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- ItemImproving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis(San Francisco, California, US : PLOS, 2016) Deliano, Matthias; Tabelow, Karsten; König, Reinhard; Polzehl, JörgEstimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning.
- ItemMonoclonal Antibodies 13A4 and AC133 Do Not Recognize the Canine Ortholog of Mouse and Human Stem Cell Antigen Prominin-1 (CD133)(San Francisco, California, US : PLOS, 2016) Thamm, Kristina; Graupner, Sylvi; Werner, Carsten; Huttner, Wieland B.; Corbeil, Denis; Nabi, Ivan RThe pentaspan membrane glycoprotein prominin-1 (CD133) is widely used in medicine as a cell surface marker of stem and cancer stem cells. It has opened new avenues in stem cell-based regenerative therapy and oncology. This molecule is largely used with human samples or the mouse model, and consequently most biological tools including antibodies are directed against human and murine prominin-1. Although the general structure of prominin-1 including its membrane topology is conserved throughout the animal kingdom, its primary sequence is poorly conserved. Thus, it is unclear if anti-human and -mouse prominin-1 antibodies cross-react with their orthologs in other species, especially dog. Answering this issue is imperative in light of the growing number of studies using canine prominin-1 as an antigenic marker. Here, we address this issue by cloning the canine prominin-1 and use its overexpression as a green fluorescent protein fusion protein in Madin-Darby canine kidney cells to determine its immunoreactivity with antibodies against human or mouse prominin-1. We used immunocytochemistry, flow cytometry and immunoblotting techniques and surprisingly found no cross-species immunoreactivity. These results raise some caution in data interpretation when anti-prominin-1 antibodies are used in interspecies studies.
- ItemScanning electron microscopy preparation of the cellular actin cortex: A quantitative comparison between critical point drying and hexamethyldisilazane drying(San Francisco, California, US : PLOS, 2021) Schu, Moritz; Terriac, Emmanuel; Koch, Marcus; Paschke, Stephan; Lautenschläger, Franziska; Flormann, Daniel A.D.The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.
- ItemEffect on healthcare utilization and costs of spinal manual therapy for acute low back pain in routine care: A propensity score matched cohort study(San Francisco, California, US : PLOS, 2017) Walker, Jochen; Mertens, Ulf Kai; Schmidt, Carsten Oliver; Chenot, Jean-FrançoisSpinal manual therapy (SMT) is a popular treatment option for low back pain (LBP). The aim of our analysis was to evaluate the effects of manual therapy delivered by general practitioners and ambulatory orthopedic surgeons in routine care on follow up consultations, sick leave, health service utilization and costs for acute LBP compared to matched patients not receiving manual therapy. This is a propensity score matched cohort study based on health claims data. We identified a total of 113.652 adult patients with acute LBP and no coded red flags of whom 21.021 (18%) received SMT by physicians. In the final analysis 17.965 patients in each group could be matched. Balance on patients' coded characteristics, comorbidity and prior health service utilization was achieved. The provision of SMT for acute LBP had no relevant impact on follow up visits and days of sick leave for LBP in the index billing period and the following year. SMT was associated with a higher proportion of imaging studies for LBP (30.6% vs. 23%, SMD: 0.164 [95% CI 0.143-0.185]). SMT did not lead to meaningful savings by replacing other health services for LBP. SMT for acute non-specific LBP in routine care was not clinically meaningful effective to reduce sick leave and reconsultation rates compared to no SMT and did not lead to meaningful savings by replacing other health services from the perspective of health insurance. This does not imply that SMT is ineffective but might reflect a problem with selection of suitable patients and the quality and quantity of SMT in routine care. National Manual Medicine societies should state clearly that imaging is not routinely needed prior to SMT in patients with low suspicion of presence of red flags and monitor the quality of provided services.
- ItemResearch data management in agricultural sciences in Germany: We are not yet where we want to be(San Francisco, California, US : PLOS, 2022) Senft, Matthias; Stahl, Ulrike; Svoboda, NikolaiTo meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond.
- ItemEvolutionary design of explainable algorithms for biomedical image segmentation([London] : Nature Publishing Group UK, 2023) Cortacero, Kévin; McKenzie, Brienne; Müller, Sabina; Khazen, Roxana; Lafouresse, Fanny; Corsaut, Gaëlle; Van Acker, Nathalie; Frenois, François-Xavier; Lamant, Laurence; Meyer, Nicolas; Vergier, Béatrice; Wilson, Dennis G.; Luga, Hervé; Staufer, Oskar; Dustin, Michael L.; Valitutti, Salvatore; Cussat-Blanc, SylvainAn unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
- ItemSelf-assembly of Co/Pt stripes with current-induced domain wall motion towards 3D racetrack devices([London] : Nature Publishing Group UK, 2024) Fedorov, Pavel; Soldatov, Ivan; Neu, Volker; Schäfer, Rudolf; Schmidt, Oliver G.; Karnaushenko, DaniilModification of the magnetic properties under the induced strain and curvature is a promising avenue to build three-dimensional magnetic devices, based on the domain wall motion. So far, most of the studies with 3D magnetic structures were performed in the helixes and nanowires, mainly with stationary domain walls. In this study, we demonstrate the impact of 3D geometry, strain and curvature on the current-induced domain wall motion and spin-orbital torque efficiency in the heterostructure, realized via a self-assembly rolling technique on a polymeric platform. We introduce a complete 3D memory unit with write, read and store functionality, all based on the field-free domain wall motion. Additionally, we conducted a comparative analysis between 2D and 3D structures, particularly addressing the influence of heat during the electric current pulse sequences. Finally, we demonstrated a remarkable increase of 30% in spin-torque efficiency in 3D configuration.
- ItemNear-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic([London] : Nature Publishing Group UK, 2020) Liu, Zhu; Ciais, Philippe; Deng, Zhu; Lei, Ruixue; Davis, Steven J.; Feng, Sha; Zheng, Bo; Cui, Duo; Dou, Xinyu; Zhu, Biqing; Guo, Rui; Ke, Piyu; Sun, Taochun; Lu, Chenxi; He, Pan; Wang, Yuan; Yue, Xu; Wang, Yilong; Lei, Yadong; Zhou, Hao; Cai, Zhaonan; Wu, Yuhui; Guo, Runtao; Han, Tingxuan; Xue, Jinjun; Boucher, Olivier; Boucher, Eulalie; Chevallier, Frédéric; Tanaka, Katsumasa; Wei, Yiming; Zhong, Haiwang; Kang, Chongqing; Zhang, Ning; Chen, Bin; Xi, Fengming; Liu, Miaomiao; Bréon, François-Marie; Lu, Yonglong; Zhang, Qiang; Guan, Dabo; Gong, Peng; Kammen, Daniel M.; He, Kebin; Schellnhuber, Hans JoachimThe COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.
- ItemState-of-the-art global models underestimate impacts from climate extremes([London] : Nature Publishing Group UK, 2019) Schewe, Jacob; Gosling, Simon N.; Reyer, Christopher; Zhao, Fang; Ciais, Philippe; Elliott, Joshua; Francois, Louis; Huber, Veronika; Lotze, Heike K.; Seneviratne, Sonia I.; van Vliet, Michelle T. H.; Vautard, Robert; Wada, Yoshihide; Breuer, Lutz; Büchner, Matthias; Carozza, David A.; Chang, Jinfeng; Coll, Marta; Deryng, Delphine; de Wit, Allard; Eddy, Tyler D.; Folberth, Christian; Frieler, Katja; Friend, Andrew D.; Gerten, Dieter; Gudmundsson, Lukas; Hanasaki, Naota; Ito, Akihiko; Khabarov, Nikolay; Kim, Hyungjun; Lawrence, Peter; Morfopoulos, Catherine; Müller, Christoph; Müller Schmied, Hannes; Orth, René; Ostberg, Sebastian; Pokhrel, Yadu; Pugh, Thomas A. M.; Sakurai, Gen; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Steenbeek, Jeroen; Steinkamp, Jörg; Tang, Qiuhong; Tian, Hanqin; Tittensor, Derek P.; Volkholz, Jan; Wang, Xuhui; Warszawski, LilaGlobal impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
- ItemComputational design and optimization of electro-physiological sensors([London] : Nature Publishing Group UK, 2021) Nittala, Aditya Shekhar; Karrenbauer, Andreas; Khan, Arshad; Kraus, Tobias; Steimle, JürgenElectro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.