Investigation of parameter-dependent material characteristics of additively manufactured specimens for data-driven part optimization

Direct Metal Laser Sintering (DMLS) is a complex production process including hosts of parameters and a multitude of physical phenomena, which make the simulation and modeling quite challenging. This work investigates the impact of modified printing parameters (e.g., hatch distance, laser power) on correlating material properties (e.g., Young's modulus, temperature gradient) of hardened aluminum specimens. The ultimate goal is to create a data model that enables data-driven and multi-physical optimization of mechanical components fabricated via DMLS

Lsd1 ablation triggers metabolic reprogramming of brown adipose tissue

Previous work indicated that lysine-specific demethylase 1 (Lsd1) can positively regulate the oxidative and thermogenic capacities of white and beige adipocytes. Here we investigate the role of Lsd1 in brown adipose tissue (BAT) and find that BAT- selective Lsd1 ablation induces a shift from oxidative to glycolytic metabolism. This shift is associated with downregulation of BAT-specific and upregulation of white adipose tissue (WAT)-selective gene expression. This results in the accumulation of di- and triacylglycerides and culminates in a profound whitening of BAT in aged Lsd1- deficient mice. Further studies show that Lsd1 maintains BAT properties via a dual role. It activates BAT-selective gene expression in concert with the transcription factor Nrf1 and represses WAT-selective genes through recruitment of the CoREST complex. In conclusion, our data uncover Lsd1 as a key regulator of gene expression and metabolic function in BAT

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach

Ontology matchmaking of product ramp-up knowledge in manufacturing industries : how to transfer a cake-baking recipe between bakeries

Zusammenfassung in deutscher SpracheThe manufacturing industry faces a shortening of product life cycles and decreasing lot sizes (lot size 1) which is particularly challenging with respect to the ability to perform an efficient and predictable ramp-up of new products. The deterministic ramp-up of new products in existing production systems is therefore mission-critical. The ramp-up of a new product starts with the transition of knowledge about the new product from the development production system to the mass-production system, and it ends when instances of the new product are produced and shipped at the latter with planned volume and with repeatable low number of defects. But manufacturing companies still struggle with the predictability of costs and duration as well as the ultimately recoverable yield for the ramp-up of new products. Unfortunately, today's multi-disciplinary ramp-up teams production systems lack a well-structured approach and a common multidisciplinary knowledge base in order to take systematically advantage of knowledge reuse from already performed processes, their capabilities and already produced forerunner products. This knowledge can be used in order to specify the production processes of the new product at the respective production system. In this thesis, a knowledge-based product ramp-up process (K-RAMP) and the underlying multidisciplinary ontology model are proposed in order to interconnect knowledge about a new product of an original production system (e.g., low volume pilot production or development line) with knowledge about the production of forerunner products of a target production system (e.g., high volume production). Based on the existing knowledge assets of forerunners-, subcomponents or already qualified process segments of the target production system, the introduced approach systematically helps to determine and to recommend opportunities for reuse in order to produce the new product. As novelty, the developed derivation logic does not only consider identities between product specifications or between specifications of capabilities of the production system but also similarities due to the generalization of information fragments. An implementation of the design is performed which is based on the Semantic Web. Domains, where alternative solutions need to be applied are also addressed which lead to a hybrid architecture of K-RAMP utilizing predominantly Semantic Web technologies with some imperatively programmed components. It is not the intention of K-RAMP to make production knowledge reusable. This challenge is subject to the respective enterprises within the scope of their management strategies concerning the modularity, scalability and compatibility of products and process segments. K-RAMP contributes with adequate ontology models being derived from existing industry standards and guidelines as well as with a structured, automatable process. Assuming the previously outlined premises as given, K-RAMP can automatically derive recommendations about production knowledge reuse in the scope of a product ramp-up scenario. Such recommendations may help to perform product ramp-up projects faster and with more deterministic results. This work is of particular interest for ICT-experts in the manufacturing industry who are facing challenges from the perspective of information science in order to improve the situation of product ramp-up projects. For the same target group, the work is also of interest with respect to the application of Semantic Web technologies in production environments in general. Due to the application of these technologies, the results of this work are also applicable as starting point for new research which is fostered by Industrie 4.0. This is specifically true for the unification and standardization of public product specifications or production service specifications along the supply chain and research on search engines for the same purpose. This work is therefore of particular interest for research on the application of the Semantic Web for mastering of digitalized supply chains in manufacturing industries as well as on knowledge representation in manufacturing industries for mastering decreasing product lifecycles.17

Characterization of proteins containing lysin-motifs and their role in peptidoglycan perception and innate immunity in Arabidopsis thaliana

Mikroben-assoziierte molekulare Muster (MAMPs) lösen in Pflanzen Immunreaktionen aus. Ein Beispiel hierfür ist Peptidoglycan (PGN), ein essentieller Bestandteil bakterieller Zellwände. Peptidoglycan aus Gram-positiven und Gram-negativen Bakterien induziert typische Immunreaktionen in Arabidopsis thaliana. In dieser Arbeit wurden mit LYM3 und CERK1 zwei Proteine mit Lysin-Motiven (LysM) in A. thaliana identifiziert, die jeweils beide für die Perzeption von hochaufgereinigtem PGN und die Induktion der A. thaliana Wirtsimmunität gegenüber bakteriellen Infektionen notwendig sind. LYM3 ist durch einen Glycosylphosphatidylinositolanker mit der pflanzlichen Cytoplasmamembran assoziiert und besitzt eine extrazelluläre Domäne aus zwei Lysin-Motiven. Mit Hilfe dieser Domäne bindet LYM3 spezifisch und reversibel PGN. CERK1 ist eine membranständige Rezeptor-ähnliche Kinase mit einer extrazellulären Domäne aus drei Lysin-Motiven. CERK1 bindet PGN selbst nicht. LYM3 und CERK1 bilden somit ein Rezeptorsystem zur PGN-Perzeption in A. thaliana. LYM3 und CERK1 erkennen gleichermaßen PGN des Lys- und des DAP-Typs. A. thaliana besitzt ein Erkennungssystem, welches nicht zwischen Gram-positivem und Gram-negativem PGN unterscheidet. Lysin-Motive sind bekannte Bindemotive für Kohlehydratoligomere aus N-Acetylglucosaminmonomeren. Die Perzeption von PGN durch LysM-Proteine neben der von pilzlichem Chitin oder rhizobiellen Nodulationsfaktoren bestätigt die Bedeutung dieser Rezeptorklasse für die pflanzliche Erkennung mikrobieller, molekularer Muster mit GlcNAc-haltigem Glycanrückgrat. LysM-Proteine vermitteln sowohl antagonistische wie auch symbiontischen Interaktionen zwischen Pflanzen und Mikroben. PGN ist als konserviertes, prominentes, bakterielles Oberflächenmolekül von essentieller Bedeutung für die Integrität von Bakterien und existiert in Eukaryonten nicht. Daher ist es prädestiniert als Mikroben-assoziiertes molekulares Muster. Die Erkennung von PGN über die Grenzen der biologischen Reiche hinweg kann als Folge konvergenter Evolution interpretiert werden. PGN stellt somit eines der molekularen Muster dar, deren spezifische Erkennung in multizellulären Eukaryonten sehr weit verbreitet ist und in Wirbeltieren, Insekten und Pflanzen zu finden ist.Microbe-associated molecular patterns (MAMPS) trigger immune responses in plants. An example is represented by peptidoglycan (PGN) which is an essential constituent of bacterial cell walls. PGN from both Gram-positive and Gram-negative bacteria induces typical immune responses in Arabidopsis thaliana. Two lysin-motif (LysM) containing proteins – LYM3 and CERK1 – are necessary for the perception of highly purified PGN and for the induction of A. thaliana host immunity to bacterial infections. LYM3 is associated with the plant plasmamembrane via a glycosylphosphatidyl anchor and contains an extracellular domain of two lysin-motifs. This domain enables LYM3 to bind PGN specifically and reversibly. CERK1 is a transmembrane receptor-like kinase (RLK) with an extracellular domain containing three lysin-motifs. CERK1 is not able to bind PGN. LYM3 and CERK1 therefore establish a receptor system for PGN perception in A. thaliana. LYM3 and CERK1 perceive PGN of both the DAP-type as well as of the Lys-type. Consequently, PGN perception in A. thaliana does not discriminate between PGN derived from Gram-positive or Gram-negative bacteria. lysin-motifs are well-known binding motifs for carbohydrate oligomers containing N-acetylglucosamin. The perception of PGN by LysM proteins besides the perception of fungal chitin or rhizobial nodulation factors confirms the significance of this receptor class in mediating symbiosis between plants and benefactors as well as defense against pathogens. PGN is a conserved bacterial surface molecule. It is essential for the bacterial physiology and does not exist in Eukaryotes. These properties make PGN an excellent target for innate immune systems. Indeed, the perception of PGN is present in different biological kingdoms. The structural differences of the perception systems point to a convergent evolution of PGN recognition

Seed Health Testing: Doing Things Right

Since seeds can be a route for pathogen introduction, they are routinely inspected and tested to prevent pest outbreaks and introduction into new territories. The need for high throughput, short lead times, and cost reduction has played an important role in the development and application of techniques in seed health testing. Examples are molecular and serological techniques, such as ELISA and PCR assays, which are commonly called indirect tests. After signal detection in ELISA or PCR assay a seed lot is a suspect lot that requires further investigation for a final conclusion about the health status of the seed lot, since these tests do not provide any information about pathogen viability or pathogenicity. The seed industry uses them as a prescreen to identify healthy seed lots and in combination with classical methods, commonly called direct tests, to confirm viability of the target pathogen and demonstrate its pathogenicity. However, outside industry, indirect tests are increasingly used to make a final decision on the health status of a seed lot. This has led to a growing number of seed lots being rejected when the risk of introducing a pathogen to importing countries may have been negligible. We propose that investments continue to be made in the development of high-throughput prescreening detection methods like HTS and PCR assays, but together with direct tests that enable accurate assessment of the risks involved when target pathogens are detected using indirect tests. Close collaboration between molecular scientists and classical phytopathologists is essential. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license

Next-generation sequencing reveals a novel role of lysine-specific demethylase 1 in adhesion of rhabdomyosarcoma cells

Lysine-specific demethylase 1 (LSD1), a histone lysine demethylase with the main specificity for H3K4me2, has been shown to be overexpressed in rhabdomyosarcoma (RMS) tumor samples. However, its role in RMS biology is not yet well understood. Here, we identified a new role of LSD1 in regulating adhesion of RMS cells. Genetic knockdown of LSD1 profoundly suppressed clonogenic growth in a panel of RMS cell lines, whereas LSD1 proved to be largely dispensable for regulating cell death and short-term survival. Combined RNA and ChIP-sequencing performed to analyze RNA expression and histone methylation at promoter regions revealed a gene set enrichment for adhesion-associated terms upon LSD1 knockdown. Consistently, LSD1 knockdown significantly reduced adhesion to untreated surfaces. Importantly, precoating of the plates with the adhesives collagen I or fibronectin rescued this reduced adhesion of LSD1 knockdown cells back to levels of control cells. Using KEGG pathway analysis, we identified 17 differentially expressed genes (DEGs) in LSD1 knockdown cells related to adhesion processes, which were validated by qRT-PCR. Combining RNA and ChIP-sequencing results revealed that, within this set of genes, SPP1, C3AR1, ITGA10 and SERPINE1 also exhibited increased H3K4me2 levels at their promoter regions in LSD1 knockdown compared to control cells. Indeed, LSD1 ChIP experiments confirmed enrichment of LSD1 at their promoter regions, suggesting a direct transcriptional regulation by LSD1. By identifying a new role of LSD1 in the modulation of cell adhesion and clonogenic growth of RMS cells, these findings highlight the importance of LSD1 in RMS