bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of exopolysaccharides Psl and Pel in resistance of
Pseudomonas aeruginosa
to the oxidative stressors sodium hypochlorite and hydrogen peroxide
Authors: da Cruz Nizer Waleska S. , Allison Kira N. , Adams Madison E. , Vargas Mario A. , Ahmed Duale , Beaulieu Carole , Raju Deepa , Cassol Edana , Howell P. Lynne , Overhage Joerg 
Published: August 2024

ABSTRACT

Pseudomonas aeruginosa
is well-known for its antimicrobial resistance and the ability to survive in harsh environmental conditions due to an abundance of resistance mechanisms, including the formation of biofilms and the production of exopolysaccharides. Exopolysaccharides are among the major components of the extracellular matrix in biofilms and aggregates of
P. aeruginosa
. Although their contribution to antibiotic resistance has been previously shown, their roles in resistance to oxidative stressors remain largely elusive. Here, we studied the function of the exopolysaccharides Psl and Pel in the resistance of
P. aeruginosa
to the commonly used disinfectants and strong oxidizing agents NaOCl and H
2
O
2
. We observed that the simultaneous inactivation of Psl and Pel in
P. aeruginosa
PAO1 mutant strain ∆
pslA pelF
resulted in a significant increase in susceptibility to both NaOCl and H
2
O
2
. Further analyses revealed that Pel is more important for oxidative stress resistance in
P. aeruginosa
and that the form of Pel (i.e., cell-associated or cell-free) did not affect NaOCl susceptibility. Additionally, we show that Psl/Pel-negative strains are protected against oxidative stress in co-culture biofilms with
P. aeruginosa
PAO1 WT. Taken together, our results demonstrate that the EPS matrix and, more specifically, Pel exhibit protective functions against oxidative stressors such as NaOCl and H
2
O
2
in
P. aeruginosa
.

IMPORTANCE

Biofilms are microbial communities of cells embedded in a self-produced polymeric matrix composed of polysaccharides, proteins, lipids, and extracellular DNA. Biofilm bacteria have been shown to possess unique characteristics, including increased stress resistance and higher antimicrobial tolerance, leading to failures in bacterial eradication during chronic infections or in technical settings, including drinking and wastewater industries. Previous studies have shown that in addition to conferring structure and stability to biofilms, the polysaccharides Psl and Pel are also involved in antibiotic resistance. This work provides evidence that these biofilm matrix components also contribute to the resistance of
Pseudomonas aeruginosa
to oxidative stressors including the widely used disinfectant NaOCl. Understanding the mechanisms by which bacteria escape antimicrobial agents, including strong oxidants, is urgently needed in the fight against antimicrobial resistance and will help in developing new strategies to eliminate resistant strains in any environmental, industrial, and clinical setting.
Evaluation of the quickmic system in the rapid diagnosis of Gram-negative bacilli bacteremia
Authors: García-Rivera Celia , Ricart-Silvestre Andrea , Parra Grande Mónica , Ventero María Paz , Tyshkovska-Germak Iryna , Sánchez-Bautista Antonia , Merino Esperanza , Rodríguez Juan Carlos 
Published: August 2024

ABSTRACT

Rapid microbiological diagnosis of the antibiotic susceptibility of Gram-negative bacilli is a priority in clinical microbiology, especially in cases of bacteremia. The rapid advancement of antimicrobial resistance proposes a challenge for empirical antibiotic therapy and shows the need for fast antibiotic susceptibility diagnostics to guide treatments. The QuickMIC System (Gradientech AB, Uppsala, Sweden) is a recently developed rapid diagnostic tool for antibiotic susceptibility testing. Our study evaluates a rapid phenotypic system (QuickMIC) that provides information on the susceptibility of 12 antibiotics against
Escherichia coli
,
Klebsiella spp
.,
Pseudomonas aeruginosa
,
Acinetobacter baumannii
,
Enterobacter cloacae
,
Proteus spp
.,
Citrobacter spp.,
and
Serratia marcescens
. A total of 816 antibiotic/microorganism combinations were tested, resulting in eight discrepancies. The concordance between the antibiotics offered by QuickMIC and reference methods (MicroScan WalkAway plus system, Beckman Coulter; Etest (BioMerieux microdilution system (Bruker); Real-time PCR (GeneXpert, Cepheid); and immunochromatography (Biotech) was 99.02%. Time elapsed to obtain a valid minimal inhibitory concentration (MIC) was between 2 and 4 h. The QuickMIC system allows for the early adjustment of antibiotic treatment in these infections. Given the existing limitations of currently available rapid methods, its clinical utility is particularly relevant in the management of
P. aeruginosa
infections and AmpC-producing Enterobacterales. The use of rapid methods can help diversify antibiotic use and reduce carbapenem consumption.

IMPORTANCE

The rapid diagnosis of antibiotic sensitivity in Gram-negative bacilli is of paramount importance in clinical microbiology, particularly in cases of bacteremia. The escalating challenge of antimicrobial resistance underscores the need for expeditious antibiotic susceptibility diagnostics to guide empirical antibiotic therapy effectively. In light of this, we present our study that evaluates the QuickMIC System, a recently developed rapid diagnostic antibiogram. QuickMIC System, offers a novel approach to phenotypic testing, providing information on the activity of 12 antibiotics against key pathogens, including
Escherichia coli
,
Klebsiella spp
.,
Pseudomonas aeruginosa
,
Acinetobacter baumannii
,
Enterobacter cloacae
,
Proteus spp
.,
Citrobacter spp
., and
Serratia marcescens
. Our investigation involved testing a total of 816 antibiotic/microorganism combinations. The study demonstrated an impressive 99.02% concordance between the QuickMIC System and the reference methods, with only eight discrepancies observed. The time to actionable minimum inhibitory concentration (MIC) ranged between 2 and 4 h, highlighting the system's efficiency in providing rapid results.
The physiological consequences of and recovery following the Australian Special Forces Selection Course
Authors: Uphill Angela C. , Kendall Kristina L. , Baker Bradley A. , Guppy Stuart N. , Brown Hannah M. , Vacher Michael , Nindl Bradley C. , Haff G. Gregory 
Published: August 2024

This study aimed to determine the energy requirements, physiological consequences, and recovery rate from the Australian Special Forces Selection Course. Ninety-three male soldiers (mean ± SD, 28.1 ± 3.6 years, 1.81 ± 0.1 m, 85.1 ± 8.1 kg) volunteered for this study. Body composition via dual-energy X-ray absorptiometry, hormones and resting metabolic rate were assessed before, immediately after, and at 1, 3, 5, and 8 weeks post-course. Energy expenditure, assessed via doubly-labelled water during the first 10 days of the course significantly exceeded energy intake (expenditure: 7680 ± 1095 kcal.day–1, intake: 3859 ± 704 kcal.day –1). Body mass (Δ –6.8 ± 1.9 kg, p < 0.01), fat mass (Δ –4.2 ± 1.0 kg, p < 0.0001) and lean mass (Δ –3.0 ± 1.7 kg, p < 0.0001) were significantly reduced in response to the course and returned to baseline 1–3 weeks post-course. Total testosterone, free testosterone, free triiodothyronine, free thyroxine and insulin like growth factor-1 significantly ( p < 0.001) declined following the course, while cortisol and sex hormone binding globulin increased ( p < 0.001). All hormones, except insulin like growth factor-1, returned to baseline concentrations within 1–3 weeks post-course. Resting metabolic rate decreased ( p < 0.01) in response to the course, and subsequently rebounded above baseline levels at 1 week post-course. The Special Forces Selection Course involved high energy output and a substantial caloric deficit, resulting in body mass loss and significant hormonal disruption that took weeks to recover. These results highlight the energy requirements, physiological consequences, and recovery processes from the Australian Special Forces Selection Course.
Enhancing Graph Neural Networks via Memorized Global Information
Authors: Zeng Ruihong , Fang Jinyuan , Liu Siwei , Meng Zaiqiao , Liang Shangsong 
Published: August 2024

Graph neural networks (GNNs) have gained significant attention for their impressive results on different graph-based tasks. The essential mechanism of GNNs is the message-passing framework, whereby node representations are aggregated from local neighborhoods. Recently, Transformer-based GNNs have been introduced to learn the long-range dependencies, enhancing performance. However, their quadratic computational complexity, due to the attention computation, has constrained their applicability on large-scale graphs. To address this issue, we propose MGIGNN (
M
emorized
G
lobal
I
nformation
G
raph
N
eural
N
etwork), an innovative approach that leverages memorized global information to enhance existing GNNs in both transductive and inductive scenarios. Specifically, MGIGNN captures long-range dependencies by identifying and incorporating global similar nodes, which are defined as nodes exhibiting similar features, structural patterns and label information within a graph. To alleviate the computational overhead associated with computing embeddings for all nodes, we introduce an external memory module to facilitate the retrieval of embeddings and optimize performance on large graphs. To enhance the memory-efficiency, MGIGNN selectively retrieves global similar nodes from a small set of candidate nodes. These candidate nodes are selected from the training nodes based on a sparse node selection distribution with a Dirichlet prior. This selecting approach not only reduces the memory size required but also ensures efficient utilization of computational resources. Through comprehensive experiments conducted on ten widely-used and real-world datasets, including seven homogeneous datasets and three heterogeneous datasets, we demonstrate that our MGIGNN can generally improve the performance of existing GNNs on node classification tasks under both inductive and transductive settings.
Singular e como todo mundo: visibilidade e as pessoas com deficiência
Authors: Sanz Claudia Linhares , Palatucci Giovanna 
Published: August 2024

The article analyzes the concept of visibility aiming to create theoretical bases to think about the invisibility of the person with disabilities today. In an essayistic perspective, it articulates theoretical review and testimonials of these people on social networks, in three movements: it thinks ofvisibility as social recognition; it discusses the visible through the notion of visibility regime; itanalyzes its current configurations, when its meaning is being reduced to mere display. It deals, finally, with an alterity in contemporary relations between image, visibility and recognition, requiring that people with disabilities, in addition to conquer places in the space of the visible, create different semantics from those hegemonically imposed, even by images.
Metacoalizão e os novos papéis de broker: o caso Observatório do Clima
Authors: Salmi Frederico , Dowbor Monika , Fleury Lorena Cândido 
Published: August 2024

This article presents an analysis of the Observatório do Clima network in the light of the categories advocacy coalition, specifically broker. A conceptual-methodological framework was mobilized based on the theoretical frameworks of the sociology of critical utopia on the climate issue and studies of socio-state interactions. Critical interpretive analysis was used as a methodological strategy. The result is the proposal of a new category, metacoalition, and two complementary roles, producer (of knowledge) and monitor (of public policies), to Gurza Lavalle and von Bülow’s (2014, 2015) conceptual framework. In addition, a new agent is introduced to the analytical scenario as a structuring configuration element of the new two roles: the artificial climate agent.
Psychosocial Health and the Association Between Cerebral Small Vessel Disease Markers With Dementia: The ARIC Study
Authors: Eswaran Surabhee , Knopman David S. , Koton Silvia , Kucharska-Newton Anna M. , Liu Albert C. , Liu Chelsea , Lutsey Pamela L. , Mosley Thomas H. , Palta Priya , Sharrett A. Richey , Sullivan Kevin J. , Walker Keenan A. , Gottesman Rebecca F. , Groechel Renee C. 
Published: August 2024

BACKGROUND:
Associations between magnetic resonance imaging markers of cerebral small vessel disease (CSVD) and dementia risk in older adults have been established, but it remains unclear how lifestyle factors, including psychosocial health, may modify this association.

METHODS:
Social support and social isolation were assessed among participants of the community-based ARIC (Atherosclerosis Risk in Communities) Study, via self-reported questionnaires (1990–1992). Following categorization of both factors, participants were classified as having strong or poor mid-life social relationships. At visit 5 (2011–2013), participants underwent 3T brain magnetic resonance imaging quantifying CSVD measures: white matter hyperintensity volume, microbleeds (subcortical), infarcts (lacunar), and white matter integrity (diffusion tensor imaging). Incident dementia cases were identified from the time of imaging through December 31, 2020 with ongoing surveillance. Associations between CSVD magnetic resonance imaging markers and incident dementia were evaluated using Cox proportional-hazard regressions adjusted for demographic and additional risk factors (from visit 2). Effect modification by mid-life social relationships was evaluated.

RESULTS:

Of the 1977 participants with magnetic resonance imaging, 1617 participants (60.7% women; 26.5% Black participants; mean age at visit 2, 55.4 years) were examined. In this sample, mid-life social relationships significantly modified the association between white matter hyperintensity volume and dementia risk (
P
interaction=0.001). Greater white matter hyperintensity volume was significantly associated with risk of dementia in all participants, yet, more substantially in those with poor (hazard ratio, 1.84 [95% CI, 1.49–2.27]) versus strong (hazard ratio, 1.26 [95% CI, 1.08–1.47]) mid-life social relationships. Although not statistically significant, subcortical microbleeds in participants with poor mid-life social relationships were associated with a greater risk of dementia, relative to those with strong social relationships, in whom subcortical microbleeds were no longer associated with elevated dementia risk.

CONCLUSIONS:
The elevated risk of dementia associated with CSVD may be reduced in participants with strong mid-life social relationships. Future studies evaluating psychosocial health through the life course and the mechanisms by which they modify the relationship between CSVD and dementia are needed.
Developing an index of national research capacity
Authors: Wagner Caroline S. , Whetsell Travis A. 
Published: August 2024

Abstract
We test the feasibility of incorporating broad social, political, and governance indicators with standard metrics as a way to enrich assessment of national research capacity. We factor analyze two sets of variables for 174 countries from 2012 to 2021, one being tradtional measures associated with national science and technology capacity, such as spending, and a second being broader social, political, and governance measures, such as academic freedom. As expected, two factors emerge, one for raw or “core” research capacity and the other indicating the wider governance context. Further analysis shows convergent validity within the two factors and divergent validity between them. The analysis also quantifies the contribution of each indicator to each factor. Nations rank differently for each factor and also when combined. Ranks vary as a function of the chosen aggregation method. As a test of the predictive validity of the capacity index, we find both factors to be associated with country-level field-weighted citation indices. Policymakers and analysts may find useful feedback from this approach to quantifying national research strength.
Characterisation, antibacterial activity, and prebiotic potential of dried Hermetia illucens L. larvae and of their fractions
Authors: Bonomini M.G. , Verstringe S. , Bruggeman G. , Vandercruyssen R. , Carmans H. , Caligiani A. 
Published: August 2024

Abstract
In this study, black soldier fly (BSF) dried larvae were fractionated into their defatted, lipid, protein, and chitin-rich fractions. The samples were then characterised in terms of proximate composition, analysis of amino acids, analysis of the molecular weight distribution of proteins via gel electrophoresis, and fatty acids analysis of the lipid fraction. The antibacterial activity of all fractions was determined against Escherichia coli F4 and Streptococcus suis, two common swine pathogens. Finally, the prebiotic activity of the whole larvae and of their protein isolate and chitin-rich pellet was determined for Limosilactobacillus reuteri, a naturally occurring species in the gastro-intestinal tract of the pig. The results on amino acid profile showed that the protein extraction method used was not fully effective in cleaving chitin-bound proteins, as expected, as the true protein content of the chitin-rich sample was 48.5%. This was in accordance with the SDS-PAGE analysis, where the molecular weight distribution of proteins in the protein isolate sample did not show band at higher molecular weight, which were instead present in the chitin-rich sample. The analysis of fatty acid (FA) profile showed that lauric acid was the most abundant FA, in accordance with the literature. The results on microbiological analyses highlighted how all nitrogen-containing samples showed antibacterial activity against E. coli, the highest being the defatted fraction at 1% with a decrease of −0.77 log CFU/mL, while only the lipid fraction against S. suis (−0.48 log CFU/mL at 1%). All tested samples showed prebiotic activity for L. reuteri, but it was noticed that the increase in chitin concentration resulted in the decrease of the prebiotic effect. By combining the results of both antibacterial and prebiotic tests, it could be inferred that chitin might be considered as an antibacterial compound.
Spatial Aligned Mean: A Method to Improve Consensus Forecasts of Precipitation from Convection-Allowing Model Ensembles
Authors: Lee ChangJae , Brewster Keith A. , Snook Nathan , Spencer Phillip , Park Jun 
Published: August 2024

Abstract
Ensembles of convection-allowing model (CAM) forecasts are increasingly being used in operational numerical weather forecasting. Several approaches have been devised to find consensus among ensemble forecast fields, including the arithmetic ensemble mean and, more recently, the patchwise localized probability-matched (LPM) mean. However, differences in spatial distribution and intensity of precipitation features among ensemble members make it difficult to construct an ensemble mean product that characterizes the consensus while preserving precipitation structures forecasted by the individual ensemble members. To overcome this problem, this study aims to develop and test a method for improving ensemble consensus precipitation forecasts by directly considering the spatial offsets among ensemble members. This study uses a multiscale spatial alignment technique to align the precipitation features of each ensemble member to a common location, and the spatial aligned mean (SAM) is obtained by averaging the realigned members. It is shown that implementing SAM and subsequently applying the LPM technique to the average of all aligned members (SAM–LPM) can significantly improve the warm season precipitation forecast scores using common metrics such as equitable threat score (ETS). Also, improvement in the structure of features of heavy rainfall is shown from summer 2023 flash-flooding cases. Thus, SAM and SAM–LPM can be excellent candidate methods for calculating an ensemble consensus and providing ensemble consensus guidance to forecasters.

Significance Statement
High-impact rainfall events, such as flash floods, result in many billion-dollar loss events in the United States each year. This study seeks to improve the prediction of such events when using guidance from convection-allowing model (CAM) ensemble forecasts, such as the U.S. operational High-Resolution Ensemble Forecast (HREF) and the nascent Rapid Refresh Forecast System (RRFS). The proposed method, the spatial aligned mean (SAM), directly addresses the common issue of disparity in the predicted location of convective systems among ensemble members that confounds traditional ensemble consensus methods. In this study, it is found that SAM improves ensemble consensus guidance for high-impact rainfall events in both the HREF and the Center for Analysis and Prediction of Storms (CAPS) Finite-Volume Cubed-Sphere (FV3)-limited area model (LAM) CAM ensemble forecast system, a proxy for the future RRFS.
Development and Validation of NOAA’s 20-Year Global Wave Ensemble Reforecast
Authors: Campos Ricardo M. , Abdolali Ali , Alves Jose-Henrique , Masarik Matthew , Meixner Jessica , Mehra Avichal , Figurskey Darin , Banihashemi Saeideh , Sienkiewicz Joseph , Lumpkin Rick 
Published: August 2024

Abstract
A new 20-yr wave reforecast was generated based on the NOAA Global Ensemble Forecast System, version 12 (GEFSv12). It was produced using the same wave model setup as the NCEP’s operational GEFSv12 wave component, which employs the numerical wave model WAVEWATCH III and utilizes three grids with spatial resolutions of 0.2° and 0.25°. The reforecast comprises five members with 1 cycle per day and a forecast range of 16 days. Once a week, it expands to 35 days and 11 members. This paper describes the development of the wave ensemble reforecast, focusing primarily on validation against buoys and altimeters. The statistical analyses demonstrated very good performance in the short range for significant wave height, with correlation coefficients of 0.95–0.96 on day 1 and between 0.86 and 0.88 within week 1, along with bias close to zero. After day 10, correlation coefficients fall below 0.70. We found that the degradation of predictability and the increase in scatter errors predominantly occur in the forecast lead time between days 4 and 10, in terms of the ensemble mean and individual members, including the control. For week 2 and beyond, a probabilistic spatiotemporal analysis of the ensemble space provides useful forecast guidance. Our results provide a framework for expanding the usefulness of wave ensemble data in operational forecasting applications.