Cluster Of Excellence Research Articles

P0008 A multi-omics approach across multiple chronic inflammatory diseases identifies a distinct type-1-interferon endotype of Inflammatory Bowel Disease

Abstract Background IBD shares many clinical and immunological features with other chronic inflammatory diseases (CIDs) like rheumatoid arthritis (RA) and psoriasis (Pso). Extraintestinal manifestations, particularly in the joints and skin, often overlap with these CIDs. We hypothesize that a systems medicine approach involving omics-driven phenotyping of multiple CIDs can yield a novel, therapy-relevant molecular taxonomy of disease. In this study, we aim to identify IBD-specific molecular signatures and those shared with other CIDs, as well as novel endotypes of IBD. Methods We recruited a cross-sectional cohort of 650 patients with CIDs (CD, UC, RA, Pso, psoriatic arthritis [PsA], and systemic lupus erythematosus [SLE]) along with 202 healthy controls (HC) at the University Hospital Kiel. Active or inactive disease was defined by clinical activity scores (i.e., CD: CDAI <150; UC: partial Mayo ≤2). Blood samples were collected and subjected to RNA sequencing and methylation profiling. Detailed clinical phenotypes and 5 years-follow-up data were obtained by chart review. We conducted differential gene expression and methylation analyses comparing each CID with HCs to identify shared molecular signatures. Core (activity-independent) signatures were defined by the overlap of differential expression in both active vs. HC and inactive disease vs. HC. Biclustering methods (UnPaSt) were used to uncover distinct patient endotypes based on expression profiles. Results IBD shared the most differential signatures with RA, indicating common pathways in their pathogenesis. Core signatures upregulated across all CIDs correlated with DNA methylation changes, reflecting the molecular mechanism of chronicity, and were enriched in pathways related to cytokine signaling, neutrophil chemotaxis, and humoral immune response. While methylation signatures in enhancer regions were shared among most CIDs, disease-specific methylation was mainly located in CpG islands. One disease-overarching subgroup of 71 patients with active disease, identified by biclustering, exhibited upregulation of interleukin-27 and type-1 interferon signaling, including 16 out of 121 active IBD patients with a skewed sex ratio toward females and higher rates of therapy escalations within 5 years (Log-rank test: p=0.0089). Conclusion Our study highlights shared and disease-specific immune dysregulation pathways contributing to the pathogenesis of IBD and other CIDs. We show the clear presence of core signatures of disease regardless of disease activity, which could represent insights into actionable targets for causative treatments and better disease control of CIDs. With our approach, we identified a distinct molecular endotype of IBD with worse prognosis, warranting further validation studies. References This project has received funding from the DFG Cluster of Excellence 2167 "Precision medicine in chronic inflammation", the BMBF (e:Med Network iTREAT 01ZX2202A), the European Union/Horizon2020 (SYSCID, No 733100) and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR) and No 853995 (ImmUniverse).The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. The content provided in this publication reflects the author's views only. Neither the Innovative Medicines Initiative (IMI JU) nor the European Commission are responsible for any use that may be made of the information it contains.

P0918 Identification of a serum proteomics signature linked with anti-TNF therapy response outcomes in Inflammatory Bowel Disease

Abstract Background While treatment options for active disease in IBD become diverse, the choice of therapies is mostly based on patient characteristics, disease course and severity but restrained by economic rationales. To maximize treatment effectiveness, predictive biomarkers are needed to guide therapies either ex ante or at the earliest possible time point after therapy initiation. Previously, we identified dynamic blood-based RNA and DNA methylation signatures that are linked with therapy response to anti-TNF in IBD1. Here, we aim to identify serum proteome biomarkers associated with therapeutic outcomes in IBD patients receiving anti-TNF treatment. Methods 31 ulcerative colitis (UC) and 27 Crohn’s disease (CD) patients with active clinical and endoscopic disease were recruited and followed at baseline (W0) and at weeks 2 (W2), 6 (W6), and 14 (W14) after initiating infliximab therapy. The clinical endpoint of interest was defined as a combination of clinical remission (partial Mayo ≤ 2/CDAI < 150) and endoscopic response (reduction in endoscopic Mayo ≥ 1/SES-CD ≥ 50%) at W14. Serum was collected at each time point and subjected to proximity extension assays (Olink® Explore 3072 panel) to screen for 2,944 proteins. Linear mixed models (LMM) were applied to identify differentially expressed proteins (DEPs) between endpoint achievers/non-achievers over time. Additionally, post-analysis of DEPs was performed using cv.glmnet with least absolute shrinkage and selection operator (LASSO) regression to identify candidate predictive marker sets. Results A total of 229 DEPs were identified over time between UC responders and non-responders: 8 at W0, 22 at W2, 181 at W6, and 78 at W14. In CD patients, 23 DEPs were identified: 9 at W0, 7 at W2, 13 at W6, and 13 at W14. These DEPs were disease-specific and linked to Gene Ontology (GO) terms related to inflammatory response and cell differentiation. Using LMM and machine learning, we identified 5 baseline proteins in UC and 6 in CD patients that differentiated combined endpoint achievers from non-achievers (AUROC: UC: 0.958, CD: 0.800). Additionally, we identified dynamic changes from W0 to W2 in 7 proteins associated with immune regulation in UC patients (1 in CD), which were linked to therapeutic outcomes at W14. Conclusion Detecting specific ex ante biomarkers or early dynamic molecular signatures are critical for precision medicine in IBD. Our data suggest that serum proteomics profiling enables the differentiation of patients who will attain therapeutic success under anti-TNF therapy from those who will not. This study warrants further investigations in larger, independent datasets to confirm the potential clinical utility of the proteomics signature. References (1) Mishra N, et al. Longitudinal multi-omics analysis identifies early blood-based predictors of anti-TNF therapy response in inflammatory bowel disease. Genome Med. 2022 Sep 24;14(1):110. doi: 10.1186/s13073-022-01112-z. PMID: 36153599; PMCID: PMC9509553. This project has received funding from the DFG Cluster of Excellence 2167 "Precision medicine in chronic inflammation", the BMBF (e:Med Network iTREAT 01ZX2202A, and GUIDE-IBD 031L0188A), and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR) and No 853995 (ImmUniverse).The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. The content provided in this publication reflects the author’s views only. Neither the Innovative Medicines Initiative (IMI JU) nor the European Commission are responsible for any use that may be made of the information it contains.

P0455 An eosinophilic endotype of ulcerative colitis is linked with a more complicated disease phenotype

Abstract Background The course, extent, and therapeutic response in ulcerative colitis (UC) are highly heterogeneous. The spatial and immunological variability of chronic inflammation in UC may explain the inconsistent responses to advanced therapies. Eosinophils are found in both inflamed and non-inflamed tissue at varying numbers, though their exact role in UC pathophysiology and clinical significance is still unclear, despite being part of the Geboes score criteria. We therefore aimed to systematically assess the clinical characteristics of UC patients with tissue eosinophilia as reported by pathology, hypothesizing that this group represents a molecularly distinct sub-entity of UC. Methods We screened all pathology reports from endoscopies performed on IBD patients at the University Hospital Schleswig-Holstein (UKSH, Kiel), between 2010 and 2022. Of 10,552 reports, we identified 179 cases with confirmed UC diagnosis, informed consent, and sufficient clinical and follow-up data. Clinical data extracted from electronic medical records included baseline demographics, histo-endoscopic disease activity, routine blood markers, and 24-month follow-up for UC-related hospitalization, surgery, and therapy escalation (with advanced therapies or systemic steroids). A molecular cross-sectional UC cohort (n=587) recruited at UKSH during the same period served as the control group. Early disease was defined as a disease duration of less than 24 months with no prior advanced therapies. Results Patients with tissue eosinophilia were younger (median age: 36 vs. 42 years, p=0.0095), had a lower BMI (25.20 vs. 33.90 kg/m², p<0.0001), higher blood eosinophil counts (0.20 vs. 0.09 /nL, p=0.0003), elevated CRP levels (3.88 vs. 2.47 mg/L, p=0.0342), and higher Endoscopic Mayo Scores (2 vs. 1, p=0.0003) compared to controls. However, the Nancy Histology Index (2 vs. 2, p>0.05) as well as the sex ratio (male sex: 56.42% vs. 57.99%; p>0.05) was similar between the groups. Within 24 months of follow-up, the tissue eosinophilia group had a higher likelihood of disease-related hospitalization (Log-rank test: p=0.0029) and UC-related surgery (p=0.0223). When stratified by disease phase, these findings were significant only in patients in the late disease phase (hospitalization: p=0.0345; surgery: p=0.0012). Conclusion Tissue eosinophilia in patients in the later stage of their disease is associated with worse long-term outcomes, such as UC-related hospitalization and surgery within 2 years. These findings hint towards the existence of a type-2 immunity-associated endotype of UC. Further studies on eosinophil count and their activation states are needed to define functional signatures of this novel group of patients that might benefit from therapies targeting type-2-cytokines. References This project has received funding from the DFG Cluster of Excellence 2167 “Precision medicine in chronic inflammation”, the BMBF (e:Med Network iTREAT 01ZX2202A), EKFS (2022_EKMS.23), the PATHWAYS Global Innovation Grant program (Sanofi & Regeneron), and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR) and No 853995 (ImmUniverse).The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. The content provided in this publication reflects the author’s views only. Neither the Innovative Medicines Initiative (IMI JU) nor the European Commission are responsible for any use that may be made of the information it contains.

The Relationship of Principal’s Authentic Leadership and Teacher’s Job Motivation in Excellence Cluster Schools.

This study investigates the relationship between principals’ authentic leadership practices and teachers’ job motivation within Excellence Cluster Secondary Schools (Sekolah Kluster Kecemerlangan, SKK) in Johor Bahru, Malaysia. Authentic leadership, characterized by integrity, ethical decision-making, and genuine behavior, has been underscored in the Malaysian Education Development Plan (PPPM) 2013–2025. Through its Fifth Shift, the PPPM emphasizes the need for high-performance leaders in schools to meet the evolving demands of global education. Despite this focus, research indicates that some school principals still fall short in executing their roles effectively. This study, therefore, aims to examine the correlation between the level of authentic leadership exhibited by principals and the resultant job motivation among teachers. Employing a quantitative methodology, the study utilized purposive sampling to gather responses from 187 teachers across three SKKs in Johor Bahru through a structured questionnaire. Data analysis was conducted via the Statistical Package for Social Sciences (SPSS), version 20, and revealed a significant positive correlation between principals’ authentic leadership practices and teachers’ job motivation, as determined by the Spearman Correlation Test. Based on these findings, the study recommends enhancing authentic leadership through ongoing training, recognition programs, and a commitment to positive reinforcement. Future research should expand this work through qualitative approaches and broader demographic sampling to explore authentic leadership impacts across varied educational settings, including private institutions and other school types under the Malaysian Ministry of Education.

Screening the Dynamic Behavior of the Electrode-Electrolyte Interphase on Hard Carbon Via Scanning (Electrochemical) Probe Microscopy

Hard carbon is an attractive anode material for alkali-ion batteries, particularly for sodium-ion batteries (SIBs), due to the high storage capacity and the fact that HC can be produced from renewable bio-resources1. Similar to lithium-ion batteries (LIBs), the performance and operational stability of SIBs is dependent on the electrode electrolyte interface (SEI)2. Although, the SEI on graphite anodes (LIBs) and HC anodes (SIBs) have similar chemical properties, it has been shown that the SEI of SIBs is less stable and its stability is strongly dependent on the experimental conditions3. For example, we have recently investigated the SEI formation on spray-coated HC composite anodes in half-cell configurations in dependence of the electrolyte (ester and ether based including studies in the presence or absence of fluoroethylene carbonate (FEC) as an additive). Using scanning (electrochemical) probe microscopy (SEPM), such as scanning electrochemical microscopy (SECM), atomic force microscopy (AFM) and hybrid AFM-SECM, we could characterize the electrochemical and nanomechanical properties of the SEI4 -6.In this contribution, we present SEPM such as scanning electrochemical cell microscopy (SECCM)7, which has been used as attractive SPM technique for battery research8,9. SECCM is used to locally form SEI layers under different experimental conditions at the surface of HC composite anodes. The advantage of this approach is that on the same electrode surface e.g., different number of charge and discharge cycles can be performed forming localized SEI spots. These spots are then investigated by AFM and AFM-SECM to study the electrochemical and nanomechanical properties as well as dynamic behaviour such as the dissolution or possible swelling. Advantages and challenges of this in situ characterization of the formed interphases at post-Li battery electrodes are discussed. Acknowledgement This work contributes to the research performed at CELEST (Center for Electrochemical Energy Storage Ulm - Karlsruhe) and was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2154 – Project number 390874152 (POLiS Cluster of Excellence).

Being a woman or being a mathematician: Self and external perceptions of female early career researchers in a mathematical cluster of excellence

In Germany, equality between men and women in mathematics, particularly in scientific leadership positions, is far from being achieved. This is despite to different equality measures implemented over the last few decades. Grounded in sociology of knowledge, interaction theory, and field theory, this article analyzes possible causes and mechanisms that maintain gender differences in a mathematical cluster of excellence in which gender equality is formulated as a goal and implemented in various measures. Based on 65 semi-structured interviews, the focus is on the self-perceptions of female early career researchers as mathematicians, as well as the (gendered) attributions they have to deal with by (male and female) scientists in leadership positions against the background of the specific culture in a mathematical cluster of excellence. We highlight the tensions that female early career researchers identify in being regarded as women when they want to be perceived and recognized first as mathematicians. We shed light on how this tension is connected to the discipline and (re)produced by scientists in leadership positions in their patterns of interpretation about equality (measures).

О практике развития некоторых элементов конвергентного образования в технологическом вузе

The article examines the experience of the Faculty of Humanities and its Center for Cognitive Psychology at the University of Technology in involving students in research and applied scientific projects through cooperation and integration of the humanities and technology departments of the University. The ideas of the transformation of the country's educational system and the change of its methodological, pedagogical and technological guidelines in response to modern challenges and risks are analyzed, primarily for the younger generation in need of social adaptation and deeper natural science and humanitarian training for professional and personal growth. The attempts to substantiate the definition of "convergent education" are analyzed. All of them are based on an understanding, to one degree or another, of an interdisciplinary methodological approach to the formation of educational programs, in order to overcome the highly professional training of specialists and avoid formalizing the content of educational material, taking into account the productive interaction of the fundamental component of humanitarian and professional knowledge, the use of modern methods of automation of various types of information activities using information and computer technologies (algorithmization of learning, information modeling). In general, the convergence of education is defined as a process of learning and upbringing, which is a consequence of the implementation of the modern educational paradigm aimed at understanding, rather than memorizing, education for change, the ability to withstand stress, live in a digital world, preserving humanity, sociability and collectivism, ensuring teamwork, preservation and development of the humanitarian and intellectual component "in the context of the interpenetration of sciences and technologies in the implementation of the convergence of real and virtual communications. The scientific and methodological basis for the development of convergent education at the first stage was the development of scientific and pedagogical practices. This can include the management of students' research activities (R&D), involving them in the development and implementation of various projects of scientific laboratories and centers of departments and faculties. The article summarizes some of the experience of the Center for Cognitive Psychology of the Faculty of Social Sciences and Humanities - SGT (until 2022 – ISGT– Institute) of the Federal State Educational Institution of Higher Education "K.G. Razumovsky Moscow State Technical University (PKU)", which was actively involved in the process of cluster formation in the conditions of the university's transformation into an innovative expert–analytical platform, the formation of an expert-educational cluster of excellence "NBICS-technologies of the food industry".

Identifying Landslide Hotspots Using Unsupervised Clustering: A Case Study

Landslides pose significant threats to life, property, and infrastructure. This study explores applying unsupervised learning techniques to identify and understand landslide-prone areas. We analyzed topographic data by employing K-Means, Hierarchical Clustering, Spectral Clustering, Mean Shift Clustering, and DBSCAN to uncover hidden patterns in landslide occurrence. Evaluation metrics, including the Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index, were used to assess the performance of these algorithms. Hierarchical Clustering achieved the highest Silhouette Score of 0.635, indicating excellent cluster separation. However, Mean Shift Clustering outperformed the other methods with a superior Davies-Bouldin Index of 0.603 and the highest Calinski-Harabasz Index of 4121.75, demonstrating the best overall clustering performance. DBSCAN also performed well, with a Silhouette Score of 0.610 and 12 noise points identified. These findings contribute to a deeper understanding of landslide spatial distribution and can inform the development of effective early warning systems and mitigation strategies.

Vitiligo is associated with an increased risk of cardiovascular diseases: a large-scale, propensity-matched, US-based retrospective study

Vitiligo is an autoimmune disease, characterized by specific destruction of melanocytes. While associations with numerous comorbid conditions, which potentially increase the risk of cardiovascular diseases have been described, data on the risk for cardiovascular disease is inconclusive. To address this relevant knowledge gap, this study aims to identify the risk of cardiovascular disease in vitiligo. The US Collaborative Network was accessed using the TriNetX platform, allowing retrospective data retrieval from electronic health records (EHRs) from 57 US based health care organizations (HCOs). Patients with vitiligo and controls were identified by their respective ICD10 codes. Risk of onset of several cardiovascular diseases was determined in patients within 15 years after diagnoses. A total of 94 diagnoses with a prevalence of ≥1% in both cohorts, which consisted of 96,581 individuals per group after propensity-score-matching, were identified. Of those, 54 displayed an increased risk in vitiligo. None of the cardiovascular diseases investigated were associated with a decreased risk in patients with vitiligo. Specifically, cerebral infarction occurred in 1.3% of patients with vitiligo, and 1.0% in controls. This difference translated into a hazard ratio (HR) of 1.21 (95% confidence interval [CI] 1.11-1.32, padj<0.001). Venous thromboembolism was recorded in 1.34% of cases and 1.02% of controls without vitiligo, resulting in an increased HR of 1.27 (95% CI 1.171-1.38, padj<0.001). Further, major adverse cardiovascular events (MACE) as a composite endpoint was evaluated. The risk for MACE was increased following a vitiligo diagnosis (HR 1.28, 95% CI 1.22-1.35, padj<0.001), which persisted in both sensitivity analyses. Patients with vitiligo display an increased risk of onset of cardiovascular diseases as compared to healthy individuals. Thus, vitiligo might require more precise monitoring and systemic treatment. This research was supported by the Schleswig-Holstein Excellence-Chair Program from the State of Schleswig Holstein, by the Excellence Cluster Precision Medicine in Chronic Inflammation (DFG, EXC 2167), and by DFG Individual Grant LU 877/25-1.

INCOMPLETE multi-view clustering based on low-rank adaptive graph learning

The challenge of acquiring complete data has led to substantial progress in incomplete multi-view clustering (IMVC) methods. Because graph structures can be excellent representations of data structure relationships, exceptional performance in handling incomplete data is demonstrated by graph-based methods at present. However, these methods still have their limitations. Most incomplete multi-view algorithms primarily focus on local information, neglecting global information. Therefore, these methods cannot dynamically recover the structural relationships in incomplete data by harnessing potential information from multiple perspectives and overall structural information. In response to the aforementioned concerns, we introduced an IMVC based on low-rank adaptive graph learning (IMVC-LAGL). This method initially constructs an affinity matrix based on the inter-view adjacency relationships. It also utilizes tensor low-rank constraints and consensus representation learning to explore higher-order correlations among different views. Subsequently, it adaptively reconstructs the incomplete graph structure to ultimately obtain a complete affinity relationship. It leads to excellent clustering results by integrating relevant information within views, overall structural information and potential information from multiple perspectives. We conducted experiments comparing our algorithm with eight incomplete multi-view algorithms using five different evaluation metrics. The results show that our algorithm achieves the best clustering results across eight datasets with varying missing rates. Particularly in the BBCSport dataset and YaleB dataset, the clustering accuracy of our algorithm is improved by 19.83 % and 16.41 %, respectively, compared with the second-best algorithm, under a 50 % missing rate.

A Review of Convex Clustering From Multiple Perspectives: Models, Optimizations, Statistical Properties, Applications, and Connections.

Traditional partition-based clustering is very sensitive to the initialized centroids, which are easily stuck in the local minimum due to their nonconvex objectives. To this end, convex clustering is proposed by relaxing K -means clustering or hierarchical clustering. As an emerging and excellent clustering technology, convex clustering can solve the instability problems of partition-based clustering methods. Generally, convex clustering objective consists of the fidelity and the shrinkage terms. The fidelity term encourages the cluster centroids to estimate the observations and the shrinkage term shrinks the cluster centroids matrix so that their observations share the same cluster centroid in the same category. Regularized by the lpn -norm ( pn ∈ {1,2,+∞} ), the convex objective guarantees the global optimal solution of the cluster centroids. This survey conducts a comprehensive review of convex clustering. It starts with the convex clustering as well as its nonconvex variants and then concentrates on the optimization algorithms and the hyperparameters setting. In particular, the statistical properties, the applications, and the connections of convex clustering with other methods are reviewed and discussed thoroughly for a better understanding the convex clustering. Finally, we briefly summarize the development of convex clustering and present some potential directions for future research.

Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients

Background:Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous studies suggest that lipids may play a role in CIPN. Therefore, the present study aimed to identify the particular types of lipids that are regulated as a consequence of paclitaxel administration and may be associated with the occurrence of post-therapeutic neuropathy.Methods:High-resolution mass spectrometry lipidomics was applied to quantify d=255 different lipid mediators in the blood of n=31 patients drawn before and after paclitaxel therapy for breast cancer treatment. A variety of supervised statistical and machine-learning methods was applied to identify lipids that were regulated during paclitaxel therapy or differed among patients with and without post-therapeutic neuropathy.Results:Twenty-seven lipids were identified that carried relevant information to train machine learning algorithms to identify, in new cases, whether a blood sample was drawn before or after paclitaxel therapy with a median balanced accuracy of up to 90%. One of the top hits, sphinganine-1-phosphate (SA1P), was found to induce calcium transients in sensory neurons via the transient receptor potential vanilloid 1 (TRPV1) channel and sphingosine-1-phosphate receptors.SA1P also showed different blood concentrations between patients with and without neuropathy.Conclusions:Present findings suggest a role for sphinganine-1-phosphate in paclitaxel-induced biological changes associated with neuropathic side effects. The identified SA1P, through its receptors, may provide a potential drug target for co-therapy with paclitaxel to reduce one of its major and therapy-limiting side effects.Funding:This work was supported by the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG, Grants SFB1039 A09 and Z01) and by the Fraunhofer Foundation Project: Neuropathic Pain as well as the Fraunhofer Cluster of Excellence for Immune-Mediated Diseases (CIMD). This work was also supported by the Leistungszentrum Innovative Therapeutics (TheraNova) funded by the Fraunhofer Society and the Hessian Ministry of Science and Arts. Jörn Lötsch was supported by the Deutsche Forschungsgemeinschaft (DFG LO 612/16-1).

Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients.

Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous studies suggest that lipids may play a role in CIPN. Therefore, the present study aimed to identify the particular types of lipids that are regulated as a consequence of paclitaxel administration and may be associated with the occurrence of post-therapeutic neuropathy. High-resolution mass spectrometry lipidomics was applied to quantify d=255 different lipid mediators in the blood of n=31 patients drawn before and after paclitaxel therapy for breast cancer treatment. A variety of supervised statistical and machine-learning methods was applied to identify lipids that were regulated during paclitaxel therapy or differed among patients with and without post-therapeutic neuropathy. Twenty-seven lipids were identified that carried relevant information to train machine learning algorithms to identify, in new cases, whether a blood sample was drawn before or after paclitaxel therapy with a median balanced accuracy of up to 90%. One of the top hits, sphinganine-1-phosphate (SA1P), was found to induce calcium transients in sensory neurons via the transient receptor potential vanilloid 1 (TRPV1) channel and sphingosine-1-phosphate receptors.SA1P also showed different blood concentrations between patients with and without neuropathy. Present findings suggest a role for sphinganine-1-phosphate in paclitaxel-induced biological changes associated with neuropathic side effects. The identified SA1P, through its receptors, may provide a potential drug target for co-therapy with paclitaxel to reduce one of its major and therapy-limiting side effects. This work was supported by the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG, Grants SFB1039 A09 and Z01) and by the Fraunhofer Foundation Project: Neuropathic Pain as well as the Fraunhofer Cluster of Excellence for Immune-Mediated Diseases (CIMD). This work was also supported by the Leistungszentrum Innovative Therapeutics (TheraNova) funded by the Fraunhofer Society and the Hessian Ministry of Science and Arts. Jörn Lötsch was supported by the Deutsche Forschungsgemeinschaft (DFG LO 612/16-1).

Gravitational effects on optical lens fabrication: First insides on Earth- and microgravity experiments

Abstract Understanding the effects of gravity on manufacturing processes is a pioneering extension of the process parameter space used to date. Until now, the improvement of manufacturing technologies has mainly focused on process parameters such as temperature, pressure, and material composition, as access to variable gravity environments is limited. The Einstein-Elevator opens up new possibilities for the variation of these process parameters and the development of in-space manufacturing technologies. Together with the research of innovative production processes for optical components within the PhoenixD Cluster of Excellence, this creates an entirely new field of research. The research presented here focuses on investigating gravity's effects on dispensed optical lens production. Using a jet dispenser, sessile droplets are produced during a flight phase in the Einstein-Elevator and cured directly by UV polymerization. As part of this study, optical lenses were produced and compared under microgravity and Earth's gravitational conditions. Geometric properties such as height and contact angle of the lenses produced were analyzed. It was found that lenses fabricated under microgravity have a larger contact angle than those fabricated under Earth gravity. Similarly, the height increases with decreasing gravity. These results are consistent with the theoretical assumptions described, although generalized theories to describe the morphology of a sessile droplet are not yet available. The case study findings on the influence of gravity as a process parameter on drop morphology represent a fundamental improvement for additive manufacturing technologies, especially for in-space manufacturing.

Artificial Intelligence-Supported Development of Health Guideline Questions.

Guideline questions are typically proposed by experts. To assess how large language models (LLMs) can support the development of guideline questions, providing insights on approaches and lessons learned. Two approaches for guideline question generation were assessed: 1) identification of questions conveyed by online search queries and 2) direct generation of guideline questions by LLMs. For the former, the researchers retrieved popular queries on allergic rhinitis using Google Trends (GT) and identified those conveying questions using both manual and LLM-based methods. They then manually structured as guideline questions the queries that conveyed relevant questions. For the second approach, they tasked an LLM with proposing guideline questions, assuming the role of either a patient or a clinician. Allergic Rhinitis and its Impact on Asthma (ARIA) 2024 guidelines. None. Frequency of relevant questions generated. The authors retrieved 3975 unique queries using GT. From these, they identified 37 questions, of which 22 had not been previously posed by guideline panel members and 2 were eventually prioritized by the panel. Direct interactions with LLMs resulted in the generation of 22 unique relevant questions (11 not previously suggested by panel members), and 4 were eventually prioritized by the panel. In total, 6 of 39 final questions prioritized for the 2024 ARIA guidelines were not initially thought of by the panel. The researchers provide a set of practical insights on the implementation of their approaches based on the lessons learned. Single case study (ARIA guidelines). Approaches using LLMs can support the development of guideline questions, complementing traditional methods and potentially augmenting questions prioritized by guideline panels. Fraunhofer Cluster of Excellence for Immune-Mediated Diseases.

IPFMC: an iterative pathway fusion approach for enhanced multi-omics clustering in cancer research.

Using multi-omics data for clustering (cancer subtyping) is crucial for precision medicine research. Despite numerous methods having been proposed, current approaches either do not perform satisfactorily or lack biological interpretability, limiting the practical application of these methods. Based on the biological hypothesis that patients with the same subtype may exhibit similar dysregulated pathways, we developed an Iterative Pathway Fusion approach for enhanced Multi-omics Clustering (IPFMC), a novel multi-omics clustering method involving two data fusion stages. In the first stage, omics data are partitioned at each layer using pathway information, with crucial pathways iteratively selected to represent samples. Ultimately, the representation information from multiple pathways is integrated. In the second stage, similarity network fusion was applied to integrate the representation information from multiple omics. Comparative experiments with nine cancer datasets from The Cancer Genome Atlas (TCGA), involving systematic comparisons with 10 representative methods, reveal that IPFMC outperforms these methods. Additionally, the biological pathways and genes identified by our approach hold biological significance, affirming not only its excellent clustering performance but also its biological interpretability.

Development and validation of a 5K low-density SNP chip for Hainan cattle

BackgroundThis study aimed to design and develop a 5K low-density liquid chip for Hainan cattle utilizing targeted capture sequencing technology. The chip incorporates a substantial number of functional single nucleotide polymorphism (SNP) loci derived from public literature, including SNP loci significantly associated with immunity, heat stress, meat quality, reproduction, and other traits. Additionally, SNPs located in the coding regions of immune-related genes from the Bovine Genome Variation Database (BGVD) and Hainan cattle-specific SNP loci were included.ResultsA total of 5,293 SNPs were selected, resulting in 9,837 DNA probes with a coverage rate of 85.69%, thereby creating a Hainan cattle-specific 5K Genotyping by Target Sequencing (GBTS) liquid chip. Evaluation with 152 cattle samples demonstrated excellent clustering performance and a detection rate ranging from 96.60 to 99.07%, with 94.5% of SNP sites exhibiting polymorphism. The chip achieved 100% gender coverage and displayed a heterozygosity rate between 14.20% and 29.65%, with a repeatability rate of 99.65–99.85%. Analyses using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed the potential regulatory roles of exonic SNPs in immune response pathways.ConclusionThe development and validation of the 5K GBTS liquid chip for Hainan cattle represent a valuable tool for genome analysis and genetic diversity assessment. Furthermore, it facilitates breed identification, gender determination, and kinship analysis, providing a foundation for the efficient utilization and development of local cattle genetic resources.

Visual detection of aldehyde gases using a silver-loaded paper-based colorimetric sensor array

The small molecule aldehydes are volatile organic compounds (VOCs), possessing cytotoxicity and carcinogenicity. Long-term exposure can pose a serious threat to human health. Based on an in-situ reduction colorimetric method to generate silver nanoparticles and induce colorimetric response, we proposed a silver-loaded paper-based colorimetric sensor array for visually detecting and differentiating five relatively common trace small molecule aldehyde gases. The silver ions are immobilized onto a porous filter paper and stabilized by complexing agents of branched polyethyleneimine, ethylenediamine, and 1,6-diaminohexane, respectively. The as-fabricated sensor array expresses remarkable stability and capacity to resist humidity. The qualitative analysis reveals that the sensor array has excellent selectivity for aldehyde gases and displays remarkable anti-interference ability. The quantitative analysis indicates that the sensor array exhibits superior sensitivity for five aldehyde gases, with limits of detection (LODs) of 9.0 ppb for formaldehyde (FA), 3.1 ppm for acetaldehyde (AA), 3.5 ppm for propionaldehyde (PA), 23.8 ppb for glutaric dialdehyde (GD), and 71.5 ppb for hydroxy formaldehyde (HF), respectively. Importantly, these LODs are all comfortably below their respective permissible exposure limits. A unique colorimetric response fingerprint is observed for each analyte. Standard chemometric methods illustrate that the sensor array has excellent clustering capability for these aldehyde gases. Additionally, the sensor array's response is irreversible and possesses outstanding performance for cumulative monitoring. This colorimetric sensor array based on silver ions reduced to silver nanoparticles offers a novel detection method for the continuous, ultrasensitive, and visual detection of trace airborne pollutants.

Leveraging measurement data quality by adoption of the FAIR guiding principles

Abstract The analysis and reuse of measured process data are enablers for sustainable and resilient manufacturing in the future. Maintaining high measurement data quality is vital for maximising the usage and value of the data at hand. To ensure this data quality, the data management must be applied consequently throughout the complete Data Life-Cycle (DLC) and adhere to the FAIR guiding principles. In the two research consortia NFDI4Ing and the Cluster of Excellence “Internet of Production,” we investigate approaches to increase the measurement of data quality by integrating the FAIR guiding principles in all data management activities of the DLC. To facilitate the uptake of the FAIR guiding principles, we underline the significance of FAIR data for the reuse of high-quality data. Second, we are introducing a harmonised DLC to streamline data management activities. Third, we concisely review current trends and best practices in FAIR-aware data management and give suggestions for implementing the FAIR guiding principles.

Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend.

Gaseous and semi-volatile organic compounds emitted by the transport sector contribute to air pollution and have adverse effects on human health. To reduce harmful effects to the environment as well as to humans, renewable and sustainable bio-hybrid fuels are explored and investigated in the cluster of excellence "The Fuel Science Center" at RWTH Aachen University. However, data on the effects of bio-hybrid fuels on human health is scarce, leaving a data gap regarding their hazard potential. To help close this data gap, this study investigates potential toxic effects of a Ketone-Ester-Alcohol-Alkane (KEAA) fuel blend on A549 human lung cells. Experiments were performed using a commercially available air-liquid interface exposure system which was optimized beforehand. Then, cells were exposed at the air-liquid interface to 50-2000 ppm C3.7 of gaseous KEAA for 1 h. After a 24 h recovery period in the incubator, cells treated with 500 ppm C3.7 KEAA showed significant lower metabolic activity and cells treated with 50, 250, 500 and 1000 ppm C3.7 KEAA showed significant higher cytotoxicity compared to controls. Our data support the international occupational exposure limits of the single KEAA constituents. This finding applies only to the exposure scenario tested in this study and is difficult to extrapolate to the complex in vivo situation.