bluuebunny/crossref_metadata_2025_split huggingface dataset:
Field collections and environmental DNA surveys reveal topographic complexity of coral reefs as a predictor of cryptobenthic biodiversity across small spatial scales
Authors: Brodnicke O. B. , Jensen M. R. , Thomsen P. F. , Brorly T. , Andersen B. L. , Knudsen S. W. , Præbel K. , Brandl S. J. , Sweet M. J. , Møller P. R. , Worsaae K. 
Published: May 2024

AbstractCoral reefs represent some of the most biodiverse ecosystems in the world but are currently undergoing large‐scale degradation due to anthropogenic stressors. Such degradation usually begins with coral bleaching, and if the stress condition is inflicted for too long may eventually result in loss of structural complexity (or “flattening”) of the reef, dramatically changing habitat availability for reef‐associated fauna. Despite having been linked to important ecosystem functions, cryptobenthic organisms are often overlooked in ecological monitoring programs, and their microhabitat dependencies are poorly understood. Here, we combined collection‐based biodiversity monitoring techniques with five different environmental DNA (eDNA) sampling techniques (Reef water, sediment, crevice water, slurp gun, and bulk sediment) to survey cryptobenthic fishes and annelids on a Maldivian fringing coral reef. Collectively, 176 fish and 140 annelid taxa were detected with eDNA across 14 surveyed sites, more than doubling the reported annelid taxa in the region with 88 new occurrences. Water filtered near the reef structure revealed the highest species richness out of the five eDNA sampling techniques tested. Furthermore, we found correlations between fish species richness and topographic complexity for both collection‐ and eDNA‐based techniques. This suggests that detection by eDNA may be linked to site‐specific predictors and reveal community differences across small spatial scales (tens of meters). We also report that reef flattening (going from structural complex to less complex sites) can cause a 50% reduction in fish diversity and that cryptobenthic fish species richness was highly associated with branching corals. In contrast, annelid communities showed no clear correlations with environmental predictors, but co‐amplification of non‐target, non‐annelid taxa may have distorted such correlations if present. This suggest that the predictive powers of eDNA for environmental gradients may be dependent on the targeted taxa.
Intracellular complement and immunometabolism: The advantages of compartmentalization
Authors: King Ben C. , Blom Anna M. 
Published: May 2024

AbstractThe complement system is a proteolytic cascade triggered by pathogen and danger‐associated molecular patterns, with resultant outcomes of inflammation, cellular activation, and opsonization of material for removal by phagocytosis. While first discovered as an activity in serum, it is now recognized that complement components play important roles at local and individual cell‐intrinsic levels. In particular, apart from the extracellular serum activities of complement, it is now believed that complement also acts intracellularly, as part of a cellular signal transduction cascade that can stimulate cellular survival and activation, and individual immune cell phenotypes, via effects on cellular metabolism. This review will describe what is currently known about how complement functions in intracellular signal transduction, and outline the functional advantages of a compartmentalized and intracellular complement system.
Novel LAMC3 pathogenic variant enriched in Finnish population causes malformations of cortical development and severe epilepsy
Authors: Saarela Anni , Timonen Oskari , Kirjavainen Jarkko , Liu Yawu , Silvennoinen Katri , Mervaala Esa , Kälviäinen Reetta 
Published: May 2024

AbstractObjectiveRecessive LAMC3 mutations are recognized to cause epilepsy with cortical malformations characterized by polymicrogyria and pachygyria. The objective of this study was to describe the clinical picture and epilepsy phenotype of four patients with a previously undescribed LAMC3 variant.MethodsAll epilepsy patients treated in Kuopio Epilepsy Center (located in Kuopio, Finland) are offered the possibility to participate in a scientific study investigating biomarkers in epilepsy (Epibiomarker study). We have collected a comprehensive database of the study population, and are currently re‐evaluating our database regarding the patients with developmental and/or epileptic encephalopathy (DEE). If the etiology of epilepsy remains unknown in the clinical setting, we are performing whole exome sequencing to recognize the genetic causes.ResultsAmong our study population of 323 DEE patients we recognized three patients with similar homozygous LAMC3 c.1866del (p.(Phe623Serfs*10)) frameshift variant and one patient with a compound heterozygous mutation where the same frameshift variant was combined with an intronic LAMC3 c.4231‐12C>G variant on another allele. All these patients have severe epilepsy and either bilateral agyria‐pachygyria or bilateral polymicrogyria in their clinical MRI scanning. Cortical malformations involve the occipital lobes in all our patients. Epilepsy phenotype is variable as two of our patients have DEE with epileptic spasms progressing to Lennox–Gastaut syndrome and intellectual disability. The other two patients have focal epilepsy without marked cognitive deficit. The four patients are unrelated. LAMC3 c.1866del p.(Phe623Serfs*10) frameshift variant is enriched in the Finnish population.SignificanceOnly a few patients with epilepsy caused by LAMC3 homozygous or compound heterozygous mutations have been described in the literature. To our knowledge, the variants discovered in our patients have not previously been published. Clinical phenotype appears to be more varied than previously assumed and patients with a milder phenotype and normal cognition have probably remained unrecognized.
Performance study of low temperature air heated rock bed thermal energy storage system
Authors: Salehudress Zelalem M. , Habtu Nigus G. , Admasu Bimrew T. , Delele Mulugeta A. , Asemu Aynadis M. 
Published: May 2024

AbstractOne of the primary types of sensible heat storage systems in drying applications is the packed rock bed. However, to create large‐scale heat storage systems for industrial use, one must comprehend the hydrodynamic and effectiveness of the heat transport mechanism inside the bed. In this study, the thermal storage unit uses river rock as heat storage materials with equivalent particle diameters of 36 mm in bed 1 and 56 mm in bed 2. The rocks were stacked in a truncated cone‐shaped concrete wall section with an average diameter and depth of 1.1 m and 1.3 m, respectively and a volume of 2.32 m3. During the charging phase, two airflow configurations were used, one from the top with an air mass flow rate of 0.753 and 0.332 kg/m2‐s and the other from the bottom with an air mass flow rate of 0.955 kg/m2‐s. During the discharging phase, the entire flow configuration is from the bottom section. It was observed that the mass flow rate and particle equivalent diameter had an important effect on the thermal performance and behaviour of the rock bed during charging and discharging operations. Maximum efficiency was achieved with an airflow configuration provided from the bottom when charging at 0.955 kg/m2.s. Consequently, a sizable quantity of heat or energy (60 MJ) was retained. It was also observed that the relationship between air mass flow rate and particle size was significant, with smaller particles retaining more energy. When comparing bed 1 with bed 2 at this air mass flow rate, bed 1 stored 2.1 times more energy than bed 2. A wind tunnel experiment was used to measure the pressure drop in the packed rock bed. The pressure drop in the bed increases with an increase in particle Reynolds number and decreases with an increase in particle size. Rock bed heat transfer coefficient and Nusselt number were calculated using the correlation that has already been established in the literature smaller particles showed higher heat transfer coefficients and lower Nusselt numbers. This is due to the increase in particle‐to‐particle interaction and larger particle surface areas. For a given Reynolds number, the Nusselt number increases with the size of the rock particle.
Can digital M&A reduce the stock price crash risk?
Authors: Guan Jingyi , Wen Yunhui 
Published: May 2024

AbstractWith the rapid development of the digital economy, digital mergers and acquisitions (M&A) have become essential means for enterprises to acquire digital technologies and accelerate their digital transformation. This paper examines the impact of digital M&A on stock price crash risk using a sample of M&A transactions of China A‐share listed companies from 2010 to 2021. The results show that digital M&A can reduce stock price crash risk after M&A. Further discussions reveal that compared to non‐digital M&A, digital M&A has a better market effect, and the target firms of digital M&A generally are in different industries from the acquirers, have relatively low registered capital, have a shorter registration time, and have better financial performance. Mechanism tests indicate that during the transaction, digital M&A increases the probability of signing earnout contracts and reduces the cash payment ratio. After the transaction, digital M&A increases research and development (R&D) investment and improves R&D investment efficiency, ultimately reducing stock price crash risk. Cross‐sectional tests suggest that in situations with intense market competition, lower digitalization level of the acquirers, and higher business similarity between the acquirer and the target firm, digital M&A is more effective in reducing stock price crash risk. The findings enrich the research on the operational mechanisms and economic consequences of digital M&A, providing theoretical references for regulatory authorities to optimise M&A regulatory policies and for enterprises to assess the benefits and risks of digital M&A.
Denoising smooth‐detail representation of MRI‐SPECT fusion
Authors: Du Jiao , Cheng Zhun , Wang Yuangen , Li Weisheng 
Published: May 2024

AbstractFusing of brain imaging data is a hot task that has been previously approached by preserving saliency information from inputs to the output enhanced fused image. In this article, we present a method for calculating fused image from an anatomical image and a functional image, in which detail saliency information is preserved while suppressing noise. Our method is based on smooth‐detail representation used as a decomposition model scheme and based on denoising fusion rules to predict a fused version of the desired output. Unlike our previous approach, the method proposed in this article presents a smooth‐detail model for greyscale image with the extension a single‐channel to a three‐channel. We also adopt denoising method for map to construct the estimated fused image. The effectiveness of our method is proved in terms of analyzing noisy image, making comparison between proposed method and deep learning methods, and computing complexity of running time, showing better performance on denoising and preserving luminance saliency information.
Multidimensional perturbed consistency learning for semi‐supervised medical image segmentation
Authors: Yuan Enze , Zhao Bin , Qin Xiao , Ding Shuxue 
Published: May 2024

AbstractIn this article, we propose a novel multidimensional perturbed consistency network (MPCNet) for more accurate semi‐supervised medical image segmentation. Specifically, we develop a multidimensional perturbation by considering the noise itself, the target object and the overall spatial architecture. This type of perturbation can disrupt the propagation process of abstract features over a wide range, enabling the model to learn the distribution of comprehensive data. In addition, we design a shared encoder to extract multi‐scale features. After subjecting these features to multidimensional perturbation, a consistency constraint is applied between different results output by three independent decoders. This constraint aims to minimize the statistical differences between these results and effectively leverage unlabeled data. Experimental results on the public LA, Pancreas‐CT and ACDC datasets demonstrate that our method outperforms recent SOTA semi‐supervised learning methods in terms of various metrics. Our code is released publicly at https://github.com/yuanenze123/MPC-Net.
Generalizing Diffusion Tensor Imaging of the Physis and Metaphysis
Authors: Luo Katherine L. , Santos Laura , Tokaria Rumana , Jambawalikar Sachin , Duong Phuong T. , Raya José G. , Mostoufi‐Moab Sogol , Jaramillo Diego 
Published: May 2024

BackgroundCurrent methods to predict height potential are inaccurate. Predicting height by using MRI of the physeal cartilage has shown promise but the applicability of this technique in different imaging setups has not been well‐evaluated.PurposeTo assess variability in diffusion tensor imaging of the physis and metaphysis (DTI‐P/M) of the distal femur between different scanners, imaging parameters, tractography software, and resolution.Study TypeProspective.Population/SubjectsEleven healthy subjects (five males and six females ages 10–16.94).Field Strength/Sequence3 T; DTI single shot echo planar sequences.AssessmentPhyseal DTI tract measurements of the distal femur were compared between different scanners, imaging parameters, tractography settings, interpolation correction, and tractography software.Statistical TestsBland–Altman, Spearman correlation, linear regression, and Shapiro–Wilk tests. Threshold for statistical significance was set at P = 0.05.ResultsDTI tract values consistently showed low variability with different imaging and analysis settings. Vendor to vendor comparison exhibited strong correlation (ρ = 0.93) and small but significant bias (bias −5.76, limits of agreement [LOA] −24.31 to 12.78). Strong correlation and no significant difference were seen between technical replicates of the General Electric MRI scanner (ρ = 1, bias 0.17 [LOA −1.5 to 1.2], P = 0.42) and the Siemens MRI scanner (ρ = 0.89, bias = 0.56, P = 0.71). Different voxel sizes (1 × 1 × 2 mm3 vs. 2 × 2 × 3 mm3) did not significantly affect DTI values (bias = 1.4 [LOA −5.7 to 8.4], P = 0.35) but maintained a strong correlation (ρ = 0.82). Gap size (0 mm vs. 0.6 mm) significantly affects tract volume (bias = 1.8 [LOA −5.4 to 1.8]) but maintains a strong correlation (ρ = 0.93). Comparison of tractography algorithms generated significant differences in tract number, length, and volume while maintaining correlation (ρ = 0.86, 0.99, 0.93, respectively). Comparison of interobserver variability between different tractography software also revealed significant differences while maintaining high correlation (ρ = 0.85–0.98).Data ConclusionDTI of the pediatric physis cartilage shows high reproducibility between different imaging and analytic parameters.Evidence Level2Technical EfficacyStage 1
Effect of product design on repurchase intention, electronic word‐of‐mouth, and museum visit intention: Museum random boxes in China
Authors: Lin Feng , Ryu Kisang , Ahn Young‐joo 
Published: May 2024

AbstractThis study examines how product design affects museum visits and museum product loyalty. Based on the gaps in previous research, the study posits interrelationships among product design (esthetics and symbolism), emotional states (pleasure and arousal), attitude toward the product, loyalty repurchase intention and electronic word‐of‐mouth (eWOM), and museum visit intention. This research applied partial least squares‐structural equation modeling to analyze data from 316 customers who purchased the museum's random boxes. The empirical results suggest that (1) esthetics and symbolism are antecedents of attitude, pleasure, and arousal; (2) attitude toward the product mediates the effect of product design on product loyalty and museum visit intention; (3) arousal helps mediate the relationship between symbolism and repurchase intention; and (4) pleasure is an antecedent of attitude toward the product. This study provides valuable practical simplications and offers new areas for future studies.
The Third Compound Promoted Copolymerization of Ethylene with 4‐Penten‐1‐ol by Using Metallocene Catalyst
Authors: Wang Wei , Guo Tianhao , Qu Shuzhang , Zhang Taoyi , Li Xinwei 
Published: May 2024

AbstractOlefin coordination copolymerization with polar monomers is an important topic both in academia and industry. During copolymerization, polar monomers will seriously reduce the polymerization activity and the molecular weight of the copolymer, making it difficult to balance the two and the polar monomer incorporation at the same time. In this study, a metallocene catalyst, Ph2C(Cp)(Flu)ZrCl2, is used for the copolymerization of ethylene with 4‐penten‐1‐ol. The incorporation of 4‐penten‐1‐ol can be effectively increased by the introduction of the steric phenol as the third component (TC). Depending on the cocatalyst, the activity or molecular weight can be improved. It is believed that the promotion effect may work by the interaction of the steric phenol with the catalyst or cocatalyst. It is also suggested that in this system, polymerization is terminated by deactivation‐chain transfer mechanism rather than β‐X elimination due to back‐biting.
m6A modification of lncRNA PHKA1‐AS1 enhances Actinin Alpha 4 stability and promotes non‐small cell lung cancer metastasis
Authors: Guo Qiao‐Ru , Zhang Guo‐Bin , Zhou Wen‐Min , Lu Yu , Chen Xin‐Zhu , Deng Zhuo‐Fen , Li Jin‐Shuo , Bi Hong , Wu Ming‐Sheng , Xie Ming‐Ran , Yan Yan‐Yan , Zhang Jian‐Ye 
Published: May 2024

AbstractCancer is a disease with molecular heterogeneity that is closely related to gene mutations and epigenetic changes. The principal histological subtype of lung cancer is non‐small cell lung cancer (NSCLC). Long noncoding RNA (lncRNA) is a kind of RNA that is without protein coding function, playing a critical role in the progression of cancer. In this research, the regulatory mechanisms of lncRNA phosphorylase kinase regulatory subunit alpha 1 antisense RNA 1 (PHKA1‐AS1) in the progression of NSCLC were explored. The increased level of N6‐methyladenosine (m6A) modification in NSCLC caused the high expression of PHKA1‐AS1. Subsequently, high‐expressed PHKA1‐AS1 significantly facilitated the proliferation and metastasis of NSCLC cells, and these effects could be reversed upon the inhibition of PHKA1‐AS1 expression, both in vivo and in vitro. Additionally, the target protein of PHKA1‐AS1 was actinin alpha 4 (ACTN4), which is known as an oncogene. Herein, PHKA1‐AS1 could enhance the protein stability of ACTN4 by inhibiting its ubiquitination degradation process, thus exerting the function of ACTN4 in promoting the progress of NSCLC. In conclusion, this research provided a theoretical basis for further exploring the potential mechanism of NSCLC metastasis and searching novel biomarkers related to the pathogenesis and progression of NSCLC.
Machine learning bias correction and downscaling of urban heatwave temperature predictions from kilometre to hectometre scale
Authors: Blunn Lewis P. , Ames Flynn , Croad Hannah L. , Gainford Adam , Higgs Ieuan , Lipson Mathew , Lo Chun Hay Brian 
Published: May 2024

AbstractThe urban heat island (UHI) effect exacerbates near‐surface air temperature (T) extremes in cities, with negative impacts for human health, building energy consumption and infrastructure. Using conventional weather models, it is both difficult and computationally expensive to simulate the complex processes controlling neighbourhood‐scale variation of T. We use machine learning (ML) to bias correct and downscale T predictions made by the Met Office operational regional forecast model (UKV) to 100 m horizontal grid length over London, UK. A set of ML models (random forest, XGBoost, multiplayer perceptron) are trained using citizen weather station observations and UKV variables from eight heatwaves, along with high‐resolution land cover data. The ML models improve the T mean absolute error (MAE) by up to 0.12°C (11%) relative to the UKV. They also improve the UHI diurnal and spatial representation, reducing the UHI profile MAE from 0.64°C (UKV) to 0.15°C. A multiple linear regression performs almost as well as the ML models in terms of T MAE, but cannot match the UHI bias correction performance of the ML models, only reducing the UHI profile MAE to 0.49°C. UKV latent heat flux is found to be the most important predictor of T bias. It is demonstrated that including more heatwaves and observation sites in training would reduce overfitting and improve ML model performance.
Raspberry Ketone Prevents LPS‐Induced Depression‐Like Behaviors in Mice by Inhibiting TLR‐4/NF‐κB Signaling Pathway via the Gut‐Brain Axis
Authors: Liu Yike , Dai Chenlin , Wang Chendi , Wang Jiayao , Yan Weikang , Luo Maowen , Dong Juane , Li Xiulian , Liu Xuebo , Lan Ying 
Published: May 2024

ScopeDepression, a prevalent mental disorder, has significantly impacted the lives of 350 million people, yet it holds promise for amelioration through food‐derived phenolics. Raspberries, renowned globally for their delectable flavor, harbor a phenolic compound known as raspberry ketone (RK). However, the impact of RK on depressive symptoms remains ambiguous. This study aims to investigate the impact of RK on lipopolysaccharide (LPS)‐induced depressed mice and elucidates its potential mechanisms, focusing on the gut‐brain axis.Methods and resultsThrough behavioral tests, RK exerts a notable preventive effect on LPS‐induced depression‐like behaviors in mice. RK proves capable of attenuating gut inflammation, repairing gut barrier impairment, modulating the composition of the gut microbiome (Muribaculaceae, Streptococcus, Lachnospiraceae, and Akkermansia), and promoting the production of short‐chain fatty acids. Furthermore, RK alleviates neuroinflammation by suppressing the TLR‐4/NF‐κB pathway and bolsters synaptic function by elevating levels of neurotrophic factors and synapse‐associated proteins.ConclusionThe current study provides compelling evidence that RK effectively inhibits the TLR‐4/NF‐κB pathway via the gut‐brain axis, leading to the improvement of LPS‐induced depression‐like behaviors in mice. This study addresses the research gap in understanding the antidepressant effects of RK and illuminates the potential of utilizing RK as a functional food for preventing depression.