bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural and biochemical characterization of the C‐terminal region of the human RTEL1 helicase
Authors: Cortone Giuseppe , Graewert Melissa A. , Kanade Manil , Longo Antonio , Hegde Raghurama , González‐Magaña Amaia , Chaves‐Arquero Belén , Blanco Francisco J. , Napolitano Luisa M. R. , Onesti Silvia 
Published: August 2024

AbstractRTEL1 is an essential DNA helicase which plays an important role in various aspects of genome stability, from telomere metabolism to DNA replication, repair and recombination. RTEL1 has been implicated in a number of genetic diseases and cancer development, including glioma, breast, lung and gastrointestinal tumors. RTEL1 is a FeS helicase but, in addition to the helicase core, it comprises a long C‐terminal region which includes a number of folded domains connected by intrinsically disordered loops and mediates RTEL1 interaction with factors involved in pivotal cellular pathways. However, information on the architecture and the function of this region is still limited. We expressed and purified a variety of fragments encompassing the folded domains and the unstructured regions. We determined the crystal structure of the second repeat, confirming that it has a fold similar to the harmonin homology domains. SAXS data provide low‐resolution information on all the fragments and suggest that the presence of the RING domain affects the overall architecture of the C‐terminal region, making the structure significantly more compact. NMR data provide experimental information on the interaction between PCNA and the RTEL1 C‐terminal region, revealing a putative low‐affinity additional site of interaction. A biochemical analysis shows that the C‐terminal region, in addition to a preference for telomeric RNA and DNA G‐quadruplexes, has a high affinity for R‐loops and D‐loops, consistent with the role played by the RTEL1 helicase in homologous recombination, telomere maintenance and preventing replication‐transcription conflicts. We further dissected the contribution of each domain in binding different substrates.
An atlas of caspase cleavage events in differentiating muscle cells
Authors: Gomez‐Cardona Erik , Dehkordi Mahshid H. , Van Baar Kolden , Vitkauskaite Aiste , Julien Olivier , Fearnhead Howard O. 
Published: August 2024

AbstractExecutioner caspases, such as caspase‐3, are known to induce apoptosis, but in other contexts, they can control very different fates, including cell differentiation and neuronal plasticity. While hundreds of caspase substrates are known to be specifically targeted during cell death, we know very little about how caspase activity brings about non‐apoptotic fates. Here, we report the first proteome identification of cleavage events in C2C12 cells undergoing myogenic differentiation and its comparison to undifferentiated or dying C2C12 cells. These data have identified new caspase substrates, including caspase substrates specifically associated with differentiation, and show that caspases are regulating proteins involved in myogenesis in myotubes, several days after caspase‐3 initiated differentiation. Cytoskeletal proteins emerged as a major group of non‐apoptotic caspase substrates. We also identified proteins with well‐established roles in muscle differentiation as substrates cleaved in differentiating cells.
Geometric descriptors for beta turns
Authors: Newell Nicholas E. 
Published: August 2024

AbstractBeta turns, in which the protein backbone abruptly changes direction over four amino acid residues, are the most common type of protein secondary structure after alpha helices and beta sheets and play key structural and functional roles. Previous work has produced classification systems for turn geometry at multiple levels of precision, but these operate in backbone dihedral‐angle (Ramachandran) space, and the absence of a local Euclidean‐space coordinate system and structural alignment for turns, or of any systematic Euclidean‐space characterization of turn backbone shape, presents challenges for the visualization, comparison and analysis of the wide range of turn conformations and the design of turns and the structures that incorporate them. This work derives a turn‐local coordinate system that implicitly aligns turns, together with a set of geometric descriptors that characterize the bulk BB shapes of turns and describe modes of structural variation not explicitly captured by existing systems. These modes are shown to be meaningful by the demonstration of clear relationships between descriptor values and the electrostatic energy of the beta‐turn H‐bond, the overrepresentations of key side‐chain motifs, and the structural contexts of turns. Geometric turn descriptors complement Ramachandran‐space classifications, and they can be used to select turn structures for compatibility with particular side‐chain interactions or contexts. Potential applications include protein design and other tasks in which an enhanced Euclidean‐space characterization of turns may improve understanding or performance. The web‐based tools ExploreTurns, MapTurns, and ProfileTurn, available at www.betaturn.com, incorporate turn‐local coordinates and turn descriptors and demonstrate their utility.
A novel antifungal peptide, SP1.2, from Rhodopseudomonas palustris against the rice blast pathogen
Authors: Wu Xiyang , Qin Yingfei , Li Chenggang , Zhang Xin , Tan Xinqiu , Liu Yong , Chen Yue , Zhang Deyong 
Published: August 2024

AbstractBACKGROUNDRice blast has a significant detrimental impact on rice yields, so developing efficient biological control technologies is an effective means for rice blast prevention and control. The GroEL protein has proven to be effective at preventing and managing the pathogenicity of rice blast.RESULTSHere, we analyzed the amino acid sequence of the GroEL protein and synthesized the ‘60 kDa chaperonin signature’ (350–373 amino acids) peptide SP1.2, which has potent antifungal activity. Notably, the SP1.2 peptide exhibited potent fungicidal activity against Magnaporthe oryzae, effectively inhibiting appressorium germination. Electron microscopy revealed that SP1.2 disrupted the fungal plasma membrane and bound to multiple bioactive phosphoinositides in vitro, triggering the production of reactive oxygen species. Furthermore, it also caused an increase in the acetylation of M. oryzae and induced autophagy in cells. The spray application of SP1.2 significantly reduced the number of disease spots caused by the fungal pathogen M. oryzae in rice, enhancing the defense response of rice plants. Field trials showed that the control effect was 64.59% after spraying SP1.2.CONCLUSIONOur study illustrates the antifungal activity of the structurally unique SP1.2 peptide against plant fungal pathogens and paves the way for the future development of this class of peptides as antifungal agents. © 2024 Society of Chemical Industry.
Geniposide modulates GSK3β to inhibit Th17 differentiation and mitigate endothelial damage in intracranial aneurysm
Authors: Zhang Qian , Shi Lu‐Feng , Chen Run‐Dong , Zhao He‐He , Yu Cong , Wang Yi‐Rong , Lu Peng 
Published: August 2024

AbstractIntracranial aneurysm (IA) is a common cerebrovascular disease. Immune system disorders and endothelial dysfunction are essential mechanisms of its pathogenesis. This study aims to explore the therapeutic effect and mechanism of Geniposide (Gen) on IA, which has a protective impact on endothelial cells and cardiovascular and cerebrovascular diseases. IA mouse models were administered intraperitoneal injections of geniposide for 2 weeks following elastase injection into the right basal ganglia of the brain for intervention. The efficacy of Gen in treating IA was evaluated through pathological testing and transcriptome sequencing analysis of Willis ring vascular tissue. The primary mechanism of action was linked to the expression of GSK3β in Th17 cells. The percentage of splenic Th17 cell differentiation in IA mice was significantly inhibited by Gen. GSK3β/STAT3, and other pathway protein expression levels were also significantly inhibited by Gen. Additionally, TNF‐α and IL‐23 cytokine contents were significantly downregulated after Gen treatment. These results indicated that Gen significantly inhibited the percentage of Th17 cell differentiation, an effect that was reversed upon overexpression of the GSK3B gene. Furthermore, Gen‐treated, Th17 differentiation‐inducing cell‐conditioned medium significantly up‐regulated the expression of tight junction proteins ZO‐1, Occludin, and Claudin‐5 in murine aortic endothelial cells. Administering the GSK3β inhibitor Tideglusib to IA mice alleviated the severity of IA disease pathology and up‐regulated aortic tight junction protein expression. In conclusion, Gen inhibits Th17 cell differentiation through GSK3β, which reduces endothelial cell injury and up‐regulates tight junction protein expression.
Machine learning methods for compound annotation in non‐targeted mass spectrometry—A brief overview of fingerprinting, in silico fragmentation and de novo methods
Authors: Russo Francesco F. , Nowatzky Yannek , Jaeger Carsten , Parr Maria K. , Benner Phillipp , Muth Thilo , Lisec Jan 
Published: August 2024

Non‐targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance–based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field.In this work, we illustrate which ML‐based methods are available for compound annotation in non‐targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.
Online LC‐Orbitrap MS method for the rapid molecular characterization of dissolved organic matter
Authors: Li Yuguo , He Chen , Zhang Yahe , Shi Quan 
Published: August 2024

RationaleHigh‐resolution mass spectrometry (HRMS) combined with electrospray ionization (ESI) has been the most useful technique for molecular characterization of dissolved organic matter (DOM) derived from diverse sources. However, the comprehensive detection of DOM composition was hindered by ionization suppression observed in ESI sources. HRMS coupled with liquid chromatography (LC) is a potential tool for comprehensive molecular characterization of DOM.MethodsThe Suwannee River fulvic acids (SRFAs) and two DOM samples from seawater and refinery wastewater extracted by solid phase extraction (SPE) were analyzed by LC‐Orbitrap MS coupled with ESI. The mobile phases, solvent composition, and gradient in the LC‐Orbitrap MS analysis were optimized.ResultsThe number of detected molecular formulae of SRFAs by online LC‐Orbitrap MS was significantly increased by approximately 40% compared to direct injection. These additional detected compounds are mainly protein and lignin‐like compounds, with a low O/C ratio and high H/C ratio. For the SRFAs, the relative standard deviations (%) of reproducibility are 5.51, 2.33, 7.97, and 1.80 for average O/C, H/C, double bond equivalent, and modified aromaticity index, respectively.ConclusionsThis study proposed a simple and rapid method based on LC‐Orbitrap MS for an in‐depth analysis of the molecular composition of DOM, achieving a remarkable analysis time of only 5 min per sample. The rapid method provides a dependable and efficient approach for the molecular characterization of DOM, thereby advancing our comprehension and investigation of DOM across diverse ecosystems.
Squeezing Out Nanoparticles from Perovskites: Controlling Exsolution with Pressure
Authors: López‐García Andrés , Remiro‐Buenamañana Sonia , Neagu Dragos , Carrillo Alfonso J. , Serra José Manuel 
Published: August 2024

AbstractNanoparticle exsolution has emerged as a versatile method to functionalize oxides with robust metallic nanoparticles for catalytic and energy applications. By modifying certain external parameters during thermal reduction (temperature, time, reducing gas), some morphological and/or compositional properties of the exsolved nanoparticles can be tuned. Here, it is shown how the application of high pressure (<100 bar H2) enables the control of the exsolution of ternary FeCoNi alloyed nanoparticles from a double perovskite. H2 pressure affects the lattice expansion and the nanoparticle characteristics (size, population, and composition). The composition of the alloyed nanoparticles could be controlled, showing a reversal of the expected thermodynamic trend at 10 and 50 bar, where Fe becomes the main component instead of Ni. In addition, pressure drastically lowers the exsolution temperature to 300 °C, resulting in unprecedented highly‐dispersed and small‐sized nanoparticles with a similar composition to those obtained at 600 °C and 10 bar. The mechanisms behind the effects of pressure on exsolution are discussed, involving kinetic, surface thermodynamics, and lattice‐strain factors. A volcano‐like trend of the exsolution extent suggests that competing pressure‐dependent mechanisms govern the process. Pressure emerges as a new design tool for metallic nanoparticle exsolution enabling novel nanocatalysts and surface‐functionalized materials.
Ultralow Power, Cleft Size‐Adjustable and pH‐Sensitive Hyaluronic Acid (HA) Biodevices for Acid‐Sensing Ion Channels Emulation
Authors: Duan Xinqing , Li Lei , Peng Zehui , Wang Mingqiang , Liu Yanxin , Hsieh Dar‐Jen , Chang Kuan‐Chang 
Published: August 2024

AbstractThe burgeoning implantable biodevices have unlocked new frontiers in healthcare, promising personalized monitoring strategies tailored to specific needs. Herein, hyaluronic acid (HA) is harnessed to create fully biocompatible, acidity‐sensitivity and cleft‐adjustable neuromorphic devices. These HA‐biodevices exhibit remarkable sensitivity to pH variations, effectively mimicking biological acid‐sensing ion channels (ASICs) through protonation reactions between electronegative atoms and hydrogen ions, even at ultralow driving voltage (5 mV). They can monitor joint cartilage acidity by tracking changes in proton concentration and successfully diagnose the onset of arthritis. Furthermore, by adjusting the synaptic device's cleft distance, which determines responsiveness, power efficiency and plasticity, HA‐based neuromorphic devices can be tailored to meet the unique demands of various implantation sites, providing both high‐sensitivity and low‐heat dissipation, thus broadening their application scopes. Moreover, the HA‐biodevices maintain stable performance across various bending degrees, up to a curvature radius of 7.5 mm, with flexibility and deformation resilience enabling installation on joints of varying curvatures. The combination of all‐biocompatibility, high sensitivity, low heat dissipation, ultralow low power (2 pW), and extraordinary deformation tolerance paves the way for the development of versatile, multipurpose medical monitoring devices with immense potential in the field of healthcare.
Robust Sequence Design Space for the Isothermal Exponential Amplification of Short Oligonucleotides
Authors: Ang Yan Shan , Yung Lin‐Yue Lanry 
Published: August 2024

AbstractAdvances in isothermal amplification techniques have accelerated development in biosensing applications and the design of complex molecular devices. The exponential amplification reaction technique, or EXPAR, is uniquely positioned to process molecular information from short oligonucleotide strands (≈10 nucleotides length) typically encountered in molecular computing or microRNA detection. Despite its conceptual simplicity (requiring only a template strand and two enzymes), the issue of nonspecific background amplification has hindered broader adoption. In this work, a new system configuration is established at 37 °C to achieve significantly improved performance. Critical sequence motifs responsible for the excellent signal‐to‐background profile are identified and generalized as a universal adapter design framework. Orthogonal template sequences generated from the framework are implemented for a triplex reaction and successfully evaluated mixtures of multiple‐target inputs in a single‐step, one‐pot format without the need for exogenous agents.
Water‐Etched Porous Ti: Surface Manipulation of Ti Foam Fabricated by Liquid Metal Dealloying Technique
Authors: Yoon Kook Noh , Kato Hidemi , Park Eun Soo 
Published: August 2024

AbstractThe liquid metal dealloying (LMD) process enables the fabrication of porous metals with various chemical compositions. Despite its advantages, LMD still faces key challenges such as maintaining the high‐temperature molten metal bath for a prolonged time, avoiding the use of toxic etchants, and so on. To overcome these challenges, the study develops a water‐leachable and oxidation‐resistant alloy melt (AM) in Ca‐Mg binary system. Specifically, Ca72Mg28 eutectic AM is designed, which exhibits higher oxidation resistance and lower melting temperature compared to pure Mg, allowing LMD to be conducted in atmospheric conditions as well as temperatures >200 K lower. The AM also enables an innovative process to fabricate Ti foams with a hexagonal faceted surface structure by carefully manipulating the etching rate during the water etching process. This approach allows for the creation of foam with a surface area over 13% larger than that of foams with smooth surfaces via normal acid etching, potentially enhancing efficiency in applications such as electrodes for electrochemical systems or biomedical materials where increased cell adhesion can be beneficial. This study paves the way for efficiently manipulating the LMD process to fabricate metal foams with customized compositions and enhanced surface properties.
Guided and unguided approaches for quantum key distribution for secure quantum communication
Authors: Sihare Shyam R. 
Published: August 2024

AbstractThis research investigates the optimization of quantum key distribution for secure quantum communication. The paper conducts a systematic analysis of quantum error rates, transmission time, error correction rates, and the correlation between distance, time, and noise in quantum communication systems. The results reveal an inverse relationship between transmission time and distance, and demonstrate that quantum error rates are dependent on quantum noise. The research presents improved formulations for calculating the probability of success in quantum systems, taking into account the dynamic nature of success in quantum communication processes. The findings have significant implications for optimizing quantum communication channels and providing insights into strategies for enhancing reliability and mitigating errors. The article presents a new approach to classical cryptography that incorporates dynamic vulnerability scores that adapt to advancements in quantum computing. It addresses various challenges in quantum communication, such as signal strength, channel losses, regeneration criteria, and the placement of quantum repeaters. Additionally, the research introduces multi‐dimensional metrics for evaluating risks in quantum communication cybersecurity, laying the groundwork for future advancements. This paper improves understanding of quantum communication, cryptography, and cybersecurity, providing a strong foundation for future research and practical applications.
Optimization methods in water system operation
Authors: Becker Bernhard Peter Josef , Jagtenberg Caroline Jeanne , Horváth Klaudia , Mitchell Ailbhe , Rodríguez‐Sarasty Jesús Andrés 
Published: August 2024

AbstractOperational water management is a critical global challenge, and decision making can be improved by using mathematical optimization. This paper provides an overview of optimization techniques, both exact and heuristic, used in water management. It focuses on the use of optimization techniques in the short term: operational planning in reservoir management, control of open channels, hydropower scheduling, and operation of polder drainage pumps. Principles of model predictive control, methods for optimization under forecast uncertainty, and approaches for conflict resolution are explained with the help of educational examples and practical cases. Challenges and research questions to be addressed in the future are presented as an outlook.This article is categorized under:
Engineering Water > Methods
Science of Water > Water and Environmental Change
Water and Life > Conservation, Management, and Awareness
Confining strings in three-dimensional gauge theories beyond the Nambu-Gotō approximation
Authors: Caselle Michele , Magnoli Nicodemo , Nada Alessandro , Panero Marco , Panfalone Dario , Verzichelli Lorenzo 
Published: August 2024

Abstract
We carry out a systematic study of the effective bosonic string describing confining flux tubes in SU(N) Yang-Mills theories in three spacetime dimensions. While their low-energy properties are known to be universal and are described well by the Nambu-Gotō action, a non-trivial dependence on the gauge group is encoded in a series of undetermined subleading corrections in an expansion around the limit of an arbitrarily long string. We quantify the first two of these corrections by means of high-precision Monte Carlo simulations of Polyakov-loop correlators in the lattice regularization. We compare the results of novel lattice simulations for theories with N = 3 and 6 color charges, and report an improved estimate for the N = 2 case, discussing the approach to the large-N limit. Our results are compatible with analytical bounds derived from the S-matrix bootstrap approach. In addition, we also present a new test of the Svetitsky-Yaffe conjecture for the SU(3) theory in three dimensions, finding that the lattice results for the Polyakov-loop correlation function are in excellent agreement with the predictions of the Svetitsky-Yaffe mapping, which are worked out quantitatively applying conformal perturbation theory to the three-state Potts model in two dimensions. The implications of these results are discussed.