bluuebunny/crossref_metadata_2025 huggingface dataset:
Comprehensive evaluation of real-time uncombined-PPP/INS tightly coupled integration with BDS−3 PPP−B2b service in urban environments
Authors: Li Wei , Pan Cheng , Gao Jingxiang , Li Zengke , Tao Zhenqiang
Published: December 2024

The BeiDou global navigation satellite system (BDS-3) employs the PPP-B2b signal as a data broadcast channel through geostationary Earth orbit (GEO) satellites, enabling the real-time transmission of precise orbit, clock, and differential code bias correction information for BDS and other global navigation satellite systems (GNSS) in the event of network outages. The uncombined precise point positioning (UCPPP) model has gained attention owing to its advantages in multi-frequency and multi-constellation processing. Addressing the challenge of frequent interference and interruption of GNSS signals in densely populated urban areas, this study leverages the complementary strengths of the inertial navigation system (INS) and GNSS, proposing a UCPPP-B2b/INS tightly coupled system and analyzing its positioning performance across various urban environments. Experimental results indicate that the positioning accuracies of the UCPPP-B2b/INS tightly coupled system in urban environments are 33.9 cm, 55.6 cm, and 48.6 cm in the east, north, and up directions, respectively. Additionally, the performance of tactical-grade inertial measurement unit (tactical-IMU) and micro-electro-mechanical systems IMU (MEMS-IMU) was compared under both loosely and tightly coupled configurations using the uncombined approach. The findings reveal that while the positioning performance of the two IMUs is comparable, regardless of whether the PPP-B2b service products or the post-processed precise products are utilized, the tactical-IMU demonstrates superior continuity and anti-jamming capabilities during GNSS signal interruptions. Finally, simulated 30 s GNSS signal outages showed that the tightly coupled PPP-B2b/MEMS-IMU system had positioning errors of 556.8 cm, 547.1 cm, and 99.4 cm, while the PPP-B2b/tactical-IMU system had errors of 6.5 cm, 24.5 cm, and 21.3 cm in the east, north, and up directions, respectively.
Research on a cloud-edge collaborative adaptive detection system for AC series arc faults
Authors: Bao Guanghai , Wang Zhaorui , He Jiantao
Published: December 2024

AC series arc faults (SAFs) are one of the leading causes of electrical fires in buildings, and the development of arc fault detection devices (AFDDs) can effectively reduce the fire risk caused by arc faults. To address the issue of unsatisfactory detection performance for SAFs and frequent false positives in existing AFDDs when dealing with unknown load combinations, this paper proposes an adaptive SAF detection system. The system is based on the remote interaction between AFDD and cloud server, which enables the AFDD to update its SAF detection model for unknown load combinations, thereby improving its generalization performance. First, a lightweight neural network model for SAF detection based on depth-wise separable convolution and inverted residual block was designed and ported to the K210 chip, combined with peripheral circuits to create the AFDD. The AFDD collects high-frequency coupling signals from the circuit at a sampling rate of 100 kHz, achieving real-time SAF detection with a detection cycle of 80 ms. The cloud server receives and filters false positive and SAF data uploaded by the AFDD during operation, and updates the detection model on the AFDD through data augmentation and transfer learning to improve its generalization capability. Experimental results show that the normal state recognition rate of the updated AFDD for unknown load combinations increased from 98.87% to 99.92%, and the SAF recognition rate improved from 96.26% to 98.16%. The results demonstrate that the adaptive SAF detection system significantly improves the AFDD’s performance in reducing false positives and missed detections for unknown load combinations.
CT-RURnet: a novel network design for radar unmanned aerial vehicles recognition
Authors: Jiang Tiezhen , Li Qingzhu , Huang Zhixiang , Zhuang Long
Published: December 2024

The rapid growth of commercial unmanned aerial vehicles (UAVs) has led to more incidents. These include illegal activities by malicious actors. Such activities pose significant threats to public facilities and people’s safety. Therefore, distinguishing UAVs from other targets is a critical measure in preventing potential hazards. This paper proposes an enhanced feature extraction and global modeling model for UAV recognition, named CT-RURnet. The model directly learns from radar echo data, firstly using the convolutional neural networks module to quickly extract local features, and then using the Transformer module to establish global connections among these local features. The proposed model primarily focuses on learning the micro-Doppler features produced by targets, which facilitates UAV recognition. The used datasets include both simulated data and the Real Doppler RAD-DAR (RDRD) dataset. The proposed network achieves accuracy rates of 98.7% (10 SNR), 97.9% (5 SNR), and 86.95% (0 SNR) on the simulated dataset under varying SNR conditions and 97.14% on the real dataset. Compared to other baseline models, the CT-RURnet consistently delivers superior results. Ablation experiments are conducted to verify the contribution of each module to the overall network performance.
Numerical simulation and electromagnetic parameter retrieve: performance evaluation of metamaterials under TE and TM polarization conditions
Authors: Li Bowen , Zhao Zhanliang , Song Lijun , Hu Ruixue , Fan Lisi , Xie Jing , Du Xue , Wang Mingxing
Published: December 2024

This study introduces a novel metamaterial design employing a bent-line unit cell structure optimized for electromagnetic applications under TE and TM polarization conditions. By leveraging the Floquet theorem and an inversion algorithm, the research extracts equivalent electromagnetic parameters to achieve efficient and precise simulations over various frequencies and incident angles. The proposed metamaterial demonstrates remarkable frequency stability, wide bandwidth, and consistent performance across polarization states and incident angles (0°–60°), with resonance frequency deviations below 1%. Experimental validation confirms the accuracy of the design, highlighting its potential for advanced communication, sensing, and antenna systems. The findings underscore the advantages of the proposed approach, including enhanced computational efficiency and improved simulation processes, making it a promising pathway for metamaterial optimization in diverse electromagnetic environments.
Hyperbolicity of a semi-Lagrangian formulation of the hydrostatic free-surface Euler system
Authors: Di Martino Bernard , El Hassanieh Chourouk , Godlewski Edwige , Guillod Julien , Sainte-Marie Jacques
Published: December 2024

By a semi-Lagrangian change of coordinates, the hydrostatic Euler equations describing free-surface sheared flows is rewritten as a system of quasilinear equations, where stability conditions can be determined by the analysis of its hyperbolic structure. The system one obtains can be written as a quasi linear system in time and horizontal variables and involves no more vertical derivatives. However, the coefficients in front of the horizontal derivatives include an integral operator acting on the new vertical variable. The spectrum of these operators is studied in detail, in particular it includes a continuous part. Riemann invariants are then determined as conserved quantities along the characteristic curves. Examples of solutions are provided, in particular stationary solutions and solutions blowing-up in finite time. Eventually, we propose an exact multilayer

P

0

-discretization, which could be used to solve numerically this semi-Lagrangian system, and analyze the eigenvalues of the corresponding discretized operator to investigate the hyperbolic nature of the approximated system.
Achievement of highly radiating plasma in negative triangularity and effect of reactor-relevant seeded impurities on confinement and transport
Authors: Casali L , Eldon D , Odstrcil T , Mattes R , Welsh A , Lee K , Nelson A O , Paz-Soldan C , Khabanov F , Cote T , McLean A G , Scotti F , Thome K E
Published: December 2024

The first achievement of highly radiating plasmas in negative triangularity (NT) is shown with an operational space featuring high core radiation at high Greenwald fraction obtained with the injection of reactor-relevant seeded gases. These NT shape diverted discharges reach high values of normalized plasma pressure (β
N > 2) at high radiation fraction with no edge localized modes (ELMs) and a simultaneous reduction of the divertor heat flux. We demonstrate that as long as the impurity level in the core is kept low to avoid excessive fuel dilution and impurity accumulation, integration of NT configuration with high radiation fraction not only is achievable but it can lead to confinement improvement with stabilization effects originating from collisionality, E × B shear and profiles changes due to impurity radiation cooling. The underlying physics mechanism is robust and reproducible and holds for a variety of impurity species. The absence of the requirement to stay in H-mode translates in a higher core radiation fraction potentially allowed in NT shape effectively mitigating the power exhaust issue. The results presented here demonstrate a path to high performance, ELM free and highly radiative regime with reactor-relevant seeding gases making this regime a potential new scenario for reactor design.
Controlled bidirectional quantum secure direct communication with hyperentangled Bell states
Authors: Feng Yun-Hao , Zhou Ri-Gui , Zhang Xiao-Xue
Published: December 2024

This paper presents a groundbreaking protocol for controlled bidirectional quantum secure direct communication based on hyperentangled Bell states, involving two longitudinal momentum and polarization degrees of freedom. In this protocol, the controller Charlie governs bidirectional communication between two legitimate participants. Participants encode their secret messages using 64 unitary operations. However, without Charlie’s permission, specifically without publishing the final measurement results, participants cannot exchange secret messages. Security analysis are conducted to prevent eavesdropper Eve from obtaining users’ secret messages through illegitimate means. Compared with previously proposed controlled bidirectional quantum secure direct communication, the proposed protocol significantly improves transmission efficiency because each pair of photons can transmit 12 bits of classical information. The protocol achieves a remarkable qubit efficiency, reaching up to 85.7%. However, when we don’t take into account the number of qubits consumed by the decoy particles, we can theoretically achieve an efficiency of 200%.
Eco-friendly gamma radiation protection using waste rice straw and animal glue enhanced by micro and nano iron oxide: a Geant4 simulation and experimental study
Authors: El-Khatib Ahmed M , Alabsy Mahmoud T , Sharaby Mahmoud A , Elzaher Mohamed Abd , Doma A S , Abbas Mahmoud I
Published: December 2024

The current investigation is directed towards the synthesis of new radiation shielding composites utilizing natural and eco-friendly components, including rice straw and animal glue. The experimental methodology involved preparing samples through the blending of 20% wt. rice straw with 80% wt. animal glue, followed by the addition of micro- and nano-sized powders of iron oxide (Fe2O3) at varying concentrations (10%, 18.2%, and 25%). The performance of γ-ray protection of the prepared composites was assessed and analyzed by measuring different shielding parameters such as mass attenuation coefficient (MAC), linear attenuation coefficient (μ), mean free path (MFP), half value layer (HVL), tenth value layer (TVL), effective atomic number (Zeff), equivalent atomic number (Zeq), and build-up factor (BFs) across various photon energies (0.059 MeV to 1.408 MeV). Experimental results of the MAC were compared with theoretical data from XCOM and simulated data from the Geant4 code, indicating good agreement and validating the experimental findings. The results showed that the addition of nano-Fe2O3 (25 wt%) to the composite sample had the highest μ values, which varied between 0.34260 and 0.05274 cm−1 as γ-ray photon energy increased from 0.0595 to 1.408 MeV, respectively. Furthermore, the highest relative increase rate in μ values between nano and micro composites was 24.11%, achieved for the nano Fe2O3 (25 wt%) composite sample at 0.0595 MeV. In conclusion, the investigation demonstrated improved γ-ray protection with the addition of nano-Fe2O3 compared to bulk counterparts.
Noether symmetry analysis for the generalized brans-dicke cosmology
Authors: Paliathanasis Andronikos
Published: December 2024

We present the complete solution to the classification problem regarding the variational symmetries of the generalized Brans-Dicke cosmological model in the presence of a second scalar field minimally coupled to gravity and the generalized Brans-Dicke scalar field theory. Through the symmetry analysis, we were able to specify the functional form of the field equations such that they become integrable. Additionally, new families of integrable cosmological models are presented.
Improved treatment of bosonic dark matter dynamics in neutron stars: consequences and constraints
Authors: Dutta Koushik , Ghosh Deep , Mukhopadhyaya Biswarup
Published: December 2024

It is conceivable that a bosonic dark matter (DM) with non-gravitational interactions with SM particles will be accumulated at the center of a neutron star (NS) and can lead to black hole formation. In contrast to previous works with a fixed NS temperature, we dynamically determine the formation of Bose-Einstein condensate (BEC) for a given set of DM parameters, namely the DM-neutron scattering cross-section (σχn), the thermal average of DM annihilation cross-section (⟨σv⟩) and the DM mass (mχ). For both non-annihilating and annihilating DM with ⟨σv⟩ ≲ 10-26 cm3 s-1, the BEC forms for mχ
≲ 10 TeV. In case of non-annihilating DM, observations of old NS allows σχn
≲ 10-52 cm2 for 10 MeV ≤ mχ
≲ 10 GeV (with BEC) and σχn
≲ 10-47 cm2 for 5 TeV ≲ mχ
≲ 30 PeV (without BEC). This analysis shows that the electroweak mass window, 10 GeV ≲ mχ
≲ 5 TeV is essentially unconstrained by NS observations and therefore is subject only to direct detection experiments. In the annihilating DM scenario, the exclusion limits on DM parameters become weaker and even vanish for typical WIMP annihilation cross-section. However, the late-time heating of the NS enables us to probe the region with σχn
≳ 10-47 cm2, using the James Webb Space Telescope in the foreseeable future. When our results are viewed in the context of indirect searches of DM, it provides a lower limit on the ⟨σv⟩, which is sensitive to the DM thermal state.
Quantum decoder design for subsystem surface code based on multi-head graph attention and edge weighting
Authors: Ji 纪 Nai-Hua 乃华 , Sun 孙 Hui-Qian 汇倩 , Xiao 肖 Bo 博 , Song 宋 Ping-Li 平俐 , Ma 马 Hong-Yang 鸿洋
Published: December 2024

Quantum error-correcting codes are essential for fault-tolerant quantum computing, as they effectively detect and correct noise-induced errors by distributing information across multiple physical qubits. The subsystem surface code with three-qubit check operators demonstrates significant application potential due to its simplified measurement operations and low logical error rates. However, the existing minimum-weight perfect matching (MWPM) algorithm exhibits high computational complexity and lacks flexibility in large-scale systems. Therefore, this paper proposes a decoder based on a graph attention network (GAT), representing error syndromes as undirected graphs with edge weights, and employing a multi-head attention mechanism to efficiently aggregate node features and enable parallel computation. Compared to MWPM, the GAT decoder exhibits linear growth in computational complexity, adapts to different quantum code structures, and demonstrates stronger robustness under high physical error rates. The experimental results demonstrate that the proposed decoder achieves an overall accuracy of 89.95% under various small code lattice sizes (L = 2,3,4,5), with the logical error rate threshold increasing to 0.0078, representing an improvement of approximately 13.04% compared to the MWPM decoder. This result significantly outperforms traditional methods, showcasing superior performance under small code lattice sizes and providing a more efficient decoding solution for large-scale quantum error correction.
Design of the first full-scale HYLITE, a charge integration pixel detector readout chip for XFEL
Authors: Li M. , Wei W. , Zhang J. , Jiang X. , Ju X. , Li Z. , Liu P. , Sun T. , Sheng Z. , Sun P. , Xu G. , Yin H. , Liu Z.
Published: December 2024

HYLITE (High dYmamic range free electron Laser Imaging deTEctor) is a charge-integration detector readout chip designed for SHINE (Shanghai HIgh repetition rate XFEL aNd Extreme light facility), featuring a dynamic range of 10000 photons at 12 keV, a resolution of a single photon, and a high frame rate aiming for 10 kHz.

HYLITE200F is the first full-scale chip of HYLITE manufactured in a 130 nm CMOS process. The engineering-run chip consists of 64 × 64 pixels with a pixel pitch of 200 μm. As the first step of the project, the HYLITE200F chip works at a frame rate of 1 kHz in a successive mode. To deal with the power supply issue and a high data rate, the layout of the pixel array and the clock distribution structure is carefully designed. Furthermore, prototype front-end modules were manufactured to verify the function of sensors, ASICs, and the reliability of the bump-bonding process. Test results show that HYLITE200F can work steadily at a frame rate of 1 kHz.
Application of electrochemical deposition of CeO2 nanoparticles modified 3D printed porous Ti6Al4V scaffold in bone defect repair
Authors: Fan Dechao , Ding Kun , Lu Junfeng , Zhao Ziwen , Mao Yuanfu , Yang Guofu
Published: December 2024

Due to the limited self-regeneration capacity of bone, medical interventions is often required for large segmental bone defects. In this study, the application of porous titanium alloy (Ti6Al4V) scaffold in bone defect repair was investigated. Owing to its excellent mechanical properties and biocompatibility, Ti6Al4V is a preferred choice for orthopedic implants. To reduce the negative impact of its high elastic modulus on bone tissue, 3D printing technology was utilized to manufacture porous structures to approximate the elastic modulus of human bone, reducing the stress shielding phenomenon. In addition, electrochemical deposition technology was employed to deposit CeO2 nanoparticles (CNPs) onto the scaffold surface, aiming to improve its biological activity. According to the experimental findings, adding CNPs significantly enhanced the scaffold osteogenic capability. In vitro experiments on proliferation and expression of osteogenic markers verified its biological activity, while in vivo experiments further confirmed its potential to promote bone regeneration. Through detailed material characterization and biological evaluation, this study demonstrated the application prospect of 3D printed porous Ti6Al4V scaffold combined with CNPs, providing a new idea for the clinical repair of bone defects.
Design and construction of two biased electrodes and preliminary experiments on the Keda Torus eXperiment
Authors: Wu Jiaren , Lan Tao , Zhuang Ge , Wu Jie , Mao Wenzhe , Chen Chen , Wang Xingkang , Deng Peng , Dong Qilong , Zhou Yongkang , Wang Tianxiong , Lu Pengcheng , Bai Zeqi , Huang Yuhua , Wu Zhengwei , Wei Zian , Wen Xiaohui , Wang Hai , Zhou Chu , Liu Adi , Xie Jinlin , Li Hong , Ding Weixing , Liu Wandong
Published: December 2024

The electromagnetic turbulence in reversed field pinch (RFP) plasmas exhibits three-dimensional characteristics. Suppression of this turbulence is crucial for enhancing plasma confinement, necessitating control over the electric field or the current profile. To this end, two sets of electrodes have been designed and installed on the Keda Torus eXperiment (KTX) RFP device to manipulate the edge electric field and the edge parallel current profile. Subsequently, the edge radial electric field and edge parallel current profile control experiments are conducted. In the edge radial electric field control experiments, the edge radial electric field is altered under bias, accompanied with an increase in the electron density and plasma duration. However, under bias, both electrostatic and magnetic fluctuations are enhanced. In the edge parallel current profile control experiments, the results indicate that bias modifies the edge parallel current profile locally, leading to a localized increase in the field reversal depth and electron density. Additionally, a reduction in magnetic fluctuations is observed within the reversed field enhanced region under bias, suggesting that the bias suppresses magnetic perturbations.
Associations of severe climate conditions and race/ethnic-specific ischemic heart disease mortality among middle-aged adults in the United States
Authors: Majeed Haris , Majeed Hamnah , Moss Emmanuel , Cecere Renzo , Wong Evan G
Published: December 2024

Ischemic heart disease (IHD) is the leading cause of death worldwide. In the United States, IHD deaths affect millions of adults, with substantial age and race/ethnic-specific variability. In recent years, emphasis has been placed on reducing the rate of IHD events among middle-aged adults. Non-Hispanic (NH) Black populations are known to have greater IHD mortality rates compared to other races/ethnicities. Researchers have established several biological, clinical, and socioeconomic IHD risk factors, but severe climate conditions have not been explored by race/ethnicity among middle-aged adults. Using generalized linear models, this study documents associations between the Palmer Drought Severity Index and race/ethnic-specific IHD mortality rates from January 1999 to December 2020 among middle-aged adults across four census regions of the United States. When controlling for covariates, we found that during months of severe droughts (in comparison to neutral phases) IHD mortality rates had an increased risk for NH Whites (RR 1.017, P = 0.017) and NH Blacks (RR 1.029, P = 0.015). Furthermore, we found that surface air temperature is a modifier, where during warm periods (⩾20 °C) throughout the United States, severe drought months exacerbated the risk of IHD mortality rates among NH White (RR 1.024, P = 0.007) and NH Blacks (RR 1.033, P = 0.039). Further studies are needed to understand the mechanism between severe climate conditions and race/ethnic-specific IHD events.
Modeling the impact of electric vehicle adoption and charging strategies in ERCOT
Authors: Murillo Sara , Potts Jerry , Castellanos Sergio
Published: December 2024

Electric vehicle (EV) deployment provides an opportunity to reduce emissions in Texas, which has the greatest transportation emissions in the United States. This study aims to evaluate the impact of light-duty EV (LDEV) adoption through a capacity expansion model of the Texas power grid (Electric Reliability Council of Texas, ERCOT). Particularly, this work investigates how various LDEV adoption rates and charging strategies (i.e., managed and unmanaged) affect the electricity generation capacity mix, hourly dispatch, transmission capacity, carbon emissions, and costs in ERCOT. Our findings show that unmanaged charging strategies can lead to 30%–70% cumulative tailpipe CO2 emission reductions in the power and transportation sectors by 2050, depending on whether the LDEV adoption is 50% or 100%, respectively. These CO2 reductions are associated with 2.5%–6.7% increases in total power system costs compared to a scenario with no EV adoption. Furthermore, we find that managed charging can lead to 10% less transmission capacity compared to unmanaged charging in the complete LDV electrification scenarios. These results indicate that policies incentivizing EV adoption and managed charging strategies can facilitate sustainable decarbonization in the transportation sector while minimally increasing costs relative to a scenario without increased EV adoption.
A role for the kinetochore protein, NUF2, in ribosome biogenesis
Authors: brown ty j. , Pichurin Jennifer , Parrado Carlos Ramirez , Kabeche Lilian , Baserga Susan J.
Published: December 2024

Ribosome biogenesis (RB) is an intricate and evolutionarily conserved process that takes place mainly in the nucleolus and is required for eukaryotic cells to maintain homeostasis, grow in size, and divide. Our laboratory has identified the NUF2 protein, part of the mitotic kinetochore, in a genome-wide siRNA screen for proteins required for making ribosomes in MCF10A human breast epithelial cells. After rigorous validation and using several biochemical and cell-based assays, we find a role for NUF2 in pre-rRNA transcription, the primary and rate-limiting step of RB. siRNA depletion of other components of the NUF2 kinetochore sub-complex, NDC80, SPC24, and SPC25, also reduce pre-rRNA transcription. Interestingly, essential protein components for pre-rRNA transcription, including the largest subunit of RNA polymerase I, POLR1A, are reduced upon siRNA depletion of NUF2 and its protein partners. Their reduced levels are a likely mechanism for the decrease in pre-rRNA transcription. siRNA depletion of NUF2 and NDC80 also cause increased TP53 and CDKN1A (p21) mRNA levels, which can be restored by codepletion of RPL5, indicating activation of the nucleolar stress pathway (NSP). These results reveal a new connection between proteins with a known role in mitosis to the function of the nucleolus in RB during interphase.
How many L2 word meanings can learners recall? A latent trait approach to vocabulary size estimation
Authors: Hamada Akira , Hoshino Yuko , Kojima Masumi , Aizawa Kazumi , Iso Tatsuo , Kobayashi Yuichiro
Published: December 2024

This study investigated the size of meaning-recall vocabulary knowledge and its variations across word-frequency and second language (L2) proficiency levels. Despite the extensive research history in determining lexical coverage and thresholds for effective L2 use, much of the evidence is based on measures of meaning-recognition vocabulary knowledge. Using a latent-trait approach, we calculated the probability that learners could recall the meaning of each word in a vocabulary size test. Differences in vocabulary size between recognition and recall formats were analyzed across word-frequency bands and L2 proficiency levels. Results indicate that most learners struggle to recall the meanings of word families beyond the second-most frequent band. Moreover, the gap between meaning-recall and meaning-recognition vocabulary sizes was substantial and expanded as word-frequency and L2 proficiency levels decreased. These findings contribute to defining realistic L2 vocabulary teaching goals and selecting appropriate teaching methods. Construct-irrelevant measurements lead to a misunderstanding of L2 lexical proficiency, emphasizing the importance of test format selection according to the developmental stages of learners’ vocabulary knowledge.
Reasons and reasoning in arbitral awards
Authors: Thong Eugene , Guo Yvonne
Published: December 2024

While the need for international arbitral awards to be supported by reasons appears self-evident, a closer analysis of relevant treaty and statutory provisions as well as tribunal practice reveals a surprising lack of consensus as to the extent to which arbitral awards should be reasoned. Through an analysis of the factors for and against reasoned awards and the reasons for the evolution towards reasoned awards in international arbitration, this article considers the practical implications of dispensing with such reasons and analyses what standard of reasoning is generally recommended in arbitral awards. It concludes with several broad principles on the recommended standard of reasoning which would enable parties to an arbitration to know the basis upon which a decision was made and allow for the decision’s review by national courts.
CDCM: a correlation-dependent connectivity map approach to rapidly screen drugs during outbreaks of infectious diseases
Authors: Liao Junlei , Yi Hongyang , Wang Hao , Yang Sumei , Jiang Duanmei , Huang Xin , Zhang Mingxia , Shen Jiayin , Lu Hongzhou , Niu Yuanling
Published: December 2024

In the context of the global damage caused by coronavirus disease 2019 (COVID-19) and the emergence of the monkeypox virus (MPXV) outbreak as a public health emergency of international concern, research into methods that can rapidly test potential therapeutics during an outbreak of a new infectious disease is urgently needed. Computational drug discovery is an effective way to solve such problems. The existence of various large open databases has mitigated the time and resource consumption of traditional drug development and improved the speed of drug discovery. However, the diversity of cell lines used in various databases remains limited, and previous drug discovery methods are ineffective for cross-cell prediction. In this study, we propose a correlation-dependent connectivity map (CDCM) to achieve cross-cell predictions of drug similarity. The CDCM mainly identifies drug–drug or disease–drug relationships from the perspective of gene networks by exploring the correlation changes between genes and identifying similarities in the effects of drugs or diseases on gene expression. We validated the CDCM on multiple datasets and found that it performed well for drug identification across cell lines. A comparison with the Connectivity Map revealed that our method was more stable and performed better across different cell lines. In the application of the CDCM to COVID-19 and MPXV data, the predictions of potential therapeutic compounds for COVID-19 were consistent with several previous studies, and most of the predicted drugs were found to be experimentally effective against MPXV. This result confirms the practical value of the CDCM. With the ability to predict across cell lines, the CDCM outperforms the Connectivity Map, and it has wider application prospects and a reduced cost of use.
Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes
Authors: Llaneza-Lago Sergio , Fraser William D , Green Darrell
Published: December 2024

Identification of cancer subtypes is a critical step for developing precision medicine. Most cancer subtyping is based on the analysis of RNA sequencing (RNA-seq) data from patient cohorts using unsupervised machine learning methods such as hierarchical cluster analysis, but these computational approaches disregard the heterogeneous composition of individual cancer samples. Here, we used a more sophisticated unsupervised Bayesian model termed latent process decomposition (LPD), which handles individual cancer sample heterogeneity and deconvolutes the structure of transcriptome data to provide clinically relevant information. The work was performed on the pediatric tumor osteosarcoma, which is a prototypical model for a rare and heterogeneous cancer. The LPD model detected three osteosarcoma subtypes. The subtype with the poorest prognosis was validated using independent patient datasets. This new stratification framework will be important for more accurate diagnostic labeling, expediting precision medicine, and improving clinical trial success. Our results emphasize the importance of using more sophisticated machine learning approaches (and for teaching deep learning and artificial intelligence) for RNA-seq data analysis, which may assist drug targeting and clinical management.
NLSDeconv: an efficient cell-type deconvolution method for spatial transcriptomics data
Authors: Chen Yunlu , Ruan Feng , Wang Ji-Ping
Published: December 2024

Spatial transcriptomics (ST) allows gene expression profiling within intact tissue samples but lacks single-cell resolution. This necessitates computational deconvolution methods to estimate the contributions of distinct cell types. This article introduces NLSDeconv, a novel cell-type deconvolution method based on non-negative least squares, along with an accompanying Python package. Benchmarking against 18 existing deconvolution methods on various ST datasets demonstrates NLSDeconv’s competitive statistical performance and superior computational efficiency.

Availability and implementation

NLSDeconv is freely available at https://github.com/tinachentc/NLSDeconv as a Python package.
Changes in skin research funding: the emergence of environmental sustainability criteria in the research competition assessment process
Authors: Badawy Hannah , Harvey Jane , Rajan Neil , Stuart Beth , Tso Simon
Published: December 2024

Our study highlighted a drive for funders to embed (or consider incorporating) environmental sustainability criteria in their research competition assessment process. This development is highly relevant to skin research communities in the UK and internationally. Funders are in the unique position to shape the direction of research and mandate potential applicants to engage with all aspects of the research competition assessment process, including environmental impact. Our study highlights the need for research communities, especially early career researchers, to increase their preparedness to integrate environmental sustainability in designing, delivering and disseminating their research.
C21ORF2 mutations point towards primary cilia dysfunction in amyotrophic lateral sclerosis
Authors: De Decker Mathias , Zelina Pavol , Moens Thomas G , Beckers Jimmy , Contardo Matilde , Dittlau Katarina Stoklund , Van Schoor Evelien , Ronisz Alicja , Eggermont Kristel , Moisse Matthieu , Chandran Siddharthan , Veldink Jan H , Thal Dietmar Rudolf , Van Den Bosch Ludo , Pasterkamp R Jeroen , Van Damme Philip
Published: December 2024

Progressive loss of motor neurons is the hallmark of the neurodegenerative disease amyotrophic lateral sclerosis (ALS), but the underlying disease mechanisms remain incompletely understood. In this study, we investigate the effects of C21ORF2 mutations, a gene recently linked to ALS, and find that primary cilia are dysfunctional. Human patient-derived mutant C21ORF2 motor neurons have a reduced ciliary frequency and length.

We report that C21ORF2 is located at the basal body of the primary cilium, and mutations associated with ALS alter this localization. Furthermore, we show that a reduction of C21ORF2 levels in cell lines and motor neurons is sufficient to cause fewer primary cilia and reduced cilial length. This ciliary dysfunction leads to defective downstream sonic hedgehog signalling and reduces the expression of cellular retinoic acid binding protein 1 (CRABP1), a protein involved in motor neuron maintenance and survival.

In a compartmentalized co-culture system of motor neurons and muscle cells, these ciliary defects were associated with a reduced ability of neuromuscular junction formation. Interestingly, these cilia defects are seemingly not restricted to C21ORF2 ALS, as we also observed perturbed primary cilia in cultured motor neurons and post-mortem motor cortex from patients with the most common genetic subtype of ALS caused by repeat expansions in the C9ORF72 gene. Finally, overexpression of C21ORF2 in mutant C21ORF2 motor neurons rescued the ciliary frequency and length, CRAPBP1 expression and neuromuscular junction formation, confirming the importance of primary cilia for motor neuron function.

These results point towards primary cilia dysfunction contributing to motor neuron degeneration in ALS and open new avenues for further research and interventions for this as yet untreatable disease.
Influence of self-assembling nonsubstrates on the enzymatic postmodification of peptide supramolecules
Authors: Higuchi Ayato , Wakabayashi Rie , Kawamura Izuru , Goto Masahiro , Kamiya Noriho
Published: December 2024

The enzymatic postmodification of supramolecules with functional motifs is a promising approach for preparing tailor-made bioactive materials. We attempted to improve the enzyme reactivity of the previously developed, self-assembling aromatic peptide amphiphile, Fmoc-L3QG, by incorporating other self-assembling components, Fmoc-Ln (n = 2, 3), without the enzyme recognition moiety. Although microscopic and spectroscopic studies suggested neither the nonsubstrate peptide amphiphile coassembled with Fmoc-L3QG, the presence of the short fibril–forming Fmoc-L2 and long fibril–forming Fmoc-L3 increased and decreased, respectively, the enzymatic reactivity of Fmoc-L3QG. The findings here suggest that the supramolecular morphologies play a role in modulating the enzyme reaction environment.
Post-pubertal effects of the Face Mask Protocol with and without Bite Block appliance in the orthopedic treatment of Class III malocclusion: a comparative evaluation
Authors: Gazzani Francesca , Rosa Marco , Manti Giuseppe , De Razza Francesca Chiara , Pavoni Chiara , Cozza Paola , Lione Roberta
Published: December 2024

Objectives

The purpose of this retrospective study was to compare the dento-skeletal changes observed in growing Class III patients treated with the Face Mask Protocol (FMP) with and without Bite Block (BB).

Materials

Thirty subjects (12 f, 18 m) who underwent FM/BB therapy were compared to a matched group (FM) of 29 patients (15 f, 14 m) treated without BB. All patients were evaluated before treatment (T0), at the end of active treatment (T1), and at a post-pubertal follow-up observation (T2). A control group (CG) of 20 subjects (10 f, 10 m) with untreated Class III disharmony was used for the comparison of post-pubertal changes. Intergroup statistical comparisons were performed with the independent samples t-test (P < .05).

Results

The comparison between treated samples showed a significant improvement of SN^GoGn (FM/BB vs FM, −2.1°), Overbite (FM/BB vs FM, +1.2 mm), and vertical position of lower molars FM/BB vs FM, −3 mm). When compared with the controls, both treated groups revealed a significant improvement of SNA (FM/BB, +1.8°; FM +2.1°), ANB (FM/BB +1.6°, FM +2.4°), gonial angle (FM/BB −4.9°; FM −4°), incisor inclination (Upper, FM/BB +1.7°, FM +2.3°; Lower, FM/BB −2.5°, FM −2.7°), and Overjet (FM/BB +3.2 mm; FM +4 mm). Improvement of SN^GoGn (−2.1°), Overbite (+1.8 mm), and vertical position of lower molars (−3.8 mm) were observed when FM/BB was compared with CG.

Limitations

Limitations are related to the difficulty to recruit a larger contemporary long-term control group due to ethical reasons.

Conclusion

Both FM protocols induced favorable changes in the treatment of Class III malocclusion with a good post-pubertal stability. The BB allows a more efficient control of the vertical skeletal relationship.
CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans
Authors: Perez Marcos Francisco
Published: December 2024

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs—∼58% of the total—from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.
cfDNA UniFlow: a unified preprocessing pipeline for cell-free DNA data from liquid biopsies
Authors: Röner Sebastian , Burkard Lea , Speicher Michael R , Kircher Martin
Published: December 2024

Background

Cell-free DNA (cfDNA), a broadly applicable biomarker commonly sourced from urine or blood, is extensively used for research and diagnostic applications. In various settings, genetic and epigenetic information is derived from cfDNA. However, a unified framework for its processing is lacking, limiting the universal application of innovative analysis strategies and the joining of data sets.

Findings

Here, we describe cfDNA UniFlow, a unified, standardized, and ready-to-use workflow for processing cfDNA samples. The workflow is written in Snakemake and can be scaled from stand-alone computers to cluster environments. It includes methods for processing raw genome sequencing data as well as specialized approaches for correcting sequencing errors, filtering, and quality control. Sophisticated methods for detecting copy number alterations and estimating and correcting GC-related biases are readily incorporated. Furthermore, it includes methods for extracting, normalizing, and visualizing coverage signals around user-defined regions in case-control settings. Ultimately, all results and metrics are aggregated in a unified report, enabling easy access to a wide variety of information for further research and downstream analysis.

Conclusions

We provide an automated pipeline for processing cell-free DNA sampled from liquid biopsies, including a wide variety of additional functionalities like bias correction and signal extraction. With our focus on scalability and extensibility, we provide a foundation for future cfDNA research and faster clinical applications. The source code and extensive documentation are available on our GitHub repository (https://github.com/kircherlab/cfDNA-UniFlow).
Diaci v3.0: chromosome-level assembly, de novo transcriptome, and manual annotation of Diaphorina citri, insect vector of Huanglongbing
Authors: Shippy Teresa D , Hosmani Prashant S , Flores-Gonzalez Mirella , Mann Marina , Miller Sherry , Weirauch Matthew T , Vosberg Chad , Massimino Crissy , Tank Will , de Oliveira Lucas , Chen Chang , Hoyt Stephanie , Adams Rebekah , Adkins Samuel , Bailey Samuel T , Chen Xiaoting , Davis Nina , DeLaFlor Yesmarie , Espino Michelle , Gervais Kylie , Grace Rebecca , Harper Douglas , Hasan Denisse L , Hoang Maria , Holcomb Rachel , Jernigan Margaryta R , Kemp Melissa , Kennedy Bailey , Kercher Kyle , Klaessan Stefan , Kruse Angela , Licata Sophia , Lu Andrea , Masse Ron , Mathew Anuja , Michels Sarah , Michels Elizabeth , Neiman Alan , Norman Seantel , Norus Jordan , Ortiz Yasmin , Panitz Naftali , Paris Thomson , Perentesis Kitty M R , Perry Michael , Reynolds Max , Sena Madison M , Tamayo Blessy , Thate Amanda , Vandervoort Sara , Ventura Jessica , Weis Nicholas , Wise Tanner , Shatters Robert G , Heck Michelle , Benoit Joshua B , Hunter Wayne B , Mueller Lukas A , Brown Susan J , D'Elia Tom , Saha Surya
Published: December 2024

Background

Diaphorina citri is an insect vector of “Candidatus Liberibacter asiaticus” (CLas), the gram-negative bacterial pathogen associated with citrus greening disease. Control measures rely on pesticides with negative impacts on the environment, natural ecosystems, and human and animal health. In contrast, gene-targeting methods have the potential to specifically target the vector species and/or reduce pathogen transmission.

Results

To improve the genomic resources needed for targeted pest control, we assembled a D. citri genome based on PacBio long reads followed by proximity ligation-based scaffolding. The 474-Mb genome has 13 chromosomal-length scaffolds. In total, 1,036 genes were manually curated as part of a community annotation project, composed primarily of undergraduate students. We also computationally identified a total of 1,015 putative transcription factors (TFs) and were able to infer motifs for 337 TFs (33%). In addition, we produced a genome-independent transcriptome and genomes for D. citri endosymbionts.

Conclusions

Manual annotation provided more accurate gene models for use by researchers and provided an excellent training opportunity for students from multiple institutions. All resources are available on CitrusGreening.org and NCBI. The chromosomal-length D. citri genome assembly serves as a blueprint for the development of collaborative genomics projects for other medically and agriculturally significant insect vectors.
Parsimonious Green function data bases for global centroid moment tensor inversions
Authors: Sawade Lucas , Ekström Göran , Ding Liang , Nettles Meredith , Tromp Jeroen
Published: December 2024

The calculation of synthetic seismograms for global centroid moment tensor (GCMT) inversions relies on advanced 3-D Earth models. However, use of the path-average approximation for mode summation and surface-wave ray theory limits the method’s accuracy. This can cause incorrect predictions of ground motion amplitude and polarization, and other unaccounted-for effects, which can bias the estimated earthquake parameters. To address this issue, we have developed a new and efficient way to calculate, store and access high-fidelity, long-period synthetic seismograms for state-of-the-art 3-D tomographic Earth models. We adapted the spectral-element wave-equation solver SPECFEM3D_GLOBE to generate a data base of Green functions on a global, sparse spectral-element grid of hypocenters for a large set of 180 station locations, using source–receiver reciprocity to speed up the calculation. The seismograms are organized and stored in a format that facilitates rapid access to a particular source region and stations of the Global Seismographic Network. Seismograms for any centroid location can be calculated efficiently via spatial interpolation without losing accuracy compared to full forward calculation. As a proof-of-concept, we perform $\sim$9000 CMT inversions using the Sawade et al. approach, with GCMT solutions as starting models and without restriction on the number of iterations. Although the location updates are consistent with Sawade et al., we find a reduction in non-double-couple components in all types of events except for shallow strike-slip events. Given these encouraging results for future routine implementation, we present a first test and an outlook for routine 3-D GCMT analysis.
Vel maiorum relatio uel librorum reuolutio: oral informants and information in the works of William of Malmesbury
Authors: Liu Ming
Published: December 2024

This paper explores the information provided by William of Malmesbury’s oral informants that he recorded in his works. It argues that older monks and the transmission of oral traditions at his own monastery, ecclesiastics from the host communities which he had visited, Norman nobles with whom he was familiar and common people he had encountered during his travels were all important oral sources for his writings. His interaction with his different informants brought both advantages and disadvantages, but William was still cautious about relying on hearsay and possible rumours, which shows his ‘subjective initiative’ in dealing with oral materials.