@misc{DellepianeVaidJaladankietal.2021, author = {Dellepiane, Sergio and Vaid, Akhil and Jaladanki, Suraj K. and Coca, Steven and Fayad, Zahi A. and Charney, Alexander W. and B{\"o}ttinger, Erwin and He, John Cijiang and Glicksberg, Benjamin S. and Chan, Lili and Nadkarni, Girish}, title = {Acute kidney injury in patients hospitalized with COVID-19 in New York City}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t}, number = {5}, issn = {2590-0595}, doi = {10.25932/publishup-58541}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-585415}, pages = {5}, year = {2021}, language = {en} } @article{DellepianeVaidJaladankietal.2021, author = {Dellepiane, Sergio and Vaid, Akhil and Jaladanki, Suraj K. and Coca, Steven and Fayad, Zahi A. and Charney, Alexander W. and B{\"o}ttinger, Erwin and He, John Cijiang and Glicksberg, Benjamin S. and Chan, Lili and Nadkarni, Girish}, title = {Acute kidney injury in patients hospitalized with COVID-19 in New York City}, series = {Kidney medicine}, volume = {3}, journal = {Kidney medicine}, number = {5}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2590-0595}, doi = {10.1016/j.xkme.2021.06.008}, pages = {877 -- 879}, year = {2021}, language = {en} } @article{DattaSachsFreitasdaCruzetal.2021, author = {Datta, Suparno and Sachs, Jan Philipp and Freitas da Cruz, Harry and Martensen, Tom and Bode, Philipp and Morassi Sasso, Ariane and Glicksberg, Benjamin S. and B{\"o}ttinger, Erwin}, title = {FIBER}, series = {JAMIA open}, volume = {4}, journal = {JAMIA open}, number = {3}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {2574-2531}, doi = {10.1093/jamiaopen/ooab048}, pages = {10}, year = {2021}, abstract = {Objectives: The development of clinical predictive models hinges upon the availability of comprehensive clinical data. Tapping into such resources requires considerable effort from clinicians, data scientists, and engineers. Specifically, these efforts are focused on data extraction and preprocessing steps required prior to modeling, including complex database queries. A handful of software libraries exist that can reduce this complexity by building upon data standards. However, a gap remains concerning electronic health records (EHRs) stored in star schema clinical data warehouses, an approach often adopted in practice. In this article, we introduce the FlexIBle EHR Retrieval (FIBER) tool: a Python library built on top of a star schema (i2b2) clinical data warehouse that enables flexible generation of modeling-ready cohorts as data frames. Materials and Methods: FIBER was developed on top of a large-scale star schema EHR database which contains data from 8 million patients and over 120 million encounters. To illustrate FIBER's capabilities, we present its application by building a heart surgery patient cohort with subsequent prediction of acute kidney injury (AKI) with various machine learning models. Results: Using FIBER, we were able to build the heart surgery cohort (n = 12 061), identify the patients that developed AKI (n = 1005), and automatically extract relevant features (n = 774). Finally, we trained machine learning models that achieved area under the curve values of up to 0.77 for this exemplary use case. Conclusion: FIBER is an open-source Python library developed for extracting information from star schema clinical data warehouses and reduces time-to-modeling, helping to streamline the clinical modeling process.}, language = {en} } @article{CopeBaukmannKlingeretal.2021, author = {Cope, Justin L. and Baukmann, Hannes A. and Klinger, J{\"o}rn E. and Ravarani, Charles N. J. and B{\"o}ttinger, Erwin and Konigorski, Stefan and Schmidt, Marco F.}, title = {Interaction-based feature selection algorithm outperforms polygenic risk score in predicting Parkinson's Disease status}, series = {Frontiers in genetics}, volume = {12}, journal = {Frontiers in genetics}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-8021}, doi = {10.3389/fgene.2021.744557}, pages = {9}, year = {2021}, abstract = {Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the state of the art in the prediction of susceptibility to complex traits or diseases, yet their predictive performance is limited for various reasons, not least of which is their failure to incorporate the effects of gene-gene interactions. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson's Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95\% CI = [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95\% CI = [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson's disease. For instance, the model revealed an interaction of previously described drug target candidate genes TMEM175 and GAPDHP25. These results demonstrate that interaction-based machine learning models can improve genetic prediction models and might provide an answer to the missing heritability problem.}, language = {en} } @article{LewkowiczBoettingerSiegel2023, author = {Lewkowicz, Daniel and B{\"o}ttinger, Erwin and Siegel, Martin}, title = {Economic evaluation of digital therapeutic care apps for unsupervised treatment of low back pain}, series = {JMIR mhealth and uhealth}, volume = {11}, journal = {JMIR mhealth and uhealth}, publisher = {JMIR Publications}, address = {Toronto}, issn = {2291-5222}, doi = {10.2196/44585}, pages = {14}, year = {2023}, abstract = {Background: Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. Objective: The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. Methods: The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. Results: The Monte Carlo simulation yielded on average a euro135.97 (a currency exchange rate of EUR euro1=US \$1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional euro34,315.19 per additional QALY. DTC yielded more QALYs in 54.96\% of the iterations. DTC dominates TAU in 24.04\% of the iterations for QALYs. Reducing the app price in the simulation from currently euro239.96 to euro164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96\%. Conclusions: Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60\% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.}, language = {en} } @article{KonigorskiWernickeSlosareketal.2022, author = {Konigorski, Stefan and Wernicke, Sarah and Slosarek, Tamara and Zenner, Alexander M. and Strelow, Nils and Ruether, Darius F. and Henschel, Florian and Manaswini, Manisha and Pottb{\"a}cker, Fabian and Edelman, Jonathan A. and Owoyele, Babajide and Danieletto, Matteo and Golden, Eddye and Zweig, Micol and Nadkarni, Girish N. and B{\"o}ttinger, Erwin}, title = {StudyU: a platform for designing and conducting innovative digital N-of-1 trials}, series = {Journal of medical internet research}, volume = {24}, journal = {Journal of medical internet research}, number = {7}, publisher = {Healthcare World}, address = {Richmond, Va.}, issn = {1439-4456}, doi = {10.2196/35884}, pages = {12}, year = {2022}, abstract = {N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.}, language = {en} } @article{WoutersenJardineGiovanniBogotaAngeletal.2018, author = {Woutersen, Amber and Jardine, Phillip E. and Giovanni Bogota-Angel, Raul and Zhang, Hong-Xiang and Silvestro, Daniele and Antonelli, Alexandre and Gogna, Elena and Erkens, Roy H. J. and Gosling, William D. and Dupont-Nivet, Guillaume and Hoorn, Carina}, title = {A novel approach to study the morphology and chemistry of pollen in a phylogenetic context, applied to the halophytic taxon Nitraria L.(Nitrariaceae)}, series = {PeerJ}, volume = {6}, journal = {PeerJ}, publisher = {PeerJ Inc.}, address = {London}, issn = {2167-8359}, doi = {10.7717/peerj.5055}, pages = {31}, year = {2018}, abstract = {Nitraria is a halophytic taxon (i.e., adapted to saline environments) that belongs to the plant family Nitrariaceae and is distributed from the Mediterranean, across Asia into the south-eastern tip of Australia. This taxon is thought to have originated in Asia during the Paleogene (66-23 Ma), alongside the proto-Paratethys epicontinental sea. The evolutionary history of Nitraria might hold important clues on the links between climatic and biotic evolution but limited taxonomic documentation of this taxon has thus far hindered this line of research. Here we investigate if the pollen morphology and the chemical composition of the pollen wall are informative of the evolutionary history of Nitraria and could explain if origination along the proto-Paratethys and dispersal to the Tibetan Plateau was simultaneous or a secondary process. To answer these questions, we applied a novel approach consisting of a combination of Fourier Transform Infrared spectroscopy (FTIR), to determine the chemical composition of the pollen wall, and pollen morphological analyses using Light Microscopy (LM) and Scanning Electron Microscopy (SEM). We analysed our data using ordinations (principal components analysis and non-metric multidimensional scaling), and directly mapped it on the Nitrariaceae phylogeny to produce a phylomorphospace and a phylochemospace. Our LM, SEM and FTIR analyses show clear morphological and chemical differences between the sister groups Peganum and Nitraria. Differences in the morphological and chemical characteristics of highland species (Nitraria schoberi, N. sphaerocarpa, N. sibirica and N. tangutorum) and lowland species (Nitraria billardierei and N. retusa) are very subtle, with phylogenetic history appearing to be a more important control on Nitraria pollen than local environmental conditions. Our approach shows a compelling consistency between the chemical and morphological characteristics of the eight studied Nitrariaceae species, and these traits are in agreement with the phylogenetic tree. Taken together, this demonstrates how novel methods for studying fossil pollen can facilitate the evolutionary investigation of living and extinct taxa, and the environments they represent.}, language = {en} } @article{VaidSomaniRussaketal.2020, author = {Vaid, Akhil and Somani, Sulaiman and Russak, Adam J. and De Freitas, Jessica K. and Chaudhry, Fayzan F. and Paranjpe, Ishan and Johnson, Kipp W. and Lee, Samuel J. and Miotto, Riccardo and Richter, Felix and Zhao, Shan and Beckmann, Noam D. and Naik, Nidhi and Kia, Arash and Timsina, Prem and Lala, Anuradha and Paranjpe, Manish and Golden, Eddye and Danieletto, Matteo and Singh, Manbir and Meyer, Dara and O'Reilly, Paul F. and Huckins, Laura and Kovatch, Patricia and Finkelstein, Joseph and Freeman, Robert M. and Argulian, Edgar and Kasarskis, Andrew and Percha, Bethany and Aberg, Judith A. and Bagiella, Emilia and Horowitz, Carol R. and Murphy, Barbara and Nestler, Eric J. and Schadt, Eric E. and Cho, Judy H. and Cordon-Cardo, Carlos and Fuster, Valentin and Charney, Dennis S. and Reich, David L. and B{\"o}ttinger, Erwin and Levin, Matthew A. and Narula, Jagat and Fayad, Zahi A. and Just, Allan C. and Charney, Alexander W. and Nadkarni, Girish N. and Glicksberg, Benjamin S.}, title = {Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation}, series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, volume = {22}, journal = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, number = {11}, publisher = {Healthcare World}, address = {Richmond, Va.}, issn = {1439-4456}, doi = {10.2196/24018}, pages = {19}, year = {2020}, abstract = {Background: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. Objective: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. Methods: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. Results: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. Conclusions: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.}, language = {en} } @article{DoellDjalaliFarahaniKofoetZrenneretal.2021, author = {D{\"o}ll, Stefanie and Djalali Farahani-Kofoet, Roxana and Zrenner, Rita and Henze, Andrea and Witzel, Katja}, title = {Tissue-specific signatures of metabolites and proteins in asparagus roots and exudates}, series = {Horticulture research}, volume = {8}, journal = {Horticulture research}, number = {1}, publisher = {Nanjing Agricultural Univ.}, address = {Nanjing}, issn = {2052-7276}, doi = {10.1038/s41438-021-00510-5}, pages = {14}, year = {2021}, abstract = {Comprehensive untargeted and targeted analysis of root exudate composition has advanced our understanding of rhizosphere processes. However, little is known about exudate spatial distribution and regulation. We studied the specific metabolite signatures of asparagus root exudates, root outer (epidermis and exodermis), and root inner tissues (cortex and vasculature). The greatest differences were found between exudates and root tissues. In total, 263 non-redundant metabolites were identified as significantly differentially abundant between the three root fractions, with the majority being enriched in the root exudate and/or outer tissue and annotated as 'lipids and lipid-like molecules' or 'phenylpropanoids and polyketides'. Spatial distribution was verified for three selected compounds using MALDI-TOF mass spectrometry imaging. Tissue-specific proteome analysis related root tissue-specific metabolite distributions and rhizodeposition with underlying biosynthetic pathways and transport mechanisms. The proteomes of root outer and inner tissues were spatially very distinct, in agreement with the fundamental differences between their functions and structures. According to KEGG pathway analysis, the outer tissue proteome was characterized by a high abundance of proteins related to 'lipid metabolism', 'biosynthesis of other secondary metabolites' and 'transport and catabolism', reflecting its main functions of providing a hydrophobic barrier, secreting secondary metabolites, and mediating water and nutrient uptake. Proteins more abundant in the inner tissue related to 'transcription', 'translation' and 'folding, sorting and degradation', in accord with the high activity of cortical and vasculature cell layers in growth- and development-related processes. In summary, asparagus root fractions accumulate specific metabolites. This expands our knowledge of tissue-specific plant cell function.}, language = {en} } @article{ToumoulinTardifBecquetDonnadieuetal.2022, author = {Toumoulin, Agathe and Tardif-Becquet, Delphine and Donnadieu, Yannick and Licht, Alexis and Ladant, Jean-Baptiste and Kunzmann, Lutz and Dupont-Nivet, Guillaume}, title = {Evolution of continental temperature seasonality from the Eocene greenhouse to the Oligocene icehouse}, series = {Climate of the past : an interactive open access journal of the European Geosciences Union}, volume = {18}, journal = {Climate of the past : an interactive open access journal of the European Geosciences Union}, number = {2}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1814-9324}, doi = {10.5194/cp-18-341-2022}, pages = {341 -- 362}, year = {2022}, abstract = {At the junction of greenhouse and icehouse climate states, the Eocene-Oligocene Transition (EOT) is a key moment in Cenozoic climate history. While it is associated with severe extinctions and biodiversity turnovers on land, the role of terrestrial climate evolution remains poorly resolved, especially the associated changes in seasonality. Some paleobotanical and geochemical continental records in parts of the Northern Hemisphere suggest the EOT is associated with a marked cooling in winter, leading to the development of more pronounced seasons (i.e., an increase in the mean annual range of temperature, MATR). However, the MATR increase has been barely studied by climate models and large uncertainties remain on its origin, geographical extent and impact. In order to better understand and describe temperature seasonality changes between the middle Eocene and the early Oligocene, we use the Earth system model IPSL-CM5A2 and a set of simulations reconstructing the EOT through three major climate forcings: pCO(2) decrease (1120, 840 and 560 ppm), the Antarctic ice-sheet (AIS) formation and the associated sea-level decrease. Our simulations suggest that pCO(2) lowering alone is not sufficient to explain the seasonality evolution described by the data through the EOT but rather that the combined effects of pCO(2) , AIS formation and increased continentality provide the best data-model agreement.pCO(2) decrease induces a zonal pattern with alternating increasing and decreasing seasonality bands particularly strong in the northern high latitudes (up to 8 degrees C MATR increase) due to sea-ice and surface albedo feedback. Conversely, the onset of the AIS is responsible for a more constant surface albedo yearly, which leads to a strong decrease in seasonality in the southern midlatitudes to high latitudes (> 40 degrees S). Finally, continental areas that emerged due to the sea-level lowering cause the largest increase in seasonality and explain most of the global heterogeneity in MATR changes (1MATR) patterns. The Delta MATR patterns we reconstruct are generally consistent with the variability of the EOT biotic crisis intensity across the Northern Hemisphere and provide insights on their underlying mechanisms.}, language = {en} } @article{KoenigBlockBeckeretal.2018, author = {K{\"o}nig, Johanna and Block, Andrea and Becker, Mathias and Fenske, Kristin and Hertel, Johannes and Van der Auwera, Sandra and Zymara, Kathleen and Voelzke, Henry and Freyberger, Harald J{\"u}rgen and Grabe, Hans Joergen}, title = {Assessment of subjective emotional valence and long-lasting impact of life events}, series = {BMC Psychiatry}, volume = {18}, journal = {BMC Psychiatry}, publisher = {BioMed Central}, address = {London}, issn = {1471-244X}, doi = {10.1186/s12888-018-1649-3}, pages = {12}, year = {2018}, abstract = {Background: Life events (LEs) are associated with future physical and mental health. They are crucial for understanding the pathways to mental disorders as well as the interactions with biological parameters. However, deeper insight is needed into the complex interplay between the type of LE, its subjective evaluation and accompanying factors such as social support. The "Stralsund Life Event List" (SEL) was developed to facilitate this research. Methods: The SEL is a standardized interview that assesses the time of occurrence and frequency of 81 LEs, their subjective emotional valence, the perceived social support during the LE experience and the impact of past LEs on present life. Data from 2265 subjects from the general population-based cohort study "Study of Health in Pomerania" (SHIP) were analysed. Based on the mean emotional valence ratings of the whole sample, LEs were categorized as "positive" or "negative". For verification, the SEL was related to lifetime major depressive disorder (MDD; Munich Composite International Diagnostic Interview), childhood trauma (Childhood Trauma Questionnaire), resilience (Resilience Scale) and subjective health (SF-12 Health Survey). Conclusions: The SEL is a valid instrument that enables the analysis of the number and frequency of LEs, their emotional valence, perceived social support and current impact on life on a global score and on an individual item level. Thus, we can recommend its use in research settings that require the assessment and analysis of the relationship between the occurrence and subjective evaluation of LEs as well as the complex balance between distressing and stabilizing life experiences.}, language = {en} } @article{HerrmannBodenMaureretal.2022, author = {Herrmann, Matthias L. and Boden, Cindy and Maurer, Christoph and Kentischer, Felix and Mennig, Eva and Wagner, S{\"o}ren and Conzelmann, Lars O. and F{\"o}rstner, Bernd R. and Rapp, Michael A. and von Arnim, Christine A. F. and Denkinger, Michael and Eschweiler, Gerhard W. and Thomas, Christine}, title = {Anticholinergic drug exposure increases the risk of delirium in older patients undergoing elective surgery}, series = {Frontiers in medicine}, volume = {9}, journal = {Frontiers in medicine}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-858X}, doi = {10.3389/fmed.2022.871229}, pages = {8}, year = {2022}, abstract = {IntroductionPostoperative delirium (POD) is a common and serious adverse event of surgery in older people. Because of its great impact on patients' safety and quality of life, identification of modifiable risk factors could be useful. Although preoperative medication intake is assumed to be an important modifiable risk factor, the impact of anticholinergic drugs on the occurrence of POD seems underestimated in elective surgery. The aim of this study was to investigate the association between preoperative anticholinergic burden and POD. We hypothesized that a high preoperative anticholinergic burden is an independent, potentially modifiable predisposing and precipitating factor of POD in older people. MethodsBetween November 2017 and April 2019, 1,470 patients of 70 years and older undergoing elective orthopedic, general, cardiac, or vascular surgery were recruited in the randomized, prospective, multicenter PAWEL trial. Anticholinergic burden of a sub-cohort of 899 patients, who did not receive a multimodal intervention for preventing POD, was assessed by two different tools at hospital admission: The established Anticholinergic Risk Scale (ARS) and the recently developed Anticholinergic Burden Score (ABS). POD was detected by confusion assessment method (CAM) and a validated post discharge medical record review. Logistic regression analyses were performed to evaluate the association between anticholinergic burden and POD. ResultsPOD was observed in 210 of 899 patients (23.4\%). Both ARS and ABS were independently associated with POD. The association persisted after adjustment for relevant confounding factors such as age, sex, comorbidities, preoperative cognitive and physical status, number of prescribed drugs, surgery time, type of surgery and anesthesia, usage of heart-lung-machine, and treatment in intensive care unit. If a patient was taking one of the 56 drugs listed in the ABS, risk for POD was 2.7-fold higher (OR = 2.74, 95\% CI = 1.55-4.94) and 1.5-fold higher per additional point on the ARS (OR = 1.54, 95\% CI = 1.15-2.02). ConclusionPreoperative anticholinergic drug exposure measured by ARS or ABS was independently associated with POD in older patients undergoing elective surgery. Therefore, identification, discontinuation or substitution of anticholinergic medication prior to surgery may be a promising approach to reduce the risk of POD in older patients.}, language = {en} } @article{JaraMunozMelnickLietal.2022, author = {Jara-Mu{\~n}oz, Julius and Melnick, Daniel and Li, Shaoyang and Socquet, Anne and Cort{\´e}s-Aranda, Joaqu{\´i}n and Brill, Dominik and Strecker, Manfred R.}, title = {The cryptic seismic potential of the Pichilemu blind fault in Chile revealed by off-fault geomorphology}, series = {Nature communications}, volume = {13}, journal = {Nature communications}, number = {1}, publisher = {Nature Research}, address = {Berlin}, issn = {2041-1723}, doi = {10.1038/s41467-022-30754-1}, pages = {13}, year = {2022}, abstract = {The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 +/- 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 +/- 0.2 ka recurrence time for Mw similar to 7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.}, language = {en} } @article{HaugkJongejansMangelsdorfetal.2022, author = {Haugk, Charlotte and Jongejans, Loeka L. and Mangelsdorf, Kai and Fuchs, Matthias and Ogneva, Olga and Palmtag, Juri and Mollenhauer, Gesine and Mann, Paul J. and Overduin, P. Paul and Grosse, Guido and Sanders, Tina and Tuerena, Robyn E. and Schirrmeister, Lutz and Wetterich, Sebastian and Kizyakov, Alexander and Karger, Cornelia and Strauss, Jens}, title = {Organic matter characteristics of a rapidly eroding permafrost cliff in NE Siberia (Lena Delta, Laptev Sea region)}, series = {Biogeosciences}, volume = {19}, journal = {Biogeosciences}, number = {7}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1726-4170}, doi = {10.5194/bg-19-2079-2022}, pages = {2079 -- 2094}, year = {2022}, abstract = {Organic carbon (OC) stored in Arctic permafrost represents one of Earth's largest and most vulnerable terrestrial carbon pools. Amplified climate warming across the Arctic results in widespread permafrost thaw. Permafrost deposits exposed at river cliffs and coasts are particularly susceptible to thawing processes. Accelerating erosion of terrestrial permafrost along shorelines leads to increased transfer of organic matter (OM) to nearshore waters. However, the amount of terrestrial permafrost carbon and nitrogen as well as the OM quality in these deposits is still poorly quantified. We define the OM quality as the intrinsic potential for further transformation, decomposition and mineralisation. Here, we characterise the sources and the quality of OM supplied to the Lena River at a rapidly eroding permafrost river shoreline cliff in the eastern part of the delta (Sobo-Sise Island). Our multi-proxy approach captures bulk elemental, molecu- lar geochemical and carbon isotopic analyses of Late Pleistocene Yedoma permafrost and Holocene cover deposits, discontinuously spanning the last similar to 52 kyr. We showed that the ancient permafrost exposed in the Sobo-Sise cliff has a high organic carbon content (mean of about 5 wt \%). The oldest sediments stem from Marine Isotope Stage (MIS) 3 interstadial deposits (dated to 52 to 28 cal ka BP) and are overlaid by last glacial MIS 2 (dated to 28 to 15 cal ka BP) and Holocene MIS 1 (dated to 7-0 cal ka BP) deposits. The relatively high average chain length (ACL) index of n-alkanes along the cliff profile indicates a predominant contribution of vascular plants to the OM composition. The elevated ratio of isoand anteiso-branched fatty acids (FAs) relative to mid- and long-chain (C >= 20) n-FAs in the interstadial MIS 3 and the interglacial MIS 1 deposits suggests stronger microbial activity and consequently higher input of bacterial biomass during these climatically warmer periods. The overall high carbon preference index (CPI) and higher plant fatty acid (HPFA) values as well as high C/N ratios point to a good quality of the preserved OM and thus to a high potential of the OM for decomposition upon thaw. A decrease in HPFA values downwards along the profile probably indicates stronger OM decomposition in the oldest (MIS 3) deposits of the cliff. The characterisation of OM from eroding permafrost leads to a better assessment of the greenhouse gas potential of the OC released into river and nearshore waters in the future.}, language = {en} } @article{VoglimacciStephanopoliWendlederLantuitetal.2022, author = {Voglimacci-Stephanopoli, Jo{\"e}lle and Wendleder, Anna and Lantuit, Hugues and Langlois, Alexandre and Stettner, Samuel and Schmitt, Andreas and Dedieu, Jean-Pierre and Roth, Achim and Royer, Alain}, title = {Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation}, series = {Cryosphere}, volume = {16}, journal = {Cryosphere}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1994-0416}, doi = {10.5194/tc-16-2163-2022}, pages = {2163 -- 2181}, year = {2022}, abstract = {Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar - SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015-2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30 circle) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.}, language = {en} } @article{AgtheKayserSchwarzetal.2023, author = {Agthe, Maria and Kayser, Daniela Niesta and Schwarz, Sascha and Maner, Jon K.}, title = {Antecedents of the red-romance effect}, series = {PLOS ONE / Public Library of Science}, volume = {18}, journal = {PLOS ONE / Public Library of Science}, number = {4}, publisher = {PLOS}, address = {San Fransisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0284035}, pages = {19}, year = {2023}, abstract = {The color red has been implicated in a variety of social processes, including those involving mating. While previous research suggests that women sometimes wear red strategically to increase their attractiveness, the replicability of this literature has been questioned. The current research is a reasonably powered conceptual replication designed to strengthen this literature by testing whether women are more inclined to display the color red 1) during fertile (as compared with less fertile) days of the menstrual cycle, and 2) when expecting to interact with an attractive man (as compared with a less attractive man and with a control condition). Analyses controlled for a number of theoretically relevant covariates (relationship status, age, the current weather). Only the latter hypothesis received mixed support (mainly among women on hormonal birth control), whereas results concerning the former hypothesis did not reach significance. Women (N = 281) displayed more red when expecting to interact with an attractive man; findings did not support the prediction that women would increase their display of red on fertile days of the cycle. Findings thus suggested only mixed replicability for the link between the color red and psychological processes involving romantic attraction. They also illustrate the importance of further investigating the boundary conditions of color effects on everyday social processes.}, language = {en} } @article{SchmickerFruehlingMenzeetal.2023, author = {Schmicker, Marlen and Fr{\"u}hling, Insa and Menze, Inga and Glanz, Wenzel and M{\"u}ller, Patrick and Noesselt, Toemme and M{\"u}ller, Notger Germar}, title = {The potential role of gustatory function as an early diagnostic marker for the risk of alzheimer's disease in subjective cognitive decline}, series = {Journal of Alzheimer's disease reports : JADR}, volume = {7}, journal = {Journal of Alzheimer's disease reports : JADR}, number = {1}, publisher = {IOS Press}, address = {Clifton, VA}, issn = {2542-4823}, doi = {10.3233/ADR220092}, pages = {249 -- 262}, year = {2023}, abstract = {Background: Patients with subjective cognitive decline (SCD) report memory deterioration and are at an increased risk of converting to Alzheimer's disease (AD) although psychophysical testing does not reveal any cognitive deficit. Objective: Here, gustatory function is investigated as a potential predictor for an increased risk of progressive cognitive decline indicating higher AD risk in SCD. Methods: Measures of smell and taste perception as well as neuropsychological data were assessed in patients with subjective cognitive decline (SCD): Subgroups with an increased likelihood of the progression to preclinical AD (SCD+) and those with a lower likelihood (SCD-) were compared to healthy controls (HC), patients with mild cognitive impairment and AD patients. The Sniffin' Sticks test contained 12 items with different qualities and taste was measured with 32 taste stripes (sweet, salty, bitter, sour) of different concentration. Results: Only taste was able to distinguish between HC/SCD- and SCD+ patients. Conclusion: This study provides a first hint of taste as a more sensitive marker than smell for detecting preclinical AD in SCD. Longitudinal observation of cognition and pathology are necessary to further evaluate taste perception as a predictor of pathological objective decline in cognition.}, language = {en} } @article{XiongDelicZengetal.2022, author = {Xiong, Yingquan and Delic, Denis and Zeng, Shufei and Chen, Xin and Chu, Chang and Hasan, Ahmed A. and Kr{\"a}mer, Bernhard K. and Klein, Thomas and Yin, Lianghong and Hocher, Berthold}, title = {Regulation of SARS CoV-2 host factors in the kidney and heart in rats with 5/6 nephrectomy-effects of salt, ARB, DPP4 inhibitor and SGLT2 blocker}, series = {BMC nephrology}, volume = {23}, journal = {BMC nephrology}, number = {1}, publisher = {Springer Nature}, address = {London}, issn = {1471-2369}, doi = {10.1186/s12882-022-02747-1}, pages = {10}, year = {2022}, abstract = {Background Host factors such as angiotensin-converting enzyme 2 (ACE2) and the transmembrane protease, serine-subtype-2 (TMPRSS2) are important factors for SARS-CoV-2 infection. Clinical and pre-clinical studies demonstrated that RAAS-blocking agents can be safely used during a SARS-CoV-2 infection but it is unknown if DPP-4 inhibitors or SGLT2-blockers may promote COVID-19 by increasing the host viral entry enzymes ACE2 and TMPRSS2. Methods We investigated telmisartan, linagliptin and empagliflozin induced effects on renal and cardiac expression of ACE2, TMPRSS2 and key enzymes involved in RAAS (REN, AGTR2, AGT) under high-salt conditions in a non-diabetic experimental 5/6 nephrectomy (5/6 Nx) model. In the present study, the gene expression of Ace2, Tmprss2, Ren, Agtr2 and Agt was assessed with qRT-PCR and the protein expression of ACE2 and TMPRSS2 with immunohistochemistry in the following experimental groups: Sham + normal diet (ND) + placebo (PBO); 5/6Nx + ND + PBO; 5/6Nx + high salt-diet (HSD) + PBO; 5/6Nx + HSD + telmisartan; 5/6Nx + HSD + linagliptin; 5/6Nx + HSD + empagliflozin. Results In the kidney, the expression of Ace2 was not altered on mRNA level under disease and treatment conditions. The renal TMPRSS2 levels (mRNA and protein) were not affected, whereas the cardiac level was significantly increased in 5/6Nx rats. Intriguingly, the elevated TMPRSS2 protein expression in the heart was significantly normalized after treatment with telmisartan, linagliptin and empagliflozin. Conclusions Our study indicated that there is no upregulation regarding host factors potentially promoting SARS-CoV-2 virus entry into host cells when the SGLT2-blocker empagliflozin, telmisartan and the DPP4-inhibitor blocker linagliptin are used. The results obtained in a preclinical, experimental non-diabetic kidney failure model need confirmation in ongoing interventional clinical trials.}, language = {en} } @article{HeistermannFranckeScheiffeleetal.2023, author = {Heistermann, Maik and Francke, Till and Scheiffele, Lena and Petrova, Katya Dimitrova and Budach, Christian and Schr{\"o}n, Martin and Trost, Benjamin and Rasche, Daniel and G{\"u}ntner, Andreas and Doepper, Veronika and F{\"o}rster, Michael and K{\"o}hli, Markus and Angermann, Lisa and Antonoglou, Nikolaos and Zude, Manuela and Oswald, Sascha}, title = {Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany}, series = {Earth system science data : ESSD}, volume = {15}, journal = {Earth system science data : ESSD}, number = {7}, publisher = {Copernics Publications}, address = {Katlenburg-Lindau}, issn = {1866-3508}, doi = {10.5194/essd-15-3243-2023}, pages = {3243 -- 3262}, year = {2023}, abstract = {Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany - the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral im-agery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for vari-ous disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b).}, language = {en} } @article{ShamsWangRoineetal.2022, author = {Shams, Boshra and Wang, Ziqian and Roine, Timo and Aydogan, Dogu Baran and Vajkoczy, Peter and Lippert, Christoph and Picht, Thomas and Fekonja, Lucius Samo}, title = {Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract}, series = {Brain communications}, volume = {4}, journal = {Brain communications}, number = {3}, publisher = {Oxford University Press}, address = {Oxford}, issn = {2632-1297}, doi = {10.1093/braincomms/fcac141}, pages = {17}, year = {2022}, abstract = {Shams et al. report that glioma patients' motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77\%. They show that these metrics are more effective than demographic and clinical variables. Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 +/- 16.32 years. Around 37\% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts' profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74\% sensitivity, 75\% specificity, 74\% overall accuracy and 77\% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model's performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.}, language = {en} }