Hexahydroquinoline (HHQ) is a widely recognized scaffold that has garnered considerable attention owing to its diverse pharmacological properties. The structure of HHQ includes a 1,4-dihydropyridine (DHP) ring, which serves as the pharmacophore for the predominant class of drugs known as calcium channel blockers. DHPs are frequently utilized in the management of cardiovascular diseases and also show potential for pain management. Since all DHPs on the market possess ester functionality, we aimed to employ bioisosteric replacement to observe if their amide-containing counterparts would still block calcium channels. Therefore, we synthesized new HHQs with ester or amide functionality (EM1-EM15) and investigated their effects on L-(Cav1.2) and T-(Cav3.2)-type calcium channels using the whole-cell patch clamp technique. Although the amide derivatives were somewhat less effective than their ester counterparts, they still blocked calcium channels to a significant degree. Retesting EM4 enantiomers on two types of calcium channels demonstrated that the (R)-isomer was more responsible for the blocking activity in both cases. Molecular docking and molecular dynamics simulations demonstrated that (R)-EM4 and (R)-EM6 adopt binding modes in Cav1.2 similar to amlodipine, while showing favorable stability. Docking studies in Cav3.2 suggested that EM compounds bind within the Ⅲ-Ⅳ fenestration, a reported non-selective DHP binding site. Furthermore, amide derivatives were found to be more metabolically stable based on the in vitro experiments conducted on rat microsomes. Overall, our study reveals HHQ with an amide group as a promising new scaffold for developing future calcium channel blockers for treating cardiovascular and pain conditions.

At a time when the rule of law is being reshaped and, in certain respects, even severely distorted, this volume examines the ways in which literature both legitimises the principles underlying the present rule of law and anticipates assumptions that take shape before new ideas are publicly felt or articulated within legal discourse. Literary acts of agency thus contribute to a reconfi guration of the legal sphere, advancing arguments through an aesthetic form that remains closely connected to broader social and cultural practices. Rather than approaching literature merely as a vehicle of ruling ideology or as a moral signpost for future legal developments, this volume considers how literary texts negotiate the interval between the rule of law as an ideal and how it is enacted in practice.

Einleitung:

Die vorliegende Handreichung für den Schulunterricht bietet Lehrkräften und ihren Schüler*innen eine künstlerische und bewegungsorientierte Herangehensweise an den Lernbereich „Wasser“. Sie dient als kreative Ergänzung zur Vermittlung von Lehrplaninhalten und eröffnet den Schüler*innen innovative, körperorientierte Lern- und Lösungsansätze für nachhaltige Praktiken. Sie beinhaltet eine Sammlung mit A n r e g u n g e n , Anleitungen und Methoden für Übungen im tanz- und bewegungsbasierten Schulunterricht – auch in anschaulicher Videoform. Die Sammlung eignet sich für alle Fächer und unterstützt durch ihren Bewegungsansatz die Lernprozesse der Kinder aktiv und motivierend. Sie fördert nicht nur die Wahrnehmungs- und Ausdrucksfähigkeit der Kinder, sondern ermöglicht es ihnen, die zunächst kognitiv vermittelten Lerninhalte aus einer forschend-spielerischen Perspektive neu zu erleben und selbst zu gestalten.

Given the scarcity of seismometers in marine environments, traditional seismology has limited effectiveness in oceanic regions. Submarine Distributed Acoustic Sensing (DAS) systems offer a promising alternative for seismic monitoring in these areas. However, the existing machine learning model trained on land-based DAS data does not perform well with submarine DAS due to differences in noise characteristics, deployment conditions and environmental factors. This study presents a machine learning approach tailored specifically to submarine DAS data to enable automated seismic event detection and P- and S-wave identification. Leveraging DeepLab v3, a neural network architecture optimized for semantic segmentation, we developed a specialized model to handle the unique challenges of submarine DAS data. Our model was trained and validated on a data set comprising nearly 57 million manually and semi-automatically labelled seismic records from multiple globally distributed submarine sites, providing a robust basis for accurate seismic detection. The model adapts to a variety of deployment scenarios and can process DAS data from cables with different lengths, configurations and channel spacings, making it versatile for various ocean environments. We thus provide an adaptable and efficient tool for automated earthquake analysis of DAS data, which has the potential to enhance real-time earthquake monitoring and tsunami early warning in submarine environments.

The Permian–Triassic environmental crisis triggered fundamental changes in marine ecosystems, culminating in the most severe biodiversity crisis of the Phanerozoic. Yet, the environmental and geochemical conditions governing the crisis and ecosystem recovery remain debated. The sedimentary succession at Lusitaniadalen, Svalbard, deposited in the Permo–Triassic Boreal Realm, offers insights into mid-paleolatitudinal, shallow marine ecosystem responses. In a multiproxy study combining lipid biomarker and geochemical data, we reconstruct environmental conditions and microbial ecosystem dynamics across the Permian–Triassic environmental crisis. Generally low enrichments of the redox-sensitive trace elements Re, V, U, and Mo, predominantly negative Ce anomalies, and a pristane/phytane ratio >1 suggest mainly oxic conditions in the investigated interval. However, while transient dysoxic to anoxic episodes recorded across the extinction horizon support that deoxygenation contributed to the severity of the mass extinction at this Boreal site, the earlier occurrence of similar episodes of deoxygenation in the late Permian challenges the hypothesis of global anoxia as the sole extinction driver across paleolatitudes. Lipid biomarkers reveal a post-extinction increase in abundance of long-chain n-alkanes derived from terrestrial plants due to increased terrigenous discharge into shallow marine settings across this interval. Pristane and phytane, lipid biomarkers predominantly derived from chlorophyll, reveal a pronounced regional increase in primary productivity following the environmental crisis. The composition of the lipid biomarker inventory recorded in early Griesbachian strata is distinct from the pre-crisis composition, and did not recover towards the pre-crisis state within the studied interval.

Time-resolved step-scan Fourier transform infrared (FTIR) difference spectroscopy was used to obtain (A1– – A1) FTIR difference spectra from photosystem I (PSI) samples isolated from eight phylogenetically diverse cyanobacterial strains and one green alga, totaling 13 PSI preparations. These included samples from cells grown under far-red light and PSI in monomeric, dimeric, trimeric, and tetrameric states. Spectral profiles were shown to be independent of oligomeric state. Remarkably, all (A1– – A1) FTIR difference spectra exhibited high similarity, underscoring the robustness of the technique and indicating minimal experimental variability. This congruence reveals a highly conserved environment for the phylloquinone cofactor at the A1 binding site across diverse taxa. Conserved bands associated with the A0 pigment further suggest structural continuity from A0 to A1. To leverage this consistency, we constructed a composite (A1– – A1) FTIR difference spectrum by averaging all 13 spectra. This composite spectrum provides enhanced resolution, enabling unambiguous identification of previously unresolved bands. The fact that a highly resolved composite spectrum can be obtained by averaging demonstrates the similarity in the spectra from the different types of samples. Band assignments were refined using prior studies, yielding an improved spectral framework for future investigations of PSI electron transfer cofactors.

The 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle in thaumarchaeota contributes significantly to global organic carbon fixation as the most energetically efficient aerobic carbon fixation pathway. The thaumarchaeal 3-Hydroxypropionyl-CoA Synthetase (ADP-forming; Nmar_1309) is crucial to this efficiency, utilizing ATP to ADP catalysis. This first reported structure of Nmar_1309 reveals a homodimer with a unique domain organization and a distinct linker between subdomains 4 and 1. This structure includes the bound substrates 3HP, non-hydrolyzable ATP (ADPNP), and a phosphate which suggest an intermediate state mimicking the non-covalent interaction between 3-hydroxypropionyl-phosphate and the active site histidine prior to reaction with Coenzyme-A. Conformational differences were observed between the two chains of the homodimer, likely influenced by the binding of a single ADPNP molecule in one chain. Phylogenetic analysis suggests that while 4HB synthetases may have evolved earlier in the evolutionary timeline, 3HP synthetases in Thaumarchaeota may have occurred after the Great Oxygenation Event. These structural data provide further characterization of the 3HP/4HB cycle and, in conjunction with the structure of 4-hydroxybutyryl-CoA synthetase, Nmar_0206, provide baseline structures of the key ADP-forming Acyl-CoA synthetases within this pathway.

The increasing support for populism is indicative of a profound crisis in European societies. The prevailing cultural narrative posits that support for populist parties, particularly those of a right-wing orientation, is predominantly a reaction to the erosion of nationalistic and religious identities. A growing critique of supranational institutions became visible in some countries. In Europe, populist parties are growing, but Euroscepticism seems to show different trends. Euroscepticism is diminishing and trust in Europe has been growing since 2018 and in particular since 2022. Is there a lack of trust in the European institutions which is reflected in all political parties? What are the reasons for trust and distrust within the political parties in general and within the populist parties in particular? In most countries, the war between Ukraine and Russia is seen as an external threat to the European Union. Did the Covid-19 pandemic and the Ukraine war lead to a “rally around the flag” phenomenon, and is trust in the European Union increasing because of this external hostility? We found evidence of people switching back from populist to mainstream parties and becoming less Eurosceptic, hinting at a “rally around the flag” effect. The study focuses on panel data from voters in 10 countries—Spain, Germany, France, Italy, the Netherlands, the UK, Sweden, Romania, the Czech Republic, and Hungary—from two waves, namely 2018 and 2023, as well as a cross-section of the 2023 wave. The main focus is on supporters of populist parties, which will be compared to mainstream parties. This study thus explores whether the Ukraine war reinvigorated trust in the European Union.

European grasslands provide biodiversity, carbon storage, and agricultural services, but face increasing pressure from intensification and climate change. We review remote sensing indices used to monitor conservation-relevant grassland environmental indicators in Europe, covering biochemical, structural, spatial, and temporal indices from satellite, airborne, uncrewed aerial vehicle (UAV) and ground-based sensors. We synthesize best-practice applications for landscape/habitat/species identification, biomass and LAI, biodiversity, management, fluxes, and temporal dynamics, and summarize key limitations (e.g., saturation and background effects, mixed pixels, and limited model transferability). Finally, we outline how data fusion and emerging hyperspectral/thermal missions can improve operational, policy-ready monitoring.

Hirshfeld Atom Refinement (HAR) is a quantum crystallographic method for analyzing single-crystal X-ray diffraction data, providing accurate and precise structural parameters. Despite its success in predicting hydrogen-atom parameters, the application of HAR is fundamentally limited to molecular crystals. Inspired by two recently developed HAR versions that employ periodic-boundary conditions, here we introduce a new variant of periodic HAR (pHAR) that is applicable to any periodic-network structure while remaining compatible with conventional HAR by using atom-centered Gaussian orbitals with a Bloch wave formalism. pHAR was tested against high-quality single-crystal diffraction data for boranes and borates comprising N–H and B–H bonds in different chemical environments. The results demonstrate a close agreement of X–H bond lengths with reference data from neutron-diffraction experiments with improved precision. Using pHAR, this study has nearly doubled the previously available body of reliable experimental structural data on B–H bonds.

Introduced species encounter novel biotic and abiotic conditions that influence their success in new environments. Their advantages often arise from reduced competition with species lacking eco-evolutionary experience and from their capacity to preempt or efficiently use resources. Once established, their success can also be shaped by interactions with soil microbial communities. Understanding how these factors influence invasion success can provide valuable insights into identifying the mechanisms that enable certain species to become dominant in a plant community. In this study, we examined how eco-evolutionary experience and invaded-range soil bacterial communities modulate the performance of the invasive subshrub Senecio inaequidens DC. We conducted a fully factorial additive experiment in growth chambers, with S. inaequidens individuals growing at the center of each pot. The design included two factors: (1) competitor community identity with three levels (i.e., plant species from the native range (South Africa), species from the invaded range (Italy), and a control with no competitor species); and (2) soil biotic conditions with two levels (i.e., autoclaved soil with reduced microbial load and non-autoclaved soil). Our results showed that plant community identity had the strongest effect on S. inaequidens growth (height and lateral spread), with the smallest individuals occurring in competition with species from the native range. Growing on autoclaved soil had no major impact on plant height, suggesting that soil microbial communities played a minor role modulating competitive interactions, which were the dominant driver of plant growth responses. Suppression was strongest when competitors were phylogenetically closer to S. inaequidens, especially those from its native range. Soil bacterial communities were influenced by both competitor community identity and soil treatment, with lower bacterial diversity found in pots with better Senecio plant growth. These results indicate that promoting competition with closely related natives and maintaining diverse soil microbiota may limit invasion success.

Antimicrobial resistance threatens millions of lives annually, yet its acceleration by non-antibiotic pollutants remains poorly understood. Artificial sweeteners, now ubiquitous in soils and waters, are known individually to promote conjugative transfer of resistance genes, but real environments contain complex mixtures whose collective impact is unknown. Extracellular vesicles (EVs) released by stressed bacteria serve as protected, long-range vectors for antibiotic resistance genes (ARGs), yet whether sweetener diversity modulates this pathway has never been tested. Here we show that increasing artificial-sweetener diversity dramatically enriches ARGs, virulence factors and mobile genetic elements inside soil-derived Evs, driving compositional shifts in 30.5% of EV-associated genera while leaving the bulk microbiome largely undisturbed. EVs originate from a small, fast-growing Pseudomonadota subset that upregulates vesicle-biogenesis genes in response to oxidative and membrane stress; these vesicles selectively package chromosomal resistance traits and transfer phenotypic resistance to recipient Escherichia coli. This stress-induced decoupling reveals EVs as rapid, hidden mediators of resistome mobilization that community-level surveys miss. By demonstrating that pollutant diversity itself drives resistance dissemination through nanoscale vectors, our findings establish EVs as a critical new indicator within the One Health framework and call for revised environmental risk models that account for chemical complexity rather than single-compound exposures.

The transfer of information from one part of a quantum system to another is fundamental to the understanding and design of quantum information processing devices. In the realm of discrete systems such as spin chains, inhomogeneous networks have been engineered that allow for the perfect transfer of qubits from one end to the other. Here, by contrast, we investigate the perfect transfer of information in continuous systems, phrased in terms of wave propagation. A remarkable difference is found between systems that possess conformal invariance and those that do not. Systems in the first class enjoy perfect wave transfer (PWT), explicitly shown for one-particle excitations and anticipated in general. In the second class, those that exhibit PWT are characterized as solutions to an inverse spectral problem. As a concrete example, we demonstrate how to formulate and solve this problem for a prototypical class of bosonic theories, showing the importance of conformal invariance for these theories to enjoy PWT. Using bosonization, our continuum results extend to theories with interactions, broadening the scope of perfect information transfer to more general quantum systems.

Carbon dioxide (CO2) is commonly used for rat euthanasia, but its potential negative side effects call for alternatives causing less distress while providing a fast and reliable loss of consciousness (LOC). Euthanasia with CO2 is currently performed in a highly non-standardized manner with different CO2 volume displacement rates/minute (VDRM) ranging from replacing 30 to 70% of the chamber volume with 100% CO2 per minute. Therefore, we evaluated euthanasia with 100% CO2 at 30% and 70% VDRM as well as carbon monoxide (8.6% CO at 70% VDRM), nitrogen (100% N2 at 70% VDRM) and isoflurane anesthesia (6% and 2.1% at 70% VDRM) in female and male rats. We used a multi-modal approach including telemetry for ECG, blood pressure (BP), heart rate measurements, EEG, and plethysmography. Video-recordings were used to track behavior during euthanasia. Stress hormones and lung pathology were assessed post-mortem. A VDRM of 70% CO2 resulted in a rapid LOC compared to 30%, thus, minimizing the time in which distress and eventually pain can be experienced. Nevertheless, the higher amount of distress experienced until LOC potentially outweighs the benefits of a faster LOC. CO and N2 resulted in longer times to LOC, seizures before LOC, increased stress hormone levels, and caused more lung damage. Therefore, CO and N2 are not humane alternatives to CO2 and should not be recommended for euthanasia in rats.

Numerous digitisation activities in manufacturing led to an enormous increase in available, accessible data. Knowledge graphs (KGs) become increasingly popular in this domain as they show strengths in integrating different data sources and serve as a basis for downstream tasks. Yet, constructing a KG is still a challenging and time-consuming process. Neuro-symbolic AI approaches, especially with powerful LLMs, have shown promising potential in research and industry and can support KG construction. Nevertheless, KG construction with neural methods must be aware of, or ideally even handle, the inexplicability of results when applying the KG to downstream manufacturing tasks, e.g., tasks of reliability- or safety-relevance. This makes it interesting to evaluate the utilisation of neuro-symbolic AI and LLMs in KG construction in manufacturing. To the best of our knowledge, there is no systematic literature review on neuro-symbolic AI and LLMs in KGs in manufacturing to date. Hence, this paper conducts a systematic literature review on neuro-symbolic AI and LLMs in KG construction in manufacturing. We show a solid increase of relevant publications on manufacturing KG construction and further show that BERT embeddings, RNN encodings, especially BiLSTM, CRF decodings, and, recently, LLMs, are common components of knowledge extraction from text documents to build KGs in manufacturing. With this systematic review, we support both further research and industry application in this field. The main question to guide this review is “Which role play neuro-symbolic AI, especially LLM approaches in knowledge graph construction for manufacturing?”.

The maturation of lineage-committed embryonic hepatocytes requires both the timed activation of metabolic gene regulatory networks (GRNs) and silencing of embryonic programs to achieve adult hepatic functions. However, in vitro derivation of mature hepatocytes remains imperfect, and key transcriptional regulators governing GRN rewiring during late development are still insufficiently defined. To address this, we generated a developmental reference atlas and employed a dCas9 activation screen with single-cell transcriptomics on primary mouse embryonic hepatocytes, enabling effect ranking among late-onset transcription regulators. We identify Nr1i3 as a potent inducer of pericentrally expressed metabolic genes and Nfix as a critical suppressor of embryonic and periportal signatures. Supplementing liver zonation patterning signals with these regulators further enhanced the expression of pericentrally zonated metabolic genes, emphasizing the importance of a microenvironment-targeted approach. Our screening and analysis therefore highlight regulatory mechanisms underlying organ maturation and offer general strategies for improving the functionality of in vitro-derived cells.

Background

Repetitive negative thinking (RNT) and neuroticism are risk factors for internalizing psychopathology. However, their interaction has only been investigated at the self-report level, and studies elucidating their interrelationship at the neural level are lacking. We therefore investigated the interaction of trait RNT and neuroticism with respect to the dynamics of neural networks during negative self-referential processing.

Methods

A sample of 110 healthy subjects reported trait RNT and neuroticism, followed by an RNT induction paradigm during fMRI. Dynamic coactivation pattern (CAP) analysis was used to identify a set of recurring coactivation patterns and to quantify their persistence and count rates. Next, the effects of trait RNT, neuroticism, and their interaction on brain dynamics were tested using regression models.

Results

Negative interactions between RNT and neuroticism were found for persistence and counts of the canonical default mode network (DMN) as well as salience network (SAL) CAP. Simple slope analysis revealed that subjects scoring high on neuroticism exhibited a negative association between trait RNT and DMN as well as canonical SAL dynamics. Furthermore, trait RNT was positively associated with persistence and count rates of a hybrid FPN+DMN coactivation state.

Conclusions

Our results suggest that individuals with high neuroticism who spend more time in SAL and DMN CAPs may be less vulnerable to RNT, potentially reflecting more adaptive network configurations. Furthermore, less segregated CAPs, evident by the concurrent activation of functionally antagonistic networks (FPN+DMN), emerge more often in individuals prone to RNT, likely reflecting disrupted network interactions.

Efficient strategies for the human health risk assessment of micro- and nanoplastics (MNPs) are urgently needed to address the complexity and diversity of these materials. Here, we propose a risk assessment framework for MNPs following the oral route of exposure. The framework is based on a flexible and modular approach, drawing on modern concepts in risk assessment, such as Integrated Approaches to Testing and Assessment (IATAs) or Adverse Outcome Pathways (AOPs), and substantially relies on New Approach Methodologies (NAMs). The framework is structured into three different main steps: i) basic physicochemical characterization of testing materials, ii) intestinal crossing, iii) hazard assessment testing. Each step of the framework is supported by scientifically sound methods, enabling a mechanistic and hypothesis-driven risk assessment of MNPs.

Eco-anxiety refers to psychological distress arising from the anticipated impacts of planetary crises. Even though young people are at major risk for both psychopathology and the long-term consequences of planetary crises, no psychometrically validated German instrument currently exists to assess eco-anxiety in this age group, and research on age differences in eco-anxiety remains limited. The present study aimed to replicate the psychometric properties of the German validation study of the Hogg Eco-Anxiety Scale (HEAS) in a younger age group (N = 414; Mage = 20.24, SDage = 2.80, age range: 15–25) as well as the four-factor structure (Affective Symptoms, Rumination, Behavioral Symptoms, and Anxiety about Personal Impact). By combining the present sample with two additional samples, measurement invariance across two age groups (15–25 years vs. >25 years) was established, suggesting that the HEAS measures eco-anxiety similarly across ages. All hypotheses were confirmed; additionally, latent mean comparisons show that the younger group experiences higher levels of eco-anxiety than the older group. Exploratory analyses further found that participants demonstrating elevated symptoms of depression or anxiety reported significantly higher levels of eco-anxiety across all HEAS subscales. Moreover, individuals residing in metropolitan areas scored higher on the scale Anxiety about the Personal Impact compared to participants from rural regions. Enhancing the precision of eco-anxiety assessment depending on age, clinical status, and geographical contexts enables the targeted development and implementation of preventive and therapeutic interventions according to the level of severity indicated by this instrument.

In the last two decades, forced removals have been the main feature of U.S. migration policy toward Latin America. In this research, we explore whether this policy has had implications in terms of Latin Americans’ public opinion toward their northern neighbour. We argue that deportations breed anti-Americanism by cutting off the flow of information and money associated with emigration, which has proven to be a source of better dispositions toward the United States. Using public opinion data and municipal data on deportations in El Salvador, we show that these perceptions have worsened over time and that rates of deportation are related to this trend. By using public opinion data on Latin America and deportation rates in the region, we also show that this pattern holds beyond our case study. We call attention to destination migration policies as a source of resentment among domestic audiences, which can be capitalised by new populisms in the region.