bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends in single-fraction palliative radiotherapy across the COVID-19 pandemic in Japan: a nationwide claims study
Authors: Koide Yutaro , Aoyama Takahiro , Noguchi Masamune , Shindo Yurika , Kitagawa Tomoki , Shimizu Hidetoshi , Hashimoto Shingo , Tachibana Hiroyuki , Kodaira Takeshi 
Published: January 2025

Abstract
This study aimed to evaluate the recent trends in single-fraction conventional radiotherapy (CRT) as palliative treatment in Japan, using data from the National Database published by the Ministry of Health, Labor, and Welfare. Data from fiscal year (FY) 2014 to FY2022, specifically related to the utilization of single-fraction CRT, were analyzed. Multi-fraction CRT, stereotactic body radiotherapy (SBRT), intensity-modulated radiotherapy (IMRT), and brachytherapy were excluded. The primary outcome was the cumulative and annual number of single-fraction CRT courses. Additionally, quarterly course data from FY2019 to FY2022, the period for which monthly data were available, were assessed to evaluate the impact of the coronavirus disease 2019 (COVID-19) pandemic on single-fraction CRT utilization. Of the total 2 315 607 radiotherapy courses, we identified 33 221 single-fraction CRT courses after excluding multi-fraction CRT (n = 1 835 650), SBRT (n = 33 935), IMRT (n = 332 827), and brachytherapy (n = 113 195). The annual number of single-fraction CRT courses increased from 1730 in FY2014 to 5642 in FY2022, with an average annual growth rate of 0.28 (range: −0.07 to 0.65). Outpatient courses significantly increased, particularly from FY2019 onward, surpassing inpatient courses in FY2022 (2914 vs 2728). The highest annual increase was observed in FY2020, particularly from April to December, although this upward trend did not persist in 2021. In conclusion, single-fraction CRT has exhibited a consistent upward trend, highlighting its expanding role in palliative radiotherapy. Although the COVID-19 pandemic temporarily accelerated this trend, its impact has already subsided, with growth rates returning to pre-pandemic levels.
Calibration and applications of the all-sky camera at the Ali Observatory in Tibet
Authors: Yin Jia , Yao Yongqiang , Qian Xuan , Liu Liyong , Chen Xu , Zhai Liuming 
Published: January 2025

ABSTRACT
A high-precision calibration method for all-sky cameras has been realized using images from the Ali observatory in Tibet, providing application results for atmospheric extinction, night sky brightness, and known variable stars. This method achieves high-precision calibration for individual all-sky images, with the calibration process introducing deviations of less than 0.5 pixels. Within a 70-deg zenith angle, the calibration deviation of the images is less than 0.25 pixels. Beyond this angle, the calibration deviation increases significantly due to the sparser distribution of stars. Increasing the number of stars with zenith angles greater than 70 deg used for calibration can improve the calibration accuracy for areas beyond the 70-deg zenith angle, reducing the calibration deviation at an 85-deg zenith angle to 0.2 pixels. Analysis of the all-sky images indicates that the atmospheric extinction coefficient at the Ali Observatory is approximately 0.20, and the night sky background brightness is about 21 mag per square arcsec, suggesting the presence of urban light pollution.
Exon location of glycine substitutions impacts kidney survival in autosomal dominant Alport Syndrome
Authors: Pagniez Marie-Sophie , Fages Victor , Gatinois Clémence , Larrue Romain , Pottier Nicolas , Laboux Timothée , Lenain Rémi , Grunewald Olivier , Robert Thomas , Rigothier Claire , Mesnard Laurent , Glowacki François 
Published: January 2025

Abstract

Background and hypothesis
Unlike X-linked or autosomal recessive Alport Syndrome, no clear genotype/phenotype correlation has yet been demonstrated in patients carrying a single variant of COL4A3 or COL4A4.

Methods
We carried out a multicenter retrospective study to assess the risk factors involved in renal survival in patients presenting a single pathogenic variant on COL4A3 or COL4A4.

Results
97 patients presenting a single pathogenic variant of COL4A3 or COL4A4 were included. The prevalence of end-stage kidney disease (ESKD) during follow-up was 28.7% (median age 47.5 years [IQR, 39.1–55.8]). 23 patients carried a ‘severe’ mutation (frameshift, stop gain, extensive deletion, impacting splicing), and 60 patients presented a glycine substitution in a collagenous domain. In patients with glycine missense variants, the location of the mutation in the distal exons was associated with worse renal survival with a more pronounced decline in eGFR compared to variants in proximal exons. Conversely, the presence of a severe mutation did not impact renal survival.

Conclusion
Our results confirm that ADAS can lead to ESKD. We demonstrated that a glycine substitution involving the distal exons had a negative impact on renal survival in ADAS patients, probably due to a trimerization defect. This could help improve personalized follow-up in ADAS patients with glycine substitution and could be integrated to a future prognostic score to accurately predict renal outcomes.
Born of frustration: the emergence of Camelina sativa as a platform for lipid biotechnology
Authors: Haslam Richard P , Michaelson Louise V , Eastmond Peter J , Napier Johnathan A 
Published: January 2025

Abstract
The emerging crop Camelina sativa (L.) Crantz (camelina) is a Brassicaceae oilseed with a rapidly growing reputation for the deployment of advanced lipid biotechnology and metabolic engineering. Camelina is recognized by agronomists for its traits, including yield, oil/protein content, drought tolerance, limited input requirements, plasticity, and resilience. Its utility as a platform for metabolic engineering was then quickly recognized, and biotechnologists have benefited from its short life cycle and facile genetic transformation, producing numerous transgenic interventions to modify seed lipid content and generate novel products. The desire to work with a plant that is both a model and crop has driven the expansion of research resources for camelina, including increased availability of genome and other -omics data sets. Collectively, the expansion of these resources has established camelina as an ideal plant to study the regulation of lipid metabolism and genetic improvement. Furthermore, the unique characteristics of camelina enables the design-build-test-learn cycle to be transitioned from the controlled environment to the field. Complex metabolic engineering to synthesize and accumulate high levels of novel fatty acids and modified oils in seeds can be deployed, tested, and undergo rounds of iteration in agronomically relevant environments. Engineered camelina oils are now increasingly being developed and used to sustainably supply improved nutrition, feed, biofuels, and fossil fuel replacements for high-value chemical products. In this review, we provide a summary of seed fatty acid synthesis and oil assembly in camelina, highlighting how discovery research in camelina supports the advance of metabolic engineering toward the predictive manipulation of metabolism to produce desirable bio-based products. Further examples of innovation in camelina seed lipid engineering and crop improvement are then provided, describing how technologies (e.g. genetic modification [GM], gene editing [GE], RNAi, alongside GM and GE stacking) can be applied to produce new products and denude undesirable traits. Focusing on the production of long chain polyunsaturated omega-3 fatty acids in camelina, we describe how lipid biotechnology can transition from discovery to a commercial prototype. The prospects to produce structured triacylglycerol with fatty acids in specified stereospecific positions are also discussed, alongside the future outlook for the agronomic uptake of camelina lipid biotechnology.
The requisite intention for constituting a Quistclose trust
Authors: Tam Anfield 
Published: January 2025

Abstract
In China Life Trustees Ltd v China Energy Reserve and Chemical Group Overseas Co Ltd [2024] HKCFA 15, the Hong Kong Court of Final Appeal clarified that a positive intention for the transferor to retain beneficial interest in the transferred assets is not necessary for a Quistclose trust to arise. Rather, it suffices when the parties intended the transferred assets to be used exclusively for a specific purpose, such that it is not at the transferee’s free disposal. This note appraises the decision for disentangling the conceptual nuances between these two types of intention. The Court rightly held that the transferor’s retention of beneficial interest is merely a legal consequence of the restrictive intention, as on a correct reading of the authorities such retention need not be intended for a Quistclose trust to arise.
Extending empirical dynamic modeling to cross-sectional data beyond traditional time series
Authors: Deyle Ethan R. , Pao Gerald , Sugihara George 
Published: January 2025

AbstractThe foundation of Empirical dynamic modeling (EDM) is in representing time-series data as the trajectory of a dynamic system in a multidimensional state space rather than as a collection of traces of individual variables changing through time. Takens’s theorem provides a rigorous basis for adopting this state-space view of time-series data even from just a single time series, but there is considerable additional value to building out a state space with explicit covariates. Multivariate EDM case studies to-date, however, generally rely on building up understanding first from univariate to multivariate and use lag-coordinate embeddings for critical steps along the path of analysis. Here, we propose an alternative set of steps for multivariate EDM analysis when the traditional roadmap is not practicable. The general approach borrows ideas of random data projection from compressed sensing, but additional justification is described within the framework of Takens’s theorem. We then detail algorithms that implement this alternative method and validate through application to simulated model data. The model demonstrations are constructed to explicitly demonstrate the possibility for this approach to extend EDM application from time-series trajectories to effectively realizations of the underlying vector field, i.e. data sets that measure change over time with very short formal time series but are otherwise “big” in terms of number of variables and samples.
Decline of Antimicrobial Resistance inPseudomonas aeruginosaBacteremia Following the COVID-19 Pandemic: a Longitudinal Observational Study
Authors: Butscheid Yulia , Frey Pascal M. , Pfister Marc , Pagani Lisa , Kouyos Roger D. , Scheier Thomas C. , Staiger Willy I. , Mancini Stefano , Brugger Silvio D. 
Published: January 2025

ABSTRACTBackgroundMultidrug-resistant Pseudomonas aeruginosa (MDRPA) poses significant challenges in hospital settings. Understanding the effects of the unprecedented changes brought by the COVID-19 pandemic on antimicrobial resistance in P. aeruginosa (PA) is essential to inform stewardship efforts. This study investigated the dynamics of antimicrobial resistance in PA bacteremia after the start of the pandemic.MethodsThis single-centre retrospective cohort study included adult inpatients with PA bacteraemia at the University Hospital Zurich between January 2014 and December 2023. Data were retrieved from electronic records. The primary outcome was the association between the start of the COVID-19 pandemic and PA with MDR, defined as resistance to ≥3 of 5 antibiotic classes. We used logistic regression to adjust for age, sex and ICU treatment, accounting for multiple bacteremia instances within the same patient using cluster-robust standard errors. Secondary outcomes included changes in resistance patterns and patient demographics, with antimicrobial exposure assessed as median monthly days of therapy (DOT).ResultsA total of 493 instances of PA bacteremia in 333 patients were observed during the study period. The proportion of MDRPA declined from 21% (62/291) pre-pandemic to 9% (19/202) post-pandemic (adjusted OR 0.38, 95% CI 0.18–0.79, p=0.01). The occurrence of MDRPA during hospitalisation following an initial instance of non-MDRPA bacteremia was rare and unlikely to happen earlier than after two weeks. Antimicrobial consumption patterns shifted after the start of the pandemic, with reduced use of amikacin and ciprofloxacin and increased use of cefepime and meropenem. Overall inhospital-mortality among patients with MDRPA bacteraemia remained high (28%), with no substantial differences before and after the pandemic (adjusted hazard ratio 1.57, 95% CI 0.43–5.67, p=0.49).ConclusionWe observed a decline in MDRPA occurrence after the start of the COVID-19 pandemic, possibly driven by intensified infection control measures, shifts in antimicrobial use, and changes in patient populations.
COSIME: Cooperative multi-view integration and Scalable and Interpretable Model Explainer
Authors: Choi Jerome J. , Cohen Kalafut Noah , Gruenloh Tim , Engelman Corinne D. , Lu Tianyuan , Wang Daifeng 
Published: January 2025

AbstractSingle-omics approaches often provide a limited view of complex biological systems, whereas multiomics integration offers a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and interpreting the intricate relationships between biological features—both within and across different data views—remains a bottleneck. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration and Scalable Interpretable Model Explainer). COSIME uses backpropagation of Learnable Optimal Transport (LOT) to deep neural networks, enabling the learning of latent features from multiple views to predict disease phenotypes. In addition, COSIME incorporates Monte Carlo sampling to efficiently estimate Shapley values and Shapley-Taylor indices, enabling the assessment of both feature importance and their pairwise interactions—synergistically or antagonistically—in predicting disease phenotypes. We applied COSIME to both simulated data and real-world datasets, including single-cell transcriptomics, single-cell spatial transcriptomics, epigenomics, and metabolomics, specifically for Alzheimer’s disease-related phenotypes. Our results demonstrate that COSIME significantly improves prediction performance while offering enhanced interpretability of feature relationships. For example, we identified that synergistic interactions between microglia and astrocyte genes associated with AD are more likely to be active at the edges of the middle temporal gyrus as indicated by spatial locations. Finally, COSIME is open-source and available for general use.
RNA3DClust: segmentation of RNA three-dimensional structures using a clustering-based approach
Authors: Le Quoc Khang , Angel Eric , Tahi Fariza , Postic Guillaume 
Published: January 2025

ABSTRACTA growing body of evidence shows that the biological activity of RNA molecules is not only due to their primary and secondary structures, but also to their spatial conformation. As the experimental determination of the three-dimensional (3D) structure is a costly and uncertain process, the development of computational methods for predicting RNA fold is a necessity. A critical task for 3D structure prediction consists of finding substructures that can be predicted independently, before being assembled into a global fold. In protein structures, these subparts are the “structural domains” and, to the best of our knowledge, no equivalent concept has ever been defined for RNA macromolecules.In this work, we present RNA3DClust, an adaptation of the Mean Shift clustering algorithm to the RNA 3D structure partitioning problem. This approach allowed us to delimit compact and separate regions in RNA conformations, analogously to the seminal definition of domains in proteins. Developing RNA3DClust required us to create a dataset of RNA 3D domain annotations, as well as a new segmentation quality score, which we both used for evaluating our method. In addition to macromolecular geometry, we also show that the RNA domain decompositions produced by RNA3DClust are relevant regarding data about RNA biological function reported in the literature. Finally, the emerging interest in long non-coding RNAs (lncRNAs) and their likeliness of containing locally folded regions has motivated us to generate an additional reference dataset of lncRNA predicted conformations. The resulting delineations of 3D domains by RNA3DClust illustrate the potential of our method for analyzing lncRNAs. Source code and datasets are freely available for download on the EvryRNA platform at:https://evryrna.ibisc.univ-evry.fr.
Modification of Non-photochemical Quenching Pathways in the C4Model PlantSetaria viridisRevealed Shared and Unique Photoprotection Mechanisms as Compared to C3Plants
Authors: Milburn Grace , Morris Cheyenne M. , Kosola Eileen , Patel-Tupper Dhruv , Liu Jian , Pham Dominique H. , Acosta-Gamboa Lucia , Stone William D. , Pardi Sarah , Hillman Kylee , McHargue William E. , Becker Eric , Kang Xiaojun , Sumner Josh , Bailey Catherine , Thielen Peter M. , Jander Georg , Kane Cade N. , McAdam Scott A. M. , Lawton Thomas J. , Nusinow Dmitri A. , Zhang Feng , Gore Michael A. , Cheng Jianlin , Niyogi Krishna K. , Zhang Ru 
Published: January 2025

SummaryLight is essential for photosynthesis; however, excess light can increase the accumulation of photoinhibitory reactive oxygen species that reduce photosynthetic efficiency. Plants have evolved photoprotective non-photochemical quenching (NPQ) pathways to dissipate excess light energy. In tobacco and soybean (C3plants), overexpression of three NPQ genes,violaxanthin de-epoxidase (VDE),Photosystem II Subunit S(PsbS), andzeaxanthin epoxidase(ZEP), hereafter VPZ, resulted in faster NPQ induction and relaxation kinetics, and increased crop yields in field conditions. NPQ is well-studied in C3plants; however, NPQ and the translatability of the VPZ approach in C4plants is poorly understood. The green foxtailSetaria viridisis an excellent model to study photosynthesis and photoprotection in C4plants. To understand the regulation of NPQ and photosynthesis in C4plants, we performed transient overexpression in Setaria protoplasts and generated (and employed) stable transgenic Setaria plants overexpressing one of the three Arabidopsis NPQ genes or all three NPQ genes (AtVPZ lines). Overexpressing (OE)AtVDEandAtZEPin Setaria produced similar results as in C3plants, with increased or reduced zeaxanthin (thus NPQ), respectively. However, overexpressingAtPsbSappeared to be challenging in Setaria, with largely reduced NPQ in protoplasts and under-represented homozygous AtPsbS-OE lines, potentially due to competitive and tight heterodimerization of AtPsbS and SvPsbS proteins. Furthermore, Setaria AtVPZ lines had increased zeaxanthin, faster NPQ induction, higher NPQ level, but slower NPQ relaxation. Despite this, AtVPZ lines had improved growth as compared to wildtype under several conditions, especially high temperatures, which is not related to the faster relaxation of NPQ but may be attributable to increased zeaxanthin and NPQ in C4plants. Our results identified shared and unique characteristics of the NPQ pathway in C4model Setaria as compared to C3plants and provide insights to improve C4crop yields under fluctuating environmental conditions.
Accurate Prediction of Protein Complex Stoichiometry by Integrating AlphaFold3 and Template Information
Authors: Liu Jian , Neupane Pawan , Cheng Jianlin 
Published: January 2025

AbstractProtein structure prediction methods require stoichiometry information (i.e., subunit counts) to predict the quaternary structure of protein complexes. However, this information is often unavailable, making stoichiometry prediction crucial for complexes with unknown stoichiometry. Despite its importance, few computational methods address this challenge. In this study, we present an approach that integrates AlphaFold3 structure predictions with homologous template data to predict stoichiometry. The method generates candidate stoichiometries, builds structural models for them using AlphaFold3, ranks them based on AlphaFold3 scores, and further refine predictions with template-based information when available. In the 16th community-wide Critical Assessment of Techniques for Protein Structure Prediction (CASP16), our method achieved 71.4% top-1 accuracy and 92.9% top-3 accuracy, outperforming other predictors in terms of the overall performance. This demonstrates the complementary strengths of AlphaFold3- and template-based predictions and highlights its applicability for uncharacterized protein complexes lacking stoichiometry data.
Expanding the phenotype spectrum of β-mannosidosis
Authors: Martin-Rios Angela , Stepien Karolina M , Gibbs Liliane H. , Hall Katherine , Hall Patricia L. , Pino Gisele Bentz , Wang Raymond , Pillai Nishitha R. , Lund Troy C. , Orchard Paul J. , Kimonis Virginia 
Published: January 2025

ABSTRACTPurposeTo expand the spectrum of clinical and biochemical phenotypes, and brain imaging features of individuals with β-mannosidosis, a rare lysosomal storage disease.MethodsWe describe the clinical features of six patients with β-mannosidosis, their findings on brain magnetic resonance imaging (MRI), and the changes over time in two of them. We also review previously reported patients, analyze the variants inMANBA,the first symptom and spectrum of symptoms, and the ages of onset and of diagnosis of the disease.ResultsForty-four patients have been reported to date, including our patients. The mean age of diagnosis is 12.8 years, and the age of onset of symptoms is 2.4 years. Hearing loss is the most frequently reported initial symptom and intellectual disability is the most frequent symptom overall. Erythromelalgia, nystagmus, macrocephaly, and obsessive-compulsive-like behavior are newly described features associated with β-mannosidosis. 40% of the patients have abnormal brain imaging. Brain MRI showed hypomyelination in one patient and abnormal white matter changes in another patient. Twenty-nine pathogenic variants inMANBAhave been reported among the 44 patients; 60.6% of patients have private variants, and 39.4% have the recurrent variant c.2158-2A>G. A new oligosaccharide structure: Neu-Man2-GlcNac2, was found in the urine of two affected patients.ConclusionDue to disease heterogeneity, establishing a genotype-phenotype correlation remains challenging in β-mannosidosis. A spectrum of brain MRI abnormalities are described as manifestations of this condition: delayed myelination, hypomyelination, and abnormal white matter signals. Additional studies are needed to delineate the pathophysiology of this condition.
Pseudo-p-Value-Based Clumping Enhanced Proteome-wide Mendelian Randomization with Application in Identifying Coronary Heart Disease-Associated Plasma Proteins
Authors: Wang Yuquan , Cao Yunlong , Chen Dong , Shi Dapeng , Fu Liwan , Chen Anqi , Shen Siyuan , Hu Yue-Qing 
Published: January 2025

AbstractMendelian randomization (MR) is a powerful tool for causal inference in epidemiology. However, the presence of weak instrumental variables (IVs) and pleiotropy can lead to biased causal effect estimates. To address these issues, we develop MR-GMM, a novel MR method based on a Gaussian Mixture Model. MR-GMM classifies IVs into four categories—invalid, valid, invalid&null, and null IVs— and models their effects using a two-dimensional spike-and-slab distribution. Simulation studies demonstrate the high efficiency and robustness of MR-GMM compared to existing methods. More importantly, we propose a pseudo-p-value-based linkage disequilibrium (LD) clumping procedure to address selection bias. This refined procedure is capable of enhancing the performance of MR-GMM as well as many existing MR methods in real-world scenarios. Applying MR-GMM in a large-scale proteome-wide MR study, we identify 45 coronary heart disease-associated plasma proteins. Subsequent network and enrichment analyses highlight the potential of these proteins as biomarkers for disease diagnosis and therapeutic development.