Recent Submissions
Zero-waste sand formworks for lightweight concrete structures
(2025) Kovaleva, Daria; Sobek, Werner (Prof. Dr. Dr. E.h. Dr. h.c.)
To address the growing urgent need to reduce resource consumption, embodied energy, and waste in construction, this thesis presents a new method for the zero-waste production of lightweight concrete structures using water-soluble sand formwork. The application of lightweight construction principles allows the creation of efficient and expressive structures with minimal material consumption and, consequently, an ecological footprint. Due to its ability to take any conceivable shape, concrete provides architects and engineers with virtually unlimited design freedom and is ideal for putting these principles into practice. However, despite the wide availability of design solutions known since the middle of the 20th century, lightweight concrete structures are still not widely used due to the lack of adequate sustainable production methods. This often involves formwork manufacturing, which is still labor-intensive and wasteful and accounts for over two-thirds of the production budget. Digital production methods, such as additive and subtractive manufacturing, enable highly precise creation of geometrically complex objects. However, their broader application in formwork production is limited by their narrow specialization in the types of geometry produced, the generation of waste during processing, and the use of toxic and non-recyclable formwork materials. Therefore, the emergence of a flexible and environmentally friendly formwork method suitable for producing geometrically complex structures is necessary for the broader application of lightweight construction with concrete.
Offering a comprehensive approach to the above-described problem, this thesis proposes a novel zero-waste technology to produce lightweight concrete structures using additive manufacturing of a specially developed water-soluble sand and binder mixture. The powder-bed-based 3D printing of granular materials gives the greatest freedom in terms of geometric complexity, while the water-soluble nature of the formwork material mix allows it to be fully recycled after casting and reused in further production cycles. Following the overall goal of promoting lightweight concrete construction, this technology also has an inverse effect on designing lightweight structures. It makes it possible to realize structural morphologies that would be inefficient or even impossible to produce with conventional formwork methods. The water solubility of the formwork material allows the creation of structures with geometrically complex external shapes and internal configurations. This enables not only improved structural performance but also the integration of other functional elements, such as MEP systems, acoustic and thermal insulation.
The work on the thesis includes the conceptualization of a closed-loop production cycle, the creation of an automated manufacturing process based on 3D printing of sand molds with a specially developed material mix, and the development of necessary accompanying CAD-CAM tools. The proposed technology is validated in the production of formworks for lightweight concrete structures of various scales, from small-scale prototypes to architectural demonstrator.
RepEnTools : an automated repeat enrichment analysis package for ChIP-seq data reveals hUHRF1 Tandem-Tudor domain enrichment in young repeats
(2024) Choudalakis, Michel; Bashtrykov, Pavel; Jeltsch, Albert
Background. Repeat elements (REs) play important roles for cell function in health and disease. However, RE enrichment analysis in short-read high-throughput sequencing (HTS) data, such as ChIP-seq, is a challenging task.
Results. Here, we present RepEnTools , a software package for genome-wide RE enrichment analysis of ChIP-seq and similar chromatin pulldown experiments. Our analysis package bundles together various software with carefully chosen and validated settings to provide a complete solution for RE analysis, starting from raw input files to tabular and graphical outputs. RepEnTools implementations are easily accessible even with minimal IT skills (Galaxy/UNIX). To demonstrate the performance of RepEnTools , we analysed chromatin pulldown data by the human UHRF1 TTD protein domain and discovered enrichment of TTD binding on young primate and hominid specific polymorphic repeats (SVA, L1PA1/L1HS) overlapping known enhancers and decorated with H3K4me1-K9me2/3 modifications. We corroborated these new bioinformatic findings with experimental data by qPCR assays using newly developed primate and hominid specific qPCR assays which complement similar research tools. Finally, we analysed mouse UHRF1 ChIP-seq data with RepEnTools and showed that the endogenous mUHRF1 protein colocalizes with H3K4me1-H3K9me3 on promoters of REs which were silenced by UHRF1. These new data suggest a functional role for UHRF1 in silencing of REs that is mediated by TTD binding to the H3K4me1-K9me3 double mark and conserved in two mammalian species.
Conclusions. RepEnTools improves the previously available programmes for RE enrichment analysis in chromatin pulldown studies by leveraging new tools, enhancing accessibility and adding some key functions. RepEnTools can analyse RE enrichment rapidly, efficiently, and accurately, providing the community with an up-to-date, reliable and accessible tool for this important type of analysis.
Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes
(2024) Cao, Xueqi; Huber, Sandra; Ahari, Ata Jadid; Traube, Franziska R.; Seifert, Marc; Oakes, Christopher C.; Secheyko, Polina; Vilov, Sergey; Scheller, Ines F.; Wagner, Nils; Yépez, Vicente A.; Blombery, Piers; Haferlach, Torsten; Heinig, Matthias; Wachutka, Leonhard; Hutter, Stephan; Gagneur, Julien
Background. Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging.
Methods. To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes.
Results. We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities.
Conclusions. Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.
The aluminum standard : using generative Artificial Intelligence tools to synthesize and annotate non-structured patient data
(2024) Diaz Ochoa, Juan G.; Mustafa, Faizan E.; Weil, Felix; Wang, Yi; Kama, Kudret; Knott, Markus
Background. Medical narratives are fundamental to the correct identification of a patient’s health condition. This is not only because it describes the patient’s situation. It also contains relevant information about the patient’s context and health state evolution. Narratives are usually vague and cannot be categorized easily. On the other hand, once the patient’s situation is correctly identified based on a narrative, it is then possible to map the patient’s situation into precise classification schemas and ontologies that are machine-readable. To this end, language models can be trained to read and extract elements from these narratives. However, the main problem is the lack of data for model identification and model training in languages other than English. First, gold standard annotations are usually not available due to the high level of data protection for patient data. Second, gold standard annotations (if available) are difficult to access. Alternative available data, like MIMIC (Sci Data 3:1, 2016) is written in English and for specific patient conditions like intensive care. Thus, when model training is required for other types of patients, like oncology (and not intensive care), this could lead to bias. To facilitate clinical narrative model training, a method for creating high-quality synthetic narratives is needed.
Method. We devised workflows based on generative AI methods to synthesize narratives in the German language to avoid the disclosure of patient’s health data. Since we required highly realistic narratives, we generated prompts, written with high-quality medical terminology, asking for clinical narratives containing both a main and co-disease. The frequency of distribution of both the main and co-disease was extracted from the hospital’s structured data, such that the synthetic narratives reflect the disease distribution among the patient’s cohort. In order to validate the quality of the synthetic narratives, we annotated them to train a Named Entity Recognition (NER) algorithm. According to our assumptions, the validation of this system implies that the synthesized data used for its training are of acceptable quality.
Result. We report precision, recall and F1 score for the NER model while also considering metrics that take into account both exact and partial entity matches. Trained models are cautious, with a precision up to 0.8 for Entity Type match metric and a F1 score of 0.3.
Conclusion. Despite its inherent limitations, this technology has the potential to allow data interoperability by using encoded diseases across languages and regions without compromising data safety. Additionally, it facilitates the synthesis of unstructured patient data. In this way, the identification and training of models can be accelerated. We believe that this method may be able to generate discharge letters for any combination of main and co-diseases, which will significantly reduce the amount of time spent writing these letters by healthcare professionals.
Discrimination of pancreato-biliary cancer and pancreatitis patients by non-invasive liquid biopsy
(2024) Hartwig, Christina; Müller, Jan; Klett, Hagen; Kouhestani, Dina; Mittelstädt, Anke; Anthuber, Anna; David, Paul; Brunner, Maximilian; Jacobsen, Anne; Glanz, Karolina; Swierzy, Izabela; Roßdeutsch, Lotta; Klösch, Bettina; Grützmann, Robert; Wittenberger, Timo; Sohn, Kai; Weber, Georg F.
Background. Current diagnostics for the detection of pancreato-biliary cancers (PBCs) need to be optimized. We therefore propose that methylated cell-free DNA (cfDNA) derived from non-invasive liquid biopsies serves as a novel biomarker with the ability to discriminate pancreato-biliary cancers from non-cancer pancreatitis patients.
Methods. Differentially methylated regions (DMRs) from plasma cfDNA between PBCs, pancreatitis and clinical control samples conditions were identified by next-generation sequencing after enrichment using methyl-binding domains and database searches to generate a discriminatory panel for a hybridization and capture assay with subsequent targeted high throughput sequencing.
Results. The hybridization and capture panel, covering around 74 kb in total, was applied to sequence a cohort of 25 PBCs, 25 pancreatitis patients, 25 clinical controls, and seven cases of Intraductal Papillary Mucinous Neoplasia (IPMN). An unbiased machine learning approach identified the 50 most discriminatory methylation markers for the discrimination of PBC from pancreatitis and controls resulting in an AUROC of 0.85 and 0.88 for a training ( n = 45) and a validation ( n = 37) data set, respectively. The panel was also able to distinguish high grade from low grade IPMN samples.
Conclusions. We present a proof of concept for a methylation biomarker panel with better performance and improved discriminatory power than the current clinical marker CA19-9 for the discrimination of pancreato-biliary cancers from non-cancerous pancreatitis patients and clinical controls. This workflow might be used in future diagnostics for the detection of precancerous lesions, e.g. the identification of high grade IPMNs vs. low grade IPMNs.
Direct numerical simulation and analysis of solid body motion in dilute suspensions using Smoothed Particle Hydrodynamics
(Stuttgart : Institute of Applied Mechanics, 2024) Kijanski, Nadine; Steeb, Holger (Prof. Dr.-Ing.)
Suspensions and their applications are found in many engineering, environmental or medical fields. While the effective rheological behavior is well understood in the framework of non-Newtonian fluid mechanics, contributions in the field of pore-scale fully resolved numerical simulations with non-spherical particles are rare. The motion of single particles immersed in the fluid is still on-going research and depends on hydromechanical forces as well as on solid-solid interactions. Using Smoothed Particle Hydrodynamics, a modeling approach for Direct Numerical Simulations of a single-phase fluid containing non-spherically formed solid aggregates is presented. The motion of single particles in dilute suspensions are observed to analyze effects like shear-wall migration or rolling, as seen in experiments. To be able to simulate the behavior of for example fresh concrete or mud flow as realistic as possible, the simulations taking into account a Newtonian as well as a non-Newtonian material model for the carrier fluid.
Motor skill competence and moderate- and vigorous-intensity physical activity : a linear and non-linear cross-sectional analysis of eight pooled trials
(2024) Barnett, L. M.; Verswijveren, S. J. J. M.; Colvin, B.; Lubans, D. R.; Telford, R. M.; Lander, N. J.; Schott, N.; Tietjens, M.; Hesketh, K. D.; Morgan, P. J.; Hinkley, T.; Downing, K. L.; Telford, R. D.; Cohen, K. E.; Ridgers, N. D.; Abbott, G.
Background. Few studies have examined the relationship between motor skill competence and device-measured physical activity in large samples and none have used non-linear modelling. This study assessed the linear and non-linear associations between motor skill competence and physical activity in children using pooled data from eight studies.
Methods. Cross-sectional ActiGraph accelerometer and motor skills competence data from 988 children (50.8% boys) aged 3-11 years were included. Total, object control and locomotor skill competence were assessed using the Test of Gross Motor Skill Development. Linear mixed models were fitted to examine linear associations between motor skill competence and physical activity. Then, restricted cubic splines models were used to assess potential non-linear relationships. Interactions by sex and age were assessed.
Results. There was evidence of positive linear associations between total skill, and object control and locomotor skills, with moderate- and vigorous-intensity physical activity; however, the associations with total skill competence and object control better fitted a non-linear model. Non-linear models indicated associations were positive but relatively weak in the low to mid ranges of TGMD/object control scores but at high ranges (~ > 70 out of 100/ and ~ 35 out of 50) the association strength increased for both moderate- and vigorous-intensity physical activity. There were sex interactions for locomotor skills only, specifically for vigorous activity with boys having a stronger positive association than girls.
Conclusions. There appears to be a threshold for object control skill proficiency that children need to reach to enhance their physical activity levels which provides support for a motor skill “proficiency barrier”. This provides a tangible benchmark for children to achieve in motor competence programs.
The influence of oral cavity physiological parameters : temperature, pH, and swelling on the performance of denture adhesives - in vitro study
(2024) Koehler, Josephine; Ramakrishnan, Anantha Narayanan; Ludtka, Christopher; Hey, Jeremias; Kiesow, Andreas; Schwan, Stefan
Background. The various physical and chemical conditions within the oral cavity are hypothesized to have a significant influence on the behavior of denture adhesives and therefore the overall comfort of denture wearers. As such, this study aims to understand the influence of oral cavity physiological parameters such as temperature (17 to 52 °C), pH (2, 7, 10), and denture adhesive swelling due to saliva (20-120%) on the behavior of denture adhesives. This study further aims to emphasize the need for a collective approach to modelling the in-situ behavior of denture adhesives.
Methods. Rheological measurements were carried out using the Super Polygrip Ultra fresh brand denture adhesive cream to evaluate its storage modulus (G´) and loss modulus (G´´) values at a range of physiologically relevant temperatures, pH values, and degrees of swelling, to represent and characterize the wide variety of conditions that occur within the oral cavity.
Results. Rheological data was recorded with respect to variation of temperature, pH, and swelling. Overall, it can be seen that the physiological conditions of the oral cavity have an influence on the rheological properties of the denture adhesive cream. Specifically, our data indicates that the adhesive’s mechanical properties are weakly influenced by pH, but do change with respect to the temperature in the oral cavity and the swelling rate of the adhesive.
Conclusions. Our results suggest that the collective inter-play of the parameters pH, temperature and swelling ratio have an influence on the behavior of the denture adhesive. The results clearly highlight the need for developing a multi-parameter viscoelastic material model to understand the collective influence of physiological parameters on the performance of denture adhesives. Multi-parameter models can also potentially be utilized in numerically simulating denture adhesives using finite element simulations.
Endogenous estrogen metabolites as oxidative stress mediators and endometrial cancer biomarkers
(2024) Bukato, Katarzyna; Kostrzewa, Tomasz; Gammazza, Antonella Marino; Gorska-Ponikowska, Magdalena; Sawicki, Sambor
Background. Endometrial cancer is the most common gynecologic malignancy found in developed countries. Because therapy can be curative at first, early detection and diagnosis are crucial for successful treatment. Early diagnosis allows patients to avoid radical therapies and offers conservative management options. There are currently no proven biomarkers that predict the risk of disease occurrence, enable early identification or support prognostic evaluation. Consequently, there is increasing interest in discovering sensitive and specific biomarkers for the detection of endometrial cancer using noninvasive approaches.
Content. Hormonal imbalance caused by unopposed estrogen affects the expression of genes involved in cell proliferation and apoptosis, which can lead to uncontrolled cell growth and carcinogenesis. In addition, due to their ability to cause oxidative stress, estradiol metabolites have both carcinogenic and anticarcinogenic properties. Catechol estrogens are converted to reactive quinones, resulting in oxidative DNA damage that can initiate the carcinogenic process. The molecular anticancer mechanisms are still not fully understood, but it has been established that some estradiol metabolites generate reactive oxygen species and reactive nitrogen species, resulting in nitro-oxidative stress that causes cancer cell cycle arrest or cell death. Therefore, identifying biomarkers that reflect this hormonal imbalance and the presence of endometrial cancer in minimally invasive or noninvasive samples such as blood or urine could significantly improve early detection and treatment outcomes.
Summary. This review analyzes the role of estrogen metabolites as potential biomarkers for the early detection and monitoring of endometrial cancer.
A conversion of the geoid to the quasigeoid at the Hong Kong territories
(2024) Nsiah Ababio, Albertini; Foroughi, Ismael; Tenzer, Robert; Bagherbandi, Mohammad
A levelling network was readjusted and a new geoid model compiled within the framework of geodetic vertical datum modernization at the Hong Kong territories. To accomplish all project objectives, the quasigeoid model has to be determined too. A quasigeoid model can be obtained from existing geoid model by applying the geoid-to-quasigeoid separation. The geoid-to-quasigeoid separation was traditionally computed as a function of the simple planar Bouguer gravity anomaly, while disregarding terrain geometry, topographic density variations, and vertical gravity changes due to mass density heterogeneities below the geoid surface. We applied this approximate method because orthometric heights of levelling benchmarks in Hong Kong were determined only approximately according to Helmert’s theory of orthometric heights. Considering a further improvement of the accuracy of orthometric heights by applying advanced numerical procedures, we determined the geoid-to-quasigeoid separation by applying an accurate method. The comparison of the accurately and approximately computed values of the geoid-to-quasigeoid separation revealed significant differences between them. The approximate values are all negative and reach -2.8 cm, whereas values from the accurate method vary between -4.1 and + 0.2 cm. In addition, we assessed the effect of anomalous topographic density on the geoid-to-quasigeoid separation by employing a newly developed digital rock density model. According to our estimates the effect of anomalous topographic density reaches a maximum value of 1.6 cm, reflecting a predominant presence of light volcanic rocks and sedimentary deposits at the Hong Kong territories. Our numerical findings indicate that the conversion between geoid and quasigeoid models should be done accurately, even in regions with a moderately elevated topography.