bluuebunny/crossref_metadata_2025_split huggingface dataset:
Salidroside improves blood–brain barrier integrity and cognitive function in hypobaric hypoxia mice by inhibiting microglia activation through GSK3β
Authors: Zhang Xianxie , Zhang Huiting , Liu Zuoxu , Huang Tianke , Yi Ru , Ma Zengchun , Gao Yue 
Published: October 2024

AbstractSalidroside, an active component found in Rhodiola rosea L., has emerged as a potential therapeutic agent for the prevention and treatment of hypoxic brain injury, while the precise target and mechanism of salidroside were remain unclear. The study utilized techniques such as network pharmacology, transcriptome sequencing to investigate the mechanism and target of salidroside in regulating blood–brain barrier (BBB) function to protect hypoxic brain injury in vivo. Utilized macromolecular docking and molecular biology techniques to explore the molecular mechanism of salidroside in alleviating brain injury induced by hypoxia in BV2 cell model. The results show that salidroside alleviated the learning and memory dysfunction and pathological injury in mice exposed to hypobaric hypoxia, reduced brain water content and attenuate the inflammatory response and oxidative stress, effectively reversed S100β in serum and promoted the repair of BBB. GSK3β is an important therapeutic target of salidroside in the treatment of hypoxic cognitive impairment, and salidroside can specifically bind GSK3β in the ATP binding pocket, inducing the phosphorylation of GSK3β, targeting downstream Nrf‐2 to regulate microglia activity, promoting the accumulation of β‐catenin, thereby inhibiting microglial activation, improving the BBB integrity injury and achieving a neuroprotective effect. This study demonstrates that salidroside can inhibit the activation of microglia by inducing GSK3β phosphorylation, achieve neuroprotective effects and alleviate learning and memory dysfunction in hypobaric hypoxia mice. This study provides a theoretical basis for the development of salidroside and the clinical application of Rhodiola rosea L.
Artificial neural networks in automatic image classifications of cloud from ground‐based observations using deep learning models
Authors: Kopeć Szymon , Duniec Grzegorz , Bochenek Bogdan , Figurski Mariusz 
Published: October 2024

AbstractCloud classification is a critical task in meteorology, with applications in weather forecasting, climate modelling, and environmental monitoring. Traditionally, cloud observations are made visually by experienced observers, which can introduce human errors and inconsistencies. This study aims to develop accurate deep learning models for automated cloud classification from ground‐based images. A dataset of over 200,000 cloud photographs was collected from professional observers at meteorological stations of the Institute of Meteorology and Water Management–National Research Institute. The images were preprocessed and annotated with cloud type labels. Convolutional neural networks and transformer models were employed for feature extraction, combined with multilayer perceptrons for classification. Different architectures were explored, including ResNet, EfficientNet, Vision Transformers, and their variants. Hyperparameter tuning and data augmentation techniques like RandAugment were applied to improve generalisation. The best‐performing model achieved 97.4% accuracy for classifying four common cloud genera: cirrus, cumulus, stratus, and clear sky. Additional experiments classified up to 11 genera, with accuracy decreasing as complexity increased, due to data limitations. Error analysis revealed confusions between visually similar classes. While promising, limitations exist from using partial cloud views versus whole‐sky imagery. We start with four classes and end with 11 classes, progressively showing subsequent errors in the cloud genera classification process, something not presented in other publications. Future work involves collecting a more balanced dataset with standardised protocols. Integration of all‐sky cameras could help address current restrictions. This research demonstrates the viability of deep learning for automated cloud observation, with opportunities to advance meteorological applications through continued methodological refinement.
Captodative Versus Push‐Pull Aromatic Cyclopentadienyl Derivatives
Authors: Shainyan B. A. 
Published: October 2024

ABSTRACTThe problem of whether and how the captodative aromatic systems with the donor and acceptor substituents at the same carbon atom of the C=C bond can be more stable than the π‐conjugated push‐pull counterparts with the two substituents in the vicinal position is analyzed for cyclopentadienyl derivatives possessing an aromatic cyclopentadienyl ring. The analysis of electronic, magnetic, and structural criteria of aromaticity showed that among typical organic donors, such as amines NR3, ethers R2O, guanidine (NH2)2C=NH, siloxane O(SiH3)2, silatrane, the captodative isomers [cyclopentadienylium]−C(X+) = CH2 can be more stable than their push‐pull isomeric counterparts [cyclopentadienylium]−—CH=CH—X+. The largest energy difference in favor of the former was found to be ca. 13 kcal/mol for X = NH=C(NH2)2.
State Transfer in Noisy Modular Quantum Networks
Authors: Hahto Markku , Piilo Jyrki , Nokkala Johannes 
Published: October 2024

AbstractQuantum state transfer is the act of transferring quantum information from one system in a quantum network to another without physically transporting carriers of quantum information, but instead engineering a Hamiltonian such that the state of the sender is transferred to the receiver through the dynamics of the whole network. A generalization of quantum state transfer called quantum routing concerns simultaneous transfers between multiple pairs in a quantum network, imposing limitations on its structure. This study considers transfer of Gaussian states over noisy quantum networks with modular structure, which have been identified as a suitable platform for quantum routing. Two noise models are compared, affecting either the network topology or the network constituents, studying their effects on both the transfer fidelities and the network properties. The two models are found to affect different features of the network allowing for the identification and quantification of the noise. These features are then used as a guide toward different strategies for the compensation of the noise, and to examine how the compensation strategies perform. The results show that in general, modular networks are more robust to noise than monolithic ones.
Effects of Dietary Nitrate Supplementation on Physical Performance and Muscle Strength in Older People—A Systematic Review
Authors: Renji Rebecca , Robinson Sian M. , Witham Miles D. 
Published: October 2024

ABSTRACTBackgroundSarcopenia, the loss of muscle strength and mass with age, is a major cause of morbidity for older people. Dietary nitrate supplementation has been proposed as an intervention to improve skeletal muscle function via action as nitric oxide (NO) donors. However, the effect of nitrate supplementation on physical performance and muscle strength in older people is unclear. We aimed to systematically review evidence on whether dietary nitrate supplementation improves markers of muscle strength, muscle mass and physical performance in older people.MethodsWe conducted a systematic review of randomised controlled trials according to a prespecified protocol by two reviewers. We included interventional studies using dietary nitrate supplementation, mean participant age of >60 years, with or without muscle weakness. Outcomes of interest were physical performance, muscle strength and muscle mass. Risk of bias was assessed using a modified version of the Cochrane Risk of Bias tool. Results were grouped by intervention and outcome measures and were described by narrative synthesis.ResultsTwenty‐eight studies were included, with a size range of 8–72 participants. Intervention duration ranged from a single dose to 12 weeks. Seven studies were in healthy older people. Most studies had a high or unclear risk of bias; three had a low risk of bias. One‐hundred‐two outcomes were reported; 67 were related to physical performance, and 35 were related to muscle strength. No included study measured muscle mass. Thirty‐three outcomes showed significant improvement, two showed significant worsening and 67 showed no statistically significant difference. Meta‐analysis was not possible due to data heterogeneity. Subgroup analyses for different doses of nitrate (above or below 10 mmol nitrate per day), duration of treatment or specific commonly measured outcomes did not indicate any subgroup more likely to show positive results. The proportion of positive outcomes was similar in studies using beetroot extract, nitrate alone or exercise as a co‐intervention.ConclusionsCurrent evidence is insufficient to decide if dietary nitrate supplementation improves skeletal muscle function in older people. Future studies should be longer, larger and target older people with sarcopenia or frailty.
Node Centrality Inference via Hypothesis Testing
Authors: He Zengyou , Lou Jun , Liu Yan , Hu Lianyu , Jiang Mudi 
Published: October 2024

ABSTRACTCentral nodes, also known as vital or critical nodes, play a unique role in networks of various domains. To date, numerous centrality evaluation methods have been proposed to identify central nodes from different types of networks. However, most of existing methods did not address this issue from a rigorous significance testing perspective. As a result, it is hard for us to judge whether an identified central node is true or not and control the quality of reported nodes in a statistically sound manner. In this paper, we propose a centrality evaluation method based on hypothesis testing, where the test statistic is the degree sum of the neighbors of the node. We further derive an analytical p value and its upper bound under the Erdös–Rényi model, which can be employed as the centrality score for vital node recognition. To demonstrate the effectiveness of our method, extensive experiments are conducted on both simulated and real networks. The experimental results show that (1) our testing‐based centrality measure in terms of p value is capable of distinguishing central nodes from non‐central ones effectively and (2) our method is able to identify central nodes more accurately than those classic centrality measures and state‐of‐the‐art (SOTA) centrality evaluation methods.
Latent Archetypes of the Spatial Patterns of Cancer
Authors: Menezes Thaís Pacheco , Prates Marcos Oliveira , Assunção Renato , De Castro Mônica Silva Monteiro 
Published: October 2024

ABSTRACTThe cancer atlas edited by several countries is the main resource for the analysis of the geographic variation of cancer risk. Correlating the observed spatial patterns with known or hypothesized risk factors is time‐consuming work for epidemiologists who need to deal with each cancer separately, breaking down the patterns according to sex and race. The recent literature has proposed to study more than one cancer simultaneously looking for common spatial risk factors. However, this previous work has two constraints: they consider only a very small (2–4) number of cancers previously known to share risk factors. In this article, we propose an exploratory method to search for latent spatial risk factors of a large number of supposedly unrelated cancers. The method is based on the singular value decomposition and nonnegative matrix factorization, it is computationally efficient, scaling easily with the number of regions and cancers. We carried out a simulation study to evaluate the method's performance and apply it to cancer atlas from the USA, England, France, Australia, Spain, and Brazil. We conclude that with very few latent maps, which can represent a reduction of up to 90% of atlas maps, most of the spatial variability is conserved. By concentrating on the epidemiological analysis of these few latent maps a substantial amount of work is saved and, at the same time, high‐level explanations affecting many cancers simultaneously can be reached.
Low‐Temperature Solvothermal Synthesis of Triangular, Spherical, and Urchin‐Like ZnO
Authors: Kapusuz Yavuz Derya , El Accen Muhammed , Bedir Metin 
Published: October 2024

AbstractThis study explores the synthesis and characterization of ZnO particles with varying morphologies—triangular, spherical, and urchin‐like—that were produced through a simple, solvothermal process. The morphology, surface area, and photocatalytic performance of the ZnO particles could be customized by meticulously regulating the synthesis parameters, particularly the temperature and solvent. The findings indicated that all samples crystallized as pure wurtzite ZnO with a uniform crystallite size of 34.7 ± 1.8 nm and energy band gap of 3.29 eV. The spherical E‐200 particles, which exhibit the highest photocatalytic efficiency, achieved an average of 25.27 ± 5.88% methylene blue (MB) degradation after 24 h. These particles were distinguished by a significant surface area of 30.56 m2/g and an average pore size of 45 nm. Furthermore, all ZnO samples exhibited a significant adsorption capacity (≤ 20%) for MB under dark condition, underscoring their potential as effective adsorbents for environmental pollutants. These results emphasize the significance of precise synthesis and morphology control in the optimization of functional properties of ZnO for environmental remediation applications.
Preparation of Bio‐Orthogonal Self‐Cross‐Linked Arabinose Isomerase for Enzymatic Synthesis of ʟ‐Ribulose
Authors: Luo Houtian , Wu Shujiao , Luo Lingling , Pan Xiaoting , Xie Tian , Qiao Li 
Published: October 2024

Abstractʟ‐Ribulose is a bioactive molecule of significance that is present in various valuable chemical scaffolds. However, the synthesis of ʟ‐ribulose is limited by the high cost of enzyme biocatalyst. In this work, we leveraged the self‐coupling reactivity of SpyTag/SpyCatcher to aggregate the key arabinose isomerase (araA) for the enzymatic isomerization of ʟ‐arabinose to ʟ‐ribulose. The cross‐linking of SpyTag/SpyCatcher fused araA was simplified by performing in cell lysates without further purification. The resulting araA cross‐linked aggregates (araA‐CLEs) inherited their original activity well with 0.32 U·mg−1. Deep analysis of araA‐CLEs by Gaussian fitting indicated a little change in secondary structure, mainly focusing on α‐helix. The araA‐CLEs maintained 69.10% catalytic activity after six repeated uses in preparing ʟ‐ribulose. This one‐step cross‐linking and purification method contributed greatly to obtaining araA‐CLEs, thus, benefiting the full use of araA protein and saving costs for ʟ‐ribulose production.
High‐Performance Pure Polymer Electrolytes with Enhanced Ionic Conductivity for Room‐Temperature Applications
Authors: Zhang Yongquan , Chen Zengxu , Wang Jingshun , Fan Shuo , Zhang Tiandong , Zhang Changhai , Zhang Yue , Chi Qingguo 
Published: October 2024

AbstractAll‐solid‐state lithium metal batteries (ASSLMBs) are renowned for their high energy density and safety, positioning them as leading candidates for next‐generation energy storage solutions. In this study, pure polymer solid‐state electrolytes are developed using the solution casting method, optimized for room temperature operation. The base material, poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP), is enhanced with succinonitrile (SN) and polyacrylonitrile (PAN) to improve its electrochemical performance at room temperature. The optimized electrolyte, PSP‐0.05, demonstrated superior characteristics, including an ionic conductivity (σ) of 3.2 × 10−4 S cm−1 and a wide voltage window of up to 5 V. When integrated into full batteries, PSP‐0.05 exhibited exceptional performance in multiplicative cycling tests at room temperature, achieving discharge specific capacities of 132 and 113 mAh g−1 at 3 and 5 C rates, respectively. Additionally, long‐term cycling at 1 C rate resulted in an initial discharge‐specific capacity of 145.2 mAh g−1 with over 94.9% capacity retention after 1000 cycles. Given the simplicity of the preparation process and its impressive electrochemical properties, the PSP‐0.05 electrolyte holds significant potential for practical applications in safer ASSLMBs.
New Suggestion of Highly Durable Electrode Design for Ordered Mesoporous Ni–Mn Binary Transition Metal Oxide Anode Material in Lithium‐Ion Batteries
Authors: Kim Taewhan , Kim Kyoung Ho , Kim Hansol , Lee Wontae , Choi Woosung , Yoon Jaesang , Song Lianghao , Kim Ki Jae , Bulakhe Ravindra N. , Yoon Won‐Sub , Kim Ji Man 
Published: October 2024

AbstractAnode materials storing large‐scale lithium ions gradually decrease electrochemical performance due to severe volume changes during cycling. Therefore, there is an urgent need to develop anode materials with high electrochemical capacity and durability, without deterioration arising due to the volume changes during the electrochemical processes. To date, mesoporous materials have received attention as anode materials due to their ability to mitigate volume expansion, offer a short pathway for Li+ transport, and exhibit anomalous high capacity. However, the nano‐frameworks of transition metal oxide collapse during conversion reactions, demanding an improvement in nano‐framework structure stability. In this study, ordered mesoporous nickel manganese oxide (m‐NMO) is designed as an anode material with a highly durable nanostructure. Interestingly, m‐NMO showed better cycle performance and higher electrochemical capacity than those of nickel oxide and manganese oxide. Operando small‐angle X‐ray scattering and ex situ transmission electron microscopic results confirmed that the binary m‐NMO sustained a highly durable nanostructure upon cycling, unlike the single metal oxide electrodes where the mesostructures collapsed. Ex situ X‐ray absorption spectroscopy proved that nickel and manganese showed different electrochemical reaction voltages, and thus undergoes sequential conversion reactions. As a result, both elements can act as complementary nano‐propping buffers to maintain stable mesostructure.
A pH‐Sensitive Glucose Oxidase and Hemin Coordination Micelle for Multi‐Enzyme Cascade and Amplified Cancer Chemodynamic Therapy
Authors: Jiang Zhen , Li Jiexin , Liu Gengqi , Qiu Qian , Zhang Jingyu , Hao Minchao , Ren He , Zhang Yumiao 
Published: October 2024

AbstractChemodynamic therapy (CDT) is an emerging therapeutic paradigm for cancer treatment that utilizes reactive oxygen species (ROS) to induce apoptosis of cancer cells but few biomaterials have been developed to differentiate the cancer cells and normal cells to achieve precise and targeted CDT. Herein, a simple cascade enzyme system is developed, termed hemin–micelles–GOx, based on hemin and glucose oxidase (GOx)‐encapsulated Pluronic F127 (F127) micelles with pH‐sensitive enzymatic activities. Histidine‐tagged GOx can be easily chelated to hemin‐F127 micelles via the coordination of histidine and ferrous ions in the center of hemin by simple admixture in an aqueous solution. In tumor microenvironment (TME), hemin–micelles–GOx exhibits enhanced peroxidase (POD)‐like activities to generate toxic hydroxyl radicals due to the acidic condition, whereas in normal cells the catalase (CAT)‐like, but not POD‐like activity is amplified, resulting in the elimination of hydrogen peroxide to generate oxygen. In a murine melanoma model, hemin–micelles–GOx significantly suppresses tumor growth, demonstrating its great potential as a pH‐mediated enzymatic switch for tumor management by CDT.
Highly‐Branched PtCu Nanocrystals with Low‐Coordination for Enhanced Oxygen Reduction Catalysis
Authors: Zhang Shaohui , Liu Suying , Luo Juan , Gu Yuke , Liu Xuanzhi , Liu Feng , Tan Pengfei , Pan Jun 
Published: October 2024

AbstractLow‐coordination platinum‐based nanocrystals emanate great potential for catalyzing the oxygen reduction reactions (ORR) in fuel cells, but are not widely applied owing to poor structural stability. Here, several PtCu nanocrystals (PtCu NCs) with low coordination numbers were prepared via a facile one‐step method, while the desirable catalyst structures were easily obtained by adjusting the reaction parameters. Wherein, the Pt1Cu1 NCs catalyst with abundant twin boundaries and high‐index facets displays 15.25 times mass activity (1.647 A mgPt−1 at 0.9 VRHE) of Pt/C owing to the abundant effective active sites, low‐coordination numbers and appropriate compressive strain. More importantly, the core‐shell and highly developed dendritic structures in Pt1Cu1 NCs catalyst give it an extremely high stability with only 17.2% attenuation of mass activity while 61.1% for Pt/C after the durability tests (30 000 cycles). In H2‐O2 fuel cells, Pt1Cu1 NCs cathode also exhibits a higher peak power density and a longer‐term lifetime than Pt/C cathode. Moreover, theoretical calculations imply that the weaker adsorption of intermediate products and the lower formation energy barrier of OOH* in Pt1Cu1 NCs collaboratively boost the ORR process. This work offers a morphology tuning approach to prepare and stabilize the low‐coordination platinum‐based nanocrystals for efficient and stable ORR.
Charge‐Mediated Interactions Affect Enzymatic Reactions in Peptide Condensates
Authors: Harris Rif , Berman Nofar , Lampel Ayala 
Published: October 2024

AbstractBiomolecular condensates, formed through liquid‐liquid phase separation (LLPS), serve as enzymatic reaction centers in cells by increasing local concentrations of enzymes and substrates, thereby facilitating reaction kinetics and regulatory mechanisms. Inspired by these natural systems, synthetic condensates are being developed for diverse applications, including payload delivery, sensing, and as microreactors where enzymatic reaction kinetics can be modulated by factors like pH, viscosity, and enzyme‐substrate co‐localization. Here, we investigate how the physicochemical properties of enzymes and substrates influence condensate formation and function as microreactors. Focusing on cellulase and alkaline phosphatase, which differ in molecular weight and isoelectric point, we employed a minimalistic complex coacervation system of oppositely charged LLPS‐promoting peptides. Our findings show how electrostatic forces within condensates influence their role as microreactors. Specifically, the ability of condensates to encapsulate or exclude phosphatase, cellulase, and their substrates, which is pivotal for the regulation of reaction kinetics, is determined by the enzyme surface charge, substrate charge, and condensate charge stoichiometry. These results highlight the potential of utilizing electrostatic forces within condensates to modulate enzymatic reactions, providing critical insights for developing synthetic condensates as microreactors in biotechnology and materials science.
Medicinal management of rumen collapse in Bubalus bubalis
Authors: Yadav Annu , Singh Prem , Budhwar Anshul , Sehrawat Disha 
Published: October 2024

AbstractRumen collapse is a rare condition usually seen in cattle with severe primary inflammatory diseases. This case report describes 6‐year‐old pregnant buffalo brought to Large Animal Outpatient Medicine Unit at college hospital with history of prolonged inappetence, dark‐coloured urine and collapsed left paralumbar fossa and last three ribs. Clinical examination revealed no rumen movements along with abdominal ping upon simultaneous auscultation and percussion. Per rectal examination showed collapsed dorsal sac of the rumen and ventral displacement of left kidney into mid‐abdomen. Rumen fluid analysis revealed complete absence of protozoal motility and non‐significant alterations in haematological parameters. The buffalo was suspected to have rumen collapse based on clinical examination. Successful treatment involved administering normal saline, calcium salt and broad‐spectrum antibiotics. Following 15 days of therapy, rumen and ribs returned to their normal positions and animal resumed feeding. This is the first reported case of rumen collapse in buffaloes in India.