Founded in 2019, the DQBM's mission is to foster research and education at the interface of biomedical research, bio-technology, and computational biomedicine, to develop the foundations of next-generation precision medicine. Ultimately, our goal is to advance precision medicine for the benefit of patients.

To fulfil our mission, we rely on excellent science done by outstanding scientists. Below, we highlight the DQBM events and academic achievements in 2021.

In Autumn 2021, the DQBM's wet labs moved into UZI5, the brand new research building on Campus Irchel. On this occasion, the DQBM wet labs were invited to introduce themselves via this video.

The DQBM's computational research groups also moved in 2021: The  Krauthammer group moved to Schmelzbergstrasse 26, floor C and the  Menze group moved to Schmelzbergstrasse 26, floor D.

(Photo: Philippe Wiget)

 

Thanks to our Invited Speakers, the UZH guests, all participants and our generous sponsors, the 2021 DQBM Founding Symposium: Frontiers in Biomedical Research on 29 November 2021 was a great success.

This synopsis video offers a summary of the Welcome Addresses by our UZH Guests: President Prof. Dr. Michael Schaepman, VP Medicine Prof. Dr. med. Beatrice Beck Schimmer, MNF Dean Prof. Dr. Roland Sigel and MeF Dean Prof. Dr. Dr. med. Frank Rühli.

Furthermore, on the occasion of our Symposium, UZH News interviewed DQBM Founding Director Bernd Bodenmiller, please find the article here.

In 2021, we had the pleasure of welcoming the following scientific speakers to the DQBM Special Seminar Series:

• Dr. Rafael Sanjuán, Principal investigator at the Institute for Integrative Systems Biology (I2SysBio), University of Valencia (Spain)
• Dr. Ali Ertürk, Director of the Institute of Tissue Engineering and Regenerative Medicine (iTERM) at the Helmholtz Zentrum München (Germany)
• Prof. Dr. Sandra Breum Andersen, Associate Professor at the Globe Institute, University of Copenhagen (Denmark)
• Prof. Clotilde Lagier-Tourenne M.D., Ph.D, Associate Professor of Neurology, Araminta Broch-Healey Endowed Chair in ALS at Massachusetts General Hospital and Harvard Medical School and Associate Member at the Broad Institute (USA)
• Prof. Dr. Dr. Verena Schünemann, Assistant Professor for Paleogenetics at the Institute of Evolutionary Medicine, University of Zurich (Switzerland).

Also in 2021, the DQBM organised its first joint Block Course BME330 - Quantitative Biomedicine, for BSc/MSc students as part of UZH's Biomedicine curriculum. Thanks to the dedicated supervision by DQBM's Faculty and (junior) scientists, we could offer research projects on the following topics:

• Single Cell Breast Cancer Pathology and Cellular Phenotypes
• Big Data in Healthcare
• Somatic Variant Detection
• Understanding Polymicrobial Infections
• CircRNAs in Neurodegenerative Diseases
• Deep-Learning Enabled Multi-Organ Segmentation
• Single Cell Pathology and Machine Learning
• Biological Imaging and Deep Learning Analysis

2021 was a successful fundraising year for DQBM's scientists. Notably:

• Bernd Bodenmiller received an SNSFproject grant in collaboration with Dr. María Rodríguez Martínez (IBM Research).
• Bernd Bodenmiller received renewed support for the Tumor Profiler Center, a collaboration between UZH, ETHZ and the University Hospital Basel.
• Michael Krauthammer received an SNSF project grant for the project "Patient Journey Analysis for Medical Knowledge Discovery and Clinical Decision Making".
• Michael Krauthammer and collaborators were granted funding for the new  Innosuisse Flagship Project 'Smart Hospital'.
• Magdalini Polymenidou received an SNSF Sinergia grant together with the labs of Ben Schuler, Fred Allain and Gunnar Jenschke for the project "Protein disorder in RNA-protein interactions: from dynamic structures to pathology".

DQBM's junior scientists also did a fantastic job in securing research funds:

• Pierre Bost (Bodenmiller lab) was awarded an EMBO Postdoctoral Fellowship.
• Haithem Dakhli (Bodenmiller lab) was awarded a Marie Skłodowska-Curie Actions Postdoctoral Fellowship for the mapping of cancer responses using breast cancer patient-derived organoids and mass cytometry.
• Nicolas Damond (Bodenmiller lab) was awarded a EFSD Research Grant.
• Alex Figueiredo (Kümmerli lab) was awarded an SNSF Postdoctoral Fellowship to go to Oxford University.
• Aron Horvath (Krauthammer group) was awarded an UZH Digital Entrepreneur Fellowship.
• Hongwei Bran Li (Menze group) was awarded an UZH Forschungskredit for the project ‘Robust Self-supervised Deep Learning in Quantitative Medical Imaging’.
• Ruchi Manglunia (Polymenidou lab) was awarded an IndiaBioscience Outreach Grant for her podcast named "IndiaAsksWhy".
• Subham Mridha (Kümmerli lab) received an UZH-FAN grant together with Dr. Simona Huwiler.
• Vera Vollenweider (Kümmerli lab) was awarded a pilot grant from the URPP: Evolution in Action.
  Jonas Windhager (Bodenmiller lab) was awarded two napari Plugin Accelerator Grants from the Chan Zuckerberg Initiative.
• Vera Wiersma (Polymenidou lab) received an NWO Rubicon Fellowship.

The Following DQBM members were honored for their scientific excellence:

• Pierre Bost (Bodenmiller lab) won the Young Researchers Bettencourt Prize.
• Alex Figueiredo (Kümmerli lab) was awarded a poster prize at the ASM Young Researcher's Symposium Switzerland.
• Jana Fischer (Bodenmiller lab) won the MNF PhD Award. 
• Johanna Furrer (Polymenidou lab) won the MNF Semester Prize for her MSc thesis.
  Ivna Ivanković (Krauthammer group) won the 2nd place at the BioMed (MTB) retreat poster competition.
• Pierre de Rossi (Polymenidou lab) won the Synapsis Foundation Career Development Award.
• Désirée Schmitz (Kümmerli lab) was awarded the Best Poster Prize (Audience Choice)” at the ASM Young Researcher’s Symposium Switzerland.
• Vera Vollenweider (Kümmerli lab) was awarded the First Prize for the best poster at the Swiss Society for Microbiology annual congress.

• Bernd Bodenmiller was appointed to the Tumor Profiler Center Leadership. 
• Rolf Kümmerli was appointed to the editorial board of ISME Journal.
• Magdalini Polymenidou gave the annual honorary Krivickas Memorial Lecture at MGH Neurology Grand Round.

The following bright minds completed their PhD thesis in 2021: 

• Alexandre Figueiredo (Kümmerli lab): "The Ecology and Evolution of Bacterial Social Interactions and How They Shape Microbial Communities and Interactions with Hosts". 
• Jana Fischer (Bodenmiller lab, with Distinction): 'High-Dimensional Profiling of the Breast Cancer Microarchitecture'.
• Subham Mridha (Kümmerli lab): "Ecology and Evolution of Bacterial Social Behaviours in Phenotypically Heterogenous Populations".
• Selina Niggli (Kümmerli lab): "Ecology and Evolution of Interspecies Interactions between Pseudomonas aeruginosa and Staphylococcus aureus".
• Sandra Tietscher (Bodenmiller lab): "Single-cell Profiling of the Tumor Immune Microenvironment of Primary and Metastatic Human Breast Cancer".

Furthermore, the following MSc students graduated in 2021 with a DQBM MSc thesis: 

• Luca Räss (Bodenmiller lab): "Multiplexed Spatial Analysis of Breast Cancer Patient-Derived Organoids".
• Hangjia Zhao (Bodenmiller lab): "Benchmark of IMC Data Batch-effect Correction and Cell Type Identification Methods for Data Integration".
• Johanna Giger (Kümmerli lab): "Testing the Evolutionary Robustness of Pyoverdine as a Novel Treatment Against Human Opportunistic Pathogens".

Bodenmiller lab:

Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment.

Kuett, L., Catena, R., Özcan, A. Plüss, A., Cancer Grand Challenges IMAXT Consortium, Schraml, P., Moch, H., de Souza, N & Bodenmiller B.
Nat Cancer 2021.
https://doi.org/10.1038/s43018-021-00301-w

Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd.
Gabor A, Tognetti M, Driessen A, Tanevski J, Guo B, Cao W, Shen H, Yu T, Chung V; Single Cell Signaling in Breast Cancer DREAM Consortium members, Bodenmiller B, Saez-Rodriguez J. 
Mol Syst Biol. 2021 Oct;17(10):e10402. 
doi: 10.15252/msb.202110402.

Establishing standardized immune phenotyping of metastatic melanoma by digital pathology.
Sobottka B, Nowak M, Frei AL, Haberecker M, Merki S; Tumor Profiler consortium, Levesque MP, Dummer R, Moch H, Koelzer VH.
Lab Invest. 2021 Dec;101(12):1561-1570. 
doi: 10.1038/s41374-021-00653-y. 

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia.
Lu J, Cannizzaro E, Meier-Abt F, Scheinost S, Bruch PM, Giles HA, Lütge A, Hüllein J, Wagner L, Giacopelli B, Nadeu F, Delgado J, Campo E, Mangolini M, Ringshausen I, Böttcher M, Mougiakakos D, Jacobs A, Bodenmiller B, Dietrich S, Oakes CC, Zenz T, Huber W. 
Nat Cancer. 2021 Aug;2(8):853-864. 
doi: 10.1038/s43018-021-00216-6. 

Clonal fitness inferred from time-series modelling of single-cell cancer genomes.
Salehi S, Kabeer F, Ceglia N, Andronescu M, Williams MJ, Campbell KR, Masud T, Wang B, Biele J, Brimhall J, Gee D, Lee H, Ting J, Zhang AW, Tran H, O'Flanagan C, Dorri F, Rusk N, de Algara TR, Lee SR, Cheng BYC, Eirew P, Kono T, Pham J, Grewal D, Lai D, Moore R, Mungall AJ, Marra MA; IMAXT Consortium, McPherson A, Bouchard-Côté A, Aparicio S, Shah SP.
Nature. 2021 Jul;595(7868):585-590.
doi: 10.1038/s41586-021-03648-3. 

Cutaneous and systemic hyperinflammation drives maculopapular drug exanthema in severely ill COVID-19 patients.
Mitamura Y, Schulz D, Oro S, Li N, Kolm I, Lang C, Ziadlou R, Tan G, Bodenmiller B, Steiger P, Marzano A, de Prost N, Caudin O, Levesque M, Stoffel C, Schmid-Grendelmeier P, Maverakis E, Akdis CA, Brüggen MC. Allergy. 2021 Jun 22:10.1111/all.14983.
doi: 10.1111/all.14983. 

Monogenic Diabetes and Integrated Stress Response Genes Display Altered Gene Expression in Type 1 Diabetes.
Hiller H, Beachy DE, Lebowitz JJ, Engler S, Mason JR, Miller DR, Kusmarteva I, Jacobsen LM, Posgai AL, Khoshbouei H, Oram RA, Schatz DA, Hattersley AT, Bodenmiller B, Atkinson MA, Nick HS, Wasserfall CH.
Diabetes. 2021 Aug;70(8):1885-1897.
doi: 10.2337/db21-0070. 

Deciphering the signaling network of breast cancer improves drug sensitivity prediction.
Tognetti M, Gabor A, Yang M, Cappelletti V, Windhager J, Rueda OM, Charmpi K, Esmaeilishirazifard E, Bruna A, de Souza N, Caldas C, Beyer A, Picotti P, Saez-Rodriguez J, Bodenmiller B. Cell Syst. 2021 May 19;12(5):401-418.e12.
doi: 10.1016/j.cels.2021.04.002. 

Profound dysregulation of T cell homeostasis and function in patients with severe COVID-19.
Adamo S, Chevrier S, Cervia C, Zurbuchen Y, Raeber ME, Yang L, Sivapatham S, Jacobs A, Baechli E, Rudiger A, Stüssi-Helbling M, Huber LC, Schaer DJ, Bodenmiller B, Boyman O, Nilsson J. Allergy. 2021 Sep;76(9):2866-2881.
doi: 10.1111/all.14866. 

Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine.
Rajewsky N, Almouzni G, Gorski SA, Aerts S, Amit I, Bertero MG, Bock C, Bredenoord AL, Cavalli G, Chiocca S, Clevers H, De Strooper B, Eggert A, Ellenberg J, Fernández XM, Figlerowicz M, Gasser SM, Hubner N, Kjems J, Knoblich JA, Krabbe G, Lichter P, Linnarsson S, Marine JC, Marioni JC, Marti-Renom MA, Netea MG, Nickel D, Nollmann M, Novak HR, Parkinson H, Piccolo S, Pinheiro I, Pombo A, Popp C, Reik W, Roman-Roman S, Rosenstiel P, Schultze JL, Stegle O, Tanay A, Testa G, Thanos D, Theis FJ, Torres-Padilla ME, Valencia A, Vallot C, van Oudenaarden A, Vidal M, Voet T; LifeTime Community Working Groups. Nature. 2021 Apr;592(7852):E8.
doi: 10.1038/s41586-021-03287-8.

 

Krauthammer lab:

Analyzing Patient Trajectories With Artificial Intelligence.
Allam A, Feuerriegel S, Rebhan M, Krauthammer M. J Med Internet Res. 2021 Dec 3;23(12):e29812.
doi: 10.2196/29812.

Commensal Clostridiales strains mediate effective anti-cancer immune response against solid tumors.
Montalban-Arques A, Katkeviciute E, Busenhart P, Bircher A, Wirbel J, Zeller G, Morsy Y, Borsig L, Glaus Garzon JF, Müller A, Arnold IC, Artola-Boran M, Krauthammer M, Sintsova A, Zamboni N, Leventhal GE, Berchtold L, de Wouters T, Rogler G, Baebler K, Schwarzfischer M, Hering L, Olivares-Rivas I, Atrott K, Gottier C, Lang S, Boyman O, Fritsch R, Manz MG, Spalinger MR, Scharl M.
Cell Host Microbe. 2021 Oct 13;29(10):1573-1588.e7.
doi: 10.1016/j.chom.2021.08.001. 

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.
Marquart KF, Allam A, Janjuha S, Sintsova A, Villiger L, Frey N, Krauthammer M, Schwank G. Nat Commun. 2021 Aug 25;12(1):5114.
doi: 10.1038/s41467-021-25375-z.

AttentionDDI: Siamese attention-based deep learning method for drug-drug interaction predictions.
Schwarz K, Allam A, Perez Gonzalez NA, Krauthammer M.
BMC Bioinformatics. 2021 Aug 21;22(1):412.
doi: 10.1186/s12859-021-04325-y.

How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19.
Maibach MA, Allam A, Hilty MP, Perez Gonzalez NA, Buehler PK, Wendel Garcia PD, Brugger SD, Ganter CC; CoViD-19 ICU-Research Group Zurich; RISC-19-ICU Investigators, Krauthammer M, Schuepbach RA, Bartussek J.
Front Med (Lausanne). 2021 Jul 8;8:607594.
doi: 10.3389/fmed.2021.607594. 

Collection and preprocessing of fine needle aspirate patient samples for single cell profiling and data analysis.
Tastanova A, Ramelyte E, Balázs Z, Menzel U, Beisel C, Krauthammer M, Dummer R, Levesque MP. STAR Protoc. 2021 Jun 5;2(2):100581.
doi: 10.1016/j.xpro.2021.100581. 

AI support for ethical decision-making around resuscitation: proceed with care.
Biller-Andorno N, Ferrario A, Joebges S, Krones T, Massini F, Barth P, Arampatzis G, Krauthammer M.
J Med Ethics. 2021 Mar 9:medethics-2020-106786.
doi: 10.1136/medethics-2020-106786. 
PMID: 33687916

Oncolytic virotherapy-mediated anti-tumor response: a single-cell perspective.
Ramelyte E, Tastanova A, Balázs Z, Ignatova D, Turko P, Menzel U, Guenova E, Beisel C, Krauthammer M, Levesque MP, Dummer R.
Cancer Cell. 2021 Mar 8;39(3):394-406.e4.
doi: 10.1016/j.ccell.2020.12.022. 
 

 

Kümmerli lab:

Losing out to improve group fitness.
Kramer J, Kümmerli R.
Elife. 2021 Dec 17;10:e75243.
doi: 10.7554/eLife.75243.

Model Systems to Study the Chronic, Polymicrobial Infections in Cystic Fibrosis: Current Approaches and Exploring Future Directions.
O'Toole GA, Crabbé A, Kümmerli R, LiPuma JJ, Bomberger JM, Davies JC, Limoli D, Phelan VV, Bliska JB, DePas WH, Dietrich LE, Hampton TH, Hunter R, Khursigara CM, Price-Whelan A, Ashare A, Cramer RA, Goldberg JB, Harrison F, Hogan DA, Henson MA, Madden DR, Mayers JR, Nadell C, Newman D, Prince A, Rivett DW, Schwartzman JD, Schultz D, Sheppard DC, Smyth AR, Spero MA, Stanton BA, Turner PE, van der Gast C, Whelan FJ, Whitaker R, Whiteson K.
mBio. 2021 Oct 26;12(5):e0176321.
doi: 10.1128/mBio.01763-21. 

Single-Cell Imaging Reveals That Staphylococcus aureus Is Highly Competitive Against Pseudomonas aeruginosa on Surfaces.
Niggli S, Wechsler T, Kümmerli R.
Front Cell Infect Microbiol. 2021 Aug 26;11:733991.
doi: 10.3389/fcimb.2021.733991.

Ecology drives the evolution of diverse social strategies in Pseudomonas aeruginosa.
Figueiredo ART, Wagner A, Kümmerli R.
Mol Ecol. 2021 Oct;30(20):5214-5228.
doi: 10.1111/mec.16119. 

Local adaptation, geographical distance and phylogenetic relatedness: Assessing the drivers of siderophore-mediated social interactions in natural bacterial communities.
Butaitė E, Kramer J, Kümmerli R.
J Evol Biol. 2021 Aug;34(8):1266-1278.
doi: 10.1111/jeb.13883. 

Erratum to "Positive linkage between bacterial social traits reveals that homogeneous rather than specialized behavioral repertoires prevail in natural Pseudomonas communities".
Kramer J, Carrasco MÁL, Kümmerli R.
FEMS Microbiol Ecol. 2021 Apr 13;97(5):fiaa250.
doi: 10.1093/femsec/fiaa250.

Loss of a pyoverdine secondary receptor in Pseudomonas aeruginosa results in a fitter strain suitable for population invasion.
González J, Salvador M, Özkaya Ö, Spick M, Reid K, Costa C, Bailey MJ, Avignone Rossa C, Kümmerli R, Jiménez JI.
ISME J. 2021 May;15(5):1330-1343.
doi: 10.1038/s41396-020-00853-2. 

 

Menze lab:

Robust, Primitive, and Unsupervised Quality Estimation for Segmentation Ensembles.
Kofler F, Ezhov I, Fidon L, Pirkl CM, Paetzold JC, Burian E, Pati S, El Husseini M, Navarro F, Shit S, Kirschke J, Bakas S, Zimmer C, Wiestler B, Menze BH.
Front Neurosci. 2021 Dec 30;15:752780.
doi: 10.3389/fnins.2021.752780. 
 

Geometry-aware neural solver for fast Bayesian calibration of brain tumor models.
Ezhov I, Mot T, Shit S, Lipkova J, Paetzold JC, Kofler F, Pellegrini C, Kollovieh M, Navarro F, Li H, Metz M, Wiestler B, Menze B.
IEEE Trans Med Imaging. 2021 Dec 20;PP.
doi: 10.1109/TMI.2021.3136582 
 

A computed tomography vertebral segmentation dataset with anatomical variations and multi-vendor scanner data.
Liebl H, Schinz D, Sekuboyina A, Malagutti L, Löffler MT, Bayat A, El Husseini M, Tetteh G, Grau K, Niederreiter E, Baum T, Wiestler B, Menze B, Braren R, Zimmer C, Kirschke JS. Sci Data. 2021 Oct 28;8(1):284.
doi: 10.1038/s41597-021-01060-0.

Face Restoration via Plug-and-Play 3D Facial Priors.
Hu X, Ren W, Yang J, Cao X, Wipf DP, Menze B, Tong X, Zha H.
IEEE Trans Pattern Anal Mach Intell. 2021 Oct 27;PP.
doi: 10.1109/TPAMI.2021.3123085.

Automated detection of the contrast phase in MDCT by an artificial neural network improves the accuracy of opportunistic bone mineral density measurements.
Rühling S, Navarro F, Sekuboyina A, El Husseini M, Baum T, Menze B, Braren R, Zimmer C, Kirschke JS.
Eur Radiol. 2021 Oct 23.
doi: 10.1007/s00330-021-08284-z. 

Imbalance-aware self-supervised learning for 3D radiomic representations.
Li H, Xue F, Chaitanya K, Luo S, Ezhov I, Wiestler B, Zhang J, Menze B. 
In Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
doi:10.1007/978-3-030-87196-3_4.

clDice-a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation.
Shit S*, Paetzold J *, Sekuboyina A, Ezhov I, Unger A, Zhylka A, Pluim J, Bauer U, Menze B. 
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 16560-16569. 2021
arXiv:2003.07311 

Automated claustrum segmentation in human brain MRI using deep learning.
Li H, Menegaux A, Schmitz-Koep B, Neubauer A, Bäuerlein FJB, Shit S, Sorg C, Menze B, Hedderich D.
Hum Brain Mapp. 2021 Dec 15;42(18):5862-5872.
doi: 10.1002/hbm.25655. 
 
AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning.
de la Rosa E, Sima DM, Menze B, Kirschke JS, Robben D.
Med Image Anal. 2021 Dec;74:102211.
doi: 10.1016/j.media.2021.102211. 
 
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset.
Payette K, de Dumast P, Kebiri H, Ezhov I, Paetzold JC, Shit S, Iqbal A, Khan R, Kottke R, Grehten P, Ji H, Lanczi L, Nagy M, Beresova M, Nguyen TD, Natalucci G, Karayannis T, Menze B, Bach Cuadra M, Jakab A.
Sci Data. 2021 Jul 6;8(1):167.
doi: 10.1038/s41597-021-00946-3.
 
Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging.
Navarro F, Dapper H, Asadpour R, Knebel C, Spraker MB, Schwarze V, Schaub SK, Mayr NA, Specht K, Woodruff HC, Lambin P, Gersing AS, Nyflot MJ, Menze BH, Combs SE, Peeken JC.
Cancers (Basel). 2021 Jun 8;13(12):2866.
doi: 10.3390/cancers13122866.

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.
Campello VM, Gkontra P, Izquierdo C, Martin-Isla C, Sojoudi A, Full PM, Maier-Hein K, Zhang Y, He Z, Ma J, Parreno M, Albiol A, Kong F, Shadden SC, Acero JC, Sundaresan V, Saber M, Elattar M, Li H, Menze B, Khader F, Haarburger C, Scannell CM, Veta M, Carscadden A, Punithakumar K, Liu X, Tsaftaris SA, Huang X, Yang X, Li L, Zhuang X, Vilades D, Descalzo ML, Guala A, Mura L, Friedrich MG, Garg R, Lebel J, Henriques F, Karakas M, Cavus E, Petersen SE, Escalera S, Segui S, Rodriguez-Palomares JF, Lekadir K.
IEEE Trans Med Imaging. 2021 Dec;40(12):3543-3554.
doi: 10.1109/TMI.2021.3090082. 
 
Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge.
Timmins KM, van der Schaaf IC, Bennink E, Ruigrok YM, An X, Baumgartner M, Bourdon P, De Feo R, Noto TD, Dubost F, Fava-Sanches A, Feng X, Giroud C, Group I, Hu M, Jaeger PF, Kaiponen J, Klimont M, Li Y, Li H, Lin Y, Loehr T, Ma J, Maier-Hein KH, Marie G, Menze B, Richiardi J, Rjiba S, Shah D, Shit S, Tohka J, Urruty T, Walińska U, Yang X, Yang Y, Yin Y, Velthuis BK, Kuijf HJ.
Neuroimage. 2021 Sep;238:118216.
doi: 10.1016/j.neuroimage.2021.118216. 
 
Tumor sink effect in 68Ga-PSMA-11 PET: Myth or Reality?
Gafita A, Wang H, Robertson A, Armstrong WR, Zaum R, Weber M, Yagubbayli F, Kratochwil C, Grogan TR, Nguyen K, Navarro F, Esfandiari R, Rauscher I, Menze B, Elashoff D, Delpassand ES, Herrmann K, Czernin J, Hofman MS, Calais J, Fendler WP, Eiber M. J Nucl Med. 2021 May 28:jnumed.121.261906.
doi: 10.2967/jnumed.121.261906. 

AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design.
Li J, Pimentel P, Szengel A, Ehlke M, Lamecker H, Zachow S, Estacio L, Doenitz C, Ramm H, Shi H, Chen X, Matzkin F, Newcombe V, Ferrante E, Jin Y, Ellis DG, Aizenberg MR, Kodym O, Spanel M, Herout A, Mainprize JG, Fishman Z, Hardisty MR, Bayat A, Shit S, Wang B, Liu Z, Eder M, Pepe A, Gsaxner C, Alves V, Zefferer U, von Campe G, Pistracher K, Schafer U, Schmalstieg D, Menze BH, Glocker B, Egger J. IEEE Trans Med Imaging. 2021 Sep;40(9):2329-2342.
doi: 10.1109/TMI.2021.3077047. 

Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging.
Pirkl CM, Nunez-Gonzalez L, Kofler F, Endt S, Grundl L, Golbabaee M, Gómez PA, Cencini M, Buonincontri G, Schulte RF, Smits M, Wiestler B, Menze BH, Menzel MI, Hernandez-Tamames JA. Neuroradiology. 2021 Nov;63(11):1831-1851.
doi: 10.1007/s00234-021-02703-0. 
 
Analyzing Longitudinal wb-MRI Data and Clinical Course in a Cohort of Former Smoldering Multiple Myeloma Patients: Connections between MRI Findings and Clinical Progression Patterns.
Wennmann M, Hielscher T, Kintzelé L, Menze BH, Langs G, Merz M, Sauer S, Kauczor HU, Schlemmer HP, Delorme S, Goldschmidt H, Weinhold N, Hillengass J, Weber MA. Cancers (Basel). 2021 Feb 25;13(5):961.
doi: 10.3390/cancers13050961.

Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type.
Guo R, Hu X, Song H, Xu P, Xu H, Rominger A, Lin X, Menze B, Li B, Shi K.
Eur J Nucl Med Mol Imaging. 2021 Sep;48(10):3151-3161.
doi: 10.1007/s00259-021-05232-3. 
 
Analyzing magnetic resonance imaging data from glioma patients using deep learning.
Menze B, Isensee F, Wiest R, Wiestler B, Maier-Hein K, Reyes M, Bakas S.
Comput Med Imaging Graph. 2021 Mar;88:101828.
doi: 10.1016/j.compmedimag.2020.101828. 
 
Deep learning for medical image analysis: a brief introduction.
Wiestler B, Menze B.
Neurooncol Adv. 2021 Jan 23;2(Suppl 4):iv35-iv41.
doi: 10.1093/noajnl/vdaa092. 
 
3D Deep Learning Enables Accurate Layer Mapping of 2D Materials.
Dong X, Li H, Jiang Z, Grünleitner T, Güler İ, Dong J, Wang K, Köhler MH, Jakobi M, Menze BH, Yetisen AK, Sharp ID, Stier AV, Finley JJ, Koch AW.
ACS Nano. 2021 Feb 23;15(2):3139-3151.
doi: 10.1021/acsnano.0c09685. 
 
Compressive MRI quantification using convex spatiotemporal priors and deep encoder-decoder networks.
Golbabaee M, Buonincontri G, Pirkl CM, Menzel MI, Menze BH, Davies M, Gómez PA. Med Image Anal. 2021 Apr;69:101945.
doi: 10.1016/j.media.2020.101945.

Morphological residual convolutional neural network (M-RCNN) for intelligent recognition of wear particles from artificial joints.
Hu X, Song J., Liao, Z., Liu Y, Gao J, Menze B & Liu W. 
Friction (2021).
https://doi.org/10.1007/s40544-021-0516-2

Modeling motor task activation from resting-state fMRI using machine learning in individual subjects.
Niu C, Cohen AD, Wen X, Chen Z, Lin P, Liu X, Menze BH, Wiestler B, Wang Y, Zhang M. Brain Imaging Behav. 2021 Feb;15(1):122-132.
doi: 10.1007/s11682-019-00239-9. 

Improving Automated Glioma Segmentation in Routine Clinical Use Through Artificial Intelligence-Based Replacement of Missing Sequences With Synthetic Magnetic Resonance Imaging Scans.
Thomas, M.F.; Kofler, F, Grundl, L, Finck, T., Li, H; Zimmer, C., Menze, B, Wiestler, B, Investigative Radiology: October 13, 2021.
doi: 10.1097/RLI.0000000000000828

Fully automated analysis combining [18F]-FET-PET and multiparametric MRI including DSC perfusion and APTw imaging: a promising tool for objective evaluation of glioma progression.
Paprottka,K. J.,  Kleiner, S., Preibisch, C., Kofler, F.,  Schmidt-Graf,F., Delbridge, C., Bernhardt, D., Combs, S.E. Gempt, J., Meyer, B. Zimmer, C., Menze, B.H., Yakushev, I., Kirschke J. S. & Wiestler B. Eur J Nucl Med Mol Imaging 48, 4445–4455 (2021).
https://doi.org/10.1007/s00259-021-05427-8
 
Multi-domain convolutional neural network (MD-CNN) for radial reconstruction of dynamic cardiac MRI.
El-Rewaidy H, Fahmy AS, Pashakhanloo F, Cai X, Kucukseymen S, Csecs I, Neisius U, Haji-Valizadeh H, Menze B, Nezafat R.
Magn Reson Med. 2021 Mar;85(3):1195-1208.
doi: 10.1002/mrm.28485. 

High-throughput AFM analysis reveals unwrapping pathways of H3 and CENP-A nucleosomes.
Konrad SF, Vanderlinden W, Frederickx W, Brouns T, Menze BH, De Feyter S, Lipfert J. Nanoscale. 2021 Mar 18;13(10):5435-5447.
doi: 10.1039/d0nr08564b.


Polymenidou lab:

FTLD-TDP assemblies seed neoaggregates with subtype-specific features via a prion-like cascade.
De Rossi P, Lewis AJ, Furrer J, De Vos L, Demeter T, Zbinden A, Zhong W, Wiersma VI, Scialo C, Weber J, Guo Z, Scaramuzza S, Di Fabrizio M, Böing C, Castaño-Díez D, Al-Amoudi A, Pérez-Berlanga M, Lashley T, Stahlberg H, Polymenidou M. EMBO Rep. 2021 Dec 6;22(12):e53877.
doi: 10.15252/embr.202153877.
 
Sharing is caring: The benefits of distributing protein aggregates among microglial networks.
Wiersma VI, Polymenidou M.
Neuron. 2021 Oct 20;109(20):3228-3230.
doi: 10.1016/j.neuron.2021.10.008.

LAG3 is not expressed in human and murine neurons and does not modulate α-synucleinopathies.
Emmenegger M, De Cecco E, Hruska-Plochan M, Eninger T, Schneider MM, Barth M, Tantardini E, de Rossi P, Bacioglu M, Langston RG, Kaganovich A, Bengoa-Vergniory N, Gonzalez-Guerra A, Avar M, Heinzer D, Reimann R, Häsler LM, Herling TW, Matharu NS, Landeck N, Luk K, Melki R, Kahle PJ, Hornemann S, Knowles TPJ, Cookson MR, Polymenidou M, Jucker M, Aguzzi A. EMBO Mol Med. 2021 Sep 7;13(9):e14745.
doi: 10.15252/emmm.202114745.
 
Synaptic FUS accumulation triggers early misregulation of synaptic RNAs in a mouse model of ALS.
Sahadevan S, Hembach KM, Tantardini E, Pérez-Berlanga M, Hruska-Plochan M, Megat S, Weber J, Schwarz P, Dupuis L, Robinson MD, De Rossi P, Polymenidou M. Nat Commun. 2021 May 21;12(1):3027.
doi: 10.1038/s41467-021-23188-8.

Cytoplasmic FUS triggers early behavioral alterations linked to cortical neuronal hyperactivity and inhibitory synaptic defects.
Scekic-Zahirovic J, Sanjuan-Ruiz I, Kan V, Megat S, De Rossi P, Dieterlé S, Cassel R, Jamet M, Kessler P, Wiesner D, Tzeplaeff L, Demais V, Sahadevan S, Hembach KM, Muller HP, Picchiarelli G, Mishra N, Antonucci S, Dirrig-Grosch S, Kassubek J, Rasche V, Ludolph A, Boutillier AL, Roselli F, Polymenidou M, Lagier-Tourenne C, Liebscher S, Dupuis L. Nat Commun. 2021 May 21;12(1):3028. doi: 10.1038/s41467-021-23187-9.

We are excited about and grateful for all our members' achievements, opportunities and successes in 2021. Moreover, we are looking forward to an exciting year ahead: In 2022, Prof. Dr. Nicole Joller and her research group will join the DQBM, we are planning our first DQBM Retreat and, of course, we will be doing more excellent science. Please stay tuned!