Schlaak, Max, Hilke, Franz J., Poch, Gabriela, Korsing, Sören, Berking, Carola, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Schadendorf, Dirk, Sondermann, Wiebke, Goebeler, Matthias, Schilling, Bastian, Kather, Jakob N., Fröhling, Stefan, Lipka, Daniel B., Krieghoff-Henning, Eva, and Brinker, Titus J.

Published
2022
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30. Oncogenic alterations in KIR3DL1 in cutaneous acral CD8+ lymphoproliferative disorder.

Author

Wobser, Marion, Appenzeller, Silke, Roth, Sabine, Siedel, Claudia, Goebeler, Matthias, Geissinger, Eva, Rosenwald, Andreas, and Maurus, Katja

Subjects
IMMUNOSTAINING, LYMPHOPROLIFERATIVE disorders, CD8 antigen, PROTEIN expression, DELETION mutation, CUTANEOUS T-cell lymphoma
Abstract

Background Primary cutaneous acral CD8+ T-cell lymphoproliferative disorder (TLPD) is a rare and indolent lymphoma entity. Although TLPD was first identified many years ago, the molecular pathogenesis is still not fully understood. Objectives In order to better understand the molecular pathogenesis of cutaneous acral CD8+ TLPD and to identify further discriminatory markers to differentiate this lymphoma subtype from other CD8+ cutaneous lymphomas, we analysed five cases of cutaneous acral CD8+ TLPD for putative molecular alterations. Methods Somatic alterations were assessed using whole-exome and targeted sequencing of paraffin-embedded tissue. Results were evaluated using immunohistochemical staining of respective relevant proteins. CD8+ cutaneous T-cell lymphomas (n = 12) served as control for KIR3DL1 staining. Results Copy number variation analysis revealed a homozygous deletion of the KIR3DL1 gene in two of the analysed cases. This resulted in loss of KIR3DL1 protein expression, which was observed in all cases of cutaneous acral CD8+ TLPD. In contrast, KIR3DL1 expression was more variable in other CD8+ cutaneous T-cell lymphomas with 50% of analysed cases (n = 12) found to be positive. In addition, one further case of acral CD8+ TLPD harboured a loss-of-function mutation in the PIK3R1 gene, presumably activating the phosphoinositide 3-kinase-AKT pathway. Conclusions Alterations of the KIR3DL1 gene may be of pathogenetic relevance for acral CD8+ TLPD. Loss of KIR3DL1 protein expression may support the diagnosis of this indolent lymphoma entity; however, this is not a subtype-specific discriminative feature. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Loss of p14 diminishes immunogenicity in melanoma via non‐canonical Wnt signaling by reducing the peptide surface density.

Author

Wohlfarth, Jonas, Kosnopfel, Corinna, Faber, Dominic, Berthold, Marion, Siedel, Claudia, Bernhardt, Melissa, Schlosser, Andreas, Aprati, Tyler, Liu, David, Schrama, David, Houben, Roland, Schadendorf, Dirk, Goebeler, Matthias, Meierjohann, Svenja, and Schilling, Bastian

Abstract

Immunotherapy has achieved tremendous success in melanoma. However, only around 50% of advanced melanoma patients benefit from immunotherapy. Cyclin‐dependent kinase inhibitor 2A (CDKN2A), encoding the two tumor‐suppressor proteins p14ARF and p16INK4a, belongs to the most frequently inactivated gene loci in melanoma and leads to decreased T cell infiltration. While the role of p16INK4a has been extensively investigated, knowledge about p14ARF in melanoma is scarce. In this study, we elucidate the impact of reduced p14ARF expression on melanoma immunogenicity. Knockdown of p14ARF in melanoma cell lines diminished their recognition and killing by melanoma differentiation antigen (MDA)‐specific T cells. Resistance was caused by a reduction of the peptide surface density of presented MDAs. Immunopeptidomic analyses revealed that antigen presentation via human leukocyte antigen class I (HLA‐I) molecules was enhanced upon p14ARF downregulation in general, but absolute and relative expression of cognate peptides was decreased. However, this phenotype is associated with a favorable outcome for melanoma patients. Limiting Wnt5a signaling reverted this phenotype, suggesting an involvement of non‐canonical Wnt signaling. Taken together, our data indicate a new mechanism limiting MDA‐specific T cell responses by decreasing both absolute and relative MDA‐peptide presentation in melanoma. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Allogeneic ABCB5+ Mesenchymal Stem Cells for Treatment-Refractory Chronic Venous Ulcers: A Phase I/IIa Clinical Trial

Author

Kerstan, Andreas, Dieter, Kathrin, Niebergall-Roth, Elke, Dachtler, Ann-Kathrin, Kraft, Korinna, Stücker, Markus, Daeschlein, Georg, Jünger, Michael, Görge, Tobias, Meyer-Pannwitt, Ulrich, Erfurt-Berge, Cornelia, von Engelhardt, Charlotte, Klare, Andreas, Pfeiffer, Christiane, Esterlechner, Jasmina, Schröder, Hannes M., Gasser, Martin, Waaga-Gasser, Ana M., Goebeler, Matthias, Ballikaya, Seda, Sadeghi, Samar, Murphy, George F., Orgill, Dennis P., Frank, Natasha Y., Ganss, Christoph, Scharffetter-Kochanek, Karin, Frank, Markus H., and Kluth, Mark A.

Published
2022
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34. Translational development of ABCB5+ dermal mesenchymal stem cells for therapeutic induction of angiogenesis in non-healing diabetic foot ulcers

Author

Kerstan, Andreas, Dieter, Kathrin, Niebergall-Roth, Elke, Klingele, Sabrina, Jünger, Michael, Hasslacher, Christoph, Daeschlein, Georg, Stemler, Lutz, Meyer-Pannwitt, Ulrich, Schubert, Kristin, Klausmann, Gerhard, Raab, Titus, Goebeler, Matthias, Kraft, Korinna, Esterlechner, Jasmina, Schröder, Hannes M., Sadeghi, Samar, Ballikaya, Seda, Gasser, Martin, Waaga-Gasser, Ana M., Murphy, George F., Orgill, Dennis P., Frank, Natasha Y., Ganss, Christoph, Scharffetter-Kochanek, Karin, Frank, Markus H., and Kluth, Mark A.

Published
2022
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37. S2k guideline for the treatment of hidradenitis suppurativa / acne inversa – Short version

Author

Zouboulis, Christos C., primary, Bechara, Falk G., additional, Fritz, Klaus, additional, Goebeler, Matthias, additional, Hetzer, Frank H., additional, Just, Elke, additional, Kirsten, Natalia, additional, Kokolakis, Georgios, additional, Kurzen, Hjalmar, additional, Nikolakis, Georgios, additional, Pinter, Andreas, additional, Podda, Maurizio, additional, Rosinski, Kerstin, additional, Schneider‐Burrus, Sylke, additional, Taube, Klaus‐M., additional, Volz, Thomas, additional, Winkler, Thomas, additional, Kristandt, Anna, additional, Presser, Dagmar, additional, and Zouboulis, Viktor A., additional

Published
2024
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40. Overview of the Safety Profile from Efgartigimod Clinical Trials in Participants with Diverse IgG-mediated Autoimmune Diseases (P4-14.016)

Author

Vu, Tuan, primary, Gwathmey, Kelly, additional, Broome, Catherine, additional, Goebeler, Matthias, additional, Murai, Hiroyuki, additional, Bata-Csörgo, Zsuzsanna, additional, Newland, Adrian, additional, Ulrichts, Peter, additional, Kerstens, Rene, additional, Guptill, Jeffrey T., additional, Agha, Sofiane, additional, Jiang, Ming, additional, and Howard, James, additional

Published
2024
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44. Genetic association and differential expression of HLAComplexGroup lncRNAs in pemphigus

Author

Salviano-Silva, Amanda, Becker, Mareike, Augusto, Danillo G., Busch, Hauke, Adelman Cipolla, Gabriel, Farias, Ticiana D.-J., Bumiller-Bini, Valéria, Calonga-Solís, Verónica, Munz, Matthias, Franke, Andre, Wittig, Michael, Camargo, Carolina M., Goebeler, Matthias, Hundt, Jennifer Elisabeth, Günther, Claudia, Gläser, Regine, Hadaschik, Eva, Pföhler, Claudia, Sárdy, Miklós, Van Beek, Nina, Worm, Margitta, Zillikens, Detlef, Boldt, Angelica B.W., Schmidt, Enno, Petzl-Erler, Maria Luiza, Ibrahim, Saleh, and Malheiros, Danielle

Published
2021
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50. Abbildungen

Author

Goebeler, Matthias, Walter, Peter, Westhofen, Martin, Goebeler, Matthias, editor, Walter, Peter, editor, and Westhofen, Martin, editor

Published
2018
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