bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks
Authors: Shi Xuejing , Zhu Juntong , Long Yahui , Liang Cheng 
Published: August 2023

Abstract
Motivation: Recent advances in spatially resolved transcriptomics (ST) technologies enable the measurement of gene expression profiles while preserving cellular spatial context. Linking gene expression of cells with their spatial distribution is essential for better understanding of tissue microenvironment and biological progress. However, effectively combining gene expression data with spatial information to identify spatial domains remains challenging. Results: To deal with the above issue, in this paper, we propose a novel unsupervised learning framework named STMGCN for identifying spatial domains using multi-view graph convolution networks (MGCNs). Specifically, to fully exploit spatial information, we first construct multiple neighbor graphs (views) with different similarity measures based on the spatial coordinates. Then, STMGCN learns multiple view-specific embeddings by combining gene expressions with each neighbor graph through graph convolution networks. Finally, to capture the importance of different graphs, we further introduce an attention mechanism to adaptively fuse view-specific embeddings and thus derive the final spot embedding. STMGCN allows for the effective utilization of spatial context to enhance the expressive power of the latent embeddings with multiple graph convolutions. We apply STMGCN on two simulation datasets and five real spatial transcriptomics datasets with different resolutions across distinct platforms. The experimental results demonstrate that STMGCN obtains competitive results in spatial domain identification compared with five state-of-the-art methods, including spatial and non-spatial alternatives. Besides, STMGCN can detect spatially variable genes with enriched expression patterns in the identified domains. Overall, STMGCN is a powerful and efficient computational framework for identifying spatial domains in spatial transcriptomics data.
Single-cell causal network inferred by cross-mapping entropy
Authors: Li Lin , Xia Rui , Chen Wei , Zhao Qi , Tao Peng , Chen Luonan 
Published: August 2023

Abstract
Gene regulatory networks (GRNs) reveal the complex molecular interactions that govern cell state. However, it is challenging for identifying causal relations among genes due to noisy data and molecular nonlinearity. Here, we propose a novel causal criterion, neighbor cross-mapping entropy (NME), for inferring GRNs from both steady data and time-series data. NME is designed to quantify ‘continuous causality’ or functional dependency from one variable to another based on their function continuity with varying neighbor sizes. NME shows superior performance on benchmark datasets, comparing with existing methods. By applying to scRNA-seq datasets, NME not only reliably inferred GRNs for cell types but also identified cell states. Based on the inferred GRNs and further their activity matrices, NME showed better performance in single-cell clustering and downstream analyses. In summary, based on continuous causality, NME provides a powerful tool in inferring causal regulations of GRNs between genes from scRNA-seq data, which is further exploited to identify novel cell types/states and predict cell type-specific network modules.
HiBrowser: an interactive and dynamic browser for synchronous Hi-C data visualization
Authors: Li Pingjing , Liu Hong , Sun Jialiang , Lu Jianguo , Liu Jian 
Published: August 2023

Abstract
With the development of chromosome conformation capture technology, the genome-wide investigation of higher-order chromatin structure by using high-throughput chromatin conformation capture (Hi-C) technology is emerging as an important component for understanding the mechanism of gene regulation. Considering genetic and epigenetic differences are typically used to explore the pathological reasons on the chromosome and gene level, visualizing multi-omics data and performing an intuitive analysis by using an interactive browser become a powerful and welcomed way. In this paper, we develop an effective sequence and chromatin interaction data display browser called HiBrowser for visualizing and analyzing Hi-C data and their associated genetic and epigenetic annotations. The advantages of HiBrowser are flexible multi-omics navigation, novel multidimensional synchronization comparisons and dynamic interaction system. In particular, HiBrowser first provides an out of the box web service and allows flexible and dynamic reconstruction of custom annotation tracks on demand during running. In order to conveniently and intuitively analyze the similarities and differences among multiple samples, such as visual comparisons of normal and tumor tissue samples, and pan genomes of multiple (consanguineous) species, HiBrowser develops a clone mode to synchronously display the genome coordinate positions or the same regions of multiple samples on the same page of visualization. HiBrowser also supports a pluralistic and precise search on correlation data of distal cis-regulatory elements and navigation to any region on Hi-C heatmap of interest according to the searching results. HiBrowser is a no-build tool, and could be easily deployed in local server. The source code is available at https://github.com/lyotvincent/HiBrowser.
A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug–drug interaction data and supervised contrastive learning
Authors: Gu Jeonghyeon , Bang Dongmin , Yi Jungseob , Lee Sangseon , Kim Dong Kyu , Kim Sun 
Published: August 2023

Abstract
Combination therapies have brought significant advancements to the treatment of various diseases in the medical field. However, searching for effective drug combinations remains a major challenge due to the vast number of possible combinations. Biomedical knowledge graph (KG)-based methods have shown potential in predicting effective combinations for wide spectrum of diseases, but the lack of credible negative samples has limited the prediction performance of machine learning models. To address this issue, we propose a novel model-agnostic framework that leverages existing drug–drug interaction (DDI) data as a reliable negative dataset and employs supervised contrastive learning (SCL) to transform drug embedding vectors to be more suitable for drug combination prediction. We conducted extensive experiments using various network embedding algorithms, including random walk and graph neural networks, on a biomedical KG. Our framework significantly improved performance metrics compared to the baseline framework. We also provide embedding space visualizations and case studies that demonstrate the effectiveness of our approach. This work highlights the potential of using DDI data and SCL in finding tighter decision boundaries for predicting effective drug combinations.
The challenges of success: Future wolf conservation and management in the United States
Authors: Ausband David E , Mech L David 
Published: August 2023

Abstract
Gray wolf (Canis lupus) recovery and conservation has been a remarkable success over the last 30 years in the United States. Remarkable success yields remarkable challenges, however. As populations expand, wolves will colonize more human-dominated landscapes and face numerous challenges, such as fragmented habitats, barriers to dispersal, and increased encounters with humans, pets, and livestock. In such areas, conflicts between humans and wolves will increase. We summarize several major scientific and social challenges that wolf conservation, recovery, and management will face in the coming years. In addition, we suggest actions to help address each challenge. Future wolf conservation in the United States will be affected by the ability of managers to predict colonization and dispersal dynamics, to reduce hybridization and disease transmission, to mitigate and deter wolf–livestock conflicts, to harvest wolves sustainably while satisfying diverse stakeholders, to avert a reduction in tolerance for wolves due to a disinterest in nature, and to engage diverse stakeholders in wolf conservation to avoid management by ballot initiative or legislative and judicial decrees.
Skin ageing and topical rejuvenation strategies
Authors: Griffiths Tamara W , Watson Rachel E B , Langton Abigail K 
Published: August 2023

Abstract
Skin ageing is a complex process involving the additive effects of skin’s interaction with its external environment, predominantly chronic sun exposure, upon a background of time-dependent intrinsic ageing. Skin health and beauty is considered one of the principal factors perceived to represent overall ‘health and wellbeing’; thus, the demand for skin rejuvenation strategies has rapidly increased, with a worldwide annual expenditure expected to grow from $US24.6 billion to around $US44.5 billion by 2030 (https://www.databridgemarketresearch.com/reports/global-facial-rejuvenation-market). Skin rejuvenation can be achieved in several ways, ranging from laser and device-based treatments to chemical peels and injectables; however, topical skin care regimes are a mainstay treatment for ageing skin and all patients seeking skin rejuvenation can benefit from this relatively low-risk intervention. While the most efficacious topical rejuvenation treatment is application of tretinoin (all-trans retinoic acid) – a prescription-only medicine considered to be the clinical ‘gold standard’ – a hybrid category of ‘cosmeceutical’ products at the midpoint of the spectrum of cosmetics and pharmaceutical has emerged. This article reviews the clinical manifestations of skin ageing and the available topical treatments for skin rejuvenation, including retinoids, peptides and antioxidants.
Liver transplantation for elderly patients with early-stage hepatocellular carcinoma
Authors: Endo Yutaka , Sasaki Kazunari , Moazzam Zorays , Lima Henrique A , Alaimo Laura , Munir Muhammad Musaab , Shaikh Chanza F , Schenk Austin , Kitago Minoru , Pawlik Timothy M 
Published: August 2023

Abstract

Background
Although liver resection is a viable option for patients with early-stage hepatocellular carcinoma (HCC), liver transplantation is the optimal treatment. The aim of this study was to identify characteristics of liver transplantation for elderly patients, and to assess the therapeutic benefit derived from liver transplantation over liver resection.

Methods
This was a population-based study of patients undergoing liver transplantation for HCC in the USA between 2004 and 2018. Data were retrieved from the National Cancer Database. Elderly patients were defined as individuals aged 70 years and over. Propensity score overlap weighting was used to control for heterogeneity between the liver resection and liver transplantation cohorts.

Results
Among 4909 liver transplant recipients, 215 patients (4.1 per cent) were classified as elderly. Among 5922 patients who underwent liver resection, 1907 (32.2 per cent) were elderly. Elderly patients who underwent liver transplantation did not have a higher hazard of dying during the first 5 years after transplantation than non-elderly recipients. After propensity score weighting, liver transplantation was associated with a lower risk of death than liver resection. Other factors associated with overall survival included diagnosis during 2016–2018, non-white/non-African American race, and α-fetoprotein level over 20 ng/dl.

Conclusion
Elderly patients with HCC should not be excluded from liver transplantation based on age only. Transplantation leads to favourable survival compared with liver resection.
Regional diversification and labour market upgrading: local access to skill-related high-income jobs helps workers escaping low-wage employment
Authors: Elekes Zoltán , Baranowska-Rataj Anna , Eriksson Rikard 
Published: August 2023

Abstract
This article investigates how the evolution of local labour market structure enables or constrains workers as regards escaping low-wage jobs. Drawing on the network-based approach of evolutionary economic geography, we employ a detailed individual-level panel dataset to construct skill-relatedness networks for 72 functional labour market regions in Sweden. Subsequent fixed-effect panel regressions indicate that increasing density of skill-related high-income jobs within a region is conducive to low-wage workers moving to better-paid jobs, hence facilitating labour market upgrading through diversification. While metropolitan regions offer a premium for this relationship, it also holds for smaller regions, and across various worker characteristics.
Claude McKay’s vagabond classicisms: empire, uplift, and antiquity
Authors: Gregson Ben 
Published: August 2023

AbstractThis article examines the classicisms of the influential Jamaican writer, Claude McKay. Taking as paradigmatic an allusion to the myth of Laocoön in Banjo, it analyses McKay’s troubling of the classical notion of translatio imperii et studii throughout his work. Consistently rejecting imperium, McKay nevertheless embraced classical studium as a potential source of racial uplift and new creative expression. He resists both hegemonic Euro-American classicisms which appropriated Greco-Roman antiquity to authorize their imperial projects and simplistic Afrocentric classicisms which relocated imperial fantasies in Egypt and Ethiopia. However, McKay still admired the cultural legacies of Greco-Roman and African ancient civilizations. Freely and selectively enlisting these various, often-contradictory, classical traditions, McKay’s vagabond classicisms attacked empire, in all its forms, while reaffirming the aesthetic and social potential of decolonized and heterogeneous antiquities.
Myocardial structural and functional changes in cardiac amyloidosis: insights from a prospective observational patient registry
Authors: Duca Franz , Rettl René , Kronberger Christina , Binder Christina , Mann Christopher , Dusik Fabian , Schrutka Lore , Dalos Daniel , Öztürk Begüm , Dachs Theresa Marie , Cherouny Bernhard , Camuz Ligios Luciana , Agis Hermine , Kain Renate , Koschutnik Matthias , Donà Carolina , Badr-Eslam Roza , Kastner Johannes , Beitzke Dietrich , Loewe Christian , Nitsche Christian , Hengstenberg Christian , Kammerlander Andreas Anselm , Bonderman Diana 
Published: August 2023

Abstract

Aims
The pathophysiological hallmark of cardiac amyloidosis (CA) is the deposition of amyloid within the myocardium. Consequently, extracellular volume (ECV) of affected patients increases. However, studies on ECV progression over time are lacking. We aimed to investigate the progression of ECV and its prognostic impact in CA patients.

Methods and results
Serial cardiac magnetic resonance (CMR) examinations, including ECV quantification, were performed in consecutive CA patients. Between 2012 and 2021, 103 CA patients underwent baseline and follow-up CMR, including ECV quantification. Median ECVs at baseline of the total (n = 103), transthyretin [(ATTR) n = 80], and [light chain (AL) n = 23] CA cohorts were 48.0%, 49.0%, and 42.6%, respectively. During a median period of 12 months, ECV increased significantly in all cohorts [change (Δ) +3.5% interquartile range (IQR): −1.9 to +6.9, P &lt; 0.001; Δ +3.5%, IQR: −2.0 to +6.7, P &lt; 0.001; and Δ +3.5%, IQR: −1.6 to +9.1, P = 0.026]. Separate analyses for treatment-naïve (n = 21) and treated (n = 59) ATTR patients revealed that the median change of ECV from baseline to follow-up was significantly higher among untreated patients (+5.7% vs. +2.3%, P = 0.004). Survival analyses demonstrated that median change of ECV was a predictor of outcome [total: hazard ratio (HR): 1.095, 95% confidence interval (CI): 1.047–1.0145, P &lt; 0.001; ATTR: HR: 1.073, 95% CI: 1.015–1.134, P = 0.013; and AL: HR: 1.131, 95% CI: 1.041–1.228, P = 0.003].

Conclusion
The present study supports the use of serial ECV quantification in CA patients, as change of ECV was a predictor of outcome and could provide information in the evaluation of amyloid-specific treatments.
First impressions of a new face are shaped by infection concerns
Authors: Bressan Paola 
Published: August 2023

Abstract
Along with a classical immune system, we have evolved a behavioral one that directs us away from potentially contagious individuals. Here I show, using publicly available cross-cultural data, that this adaptation is so fundamental that our first impressions of a male stranger are largely driven by the perceived health of his face. Positive (likeable, capable, intelligent, trustworthy) and negative (unfriendly, ignorant, lazy) first impressions are affected by facial health in adaptively different ways, inconsistent with a mere halo effect; they are also modulated by one’s current state of health and inclination to feel disgusted by pathogens. These findings, which replicated across two countries as different as the USA and India, suggest that instinctive perceptions of badness and goodness from faces are not two sides of the same coin but reflect the (nonsymmetrical) expected costs and benefits of interaction. Apparently, pathogens run the show—and first impressions come second. Lay Summary: Our first impressions of strangers (whether they seem trustworthy, intelligent, unfriendly, or aggressive) are shaped by how healthy their faces look and by our unconscious motivation to avoid infections. Bad and good impressions turn out to reflect the concrete, potentially vital, expected costs and benefits of interacting with our fellow humans. Apparently, pathogens run the show—and first impressions come second.
Exchange rate and inflation under weak monetary policy: Turkey verifies theory
Authors: Gürkaynak Refet S , Kısacıkoğlu Burçin , Lee Sang Seok 
Published: August 2023

SUMMARY
For the academic audience, this paper presents the outcome of a well-identified, large change in the monetary policy rule from the lens of a standard New Keynesian model and asks whether the model properly captures the effects. For policymakers, it presents a cautionary tale of the dismal effects of ignoring basic macroeconomics. In doing so, it also clarifies how neo-Fisherian disinflation may work or fail, in theory and in practice. The Turkish monetary policy experiment of the past decade, stemming from a belief of the government that higher interest rates cause higher inflation, provides an unfortunately clean exogenous variance in the policy rule. The mandate to keep rates low, and the frequent policymaker turnover orchestrated by the government to enforce this, led to the Taylor principle not being satisfied and eventually a negative coefficient on inflation in the policy rule. In such an environment, was the exchange rate still a random walk? Was inflation anchored? Does the “standard model” suffice to explain the broad contours of macroeconomic outcomes in an emerging economy with large identifying variance in the policy rule? There are no surprises for students of open-economy macroeconomics; the answers are no, no and yes.
On the effect of the New Year’s Eve sexual assaults on anti-refugee violence: a rejoinder to Schwitter and Liebe (2023)
Authors: Frey Arun 
Published: August 2023

Abstract
In their comment on my 2020 ESR article, Schwitter and Liebe suggest that the increase in anti-refugee attacks following the 2015 New Year’s Eve sexual assaults (NYE) could be due to a simultaneous broadening of the German Federal Criminal Police Office definition of anti-refugee violence. I address Schwitter and Liebe’s concerns by (i) removing attacks that were included because of the new definition and (ii) restricting the analysis to attacks that were sourced from non-governmental sources. In both cases, the NYE event continues to have a profound effect on anti-refugee attacks, but the revised estimates are smaller than those reported in the original study: for example, in this analysis, the probability of an attack more than doubles in the first week of January 2016, as opposed to tripling in the original study. In line with the original findings, the impact of the NYE event is also more pronounced in districts with low prior levels of anti-refugee hostility.
Laboratory investigation of high-frequency electromagnetic induction measurements for macro-scale relaxation signatures
Authors: Glaser Dan R , Barrowes Benjamin E , Shubitidze Fridon , Slater Lee D 
Published: August 2023

SUMMARYDirect contact, frequency-dependent, electrical relaxation effects in soils are well documented in both conductivity and dielectric permittivity-dominated frequency regimes. These relaxation signatures result from charge displacement in physical processes at varying scales ranging from conductivity-dominated ionic transport at soil–grain pore-fluid interfaces to permittivity-dominated water molecule rotation. Given the physical mechanisms associated with these relaxation signatures, it is possible to gain vital soil characteristics needed for a variety of civil and environmental applications. Yet, at the field scale, these direct contact geophysical methods are generally time-consuming and cumbersome hindering the extent at which data can be reasonably acquired. Here, we evaluate a standoff high-frequency electromagnetic induction (HFEMI) instrument, designed for remote, non-contact detection of non-metallic unexploded ordinance and repurposed as a means to measure soil relaxation effects remotely. The instrument offers a proven interrogation range of 100 kHz–10 MHz but has the ability to record data as low as 100 Hz. In this laboratory study, we demonstrate the effects of sample volume using NaCl solutions, where greater volume samples are necessary to overcome low signal-to-noise signatures. Further, pyrite, a mineral known to exhibit relaxation signatures at low frequencies was used in sand mixtures of varying concentrations and varying pore-fluid conductivity to explore the lower frequency range of the HFEMI instrument. The resulting measured HFEMI responses demonstrated sensitivity to the changes in conductivity due to increased pyrite and pore-fluid NaCl concentrations at high frequencies, but the lower frequency range of 100 Hz to 100 kHz was dominated by system noise, disallowing interrogation of low-frequency relaxation effects. This initial investigation compiles the comparative knowledge for relaxation responses in both direct electrical and standoff electromagnetic measurements while demonstrating high-frequency signatures of low-conductivity soils and sample volume effects. As a result of this research, a new EMI system is in development addressing a lower range of frequencies for continued relaxation process investigations.
Teachers’ Self-Reported Classroom Practices Regarding Dictionary Use: The Role of Teachers’ Attitude and School Level
Authors: Tremblay Ophélie , Plante Isabelle , Fréchette-Simard Catherine 
Published: August 2023

Abstract
This study examined the self-reported practices of 300 elementary and high school Quebec teachers regarding dictionary use (paper and electronic) in the classroom as a function of teaching level and attitudes towards dictionaries. ANOVA results highlighted the diversity of teachers’ pedagogical intentions and students’ learning goals while consulting dictionaries. Results, however, revealed a traditional portrait of dictionary use (e.g., correcting spelling, finding a word definition). In addition, teaching levels did not significantly influence teaching content and activities, nor teachers’ perceptions of students’ goals while using a dictionary. Nonetheless, teachers’ attitudes towards dictionary use were found to significantly predict their classroom practices: those with a positive attitude reported a greater variety of pedagogical intentions (e.g., searching for synonyms) and reported more frequent and diversified dictionary-related activities. In sum, findings underscore the importance of training students and teachers in dictionary use to acquire (and teach) proper and diversified dictionary skills.