bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid Access to Divergent Fused Polycycles Via One‐Pot A3 Coupling and Intramolecular Diels‐Alder Reaction
Authors: Narra Rajashekar Reddy , Unnithan Vignesh Gopalakrishnan , Liu Yifan , Guo Zhihong 
Published: May 2024

AbstractDivergent nitrogen‐containing fused polycyclic ring systems are constructed from simple starting materials via a one‐pot aldehyde‐alkyne‐amine (A3) coupling and intramolecular Diels‐Alder reaction. This domino reaction directly furnishes linear 5/5/5 and 5/5/6, or nonlinear 5/5/6/5, polycyclic rings containing an oxa‐bridged fused 5/5 bicycle and a 1,6‐enyne substructure. One‐step derivation of the oxa‐bridged 5/5 bicycle leads to a polyfunctionalized 5/5 bicycle with tetrahydrofuran fused back‐to‐back to pyrroline or a 6/5 bicycle with the hexahydro‐1H‐isoindole structure, while cycloisomerizing the enyne substructure adds an extra fused 5‐membered ring to afford functionalized linear 5/5/5/5 or 5/5/5/5/5 fused ring systems from selected substrates. In addition, the one‐pot product can be designed so that the alkyne moiety is hydroalkoxylated to form an additional heterocyle in a linear 5/5/5/6 or nonlinear 5/5/6/5/5 ring system. This diversity‐oriented synthetic approach thus allows rapid access to an under‐explored structural space for discovery of new biological or non‐biological activities or functions.
Nature Products Chlorophyll Derivatives for NIR‐II Fluorescence Bioimaging and Plant‐Imaging
Authors: Chen Kaixin , Shi Hui , Li Lei , Yang Mao , Qian Kun , Xu Wen , Qu Chunrong , Cheng Zhen 
Published: May 2024

AbstractThe second near‐infrared window (NIR‐II, 1000–1700 nm) fluorescence imaging has attracted significant attention in research fields because of its unique advantages compared with conventional optical windows (400–900 nm). A variety of NIR‐II fluorophores have been actively studied because they serve as a key component of fluorescence imaging. Among them, organic small molecule NIR‐II fluorophores display outstanding imaging performance and many advantages, but types of small molecule NIR‐II fluorophores with high biocompatibility are still quite limited. Novel molecular scaffolds based NIR‐II dyes are highly desired. Herein, we hypothesized that chlorophyll is a new promising molecular platform for discovery NIR‐II fluorophores. Thus, seven derivatives of derivatives were selected to characterize their optical properties. Interestingly, six chlorophyll derivatives displayed NIR‐II fluorescence imaging capability. This characteristic allowed the successful NIR‐II imaging of green leaves of various plants. Furthermore, most of these fluorophores showed capacity to monitor viscosity change because of their sensitive for viscosity. For demonstration of its biomedical applications, these probes were successfully used for NIR‐II fluorescence‐guided surgical resection of lymph nodes. In summary, chlorophylls are novel valuable tool molecules for NIR‐II fluorescence imaging and have potential to expand their applications in biomedical field and plant science.
Chirality in electromagnetic radiation from relativistic electrons
Authors: Katoh Masahiro , Fujimoto Masaki , Salehi Elham , Hosaka Masahito , Kawaguchi Hideki 
Published: May 2024

AbstractElectrons in circular motion emit electromagnetic radiation and lose their energy and angular momentum, both of which are carried away by the radiation field. Electromagnetic radiation from such electrons is not only circularly polarized but also, in general, possessing helical phase structure, the former of which corresponds to spin angular momentum and the latter orbital angular momentum. Based on the classical electrodynamics, we show that the chiral topological property related to the orbital angular momentum arises from deformation of the electromagnetic field due to the relativistic effect.
Next‐generation energy‐efficient optical networking: DQ‐RGK algorithm for dynamic quality of service and adaptive resource allocation
Authors: Swamidoss Mathumohan , Samiayya Duraimurugan , Gunasekar Manikandan 
Published: May 2024

SummaryIn green optical networking, designing an adaptive energy‐saving scheme plays a vital role, in optimizing energy consumption by dynamically adjusting resources based on network traffic and environmental conditions, to a more sustainable and efficient optical communication infrastructure. Traditional methods in optical networking face challenges such as static resource allocation, limited adaptability, inefficient power usage, environmental insensitivity, and scalability issues. Therefore this article proposed a novel method named Dynamic Quality of Service based Random update Genghis Khan (DQ‐RGK) algorithm, the proposed model can tackle the abovementioned complexities. In this study, cluster head dynamic placement is utilized to optimize the network's performance by adapting the placement of cluster heads to the current topology, load distribution, and energy levels in the network nodes. Additionally, Dynamic Quality of Service (QoS) is employed to respond dynamically to changes in network conditions, adapting to varying traffic patterns and resource availability. In this work, the Genghis Khan Shark optimization with a random update strategy is implemented for hyperparameter optimization to enhance the performance of the DQ‐RGK method. The DQ‐RGK adjusts the parameters of QoS in real‐time, and this ensures that network resources based on the requirements changed and priorities of applications, which ultimately optimizes performance and enhances user experience. By dynamically assigning and reallocating resources based on the current demand the algorithm enhances overall network efficiency and reduces energy consumption. Then, this work analyzes the experimental results, where some evaluation measures estimate the DQ‐RGK method's performance. Routing efficiency, latency, scalability, spectral efficiency, Packet Delivery Ratio, throughput, network lifetime, energy consumption, jitter, and energy consumption are the measures employed by the DQ‐RGK model. In The results, other routing models that do not provide efficiency are utilized, a comparison of these other routing models is represented in results. The overall DQ‐RGK model's effectiveness is represented in the experimental results and its effectiveness is greater among other methods.
Seamless multi‐mode switching controller of four‐switch buck–boost converter based on integrated natural trajectory method
Authors: Chen Zhangyong , Liu Haifeng , Chen Yong , Tang Weihan , Liu Yunyan 
Published: May 2024

SummaryWith the characteristics of high efficiency and high power density, the four switch buck–boost (FSBB) converter is widely used in electric vehicles, direct current microgrids, and so forth. However, how to achieve smooth switching between different modes of FSBB has always been a hot issue in the theoretical and engineering fields. In this paper, considering the dynamic performance and output voltage or inductance current deviation, a control algorithm with integrated natural trajectory method is designed to realize the switching of different modes of FSBB converter. The proposed control algorithm is based on the theory of large signal natural locus and average natural locus. The normalized phase locus of inductance current and output voltage divides the phase plane into five regions and performs large signal or average switching operations in different regions. Theoretical analysis shows that the proposed control algorithm can achieve the balance between the dynamic performance and output voltage or inductance current deviation of FSBB converter in different mode switching. Finally, the performance of the proposed control algorithm is verified by experiments results.
Effect of a generalist mesopredator on modular and unitary sessile prey associated with a foundation species
Authors: Chava Alexandra , Artemieva Anna , Yakovis Eugeniy 
Published: May 2024

AbstractUnitary and modular sessile organisms both dominate in marine benthic communities, commonly preyed upon by the same generalist predators. The differences between unitary and modular defensive strategies may underlie the ways generalist predators control community structure, but this has never been empirically examined. We hypothesize that the individual size of an omnivorous mesopredatory shrimp affects the relative vulnerability of unitary and modular prey and hence translates into community structure. In a short‐term laboratory microcosm experiment, we assessed the effect of the shrimp individual size on an epibiotic assemblage of red algae blades initially dominated by three species of modular bryozoans and a unitary serpulid tubeworm. We found that the individual size of a shrimp determines its effect on the prey community composition. Large shrimp stronger than small shrimp increased the proportion of unitary tubeworms among the epibionts surviving predation. While large shrimp reduced the proportions of all the three dominant bryozoan species, small shrimp, in contrast, mostly increased the proportion of a bryozoan species with the smallest modules and largest colonies. This bryozoan, like the tubeworms, demonstrated a higher survival rate with larger individual (colony) size. Yet, against large shrimp this bryozoan was outperformed by the largest tubeworms almost immune to predation. Partial predation by small shrimp modestly improved survival of the largest bryozoan colonies. Thus, relative vulnerability of unitary and modular prey is determined by the predator individual size. Our findings clarify the complex way the size structures of generalist consumers and their prey shape communities by affecting the species‐specific relative performance of modular and unitary organisms. The demography of a foundation species and the competitive hierarchy can have additional effects by altering the balance of predation and competition.
Predicting heart failure symptoms from the apnoea–hypopnoea index determined by full‐ night polysomnography
Authors: Ikeda Takeshi , Kubota Yoshiaki , Inami Toru , Seino Yoshihiko , Asai Kuniya 
Published: May 2024

AbstractAimsSleep‐disordered breathing (SDB) is closely related to cardiovascular diseases. The higher the apnoea–hypopnoea index (AHI), the higher the prevalence of cardiovascular diseases. Despite these findings suggesting a close link between SDB and heart failure, the relationship between the severity of SDB and the onset of heart failure symptoms in individuals without apparent heart failure symptoms (Heart Failure Stage A + B) remains poorly understood.Methods and resultsBetween December 2010 and June 2017, we conducted full‐night polysomnography (PSG) at the Nippon Medical School Chiba Hokusoh Hospital, extracting patients who were at risk of heart failure (Stage A or B in the Heart Failure Guidelines). Using a median cut‐off of AHI ≥ 41.6 events/hour, we divided the patients into two groups and examined the composite endpoint of all‐cause mortality plus hospitalization due to heart failure as the primary endpoint. We included 230 patients (mean age 63.0 ± 12.5 years, 78.3% males) meeting the selection criteria. When comparing the two groups, those with AHI < 41.6 events/hour (L group, n = 115) and those with AHI ≥ 41.6 events/hour (H group, n = 115), the H group had higher body mass index and higher serum triglyceride, and lower the frequency of acute coronary syndrome and lower estimated glomerular filtration rate than did the L group, but no other patient characteristics differed significantly. The H group had a significantly higher incidence of the composite endpoint than did the L group (10.6% vs. 2.6%, P = 0.027). Factors associated with the composite endpoint were identified through multivariate analyses, with AHI, haemoglobin, and left atrial dimension emerging as significant factors (hazard ratio [HR] = 1.02, 95% confidence interval [CI] = 1.00–1.04, P = 0.024; HR = 0.71, 95% CI = 0.54–0.94, P = 0.017; and HR = 1.10, 95% CI = 1.03–1.18, P = 0.006, respectively). Conversely, the minimum SpO2 during PSG (<80%) was not associated with the composite endpoint.ConclusionsIn patients with SDB who are at risk of heart failure, severe SDB is associated with a high risk of all‐cause mortality and the development of heart failure. Additionally, combining cardiac echocardiography and PSG data may improve risk stratification, offering potential assistance for early intervention. Further examination with a validation cohort is necessary.
Development of Configurationally Labile Biaryl Reagents for Atropisomer Synthesis
Authors: Wu Changhui , Jin Yang , Zhang Xiaoyuan , Gao Ruiqi , Dou Xiaowei 
Published: May 2024

AbstractAxially chiral biaryl scaffolds are important in pharmaceuticals, natural products, and asymmetric synthesis. Atroposelective ring‐opening of configurationally labile biaryl reagents via dynamic kinetic asymmetric transformation provides a valuable approach to access axially chiral biaryl atropisomers. This review summarizes seminal contributions and recent advancements on this topic based on the use of different types of configurationally labile biaryl reagents.
A group key agreement protocol for Vanet based on Chinese remainder theorem and blockchain
Authors: Xiao Haitao , He An 
Published: May 2024

AbstractVehicular ad hoc Network (VANET) is a wireless self‐organizing network for obtaining information about road conditions, vehicle speed, vehicle location and traffic congestion. Traditional key negotiation protocols create many problems when dealing with a group of vehicles that need to communicate over a public channel. For example, traditional key negotiation protocols rely too much on the participation of trusted institutions and suffer from a single point of failure. Meanwhile, group session key negotiation is usually inefficient with high computational cost and communication overhead. To solve these problems, this paper proposes a blockchain‐based Chinese Remainder Theorem (CRT) VANET group key agreement. In addition, the protocol supports dynamic management of vehicles, including joining and exit. Formal security proofs show that our solution satisfies basic security requirements. Experiments using ProVerif show that the protocol functions properly even under many active and passive attacks, such as eavesdropping attacks. Performance analysis shows that the protocol is more efficient in the face of multi‐vehicle communication, in particular by reducing the computational cost by up to 75% and the communication overhead by up to 66%.
Changes in urinary metabolomic profile show the effectiveness of a nutritional intervention in children 6–12 years old: The ALINFA study
Authors: Andueza Naroa , Muñoz‐Prieto David , Romo‐Hualde Ana , Cuervo Marta , Navas‐Carretero Santiago 
Published: May 2024

AbstractDiet plays an essential role in health and disease. Therefore, its determination is an important component of many investigations. The aim of the study was to evaluate the effect of a nutritional intervention on the urinary metabolome in children aged 6–12 years. Also, it was intended to identify biomarkers of diet quality and dietary intake. A 2‐month, randomized, controlled, parallel trial was conducted in Spanish children. The analyses focused on the ALINFA group, which followed a full‐fixed meal plan including healthy products, ready‐to‐eat meals, and healthy recipes. Diet quality was assessed by the KIDMED index and dietary intake by a food frequency questionnaire. Untargeted metabolomic analysis on urine samples was carried out, and multivariate analyses were performed for pattern recognition and characteristic metabolite identification. PLS‐DA and Volcano plot analyses were performed to identify the discriminating metabolites of this group. 12 putative metabolites were found to be the most relevant to this intervention. Most of them were products derived from protein and amino acid metabolism (N‐Ribosylhistidine, indolacrylic acid, and peptides) and lipid metabolism (3‐oxo‐2‐pentylcyclopentane‐1‐hexanoic acid methyl, Suberoyl‐L‐carnitine, and 7‐Dehydrodichapetalin E). All these metabolites decreased after the intervention, which was mainly associated with a decrease in the consumption of fatty meat and total fat, especially saturated fat. In turn, N‐Ribosylhistidine and Suberoyl‐L‐carnitine were negatively associated with diet quality, as well as able to predict the change in KIDMED index. In conclusion, the changes observed in urinary metabolome demonstrate the effectiveness of the ALINFA nutritional intervention.
Identifying genes associated with disease outcomes using joint sparse canonical correlation analysis—An application in renal clear cell carcinoma
Authors: Dutta Diptavo , Sen Ananda , Satagopan Jaya M. 
Published: May 2024

AbstractSomatic changes like copy number aberrations (CNAs) and epigenetic alterations like methylation have pivotal effects on disease outcomes and prognosis in cancer, by regulating gene expressions, that drive critical biological processes. To identify potential biomarkers and molecular targets and understand how they impact disease outcomes, it is important to identify key groups of CNAs, the associated methylation, and the gene expressions they impact, through a joint integrative analysis. Here, we propose a novel analysis pipeline, the joint sparse canonical correlation analysis (jsCCA), an extension of sCCA, to effectively identify an ensemble of CNAs, methylation sites and gene (expression) components in the context of disease endpoints, especially tumor characteristics. Our approach detects potentially orthogonal gene components that are highly correlated with sets of methylation sites which in turn are correlated with sets of CNA sites. It then identifies the genes within these components that are associated with the outcome. Further, we aggregate the effect of each gene expression set on tumor stage by constructing “gene component scores” and test its interaction with traditional risk factors. Analyzing clinical and genomic data on 515 renal clear cell carcinoma (ccRCC) patients from the TCGA‐KIRC, we found eight gene components to be associated with methylation sites, regulated by groups of proximally located CNA sites. Association analysis with tumor stage at diagnosis identified a novel association of expression of ASAH1 gene trans‐regulated by methylation of several genes including SIX5 and by CNAs in the 10q25 region including TCF7L2. Further analysis to quantify the overall effect of gene sets on tumor stage, revealed that two of the eight gene components have significant interaction with smoking in relation to tumor stage. These gene components represent distinct biological functions including immune function, inflammatory responses, and hypoxia‐regulated pathways. Our findings suggest that jsCCA analysis can identify interpretable and important genes, regulatory structures, and clinically consequential pathways. Such methods are warranted for comprehensive analysis of multimodal data especially in cancer genomics.
An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment
Authors: Schaupp Christopher M. , Byrne Gregory , Chan Manli , Haggard Derik E. , Hazemi Monique , Jankowski Mark D. , LaLone Carlie A. , LaTier Andrea , Mattingly Kali Z. , Olker Jennifer H. , Renner James , Sharma Bhaskar , Villeneuve Daniel L. 
Published: May 2024

Abstract
Biological Evaluations support Endangered Species Act (ESA) consultation with the US Fish and Wildlife Service and National Marine Fisheries Service by federal action agencies, such as the USEPA, regarding impacts of federal activities on threatened or endangered species. However, they are often time-consuming and challenging to conduct. The identification of pollutant benchmarks or guidance to protect taxa for states and tribes when USEPA has not yet developed criteria recommendations is also of importance to ensure a streamlined approach to Clean Water Act program implementation. Due to substantial workloads, tight regulatory timelines, and the often-protracted length of ESA consultations, there is a need to streamline the development of biological evaluation toxicity assessments for determining the impact of chemical pollutants on ESA-listed species. Moreover, there is limited availability of species-specific toxicity data for many contaminants, further complicating the consultation process. New approach methodologies are being increasingly used in toxicology and chemical safety assessment to rapidly and cost-effectively provide data that can fill gaps in hazard and/or exposure characterization. Here, we present the development of an automated computational pipeline—RASRTox (Rapidly Acquire, Score, and Rank Toxicological data)—to rapidly extract and categorize ecological toxicity benchmark values from curated data sources (ECOTOX, ToxCast) and well-established quantitative structure–activity relationships (TEST, ECOSAR). As a proof of concept, points-of-departure (PODs) generated in RASRTox for 13 chemicals were compared against benchmark values derived using traditional methods—toxicity reference values (TRVs) and water quality criteria (WQC). The RASRTox PODs were generally within an order of magnitude of corresponding TRVs, though less concordant compared with WQC. The greatest utility of RASRTox, however, lies in its ability to quickly and systematically identify critical studies that may serve as a basis for screening value derivation by toxicologists as part of an ecological hazard assessment. As such, the strategy described in this case study can potentially be adapted for other risk assessment contexts and stakeholder needs. Integr Environ Assess Manag 2024;20:2203–2217. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Applying Neural ODEs to Derive a Mechanism‐Based Model for Characterizing Maturation‐Related Serum Creatinine Dynamics in Preterm Newborns
Authors: Bräm Dominic Stefan , Koch Gilbert , Allegaert Karel , van den Anker John , Pfister Marc 
Published: May 2024

AbstractSerum creatinine in neonates follows complex dynamics due to maturation processes, most pronounced in the first few weeks of life. The development of a mechanism‐based model describing complex dynamics requires high expertise in pharmacometric (PMX) modeling and substantial model development time. A recently published machine learning (ML) approach of low‐dimensional neural ordinary differential equations (NODEs) is capable of modeling such data from newborns automatically. However, this efficient data‐driven approach in itself does not result in a clinically interpretable model. In this work, an approach to deriving an interpretable model with reasonable PMX‐type functions is presented. This “translation” was applied to derive a PMX model for serum creatinine in neonates considering maturation processes and covariates. The developed model was compared to a previously published mechanism‐based PMX model whereas both models had similar mechanistic structures. The developed model was then utilized to simulate serum creatinine concentrations in the first few weeks of life considering different covariate values for gestational age and birth weight. The reference serum creatinine values derived from these simulations are consistent with observed serum creatinine values and previously published reference values. Thus, the presented NODE‐based ML approach to model complex serum creatinine dynamics in newborns and derive interpretable, mathematical‐statistical components similar to those in a conventional PMX model demonstrates a novel, viable approach to facilitate the modeling of complex dynamics in clinical settings and pediatric drug development.