bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global perspectives of the bulk electronic structure of URu2Si2 from angle-resolved photoemission
Authors: Denlinger J D , Kang J-S , Dudy L , Allen J W , Kim Kyoo , Shim J-H , Haule K , Sarrao J L , Butch N P , Maple M B 
Published: December 2021

Abstract
Previous high-resolution angle-resolved photoemission (ARPES) studies of URu2Si2 have characterized the temperature-dependent behavior of narrow-band states close to the Fermi level (E
F) at low photon energies near the zone center, with an emphasis on electronic reconstruction due to Brillouin zone folding. A substantial challenge to a proper description is that these states interact with other hole-band states that are generally absent from bulk-sensitive soft x-ray ARPES measurements. Here we provide a more global k-space context for the presence of such states and their relation to the bulk Fermi surface (FS) topology using synchrotron-based wide-angle and photon energy-dependent ARPES mapping of the electronic structure using photon energies intermediate between the low-energy regime and the high-energy soft x-ray regime. Small-spot spatial dependence, f-resonant photoemission, Si 2p core-levels, x-ray polarization, surface-dosing modification, and theoretical surface slab calculations are employed to assist identification of bulk versus surface state character of the E
F-crossing bands and their relation to specific U- or Si-terminations of the cleaved surface. The bulk FS topology is critically compared to density functional theory (DFT) and to dynamical mean field theory calculations. In addition to clarifying some aspects of the previously measured high symmetry Γ, Z and X points, incommensurate 0.6a* nested Fermi-edge states located along Z–N–Z are found to be distinctly different from the DFT FS prediction. The temperature evolution of these states above T
HO, combined with a more detailed theoretical investigation of this region, suggests a key role of the N-point in the hidden order transition.
Effects of uniform-allocation constraints in networked common-pool resource extraction games
Authors: Schauf Andrew , Oh Poong 
Published: December 2021

Abstract
Communities that share common-pool resources (CPRs) often coordinate their actions to sustain resource quality more effectively than if they were regulated by some centralized authority. Networked models of CPR extraction suggest that the flexibility of individual agents to selectively allocate extraction effort among multiple resources plays an important role in maximizing their payoffs. However, empirical evidence suggests that real-world CPR appropriators may often de-emphasize issues of allocation, for example by responding to the degradation of a single resource by reducing extraction from multiple resources, rather than by reallocating extraction effort away from the degraded resource. Here, we study the population-level consequences that emerge when individuals are constrained to apply an equal amount of extraction effort to all CPRs that are available to them within an affiliation network linking agents to resources. In systems where all resources have the same capacity, this uniform-allocation constraint leads to reduced collective wealth compared to unconstrained best-response extraction, but it can produce more egalitarian wealth distributions. The differences are more pronounced in networks that have higher degree heterogeneity among resources. In the case that the capacity of each CPR is proportional to its number of appropriators, the uniform-allocation constraint can lead to more efficient collective extraction since it serves to distribute the burden of over-extraction more evenly among the network’s CPRs. Our results reinforce the importance of adaptive allocation in self-regulation for populations who share linearly degrading CPRs; although uniform-allocation extraction habits can help to sustain higher resource quality than does unconstrained extraction, in general this does not improve collective benefits for a population in the long term.
A universal approach for integrating super large-scale single-cell transcriptomes by exploring gene rankings
Authors: Shen Hongru , Shen Xilin , Feng Mengyao , Wu Dan , Zhang Chao , Yang Yichen , Yang Meng , Hu Jiani , Liu Jilei , Wang Wei , Li Yang , Zhang Qiang , Yang Jilong , Chen Kexin , Li Xiangchun 
Published: December 2021

AbstractAdvancement in single-cell RNA sequencing leads to exponential accumulation of single-cell expression data. However, there is still lack of tools that could integrate these unlimited accumulations of single-cell expression data. Here, we presented a universal approach iSEEEK for integrating super large-scale single-cell expression via exploring expression rankings of top-expressing genes. We developed iSEEEK with 11.9 million single cells. We demonstrated the efficiency of iSEEEK with canonical single-cell downstream tasks on five heterogenous datasets encompassing human and mouse samples. iSEEEK achieved good clustering performance benchmarked against well-annotated cell labels. In addition, iSEEEK could transfer its knowledge learned from large-scale expression data on new dataset that was not involved in its development. iSEEEK enables identification of gene–gene interaction networks that are characteristic of specific cell types. Our study presents a simple and yet effective method to integrate super large-scale single-cell transcriptomes and would facilitate translational single-cell research from bench to bedside.
TMBleR: a bioinformatic tool to optimize TMB estimation and predictive power
Authors: Fancello Laura , Guida Alessandro , Frige Gianmaria , Ceol Arnaud Gerard Michel , Babini Gabriele , Scaglione Giovanni Luca , Zanfardino Mario , Mazza Tommaso , Ferrando Lorenzo , Pelicci Pier Giuseppe , Mazzarella Luca 
Published: December 2021

Abstract

Motivation
Tumor mutational burden (TMB) has been proposed as a predictive biomarker for immunotherapy response in cancer patients, as it is thought to enrich for tumors with high neoantigen load. TMB assessed by whole-exome sequencing is considered the gold standard but remains confined to research settings. In the clinical setting, targeted gene panels sampling various genomic sizes along with diverse strategies to estimate TMB were proposed and no real standard has emerged yet.

Results
We provide the community with TMBleR, a tool to measure the clinical impact of various strategies of panel-based TMB measurement.

Availability and implementation
R package and docker container (GPL-3 Open Source license): https://acc-bioinfo.github.io/TMBleR/. Graphical-user interface website: https://bioserver.ieo.it/shiny/app/tmbler.

Supplementary information
Supplementary data are available at Bioinformatics online.
Identifying cancer pathway dysregulations using differential causal effects
Authors: Jablonski Kim Philipp , Pirkl Martin , Ćevid Domagoj , Bühlmann Peter , Beerenwinkel Niko 
Published: December 2021

Abstract

Motivation
Signaling pathways control cellular behavior. Dysregulated pathways, for example, due to mutations that cause genes and proteins to be expressed abnormally, can lead to diseases, such as cancer.

Results
We introduce a novel computational approach, called Differential Causal Effects (dce), which compares normal to cancerous cells using the statistical framework of causality. The method allows to detect individual edges in a signaling pathway that are dysregulated in cancer cells, while accounting for confounding. Hence, technical artifacts have less influence on the results and dce is more likely to detect the true biological signals. We extend the approach to handle unobserved dense confounding, where each latent variable, such as, for example, batch effects or cell cycle states, affects many covariates. We show that dce outperforms competing methods on synthetic datasets and on CRISPR knockout screens. We validate its latent confounding adjustment properties on a GTEx (Genotype–Tissue Expression) dataset. Finally, in an exploratory analysis on breast cancer data from TCGA (The Cancer Genome Atlas), we recover known and discover new genes involved in breast cancer progression.

Availability and implementation
The method dce is freely available as an R package on Bioconductor (https://bioconductor.org/packages/release/bioc/html/dce.html) as well as on https://github.com/cbg-ethz/dce. The GitHub repository also contains the Snakemake workflows needed to reproduce all results presented here.

Supplementary information
Supplementary data are available at Bioinformatics online.
Safety of transoesophageal echocardiography during structural heart disease interventions under procedural sedation: a single-centre study
Authors: Afzal Shazia , Zeus Tobias , Hofsähs Timo , Kuballa Matti , Veulemans Verena , Piayda Kerstin , Heidari Houtan , Polzin Amin , Horn Patrick , Westenfeld Ralf , Kelm Malte , Hellhammer Katharina 
Published: December 2021

Abstract

Aims
The aim of this study was to determine the incidence of transoesophageal echocardiography (TOE)-related adverse events (AEs) during structural heart disease (SHD) interventions and to identify potential risk factors.

Methods and results
We retrospectively analysed 898 consecutive patients undergoing TOE-guided SHD interventions under procedural sedation. TOE-related AEs were classified as bleeding complications, mechanical lesions, conversion to general anaesthesia with intubation, and the occurrence of pneumonia. A follow-up was conducted up to 3 months after the intervention. TOE-related AEs were observed in 5.3% of the patients (n = 48). The highest rate of AEs was observed in the percutaneous mitral valve repair (PMVR) group with 8.2% (n = 32), whereas 4.8% (n = 11) of the patients in the left atrial appendage group and 1.8% (n = 5) in the patent foramen ovale/atrial septal defect group developed a TOE-related AE (P = 0.001). The most frequent AE was pneumonia with an incidence of 2.6% (n = 26) in the total cohort. Bleeding events occurred in 1.8% (n = 16) of the patients, mostly in the PMVR group with 2.1% (n = 8). In the multivariate regression analysis, we found a lower haemoglobin {odds ratio (OR) [95% confidence interval (CI)]: 8.82 (0.68–0.98) P = 0.025} and an obstructive sleep apnoea syndrome (OSAS) [OR (95% CI): 2.51 (1.08–5.84) P = 0.033] to be associated with AE. Furthermore, AEs were related to procedural time [OR (95% CI): 1.01 (1.0–1.01) P = 0.056] and oral anticoagulation [OR (95% CI): 1.97 (0.9–4.3) P = 0.076] with borderline significance in the multivariate regression analysis. No persistent damages were observed.

Conclusion
TOE-related AEs during SHD interventions are clinically relevant. It was highest in patients undergoing PMVR. A lower baseline haemoglobin level and an OSAS were found to be associated with the occurrence of a TOE-related AE.
Multi-territory stroke preceded by pulmonary embolism with asymptomatic coronavirus disease 2019: a case report
Authors: Van Herck Jakob , Thoen Hendrik , Delens Christophe , Voet Joeri 
Published: December 2021

Abstract

Background
Non-bacterial thrombotic endocarditis is characterized by the presence of sterile vegetations on a cardiac valve. We present a case of multi-territory stroke caused by embolism of a non-bacterial thrombotic aortic valve endocarditis, leading to the diagnosis of a prostate adenocarcinoma with bone metastases.

Case summary
A 66-year-old patient was diagnosed with pulmonary embolism, first attributed to an asymptomatic coronavirus disease 2019 infection. Edoxaban was started, which was discontinued by the patient. Four weeks later, he presented with subacute vertigo and balance disorders. Magnetic resonance imaging showed a multi-territory stroke. A transoesophageal echocardiogram demonstrated a small vegetation on the aortic valve with moderate aortic insufficiency. Blood cultures remained negative. Malignancy screening showed a markedly elevated prostate-specific antigen. Prostate adenocarcinoma was confirmed on biopsy. A positron emission tomography revealed metastatic disease. A diagnosis of non-bacterial thrombotic endocarditis and paraneoplastic pulmonary embolism secondary to prostate cancer was made. Edoxaban was restarted and the patient was referred for treatment of the prostate adenocarcinoma. Follow-up after 5 months showed no evidence of aortic valve vegetations.

Discussion
Coronavirus disease 2019 in ambulatory patients may be insufficient as a predisposing factor for venous thrombo-embolism and these patients, especially the elderly, should undergo a screening for malignancy. Non-bacterial thrombotic endocarditis is a rare cause of multi-territory stroke. When related to cancer, the prostate can be the primary tumour.
Do individuals’ attitudes toward immigrants affect their own health? Analysis of 15 European countries
Authors: Pinillos-Franco Sara , Kawachi Ichiro 
Published: December 2021

Abstract

Background
Hostility toward others is related to negative emotions, which is hypothesized to have negative health consequences. In this article, we sought to test the relationship between individuals’ attitudes toward immigrants and their self-rated health (SRH) across time in large dataset of 15 European countries.

Methods
We used the 2010, 2012, 2014 and 2016 waves of the European Social Survey, which include information about attitudes toward immigrants and individuals’ SRH.

Results
Combining all countries and survey years, we found an association between negative attitudes toward immigrants and fair/poor SRH. However, when analyzing the relationship within each country, we found variations (depending on the year of the survey) in some countries, such as Hungary, Poland, Portugal, Sweden and Slovenia. Additionally, we found that there are more middle class individuals who hold unfavorable attitudes toward immigrants over time.

Conclusions
In general, poor attitudes toward immigrants are associated with higher odds of reporting fair/poor health, although the ‘health advantage’ of those with favorable attitudes is diminishing over time. However, in some countries, this relationship is contingent on when the survey was conducted, possibly reflecting the changing composition of individuals who hold unfavorable attitudes toward immigrants.
The role of health literacy in the association between academic performance and substance use
Authors: Kinnunen Jaana M , Paakkari Leena , Rimpelä Arja H , Kulmala Markus , Richter Matthias , Kuipers Mirte A G , Kunst Anton E , Lindfors Pirjo L 
Published: December 2021

Abstract

Background
To address social inequalities in adolescent substance use and consequent disparities in health, it is important to identify the mechanisms of the association between substance use and academic performance. We study the role of health literacy (HL) in the association between academic performance and weekly smoking, monthly alcohol use and cannabis ever-use among adolescents in Europe.

Methods
SILNE-R school survey data, which was collected in 2016–17 with paper-and-pencil-method from Hanover (GE), Amersfoort (NL) and Tampere (FI), were used (N = 5088, age 13–19). Health Literacy for School-aged Children instrument was used to assess students’ HL. Logistic regression analyzed the association of substance use with academic performance and HL, separately and in the same model. Linear and multinomial logistic regression analyzed the association between academic performance and HL.

Results
Poor academic performance compared with high was associated with smoking [odds ratio (OR) 3.94, 95% confidence interval (CI) 2.83–5.49], alcohol use (OR: 2.94, 95% CI: 2.34–3.68) and cannabis use (OR: 2.56, 95% CI: 1.89–3.48). Poor HL was also associated with each substance use (with ORs of 2.32, 1.85 and 1.29). HL was positively associated with academic performance (β = 1.04, 95% CI: 0.89–1.20). The associations between academic performance and substance use were only slightly attenuated after controlling for HL.

Conclusions
Academic performance and HL were both determinants of substance use, confirming their role in tackling the disparities in substance use. However, HL did not demonstrably mediate the association between academic performance and substance use. A wider set of factors needs to be tackled to address emerging social inequalities in adolescent substance use.
Strip Clearcutting Drives Vegetation Diversity and Composition in the Moso Bamboo Forests
Authors: Zheng Yaxiong , Fan Shaohui , Guan Fengying , Xia Wen , Wang Shumei , Xiao Xiao 
Published: December 2021

Abstract
Strip clearcutting of Moso bamboo forests in southern China has seen increasing interest as a way of reducing harvesting costs. Previous research has shown that cutting influences the overstory structure and drives changes in the microclimate and soil properties. However, the effects of strip cutting on understory vegetation diversity and composition remain unclear. To better understand the influence of cutting on the understory vegetation, this study compares sites under natural restoration after cut and uncut sites in the Moso bamboo forest. We selected plots that were cut in 2019 (C19) and 2017 (C17), as well as unharvested plots as controls (CK). The results showed that strip clearcutting increased the understory vegetation richness and diversity, and a significant difference (A = 0.23, P = 0.001) existed in the composition of the vegetation between the three treatments. Furthermore, the decrease of soil total phosphorus and total potassium content resulted in the difference in undergrowth vegetation distribution and composition between the uncut plots and the cut plots. Our results suggest that strip clearcutting may not be harmful to biodiversity on a local scale in the Moso bamboo forest.
New estimates of ongoing sea level change and land movements caused by Glacial Isostatic Adjustment in the Mediterranean region
Authors: Spada Giorgio , Melini Daniele 
Published: December 2021

SUMMARY
Glacial Isostatic Adjustment (GIA) caused by the melting of past ice sheets is still a major cause of sea level variations and 3-D crustal deformation in the Mediterranean region. However, since the contribution of GIA cannot be separated from those of oceanic or tectonic origin, its role can be only assessed by numerical modelling, solving the gravitationally self-consistent sea level equation. Nonetheless, uncertainties about the melting history of the late-Pleistocene ice sheets and the rheological profile of the Earth’s mantle affect the GIA predictions by an unknown amount. Estimating the GIA modelling uncertainties would be particularly important in the Mediterranean region, due to the amount of high quality geodetic data from space-borne and ground-based observations currently available, whose interpretation demands a suitable isostatic correction. Here we first review previous results about the effects of GIA in the Mediterranean Sea, enlightening the variability of all the fields affected by the persistent condition of isostatic disequilibrium. Then, for the first time in this region, we adopt an ensemble modelling approach to better constrain the present-day GIA contributions to sea level rise and geodetic variations, and their uncertainty.
Learning stochastic closures using ensemble Kalman inversion
Authors: Schneider Tapio , Stuart Andrew M , Wu Jin-Long 
Published: December 2021

Abstract
Although the governing equations of many systems, when derived from first principles, may be viewed as known, it is often too expensive to numerically simulate all the interactions they describe. Therefore, researchers often seek simpler descriptions that describe complex phenomena without numerically resolving all the interacting components. Stochastic differential equations (SDEs) arise naturally as models in this context. The growth in data acquisition, both through experiment and through simulations, provides an opportunity for the systematic derivation of SDE models in many disciplines. However, inconsistencies between SDEs and real data at short time scales often cause problems, when standard statistical methodology is applied to parameter estimation. The incompatibility between SDEs and real data can be addressed by deriving sufficient statistics from the time-series data and learning parameters of SDEs based on these. Here, we study sufficient statistics computed from time averages, an approach that we demonstrate to lead to sufficient statistics on a variety of problems and that has the secondary benefit of obviating the need to match trajectories. Following this approach, we formulate the fitting of SDEs to sufficient statistics from real data as an inverse problem and demonstrate that this inverse problem can be solved by using ensemble Kalman inversion. Furthermore, we create a framework for non-parametric learning of drift and diffusion terms by introducing hierarchical, refinable parameterizations of unknown functions, using Gaussian process regression. We demonstrate the proposed methodology for the fitting of SDE models, first in a simulation study with a noisy Lorenz ’63 model, and then in other applications, including dimension reduction in deterministic chaotic systems arising in the atmospheric sciences, large-scale pattern modeling in climate dynamics and simplified models for key observables arising in molecular dynamics. The results confirm that the proposed methodology provides a robust and systematic approach to fitting SDE models to real data.
Towards virtual modelling environments for functional–structural plant models based on Jupyter notebooks: application to the modelling of mango tree growth and development
Authors: Vaillant Jan , Grechi Isabelle , Normand Frédéric , Boudon Frédéric 
Published: December 2021

Abstract
Functional–structural plant models (FSPMs) are powerful tools to explore the complex interplays between plant growth, underlying physiological processes and the environment. Various modelling platforms dedicated to FSPMs have been developed with limited support for collaborative and distributed model design, reproducibility and dissemination. With the objective to alleviate these problems, we used the Jupyter project, an open-source computational notebook ecosystem, to create virtual modelling environments for plant models. These environments combined Python scientific modules, L-systems formalism, multidimensional arrays and 3D plant architecture visualization in Jupyter notebooks. As a case study, we present an application of such an environment by reimplementing V-Mango, a model of mango tree development and fruit production built on interrelated processes of architectural development and fruit growth that are affected by temporal, structural and environmental factors. This new implementation increased model modularity, with modules representing single processes and the workflows between them. The model modularity allowed us to run simulations for a subset of processes only, on simulated or empirical architectures. The exploration of carbohydrate source–sink relationships on a measured mango branch architecture illustrates this possibility. We also proposed solutions for visualization, distant distributed computation and parallel simulations of several independent mango trees during a growing season. The development of models on locations far from computational resources makes collaborative and distributed model design and implementation possible, and demonstrates the usefulness and efficiency of a customizable virtual modelling environment.