bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bell pepper endornavirus alters green peach aphid (Hemiptera: Aphididae) host choice and population dynamics
Authors: Paudel Sunil , Valverde Rodrigo A , Davis Jeffrey A 
Published: October 2024

Abstract
Bell pepper endornavirus (BPEV) Alphaendornavirus capsici (Endornaviridae) is an RNA virus that infects many pepper (Capsicum annuum) horticultural types and is seed transmitted. BPEV does not cause apparent symptoms and is found at every plant developmental stage. During the domestication of bell pepper, plant breeders, unaware of the existence of endornaviruses in the germplasm, selected endornavirus-infected genotypes. This could be an indication that the presence of endornaviruses in this crop is beneficial. Among the possible beneficial effects that endornaviruses may provide to their host could include tolerance or resistance to biotic and abiotic agents and, therefore, may have evolved a symbiotic relationship with their hosts. With this in mind, we set out to determine host preference, host suitability, and population dynamics of green peach aphid Myzus persicae (Sulzer) on BPEV-infected and virus-free bell pepper near-isogenic lines. During choice bioassay experiments, we observed that a higher proportion of M. persicae adults settled on BPEV noninfected leaves as compared to BPEV-infected leaves. Life table analysis revealed that M. persicae performed less well on BPEV-infected leaf tissues, with reductions in longevity, progeny, and intrinsic rate of increase. These results indicate BPEV is beneficial to its host, protecting against an important generalist pest.
Adaptive meshless local maximum-entropy finite element method for Navier-Stokes equations
Authors: Young D L , Shih C-L , Yen L J , Chu C-R 
Published: October 2024

Abstract
Based on the successful application of the adaptive meshless local maximum-entropy finite element method to solve the convection-diffusion equation, this study extends the same principle to study the 2-dimensional Navier-Stokes equations. Through extensive case studies, this work demonstrates that the present approach is a viable alternative to resolve the high Reynolds number Navier-Stokes equations. The simulation results indicate that by incorporating additional points into the elements without increasing the bandwidth or refinement via the local maximum-entropy procedure, it will enhance the accuracy and efficiency of numerical simulations. A 2-dimensional square lid-driven cavity with various Reynolds numbers will serve as the first example. In the second example, we address a more complex geometry by solving the cavity with a hole inside the cavity center. The numerical results of the model compare favorably with other numerical solutions, including the finite difference method and the finite element method. This paper provides a very powerful tool to study the boundary layer theory with irregular geometry of the Navier-Stokes equations.
The cloud cover and meteorological parameters at the Lenghu site on the Tibetan Plateau
Authors: Li Ruiyue , He Fei , Deng Licai , Chen Xiaodian , Yang Fan , Zhao Yong , Zhang Bo , Zhang Chunguang , Yang Chen , Lan Tian 
Published: October 2024

ABSTRACT
The cloud cover and meteorological parameters serve as fundamental criteria for an astronomical observatory working in optical and infrared wavelengths. In this paper, we present a systematic assessment of key meteorological parameters at the Lenghu astronomical observing site on the Tibetan Plateau. The data sets adopted includes the meteorological parameters collected at the local weather stations at the site and in the Lenghu Town, the sky brightness acquired by the Sky Quality Meters and all-sky images from a digital camera, the ERA5 reanalysis data base, and global climate monitoring data. From 2019 to 2023, the fractional observable time of photometric condition is 69.70 per cent, 74.97 per cent, 70.26 per cent, 74.27 per cent, and 65.12 per cent, respectively, which is influenced by a variety of meteorological parameters. Large-scale air–sea interactions affect the climate at Lenghu site, which in fact delivers a clue to understand the irregularity of 2023. Specifically, precipitable water vapour at Lenghu site is correlated to both the westerly wind index and the summer North Atlantic Oscillation index, the yearly average temperature of Lenghu site is observed to increase significantly during the occurrence of a strong El Niño event, and the relative humidity anomaly at Lenghu site is correlated to the Pacific Decadal Oscillation index. The decrease of fractional observing time in 2023 was due to the ongoing strong El Niño event and relevant global climate change. We underscore the substantial role of global climate change in regulating astronomical observing conditions and the necessity for long-term continuous monitoring of the astronomical meteorological parameters at Lenghu site.
Survey of gravitationally lensed objects in HSC imaging (SuGOHI) – X. Strong lens finding in the HSC-SSP using convolutional neural networks
Authors: Jaelani Anton T , More Anupreeta , Wong Kenneth C , Inoue Kaiki T , Chao Dani C -Y , Premadi Premana W , Cañameras Raoul 
Published: October 2024

ABSTRACT
We apply a novel model based on convolutional neural networks (CNN) to identify gravitationally lensed galaxies in multiband imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. The trained CNN assigns a score from 0 to 1, with 1 representing lenses and 0 representing non-lenses. Initially, the CNN selects a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1522 cutouts after removing definite non-lenses for further visual inspection. We discover 43 grade A (definite) and 269 grade B (probable) strong lens candidates, of which 97 are completely new. In addition, we also discover 880 grade C (possible) lens candidates, 289 of which are known systems in the literature. We identify 143 candidates from the known systems of grade C that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems are not included in the training, a sample of 32 SuGOHI-c (i.e. group/cluster-scale systems) lens candidates is retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling.
Tree Sequences as a General-Purpose Tool for Population Genetic Inference
Authors: Whitehouse Logan S , Ray Dylan D , Schrider Daniel R 
Published: October 2024

Abstract
As population genetic data increase in size, new methods have been developed to store genetic information in efficient ways, such as tree sequences. These data structures are computationally and storage efficient but are not interchangeable with existing data structures used for many population genetic inference methodologies such as the use of convolutional neural networks applied to population genetic alignments. To better utilize these new data structures, we propose and implement a graph convolutional network to directly learn from tree sequence topology and node data, allowing for the use of neural network applications without an intermediate step of converting tree sequences to population genetic alignment format. We then compare our approach to standard convolutional neural network approaches on a set of previously defined benchmarking tasks including recombination rate estimation, positive selection detection, introgression detection, and demographic model parameter inference. We show that tree sequences can be directly learned from using a graph convolutional network approach and can be used to perform well on these common population genetic inference tasks with accuracies roughly matching or even exceeding that of a convolutional neural network-based method. As tree sequences become more widely used in population genetic research, we foresee developments and optimizations of this work to provide a foundation for population genetic inference moving forward.
Stacking correlation length in single-stranded DNA
Authors: Viader-Godoy Xavier , Manosas Maria , Ritort Felix 
Published: October 2024

Abstract
Base stacking is crucial in nucleic acid stabilization, from DNA duplex hybridization to single-stranded DNA (ssDNA) protein binding. While stacking energies are tiny in ssDNA, they are inextricably mixed with hydrogen bonding in DNA base pairing, making their measurement challenging. We conduct unzipping experiments with optical tweezers of short poly-purine (dA and alternating dG and dA) sequences of 20–40 bases. We introduce a helix-coil model of the stacking–unstacking transition that includes finite length effects and reproduces the force-extension curves. Fitting the model to the experimental data, we derive the stacking energy per base, finding the salt-independent value $\Delta G_0^{ST}=0.14(3)$ kcal/mol for poly-dA and $\Delta G_0^{ST}=0.07(3)$ kcal/mol for poly-dGdA. Stacking in these polymeric sequences is predominantly cooperative with a correlation length of ∼4 bases at zero force . The correlation length reaches a maximum of ∼10 and 5 bases at the stacking–unstacking transition force of ∼10 and 20 pN for poly-dA and poly-dGdA, respectively. The salt dependencies of the cooperativity parameter in ssDNA and the energy of DNA hybridization are in agreement, suggesting that double-helix stability is primarily due to stacking. Analysis of poly-rA and poly-rC RNA sequences shows a larger stacking stability but a lower stacking correlation length of ∼2 bases.
Insertion sequence elements and unique symmetrical genomic regions mediate chromosomal inversions in Streptococcus pyogenes
Authors: Jespersen Magnus G , Hayes Andrew J , Tong Steven Y C , Davies Mark R 
Published: October 2024

Abstract
Chromosomal inversions are a phenomenon in many bacterial species, often across the axis of replication. Inversions have been shown to alter gene expression, changing persistence of colonisation and infection following environmental stresses. In Streptococcus pyogenes, inversions have been reported. However, frequency and molecular markers of inversions have not been systematically examined. Here, 249 complete S.pyogenes genomes were analysed using a pangenomic core gene synteny framework to identify sequences associated with inversions. 47% of genomes (118/249) contained at least one inversion, from 23 unique inversion locations. Chromosomal locations enabling inversions were usually associated with mobile elements (insertion sequences n = 9 and prophages n = 7). Two insertion sequences, IS1548 and IS1239, accounted for &gt;80% of insertion sequences and were the only insertion sequences associated with inversions. The most observed inversion location (n = 104 genomes, 88% of genomes with an inversion) occurs between two conserved regions encoding rRNAs, tRNAs and sigma factor genes. The regions are symmetrically placed around the origin of replication forming a unique chromosomal structure in S. pyogenes, relative to other streptococci. Cataloging of the chromosomal location and frequency of inversions can direct dissection of phenotypic changes following chromosomal inversions. The framework used here can be transferred to other bacterial species to characterise chromosomal inversions.
YY1 is a transcriptional activator of the mouse LINE-1 Tf subfamily
Authors: Saha Karabi , Nielsen Grace I , Nandani Raj , Zhang Yizi , Kong Lingqi , Ye Ping , An Wenfeng 
Published: October 2024

Abstract
Long interspersed element type 1 (LINE-1, L1) is an active autonomous transposable element in human and mouse genomes. L1 transcription is controlled by an internal RNA polymerase II promoter in the 5′ untranslated region (5′UTR) of a full-length L1. It has been shown that transcription factor YY1 binds to a conserved sequence at the 5′ end of the human L1 5′UTR and primarily dictates where transcription initiates. Putative YY1-binding motifs have been predicted in the 5′UTRs of two distinct mouse L1 subfamilies, Tf and Gf. Using site-directed mutagenesis, in vitro binding and gene knockdown assays, we experimentally tested the role of YY1 in mouse L1 transcription. Our results indicate that Tf, but not Gf subfamily, harbors functional YY1-binding sites in 5′UTR monomers and YY1 functions as a transcriptional activator for the mouse Tf subfamily. Activation of Tf transcription by YY1 during early embryogenesis is also supported by a reanalysis of published zygotic knockdown data. Furthermore, YY1-binding motifs are solely responsible for the synergistic interaction between Tf monomers, consistent with a model wherein distant monomers act as enhancers for mouse L1 transcription. The abundance of YY1-binding sites in Tf elements also raise important implications for gene regulation across the genome.
RPS 2.0: an updated database of RNAs involved in liquid–liquid phase separation
Authors: He Yongxin , Bao Xiaoqiong , Chen Tianjian , Jiang Qi , Zhang Luowanyue , He Li-Na , Zheng Jian , Zhao An , Ren Jian , Zuo Zhixiang 
Published: October 2024

Abstract
Liquid–liquid phase separation (LLPS) is a crucial process for the formation of biomolecular condensates such as coacervate droplets, P-bodies and stress granules, which play critical roles in many physiological and pathological processes. Increasing studies have shown that not only proteins but also RNAs play a critical role in LLPS. To host LLPS-associated RNAs, we previously developed a database named ‘RPS’ in 2021. In this study, we present an updated version RPS 2.0 (https://rps.renlab.cn/) to incorporate the newly generated data and to host new LLPS-associated RNAs driven by post-transcriptional regulatory mechanisms. Currently, RPS 2.0 hosts 171 301 entries of LLPS-associated RNAs in 24 different biomolecular condensates with four evidence types, including ‘Reviewed’, ‘High-throughput (LLPS enrichment)’, ‘High-throughput (LLPS perturbation)’ and ‘Predicted’, and five event types, including ‘Expression’, ‘APA’, ‘AS’, ‘A-to-I’ and ‘Modification’. Additionally, extensive annotations of LLPS-associated RNAs are provided in RPS 2.0, including RNA sequence and structure features, RNA–protein/RNA–RNA interactions, RNA modifications, as well as diseases related annotations. We expect that RPS 2.0 will further promote research of LLPS-associated RNAs and deepen our understanding of the biological functions and regulatory mechanisms of LLPS.
CancerSCEM 2.0: an updated data resource of single-cell expression map across various human cancers
Authors: Zeng Jingyao , Nie Zhi , Shang Yunfei , Mai Jialin , Zhang Yadong , Yang Yuntian , Xu Chenle , Zhao Jing , Fan Zhuojing , Xiao Jingfa 
Published: October 2024

Abstract
The field of single-cell RNA sequencing (scRNA-seq) has advanced rapidly in the past decade, generating significant amounts of valuable data for researchers to study complex tumor profiles. This data is crucial for gaining innovative insights into cancer biology. CancerSCEM (https://ngdc.cncb.ac.cn/cancerscem) is a public resource that integrates, analyzes and visualizes scRNA-seq data related to cancer, and it provides invaluable support to numerous cancer-related studies. With CancerSCEM 2.0, scRNA-seq data have increased from 208 to 1466 datasets, covering tumor, matching-normal and peripheral blood samples across 127 research projects and 74 cancer types. The new version of this resource enhances transcriptome analysis by adding copy number variation evaluation, transcription factor enrichment, pseudotime trajectory construction, and diverse biological feature scoring. It also introduces a new cancer metabolic map at the single-cell level, providing an intuitive understanding of metabolic regulation across different cancer types. CancerSCEM 2.0 has a more interactive analysis platform, including four modules and 14 analytical functions, allowing researchers to perform cancer scRNA-seq data analyses in various dimensions. These enhancements are expected to expand the usability of CancerSCEM 2.0 to a broader range of cancer research and clinical applications, potentially revolutionizing our understanding of cancer mechanisms and treatments.
Differential redox sensitivity of tRNA dihydrouridylation
Authors: Kilz Lea-Marie , Zimmermann Simone , Marchand Virginie , Bourguignon Valérie , Sudol Claudia , Brégeon Damien , Hamdane Djemel , Motorin Yuri , Helm Mark 
Published: October 2024

Abstract
Various transfer RNA (tRNA) modifications have recently been shown to regulate stress-dependent gene expression by modulating messenger RNA translation. Among these modifications, dihydrouridine stands out for its increase of tRNA structural flexibility. However, whether and how dihydrouridine synthesis reacts to environmental stimuli is largely unknown. In this study, we manipulated the intracellular redox state of Escherichia coli using paraquat, revealing differential sensitivities of the three tRNA-dihydrouridine synthases towards oxidative stress. Using liquid chromatography–mass spectrometry quantification of dihydrouridine in various knockout strains, we validated the use of a specific RNA sequencing method, namely AlkAnilineSeq, for the precise mapping of dihydrouridines throughout E. coli tRNAs. We found DusA showing high activity, followed by DusB and DusC, whose activity was decreased under paraquat treatment. The relative sensitivity is most plausibly explained by a paraquat-dependent drop of NADPH availability. These findings are substantiated by in vitro kinetics, revealing DusA as the most active enzyme, followed by DusB, while DusC showed little activity, likely related to the efficacy of the redox reaction of the flavin coenzyme with NADPH. Overall, our study underscores the intricate interplay between redox dynamics and tRNA modification processes, revealing a new facet of the regulatory mechanisms influencing cellular responses to oxidative stress.
Understanding the Crucial Role of Phosphate and Iron Availability in Regulating Root Nodule Symbiosis
Authors: Isidra-Arellano Mariel C , Valdés-López Oswaldo 
Published: October 2024

Abstract
The symbiosis between legumes and nitrogen-fixing bacteria (rhizobia) is instrumental in sustaining the nitrogen cycle and providing fixed nitrogen to the food chain. Both partners must maintain an efficient nutrient exchange to ensure a successful symbiosis. This mini-review highlights the intricate phosphate and iron uptake and homeostasis processes taking place in legumes during their interactions with rhizobia. The coordination of transport and homeostasis of these nutrients in host plants and rhizobia ensures an efficient nitrogen fixation process and nutrient use. We discuss the genetic machinery controlling the uptake and homeostasis of these nutrients in the absence of rhizobia and under symbiotic conditions with this soil bacterium. We also highlight the genetic impact of the availability of phosphate and iron to coordinate the activation of the genetic programs that allow legumes to engage in symbiosis with rhizobia. Finally, we discuss how the transcription factor phosphate starvation response might be a crucial genetic element to integrate the plant’s needs of nitrogen, iron and phosphate while interacting with rhizobia. Understanding the coordination of the iron and phosphate uptake and homeostasis can lead us to better harness the ecological benefits of the legume-rhizobia symbiosis, even under adverse environmental conditions.
LinkedOut? A Field Experiment on Discrimination in Job Network Formation
Authors: Evsyukova® Yulia , Rusche® Felix , Mill Wladislaw 
Published: October 2024

Abstract
We assess the impact of discrimination on Black individuals’ job networks across the United States using a two-stage field experiment with 400+ fictitious LinkedIn profiles. In the first stage, we vary race via AI-generated images only and find that Black profiles’ connection requests are 13% less likely to be accepted. Based on users’ CVs, we find widespread discrimination across social groups. In the second stage, we exogenously endow Black and white profiles with the same networks and ask connected users for career advice. We find no evidence of direct discrimination in information provision. However, when taking into account differences in the composition and size of networks, Black profiles receive substantially fewer replies. Our findings suggest that gatekeeping is a key driver of Black–white disparities.
Quantification of myocardial oxygen extraction fraction on noncontrast MRI enabled by deep learning
Authors: Li Ran , Eldeniz Cihat , Wang Keyan , Nguyen Natalie , Schindler Thomas H , Huang Qi , Peterson Linda R , Yang Yang , Yan Yan , Cheng Jingliang , Woodard Pamela K , Zheng Jie 
Published: October 2024

Abstract

Purpose
To develop a new deep learning enabled cardiovascular magnetic resonance (CMR) approach for noncontrast quantification of myocardial oxygen extraction fraction (mOEF) and myocardial blood volume (MBV) in vivo.

Materials and Methods
An asymmetric spin-echo prepared CMR sequence was created in a 3 T MRI clinical system. A UNet-based fully connected neural network was developed based on a theoretical model of CMR signals to calculate mOEF and MBV. Twenty healthy volunteers (20–30 years old, 11 females) underwent CMR scans at 3 short-axial slices (16 myocardial segments) on 2 different days. The reproducibility was assessed by the coefficient of variation. Ten patients with chronic myocardial infarction were examined to evaluate the feasibility of this CMR method to detect abnormality of mOEF and MBV.

Results
Among the volunteers, the average global mOEF and MBV on both days was 0.58 ± 0.07 and 9.5% ± 1.5%, respectively, which agreed well with data measured by other imaging modalities. The coefficient of variation of mOEF was 8.4%, 4.5%, and 2.6%, on a basis of segment, slice, and participant, respectively. No significant difference in mOEF was shown among 3 slices or among different myocardial segments. Female participants showed significantly higher segmental mOEF than male participants (P &lt; .001). Regional mOEF decrease 40% in CMR-confirmed myocardial infarction core, compared to normal myocardial regions.

Conclusion
The new deep learning–enabled CMR approach allows noncontrast quantification of mOEF and MBV with good to excellent reproducibility. This technique could provide an objective contrast-free means to assess and serially measure hypoxia-relief effects of therapeutic interventional strategies to save viable myocardial tissues.