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Chronic inflammation is driven by proinflammatory cytokines such as interleukin 6 (IL-6), tumor necrosis factor-α (TNF-α), and chemokines, such as c-c motif chemokine ligand 2 (CCL2), CCL3, C-X-C motif chemokine ligand 2 (CXCL2), and CXCL10. Inflammatory processes of the central nervous system (CNS) play an important role in the pathogenesis of various neurological and psychiatric disorders like Alzheimer's disease, Parkinson's disease, and depression. Therefore, identifying novel anti-inflammatory drugs may be beneficial for treating disorders with a neuroinflammatory background. The G-protein-coupled receptor 55 (GPR55) gained interest due to its role in inflammatory processes and possible involvement in different disorders. This study aims to identify the anti-inflammatory effects of the coumarin-based compound KIT C, acting as an antagonist with inverse agonistic activity at GPR55, in lipopolysaccharide (LPS)-stimulated BV2 microglial cells in comparison to the commercial GPR55 agonist O-1602 and antagonist ML-193. All compounds significantly suppressed IL-6, TNF-α, CCL2, CCL3, CXCL2, and CXCL10 expression and release in LPS-treated BV2 microglial cells. The anti-inflammatory effects of the compounds are partially explained by modulation of the phosphorylation of p38 mitogen-activated protein kinase (MAPK), p42/44 MAPK (ERK 1/2), protein kinase C (PKC) pathways, and the transcription factor nuclear factor (NF)-κB, respectively. Due to its potent anti-inflammatory properties, KIT C is a promising compound for further research and potential use in inflammatory-related disorders. [ABSTRACT FROM AUTHOR]

The basic modules for materials research are systems for the design, synthesis, preparation, analysis, and application of materials and materials systems. To be efficient and produce findable, accessible, interoperable, and reusable (FAIR) data, state‐of‐the‐art materials research needs to consider the integration of research data management (RDM) workflows and, in the end, the implementation of process automation concepts for all parts of the main modules. Here, the state‐of‐the‐art methods of RDM in academia are described and a perspective on the future of digitalized molecular material systems workflows is given. The different elements of an integrated research data management strategy are described, and examples of automated processes are depicted. As such, the use of electronic lab notebooks for comprehensive documentation, the use of data‐integration and data‐conversion strategies, and the establishment of two platforms that enable the automated synthesis of chemical components for materials and the analysis of materials by electron microscopy, are highlighted. Two examples of beneficial effects of successful RDM strategies are presented, showing a sophisticated tool for data prediction based on machine learning and options for creating community‐driven databases by extracting and re‐using data from different scientific projects. [ABSTRACT FROM AUTHOR]

The development of new functional materials is crucial for addressing global challenges such as clean energy or the discovery of new drugs and antibiotics. Functional material systems are typically composed of functional molecular building blocks, organized across multiple length scales in a hierarchical order. The large design space allows for precise tuning of properties to specific applications, but also makes it time‐consuming and expensive to screen for optimal structures using traditional experimental methods. Machine learning (ML) models can potentially revolutionize the field of materials science by predicting chemical syntheses and materials properties with high accuracy. However, ML models require data to be trained and validated. Methods to automatically extract data from scientific literature make it possible to build large and diverse datasets for ML models. In this article, opportunities and challenges of data extraction and machine learning methods are discussed to accelerate the discovery of high‐performing functional material systems, while ensuring that the predicted materials are stable, synthesizable, scalable, and sustainable. The potential impact of large language models (LLMs) on the data extraction process are discussed. Additionally, the importance of research data management tools is discussed to overcome the intrinsic limitations of data extraction approaches. [ABSTRACT FROM AUTHOR]

Inflammation processes of the central nervous system (CNS) play a vital role in the pathogenesis of several neurological and psychiatric disorders like depression. These processes are characterized by the activation of glia cells, such as microglia. Clinical studies showed a decrease in symptoms associated with the mentioned diseases after the treatment with anti-inflammatory drugs. Therefore, the investigation of novel anti-inflammatory drugs could hold substantial potential in the treatment of disorders with a neuroinflammatory background. In this in vitro study, we report the anti-inflammatory effects of a novel hexacyclic peptide-peptoid hybrid in lipopolysaccharide (LPS)-stimulated BV2 microglial cells. The macrocyclic compound X15856 significantly suppressed Interleukin 6 (IL-6), tumor necrosis factor-α (TNF-α), c-c motif chemokine ligand 2 (CCL2), CCL3, C-X-C motif chemokine ligand 2 (CXCL2), and CXCL10 expression and release in LPS-treated BV2 microglial cells. The anti-inflammatory effects of the compound are partially explained by the modulation of the phosphorylation of p38 mitogen-activated protein kinases (MAPK), p42/44 MAPK (ERK 1/2), protein kinase C (PKC), and the nuclear factor (NF)-κB, respectively. Due to its remarkable anti-inflammatory properties, this compound emerges as an encouraging option for additional research and potential utilization in disorders influenced by inflammation, such as depression. [ABSTRACT FROM AUTHOR]

Background and Purpose: In macrophages, transient receptor potential vanilloid 2 (TRPV2) channel contributes to various cellular processes such as cytokine production, differentiation, phagocytosis and migration. Due to a lack of selective pharmacological tools, its function in immunological processes is not well understood and the identification of novel and selective TRPV2 modulators is highly desirable. Experimental Approach: Novel and selective TRPV2 modulators were identified by screening a compound library using Ca2+ influx assays with human embryonic kidney 293 (HEK293) cells heterologously expressing rat TRPV2. Hits were further characterized and validated with Ca2+ influx and electrophysiological assays. Phagocytosis and migration of macrophages were analysed and the contribution of TRPV2 to the generation of Ca2+ microdomains was studied by total internal reflection fluorescence microscopy (TIRFM). Key Results: The compound IV2‐1, a dithiolane derivative (1,3‐dithiolan‐2‐ylidene)‐4‐methyl‐5‐phenylpentan‐2‐one), is a potent inhibitor of heterologously expressed TRPV2 channels (IC50 = 6.3 ± 0.7 μM) but does not modify TRPV1, TRPV3 or TRPV4 channels. IV2‐1 also inhibits TRPV2‐mediated Ca2+ influx in macrophages. IV2‐1 inhibits macrophage phagocytosis along with valdecoxib and after siRNA‐mediated knockdown. Moreover, TRPV2 inhibition inhibits lipopolysaccharide‐induced migration of macrophages whereas TRPV2 activation promotes migration. After activation, TRPV2 shapes Ca2+ microdomains predominantly at the margin of macrophages, which are important cellular regions to promote phagocytosis and migration. Conclusions and Implications: IV2‐1 is a novel TRPV2‐selective blocker and underline the role of TRPV2 in macrophage‐mediated phagocytosis and migration. Furthermore, we provide evidence that TRPV2 activation generates Ca2+ microdomains, which may be involved in phagocytosis and migration of macrophages. [ABSTRACT FROM AUTHOR]

New oligomers based on quinoxaline units were successfully synthesized through multistep reactions using Wittig coupling, affording (E)‐(quinoxalin‐2‐yl)ethene oligomers. Diverse quinoxaline‐based phosphonium salts were designed and synthesized, enabling versatility and compatibility regarding the oligomer‐building process. The characterization of the oligomers showed excellent stereoisomer specificity, i.e., a fully E‐configurated conjugated π‐system. The oligomers' light absorption/emission profiles indicate potential properties for an application in materials science. [ABSTRACT FROM AUTHOR]

Research data management (RDM) is needed to assist experimental advances and data collection in the chemical sciences. Many funders require RDM because experiments are often paid for by taxpayers and the resulting data should be deposited sustainably for posterity. However, paper notebooks are still common in laboratories and research data is often stored in proprietary and/or dead‐end file formats without experimental context. Data must mature beyond a mere supplement to a research paper. Electronic lab notebooks (ELN) and laboratory information management systems (LIMS) allow researchers to manage data better and they simplify research and publication. Thus, an agreement is needed on minimum information standards for data handling to support structured approaches to data reporting. As digitalization becomes part of curricular teaching, future generations of digital native chemists will embrace RDM and ELN as an organic part of their research. [ABSTRACT FROM AUTHOR]

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Multidrug‐resistant (MDR) bacteria is a severe threat to public health. Therefore, it is urgent to establish effective screening systems for identifying novel antibacterial compounds. In this study, a highly miniaturized droplet microarray (DMA) based high‐throughput screening system is established to screen over 2000 compounds for their antimicrobial properties against carbapenem‐resistant Klebsiella pneumoniae and methicillin resistant Staphylococcus aureus (MRSA). The DMA consists of an array of hydrophilic spots divided by superhydrophobic borders. Due to the differences in the surface wettability between the spots and the borders, arrays of hundreds of nanoliter‐sized droplets containing bacteria and different drugs can be generated for screening applications. A simple colorimetric viability readout utilizing a conventional photo scanner is developed for fast single‐step detection of the inhibitory effect of the compounds on bacterial growth on the whole array. Six hit compounds, including coumarins and structurally simplified estrogen analogs are identified in the primary screening and validated with minimum inhibition concentration assay for their antibacterial effect. This study demonstrates that the DMA‐based high‐throughput screening system enables the identification of potential antibiotics from novel synthetic compound libraries, offering opportunities for development of new treatments against multidrug‐resistant bacteria. [ABSTRACT FROM AUTHOR]

The documentation and storage of experimental data is crucial in research data management and science in general. With regard to automated data curation and the generation of data for machine learning processes, the collection and sharing of machine‐readable data, including negative results, is a key step. The electronic laboratory notebook (ELN) Chemotion provides the possibility to share synthesis data with other scientists taking the mentioned aspects into account. In these guidelines, we offer general information on how to share data in Chemotion and present our sharing policy as a best practice example on how to use Chemotion's sharing functions in a working group with several group members on various hierarchy levels. [ABSTRACT FROM AUTHOR]

Keywords: Analytical chemistry; cheminformatics: data and standards; data standard; file format; mass spectrometry; NMR EN Analytical chemistry cheminformatics: data and standards data standard file format mass spectrometry NMR 725 736 12 08/09/22 20220601 NES 220601 Introduction The amount of research data is growing in all disciplines, and chemistry is no exception. The NMR record in NMReDATA format includes the instrument (raw) data, a SDFile and, since version 2, also spectral data in JCAMP format in a folder, which can be compressed in the zip format for data exchange. Data standards for NMR spectroscopy NMR is an indispensable analytical technique providing rich information on bonding and structure as well as molecule interaction and abundance of molecules in samples. Data formats for analytical data When developing infrastructures for chemistry, one of the major tasks is to adopt or define data models and formats for exchange, storage and archival of analytical data. [Extracted from the article]