bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-pass whole genome sequencing of circulating tumor cells to evaluate chromosomal instability in triple-negative breast cancer
Authors: Di Cosimo Serena , Silvestri Marco , De Marco Cinzia , Calzoni Alessia , De Santis Maria Carmen , Carnevale Maria Grazia , Reduzzi Carolina , Cristofanilli Massimo , Cappelletti Vera 
Published: September 2024

AbstractChromosomal Instability (CIN) is a common and evolving feature in breast cancer. Large-scale Transitions (LSTs), defined as chromosomal breakages leading to gains or losses of at least 10 Mb, have recently emerged as a metric of CIN due to their standardized definition across platforms. Herein, we report the feasibility of using low-pass Whole Genome Sequencing to assess LSTs, copy number alterations (CNAs) and their relationship in individual circulating tumor cells (CTCs) of triple-negative breast cancer (TNBC) patients. Initial assessment of LSTs in breast cancer cell lines consistently showed wide-ranging values (median 22, range 4–33, mean 21), indicating heterogeneous CIN. Subsequent analysis of CTCs revealed LST values (median 3, range 0–18, mean 5), particularly low during treatment, suggesting temporal changes in CIN levels. CNAs averaged 30 (range 5–49), with loss being predominant. As expected, CTCs with higher LSTs values exhibited increased CNAs. A CNA-based classifier of individual patient-derived CTCs, developed using machine learning, identified genes associated with both DNA proliferation and repair, such as RB1, MYC, and EXO1, as significant predictors of CIN. The model demonstrated a high predictive accuracy with an Area Under the Curve (AUC) of 0.89. Overall, these findings suggest that sequencing CTCs holds the potential to facilitate CIN evaluation and provide insights into its dynamic nature over time, with potential implications for monitoring TNBC progression through iterative assessments.
Heritability of carotid intima-media thickness and inflammatory factors of atherosclerosis in a Chinese population
Authors: Li Tsai-Chung , Lin Cheng-Chieh , Liu Chiu-Shong , Lin Chih-Hsueh , Yang Shing-Yu , Li Chia-Ing 
Published: September 2024

AbstractCarotid intima-media thickness (cIMT), a marker of subclinical atherosclerosis, has been found to be associated with incident stroke. High-sensitivity C-reactive protein (CRP) and fibrinogen have been demonstrated to be associated with atherosclerosis. Previous studies on heritability estimates of IMT, CRP, and fibrinogen among Chinese populations are limited. This study aims to estimate the heritability of these risk factors in residents who participated in the Taichung Community Health Study (TCHS) and their family members. A total of 2671 study subjects from 805 families were enrolled in the study, selected from a random sample of TCHS participants and their family members. CRP, and fibrinogen were obtained from each participant, and a questionnaire interview was conducted. cIMT was measured by high-resolution B-mode ultrasound and expressed as the mean of the maximum. Heritability estimates and the familial correlation of cIMT, CRP, and fibrinogen among family pairs were determined with SAGE software. With multivariate adjustments, significant heritability was found for cIMT (h2 = 0.26, P < 0.001), CRP (h2 = 0.34, P < 0.001), and fibrinogen (h2 = 0.48, P < 0.001). The intrafamilial correlation coefficients for the three indexes in the parent–offspring pairs were significant (P < 0.001) and ranged from 0.17 to 0.41. The full sibship correlations were also significant (P < 0.001) for the three indexes and ranged from 0.19 to 0.47. This study indicates that a moderate proportion of the variability in CRP, fibrinogen, and cIMT can be attributed to genetic factors in Chinese populations. The findings suggest that CRP is associated with cIMT, whereas no significant association exists between fibrinogen and cIMT.
Leveraging the link between pro-environmental behaviour and well-being to encourage sustainable lifestyle shifts
Authors: Prinzing Michael M. , Laffan Kate 
Published: September 2024

AbstractFour studies investigated whether awareness of links between pro-environmental behaviour (PEB) and well-being can motivate sustainable lifestyle shifts. We find that most US adults believe most PEBs do not affect well-being. Yet, when people do expect such benefits, they tend to have more positive attitudes and intentions regarding PEBs and enact more PEBs. We also find that messages about how PEB can increase well-being consistently improved attitudes towards PEBs and made people more persuasive in their subsequent efforts to encourage others to live sustainably. These effects were especially pronounced among people who did not previously believe that PEB improves well-being. Effects on PEB intentions were inconsistent, however, and we found no effect on a revealed measure of PEB (i.e., seeking sustainability tips). Overall, these results underscore the importance of beliefs about PEBs’ impact on well-being and suggest that public messaging about that relationship might help motivate sustainable lifestyles.
A path splitting and pruning strategy on list decoder for PAC codes
Authors: Lan Lei , Wang Zhongpeng , Zhang Lijuan 
Published: September 2024

AbstractRecently, Arıkan proposed a polarization‐adjusted convolutional (PAC) codes, demonstrating their superior error correction performance over polar codes at short block lengths. It was confirmed that PAC codes approached the optimal performance achievable with limited code length. This paper proposes a novel low‐complexity list decoding algorithm for PAC codes, incorporating path splitting and pruning strategies based on a set of highly reliable information bits. Simulation results reveal that the proposed algorithm significantly reduces sorting complexity and average list size, all while incurring negligible performance loss. Unlike previous pruning algorithms designed for polar codes, the proposed strategy eliminates the need to individually assess the reliability of decoding paths in each decoding process. Instead, the algorithm minimizes redundant decoding paths through a high‐reliability information bit set, constructed using Monte Carlo experiments.
Enhancing 5G energy efficiency through digital twin networks: A comprehensive review
Authors: Maiwada Umar Danjuma , Danyaro Kamaluddeen Usman , Sarlan Aliza Bt 
Published: September 2024

AbstractIn the era of 5G, seamless mobility handovers are critical in densely populated regions like Malaysia to mitigate disruptions and inefficiencies. 5G networks offer unprecedented data speeds and reliability, essential for advancing mobile communication and Internet of Things applications. However, ensuring continuous connectivity and service during mobility remains challenging, especially in urban settings. Digital twin technology presents a promising solution to enhance 5G handover mechanisms. A digital twin network (DTN) mirroring Malaysia's 5G infrastructure is proposed, utilising real‐time data and user behaviour insights to optimise energy consumption during handovers. The focus is on energy‐efficient protocols and algorithms, reviewed through a systematic literature review. The DTN aims to enhance mobility handover efficiency through predictive handovers and adaptive resource allocation, bolstered by sustainable practices such as edge computing. The potential of DTNs to optimise 5G handover processes is explored, starting with the foundational concepts of 5G mobility and digital twins, highlighting the need for improved strategies in high‐mobility scenarios. Methodologies leveraging digital twins to predict network conditions, simulate handover scenarios, and proactively manage decisions are examined, reducing latency and packet loss. Case studies demonstrate how digital twins adapt dynamically to network changes and user mobility, thereby improving quality of service and user experience. Malaysia's specific 5G mobility challenges are addressed with a tailored DTN emphasising energy efficiency, evaluated through practical applications. Evaluation criteria assess effectiveness with in‐depth analysis of methods, performance metrics, limitations, and recommendations for future research. Challenges and future directions including scalability, security, and real‐time data processing, are discussed, aiming to integrate digital twin technology with 5G networks for enhanced connectivity. This abstract provides a roadmap for leveraging digital twins to optimise 5G network performance sustainably, guiding future research and implementation strategies.
Hi‐Z fault location identification on low voltage distribution systems using IoT‐based digital twin model computation
Authors: Pamulaparthy Balakrishna 
Published: September 2024

AbstractDistribution feeders carry and supply power to industrial, commercial and residential loads from the point where sub‐transmission (33 kV level) ends after stepping down to suitable voltages, such as 11 kV and further down to 400/230 V. In recent times, high impedance (Hi‐Z) faults on distribution systems are creating unique challenges to utilities both from operational and safety perspectives. Most of these Hi‐Z faults occur at distribution voltages of 15 kV or below, with the problem being worse at lower voltages. Hi‐Z fault detection technologies emerged and were developed and incorporated on embedded platforms, such as relays, reclosers and sensors, which protect and monitor distribution systems. Although these technologies can detect Hi‐Z fault on feeders, most of them cannot identify the exact location of the fault. Specifically, there is no solution available in literature for detecting Hi‐Z fault location on low voltage (LV) circuits like 3‐phase 4‐wire 400 V distribution network. In this paper, we introduce a novel and a unique algorithm to identify the location of Hi‐Z faults using proposed smart metres IoT data‐based distribution system load flow and digital twin model representation of the network. Furthermore, a case study on the standard 33 bus LV system clearly depicts the functionality of the proposed algorithm.
Atten‐SEVNETR for volumetric segmentation of glioblastoma and interactive refinement to limit over‐segmentation
Authors: Kundu Swagata , Toumpanakis Dimitrios , Wikstrom Johan , Strand Robin , Dhara Ashis Kumar 
Published: September 2024

AbstractPrecise localization and volumetric segmentation of glioblastoma before and after surgery are crucial for various clinical purposes, including post‐surgery treatment planning, monitoring tumour recurrence, and creating radiotherapy maps. Manual delineation is time‐consuming and prone to errors, hence the adoption of automated 3D quantification methods using deep learning algorithms from MRI scans in recent times. However, automated segmentation often leads to over‐segmentation or under‐segmentation of tumour regions. Introducing an interactive deep‐learning tool would empower radiologists to rectify these inaccuracies by adjusting the over‐segmented and under‐segmented voxels as needed. This paper proposes a network named Atten‐SEVNETR, that has a combined architecture of vision transformers and convolutional neural networks (CNN). This hybrid architecture helps to learn the input volume representation in sequences and focuses on the global multi‐scale information. An interactive graphical user interface is also developed where the initial 3D segmentation of glioblastoma can be interactively corrected to remove falsely detected spurious tumour regions. Atten‐SEVNETR is trained on BraTS training dataset and tested on BraTS validation dataset and on Uppsala University post‐operative glioblastoma dataset. The methodology outperformed state‐of‐the‐art networks like nnFormer, SwinUNet, and SwinUNETR. The mean dice score achieved is 0.7302, and the mean Hausdorff distance‐95 got is 7.78 mm for the Uppsala University dataset.
VENICE: A multi-scale operator-splitting algorithm for multi-physics simulations
Authors: Wilhelm Maite J. C. , Portegies Zwart S. 
Published: September 2024

Context. We present VENICE, an operator-splitting algorithm to integrate a numerical model on a hierarchy of timescales.
Aims. VENICE allows a wide variety of different physical processes operating on different scales to be coupled on individual and adaptive time-steps. It therewith mediates the development of complex multi-scale and multi-physics simulation environments with a wide variety of independent components.
Methods. The coupling between various physical models and scales is dynamic, and realised through (Strang) operators splitting using adaptive time-steps.
Results. We demonstrate the functionality and performance of this algorithm using astrophysical models of a stellar cluster, first coupling gravitational dynamics and stellar evolution, then coupling internal gravitational dynamics with dynamics within a galactic background potential, and finally combining these models while also introducing dwarf galaxy-like perturbers. These tests show numerical convergence for decreasing coupling timescales, demonstrate how VENICE can improve the performance of a simulation by shortening coupling timescales when appropriate, and provide a case study of how VENICE can be used to gradually build up and tune a complex multi-physics model. Although the examples provided here couple dedicated numerical models, VENICE can also be used to efficiently solve systems of stiff differential equations.
Near-infrared spectral behavior of space-weathered olivine with varying iron content
Authors: Wang Ziyu , Lin Honglei , Ye Binlong , Zhao Yu-Yan Sara , Qi Chao , Xu Jingyan , Wei Yong 
Published: September 2024

Context. Space weathering alters the surfaces of airless celestial bodies, thereby modifying their spectra significantly. Olivine plays a crucial role in responding to space weathering on silicate planets. However, the spectral variations that occur in olivine with varying iron content as a result of space weathering conditions remain unclear.
Aims. We aim to systematically characterize the spectral variability of surface iron-rich olivine in the space weathering environments of Phobos and the Moon.
Methods. We conducted nanosecond pulsed laser irradiation experiments on a set of synthetic Fe-rich olivine (Fa29, Fa50, Fa71, and Fa100). The energy levels were simulated for Phobos and the Moon. We analyzed the available near-infrared (NIR) spectroscopy.
Results. We find that olivine with higher Fe content undergoes stronger weathering under the same irradiation energy, shifting absorption centers around 1.08 µm and 1.35 µm to longer wavelengths. When comparing the high energy and low frequency, spectral changes are more pronounced at low energy and high frequency. The olivine with the same iron content exhibits a more noticeable shift around 1.08 µm under various irradiation levels, while the band center around 1.35 µm remains stable.
Conclusions. When the same amount of radiation energy is received, changes in the spectrum are more noticeable at low energy and high impact frequency than at high energy and low impact frequency. The absorption position at ~1.35 µm is a good indicator of the Mg# value of space-weathered olivine.
Barred active galactic nucleus galaxies in paired systems: Exploring the impact on nuclear activity
Authors: Alonso Sol , Vera-Rueda Matias , Coldwell Georgina , Duplancic Fernanda , Mesa Valeria 
Published: September 2024

Aims. To unveil the influence of galaxy-galaxy interactions on the material transport driven by galactic bars toward the central regions of active galactic nucleus (AGN) galaxies, and to assess the efficiency of the combined mechanisms of interactions and bars in fueling massive black holes, we meticulously examine barred active galaxies in paired systems.
Methods. Our study focuses on barred AGN galaxies in pairs with projected separations of rp < 100 kpc h−1 and relative radial velocities of ΔV < 500 km s−1 within z < 0.1, identified by the Sloan Digital Sky Survey (SDSS). To quantify the impact of interactions on material transport by galactic bars, we also constructed a suitable control sample of barred active galaxies without paired companions, matched in redshift, absolute r-band magnitude, stellar mass, color, and stellar age distributions. Additionally, we calculated the structural characteristics of galactic bars through two-dimensional image modeling, considering that bars exhibit a wide range of shapes and sizes, which may influence their ability to channel material.
Results. From this study, we clearly found that nuclear activity (derived from the Lum[OIII]) increases as the projected separations between galaxy pair members decrease. Notably, barred AGN galaxies in close pairs (rp ⪅ 25 kpc h−1) exhibit significantly higher nuclear activity compared to galaxies in the control sample. Additionally, barred galaxies with a close pair companion show enhanced nuclear activity across all ranges of luminosity, stellar mass, and color. We also found that barred AGN galaxies with longer bar structures exhibit more efficient nuclear activity compared to those with shorter bars. This trend is especially pronounced in barred AGN galaxies within close pair systems, which show a significant excess of high Lum[OIII] values. Furthermore, we examined the central nuclear activity in barred AGNs undergoing major and minor interactions. Our findings show a clear escalation in nuclear activity as the pair projected separations decrease, particularly pronounced in major systems. Additionally, nuclear activity distributions in barred AGN samples within major and minor pairs exhibit similar trends. However, a significant deviation occurs among barred AGN galaxies in close pair systems within major interactions, showing a substantial excess of high Lum[OIII] values. This result is also reflected in the analysis of the accretion strength onto central black holes. These findings indicate that external perturbations from a nearby galaxy companion can influence gas flows induced by galactic bars, leading to increased nuclear activity in barred AGN galaxies within pair systems. Thus, the coexistence of both – bars and interactions – significantly amplifies central nuclear activity, thereby influencing the accretion processes onto massive black holes.
Recurrence following successful eradication of neoplasia with endoscopic mucosal resection compared with endoscopic submucosal dissection in Barrett’s esophagus: a retrospective comparison
Authors: Fujiyoshi Yusuke , Khalaf Kareem , Tham Daniel , Fujiyoshi Mary Raina Angeli , Calo Natalia C. , Mosko Jeffrey D. , May Gary R. , Teshima Christopher W. 
Published: September 2024

Abstract
Background Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are effective treatments for Barrett’s neoplasia. However, little is known about recurrence rates following these techniques. We compared long-term neoplasia recurrence rates following EMR and ESD.
Methods This study included patients with Barrett’s neoplasia (high grade dysplasia/adenocarcinoma) treated between July 2019 and December 2023 at a tertiary referral center in Canada. Outcomes were residual neoplasia at first follow-up, complete remission of neoplasia (CRN), and neoplasia recurrence following CRN.
Results 157 patients were included (87 EMR, 70 ESD). Compared
with EMR, the ESD group had larger lesions (median 2 vs. 3 cm, P<0.05), more adenocarcinoma
(85.1% vs. 94.3%, P = 0.07), and deeper submucosal invasion (T1a: 71.6% vs. 75.8%; T1b-SM1:
25.7% vs. 6.1%; T1b≥SM2: 2.7% vs. 18.2%; P<0.05). Among 124 patients with follow-up (71
EMR, 53 ESD), 84.9% of ESD-treated patients had curative resections (i.e. R0 resection with
low risk for lymph node metastasis), whereas 94.4% of EMR-treated patients had deep margin R0
resection of low risk lesions. At first follow-up, residual neoplasia (14.1% vs. 11.3%) and
CRN (97.2% vs. 100%) were similar in the EMR and ESD groups, but neoplasia recurrence
following CRN was significantly higher with EMR (13% vs. 1.9%, P<0.05), with cumulative
probability of recurrence at 3 years of 18.3% vs. 4.2%, respectively.
Conclusions Neoplasia recurrence following CRN was significantly higher following EMR compared with ESD, suggesting that ESD may be superior to EMR in preventing neoplasia recurrence in Barrett’s esophagus.
Bedarfsanalyse für ein Selbsthilfetraining im Rahmen der Cochlea-Implantat-Rehabilitation
Authors: Geßner Sophie , Meuret Sylvia , Fuchs Michael , Tretbar Kathleen 
Published: September 2024

Zusammenfassung
Hintergrund Trotz Cochlea-Implantation erleben CI-Träger*innen Schwierigkeiten in anspruchsvollen Hörsituationen. Im deutschsprachigen Raum gibt es keinerlei Interventionen zur Förderung von gezielten Bewältigungsstrategien für derartige Situationen. Die vorliegende Studie untersucht die nach Implantation fortbestehenden Alltagseinschränkungen sowie die Relevanz potenzieller Interventionsinhalte, um ein Selbsthilfeprogramm für die CI-Rehabilitation zu entwickeln.
Material und Methoden Es wurden 56 CI-Träger*innen aus 3 deutschen CI-Zentren rekrutiert, die eine Online-Befragung zu demografischen Daten, zur Hörbiografie, zum Hörhandicap und zu potenziell relevanten Interventionsinhalten ausfüllten. Die präsentierten Interventionsinhalte umfassten dabei die folgenden Kategorien: medizinische Aspekte, Aspekte zur Kommunikationsverbesserung, psychosoziale Aspekte, technische Aspekte und spezifische Aspekte.
Ergebnisse Das Hörhandicap war in der vorliegenden Stichprobe moderat bis schwerwiegend ausgeprägt. Die vorgestellten Inhaltskategorien für die Gestaltung eines Selbsthilfeprogramms wurden alle als „wichtig“ eingestuft. Die Dauer der CI-Versorgung korrelierte signifikant negativ mit der Einschätzung der Relevanz von psychosozialen Aspekten. Weitere signifikante Zusammenhänge konnten zwischen der Ausprägung des Hörhandicaps und der Einschätzung der Relevanz von Aspekten zur Kommunikationsverbesserung sowie psychosozialer und technischer Aspekte aufgezeigt werden.
Schlussfolgerung Ein Selbsthilfeprogramm, das die untersuchten Inhalte berücksichtigt, könnte eine vielversprechende Unterstützung für den CI-Rehabilitationsprozess darstellen und soll im Folgenden entwickelt sowie evaluiert werden.
Unraveling the Molecular Pathogenesis of Protein C Deficiency–Associated VTE: Insights from Protein C Mutations C238G and R189W in Thai Patients
Authors: Tanratana Pansakorn , Seanoon Karnsasin , Payongsri Panwajee , Kadegasem Praguywan , Chuansumrit Ampaiwan , Sirachainan Nongnuch 
Published: September 2024

Background Protein C (PC) deficiency is a well-established risk factor for thromboembolism (TE), commonly manifesting in pediatric patients. This study aimed to elucidate the pathogenic mechanisms of two novel PC mutations, C238G and R189W, identified in Thai children with both venous and arterial TE.
Material and Methods The effects of wild-type (WT), C238G, and R189W PC variants were investigated through transient transfection of HEK293T cells. PC secretion levels were measured, and immunofluorescence analysis was performed to assess intracellular localization. ER stress-related gene expression and UPR activation were evaluated. Structural analysis was conducted to explore the significance of the C238 and R189W residue in PC functionality.
Results The C238G mutation led to a severe 95% reduction in PC secretion, while R189W showed a 30% decrease compared with WT. Immunofluorescence revealed that C238G-PC was predominantly retained in the ER, indicating protein misfolding. C238G-expressing cells exhibited significant upregulation of ER stress-related genes and UPR activation. In contrast, R189W resulted in only a modest increase in UPR gene expression, suggesting a less pronounced impact on protein folding and secretion. Structural analysis demonstrated the critical role of the C238 residue in maintaining PC's disulfide bond and overall conformation.
Conclusion This study reveals distinct molecular mechanisms by which the C238G and R189W mutations contribute to PC deficiency and increased thrombotic risk. The findings emphasize the essential role of the C238 residue in preserving PC structure and secretion, enhancing the understanding of PC deficiency-associated TE in pediatric patients.