bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical application of machine-based deep learning in patients with radiologically presumed adult-type diffuse glioma grades 2 or 3
Authors: Gómez Vecchio Tomás , Neimantaite Alice , Thurin Erik , Furtner Julia , Solheim Ole , Pallud Johan , Berger Mitchel , Widhalm Georg , Bartek Jiri , Häggström Ida , Gu Irene Y H , Jakola Asgeir Store 
Published: November 2024

Abstract

Background
Radiologically presumed diffuse lower-grade glioma (dLGG) are typically non or minimal enhancing tumors, with hyperintensity in T2w-images. The aim of this study was to test the clinical usefulness of deep learning (DL) in IDH mutation prediction in patients with radiologically presumed dLGG.

Methods
Three hundred and fourteen patients were retrospectively recruited from 6 neurosurgical departments in Sweden, Norway, France, Austria, and the United States. Collected data included patients’ age, sex, tumor molecular characteristics (IDH, and 1p19q), and routine preoperative radiological images. A clinical model was built using multivariable logistic regression with the variables age and tumor location. DL models were built using MRI data only, and 4 DL architectures used in glioma research. In the final validation test, the clinical model and the best DL model were scored on an external validation cohort with 155 patients from the Erasmus Glioma Dataset.

Results
The mean age in the recruited and external cohorts was 45.0 (SD 14.3) and 44.3 years (SD 14.6). The cohorts were rather similar, except for sex distribution (53.5% vs 64.5% males, P-value = .03) and IDH status (30.9% vs 12.9% IDH wild-type, P-value &lt;.01). Overall, the area under the curve for the prediction of IDH mutations in the external validation cohort was 0.86, 0.82, and 0.87 for the clinical model, the DL model, and the model combining both models’ probabilities.

Conclusions
In their current state, when these complex models were applied to our clinical scenario, they did not seem to provide a net gain compared to our baseline clinical model.
Expenditure behaviour of pensioners: exploring differences between breadwinners and non-breadwinners
Authors: Muñiz-Fernández Álvaro , Cabanillas-Jiménez Guillermo 
Published: November 2024

Abstract
This article examines the expenditure behaviours of households headed by pensioners who are financially responsible for other household members. By analysing household-level consumption data from the Spanish Family Income Survey from 2018 to 2021, our findings reveal that pensioner-led households with dependents exhibit a 10.2 per cent reduction in total spending compared to pensioner-led households without dependents. Moreover, expenditure on durable and non-durable goods is lower by 10.4 and 8.8 per cent, respectively. We find no heterogeneous effects across income levels or with cohort-fixed effects.
Effectiveness of military spending in reducing the intensity of armed conflict in Sub-Saharan Africa
Authors: AYA Idrissa Aladji 
Published: November 2024

Abstract
This study empirically examines the effectiveness of military spending in reducing the intensity of armed conflict in Sub-Saharan Africa. We use a dynamic probit model, and the results show that military spending reduces the intensity of conflict. It significantly reduces low-intensity conflicts more than high-intensity conflicts. Additionally, the effectiveness of military spending depends on its level and the quality of institutions. Finally, the analysis of transmission channels shows that military spending affects conflict intensity mainly through the channel of military capabilities. We conducted several tests and robustness checks to ensure the validity of our results.
Does gender matter for trade policy? Evidence from contingent protection
Authors: Bros Catherine , Lochard Julie , Upadhayay Neha B 
Published: November 2024

Abstract
Do female heads of government make different policy choices? In this article, we show that gender matters in the definition of international trade policy. We focus on an increasingly used instrument of trade policy, namely contingent protection, that is decided unilaterally by governments. Using panel data covering 149 countries over the period 1995–2019, we provide evidence that female heads of government have been significantly more intensive users of contingent protection. Our results suggest that this gender effect is unlikely to stem from gendered preferences against free trade but rather from an incentive for female heads of government to overcome gender stereotypes in international relations.
Development and Characterization of a 13-Plex Binding Assay to Detect Shigella Antibodies in Human Samples
Authors: Vezzani G , Mancini F , Raso M M , Giannelli C , Nappini R , Gasperini G , Rappuoli R , Berlanda Scorza F , Iturriza M , Micoli F , Rossi O 
Published: November 2024

Abstract
Shigella is the leading bacterial cause of diarrhea worldwide, with increasing levels of antibiotic resistance. The greatest burden is among children aged &lt;5 years in low- and middle-income countries, and efforts are ongoing to develop vaccines against this pathogen. One of the challenges associated with the development of a vaccine against Shigella is the need for a multivalent vaccine covering the most prevalent Shigella serotypes. Epidemiologic studies to better understand the prevalence of the Shigella serotypes and inform vaccination schedules are very useful, with clinical data showing the ability of vaccines to elicit cross-reactive antibodies. Here, we set up a Luminex-based method able to reproducibly measure antibodies specific to 13 Shigella antigens in human sera. This method will allow the rapid collection of large amounts of data based on the analysis of serum samples from vaccinated individuals or people naturally exposed to Shigella, supporting the development of a vaccine against this disease.
Disrupted nitric oxide homeostasis impacts fertility through multiple processes including protein quality control
Authors: Treffon Patrick , Vierling Elizabeth 
Published: November 2024

Abstract
Plant fertility is fundamental to plant survival and requires the coordinated interaction of developmental pathways and signaling molecules. Nitric oxide (NO) is a small, gaseous signaling molecule that plays crucial roles in plant fertility as well as other developmental processes and stress responses. NO influences biological processes through S-nitrosation, the posttranslational modification of protein cysteines to S-nitrosocysteine (R-SNO). NO homeostasis is controlled by S-nitrosoglutathione reductase (GSNOR), which reduces S-nitrosoglutathione (GSNO), the major form of NO in cells. GSNOR mutants (hot5-2/gsnor1) have defects in female gametophyte development along with elevated levels of reactive nitrogen species and R-SNOs. To better understand the fertility defects in hot5-2, we investigated the in vivo nitrosoproteome of Arabidopsis (Arabidopsis thaliana) floral tissues coupled with quantitative proteomics of pistils. To identify protein-SNOs, we used an organomercury-based method that involves direct reaction with S-nitrosocysteine, enabling specific identification of S-nitrosocysteine–containing peptides and S-nitrosated proteins. We identified 1,102 endogenously S-nitrosated proteins in floral tissues, of which 1,049 were unique to hot5-2. Among the identified proteins, 728 were novel S-nitrosation targets. Notably, specific UDP-glycosyltransferases and argonaute proteins are S-nitrosated in floral tissues and differentially regulated in pistils. We also discovered S-nitrosation of subunits of the 26S proteasome together with increased abundance of proteasomal components and enhanced trypsin-like proteasomal activity in hot5-2 pistils. Our data establish a method for nitrosoprotein detection in plants, expand knowledge of the plant S-nitrosoproteome, and suggest that nitro-oxidative modification and NO homeostasis are critical to protein quality control in reproductive tissues.
Changes in diabetes care and management practices during the COVID-19 pandemic
Authors: Vashist Kushagra , Frediani Jennifer K , Weber Mary Beth , Ali Mohammed K , Narayan K M Venkat , Patel Shivani A 
Published: November 2024

Abstract

Background
We examined changes in diabetes care and management practices before and during the COVID-19 pandemic.

Methods
Population-based data regarding four diabetes-related healthcare engagement and four self-management indicators were obtained from adults with diabetes surveyed in 19 US States and Washington DC through the Behavioral Risk Factor Surveillance System. Using logistic regression, we estimated changes in the prevalence of each indicator, overall and by sociodemographic subgroups in 2019 (before the pandemic) and 2021 (during the pandemic).

Results
Between 2019 and 2021, the prevalence of biannual HbA1c tests reduced by 2.6 percentage points (pp; 95% confidence interval: −4.8, −0.4), from 75.4% to 73.1%, and prevalence of annual eye exams fell by 4.0 pp (−6.2, −2.8), from 72.2% to 68.7%. The composite indicator of engagement with healthcare for diabetes control fell by 3.5 pp (−5.9, −1.1), from 44.9% to 41.9%. Of self-management behaviors, avoidance of smoking increased by 2.0 pp (0.4, 3.6) from 84.7% to 87.1%.

Conclusions
The findings suggest a deterioration of the uptake of evidence-based, preventive health services requiring laboratory services and clinical examination for diabetes control during the pandemic. On the other hand, smoking rates decreased, suggesting potential positive impacts of the pandemic on health behaviors in people with diabetes.
Simulation-based inference of the sky-averaged 21-cm signal from CD-EoR with REACH
Authors: Saxena Anchal , Meerburg P Daniel , Weniger Christoph , Acedo Eloy de Lera , Handley Will 
Published: November 2024

ABSTRACT
The redshifted 21-cm signal from the cosmic dawn and epoch of reionization carries invaluable information about the cosmology and astrophysics of the early Universe. Analysing data from a sky-averaged 21-cm signal experiment requires navigating through an intricate parameter space addressing various factors such as foregrounds, beam uncertainties, ionospheric distortions, and receiver noise for the search of the 21-cm signal. The traditional likelihood-based sampling methods for modelling these effects could become computationally demanding for such complex models, which makes it infeasible to include physically motivated 21-cm signal models in the analysis. Moreover, the inference is driven by the assumed functional form of the likelihood. We demonstrate how simulation-based inference through truncated marginal neural ratio estimation (TMNRE) can naturally handle these issues at a reduced computational cost. We estimate the posterior distribution on our model parameters with TMNRE for simulated mock observations, incorporating beam-weighted foregrounds, physically motivated 21-cm signal, and radiometric noise. We find that maximizing information content by analysing data from multiple time slices and antennas significantly improves the parameter constraints and enhances the exploration of the cosmological signal. We discuss the application of TMNRE for the current configuration of the REACH experiment and demonstrate its potential for exploring new avenues.
Data inaccuracy quantification and uncertainty propagation for bibliometric indicators
Authors: Donner Paul 
Published: November 2024

Abstract
This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, which are used to predict error-free data. Through direct Monte Carlo simulation—drawing many replicates of predicted data from the estimated regression models for the same input data—probability distributions for indicator values can be obtained which provide the information on their uncertainty due to data errors. It is demonstrated how uncertainty in base quantities, such as the number of publications of certain document types of a unit of analysis and the number of citations of a publication, can be propagated along a measurement model into final indicator values. Synthetic examples are used to illustrate the method and real bibliometric research evaluation data is used to show its application in practice. Though in this contribution we just use two out of a larger number of known bibliometric error categories and therefore can account for only some part of the total uncertainty due to inaccuracies, the latter example reveals that average values of citation impact scores of publications of research groups need to be used very cautiously as they often have large margins of error resulting from data inaccuracies.
How qualitative criteria can improve the assessment process of interdisciplinary research proposals
Authors: Schölvinck Anne-Floor , Uygun-Tunç Duygu , Lakens Daniël , Vaesen Krist , Hessels Laurens K 
Published: November 2024

Abstract
Despite the increasing recognition for the scientific and societal potential of interdisciplinary research, selection committees struggle with the evaluation of interdisciplinary proposals. Interdisciplinary proposals include a wider range of theories and methods, involve a more diverse team, pose a higher level of uncertainty, and their evaluation requires expertise from multiple disciplines. In this study, we investigate the possibility to support the evaluation of interdisciplinary research proposals with measures of interdisciplinary research quality. Based on the literature, we curated a set of qualitative criteria and bibliometric indicators. Subsequently, we examined their feasibility using interviews with interdisciplinary researchers and a re-assessment session of a grant-allocation procedure. In the re-assessment session members of an original evaluation panel assessed four original research proposals again, but now supported with our measures. This study confirmed the potential of qualitative criteria to assess the interdisciplinarity or research proposals. These indicators helped to make explicit what different people mean with interdisciplinary research, which improved the quality of the discussions and decision-making. The utility of bibliometric indicators turned out to be limited, due to technical limitations and concerns about unintended side effects.
A simple phylogenetic approach to analyze hypermutated HIV proviruses reveals insights into their dynamics and persistence during antiretroviral therapy
Authors: Shahid Aniqa , Jones Bradley R , Duncan Maggie C , MacLennan Signe , Dapp Michael J , Kuniholm Mark H , Aouizerat Bradley , Archin Nancie M , Gange Stephen , Ofotokun Igho , Fischl Margaret A , Kassaye Seble , Goldstein Harris , Anastos Kathryn , Joy Jeffrey B , Brumme Zabrina L 
Published: November 2024

Abstract
Hypermutated proviruses, which arise in a single Human Immunodeficiency Virus (HIV) replication cycle when host antiviral APOBEC3 proteins introduce extensive guanine to adenine mutations throughout the viral genome, persist in all people living with HIV receiving antiretroviral therapy (ART). However, hypermutated sequences are routinely excluded from phylogenetic trees because their extensive mutations complicate phylogenetic inference, and as a result, we know relatively little about their within-host evolutionary origins and dynamics. Using &gt;1400 longitudinal single-genome-amplified HIV env-gp120 sequences isolated from six women over a median of 18 years of follow-up—including plasma HIV RNA sequences collected over a median of 9 years between seroconversion and ART initiation, and &gt;500 proviruses isolated over a median of 9 years on ART—we evaluated three approaches for masking hypermutation in nucleotide alignments. Our goals were to (i) reconstruct phylogenies that can be used for molecular dating and (ii) phylogenetically infer the integration dates of hypermutated proviruses persisting during ART. Two of the approaches (stripping all positions containing putative APOBEC3 mutations from the alignment or replacing individual putative APOBEC3 mutations in hypermutated sequences with the ambiguous base R) consistently normalized tree topologies, eliminated erroneous clustering of hypermutated proviruses, and brought env-intact and hypermutated proviruses into comparable ranges with respect to multiple tree-based metrics. Importantly, these corrected trees produced integration date estimates for env-intact proviruses that were highly concordant with those from benchmark trees that excluded hypermutated sequences, supporting the use of these corrected trees for molecular dating. Subsequent molecular dating of hypermutated proviruses revealed that these sequences spanned a wide within-host age range, with the oldest ones dating to shortly after infection. This indicates that hypermutated proviruses, like other provirus types, begin to be seeded into the proviral pool immediately following infection and can persist for decades. In two of the six participants, hypermutated proviruses differed from env-intact ones in terms of their age distributions, suggesting that different provirus types decay at heterogeneous rates in some hosts. These simple approaches to reconstruct hypermutated provirus’ evolutionary histories reveal insights into their in vivo origins and longevity toward a more comprehensive understanding of HIV persistence during ART.
Phenylacetic acid metabolism in land plants: novel pathways and metabolites
Authors: Hladík Pavel , Brunoni Federica , Žukauskaitė Asta , Zatloukal Marek , Bělíček Jakub , Kopečný David , Briozzo Pierre , Ferchaud Nathan , Novák Ondřej , Pěnčík Aleš 
Published: November 2024

AbstractIn recent years, substantial progress has been made in exploring auxin conjugation and metabolism, primarily aiming at indole-3-acetic acid (IAA). However, the metabolic regulation of another key auxin, phenylacetic acid (PAA), remains largely uncharacterized. Here, we provide a comprehensive exploration of PAA metabolism in land plants. Through LC-MS screening across multiple plant species and their organs, we identified four previously unreported endogenous PAA metabolites: phenylacetyl-leucine (PAA-Leu), phenylacetyl-phenylalanine (PAA-Phe), phenylacetyl-valine (PAA-Val), and phenylacetyl-glucose (PAA-glc). Enzyme assays, genetic evidence, crystal structures, and docking studies demonstrate that PAA and IAA share core metabolic machinery, revealing a complex regulatory network that maintains auxin homeostasis. Furthermore, our study of PAA conjugation with amino acids and glucose suggests limited compensatory mechanisms within known conjugation pathways, pointing to the existence of alternative metabolic routes in land plants. These insights advance our knowledge of auxin-specific metabolic networks and highlight the unique complexity within plant hormone regulation.
Stroke and Motor Recovery are Associated with Regional and Age-Specific Changes in Periodic and Aperiodic Cortical Activity
Authors: Albertson Asher J. , Landsness Eric. C. , Eisfelder Margaret , Young Brittany M , Judge Bradley , Brier Matthew R. , Euler Matthew J. , Cramer Steven C. , Lee Jin-Moo , Lohse Keith R 
Published: November 2024

AbstractNormal aging is associated with widespread changes in neuronal structure, function, and activity. The consequences of focal brain injury on global neuronal activity in aged individuals are poorly understood. Historically, stroke and aging have been associated with changes in narrow-band periodic neuronal activity, however recent work has highlighted the importance of broad-band aperiodic activity. Aperiodic activity is represented by the 1/f slope of power spectral density generated by cortical activity.Abnormalities in aperiodic activity have been identified in psychiatric disorders and stroke, are associated with cognitive dysfunction in aging, and have been hypothesized to reflect changes in excitation/inhibition balance. Here we sought to further explore changes in both periodic and aperiodic cortical activity in neurotypical intact young and aged healthy individuals and individuals with stroke. We compared “resting state” electroencephalograms from all participants after applying thespecparamalgorithm, which decomposes the power spectrum into aperiodic and periodic components. We also correlated stroke outcomes using previously obtained tests of motor outcome (box and block) to average whole cortex spectral slopes within the stroke group. Consistent with prior work we found a significant flattening (decrease in exponent) of power spectral slope with normal aging. We also found that both aging and stroke were associated with fewer periodic peaks within the power spectrum. Interestingly, we found that stroke was associated with a significant increase in spectral slope, but age moderated this effect. Younger stroke patients showed minimal difference in slope while older stroke patients had significantly steeper slopes (opposite to the direction in normal aging). Using MRIs from stroke participants we investigated the lesion locations most associated with changes in slope. Interestingly deep lesions were observed to have the greatest influence on cortical spectral slope. Finally, slope in the stroke group was correlated with performance on a test of manual dexterity, however this correlation was much more significant in aged individuals. Our data suggest that stroke in the aged brain has unique effects on aperiodic activity possibly reflecting unique influence of injury on cerebral excitation/inhibition balance in aged individuals and that the degree of these changes may be related to stroke outcomes.
Language model generatescis-regulatory elements across prokaryotes
Authors: Xia Yan , Sun Jinyuan , Du Xiaowen , Liang Zeyu , Shi Wenyu , Guo Shuyuan , Huo Yi-Xin 
Published: November 2024

AbstractDeep learning had succeeded in designingCis-regulatory elements (CREs) for certain species, but necessitated training data derived from experiments. Here, we present Promoter-Factory, a protocol that leverages language models (LM) to design CREs for prokaryotes without experimental prior. Millions of sequences were drawn from thousands of prokaryotic genomes to train a suite of language models, named PromoGen2, and achieved the highest zero-shot promoter strength prediction accuracy among tested LMs. Artificial CREs designed with Promoter-Factory achieved a 100% success rate to express gene inEscherichia coli,Bacillus subtilis, andBacillus licheniformis. Furthermore, most of the promoters designed targetingJejubactersp. L23, a halophilic bacterium without available CREs, were active and successfully drove lycopene overproduction. The generation of 2 million putative promoters across 1,757 prokaryotic genera, along with the Promoter-Factory protocol, will significantly expand the sequence space and facilitate the development of an extensive repertoire of prokaryotic CREs.
Unpacking fitness differences between invaders in a multispecies context
Authors: Freire Tomas , Madec Sten , Gjini Erida 
Published: November 2024

AbstractEcosystems are constantly exposed to new strains of a given species. Which strain will be able to invade a resident multi-species community depends on the strain’s relative fitness. Here we develop an approach to quantify fitness differences between two co-invading strains based on the replicator equation. By assuming that the resident species’ frequencies remain constant during the initial phase of invasion, we are able to determine the invasion fitness differential between the two strains, which drives growth rate differences post-invasion. We then apply our approach to a critical current global problem: invasion of the gut microbiota by antibiotic resistant strains of the pathobiontEscherichia coli. Our results underscore the context-dependent nature of fitness and demonstrate how species frequencies in a host environment can explicitly modulate the selection coefficient between two strains. This framework can predict relative fitness in new environments and may contribute to design strategies to lower resistance levels in microbiomes.