bluuebunny/crossref_metadata_2025_split huggingface dataset:
ICN-Leitlinien zur psychosozialen Pflege
Authors: Zuaboni Gianfranco , Burr Christian , Hahn Sabine , Meyer Michael , Rixe Jacqueline , Sauter Dorothea , Wagner Petra , Wolfensberger Peter , Wostry Florian , Zappe Robert 
Published: January 2025

Was ist zu diesem Thema bereits bekannt? Die Berufsgruppe der Pflege unterscheiden sich im internationalen Vergleich hinsichtlich Ausbildung, Arbeitsinhalte und -kompetenzen. Die ICN-Leitlinien beschreiben den aktuellen Bedarf für fachgerechte Pflege und dafür notwendige Konsequenzen für die Praxis und der Aus- und Weiterbildung psychiatrischer Pflege. Wie wird eine neue Perspektive eingebracht? Wir haben Fachpersonen aus Deutschland, Österreich und der Schweiz eingeladen, die potenziellen Auswirkungen der ICN-Leitlinien auf die einzelnen Länder zu bewerten. Was sind die Auswirkungen für die Praxis? Die Ablösung einer primär medizinisch-biologischen Ausrichtung in der psychiatrischen Pflege hin zu einem menschenrechtsbasierten, ganzheitlichen Ansatz stellt in allen drei Ländern eine zentrale Herausforderung dar. Der Entwicklungsstand der akademischen Pflege hinkt im internationalen Vergleich weiterhin hinterher.
Sensitivity of Chlorophyll Vertical Structure to Model Parameters in the Biogeochemical Southern Ocean State Estimate (B‐SOSE)
Authors: Kuhn Angela M. , Mazloff Matthew R. , Gille Sarah T. , Verdy Ariane 
Published: January 2025

AbstractThe Southern Ocean is a region of intense air–sea exchange that plays a critical role for ocean circulation, global carbon cycling, and climate. Subsurface chlorophyll‐a maxima, annually recurrent features throughout the Southern Ocean, may increase the energy flux to higher trophic levels and facilitate downward carbon export. It is important that model parameterizations appropriately represent the chlorophyll vertical structure in the Southern Ocean. Using BGC‐Argo chlorophyll profiles and the Biogeochemical Southern Ocean State Estimate (B‐SOSE), we investigate the sensitivity of chlorophyll vertical structure to model parameters. Based on the sensitivity analysis results, we estimate optimized parameters, which efficiently improve the model consistency with observations. We characterize chlorophyll vertical structure in terms of Empirical Orthogonal Functions and define metrics to compare model results and observations in a series of parameter perturbation experiments. We show that chlorophyll magnitudes are likely to respond quasi‐symmetrically to perturbations in the analyzed parameters, while depth and thickness of the subsurface chlorophyll maximum show an asymmetric response. Perturbing the phytoplankton growth tends to generate more symmetric responses than perturbations in the grazing rate. We identify parameters that affect chlorophyll magnitude, subsurface chlorophyll or both and discuss insights into the processes that determine chlorophyll vertical structure in B‐SOSE. We highlight turbulence, differences in phytoplankton traits, and grazing parameterizations as key areas for improvement in models of the Southern Ocean.
Who drives weight stigma? A multinational exploration of clustering characteristics behind weight bias against preconception, pregnant, and postpartum women
Authors: Hailu Haimanot , Incollingo Rodriguez Angela C. , Rodriguez Anthony , Skouteris Helen , Hill Briony 
Published: January 2025

Abstract

Background
Weight bias is a global health challenge and community members are endorsed as the most common source of weight bias. The nature of weight biases specifically against preconception, pregnant, and postpartum (PPP) women from the perspective of community members is not known, especially in terms of cross-cultural trends. We investigated the magnitude of explicit and implicit weight bias and profiles of characteristics associated with harbouring weight bias.

Methods
We conducted a multinational investigation of clusters of factors associated with weight bias against PPP women (May–July 2023). Community members from Australia, Canada, United States (US), United Kingdom (UK), Malaysia, and India completed a cross-sectional survey measuring explicit and implicit weight biases, beliefs about weight controllability, and awareness of sociocultural body ideals. Hierarchical multiple regression and latent profile analyses identified clusters of factors associated with weight bias.

Results
Participants from India reported the lowest explicit weight bias (B = −0.45, p = 0.02). Participants from Australia (B = −0.14, p = 0.04) and the UK (B = −0.16, p = 0.02) (vs. US) reported the lowest implicit weight bias. Three distinct profiles were identified clustering on body mass index (BMI) and weight-controllability beliefs: low-BMI/moderate-beliefs, high-BMI/more biased beliefs, and high-BMI/less biased beliefs. Profile membership varied by country of residence and weight bias outcomes with low-BMI/moderate-beliefs profiles containing more people from non-Western countries and with low explicit weight bias.

Conclusions
Explicit and implicit weight bias was harboured by participants across all included nations, although less pronounced in non-Western countries. Our profiles highlight that individuals who held a stronger belief that weight is controllable, regardless of their body weight, should be targeted for interventions to eliminate weight stigma.
Regulatory role of PPAR in colorectal cancer
Authors: Wang Cong , Lv Tingcong , Jin Binghui , Li Yang , Fan Zhe 
Published: January 2025

Abstract
Colorectal cancer (CRC) is one of the most common tumors in the digestive system, and the majority of patients are found to be in advanced stages, which is a burden to human health all over the world. Moreover, in recent years, CRC has been progressively becoming younger, with an increasing incidence mainly among patients <50 years old. Despite the increase in awareness of CRC and the continuous improvement of medical treatment nowadays, the challenge of CRC still needs to be conquered. By now, the pathogenesis of CRC is complex and not fully understood. With the deepening of research, it has been revealed that PPARs, as a transcription factor, are inextricably linked to CRC. This article outlines the mechanisms by which PPARs are involved in CRC development. An in-depth understanding of the pathways related to PPARs may provide new ways of developing effective therapies for CRC with PPARs as potential targets.
Effects of β-glucans on fatigue: a systematic review and meta-analysis
Authors: Muroya Masahiro , Nakada Kumiko , Maruo Kazushi , Hashimoto Koichi 
Published: January 2025

Abstract
Several clinical trials suggest that β-glucans may reduce feelings of fatigue, however the results of clinical trials are inconsistent. Additionally, no systematic reviews or meta-analyses have assessed the effects of β-glucans on fatigue. Therefore, this study investigates the effects of β-glucans on fatigue in healthy subjects through a systematic review and meta-analysis. PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from database inception to March 15, 2024. The inclusion criterion was a randomized controlled trial (RCT) investigating the effects of β-glucans on healthy subjects’ fatigue, vigor, and mood state. To assess risk of bias, we employed the Cochrane risk of bias tool. A random-effects meta-analysis was conducted for the standardized mean difference (SMD). Sixteen RCTs with a total of 1,449 participants were included, and 12 studies provided data suitable for meta-analysis. Meta-analysis revealed that β-glucans significantly reduced feelings of fatigue (SMD = −0.32, 95% CI = −0.53 to −0.12; p = 0.0021), increased vigor (SMD = 0.46, 95% CI = 0.26–0.66; p < 0.0001), and improved mood state (SMD = 0.32, 95% CI = 0.11–0.53; p = 0.0026) compared to the placebo group. The results of the systematic review and meta-analysis indicate that β-glucans may be effective in reducing feelings of fatigue in healthy individuals. However, the number of studies included is insufficient, suggesting that further clinical trials are needed to validate this effect.
The disparities and development trajectories of nations in achieving the sustainable development goals
Authors: Ma Fengmei , Wang Heming , Tzachor Asaf , Hidalgo César A. , Schandl Heinz , Zhang Yue , Zhang Jingling , Chen Wei-Qiang , Zhao Yanzhi , Zhu Yong-Guan , Fu Bojie 
Published: January 2025

Abstract
The Sustainable Development Goals (SDGs) provide a comprehensive framework for societal progress and planetary health. However, it remains unclear whether universal patterns exist in how nations pursue these goals and whether key development areas are being overlooked. Here, we apply the product space methodology, widely used in development economics, to construct an ‘SDG space of nations’. The SDG space models the relative performance and specialization patterns of 166 countries across 96 SDG indicators from 2000 to 2022. Our SDG space reveals a polarized global landscape, characterized by distinct groups of nations, each specializing in specific development indicators. Furthermore, we find that as countries improve their overall SDG scores, they tend to modify their sustainable development trajectories, pursuing different development objectives. Additionally, we identify orphaned SDG indicators — areas where certain country groups remain under-specialized. These patterns, and the SDG space more broadly, provide a high-resolution tool to understand and evaluate the progress and disparities of countries towards achieving the SDGs.
SPACIER: on-demand polymer design with fully automated all-atom classical molecular dynamics integrated into machine learning pipelines
Authors: Nanjo Shun , Arifin  , Maeda Hayato , Hayashi Yoshihiro , Hatakeyama-Sato Kan , Himeno Ryoji , Hayakawa Teruaki , Yoshida Ryo 
Published: January 2025

Abstract
Machine learning has rapidly advanced the design and discovery of new materials with targeted applications in various systems. First-principles calculations and other computer experiments have been integrated into material design pipelines to address the lack of experimental data and the limitations of interpolative machine learning predictors. However, the enormous computational costs and technical challenges of automating computer experiments for polymeric materials have limited the availability of open-source automated polymer design systems that integrate molecular simulations and machine learning. We developed SPACIER, an open-source software program that incorporates RadonPy, a Python library for fully automated polymer physical property calculations based on all-atom classical molecular dynamics, into a Bayesian optimization-based polymer design system to overcome these challenges. As a proof-of-concept study, we synthesized optical polymers that surpass the Pareto boundary formed by the tradeoff between the refractive index and the Abbe number.
Associations between common genetic variants and income provide insights about the socio-economic health gradient
Authors: Kweon Hyeokmoon , Burik Casper A. P. , Ning Yuchen , Ahlskog Rafael , Xia Charley , Abner Erik , Bao Yanchun , Bhatta Laxmi , Faquih Tariq O. , de Feijter Maud , Fisher Paul , Gelemanović Andrea , Giannelis Alexandros , Hottenga Jouke-Jan , Khalili Bita , Lee Yunsung , Li-Gao Ruifang , Masso Jaan , Myhre Ronny , Palviainen Teemu , Rietveld Cornelius A. , Teumer Alexander , Verweij Renske M. , Willoughby Emily A. , Agerbo Esben , Bergmann Sven , Boomsma Dorret I. , Børglum Anders D. , Brumpton Ben M. , Davies Neil Martin , Esko Tõnu , Gordon Scott D. , Homuth Georg , Ikram M. Arfan , Johannesson Magnus , Kaprio Jaakko , Kidd Michael P. , Kutalik Zoltán , Kwong Alex S. F. , Lee James J. , Luik Annemarie I. , Magnus Per , Marques-Vidal Pedro , Martin Nicholas G. , Mook-Kanamori Dennis O. , Mortensen Preben Bo , Oskarsson Sven , Pedersen Emil M. , Polašek Ozren , Rosendaal Frits R. , Smart Melissa C. , Snieder Harold , van der Most Peter J. , Vollenweider Peter , Völzke Henry , Willemsen Gonneke , Beauchamp Jonathan P. , DiPrete Thomas A. , Linnér Richard Karlsson , Lu Qiongshi , Morris Tim T. , Okbay Aysu , Harden K. Paige , Abdellaoui Abdel , Hill W. David , de Vlaming Ronald , Benjamin Daniel J. , Koellinger Philipp D. 
Published: January 2025

Abstract
We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1–5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.
Machine learning and AVO class II workflow for hydrocarbon prospectivity in the Messinian offshore Nile Delta Egypt
Authors: Abd-Elfattah Nadia , Dahroug Aia , El Kammar Manal , Fahmy Ramy 
Published: January 2025

Abstract
This study presents a comprehensive workflow to detect low seismic amplitude gas fields in hydrocarbon exploration projects, focusing on the West Delta Deep Marine (WDDM) concession, offshore Egypt. The workflow integrates seismic spectral decomposition and machine learning algorithms to identify subtle anomalies, including low seismic amplitude gas sand and background amplitude water sand. Spectral decomposition helps delineate the fairway boundaries and structural features, while Amplitude Versus Offset (AVO) analysis is used to validate gas sand anomalies. The entire seismic volume is classified into facies domains using machine learning, which isolates target features from seismic background data. The study area, covering 1850 km2, includes major structures such as the Rosetta fault and Nile Delta offshore anticline, with reservoirs consisting of layered sandstones and mudstones. Over 90 wells, including exploration and development wells, have been drilled in the area. Seismic amplitude data, including full and partial offset stacked, were analyzed to classify gas, water, and shale zones. The workflow’s performance is demonstrated through the successful identification of the low-amplitude Swan-E Messinian anomaly, characterized as a high-risk gas prospect. Machine learning techniques, specifically neural network models, were trained to differentiate seismic features such as low-amplitude gas sand from background-amplitude water sand and shale. By iterating over multiple attributes and validating the models on blind test sets and on a blind section, which excluded a known shallow gas field, the workflow significantly improved the ability to detect potential hydrocarbon reservoirs characterized by low seismic amplitude. The results show that this integrated approach reduces exploration risk, quantifies the chance of success, and enhances decision-making in well placement and hydrocarbon exploration. This method is particularly useful for identifying low seismic amplitude anomalies, which are often challenging to detect with conventional seismic analysis. (1) This study developed a workflow to detect low seismic amplitude gas fields in near-field exploration. (2) It uses a machine learning algorithm to classify and explore low-seismic-amplitude gas sand reservoirs. (3) This approach helps estimate the likelihood of success and reduces the risk associated with hydrocarbon exploration wells.
Chromatin environment-dependent effects of DOT1L on gene expression in male germ cells
Authors: Coulée Manon , de la Iglesia Alberto , Blanco Mélina , Gobé Clara , Lapoujade Clémentine , Ialy-Radio Côme , Alvarez-Gonzalez Lucia , Meurice Guillaume , Ruiz-Herrera Aurora , Fouchet Pierre , Cocquet Julie , El Khattabi Laïla 
Published: January 2025

Abstract
The H3K79 methyltransferase DOT1L is essential for multiple aspects of mammalian development where it has been shown to regulate gene expression. Here, by producing and integrating epigenomic and spike-in RNA-seq data, we decipher the molecular role of DOT1L during mouse spermatogenesis and show that it has opposite effects on gene expression depending on chromatin environment. On one hand, DOT1L represses autosomal genes that are devoid of H3K79me2 at their bodies and located in H3K27me3-rich/H3K27ac-poor environments. On the other hand, it activates the expression of genes enriched in H3K79me2 and located in H3K27me3-poor/H3K27ac-rich environments, predominantly X chromosome-linked genes, after meiosis I. This coincides with a significant increase in DOT1L expression at this stage and a genome-wide acquisition of H3K79me2, particularly on the sex chromosomes. Taken together, our results show that H3K79me2 positively correlates with male germ cell genetic program throughout spermatogenesis, with DOT1L predominantly inhibiting rather than activating gene expression. Interestingly, while DOT1L appears to directly regulate the (re)activation of X genes following meiotic sex chromosome inactivation, it also controls the timely expression of (autosomal) differentiation genes during spermatogenesis.
TDP-43 nuclear retention is antagonized by hypo-phosphorylation of its C-terminus in the cytoplasm
Authors: Rabhi Célia , Babault Nicolas , Martin Céline , Desforges Bénédicte , Maucuer Alexandre , Joshi Vandana , Pankivskyi Serhii , Feng Yitian , Bollot Guillaume , Rattenbach Revital , Pastré David , Bouhss Ahmed 
Published: January 2025

Abstract
Protein aggregation is a hallmark of many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), in which TDP-43, a nuclear RNA-binding protein, forms cytoplasmic inclusions. Here, we have developed a robust and automated method to assess protein self-assembly in the cytoplasm using microtubules as nanoplatforms. Importantly, we have analyzed specifically the self-assembly of full-length TDP-43 and its mRNA binding that are regulated by the phosphorylation of its self-adhesive C-terminus, which is the recipient of many pathological mutations. We show that C-terminus phosphorylation prevents the recruitment of TDP-43 in mRNA-rich stress granules only under acute stress conditions because of a low affinity for mRNA but not under mild stress conditions. In addition, the self-assembly of the C-terminus is negatively regulated by phosphorylation in the cytoplasm which in turn promotes TDP-43 nuclear import. We anticipate that reducing TDP-43 C-terminus self-assembly in the cytoplasm may be an interesting strategy to reverse TDP-43 nuclear depletion in neurodegenerative diseases.
Calculations of extreme sea level rise scenarios are strongly dependent on ice sheet model resolution
Authors: Williams C. Rosie , Thodoroff Pierre , Arthern Robert J. , Byrne James , Hosking J. Scott , Kaiser Markus , Lawrence Neil D. , Kazlauskaite Ieva 
Published: January 2025

Abstract
The West Antarctic Ice Sheet (WAIS) is losing ice and its annual contribution to sea level is increasing. The future behaviour of WAIS will impact societies worldwide, yet deep uncertainty remains in the expected rate of ice loss. High-impact low-likelihood scenarios of sea-level rise are needed by risk-averse stakeholders but are particularly difficult to constrain. Here, we combine traditional model simulations of the Amundsen Sea sector of WAIS with Gaussian process emulation to show that ice-sheet models capable of resolving kilometre-scale basal topography will be needed to assess the probability of extreme scenarios of sea-level rise. This resolution exceeds many state-of-the-art continent-scale simulations. Our ice-sheet model simulations show that coarser resolutions tend to project a larger range of sea-level contributions than finer resolutions, inflating the tails of the distribution. We therefore caution against relying purely upon simulations 5 km or coarser when assessing the potential for societally important high-impact sea-level rise.
Blockchain in healthcare: Bridging the business value and patient benefit
Authors: Kröckel Pavlina , Wickramasinghe Nilmini , van de Logt Jule , Andargoli Amir , Ulapane Nalika , Bodendorf Freimut 
Published: January 2025

AbstractIn today's rapidly evolving technological landscape, the healthcare industry is a pivotal sector that demands continuous innovation. Although extensive research on blockchain technology exists, the literature has predominantly emphasized technical aspects and specific applications within industries. However, a comprehensive exploration of blockchain's business and patient value in healthcare remains limited. This study aims to address this gap by conducting a systematic literature review using the PRISMA framework, analyzing highly cited articles from reputable journals. The findings highlight blockchain's potential to revolutionize patient care and optimize business practices within the healthcare sector. This research provides valuable insights for stakeholders, emphasizing the transformative power of blockchain technology to foster innovation, particularly in public healthcare institutions. The results are presented through a value chain analysis and a mindmap, offering a clear framework that can guide researchers and developers in considering the value of blockchain use cases from multiple perspectives.
Face de‐morphing based on identity feature transfer
Authors: Zhang Le‐Bing , Chen Song , Long Min , Cai Juan 
Published: January 2025

AbstractFace morphing attacks have emerged as a significant security threat, compromising the reliability of facial recognition systems. Despite extensive research on morphing detection, limited attention has been given to restoring accomplice face images, which is critical for forensic applications. This study aims to address this gap by proposing a novel face de‐morphing (FD) method based on identity feature transfer for restoring accomplice face images. The method encodes facial attribute and identity features separately and employs cross‐attention mechanisms to extract identity features from morphed faces relative to reference images. This process isolates and enhances the accomplice's identity features. Additionally, inverse linear interpolation is applied to transfer identity features to attribute features, further refining the restoration process. The enhanced identity features are then integrated with the StyleGAN generator to reconstruct high‐quality accomplice facial images. Experimental evaluations on two morphed face datasets demonstrate the effectiveness of the proposed approach, improving the average restoration accuracy by at least 5% compared with other methods. These findings highlight the potential of this approach for advancing forensic and security applications.